diff --git a/.travis.yml b/.travis.yml index 093fc49a..a866cb5a 100644 --- a/.travis.yml +++ b/.travis.yml @@ -17,7 +17,7 @@ before_install: - sudo ln -s /run/shm /dev/shm install: - - conda install --yes python=$TRAVIS_PYTHON_VERSION atlas numpy=1.7 scipy=0.12 matplotlib nose sphinx pip nose + - conda install --yes python=$TRAVIS_PYTHON_VERSION atlas numpy=1.9 scipy=0.16 matplotlib nose sphinx pip nose #- pip install . - python setup.py build_ext --inplace #--use-mirrors diff --git a/AUTHORS.txt b/AUTHORS.txt index f81db5ec..a446ebb4 100644 --- a/AUTHORS.txt +++ b/AUTHORS.txt @@ -1,7 +1 @@ -James Hensman -Nicolo Fusi -Ricardo Andrade -Nicolas Durrande -Alan Saul -Max Zwiessele -Neil D. Lawrence +See contributors. diff --git a/GPy/__init__.py b/GPy/__init__.py index 26713406..2b5c233f 100644 --- a/GPy/__init__.py +++ b/GPy/__init__.py @@ -21,16 +21,18 @@ from . import plotting from .core import Model from .core.parameterization import Param, Parameterized, ObsAr +from .__version__ import __version__ + #@nottest try: #Get rid of nose dependency by only ignoring if you have nose installed from nose.tools import nottest @nottest - def tests(): - Tester(testing).test(verbose=10) + def tests(verbose=10): + Tester(testing).test(verbose=verbose) except: - def tests(): - Tester(testing).test(verbose=10) + def tests(verbose=10): + Tester(testing).test(verbose=verbose) def load(file_path): """ diff --git a/GPy/__version__.py b/GPy/__version__.py new file mode 100644 index 00000000..aa00ec3d --- /dev/null +++ b/GPy/__version__.py @@ -0,0 +1 @@ +__version__ = "0.8.8" diff --git a/GPy/core/__init__.py b/GPy/core/__init__.py index 1c6ebea6..142eccbf 100644 --- a/GPy/core/__init__.py +++ b/GPy/core/__init__.py @@ -7,6 +7,6 @@ from .parameterization.param import Param, ParamConcatenation from .parameterization.observable_array import ObsAr from .gp import GP -#from .svgp import SVGP +from .svgp import SVGP from .sparse_gp import SparseGP from .mapping import * diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 5ca86d9e..d265161c 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -60,9 +60,11 @@ class GP(Model): self.normalizer.scale_by(Y) self.Y_normalized = ObsAr(self.normalizer.normalize(Y)) self.Y = Y - else: + elif isinstance(Y, np.ndarray): self.Y = ObsAr(Y) self.Y_normalized = self.Y + else: + self.Y = Y if Y.shape[0] != self.num_data: #There can be cases where we want inputs than outputs, for example if we have multiple latent @@ -104,8 +106,23 @@ class GP(Model): self.link_parameter(self.likelihood) self.posterior = None + # The predictive variable to be used to predict using the posterior object's + # woodbury_vector and woodbury_inv is defined as predictive_variable + # as long as the posterior has the right woodbury entries. + # It is the input variable used for the covariance between + # X_star and the posterior of the GP. + # This is usually just a link to self.X (full GP) or self.Z (sparse GP). + # Make sure to name this variable and the predict functions will "just work" + # In maths the predictive variable is: + # K_{xx} - K_{xp}W_{pp}^{-1}K_{px} + # W_{pp} := \texttt{Woodbury inv} + # p := _predictive_variable - def set_XY(self, X=None, Y=None, trigger_update=True): + @property + def _predictive_variable(self): + return self.X + + def set_XY(self, X=None, Y=None): """ Set the input / output data of the model This is useful if we wish to change our existing data but maintain the same model @@ -115,7 +132,7 @@ class GP(Model): :param Y: output observations :type Y: np.ndarray """ - if trigger_update: self.update_model(False) + self.update_model(False) if Y is not None: if self.normalizer is not None: self.normalizer.scale_by(Y) @@ -131,34 +148,33 @@ class GP(Model): assert isinstance(X, type(self.X)), "The given X must have the same type as the X in the model!" self.unlink_parameter(self.X) self.X = X - self.link_parameters(self.X) + self.link_parameter(self.X) else: self.unlink_parameter(self.X) from ..core import Param self.X = Param('latent mean',X) - self.link_parameters(self.X) + self.link_parameter(self.X) else: self.X = ObsAr(X) - if trigger_update: self.update_model(True) - if trigger_update: self._trigger_params_changed() + self.update_model(True) - def set_X(self,X, trigger_update=True): + def set_X(self,X): """ Set the input data of the model :param X: input observations :type X: np.ndarray """ - self.set_XY(X=X, trigger_update=trigger_update) + self.set_XY(X=X) - def set_Y(self,Y, trigger_update=True): + def set_Y(self,Y): """ Set the output data of the model :param X: output observations :type X: np.ndarray """ - self.set_XY(Y=Y, trigger_update=trigger_update) + self.set_XY(Y=Y) def parameters_changed(self): """ @@ -181,7 +197,7 @@ class GP(Model): """ return self._log_marginal_likelihood - def _raw_predict(self, _Xnew, full_cov=False, kern=None): + def _raw_predict(self, Xnew, full_cov=False, kern=None): """ For making predictions, does not account for normalization or likelihood @@ -197,24 +213,33 @@ class GP(Model): if kern is None: kern = self.kern - Kx = kern.K(_Xnew, self.X).T - WiKx = np.dot(self.posterior.woodbury_inv, Kx) + Kx = kern.K(self._predictive_variable, Xnew) mu = np.dot(Kx.T, self.posterior.woodbury_vector) + if len(mu.shape)==1: + mu = mu.reshape(-1,1) if full_cov: - Kxx = kern.K(_Xnew) - var = Kxx - np.dot(Kx.T, WiKx) + Kxx = kern.K(Xnew) + if self.posterior.woodbury_inv.ndim == 2: + var = Kxx - np.dot(Kx.T, np.dot(self.posterior.woodbury_inv, Kx)) + elif self.posterior.woodbury_inv.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0],Kxx.shape[1],self.posterior.woodbury_inv.shape[2])) + from ..util.linalg import mdot + for i in range(var.shape[2]): + var[:, :, i] = (Kxx - mdot(Kx.T, self.posterior.woodbury_inv[:, :, i], Kx)) + var = var else: - Kxx = kern.Kdiag(_Xnew) - var = Kxx - np.sum(WiKx*Kx, 0) - var = var.reshape(-1, 1) - var[var<0.] = 0. + Kxx = kern.Kdiag(Xnew) + if self.posterior.woodbury_inv.ndim == 2: + var = (Kxx - np.sum(np.dot(self.posterior.woodbury_inv.T, Kx) * Kx, 0))[:,None] + elif self.posterior.woodbury_inv.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0],self.posterior.woodbury_inv.shape[2])) + for i in range(var.shape[1]): + var[:, i] = (Kxx - (np.sum(np.dot(self.posterior.woodbury_inv[:, :, i].T, Kx) * Kx, 0))) + var = var + #add in the mean function + if self.mean_function is not None: + mu += self.mean_function.f(Xnew) - #force mu to be a column vector - if len(mu.shape)==1: mu = mu[:,None] - - #add the mean function in - if not self.mean_function is None: - mu += self.mean_function.f(_Xnew) return mu, var def predict(self, Xnew, full_cov=False, Y_metadata=None, kern=None): @@ -247,7 +272,7 @@ class GP(Model): mean, var = self.likelihood.predictive_values(mu, var, full_cov, Y_metadata=Y_metadata) return mean, var - def predict_quantiles(self, X, quantiles=(2.5, 97.5), Y_metadata=None): + def predict_quantiles(self, X, quantiles=(2.5, 97.5), Y_metadata=None, kern=None): """ Get the predictive quantiles around the prediction at X @@ -255,10 +280,12 @@ class GP(Model): :type X: np.ndarray (Xnew x self.input_dim) :param quantiles: tuple of quantiles, default is (2.5, 97.5) which is the 95% interval :type quantiles: tuple + :param kern: optional kernel to use for prediction + :type predict_kw: dict :returns: list of quantiles for each X and predictive quantiles for interval combination :rtype: [np.ndarray (Xnew x self.output_dim), np.ndarray (Xnew x self.output_dim)] """ - m, v = self._raw_predict(X, full_cov=False) + m, v = self._raw_predict(X, full_cov=False, kern=kern) if self.normalizer is not None: m, v = self.normalizer.inverse_mean(m), self.normalizer.inverse_variance(v) return self.likelihood.predictive_quantiles(m, v, quantiles, Y_metadata=Y_metadata) @@ -292,6 +319,120 @@ class GP(Model): return dmu_dX, dv_dX + def predict_jacobian(self, Xnew, kern=None, full_cov=True): + """ + Compute the derivatives of the posterior of the GP. + + Given a set of points at which to predict X* (size [N*,Q]), compute the + mean and variance of the derivative. Resulting arrays are sized: + + dL_dX* -- [N*, Q ,D], where D is the number of output in this GP (usually one). + Note that this is the mean and variance of the derivative, + not the derivative of the mean and variance! (See predictive_gradients for that) + + dv_dX* -- [N*, Q], (since all outputs have the same variance) + If there is missing data, it is not implemented for now, but + there will be one output variance per output dimension. + + :param X: The points at which to get the predictive gradients. + :type X: np.ndarray (Xnew x self.input_dim) + :param kern: The kernel to compute the jacobian for. + :param boolean full_cov: whether to return the full covariance of the jacobian. + + :returns: dmu_dX, dv_dX + :rtype: [np.ndarray (N*, Q ,D), np.ndarray (N*,Q,(D)) ] + + Note: We always return sum in input_dim gradients, as the off-diagonals + in the input_dim are not needed for further calculations. + This is a compromise for increase in speed. Mathematically the jacobian would + have another dimension in Q. + """ + if kern is None: + kern = self.kern + + mean_jac = np.empty((Xnew.shape[0],Xnew.shape[1],self.output_dim)) + + for i in range(self.output_dim): + mean_jac[:,:,i] = kern.gradients_X(self.posterior.woodbury_vector[:,i:i+1].T, Xnew, self._predictive_variable) + + dK_dXnew_full = np.empty((self._predictive_variable.shape[0], Xnew.shape[0], Xnew.shape[1])) + for i in range(self._predictive_variable.shape[0]): + dK_dXnew_full[i] = kern.gradients_X([[1.]], Xnew, self._predictive_variable[[i]]) + + if full_cov: + dK2_dXdX = kern.gradients_XX([[1.]], Xnew) + else: + dK2_dXdX = kern.gradients_XX_diag([[1.]], Xnew) + + def compute_cov_inner(wi): + if full_cov: + # full covariance gradients: + var_jac = dK2_dXdX - np.einsum('qnm,miq->niq', dK_dXnew_full.T.dot(wi), dK_dXnew_full) + else: + var_jac = dK2_dXdX - np.einsum('qim,miq->iq', dK_dXnew_full.T.dot(wi), dK_dXnew_full) + return var_jac + + if self.posterior.woodbury_inv.ndim == 3: # Missing data: + if full_cov: + var_jac = np.empty((Xnew.shape[0],Xnew.shape[0],Xnew.shape[1],self.output_dim)) + for d in range(self.posterior.woodbury_inv.shape[2]): + var_jac[:, :, :, d] = compute_cov_inner(self.posterior.woodbury_inv[:, :, d]) + else: + var_jac = np.empty((Xnew.shape[0],Xnew.shape[1],self.output_dim)) + for d in range(self.posterior.woodbury_inv.shape[2]): + var_jac[:, :, d] = compute_cov_inner(self.posterior.woodbury_inv[:, :, d]) + else: + var_jac = compute_cov_inner(self.posterior.woodbury_inv) + return mean_jac, var_jac + + def predict_wishard_embedding(self, Xnew, kern=None, mean=True, covariance=True): + """ + Predict the wishard embedding G of the GP. This is the density of the + input of the GP defined by the probabilistic function mapping f. + G = J_mean.T*J_mean + output_dim*J_cov. + + :param array-like Xnew: The points at which to evaluate the magnification. + :param :py:class:`~GPy.kern.Kern` kern: The kernel to use for the magnification. + + Supplying only a part of the learning kernel gives insights into the density + of the specific kernel part of the input function. E.g. one can see how dense the + linear part of a kernel is compared to the non-linear part etc. + """ + if kern is None: + kern = self.kern + + mu_jac, var_jac = self.predict_jacobian(Xnew, kern, full_cov=False) + mumuT = np.einsum('iqd,ipd->iqp', mu_jac, mu_jac) + Sigma = np.zeros(mumuT.shape) + if var_jac.ndim == 3: + Sigma[(slice(None), )+np.diag_indices(Xnew.shape[1], 2)] = var_jac.sum(-1) + else: + Sigma[(slice(None), )+np.diag_indices(Xnew.shape[1], 2)] = self.output_dim*var_jac + G = 0. + if mean: + G += mumuT + if covariance: + G += Sigma + return G + + def predict_magnification(self, Xnew, kern=None, mean=True, covariance=True): + """ + Predict the magnification factor as + + sqrt(det(G)) + + for each point N in Xnew + """ + G = self.predict_wishard_embedding(Xnew, kern, mean, covariance) + from ..util.linalg import jitchol + mag = np.empty(Xnew.shape[0]) + for n in range(Xnew.shape[0]): + try: + mag[n] = np.sqrt(np.exp(2*np.sum(np.log(np.diag(jitchol(G[n, :, :])))))) + except: + mag[n] = np.sqrt(np.linalg.det(G[n, :, :])) + return mag + def posterior_samples_f(self,X,size=10, full_cov=True): """ Samples the posterior GP at the points X. @@ -395,8 +536,8 @@ class GP(Model): def plot(self, plot_limits=None, which_data_rows='all', which_data_ycols='all', fixed_inputs=[], levels=20, samples=0, fignum=None, ax=None, resolution=None, - plot_raw=False, - linecol=None,fillcol=None, Y_metadata=None, data_symbol='kx', predict_kw=None): + plot_raw=False, linecol=None,fillcol=None, Y_metadata=None, + data_symbol='kx', predict_kw=None, plot_training_data=True, samples_y=0, apply_link=False): """ Plot the posterior of the GP. - In one dimension, the function is plotted with a shaded region identifying two standard deviations. @@ -419,7 +560,7 @@ class GP(Model): :param levels: number of levels to plot in a contour plot. :param levels: for 2D plotting, the number of contour levels to use is ax is None, create a new figure :type levels: int - :param samples: the number of a posteriori samples to plot + :param samples: the number of a posteriori samples to plot, p(f*|y) :type samples: int :param fignum: figure to plot on. :type fignum: figure number @@ -433,6 +574,12 @@ class GP(Model): :type Y_metadata: dict :param data_symbol: symbol as used matplotlib, by default this is a black cross ('kx') :type data_symbol: color either as Tango.colorsHex object or character ('r' is red, 'g' is green) alongside marker type, as is standard in matplotlib. + :param plot_training_data: whether or not to plot the training points + :type plot_training_data: boolean + :param samples_y: the number of a posteriori samples to plot, p(y*|y) + :type samples_y: int + :param apply_link: if there is a link function of the likelihood, plot the link(f*) rather than f*, when plotting posterior samples f + :type apply_link: boolean """ assert "matplotlib" in sys.modules, "matplotlib package has not been imported." from ..plotting.matplot_dep import models_plots @@ -445,7 +592,103 @@ class GP(Model): which_data_ycols, fixed_inputs, levels, samples, fignum, ax, resolution, plot_raw=plot_raw, Y_metadata=Y_metadata, - data_symbol=data_symbol, predict_kw=predict_kw, **kw) + data_symbol=data_symbol, predict_kw=predict_kw, + plot_training_data=plot_training_data, samples_y=samples_y, apply_link=apply_link, **kw) + + + def plot_data(self, which_data_rows='all', + which_data_ycols='all', visible_dims=None, + fignum=None, ax=None, data_symbol='kx'): + """ + Plot the training data + - For higher dimensions than two, use fixed_inputs to plot the data points with some of the inputs fixed. + + Can plot only part of the data + using which_data_rows and which_data_ycols. + + :param plot_limits: The limits of the plot. If 1D [xmin,xmax], if 2D [[xmin,ymin],[xmax,ymax]]. Defaluts to data limits + :type plot_limits: np.array + :param which_data_rows: which of the training data to plot (default all) + :type which_data_rows: 'all' or a slice object to slice model.X, model.Y + :param which_data_ycols: when the data has several columns (independant outputs), only plot these + :type which_data_ycols: 'all' or a list of integers + :param visible_dims: an array specifying the input dimensions to plot (maximum two) + :type visible_dims: a numpy array + :param resolution: the number of intervals to sample the GP on. Defaults to 200 in 1D and 50 (a 50x50 grid) in 2D + :type resolution: int + :param levels: number of levels to plot in a contour plot. + :param levels: for 2D plotting, the number of contour levels to use is ax is None, create a new figure + :type levels: int + :param samples: the number of a posteriori samples to plot, p(f*|y) + :type samples: int + :param fignum: figure to plot on. + :type fignum: figure number + :param ax: axes to plot on. + :type ax: axes handle + :param linecol: color of line to plot [Tango.colorsHex['darkBlue']] + :type linecol: color either as Tango.colorsHex object or character ('r' is red, 'g' is green) as is standard in matplotlib + :param fillcol: color of fill [Tango.colorsHex['lightBlue']] + :type fillcol: color either as Tango.colorsHex object or character ('r' is red, 'g' is green) as is standard in matplotlib + :param data_symbol: symbol as used matplotlib, by default this is a black cross ('kx') + :type data_symbol: color either as Tango.colorsHex object or character ('r' is red, 'g' is green) alongside marker type, as is standard in matplotlib. + """ + assert "matplotlib" in sys.modules, "matplotlib package has not been imported." + from ..plotting.matplot_dep import models_plots + kw = {} + return models_plots.plot_data(self, which_data_rows, + which_data_ycols, visible_dims, + fignum, ax, data_symbol, **kw) + + + def errorbars_trainset(self, which_data_rows='all', + which_data_ycols='all', fixed_inputs=[], fignum=None, ax=None, + linecol=None, data_symbol='kx', predict_kw=None, plot_training_data=True,lw=None): + + """ + Plot the posterior error bars corresponding to the training data + - For higher dimensions than two, use fixed_inputs to plot the data points with some of the inputs fixed. + + Can plot only part of the data + using which_data_rows and which_data_ycols. + + :param which_data_rows: which of the training data to plot (default all) + :type which_data_rows: 'all' or a slice object to slice model.X, model.Y + :param which_data_ycols: when the data has several columns (independant outputs), only plot these + :type which_data_rows: 'all' or a list of integers + :param fixed_inputs: a list of tuple [(i,v), (i,v)...], specifying that input index i should be set to value v. + :type fixed_inputs: a list of tuples + :param fignum: figure to plot on. + :type fignum: figure number + :param ax: axes to plot on. + :type ax: axes handle + :param plot_training_data: whether or not to plot the training points + :type plot_training_data: boolean + """ + assert "matplotlib" in sys.modules, "matplotlib package has not been imported." + from ..plotting.matplot_dep import models_plots + kw = {} + if lw is not None: + kw['lw'] = lw + return models_plots.errorbars_trainset(self, which_data_rows, which_data_ycols, fixed_inputs, + fignum, ax, linecol, data_symbol, + predict_kw, plot_training_data, **kw) + + + def plot_magnification(self, labels=None, which_indices=None, + resolution=50, ax=None, marker='o', s=40, + fignum=None, legend=True, + plot_limits=None, + aspect='auto', updates=False, plot_inducing=True, kern=None, **kwargs): + + import sys + assert "matplotlib" in sys.modules, "matplotlib package has not been imported." + from ..plotting.matplot_dep import dim_reduction_plots + + return dim_reduction_plots.plot_magnification(self, labels, which_indices, + resolution, ax, marker, s, + fignum, plot_inducing, legend, + plot_limits, aspect, updates, **kwargs) + def input_sensitivity(self, summarize=True): """ diff --git a/GPy/core/mapping.py b/GPy/core/mapping.py index 30614384..9853ea8a 100644 --- a/GPy/core/mapping.py +++ b/GPy/core/mapping.py @@ -32,7 +32,7 @@ class Bijective_mapping(Mapping): also back from f to X. The inverse mapping is called g(). """ def __init__(self, input_dim, output_dim, name='bijective_mapping'): - super(Bijective_apping, self).__init__(name=name) + super(Bijective_mapping, self).__init__(name=name) def g(self, f): """Inverse mapping from output domain of the function to the inputs.""" diff --git a/GPy/core/parameterization/param.py b/GPy/core/parameterization/param.py index 91ce9e24..8fdd744e 100644 --- a/GPy/core/parameterization/param.py +++ b/GPy/core/parameterization/param.py @@ -42,7 +42,7 @@ class Param(Parameterizable, ObsAr): Multilevel indexing (e.g. self[:2][1:]) is not supported and might lead to unexpected behaviour. Try to index in one go, using boolean indexing or the numpy builtin np.index function. - + See :py:class:`GPy.core.parameterized.Parameterized` for more details on constraining etc. """ @@ -180,6 +180,7 @@ class Param(Parameterizable, ObsAr): import copy Pickleable.__setstate__(s, copy.deepcopy(self.__getstate__(), memo)) return s + def _setup_observers(self): """ Setup the default observers diff --git a/GPy/core/parameterization/parameterized.py b/GPy/core/parameterization/parameterized.py index 96810927..5aa95695 100644 --- a/GPy/core/parameterization/parameterized.py +++ b/GPy/core/parameterization/parameterized.py @@ -74,7 +74,7 @@ class Parameterized(Parameterizable): # Metaclass for parameters changed after init. # This makes sure, that parameters changed will always be called after __init__ # **Never** call parameters_changed() yourself - #This is ignored in Python 3 -- you need to put the meta class in the function definition. + #This is ignored in Python 3 -- you need to put the meta class in the function definition. #__metaclass__ = ParametersChangedMeta #The six module is used to support both Python 2 and 3 simultaneously #=========================================================================== @@ -197,9 +197,10 @@ class Parameterized(Parameterizable): raise RuntimeError("{} does not seem to be a parameter, remove parameters directly from their respective parents".format(str(param))) start = sum([p.size for p in self.parameters[:param._parent_index_]]) - self._remove_parameter_name(param) self.size -= param.size del self.parameters[param._parent_index_] + self._remove_parameter_name(param) + param._disconnect_parent() param.remove_observer(self, self._pass_through_notify_observers) @@ -315,7 +316,7 @@ class Parameterized(Parameterizable): param[:] = val; return except AttributeError: pass - object.__setattr__(self, name, val); + return object.__setattr__(self, name, val); #=========================================================================== # Pickling diff --git a/GPy/core/parameterization/priors.py b/GPy/core/parameterization/priors.py index 83c83dfd..2d52bff0 100644 --- a/GPy/core/parameterization/priors.py +++ b/GPy/core/parameterization/priors.py @@ -366,6 +366,7 @@ class InverseGamma(Gamma): def rvs(self, n): return 1. / np.random.gamma(scale=1. / self.b, shape=self.a, size=n) + class DGPLVM_KFDA(Prior): """ Implementation of the Discriminative Gaussian Process Latent Variable function using @@ -512,6 +513,7 @@ class DGPLVM_KFDA(Prior): self.A = self.compute_A(lst_ni) self.x_shape = x_shape + class DGPLVM(Prior): """ Implementation of the Discriminative Gaussian Process Latent Variable model paper, by Raquel. @@ -669,7 +671,7 @@ class DGPLVM(Prior): M_i = self.compute_Mi(cls) Sb = self.compute_Sb(cls, M_i, M_0) Sw = self.compute_Sw(cls, M_i) - # Sb_inv_N = np.linalg.inv(Sb + np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1)) + # sb_N = np.linalg.inv(Sb + np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1)) #Sb_inv_N = np.linalg.inv(Sb+np.eye(Sb.shape[0])*0.1) #Sb_inv_N = pdinv(Sb+ np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1))[0] Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.1)[0] @@ -903,7 +905,7 @@ class DGPLVM_Lamda(Prior, Parameterized): # Sb_inv_N = np.linalg.inv(Sb + np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1)) #Sb_inv_N = np.linalg.inv(Sb+np.eye(Sb.shape[0])*0.1) #Sb_inv_N = pdinv(Sb+ np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.5))[0] - Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.9)[0] + Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.9)[0] return (-1 / self.sigma2) * np.trace(Sb_inv_N.dot(Sw)) # This function calculates derivative of the log of prior function @@ -927,7 +929,7 @@ class DGPLVM_Lamda(Prior, Parameterized): # Sb_inv_N = np.linalg.inv(Sb + np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1)) #Sb_inv_N = np.linalg.inv(Sb+np.eye(Sb.shape[0])*0.1) #Sb_inv_N = pdinv(Sb+ np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.5))[0] - Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.9)[0] + Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.9)[0] Sb_inv_N_trans = np.transpose(Sb_inv_N) Sb_inv_N_trans_minus = -1 * Sb_inv_N_trans Sw_trans = np.transpose(Sw) @@ -1198,6 +1200,7 @@ class DGPLVM_T(Prior): + class HalfT(Prior): """ Implementation of the half student t probability function, coupled with random variables. @@ -1208,15 +1211,17 @@ class HalfT(Prior): """ domain = _POSITIVE _instances = [] - def __new__(cls, A, nu): # Singleton: + + def __new__(cls, A, nu): # Singleton: if cls._instances: cls._instances[:] = [instance for instance in cls._instances if instance()] for instance in cls._instances: if instance().A == A and instance().nu == nu: - return instance() + return instance() o = super(Prior, cls).__new__(cls, A, nu) cls._instances.append(weakref.ref(o)) return cls._instances[-1]() + def __init__(self, A, nu): self.A = float(A) self.nu = float(nu) @@ -1225,37 +1230,81 @@ class HalfT(Prior): def __str__(self): return "hT({:.2g}, {:.2g})".format(self.A, self.nu) - def lnpdf(self,theta): - return (theta>0) * ( self.constant -.5*(self.nu+1) * np.log( 1.+ (1./self.nu) * (theta/self.A)**2 ) ) + def lnpdf(self, theta): + return (theta > 0) * (self.constant - .5*(self.nu + 1) * np.log(1. + (1./self.nu) * (theta/self.A)**2)) - #theta = theta if isinstance(theta,np.ndarray) else np.array([theta]) - #lnpdfs = np.zeros_like(theta) - #theta = np.array([theta]) - #above_zero = theta.flatten()>1e-6 - #v = self.nu - #sigma2=self.A - #stop - #lnpdfs[above_zero] = (+ gammaln((v + 1) * 0.5) - # - gammaln(v * 0.5) - # - 0.5*np.log(sigma2 * v * np.pi) - # - 0.5*(v + 1)*np.log(1 + (1/np.float(v))*((theta[above_zero][0]**2)/sigma2)) - #) - #return lnpdfs + # theta = theta if isinstance(theta,np.ndarray) else np.array([theta]) + # lnpdfs = np.zeros_like(theta) + # theta = np.array([theta]) + # above_zero = theta.flatten()>1e-6 + # v = self.nu + # sigma2=self.A + # stop + # lnpdfs[above_zero] = (+ gammaln((v + 1) * 0.5) + # - gammaln(v * 0.5) + # - 0.5*np.log(sigma2 * v * np.pi) + # - 0.5*(v + 1)*np.log(1 + (1/np.float(v))*((theta[above_zero][0]**2)/sigma2)) + # ) + # return lnpdfs - def lnpdf_grad(self,theta): - theta = theta if isinstance(theta,np.ndarray) else np.array([theta]) + def lnpdf_grad(self, theta): + theta = theta if isinstance(theta, np.ndarray) else np.array([theta]) grad = np.zeros_like(theta) - above_zero = theta>1e-6 + above_zero = theta > 1e-6 v = self.nu - sigma2=self.A + sigma2 = self.A grad[above_zero] = -0.5*(v+1)*(2*theta[above_zero])/(v*sigma2 + theta[above_zero][0]**2) return grad def rvs(self, n): - #return np.random.randn(n) * self.sigma + self.mu - from scipy.stats import t - #[np.abs(x) for x in t.rvs(df=4,loc=0,scale=50, size=10000)]) - ret = t.rvs(self.nu,loc=0,scale=self.A, size=n) - ret[ret<0] = 0 - return ret + # return np.random.randn(n) * self.sigma + self.mu + from scipy.stats import t + # [np.abs(x) for x in t.rvs(df=4,loc=0,scale=50, size=10000)]) + ret = t.rvs(self.nu, loc=0, scale=self.A, size=n) + ret[ret < 0] = 0 + return ret + +class Exponential(Prior): + """ + Implementation of the Exponential probability function, + coupled with random variables. + + :param l: shape parameter + + """ + domain = _POSITIVE + _instances = [] + + def __new__(cls, l): # Singleton: + if cls._instances: + cls._instances[:] = [instance for instance in cls._instances if instance()] + for instance in cls._instances: + if instance().l == l: + return instance() + o = super(Exponential, cls).__new__(cls, l) + cls._instances.append(weakref.ref(o)) + return cls._instances[-1]() + + def __init__(self, l): + self.l = l + + def __str__(self): + return "Exp({:.2g})".format(self.l) + + def summary(self): + ret = {"E[x]": 1. / self.l, + "E[ln x]": np.nan, + "var[x]": 1. / self.l**2, + "Entropy": 1. - np.log(self.l), + "Mode": 0.} + return ret + + def lnpdf(self, x): + return np.log(self.l) - self.l * x + + def lnpdf_grad(self, x): + return - self.l + + def rvs(self, n): + return np.random.exponential(scale=self.l, size=n) diff --git a/GPy/core/parameterization/transformations.py b/GPy/core/parameterization/transformations.py index 01a1f44b..830809d6 100644 --- a/GPy/core/parameterization/transformations.py +++ b/GPy/core/parameterization/transformations.py @@ -62,7 +62,7 @@ class Transformation(object): import matplotlib.pyplot as plt from ...plotting.matplot_dep import base_plots x = np.linspace(-8,8) - base_plots.meanplot(x, self.f(x),axes=axes*args,**kw) + base_plots.meanplot(x, self.f(x), *args, ax=axes, **kw) axes = plt.gca() axes.set_xlabel(xlabel) axes.set_ylabel(ylabel) diff --git a/GPy/core/sparse_gp.py b/GPy/core/sparse_gp.py index c7c99be6..d03ebd5a 100644 --- a/GPy/core/sparse_gp.py +++ b/GPy/core/sparse_gp.py @@ -49,7 +49,7 @@ class SparseGP(GP): else: #inference_method = ?? raise NotImplementedError("what to do what to do?") - print("defaulting to ", inference_method, "for latent function inference") + print(("defaulting to ", inference_method, "for latent function inference")) self.Z = Param('inducing inputs', Z) self.num_inducing = Z.shape[0] @@ -60,6 +60,10 @@ class SparseGP(GP): self.link_parameter(self.Z, index=0) self.posterior = None + @property + def _predictive_variable(self): + return self.Z + def has_uncertain_inputs(self): return isinstance(self.X, VariationalPosterior) @@ -114,63 +118,66 @@ class SparseGP(GP): Make a prediction for the latent function values. For certain inputs we give back a full_cov of shape NxN, - if there is missing data, each dimension has its own full_cov of shape NxNxD, and if full_cov is of, + if there is missing data, each dimension has its own full_cov of shape NxNxD, and if full_cov is of, we take only the diagonal elements across N. - - For uncertain inputs, the SparseGP bound produces a full covariance structure across D, so for full_cov we - return a NxDxD matrix and in the not full_cov case, we return the diagonal elements across D (NxD). - This is for both with and without missing data. See for missing data SparseGP implementation py:class:'~GPy.models.sparse_gp_minibatch.SparseGPMiniBatch'. + + For uncertain inputs, the SparseGP bound produces cannot predict the full covariance matrix full_cov for now. + The implementation of that will follow. However, for each dimension the + covariance changes, so if full_cov is False (standard), we return the variance + for each dimension [NxD]. """ if kern is None: kern = self.kern if not isinstance(Xnew, VariationalPosterior): - Kx = kern.K(self.Z, Xnew) - mu = np.dot(Kx.T, self.posterior.woodbury_vector) - if full_cov: - Kxx = kern.K(Xnew) - if self.posterior.woodbury_inv.ndim == 2: - var = Kxx - np.dot(Kx.T, np.dot(self.posterior.woodbury_inv, Kx)) - elif self.posterior.woodbury_inv.ndim == 3: - var = np.empty((Kxx.shape[0],Kxx.shape[1],self.posterior.woodbury_inv.shape[2])) - for i in range(var.shape[2]): - var[:, :, i] = (Kxx - mdot(Kx.T, self.posterior.woodbury_inv[:, :, i], Kx)) - var = var - else: - Kxx = kern.Kdiag(Xnew) - if self.posterior.woodbury_inv.ndim == 2: - var = (Kxx - np.sum(np.dot(self.posterior.woodbury_inv.T, Kx) * Kx, 0))[:,None] - elif self.posterior.woodbury_inv.ndim == 3: - var = np.empty((Kxx.shape[0],self.posterior.woodbury_inv.shape[2])) - for i in range(var.shape[1]): - var[:, i] = (Kxx - (np.sum(np.dot(self.posterior.woodbury_inv[:, :, i].T, Kx) * Kx, 0))) - var = var - #add in the mean function - if self.mean_function is not None: - mu += self.mean_function.f(Xnew) + # Kx = kern.K(self._predictive_variable, Xnew) + # mu = np.dot(Kx.T, self.posterior.woodbury_vector) + # if full_cov: + # Kxx = kern.K(Xnew) + # if self.posterior.woodbury_inv.ndim == 2: + # var = Kxx - np.dot(Kx.T, np.dot(self.posterior.woodbury_inv, Kx)) + # elif self.posterior.woodbury_inv.ndim == 3: + # var = np.empty((Kxx.shape[0],Kxx.shape[1],self.posterior.woodbury_inv.shape[2])) + # for i in range(var.shape[2]): + # var[:, :, i] = (Kxx - mdot(Kx.T, self.posterior.woodbury_inv[:, :, i], Kx)) + # var = var + # else: + # Kxx = kern.Kdiag(Xnew) + # if self.posterior.woodbury_inv.ndim == 2: + # var = (Kxx - np.sum(np.dot(self.posterior.woodbury_inv.T, Kx) * Kx, 0))[:,None] + # elif self.posterior.woodbury_inv.ndim == 3: + # var = np.empty((Kxx.shape[0],self.posterior.woodbury_inv.shape[2])) + # for i in range(var.shape[1]): + # var[:, i] = (Kxx - (np.sum(np.dot(self.posterior.woodbury_inv[:, :, i].T, Kx) * Kx, 0))) + # var = var + # #add in the mean function + # if self.mean_function is not None: + # mu += self.mean_function.f(Xnew) + mu, var = super(SparseGP, self)._raw_predict(Xnew, full_cov, kern) else: - psi0_star = kern.psi0(self.Z, Xnew) - psi1_star = kern.psi1(self.Z, Xnew) + psi0_star = kern.psi0(self._predictive_variable, Xnew) + psi1_star = kern.psi1(self._predictive_variable, Xnew) #psi2_star = kern.psi2(self.Z, Xnew) # Only possible if we get NxMxM psi2 out of the code. la = self.posterior.woodbury_vector mu = np.dot(psi1_star, la) # TODO: dimensions? - - if full_cov: + + if full_cov: + raise NotImplementedError("Full covariance for Sparse GP predicted with uncertain inputs not implemented yet.") var = np.empty((Xnew.shape[0], la.shape[1], la.shape[1])) di = np.diag_indices(la.shape[1]) - else: + else: var = np.empty((Xnew.shape[0], la.shape[1])) - + for i in range(Xnew.shape[0]): _mu, _var = Xnew.mean.values[[i]], Xnew.variance.values[[i]] - psi2_star = kern.psi2(self.Z, NormalPosterior(_mu, _var)) + psi2_star = kern.psi2(self._predictive_variable, NormalPosterior(_mu, _var)) tmp = (psi2_star[:, :] - psi1_star[[i]].T.dot(psi1_star[[i]])) var_ = mdot(la.T, tmp, la) p0 = psi0_star[i] t = np.atleast_3d(self.posterior.woodbury_inv) t2 = np.trace(t.T.dot(psi2_star), axis1=1, axis2=2) - + if full_cov: var_[di] += p0 var_[di] += -t2 diff --git a/GPy/core/sparse_gp_mpi.py b/GPy/core/sparse_gp_mpi.py index 28de3124..a26b858f 100644 --- a/GPy/core/sparse_gp_mpi.py +++ b/GPy/core/sparse_gp_mpi.py @@ -34,7 +34,7 @@ class SparseGP_MPI(SparseGP): """ - def __init__(self, X, Y, Z, kernel, likelihood, variational_prior=None, inference_method=None, name='sparse gp mpi', Y_metadata=None, mpi_comm=None, normalizer=False): + def __init__(self, X, Y, Z, kernel, likelihood, variational_prior=None, inference_method=None, name='sparse gp', Y_metadata=None, mpi_comm=None, normalizer=False): self._IN_OPTIMIZATION_ = False if mpi_comm != None: if inference_method is None: diff --git a/GPy/core/svgp.py b/GPy/core/svgp.py index c5eb3374..b87fd493 100644 --- a/GPy/core/svgp.py +++ b/GPy/core/svgp.py @@ -1,11 +1,11 @@ # Copyright (c) 2014, James Hensman, Alex Matthews -# Distributed under the terms of the GNU General public License, see LICENSE.txt +# Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np from ..util import choleskies from .sparse_gp import SparseGP from .parameterization.param import Param -from ..inference.latent_function_inference import SVGP as svgp_inf +from ..inference.latent_function_inference.svgp import SVGP as svgp_inf class SVGP(SparseGP): diff --git a/GPy/core/verbose_optimization.py b/GPy/core/verbose_optimization.py index 08c5e2dd..c4539736 100644 --- a/GPy/core/verbose_optimization.py +++ b/GPy/core/verbose_optimization.py @@ -24,7 +24,6 @@ class VerboseOptimization(object): self.model.add_observer(self, self.print_status) self.status = 'running' self.clear = clear_after_finish - self.deltat = .2 self.update() @@ -80,6 +79,7 @@ class VerboseOptimization(object): def __enter__(self): self.start = time.time() + self._time = self.start return self def print_out(self, seconds): @@ -143,12 +143,12 @@ class VerboseOptimization(object): def print_status(self, me, which=None): self.update() - seconds = time.time()-self.start + t = time.time() + seconds = t-self.start #sys.stdout.write(" "*len(self.message)) - self.deltat += seconds - if self.deltat > .2: + if t-self._time > .3 or seconds < .3: self.print_out(seconds) - self.deltat = 0 + self._time = t self.iteration += 1 diff --git a/GPy/examples/coreg_example.py b/GPy/examples/coreg_example.py index 4e9566dc..3afeb9fb 100644 --- a/GPy/examples/coreg_example.py +++ b/GPy/examples/coreg_example.py @@ -3,7 +3,7 @@ import numpy as np try: - import pylab as pb + from matplotlib import pyplot as pb except: pass import GPy diff --git a/GPy/examples/non_gaussian.py b/GPy/examples/non_gaussian.py index 3652b4d3..5d5fc7f6 100644 --- a/GPy/examples/non_gaussian.py +++ b/GPy/examples/non_gaussian.py @@ -77,7 +77,7 @@ def student_t_approx(optimize=True, plot=True): debug=True if debug: m4.optimize(messages=1) - import pylab as pb + from matplotlib import pyplot as pb pb.plot(m4.X, m4.inference_method.f_hat) pb.plot(m4.X, m4.Y, 'rx') m4.plot() diff --git a/GPy/examples/regression.py b/GPy/examples/regression.py index 267c6d1e..1ce2f6f4 100644 --- a/GPy/examples/regression.py +++ b/GPy/examples/regression.py @@ -5,7 +5,7 @@ Gaussian Processes regression examples """ try: - import pylab as pb + from matplotlib import pyplot as pb except: pass import numpy as np diff --git a/GPy/inference/latent_function_inference/__init__.py b/GPy/inference/latent_function_inference/__init__.py index f927aba4..7bdd6ff2 100644 --- a/GPy/inference/latent_function_inference/__init__.py +++ b/GPy/inference/latent_function_inference/__init__.py @@ -69,7 +69,7 @@ from .expectation_propagation_dtc import EPDTC from .dtc import DTC from .fitc import FITC from .var_dtc_parallel import VarDTC_minibatch -#from .svgp import SVGP +from .var_gauss import VarGauss # class FullLatentFunctionData(object): # diff --git a/GPy/inference/latent_function_inference/inferenceX.py b/GPy/inference/latent_function_inference/inferenceX.py index 19013b06..f253a31e 100644 --- a/GPy/inference/latent_function_inference/inferenceX.py +++ b/GPy/inference/latent_function_inference/inferenceX.py @@ -4,6 +4,8 @@ import numpy as np from ...core import Model from ...core.parameterization import variational +from ...util.linalg import tdot +from GPy.core.parameterization.variational import VariationalPosterior def infer_newX(model, Y_new, optimize=True, init='L2'): """ @@ -60,18 +62,19 @@ class InferenceX(Model): # self.kern.GPU(True) from copy import deepcopy self.posterior = deepcopy(model.posterior) - if hasattr(model, 'variational_prior'): + from ...core.parameterization.variational import VariationalPosterior + if isinstance(model.X, VariationalPosterior): self.uncertain_input = True from ...models.ss_gplvm import IBPPrior from ...models.ss_mrd import IBPPrior_SSMRD if isinstance(model.variational_prior, IBPPrior) or isinstance(model.variational_prior, IBPPrior_SSMRD): from ...core.parameterization.variational import SpikeAndSlabPrior - self.variational_prior = SpikeAndSlabPrior(pi=05,learnPi=False, group_spike=False) + self.variational_prior = SpikeAndSlabPrior(pi=0.5, learnPi=False, group_spike=False) else: self.variational_prior = model.variational_prior.copy() else: self.uncertain_input = False - if hasattr(model, 'inducing_inputs'): + if hasattr(model, 'Z'): self.sparse_gp = True self.Z = model.Z.copy() else: @@ -125,13 +128,13 @@ class InferenceX(Model): wv = wv[:,self.valid_dim] output_dim = self.valid_dim.sum() if self.ninan is not None: - self.dL_dpsi2 = beta/2.*(self.posterior.woodbury_inv[:,:,self.valid_dim] - np.einsum('md,od->mo',wv, wv)[:, :, None]).sum(-1) + self.dL_dpsi2 = beta/2.*(self.posterior.woodbury_inv[:,:,self.valid_dim] - tdot(wv)[:, :, None]).sum(-1) else: - self.dL_dpsi2 = beta/2.*(output_dim*self.posterior.woodbury_inv - np.einsum('md,od->mo',wv, wv)) + self.dL_dpsi2 = beta/2.*(output_dim*self.posterior.woodbury_inv - tdot(wv)) self.dL_dpsi1 = beta*np.dot(self.Y[:,self.valid_dim], wv.T) self.dL_dpsi0 = - beta/2.* np.ones(self.Y.shape[0]) else: - self.dL_dpsi2 = beta*(output_dim*self.posterior.woodbury_inv - np.einsum('md,od->mo',wv, wv))/2. + self.dL_dpsi2 = beta*(output_dim*self.posterior.woodbury_inv - tdot(wv))/2. #np.einsum('md,od->mo',wv, wv) self.dL_dpsi1 = beta*np.dot(self.Y, wv.T) self.dL_dpsi0 = -beta/2.*output_dim* np.ones(self.Y.shape[0]) diff --git a/GPy/inference/latent_function_inference/laplace.py b/GPy/inference/latent_function_inference/laplace.py index 902d5fff..69eda64a 100644 --- a/GPy/inference/latent_function_inference/laplace.py +++ b/GPy/inference/latent_function_inference/laplace.py @@ -172,6 +172,7 @@ class Laplace(LatentFunctionInference): def obj(Ki_f, f): ll = -0.5*np.sum(np.dot(Ki_f.T, f)) + np.sum(likelihood.logpdf(f, Y, Y_metadata=Y_metadata)) if np.isnan(ll): + import ipdb; ipdb.set_trace() # XXX BREAKPOINT return -np.inf else: return ll diff --git a/GPy/inference/latent_function_inference/var_dtc.py b/GPy/inference/latent_function_inference/var_dtc.py index 97d8dfe3..e50daa24 100644 --- a/GPy/inference/latent_function_inference/var_dtc.py +++ b/GPy/inference/latent_function_inference/var_dtc.py @@ -64,9 +64,7 @@ class VarDTC(LatentFunctionInference): def get_VVTfactor(self, Y, prec): return Y * prec # TODO chache this, and make it effective - - - def inference(self, kern, X, Z, likelihood, Y, Y_metadata=None, Lm=None, dL_dKmm=None): + def inference(self, kern, X, Z, likelihood, Y, Y_metadata=None, Lm=None, dL_dKmm=None, psi0=None, psi1=None, psi2=None): _, output_dim = Y.shape uncertain_inputs = isinstance(X, VariationalPosterior) @@ -95,17 +93,28 @@ class VarDTC(LatentFunctionInference): # The rather complex computations of A, and the psi stats if uncertain_inputs: - psi0 = kern.psi0(Z, X) - psi1 = kern.psi1(Z, X) + if psi0 is None: + psi0 = kern.psi0(Z, X) + if psi1 is None: + psi1 = kern.psi1(Z, X) if het_noise: - psi2_beta = np.sum([kern.psi2(Z,X[i:i+1,:]) * beta_i for i,beta_i in enumerate(beta)],0) + if psi2 is None: + assert len(psi2.shape) == 3 # Need to have not summed out N + #FIXME: Need testing + psi2_beta = np.sum([psi2[X[i:i+1,:], :, :] * beta_i for i,beta_i in enumerate(beta)],0) + else: + psi2_beta = np.sum([kern.psi2(Z,X[i:i+1,:]) * beta_i for i,beta_i in enumerate(beta)],0) else: - psi2_beta = kern.psi2(Z,X) * beta + if psi2 is None: + psi2 = kern.psi2(Z,X) + psi2_beta = psi2 * beta LmInv = dtrtri(Lm) A = LmInv.dot(psi2_beta.dot(LmInv.T)) else: - psi0 = kern.Kdiag(X) - psi1 = kern.K(X, Z) + if psi0 is None: + psi0 = kern.Kdiag(X) + if psi1 is None: + psi1 = kern.K(X, Z) if het_noise: tmp = psi1 * (np.sqrt(beta)) else: diff --git a/GPy/inference/latent_function_inference/var_dtc_parallel.py b/GPy/inference/latent_function_inference/var_dtc_parallel.py index 4b884d4c..ef7d03d0 100644 --- a/GPy/inference/latent_function_inference/var_dtc_parallel.py +++ b/GPy/inference/latent_function_inference/var_dtc_parallel.py @@ -172,18 +172,23 @@ class VarDTC_minibatch(LatentFunctionInference): if not np.isfinite(Kmm).all(): print(Kmm) Lm = jitchol(Kmm) + LmInv = dtrtri(Lm) - LmInvPsi2LmInvT = backsub_both_sides(Lm,psi2_full,transpose='right') + LmInvPsi2LmInvT = LmInv.dot(psi2_full.dot(LmInv.T)) Lambda = np.eye(Kmm.shape[0])+LmInvPsi2LmInvT LL = jitchol(Lambda) + LLInv = dtrtri(LL) logdet_L = 2.*np.sum(np.log(np.diag(LL))) - b = dtrtrs(LL,dtrtrs(Lm,psi1Y_full.T)[0])[0] + LmLLInv = LLInv.dot(LmInv) + + b = psi1Y_full.dot(LmLLInv.T) bbt = np.square(b).sum() - v = dtrtrs(Lm,dtrtrs(LL,b,trans=1)[0],trans=1)[0] - - tmp = -backsub_both_sides(LL, tdot(b)+output_dim*np.eye(input_dim), transpose='left') - dL_dpsi2R = backsub_both_sides(Lm, tmp+output_dim*np.eye(input_dim), transpose='left')/2. - + v = b.dot(LmLLInv).T + LLinvPsi1TYYTPsi1LLinvT = tdot(b.T) + + tmp = -LLInv.T.dot(LLinvPsi1TYYTPsi1LLinvT+output_dim*np.eye(input_dim)).dot(LLInv) + dL_dpsi2R = LmInv.T.dot(tmp+output_dim*np.eye(input_dim)).dot(LmInv)/2. + # Cache intermediate results self.midRes['dL_dpsi2R'] = dL_dpsi2R self.midRes['v'] = v @@ -201,7 +206,7 @@ class VarDTC_minibatch(LatentFunctionInference): # Compute dL_dKmm #====================================================================== - dL_dKmm = dL_dpsi2R - output_dim*backsub_both_sides(Lm, LmInvPsi2LmInvT, transpose='left')/2. + dL_dKmm = dL_dpsi2R - output_dim*LmInv.T.dot(LmInvPsi2LmInvT).dot(LmInv)/2. #====================================================================== # Compute the Posterior distribution of inducing points p(u|Y) diff --git a/GPy/inference/latent_function_inference/var_gauss.py b/GPy/inference/latent_function_inference/var_gauss.py new file mode 100644 index 00000000..bef1cce6 --- /dev/null +++ b/GPy/inference/latent_function_inference/var_gauss.py @@ -0,0 +1,69 @@ +# Copyright (c) 2015, James Hensman +# Licensed under the BSD 3-clause license (see LICENSE.txt) +import numpy as np +from ...util.linalg import pdinv +from .posterior import Posterior +from . import LatentFunctionInference +log_2_pi = np.log(2*np.pi) + +class VarGauss(LatentFunctionInference): + """ + The Variational Gaussian Approximation revisited + + @article{Opper:2009, + title = {The Variational Gaussian Approximation Revisited}, + author = {Opper, Manfred and Archambeau, C{\'e}dric}, + journal = {Neural Comput.}, + year = {2009}, + pages = {786--792}, + } + """ + def __init__(self, alpha, beta): + """ + :param alpha: GPy.core.Param varational parameter + :param beta: GPy.core.Param varational parameter + """ + self.alpha, self.beta = alpha, beta + + def inference(self, kern, X, likelihood, Y, mean_function=None, Y_metadata=None, Z=None): + if mean_function is not None: + raise NotImplementedError + num_data, output_dim = Y.shape + assert output_dim ==1, "Only one output supported" + + K = kern.K(X) + m = K.dot(self.alpha) + KB = K*self.beta[:, None] + BKB = KB*self.beta[None, :] + A = np.eye(num_data) + BKB + Ai, LA, _, Alogdet = pdinv(A) + Sigma = np.diag(self.beta**-2) - Ai/self.beta[:, None]/self.beta[None, :] # posterior coavairance: need full matrix for gradients + var = np.diag(Sigma).reshape(-1,1) + + F, dF_dm, dF_dv, dF_dthetaL = likelihood.variational_expectations(Y, m, var, Y_metadata=Y_metadata) + if dF_dthetaL is not None: + dL_dthetaL = dF_dthetaL.sum(1).sum(1) + else: + dL_dthetaL = np.array([]) + dF_da = np.dot(K, dF_dm) + SigmaB = Sigma*self.beta + #dF_db_ = -np.diag(Sigma.dot(np.diag(dF_dv.flatten())).dot(SigmaB))*2 + dF_db = -2*np.sum(Sigma**2 * (dF_dv * self.beta), 0) + #assert np.allclose(dF_db, dF_db_) + + KL = 0.5*(Alogdet + np.trace(Ai) - num_data + np.sum(m*self.alpha)) + dKL_da = m + A_A2 = Ai - Ai.dot(Ai) + dKL_db = np.diag(np.dot(KB.T, A_A2)) + log_marginal = F.sum() - KL + self.alpha.gradient = dF_da - dKL_da + self.beta.gradient = dF_db - dKL_db + + # K-gradients + dKL_dK = 0.5*(self.alpha*self.alpha.T + self.beta[:, None]*self.beta[None, :]*A_A2) + tmp = Ai*self.beta[:, None]/self.beta[None, :] + dF_dK = self.alpha*dF_dm.T + np.dot(tmp*dF_dv, tmp.T) + + return Posterior(mean=m, cov=Sigma ,K=K),\ + log_marginal,\ + {'dL_dK':dF_dK-dKL_dK, 'dL_dthetaL':dL_dthetaL} diff --git a/GPy/inference/mcmc/__init__.py b/GPy/inference/mcmc/__init__.py index 8f185457..9f6457e6 100644 --- a/GPy/inference/mcmc/__init__.py +++ b/GPy/inference/mcmc/__init__.py @@ -1 +1,2 @@ from .hmc import HMC +from .samplers import * diff --git a/GPy/inference/mcmc/samplers.py b/GPy/inference/mcmc/samplers.py index 6459e8af..12939cfe 100644 --- a/GPy/inference/mcmc/samplers.py +++ b/GPy/inference/mcmc/samplers.py @@ -1,14 +1,10 @@ # ## Copyright (c) 2014, Zhenwen Dai # Licensed under the BSD 3-clause license (see LICENSE.txt) - +from __future__ import print_function import numpy as np -from scipy import linalg, optimize -import Tango import sys -import re -import numdifftools as ndt -import pdb + try: #In Python 2, cPickle is faster. It does not exist in Python 3 but the underlying code is always used @@ -22,11 +18,11 @@ class Metropolis_Hastings: def __init__(self,model,cov=None): """Metropolis Hastings, with tunings according to Gelman et al. """ self.model = model - current = self.model._get_params_transformed() + current = self.model.optimizer_array self.D = current.size self.chains = [] if cov is None: - self.cov = model.Laplace_covariance() + self.cov = np.eye(self.D) else: self.cov = cov self.scale = 2.4/np.sqrt(self.D) @@ -37,20 +33,20 @@ class Metropolis_Hastings: if start is None: self.model.randomize() else: - self.model._set_params_transformed(start) + self.model.optimizer_array = start - - - def sample(self, Ntotal, Nburn, Nthin, tune=True, tune_throughout=False, tune_interval=400): - current = self.model._get_params_transformed() - fcurrent = self.model.log_likelihood() + self.model.log_prior() + def sample(self, Ntotal=10000, Nburn=1000, Nthin=10, tune=True, tune_throughout=False, tune_interval=400): + current = self.model.optimizer_array + fcurrent = self.model.log_likelihood() + self.model.log_prior() + \ + self.model._log_det_jacobian() accepted = np.zeros(Ntotal,dtype=np.bool) for it in range(Ntotal): - print("sample %d of %d\r"%(it,Ntotal), end=' ') + print("sample %d of %d\r"%(it,Ntotal),end="\t") sys.stdout.flush() prop = np.random.multivariate_normal(current, self.cov*self.scale*self.scale) - self.model._set_params_transformed(prop) - fprop = self.model.log_likelihood() + self.model.log_prior() + self.model.optimizer_array = prop + fprop = self.model.log_likelihood() + self.model.log_prior() + \ + self.model._log_det_jacobian() if fprop>fcurrent:#sample accepted, going 'uphill' accepted[it] = True @@ -78,10 +74,11 @@ class Metropolis_Hastings: def predict(self,function,args): """Make a prediction for the function, to which we will pass the additional arguments""" - param = self.model._get_params() + param = self.model.param_array fs = [] for p in self.chain: - self.model._set_params(p) + self.model.param_array = p fs.append(function(*args)) - self.model._set_params(param)# reset model to starting state + # reset model to starting state + self.model.param_array = param return fs diff --git a/GPy/inference/optimization/stochastics.py b/GPy/inference/optimization/stochastics.py index 645c5f64..902c4290 100644 --- a/GPy/inference/optimization/stochastics.py +++ b/GPy/inference/optimization/stochastics.py @@ -5,7 +5,7 @@ class StochasticStorage(object): ''' This is a container for holding the stochastic parameters, such as subset indices or step length and so on. - + self.d has to be a list of lists: [dimension indices, nan indices for those dimensions] so that the minibatches can be used as efficiently as possible.10 @@ -38,16 +38,17 @@ class SparseGPMissing(StochasticStorage): import numpy as np self.Y = model.Y_normalized bdict = {} + #For N > 1000 array2string default crops + opt = np.get_printoptions() + np.set_printoptions(threshold=np.inf) for d in range(self.Y.shape[1]): - inan = np.isnan(self.Y[:, d]) - arr_str = np.array2string(inan, - np.inf, 0, - True, '', - formatter={'bool':lambda x: '1' if x else '0'}) + inan = np.isnan(self.Y)[:, d] + arr_str = np.array2string(inan, np.inf, 0, True, '', formatter={'bool':lambda x: '1' if x else '0'}) try: bdict[arr_str][0].append(d) except: bdict[arr_str] = [[d], ~inan] + np.set_printoptions(**opt) self.d = bdict.values() class SparseGPStochastics(StochasticStorage): @@ -55,32 +56,36 @@ class SparseGPStochastics(StochasticStorage): For the sparse gp we need to store the dimension we are in, and the indices corresponding to those """ - def __init__(self, model, batchsize=1): + def __init__(self, model, batchsize=1, missing_data=True): self.batchsize = batchsize self.output_dim = model.Y.shape[1] self.Y = model.Y_normalized + self.missing_data = missing_data self.reset() self.do_stochastics() def do_stochastics(self): + import numpy as np if self.batchsize == 1: self.current_dim = (self.current_dim+1)%self.output_dim - self.d = [[[self.current_dim], np.isnan(self.Y[:, self.d])]] + self.d = [[[self.current_dim], np.isnan(self.Y[:, self.current_dim]) if self.missing_data else None]] else: - import numpy as np self.d = np.random.choice(self.output_dim, size=self.batchsize, replace=False) bdict = {} - for d in self.d: - inan = np.isnan(self.Y[:, d]) - arr_str = int(np.array2string(inan, - np.inf, 0, - True, '', - formatter={'bool':lambda x: '1' if x else '0'}), 2) - try: - bdict[arr_str][0].append(d) - except: - bdict[arr_str] = [[d], ~inan] - self.d = bdict.values() + if self.missing_data: + opt = np.get_printoptions() + np.set_printoptions(threshold=np.inf) + for d in self.d: + inan = np.isnan(self.Y[:, d]) + arr_str = np.array2string(inan,np.inf, 0,True, '',formatter={'bool':lambda x: '1' if x else '0'}) + try: + bdict[arr_str][0].append(d) + except: + bdict[arr_str] = [[d], ~inan] + np.set_printoptions(**opt) + self.d = bdict.values() + else: + self.d = [[self.d, None]] def reset(self): self.current_dim = -1 diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index f479c387..c4464db9 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -6,6 +6,7 @@ from ._src.brownian import Brownian from ._src.stationary import Exponential, OU, Matern32, Matern52, ExpQuad, RatQuad, Cosine from ._src.mlp import MLP from ._src.periodic import PeriodicExponential, PeriodicMatern32, PeriodicMatern52 +from ._src.standard_periodic import StdPeriodic from ._src.independent_outputs import IndependentOutputs, Hierarchical from ._src.coregionalize import Coregionalize from ._src.ODE_UY import ODE_UY @@ -17,7 +18,7 @@ from ._src.eq_ode2 import EQ_ODE2 from ._src.trunclinear import TruncLinear,TruncLinear_inf from ._src.splitKern import SplitKern,DEtime from ._src.splitKern import DEtime as DiffGenomeKern - - +from ._src.spline import Spline +from ._src.eq_ode2 import EQ_ODE2 from ._src.basis_funcs import LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel diff --git a/GPy/kern/_src/add.py b/GPy/kern/_src/add.py index 696a8b04..2835ee29 100644 --- a/GPy/kern/_src/add.py +++ b/GPy/kern/_src/add.py @@ -14,7 +14,7 @@ class Add(CombinationKernel): This kernel will take over the active dims of it's subkernels passed in. """ - def __init__(self, subkerns, name='add'): + def __init__(self, subkerns, name='sum'): for i, kern in enumerate(subkerns[:]): if isinstance(kern, Add): del subkerns[i] @@ -71,16 +71,29 @@ class Add(CombinationKernel): target = np.zeros(X.shape) [target.__iadd__(p.gradients_X_diag(dL_dKdiag, X)) for p in self.parts] return target - - @Cache_this(limit=2, force_kwargs=['which_parts']) + + def gradients_XX(self, dL_dK, X, X2): + if X2 is None: + target = np.zeros((X.shape[0], X.shape[0], X.shape[1])) + else: + target = np.zeros((X.shape[0], X2.shape[0], X.shape[1])) + [target.__iadd__(p.gradients_XX(dL_dK, X, X2)) for p in self.parts] + return target + + def gradients_XX_diag(self, dL_dKdiag, X): + target = np.zeros(X.shape) + [target.__iadd__(p.gradients_XX_diag(dL_dKdiag, X)) for p in self.parts] + return target + + @Cache_this(limit=1, force_kwargs=['which_parts']) def psi0(self, Z, variational_posterior): return reduce(np.add, (p.psi0(Z, variational_posterior) for p in self.parts)) - - @Cache_this(limit=2, force_kwargs=['which_parts']) + + @Cache_this(limit=1, force_kwargs=['which_parts']) def psi1(self, Z, variational_posterior): return reduce(np.add, (p.psi1(Z, variational_posterior) for p in self.parts)) - @Cache_this(limit=2, force_kwargs=['which_parts']) + @Cache_this(limit=1, force_kwargs=['which_parts']) def psi2(self, Z, variational_posterior): psi2 = reduce(np.add, (p.psi2(Z, variational_posterior) for p in self.parts)) #return psi2 @@ -115,6 +128,41 @@ class Add(CombinationKernel): raise NotImplementedError("psi2 cannot be computed for this kernel") return psi2 + @Cache_this(limit=1, force_kwargs=['which_parts']) + def psi2n(self, Z, variational_posterior): + psi2 = reduce(np.add, (p.psi2n(Z, variational_posterior) for p in self.parts)) + #return psi2 + # compute the "cross" terms + from .static import White, Bias + from .rbf import RBF + #from rbf_inv import RBFInv + from .linear import Linear + #ffrom fixed import Fixed + + for p1, p2 in itertools.combinations(self.parts, 2): + # i1, i2 = p1.active_dims, p2.active_dims + # white doesn;t combine with anything + if isinstance(p1, White) or isinstance(p2, White): + pass + # rbf X bias + #elif isinstance(p1, (Bias, Fixed)) and isinstance(p2, (RBF, RBFInv)): + elif isinstance(p1, Bias) and isinstance(p2, (RBF, Linear)): + tmp = p2.psi1(Z, variational_posterior).sum(axis=0) + psi2 += p1.variance * (tmp[:, :, None] + tmp[:, None, :]) + #elif isinstance(p2, (Bias, Fixed)) and isinstance(p1, (RBF, RBFInv)): + elif isinstance(p2, Bias) and isinstance(p1, (RBF, Linear)): + tmp = p1.psi1(Z, variational_posterior).sum(axis=0) + psi2 += p2.variance * (tmp[:, :, None] + tmp[:, None, :]) + elif isinstance(p2, (RBF, Linear)) and isinstance(p1, (RBF, Linear)): + assert np.intersect1d(p1.active_dims, p2.active_dims).size == 0, "only non overlapping kernel dimensions allowed so far" + tmp1 = p1.psi1(Z, variational_posterior) + tmp2 = p2.psi1(Z, variational_posterior) + psi2 += np.einsum('nm,no->nmo',tmp1,tmp2)+np.einsum('nm,no->nmo',tmp2,tmp1) + #(tmp1[:, :, None] * tmp2[:, None, :]) + (tmp2[:, :, None] * tmp1[:, None, :]) + else: + raise NotImplementedError("psi2 cannot be computed for this kernel") + return psi2 + def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): from .static import White, Bias for p1 in self.parts: @@ -126,9 +174,9 @@ class Add(CombinationKernel): if isinstance(p2, White): continue elif isinstance(p2, Bias): - eff_dL_dpsi1 += dL_dpsi2.sum(0) * p2.variance * 2. + eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.variance * 2. else:# np.setdiff1d(p1.active_dims, ar2, assume_unique): # TODO: Careful, not correct for overlapping active_dims - eff_dL_dpsi1 += dL_dpsi2.sum(0) * p2.psi1(Z, variational_posterior) * 2. + eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(Z, variational_posterior) * 2. p1.update_gradients_expectations(dL_dpsi0, eff_dL_dpsi1, dL_dpsi2, Z, variational_posterior) def gradients_Z_expectations(self, dL_psi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): @@ -143,9 +191,9 @@ class Add(CombinationKernel): if isinstance(p2, White): continue elif isinstance(p2, Bias): - eff_dL_dpsi1 += dL_dpsi2.sum(0) * p2.variance * 2. + eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.variance * 2. else: - eff_dL_dpsi1 += dL_dpsi2.sum(0) * p2.psi1(Z, variational_posterior) * 2. + eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(Z, variational_posterior) * 2. target += p1.gradients_Z_expectations(dL_psi0, eff_dL_dpsi1, dL_dpsi2, Z, variational_posterior) return target @@ -161,9 +209,9 @@ class Add(CombinationKernel): if isinstance(p2, White): continue elif isinstance(p2, Bias): - eff_dL_dpsi1 += dL_dpsi2.sum(0) * p2.variance * 2. + eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.variance * 2. else: - eff_dL_dpsi1 += dL_dpsi2.sum(0) * p2.psi1(Z, variational_posterior) * 2. + eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(Z, variational_posterior) * 2. grads = p1.gradients_qX_expectations(dL_dpsi0, eff_dL_dpsi1, dL_dpsi2, Z, variational_posterior) [np.add(target_grads[i],grads[i],target_grads[i]) for i in range(len(grads))] return target_grads diff --git a/GPy/kern/_src/basis_funcs.py b/GPy/kern/_src/basis_funcs.py index a6c1f36c..dc21a687 100644 --- a/GPy/kern/_src/basis_funcs.py +++ b/GPy/kern/_src/basis_funcs.py @@ -11,7 +11,7 @@ class BasisFuncKernel(Kern): def __init__(self, input_dim, variance=1., active_dims=None, ARD=False, name='basis func kernel'): """ Abstract superclass for kernels with explicit basis functions for use in GPy. - + This class does NOT automatically add an offset to the design matrix phi! """ super(BasisFuncKernel, self).__init__(input_dim, active_dims, name) @@ -23,24 +23,24 @@ class BasisFuncKernel(Kern): variance = np.array(variance) self.variance = Param('variance', variance, Logexp()) self.link_parameter(self.variance) - + def parameters_changed(self): self.alpha = np.sqrt(self.variance) self.beta = 1./self.variance - + @Cache_this(limit=3, ignore_args=()) def phi(self, X): return self._phi(X) def _phi(self, X): raise NotImplementedError('Overwrite this _phi function, which maps the input X into the higher dimensional space and returns the design matrix Phi') - + def K(self, X, X2=None): return self._K(X, X2) def Kdiag(self, X, X2=None): return np.diag(self._K(X, X2)) - + def update_gradients_full(self, dL_dK, X, X2=None): if self.ARD: phi1 = self.phi(X) @@ -51,22 +51,22 @@ class BasisFuncKernel(Kern): self.variance.gradient = np.einsum('ij,iq,jq->q', dL_dK, phi1, phi2) else: self.variance.gradient = np.einsum('ij,ij', dL_dK, self._K(X, X2)) * self.beta - + def update_gradients_diag(self, dL_dKdiag, X): if self.ARD: phi1 = self.phi(X) self.variance.gradient = np.einsum('i,iq,iq->q', dL_dKdiag, phi1, phi1) else: self.variance.gradient = np.einsum('i,i', dL_dKdiag, self.Kdiag(X)) * self.beta - + def concatenate_offset(self, X): return np.c_[np.ones((X.shape[0], 1)), X] - + def posterior_inf(self, X=None, posterior=None): """ - Do the posterior inference on the parameters given this kernels functions - and the model posterior, which has to be a GPy posterior, usually found at m.posterior, if m is a GPy model. - If not given we search for the the highest parent to be a model, containing the posterior, and for X accordingly. + Do the posterior inference on the parameters given this kernels functions + and the model posterior, which has to be a GPy posterior, usually found at m.posterior, if m is a GPy model. + If not given we search for the the highest parent to be a model, containing the posterior, and for X accordingly. """ if X is None: try: @@ -80,7 +80,7 @@ class BasisFuncKernel(Kern): raise RuntimeError("This kernel is not part of a model and cannot be used for posterior inference") phi_alpha = self.phi(X) * self.variance return (phi_alpha).T.dot(posterior.woodbury_vector), (np.eye(phi_alpha.shape[1])*self.variance - mdot(phi_alpha.T, posterior.woodbury_inv, phi_alpha)) - + @Cache_this(limit=3, ignore_args=()) def _K(self, X, X2): if X2 is None or X is X2: @@ -95,35 +95,35 @@ class BasisFuncKernel(Kern): phi1 = phi1[:, None] phi2 = phi2[:, None] return phi1.dot(phi2.T) - - + + class LinearSlopeBasisFuncKernel(BasisFuncKernel): def __init__(self, input_dim, start, stop, variance=1., active_dims=None, ARD=False, name='linear_segment'): """ A linear segment transformation. The segments start at start, \ - are then linear to stop and constant again. The segments are - normalized, so that they have exactly as much mass above - as below the origin. - - Start and stop can be tuples or lists of starts and stops. + are then linear to stop and constant again. The segments are + normalized, so that they have exactly as much mass above + as below the origin. + + Start and stop can be tuples or lists of starts and stops. Behaviour of start stop is as np.where(X self.stop, self.stop, phi) return ((phi-(self.stop+self.start)/2.))#/(.5*(self.stop-self.start)))-1. - + class ChangePointBasisFuncKernel(BasisFuncKernel): def __init__(self, input_dim, changepoint, variance=1., active_dims=None, ARD=False, name='changepoint'): self.changepoint = np.array(changepoint) super(ChangePointBasisFuncKernel, self).__init__(input_dim, variance, active_dims, ARD, name) - + @Cache_this(limit=3, ignore_args=()) def _phi(self, X): return np.where((X < self.changepoint), -1, 1) @@ -131,7 +131,7 @@ class ChangePointBasisFuncKernel(BasisFuncKernel): class DomainKernel(LinearSlopeBasisFuncKernel): def __init__(self, input_dim, start, stop, variance=1., active_dims=None, ARD=False, name='constant_domain'): super(DomainKernel, self).__init__(input_dim, start, stop, variance, active_dims, ARD, name) - + @Cache_this(limit=3, ignore_args=()) def _phi(self, X): phi = np.where((X>self.start)*(X #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) @@ -54,35 +42,40 @@ #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #endif -#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 +#if !defined(CYTHON_USE_PYLONG_INTERNALS) && CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x02070000 +#define CYTHON_USE_PYLONG_INTERNALS 1 +#endif +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" #define CYTHON_FORMAT_SSIZE_T "z" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif -#if PY_MAJOR_VERSION >= 3 +#ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif -#if PY_MAJOR_VERSION >= 3 +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif -#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE) +#ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 - #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \ + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) @@ -103,9 +96,12 @@ #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \ + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 @@ -151,6 +147,11 @@ #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong @@ -160,18 +161,22 @@ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif -#ifndef CYTHON_INLINE - #if defined(__GNUC__) - #define CYTHON_INLINE __inline__ - #elif defined(_MSC_VER) - #define CYTHON_INLINE __inline - #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L - #define CYTHON_INLINE inline - #else - #define CYTHON_INLINE - #endif +#if PY_VERSION_HEX >= 0x030500B1 +#define __Pyx_PyAsyncMethodsStruct PyAsyncMethods +#define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) +#elif CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 +typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; +} __Pyx_PyAsyncMethodsStruct; +#define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) +#else +#define __Pyx_PyType_AsAsync(obj) NULL #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) @@ -184,24 +189,33 @@ #define CYTHON_RESTRICT #endif #endif +#define __Pyx_void_to_None(void_result) (void_result, Py_INCREF(Py_None), Py_None) + +#ifndef CYTHON_INLINE + #if defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include #ifdef NAN #define __PYX_NAN() ((float) NAN) #else static CYTHON_INLINE float __PYX_NAN() { - /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and - a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is - a quiet NaN. */ float value; memset(&value, 0xFF, sizeof(value)); return value; } #endif -#ifdef __cplusplus -template -void __Pyx_call_destructor(T* x) { - x->~T(); -} -#endif #if PY_MAJOR_VERSION >= 3 @@ -220,10 +234,6 @@ void __Pyx_call_destructor(T* x) { #endif #endif -#if defined(WIN32) || defined(MS_WINDOWS) -#define _USE_MATH_DEFINES -#endif -#include #define __PYX_HAVE__GPy__kern___src__coregionalize_cython #define __PYX_HAVE_API__GPy__kern___src__coregionalize_cython #include "string.h" @@ -252,6 +262,13 @@ void __Pyx_call_destructor(T* x) { # define CYTHON_UNUSED # endif #endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; @@ -260,16 +277,34 @@ typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding; #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize -#define __Pyx_fits_Py_ssize_t(v, type, is_signed) ( \ - (sizeof(type) < sizeof(Py_ssize_t)) || \ - (sizeof(type) > sizeof(Py_ssize_t) && \ - likely(v < (type)PY_SSIZE_T_MAX || \ - v == (type)PY_SSIZE_T_MAX) && \ - (!is_signed || likely(v > (type)PY_SSIZE_T_MIN || \ - v == (type)PY_SSIZE_T_MIN))) || \ - (sizeof(type) == sizeof(Py_ssize_t) && \ - (is_signed || likely(v < (type)PY_SSIZE_T_MAX || \ +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX))) ) +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (_MSC_VER) && defined (_M_X64) + #define __Pyx_sst_abs(value) _abs64(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*); static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); #define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) @@ -286,11 +321,11 @@ static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { @@ -304,8 +339,9 @@ static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) #define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) #define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode #define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode -#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None) -#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False)) +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +#define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False)) static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x); static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); @@ -326,7 +362,7 @@ static int __Pyx_init_sys_getdefaultencoding_params(void) { const char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); @@ -474,7 +510,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -483,7 +519,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -492,7 +528,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -501,7 +537,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -510,7 +546,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -519,7 +555,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -528,7 +564,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -537,7 +573,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -546,7 +582,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":739 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -555,7 +591,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -564,7 +600,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -573,7 +609,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -582,7 +618,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -591,7 +627,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -600,7 +636,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -609,7 +645,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -618,7 +654,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":757 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -627,7 +663,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -636,7 +672,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -645,7 +681,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -654,7 +690,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -685,7 +721,7 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; /*--- Type declarations ---*/ -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -694,7 +730,7 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":765 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -703,7 +739,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -712,7 +748,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -720,6 +756,8 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; + +/* --- Runtime support code (head) --- */ #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -736,19 +774,19 @@ typedef npy_cdouble __pyx_t_5numpy_complex_t; static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname); #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL; #ifdef WITH_THREAD - #define __Pyx_RefNannySetupContext(name, acquire_gil) \ - if (acquire_gil) { \ - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); \ - __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \ - PyGILState_Release(__pyx_gilstate_save); \ - } else { \ - __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \ + #define __Pyx_RefNannySetupContext(name, acquire_gil)\ + if (acquire_gil) {\ + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();\ + __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__);\ + PyGILState_Release(__pyx_gilstate_save);\ + } else {\ + __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__);\ } #else - #define __Pyx_RefNannySetupContext(name, acquire_gil) \ + #define __Pyx_RefNannySetupContext(name, acquire_gil)\ __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__) #endif - #define __Pyx_RefNannyFinishContext() \ + #define __Pyx_RefNannyFinishContext()\ __Pyx_RefNanny->FinishContext(&__pyx_refnanny) #define __Pyx_INCREF(r) __Pyx_RefNanny->INCREF(__pyx_refnanny, (PyObject *)(r), __LINE__) #define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__) @@ -771,13 +809,13 @@ typedef npy_cdouble __pyx_t_5numpy_complex_t; #define __Pyx_XGOTREF(r) #define __Pyx_XGIVEREF(r) #endif -#define __Pyx_XDECREF_SET(r, v) do { \ - PyObject *tmp = (PyObject *) r; \ - r = v; __Pyx_XDECREF(tmp); \ +#define __Pyx_XDECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_XDECREF(tmp);\ } while (0) -#define __Pyx_DECREF_SET(r, v) do { \ - PyObject *tmp = (PyObject *) r; \ - r = v; __Pyx_DECREF(tmp); \ +#define __Pyx_DECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_DECREF(tmp);\ } while (0) #define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0) #define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0) @@ -804,8 +842,8 @@ static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); -static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \ - PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ const char* function_name); static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, @@ -831,21 +869,42 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObjec static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); -static void __Pyx_RaiseBufferIndexError(int axis); - #define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) #define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1) +#define __Pyx_BufPtrCContig2d(type, buf, i0, s0, i1, s1) ((type)((char*)buf + i0 * s0) + i1) static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) + PyErr_SetObject(PyExc_KeyError, args); + Py_XDECREF(args); + } + return NULL; + } + Py_INCREF(value); + return value; +} +#else + #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#endif + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + typedef struct { int code_line; PyCodeObject* code_object; @@ -888,12 +947,14 @@ typedef struct { static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0}; static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); - static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) @@ -992,6 +1053,8 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do #endif #endif +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); @@ -1017,19 +1080,21 @@ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); /* Module declarations from 'cpython.buffer' */ -/* Module declarations from 'cpython.ref' */ - /* Module declarations from 'libc.string' */ /* Module declarations from 'libc.stdio' */ -/* Module declarations from 'cpython.object' */ - /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.type' */ static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + /* Module declarations from 'libc.stdlib' */ /* Module declarations from 'numpy' */ @@ -1053,11 +1118,6 @@ int __pyx_module_is_main_GPy__kern___src__coregionalize_cython = 0; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_RuntimeError; -static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_B, PyArrayObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_B, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_X2); /* proto */ -static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_reduce(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_D, PyArrayObject *__pyx_v_dL_dK, PyArrayObject *__pyx_v_index, PyArrayObject *__pyx_v_index2); /* proto */ -static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static char __pyx_k_B[] = "B"; static char __pyx_k_D[] = "D"; static char __pyx_k_H[] = "H"; @@ -1103,7 +1163,7 @@ static char __pyx_k_K_asymmetric[] = "K_asymmetric"; static char __pyx_k_RuntimeError[] = "RuntimeError"; static char __pyx_k_gradient_reduce[] = "gradient_reduce"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; -static char __pyx_k_home_james_work_GPy_GPy_kern__s[] = "/home/james/work/GPy/GPy/kern/_src/coregionalize_cython.pyx"; +static char __pyx_k_home_david_gits_GPy_GPy_kern__s[] = "/home/david/gits/GPy/GPy/kern/_src/coregionalize_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static char __pyx_k_GPy_kern__src_coregionalize_cyth[] = "GPy.kern._src.coregionalize_cython"; @@ -1129,7 +1189,7 @@ static PyObject *__pyx_n_s_dL_dK; static PyObject *__pyx_n_s_dL_dK_small; static PyObject *__pyx_n_s_empty; static PyObject *__pyx_n_s_gradient_reduce; -static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_kern__s; +static PyObject *__pyx_kp_s_home_david_gits_GPy_GPy_kern__s; static PyObject *__pyx_n_s_i; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_index; @@ -1147,6 +1207,11 @@ static PyObject *__pyx_n_s_size; static PyObject *__pyx_n_s_test; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; static PyObject *__pyx_n_s_zeros; +static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_B, PyArrayObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_B, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_X2); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_reduce(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_D, PyArrayObject *__pyx_v_dL_dK, PyArrayObject *__pyx_v_index, PyArrayObject *__pyx_v_index2); /* proto */ +static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static PyObject *__pyx_tuple_; static PyObject *__pyx_tuple__2; static PyObject *__pyx_tuple__3; @@ -1160,12 +1225,12 @@ static PyObject *__pyx_codeobj__8; static PyObject *__pyx_codeobj__10; static PyObject *__pyx_codeobj__12; -/* "GPy/kern/_src/coregionalize_cython.pyx":7 +/* "GPy/kern/_src/coregionalize_cython.pyx":8 * cimport numpy as np * * def K_symmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X): # <<<<<<<<<<<<<< * cdef int N = X.size - * cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, N)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) */ /* Python wrapper */ @@ -1200,11 +1265,11 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_20coregionalize_cython_1K_symmetric(P case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("K_symmetric", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("K_symmetric", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "K_symmetric") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "K_symmetric") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 2) { goto __pyx_L5_argtuple_error; @@ -1217,14 +1282,14 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_20coregionalize_cython_1K_symmetric(P } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("K_symmetric", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("K_symmetric", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.coregionalize_cython.K_symmetric", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_B), __pyx_ptype_5numpy_ndarray, 1, "B", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X), __pyx_ptype_5numpy_ndarray, 1, "X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_B), __pyx_ptype_5numpy_ndarray, 1, "B", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X), __pyx_ptype_5numpy_ndarray, 1, "X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(__pyx_self, __pyx_v_B, __pyx_v_X); /* function exit code */ @@ -1259,13 +1324,12 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(CY int __pyx_t_8; int __pyx_t_9; int __pyx_t_10; - int __pyx_t_11; - int __pyx_t_12; - int __pyx_t_13; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + __pyx_t_5numpy_int64_t __pyx_t_13; __pyx_t_5numpy_int64_t __pyx_t_14; - __pyx_t_5numpy_int64_t __pyx_t_15; - int __pyx_t_16; - int __pyx_t_17; + Py_ssize_t __pyx_t_15; + Py_ssize_t __pyx_t_16; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -1284,50 +1348,50 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(CY __pyx_pybuffernd_X.rcbuffer = &__pyx_pybuffer_X; 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__pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X.rcbuffer->pybuffer, (PyObject*)__pyx_v_X, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_X.diminfo[0].strides = __pyx_pybuffernd_X.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X.diminfo[0].shape = __pyx_pybuffernd_X.rcbuffer->pybuffer.shape[0]; - /* "GPy/kern/_src/coregionalize_cython.pyx":8 + /* "GPy/kern/_src/coregionalize_cython.pyx":9 * * def K_symmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X): * cdef int N = X.size # <<<<<<<<<<<<<< - * cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, N)) - * for n in range(N): + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) + * with nogil: */ - __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_X), __pyx_n_s_size); 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+ Py_UNBLOCK_THREADS + #endif + /*try:*/ { - /* "GPy/kern/_src/coregionalize_cython.pyx":11 - * cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, N)) - * for n in range(N): - * for m in range(N): # <<<<<<<<<<<<<< - * K[n,m] = B[X[n],X[m]] + /* "GPy/kern/_src/coregionalize_cython.pyx":12 + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) + * with nogil: + * for n in range(N): # <<<<<<<<<<<<<< + * for m in range(N): + * K[n, m] = B[X[n], X[m]] + */ + __pyx_t_2 = __pyx_v_N; + for (__pyx_t_8 = 0; __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) { + __pyx_v_n = __pyx_t_8; + + /* "GPy/kern/_src/coregionalize_cython.pyx":13 + * with nogil: + * for n in range(N): + * for m in range(N): # <<<<<<<<<<<<<< + * K[n, m] = B[X[n], X[m]] * return K */ - __pyx_t_9 = __pyx_v_N; - for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { - __pyx_v_m = __pyx_t_10; + __pyx_t_9 = __pyx_v_N; + for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { + __pyx_v_m = __pyx_t_10; - /* "GPy/kern/_src/coregionalize_cython.pyx":12 - * for n in range(N): - * for m in range(N): - * K[n,m] = B[X[n],X[m]] # <<<<<<<<<<<<<< + /* "GPy/kern/_src/coregionalize_cython.pyx":14 + * for n in range(N): + * for m in range(N): + * K[n, m] = B[X[n], X[m]] # <<<<<<<<<<<<<< * return K * */ - __pyx_t_11 = __pyx_v_n; 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+ } + } } - __pyx_t_12 = __pyx_v_m; - __pyx_t_13 = -1; - if (__pyx_t_12 < 0) { - __pyx_t_12 += __pyx_pybuffernd_X.diminfo[0].shape; - if (unlikely(__pyx_t_12 < 0)) __pyx_t_13 = 0; - } else if (unlikely(__pyx_t_12 >= __pyx_pybuffernd_X.diminfo[0].shape)) __pyx_t_13 = 0; - if (unlikely(__pyx_t_13 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_13); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "GPy/kern/_src/coregionalize_cython.pyx":11 + * cdef int N = X.size + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) + * with nogil: # <<<<<<<<<<<<<< + * for n in range(N): + * for m in range(N): + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; } - __pyx_t_14 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_X.rcbuffer->pybuffer.buf, __pyx_t_11, __pyx_pybuffernd_X.diminfo[0].strides)); - __pyx_t_15 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_X.rcbuffer->pybuffer.buf, __pyx_t_12, __pyx_pybuffernd_X.diminfo[0].strides)); - __pyx_t_13 = -1; - if (__pyx_t_14 < 0) { - __pyx_t_14 += __pyx_pybuffernd_B.diminfo[0].shape; - if (unlikely(__pyx_t_14 < 0)) __pyx_t_13 = 0; - } else if (unlikely(__pyx_t_14 >= __pyx_pybuffernd_B.diminfo[0].shape)) __pyx_t_13 = 0; - if (__pyx_t_15 < 0) { - __pyx_t_15 += __pyx_pybuffernd_B.diminfo[1].shape; - if (unlikely(__pyx_t_15 < 0)) __pyx_t_13 = 1; - } else if (unlikely(__pyx_t_15 >= __pyx_pybuffernd_B.diminfo[1].shape)) __pyx_t_13 = 1; - if (unlikely(__pyx_t_13 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_13); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - __pyx_t_13 = __pyx_v_n; - __pyx_t_16 = __pyx_v_m; - __pyx_t_17 = -1; - if (__pyx_t_13 < 0) { - __pyx_t_13 += __pyx_pybuffernd_K.diminfo[0].shape; - if (unlikely(__pyx_t_13 < 0)) __pyx_t_17 = 0; - } else if (unlikely(__pyx_t_13 >= __pyx_pybuffernd_K.diminfo[0].shape)) __pyx_t_17 = 0; - if (__pyx_t_16 < 0) { - __pyx_t_16 += __pyx_pybuffernd_K.diminfo[1].shape; - if (unlikely(__pyx_t_16 < 0)) __pyx_t_17 = 1; - } else if (unlikely(__pyx_t_16 >= __pyx_pybuffernd_K.diminfo[1].shape)) __pyx_t_17 = 1; - if (unlikely(__pyx_t_17 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_17); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_pybuffernd_K.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_K.diminfo[0].strides, __pyx_t_16, __pyx_pybuffernd_K.diminfo[1].strides) = (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_B.rcbuffer->pybuffer.buf, __pyx_t_14, __pyx_pybuffernd_B.diminfo[0].strides, __pyx_t_15, __pyx_pybuffernd_B.diminfo[1].strides)); - } } - /* "GPy/kern/_src/coregionalize_cython.pyx":13 - * for m in range(N): - * K[n,m] = B[X[n],X[m]] + /* "GPy/kern/_src/coregionalize_cython.pyx":15 + * for m in range(N): + * K[n, m] = B[X[n], X[m]] * return K # <<<<<<<<<<<<<< * * def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X, np.ndarray[np.int64_t, ndim=1] X2): @@ -1465,12 +1518,12 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(CY __pyx_r = ((PyObject *)__pyx_v_K); goto __pyx_L0; - /* "GPy/kern/_src/coregionalize_cython.pyx":7 + /* "GPy/kern/_src/coregionalize_cython.pyx":8 * cimport numpy as np * * def K_symmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X): # <<<<<<<<<<<<<< * cdef int N = X.size - * cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, N)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) */ /* function exit code */ @@ -1500,7 +1553,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_K_symmetric(CY return __pyx_r; } -/* "GPy/kern/_src/coregionalize_cython.pyx":15 +/* "GPy/kern/_src/coregionalize_cython.pyx":17 * return K * * def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X, np.ndarray[np.int64_t, ndim=1] X2): # <<<<<<<<<<<<<< @@ -1542,16 +1595,16 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_20coregionalize_cython_3K_asymmetric( case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("K_asymmetric", 1, 3, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("K_asymmetric", 1, 3, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("K_asymmetric", 1, 3, 3, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("K_asymmetric", 1, 3, 3, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "K_asymmetric") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "K_asymmetric") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 3) { goto __pyx_L5_argtuple_error; @@ -1566,15 +1619,15 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_20coregionalize_cython_3K_asymmetric( } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("K_asymmetric", 1, 3, 3, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("K_asymmetric", 1, 3, 3, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.coregionalize_cython.K_asymmetric", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_B), __pyx_ptype_5numpy_ndarray, 1, "B", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X), __pyx_ptype_5numpy_ndarray, 1, "X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X2), __pyx_ptype_5numpy_ndarray, 1, "X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_B), __pyx_ptype_5numpy_ndarray, 1, "B", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X), __pyx_ptype_5numpy_ndarray, 1, "X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X2), __pyx_ptype_5numpy_ndarray, 1, "X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric(__pyx_self, __pyx_v_B, __pyx_v_X, __pyx_v_X2); /* function exit code */ @@ -1612,13 +1665,12 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric( int __pyx_t_8; int __pyx_t_9; int __pyx_t_10; - int __pyx_t_11; - int __pyx_t_12; - int __pyx_t_13; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + __pyx_t_5numpy_int64_t __pyx_t_13; __pyx_t_5numpy_int64_t __pyx_t_14; - __pyx_t_5numpy_int64_t __pyx_t_15; - int __pyx_t_16; - int __pyx_t_17; + Py_ssize_t __pyx_t_15; + Py_ssize_t __pyx_t_16; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -1641,68 +1693,68 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric( __pyx_pybuffernd_X2.rcbuffer = &__pyx_pybuffer_X2; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_B.rcbuffer->pybuffer, (PyObject*)__pyx_v_B, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_B.rcbuffer->pybuffer, (PyObject*)__pyx_v_B, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_B.diminfo[0].strides = __pyx_pybuffernd_B.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_B.diminfo[0].shape = __pyx_pybuffernd_B.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_B.diminfo[1].strides = __pyx_pybuffernd_B.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_B.diminfo[1].shape = __pyx_pybuffernd_B.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X.rcbuffer->pybuffer, (PyObject*)__pyx_v_X, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X.rcbuffer->pybuffer, (PyObject*)__pyx_v_X, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_X.diminfo[0].strides = __pyx_pybuffernd_X.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X.diminfo[0].shape = __pyx_pybuffernd_X.rcbuffer->pybuffer.shape[0]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X2.rcbuffer->pybuffer, (PyObject*)__pyx_v_X2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X2.rcbuffer->pybuffer, (PyObject*)__pyx_v_X2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_X2.diminfo[0].strides = __pyx_pybuffernd_X2.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X2.diminfo[0].shape = __pyx_pybuffernd_X2.rcbuffer->pybuffer.shape[0]; - /* "GPy/kern/_src/coregionalize_cython.pyx":16 + /* "GPy/kern/_src/coregionalize_cython.pyx":18 * * def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X, np.ndarray[np.int64_t, ndim=1] X2): * cdef int N = X.size # <<<<<<<<<<<<<< * cdef int M = X2.size - * cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, M)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, M)) */ - __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_X), __pyx_n_s_size); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_X), __pyx_n_s_size); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_5 = __Pyx_PyInt_From_int(__pyx_v_M); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyInt_From_int(__pyx_v_M); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); - PyTuple_SET_ITEM(__pyx_t_6, 1, __pyx_t_5); + PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_5); + PyTuple_SET_ITEM(__pyx_t_6, 1, __pyx_t_5); 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__Pyx_GIVEREF(__pyx_t_5); __pyx_t_5 = NULL; - PyTuple_SET_ITEM(__pyx_t_3, 0+1, __pyx_t_6); + __Pyx_GIVEREF(__pyx_t_5); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_5); __pyx_t_5 = NULL; __Pyx_GIVEREF(__pyx_t_6); + PyTuple_SET_ITEM(__pyx_t_3, 0+1, __pyx_t_6); __pyx_t_6 = 0; - __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_3, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_3, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; } __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_7 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_K.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES| PyBUF_WRITABLE, 2, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_K.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS| PyBUF_WRITABLE, 2, 0, __pyx_stack) == -1)) { __pyx_v_K = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_K.rcbuffer->pybuffer.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_pybuffernd_K.diminfo[0].strides = __pyx_pybuffernd_K.rcbuffer->pybuffer.strides[0]; 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- __pyx_t_12 = -1; - if (__pyx_t_11 < 0) { - __pyx_t_11 += __pyx_pybuffernd_X.diminfo[0].shape; - if (unlikely(__pyx_t_11 < 0)) __pyx_t_12 = 0; - } else if (unlikely(__pyx_t_11 >= __pyx_pybuffernd_X.diminfo[0].shape)) __pyx_t_12 = 0; - if (unlikely(__pyx_t_12 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_12); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = __pyx_v_n; + __pyx_t_12 = __pyx_v_m; + __pyx_t_13 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_X.rcbuffer->pybuffer.buf, __pyx_t_11, __pyx_pybuffernd_X.diminfo[0].strides)); + __pyx_t_14 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_X2.rcbuffer->pybuffer.buf, __pyx_t_12, __pyx_pybuffernd_X2.diminfo[0].strides)); + __pyx_t_15 = __pyx_v_n; + __pyx_t_16 = __pyx_v_m; + *__Pyx_BufPtrCContig2d(__pyx_t_5numpy_double_t *, __pyx_pybuffernd_K.rcbuffer->pybuffer.buf, __pyx_t_15, __pyx_pybuffernd_K.diminfo[0].strides, __pyx_t_16, __pyx_pybuffernd_K.diminfo[1].strides) = (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_B.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_B.diminfo[0].strides, __pyx_t_14, __pyx_pybuffernd_B.diminfo[1].strides)); + } + } } - __pyx_t_12 = __pyx_v_m; - __pyx_t_13 = -1; - if (__pyx_t_12 < 0) { - __pyx_t_12 += __pyx_pybuffernd_X2.diminfo[0].shape; - if (unlikely(__pyx_t_12 < 0)) __pyx_t_13 = 0; - } else if (unlikely(__pyx_t_12 >= __pyx_pybuffernd_X2.diminfo[0].shape)) __pyx_t_13 = 0; - if (unlikely(__pyx_t_13 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_13); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "GPy/kern/_src/coregionalize_cython.pyx":21 + * cdef int M = X2.size + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, M)) + * with nogil: # <<<<<<<<<<<<<< + * for n in range(N): + * for m in range(M): + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; } - __pyx_t_14 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_X.rcbuffer->pybuffer.buf, __pyx_t_11, __pyx_pybuffernd_X.diminfo[0].strides)); - __pyx_t_15 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_X2.rcbuffer->pybuffer.buf, __pyx_t_12, __pyx_pybuffernd_X2.diminfo[0].strides)); - __pyx_t_13 = -1; - if (__pyx_t_14 < 0) { - __pyx_t_14 += __pyx_pybuffernd_B.diminfo[0].shape; - if (unlikely(__pyx_t_14 < 0)) __pyx_t_13 = 0; - } else if (unlikely(__pyx_t_14 >= __pyx_pybuffernd_B.diminfo[0].shape)) __pyx_t_13 = 0; - if (__pyx_t_15 < 0) { - __pyx_t_15 += __pyx_pybuffernd_B.diminfo[1].shape; - if (unlikely(__pyx_t_15 < 0)) __pyx_t_13 = 1; - } else if (unlikely(__pyx_t_15 >= __pyx_pybuffernd_B.diminfo[1].shape)) __pyx_t_13 = 1; - if (unlikely(__pyx_t_13 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_13); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - __pyx_t_13 = __pyx_v_n; - __pyx_t_16 = __pyx_v_m; - __pyx_t_17 = -1; - if (__pyx_t_13 < 0) { - __pyx_t_13 += __pyx_pybuffernd_K.diminfo[0].shape; - if (unlikely(__pyx_t_13 < 0)) __pyx_t_17 = 0; - } else if (unlikely(__pyx_t_13 >= __pyx_pybuffernd_K.diminfo[0].shape)) __pyx_t_17 = 0; - if (__pyx_t_16 < 0) { - __pyx_t_16 += __pyx_pybuffernd_K.diminfo[1].shape; - if (unlikely(__pyx_t_16 < 0)) __pyx_t_17 = 1; - } else if (unlikely(__pyx_t_16 >= __pyx_pybuffernd_K.diminfo[1].shape)) __pyx_t_17 = 1; - if (unlikely(__pyx_t_17 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_17); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_pybuffernd_K.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_K.diminfo[0].strides, __pyx_t_16, __pyx_pybuffernd_K.diminfo[1].strides) = (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_B.rcbuffer->pybuffer.buf, __pyx_t_14, __pyx_pybuffernd_B.diminfo[0].strides, __pyx_t_15, __pyx_pybuffernd_B.diminfo[1].strides)); - } } - /* "GPy/kern/_src/coregionalize_cython.pyx":22 - * for m in range(M): - * K[n,m] = B[X[n],X2[m]] + /* "GPy/kern/_src/coregionalize_cython.pyx":25 + * for m in range(M): + * K[n, m] = B[X[n], X2[m]] * return K # <<<<<<<<<<<<<< * * def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): @@ -1840,7 +1881,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric( __pyx_r = ((PyObject *)__pyx_v_K); goto __pyx_L0; - /* "GPy/kern/_src/coregionalize_cython.pyx":15 + /* "GPy/kern/_src/coregionalize_cython.pyx":17 * return K * * def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X, np.ndarray[np.int64_t, ndim=1] X2): # <<<<<<<<<<<<<< @@ -1877,11 +1918,11 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_2K_asymmetric( return __pyx_r; } -/* "GPy/kern/_src/coregionalize_cython.pyx":24 +/* "GPy/kern/_src/coregionalize_cython.pyx":27 * return K * * def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): # <<<<<<<<<<<<<< - * cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) * cdef int N = index.size */ @@ -1921,21 +1962,21 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_20coregionalize_cython_5gradient_redu case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_dL_dK)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_index)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_index2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "gradient_reduce") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "gradient_reduce") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 4) { goto __pyx_L5_argtuple_error; @@ -1945,22 +1986,22 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_20coregionalize_cython_5gradient_redu values[2] = PyTuple_GET_ITEM(__pyx_args, 2); values[3] = PyTuple_GET_ITEM(__pyx_args, 3); } - __pyx_v_D = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_D = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_v_dL_dK = ((PyArrayObject *)values[1]); __pyx_v_index = ((PyArrayObject *)values[2]); __pyx_v_index2 = ((PyArrayObject *)values[3]); } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("gradient_reduce", 1, 4, 4, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.coregionalize_cython.gradient_reduce", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dL_dK), __pyx_ptype_5numpy_ndarray, 1, "dL_dK", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_index), __pyx_ptype_5numpy_ndarray, 1, "index", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_index2), __pyx_ptype_5numpy_ndarray, 1, "index2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dL_dK), __pyx_ptype_5numpy_ndarray, 1, "dL_dK", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_index), __pyx_ptype_5numpy_ndarray, 1, "index", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_index2), __pyx_ptype_5numpy_ndarray, 1, "index2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_reduce(__pyx_self, __pyx_v_D, __pyx_v_dL_dK, __pyx_v_index, __pyx_v_index2); /* function exit code */ @@ -1998,13 +2039,12 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_redu int __pyx_t_8; int __pyx_t_9; int __pyx_t_10; - int __pyx_t_11; - int __pyx_t_12; - int __pyx_t_13; - int __pyx_t_14; - int __pyx_t_15; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + Py_ssize_t __pyx_t_13; + Py_ssize_t __pyx_t_14; + __pyx_t_5numpy_int64_t __pyx_t_15; __pyx_t_5numpy_int64_t __pyx_t_16; - __pyx_t_5numpy_int64_t __pyx_t_17; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -2027,42 +2067,42 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_redu __pyx_pybuffernd_index2.rcbuffer = &__pyx_pybuffer_index2; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL_dK.rcbuffer->pybuffer, (PyObject*)__pyx_v_dL_dK, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL_dK.rcbuffer->pybuffer, (PyObject*)__pyx_v_dL_dK, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_dL_dK.diminfo[0].strides = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_dL_dK.diminfo[0].shape = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_dL_dK.diminfo[1].strides = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_dL_dK.diminfo[1].shape = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_index.rcbuffer->pybuffer, (PyObject*)__pyx_v_index, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_index.rcbuffer->pybuffer, (PyObject*)__pyx_v_index, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_index.diminfo[0].strides = __pyx_pybuffernd_index.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_index.diminfo[0].shape = __pyx_pybuffernd_index.rcbuffer->pybuffer.shape[0]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_index2.rcbuffer->pybuffer, (PyObject*)__pyx_v_index2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_index2.rcbuffer->pybuffer, (PyObject*)__pyx_v_index2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_index2.diminfo[0].strides = __pyx_pybuffernd_index2.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_index2.diminfo[0].shape = __pyx_pybuffernd_index2.rcbuffer->pybuffer.shape[0]; - /* "GPy/kern/_src/coregionalize_cython.pyx":25 + /* "GPy/kern/_src/coregionalize_cython.pyx":28 * * def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): - * cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) # <<<<<<<<<<<<<< + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) # <<<<<<<<<<<<<< * cdef int N = index.size * cdef int M = index2.size */ - __pyx_t_2 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); 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__Pyx_GIVEREF(__pyx_t_4); __pyx_t_4 = NULL; - PyTuple_SET_ITEM(__pyx_t_2, 0+1, __pyx_t_5); + __Pyx_GIVEREF(__pyx_t_4); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_4); __pyx_t_4 = NULL; __Pyx_GIVEREF(__pyx_t_5); + PyTuple_SET_ITEM(__pyx_t_2, 0+1, __pyx_t_5); __pyx_t_5 = 0; - __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 28; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; 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__pyx_pybuffernd_dL_dK_small.diminfo[0].shape = __pyx_pybuffernd_dL_dK_small.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_dL_dK_small.diminfo[1].strides = __pyx_pybuffernd_dL_dK_small.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_dL_dK_small.diminfo[1].shape = __pyx_pybuffernd_dL_dK_small.rcbuffer->pybuffer.shape[1]; } } @@ -2105,118 +2145,107 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_redu __pyx_v_dL_dK_small = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/coregionalize_cython.pyx":26 + /* "GPy/kern/_src/coregionalize_cython.pyx":29 * def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): - * cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) * cdef int N = index.size # <<<<<<<<<<<<<< * cdef int M = index2.size - * for i in range(N): + * with nogil: */ - __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_index), __pyx_n_s_size); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 26; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_index), __pyx_n_s_size); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 29; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_7 = __Pyx_PyInt_As_int(__pyx_t_1); if (unlikely((__pyx_t_7 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 26; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __Pyx_PyInt_As_int(__pyx_t_1); if (unlikely((__pyx_t_7 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 29; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_N = __pyx_t_7; - /* "GPy/kern/_src/coregionalize_cython.pyx":27 - * cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) + /* "GPy/kern/_src/coregionalize_cython.pyx":30 + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) * cdef int N = index.size * cdef int M = index2.size # <<<<<<<<<<<<<< - * for i in range(N): - * for j in range(M): + * with nogil: + * for i in range(N): */ - __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_index2), __pyx_n_s_size); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_index2), __pyx_n_s_size); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_7 = __Pyx_PyInt_As_int(__pyx_t_1); if (unlikely((__pyx_t_7 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __Pyx_PyInt_As_int(__pyx_t_1); if (unlikely((__pyx_t_7 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_M = __pyx_t_7; - /* "GPy/kern/_src/coregionalize_cython.pyx":28 + /* "GPy/kern/_src/coregionalize_cython.pyx":31 * cdef int N = index.size * cdef int M = index2.size - * for i in range(N): # <<<<<<<<<<<<<< - * for j in range(M): - * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; + * with nogil: # <<<<<<<<<<<<<< + * for i in range(N): + * for j in range(M): */ - __pyx_t_7 = __pyx_v_N; - for (__pyx_t_8 = 0; __pyx_t_8 < __pyx_t_7; __pyx_t_8+=1) { - __pyx_v_i = __pyx_t_8; + { + #ifdef WITH_THREAD + PyThreadState *_save; + Py_UNBLOCK_THREADS + #endif + /*try:*/ { - /* "GPy/kern/_src/coregionalize_cython.pyx":29 + /* "GPy/kern/_src/coregionalize_cython.pyx":32 * cdef int M = index2.size - * for i in range(N): - * for j in range(M): # <<<<<<<<<<<<<< - * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; + * with nogil: + * for i in range(N): # <<<<<<<<<<<<<< + * for j in range(M): + * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; + */ + __pyx_t_7 = __pyx_v_N; + for (__pyx_t_8 = 0; __pyx_t_8 < __pyx_t_7; __pyx_t_8+=1) { + __pyx_v_i = __pyx_t_8; + + /* "GPy/kern/_src/coregionalize_cython.pyx":33 + * with nogil: + * for i in range(N): + * for j in range(M): # <<<<<<<<<<<<<< + * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; * return dL_dK_small */ - __pyx_t_9 = __pyx_v_M; - for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { - __pyx_v_j = __pyx_t_10; + __pyx_t_9 = __pyx_v_M; + for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { + __pyx_v_j = __pyx_t_10; - /* "GPy/kern/_src/coregionalize_cython.pyx":30 - * for i in range(N): - * for j in range(M): - * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; # <<<<<<<<<<<<<< + /* "GPy/kern/_src/coregionalize_cython.pyx":34 + * for i in range(N): + * for j in range(M): + * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; # <<<<<<<<<<<<<< * return dL_dK_small * */ - __pyx_t_11 = __pyx_v_i; - __pyx_t_12 = __pyx_v_j; - __pyx_t_13 = -1; - if (__pyx_t_11 < 0) { - __pyx_t_11 += __pyx_pybuffernd_dL_dK.diminfo[0].shape; - if (unlikely(__pyx_t_11 < 0)) __pyx_t_13 = 0; - } else if (unlikely(__pyx_t_11 >= __pyx_pybuffernd_dL_dK.diminfo[0].shape)) __pyx_t_13 = 0; - if (__pyx_t_12 < 0) { - __pyx_t_12 += __pyx_pybuffernd_dL_dK.diminfo[1].shape; - if (unlikely(__pyx_t_12 < 0)) __pyx_t_13 = 1; - } else if (unlikely(__pyx_t_12 >= __pyx_pybuffernd_dL_dK.diminfo[1].shape)) __pyx_t_13 = 1; - if (unlikely(__pyx_t_13 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_13); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = __pyx_v_i; + __pyx_t_12 = __pyx_v_j; + __pyx_t_13 = __pyx_v_j; + __pyx_t_14 = __pyx_v_i; + __pyx_t_15 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_index2.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_index2.diminfo[0].strides)); + __pyx_t_16 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_index.rcbuffer->pybuffer.buf, __pyx_t_14, __pyx_pybuffernd_index.diminfo[0].strides)); + *__Pyx_BufPtrCContig2d(__pyx_t_5numpy_double_t *, __pyx_pybuffernd_dL_dK_small.rcbuffer->pybuffer.buf, __pyx_t_15, __pyx_pybuffernd_dL_dK_small.diminfo[0].strides, __pyx_t_16, __pyx_pybuffernd_dL_dK_small.diminfo[1].strides) += (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_11, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_12, __pyx_pybuffernd_dL_dK.diminfo[1].strides)); + } + } } - __pyx_t_13 = __pyx_v_j; - __pyx_t_14 = -1; - if (__pyx_t_13 < 0) { - __pyx_t_13 += __pyx_pybuffernd_index2.diminfo[0].shape; - if (unlikely(__pyx_t_13 < 0)) __pyx_t_14 = 0; - } else if (unlikely(__pyx_t_13 >= __pyx_pybuffernd_index2.diminfo[0].shape)) __pyx_t_14 = 0; - if (unlikely(__pyx_t_14 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_14); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "GPy/kern/_src/coregionalize_cython.pyx":31 + * cdef int N = index.size + * cdef int M = index2.size + * with nogil: # <<<<<<<<<<<<<< + * for i in range(N): + * for j in range(M): + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; } - __pyx_t_14 = __pyx_v_i; - __pyx_t_15 = -1; - if (__pyx_t_14 < 0) { - __pyx_t_14 += __pyx_pybuffernd_index.diminfo[0].shape; - if (unlikely(__pyx_t_14 < 0)) __pyx_t_15 = 0; - } else if (unlikely(__pyx_t_14 >= __pyx_pybuffernd_index.diminfo[0].shape)) __pyx_t_15 = 0; - if (unlikely(__pyx_t_15 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_15); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - __pyx_t_16 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_index2.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_index2.diminfo[0].strides)); - __pyx_t_17 = (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int64_t *, __pyx_pybuffernd_index.rcbuffer->pybuffer.buf, __pyx_t_14, __pyx_pybuffernd_index.diminfo[0].strides)); - __pyx_t_15 = -1; - if (__pyx_t_16 < 0) { - __pyx_t_16 += __pyx_pybuffernd_dL_dK_small.diminfo[0].shape; - if (unlikely(__pyx_t_16 < 0)) __pyx_t_15 = 0; - } else if (unlikely(__pyx_t_16 >= __pyx_pybuffernd_dL_dK_small.diminfo[0].shape)) __pyx_t_15 = 0; - if (__pyx_t_17 < 0) { - __pyx_t_17 += __pyx_pybuffernd_dL_dK_small.diminfo[1].shape; - if (unlikely(__pyx_t_17 < 0)) __pyx_t_15 = 1; - } else if (unlikely(__pyx_t_17 >= __pyx_pybuffernd_dL_dK_small.diminfo[1].shape)) __pyx_t_15 = 1; - if (unlikely(__pyx_t_15 != -1)) { - __Pyx_RaiseBufferIndexError(__pyx_t_15); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_pybuffernd_dL_dK_small.rcbuffer->pybuffer.buf, __pyx_t_16, __pyx_pybuffernd_dL_dK_small.diminfo[0].strides, __pyx_t_17, __pyx_pybuffernd_dL_dK_small.diminfo[1].strides) += (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_11, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_12, __pyx_pybuffernd_dL_dK.diminfo[1].strides)); - } } - /* "GPy/kern/_src/coregionalize_cython.pyx":31 - * for j in range(M): - * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; + /* "GPy/kern/_src/coregionalize_cython.pyx":35 + * for j in range(M): + * dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; * return dL_dK_small # <<<<<<<<<<<<<< * * @@ -2226,11 +2255,11 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_redu __pyx_r = ((PyObject *)__pyx_v_dL_dK_small); goto __pyx_L0; - /* "GPy/kern/_src/coregionalize_cython.pyx":24 + /* "GPy/kern/_src/coregionalize_cython.pyx":27 * return K * * def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): # <<<<<<<<<<<<<< - * cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) * cdef int N = index.size */ @@ -2263,7 +2292,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_20coregionalize_cython_4gradient_redu return __pyx_r; } -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":197 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -2313,7 +2342,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GIVEREF(__pyx_v_info->obj); } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":200 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 * # of flags * * if info == NULL: return # <<<<<<<<<<<<<< @@ -2326,7 +2355,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P goto __pyx_L0; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 * * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 # <<<<<<<<<<<<<< @@ -2335,7 +2364,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_endian_detector = 1; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":204 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":207 * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< @@ -2344,7 +2373,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 * cdef bint little_endian = ((&endian_detector)[0] != 0) * * ndim = PyArray_NDIM(self) # <<<<<<<<<<<<<< @@ -2353,7 +2382,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_ndim = PyArray_NDIM(__pyx_v_self); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":208 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 * ndim = PyArray_NDIM(self) * * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -2363,7 +2392,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (((sizeof(npy_intp)) != (sizeof(Py_ssize_t))) != 0); if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":212 * * if sizeof(npy_intp) != sizeof(Py_ssize_t): * copy_shape = 1 # <<<<<<<<<<<<<< @@ -2371,22 +2400,30 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P * copy_shape = 0 */ __pyx_v_copy_shape = 1; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 + * ndim = PyArray_NDIM(self) + * + * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< + * copy_shape = 1 + * else: + */ goto __pyx_L4; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 * copy_shape = 1 * else: * copy_shape = 0 # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) */ + /*else*/ { __pyx_v_copy_shape = 0; } __pyx_L4:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":213 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 * copy_shape = 0 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -2395,14 +2432,12 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_C_CONTIGUOUS) == PyBUF_C_CONTIGUOUS) != 0); if (__pyx_t_2) { - goto __pyx_L7_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L6_bool_binop_done; } - __pyx_L7_next_and:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -2412,23 +2447,39 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_2 = ((!(PyArray_CHKFLAGS(__pyx_v_self, NPY_C_CONTIGUOUS) != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L6_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 + * copy_shape = 0 + * + * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): + * raise ValueError(u"ndarray is not C contiguous") + */ if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 + * copy_shape = 0 + * + * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): + * raise ValueError(u"ndarray is not C contiguous") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 * raise ValueError(u"ndarray is not C contiguous") * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -2437,14 +2488,12 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS) != 0); if (__pyx_t_2) { - goto __pyx_L10_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L9_bool_binop_done; } - __pyx_L10_next_and:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -2454,23 +2503,39 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_2 = ((!(PyArray_CHKFLAGS(__pyx_v_self, NPY_F_CONTIGUOUS) != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L9_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + * raise ValueError(u"ndarray is not C contiguous") + * + * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): + * raise ValueError(u"ndarray is not Fortran contiguous") + */ if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< * * info.buf = PyArray_DATA(self) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + * raise ValueError(u"ndarray is not C contiguous") + * + * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): + * raise ValueError(u"ndarray is not Fortran contiguous") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":224 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -2479,7 +2544,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->buf = PyArray_DATA(__pyx_v_self); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":225 * * info.buf = PyArray_DATA(self) * info.ndim = ndim # <<<<<<<<<<<<<< @@ -2488,7 +2553,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->ndim = __pyx_v_ndim; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":223 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 * info.buf = PyArray_DATA(self) * info.ndim = ndim * if copy_shape: # <<<<<<<<<<<<<< @@ -2498,7 +2563,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (__pyx_v_copy_shape != 0); if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 * # Allocate new buffer for strides and shape info. * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) # <<<<<<<<<<<<<< @@ -2507,7 +2572,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * ((size_t)__pyx_v_ndim)) * 2))); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":227 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim # <<<<<<<<<<<<<< @@ -2516,7 +2581,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":228 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":231 * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -2527,7 +2592,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -2536,7 +2601,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -2545,20 +2610,28 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->shape[__pyx_v_i]) = (PyArray_DIMS(__pyx_v_self)[__pyx_v_i]); } + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + * info.buf = PyArray_DATA(self) + * info.ndim = ndim + * if copy_shape: # <<<<<<<<<<<<<< + * # Allocate new buffer for strides and shape info. + * # This is allocated as one block, strides first. + */ goto __pyx_L11; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL */ + /*else*/ { __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self)); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -2569,7 +2642,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L11:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":237 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -2578,7 +2651,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->suboffsets = NULL; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":238 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -2587,7 +2660,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -2596,28 +2669,28 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->readonly = (!(PyArray_ISWRITEABLE(__pyx_v_self) != 0)); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":242 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< * cdef dtype descr = self.descr - * cdef list stack + * cdef int offset */ __pyx_v_f = NULL; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":243 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< - * cdef list stack * cdef int offset + * */ __pyx_t_3 = ((PyObject *)__pyx_v_self->descr); __Pyx_INCREF(__pyx_t_3); __pyx_v_descr = ((PyArray_Descr *)__pyx_t_3); __pyx_t_3 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -2626,7 +2699,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -2635,18 +2708,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_2) { - goto __pyx_L16_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L15_bool_binop_done; } - __pyx_L16_next_and:; __pyx_t_2 = ((!(__pyx_v_copy_shape != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L15_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":250 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -2658,17 +2729,25 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GOTREF(__pyx_v_info->obj); __Pyx_DECREF(__pyx_v_info->obj); __pyx_v_info->obj = Py_None; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + * cdef bint hasfields = PyDataType_HASFIELDS(descr) + * + * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< + * # do not call releasebuffer + * info.obj = None + */ goto __pyx_L14; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< * * if not hasfields: */ + /*else*/ { __Pyx_INCREF(((PyObject *)__pyx_v_self)); __Pyx_GIVEREF(((PyObject *)__pyx_v_self)); __Pyx_GOTREF(__pyx_v_info->obj); @@ -2677,7 +2756,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L14:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -2687,7 +2766,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -2697,7 +2776,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_4 = __pyx_v_descr->type_num; __pyx_v_t = __pyx_t_4; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -2708,19 +2787,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P if (!__pyx_t_2) { goto __pyx_L20_next_or; } else { - goto __pyx_L21_next_and; } - __pyx_L21_next_and:; __pyx_t_2 = (__pyx_v_little_endian != 0); if (!__pyx_t_2) { - goto __pyx_L20_next_or; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } __pyx_L20_next_or:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -2729,52 +2805,58 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((__pyx_v_descr->byteorder == '<') != 0); if (__pyx_t_2) { - goto __pyx_L22_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } - __pyx_L22_next_and:; __pyx_t_2 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L19_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + * if not hasfields: + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (descr.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + * if not hasfields: + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (descr.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 - * elif t == NPY_CDOUBLE: f = "Zd" - * elif t == NPY_CLONGDOUBLE: f = "Zg" - * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< - * else: - * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) - */ - switch (__pyx_v_t) { - - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" */ + switch (__pyx_v_t) { case NPY_BYTE: __pyx_v_f = __pyx_k_b; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -2785,7 +2867,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_B; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -2796,7 +2878,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_h; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -2807,7 +2889,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_H; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -2818,7 +2900,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_i; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -2829,7 +2911,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_I; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -2840,7 +2922,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_l; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -2851,7 +2933,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_L; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -2862,7 +2944,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_q; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -2873,7 +2955,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Q; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -2884,7 +2966,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_f; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -2895,7 +2977,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_d; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -2906,7 +2988,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_g; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -2917,7 +2999,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zf; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -2928,7 +3010,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zd; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":275 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -2939,7 +3021,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zg; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -2951,33 +3033,33 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P break; default: - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 * elif t == NPY_OBJECT: f = "O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< * info.format = f * return */ - __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_6 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_6); __Pyx_GIVEREF(__pyx_t_6); + PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_Raise(__pyx_t_6, 0, 0, 0); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} break; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":279 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f # <<<<<<<<<<<<<< @@ -2986,7 +3068,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->format = __pyx_v_f; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f * return # <<<<<<<<<<<<<< @@ -2995,19 +3077,27 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_r = 0; goto __pyx_L0; - } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + * info.obj = self + * + * if not hasfields: # <<<<<<<<<<<<<< + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or + */ + } + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":282 * return * else: * info.format = stdlib.malloc(_buffer_format_string_len) # <<<<<<<<<<<<<< * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 */ + /*else*/ { __pyx_v_info->format = ((char *)malloc(255)); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 * else: * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment # <<<<<<<<<<<<<< @@ -3016,7 +3106,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->format[0]) = '^'; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":282 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":284 * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 # <<<<<<<<<<<<<< @@ -3025,17 +3115,17 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_offset = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":285 * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 * f = _util_dtypestring(descr, info.format + 1, # <<<<<<<<<<<<<< * info.format + _buffer_format_string_len, * &offset) */ - __pyx_t_7 = __pyx_f_5numpy__util_dtypestring(__pyx_v_descr, (__pyx_v_info->format + 1), (__pyx_v_info->format + 255), (&__pyx_v_offset)); if (unlikely(__pyx_t_7 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __pyx_f_5numpy__util_dtypestring(__pyx_v_descr, (__pyx_v_info->format + 1), (__pyx_v_info->format + 255), (&__pyx_v_offset)); if (unlikely(__pyx_t_7 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 285; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_f = __pyx_t_7; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":286 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":288 * info.format + _buffer_format_string_len, * &offset) * f[0] = c'\0' # Terminate format string # <<<<<<<<<<<<<< @@ -3045,7 +3135,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P (__pyx_v_f[0]) = '\x00'; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":197 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -3077,7 +3167,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P return __pyx_r; 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} -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":785 * return PyArray_MultiIterNew(5, a, b, c, d, e) * * cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL: # <<<<<<<<<<<<<< @@ -3439,17 +3541,17 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx int __pyx_clineno = 0; __Pyx_RefNannySetupContext("_util_dtypestring", 0); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 - * cdef int delta_offset - * cdef tuple i + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 + * + * cdef dtype child * cdef int endian_detector = 1 # <<<<<<<<<<<<<< * cdef bint little_endian = ((&endian_detector)[0] != 0) * cdef tuple fields */ __pyx_v_endian_detector = 1; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 - * cdef tuple i + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 + * cdef dtype child * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< * cdef tuple fields @@ -3457,7 +3559,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); 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if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + if (unlikely(__pyx_v_descr->fields == Py_None)) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not subscriptable"); + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_t_3 = __Pyx_PyDict_GetItem(__pyx_v_descr->fields, __pyx_v_childname); if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; __Pyx_GOTREF(__pyx_t_3); if (!(likely(PyTuple_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "tuple", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_XDECREF_SET(__pyx_v_fields, ((PyObject*)__pyx_t_3)); __pyx_t_3 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 * for childname in descr.names: * fields = descr.fields[childname] * child, new_offset = fields # <<<<<<<<<<<<<< @@ -3531,7 +3638,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_new_offset, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 * child, new_offset = fields * * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< @@ -3548,7 +3655,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = ((((__pyx_v_end - __pyx_v_f) - ((int)__pyx_t_5)) < 15) != 0); if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< @@ -3560,9 +3667,17 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + * child, new_offset = fields + * + * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") * * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -3573,19 +3688,16 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx if (!__pyx_t_7) { goto __pyx_L8_next_or; } else { - goto __pyx_L9_next_and; } - __pyx_L9_next_and:; __pyx_t_7 = (__pyx_v_little_endian != 0); if (!__pyx_t_7) { - goto __pyx_L8_next_or; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L7_bool_binop_done; } __pyx_L8_next_or:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 * * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -3594,18 +3706,24 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_t_7 = ((__pyx_v_child->byteorder == '<') != 0); if (__pyx_t_7) { - goto __pyx_L10_next_and; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L7_bool_binop_done; } - __pyx_L10_next_and:; __pyx_t_7 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_6 = __pyx_t_7; __pyx_L7_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (child.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -3617,9 +3735,17 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (child.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 * * # Output padding bytes * while offset[0] < new_offset: # <<<<<<<<<<<<<< @@ -3635,7 +3761,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; if (!__pyx_t_6) break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 * # Output padding bytes * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte # <<<<<<<<<<<<<< @@ -3644,7 +3770,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ (__pyx_v_f[0]) = 120; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte * f += 1 # <<<<<<<<<<<<<< @@ -3653,7 +3779,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_v_f = (__pyx_v_f + 1); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 * f[0] = 120 # "x"; pad byte * f += 1 * offset[0] += 1 # <<<<<<<<<<<<<< @@ -3664,7 +3790,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + 1); } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 * offset[0] += 1 * * offset[0] += child.itemsize # <<<<<<<<<<<<<< @@ -3674,7 +3800,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_8 = 0; (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + __pyx_v_child->elsize); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 * offset[0] += child.itemsize * * if not PyDataType_HASFIELDS(child): # <<<<<<<<<<<<<< @@ -3684,7 +3810,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = ((!(PyDataType_HASFIELDS(__pyx_v_child) != 0)) != 0); if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":821 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":821 * * if not PyDataType_HASFIELDS(child): * t = child.type_num # <<<<<<<<<<<<<< @@ -3696,7 +3822,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_t, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 * if not PyDataType_HASFIELDS(child): * t = child.type_num * if end - f < 5: # <<<<<<<<<<<<<< @@ -3706,7 +3832,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = (((__pyx_v_end - __pyx_v_f) < 5) != 0); if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 * t = child.type_num * if end - f < 5: * raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<< @@ -3718,16 +3844,24 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_4, 0, 0, 0); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 + * if not PyDataType_HASFIELDS(child): + * t = child.type_num + * if end - f < 5: # <<<<<<<<<<<<<< + * raise RuntimeError(u"Format string allocated too short.") + * + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 * * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" # <<<<<<<<<<<<<< * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" */ - __pyx_t_4 = PyInt_FromLong(NPY_BYTE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_BYTE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3738,14 +3872,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" # <<<<<<<<<<<<<< * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" */ - __pyx_t_3 = PyInt_FromLong(NPY_UBYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_UBYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3756,14 +3890,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" # <<<<<<<<<<<<<< * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" */ - __pyx_t_4 = PyInt_FromLong(NPY_SHORT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_SHORT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3774,14 +3908,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" # <<<<<<<<<<<<<< * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" */ - __pyx_t_3 = PyInt_FromLong(NPY_USHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_USHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3792,14 +3926,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" # <<<<<<<<<<<<<< * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" */ - __pyx_t_4 = PyInt_FromLong(NPY_INT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_INT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3810,14 +3944,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" # <<<<<<<<<<<<<< * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" */ - __pyx_t_3 = PyInt_FromLong(NPY_UINT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_UINT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3828,14 +3962,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":832 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":832 * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" # <<<<<<<<<<<<<< * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" */ - __pyx_t_4 = PyInt_FromLong(NPY_LONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_LONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3846,14 +3980,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" # <<<<<<<<<<<<<< * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" */ - __pyx_t_3 = PyInt_FromLong(NPY_ULONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_ULONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3864,14 +3998,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" # <<<<<<<<<<<<<< * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" */ - __pyx_t_4 = PyInt_FromLong(NPY_LONGLONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_LONGLONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3882,14 +4016,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" # <<<<<<<<<<<<<< * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" */ - __pyx_t_3 = PyInt_FromLong(NPY_ULONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_ULONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3900,14 +4034,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" # <<<<<<<<<<<<<< * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" */ - __pyx_t_4 = PyInt_FromLong(NPY_FLOAT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_FLOAT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3918,14 +4052,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":837 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":837 * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" # <<<<<<<<<<<<<< * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf */ - __pyx_t_3 = PyInt_FromLong(NPY_DOUBLE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_DOUBLE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3936,14 +4070,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":838 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":838 * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" # <<<<<<<<<<<<<< * elif t == NPY_CFLOAT: f[0] = 90; 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__Pyx_GIVEREF(__pyx_tuple__2); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_u_Non_native_byte_order_not_suppor); if (unlikely(!__pyx_tuple__3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_u_Non_native_byte_order_not_suppor); if (unlikely(!__pyx_tuple__3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__3); __Pyx_GIVEREF(__pyx_tuple__3); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< @@ -4396,7 +4554,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__4); 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if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__7 = PyTuple_Pack(6, __pyx_n_s_B, __pyx_n_s_X, __pyx_n_s_N, __pyx_n_s_K, __pyx_n_s_n, __pyx_n_s_m); if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__7); __Pyx_GIVEREF(__pyx_tuple__7); - __pyx_codeobj__8 = (PyObject*)__Pyx_PyCode_New(2, 0, 6, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__7, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_kern__s, __pyx_n_s_K_symmetric, 7, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_codeobj__8 = (PyObject*)__Pyx_PyCode_New(2, 0, 6, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__7, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_david_gits_GPy_GPy_kern__s, __pyx_n_s_K_symmetric, 8, __pyx_empty_bytes); 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if (unlikely(!__pyx_tuple__11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__11 = PyTuple_Pack(9, __pyx_n_s_D, __pyx_n_s_dL_dK, __pyx_n_s_index, __pyx_n_s_index2, __pyx_n_s_dL_dK_small, __pyx_n_s_N, __pyx_n_s_M, __pyx_n_s_i, __pyx_n_s_j); if (unlikely(!__pyx_tuple__11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__11); __Pyx_GIVEREF(__pyx_tuple__11); - __pyx_codeobj__12 = (PyObject*)__Pyx_PyCode_New(4, 0, 9, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__11, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_kern__s, __pyx_n_s_gradient_reduce, 24, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_codeobj__12 = (PyObject*)__Pyx_PyCode_New(4, 0, 9, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__11, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_david_gits_GPy_GPy_kern__s, __pyx_n_s_gradient_reduce, 27, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -4490,18 +4648,24 @@ PyMODINIT_FUNC PyInit_coregionalize_cython(void) } #endif __Pyx_RefNannySetupContext("PyMODINIT_FUNC PyInit_coregionalize_cython(void)", 0); - if ( __Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_empty_tuple = PyTuple_New(0); if (unlikely(!__pyx_empty_tuple)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_empty_bytes = PyBytes_FromStringAndSize("", 0); if (unlikely(!__pyx_empty_bytes)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #ifdef __Pyx_CyFunction_USED - if (__Pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif #ifdef __Pyx_FusedFunction_USED if (__pyx_FusedFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif + #ifdef __Pyx_Coroutine_USED + if (__pyx_Coroutine_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif #ifdef __Pyx_Generator_USED if (__pyx_Generator_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif + #ifdef __Pyx_StopAsyncIteration_USED + if (__pyx_StopAsyncIteration_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif /*--- Library function declarations ---*/ /*--- Threads initialization code ---*/ #if defined(__PYX_FORCE_INIT_THREADS) && __PYX_FORCE_INIT_THREADS @@ -4524,12 +4688,12 @@ PyMODINIT_FUNC PyInit_coregionalize_cython(void) #endif if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; /*--- Initialize various global constants etc. ---*/ - if (unlikely(__Pyx_InitGlobals() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitGlobals() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #if PY_MAJOR_VERSION < 3 && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if (__Pyx_init_sys_getdefaultencoding_params() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif if (__pyx_module_is_main_GPy__kern___src__coregionalize_cython) { - if (PyObject_SetAttrString(__pyx_m, "__name__", __pyx_n_s_main) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + if (PyObject_SetAttrString(__pyx_m, "__name__", __pyx_n_s_main) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } #if PY_MAJOR_VERSION >= 3 { @@ -4540,9 +4704,9 @@ PyMODINIT_FUNC PyInit_coregionalize_cython(void) } #endif /*--- Builtin init code ---*/ - if (unlikely(__Pyx_InitCachedBuiltins() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitCachedBuiltins() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Constants init code ---*/ - if (unlikely(__Pyx_InitCachedConstants() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitCachedConstants() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Global init code ---*/ /*--- Variable export code ---*/ /*--- Function export code ---*/ @@ -4556,73 +4720,76 @@ PyMODINIT_FUNC PyInit_coregionalize_cython(void) #endif 0); if (unlikely(!__pyx_ptype_7cpython_4type_type)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr), 0); if (unlikely(!__pyx_ptype_5numpy_dtype)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 155; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 169; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 168; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 172; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 861; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Variable import code ---*/ /*--- Function import code ---*/ /*--- Execution code ---*/ + #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) + if (__Pyx_patch_abc() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif - /* "GPy/kern/_src/coregionalize_cython.pyx":4 - * #cython: wraparound=True + /* "GPy/kern/_src/coregionalize_cython.pyx":5 + * #cython: nonecheck=False * import cython * import numpy as np # <<<<<<<<<<<<<< * cimport numpy as np * */ - __pyx_t_1 = __Pyx_Import(__pyx_n_s_numpy, 0, -1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_Import(__pyx_n_s_numpy, 0, -1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_np, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_np, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/coregionalize_cython.pyx":7 + /* "GPy/kern/_src/coregionalize_cython.pyx":8 * cimport numpy as np * * def K_symmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X): # <<<<<<<<<<<<<< * cdef int N = X.size - * cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, N)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_20coregionalize_cython_1K_symmetric, NULL, __pyx_n_s_GPy_kern__src_coregionalize_cyth); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_20coregionalize_cython_1K_symmetric, NULL, __pyx_n_s_GPy_kern__src_coregionalize_cyth); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_K_symmetric, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_K_symmetric, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/coregionalize_cython.pyx":15 + /* "GPy/kern/_src/coregionalize_cython.pyx":17 * return K * * def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X, np.ndarray[np.int64_t, ndim=1] X2): # <<<<<<<<<<<<<< * cdef int N = X.size * cdef int M = X2.size */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_20coregionalize_cython_3K_asymmetric, NULL, __pyx_n_s_GPy_kern__src_coregionalize_cyth); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_20coregionalize_cython_3K_asymmetric, NULL, __pyx_n_s_GPy_kern__src_coregionalize_cyth); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_K_asymmetric, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_K_asymmetric, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/coregionalize_cython.pyx":24 + /* "GPy/kern/_src/coregionalize_cython.pyx":27 * return K * * def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): # <<<<<<<<<<<<<< - * cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) + * cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) * cdef int N = index.size */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_20coregionalize_cython_5gradient_reduce, NULL, __pyx_n_s_GPy_kern__src_coregionalize_cyth); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_20coregionalize_cython_5gradient_reduce, NULL, __pyx_n_s_GPy_kern__src_coregionalize_cyth); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_gradient_reduce, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_gradient_reduce, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/kern/_src/coregionalize_cython.pyx":1 - * #cython: boundscheck=True # <<<<<<<<<<<<<< - * #cython: wraparound=True - * import cython + * #cython: boundscheck=False # <<<<<<<<<<<<<< + * #cython: wraparound=False + * #cython: nonecheck=False */ __pyx_t_1 = PyDict_New(); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 * arr.base = baseptr * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -4638,7 +4805,6 @@ PyMODINIT_FUNC PyInit_coregionalize_cython(void) if (__pyx_m) { if (__pyx_d) { __Pyx_AddTraceback("init GPy.kern._src.coregionalize_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); - Py_DECREF(__pyx_d); __pyx_d = 0; } Py_DECREF(__pyx_m); __pyx_m = 0; } else if (!PyErr_Occurred()) { @@ -4653,7 +4819,7 @@ PyMODINIT_FUNC PyInit_coregionalize_cython(void) #endif } -/* Runtime support code */ +/* --- Runtime support code --- */ #if CYTHON_REFNANNY static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { PyObject *m = NULL, *p = NULL; @@ -5494,11 +5660,6 @@ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { return 0; } -static void __Pyx_RaiseBufferIndexError(int axis) { - PyErr_Format(PyExc_IndexError, - "Out of bounds on buffer access (axis %d)", axis); -} - static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) { #if CYTHON_COMPILING_IN_CPYTHON PyObject *tmp_type, *tmp_value, *tmp_tb; @@ -5604,10 +5765,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject if (value && PyExceptionInstance_Check(value)) { instance_class = (PyObject*) Py_TYPE(value); if (instance_class != type) { - if (PyObject_IsSubclass(instance_class, type)) { - type = instance_class; - } else { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; } } } @@ -5665,6 +5829,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject } PyErr_SetObject(type, value); if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { @@ -5672,6 +5843,7 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } +#endif } bad: Py_XDECREF(owned_instance); @@ -5694,13 +5866,86 @@ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); } +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_VERSION_HEX < 0x03030000 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if (strchr(__Pyx_MODULE_NAME, '.')) { + #if PY_VERSION_HEX < 0x03030000 + PyObject *py_level = PyInt_FromLong(1); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + #endif + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_VERSION_HEX < 0x03030000 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_VERSION_HEX < 0x03030000 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { return count; } while (start < end) { - mid = (start + end) / 2; + mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { @@ -5874,102 +6119,33 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { - PyObject *empty_list = 0; - PyObject *module = 0; - PyObject *global_dict = 0; - PyObject *empty_dict = 0; - PyObject *list; - #if PY_VERSION_HEX < 0x03030000 - PyObject *py_import; - py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); - if (!py_import) - goto bad; - #endif - if (from_list) - list = from_list; - else { - empty_list = PyList_New(0); - if (!empty_list) - goto bad; - list = empty_list; - } - global_dict = PyModule_GetDict(__pyx_m); - if (!global_dict) - goto bad; - empty_dict = PyDict_New(); - if (!empty_dict) - goto bad; - { - #if PY_MAJOR_VERSION >= 3 - if (level == -1) { - if (strchr(__Pyx_MODULE_NAME, '.')) { - #if PY_VERSION_HEX < 0x03030000 - PyObject *py_level = PyInt_FromLong(1); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, 1); - #endif - if (!module) { - if (!PyErr_ExceptionMatches(PyExc_ImportError)) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - #endif - if (!module) { - #if PY_VERSION_HEX < 0x03030000 - PyObject *py_level = PyInt_FromLong(level); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, level); - #endif - } - } -bad: - #if PY_VERSION_HEX < 0x03030000 - Py_XDECREF(py_import); - #endif - Py_XDECREF(empty_list); - Py_XDECREF(empty_dict); - return module; -} - -#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \ - { \ - func_type value = func_value; \ - if (sizeof(target_type) < sizeof(func_type)) { \ - if (unlikely(value != (func_type) (target_type) value)) { \ - func_type zero = 0; \ - if (is_unsigned && unlikely(value < zero)) \ - goto raise_neg_overflow; \ - else \ - goto raise_overflow; \ - } \ - } \ - return (target_type) value; \ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ } -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS #include "longintrepr.h" - #endif #endif static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { - const int neg_one = (int) -1, const_zero = 0; + const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -5986,36 +6162,125 @@ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(int) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) -(((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) -(((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) -(((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x)) - } else if (sizeof(int) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -6064,21 +6329,21 @@ raise_neg_overflow: } static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { - const int neg_one = (int) -1, const_zero = 0; + const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(int) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); } } { @@ -6329,22 +6594,48 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { #endif #endif +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { + const enum NPY_TYPES neg_one = (enum NPY_TYPES) -1, const_zero = (enum NPY_TYPES) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(enum NPY_TYPES) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); + } + } else { + if (sizeof(enum NPY_TYPES) <= sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES), + little, !is_unsigned); + } +} + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { - const long neg_one = (long) -1, const_zero = 0; + const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(long) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); } } { @@ -6356,7 +6647,7 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { } static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { - const long neg_one = (long) -1, const_zero = 0; + const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -6373,36 +6664,125 @@ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(long) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) -(((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) -(((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) -(((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x)) - } else if (sizeof(long) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -6584,7 +6964,7 @@ static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && @@ -6625,7 +7005,7 @@ static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_ #endif } else #endif -#if !CYTHON_COMPILING_IN_PYPY +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); @@ -6655,7 +7035,7 @@ static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) { #else if (PyLong_Check(x)) #endif - return Py_INCREF(x), x; + return __Pyx_NewRef(x); m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { @@ -6695,18 +7075,55 @@ static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(b))) - return PyInt_AS_LONG(b); + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(x); + } #endif if (likely(PyLong_CheckExact(b))) { - #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - switch (Py_SIZE(b)) { - case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0]; - case 0: return 0; - case 1: return ((PyLongObject*)b)->ob_digit[0]; - } - #endif + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + } + } #endif return PyLong_AsSsize_t(b); } diff --git a/GPy/kern/_src/coregionalize_cython.pyx b/GPy/kern/_src/coregionalize_cython.pyx index ede21edf..0cc66fcb 100644 --- a/GPy/kern/_src/coregionalize_cython.pyx +++ b/GPy/kern/_src/coregionalize_cython.pyx @@ -1,33 +1,37 @@ -#cython: boundscheck=True -#cython: wraparound=True +#cython: boundscheck=False +#cython: wraparound=False +#cython: nonecheck=False import cython import numpy as np cimport numpy as np def K_symmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X): cdef int N = X.size - cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, N)) - for n in range(N): - for m in range(N): - K[n,m] = B[X[n],X[m]] + cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, N)) + with nogil: + for n in range(N): + for m in range(N): + K[n, m] = B[X[n], X[m]] return K def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[np.int64_t, ndim=1] X, np.ndarray[np.int64_t, ndim=1] X2): cdef int N = X.size cdef int M = X2.size - cdef np.ndarray[np.double_t, ndim=2] K = np.empty((N, M)) - for n in range(N): - for m in range(M): - K[n,m] = B[X[n],X2[m]] + cdef np.ndarray[np.double_t, ndim=2, mode='c'] K = np.empty((N, M)) + with nogil: + for n in range(N): + for m in range(M): + K[n, m] = B[X[n], X2[m]] return K def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[np.int64_t, ndim=1] index, np.ndarray[np.int64_t, ndim=1] index2): - cdef np.ndarray[np.double_t, ndim=2] dL_dK_small = np.zeros((D, D)) + cdef np.ndarray[np.double_t, ndim=2, mode='c'] dL_dK_small = np.zeros((D, D)) cdef int N = index.size cdef int M = index2.size - for i in range(N): - for j in range(M): - dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; + with nogil: + for i in range(N): + for j in range(M): + dL_dK_small[index2[j],index[i]] += dL_dK[i,j]; return dL_dK_small diff --git a/GPy/kern/_src/independent_outputs.py b/GPy/kern/_src/independent_outputs.py index 9ebb5711..e9c575bf 100644 --- a/GPy/kern/_src/independent_outputs.py +++ b/GPy/kern/_src/independent_outputs.py @@ -105,7 +105,7 @@ class IndependentOutputs(CombinationKernel): if X2 is None: # TODO: make use of index_to_slices # FIXME: Broken as X is already sliced out - print("Warning, gradients_X may not be working, I believe X has already been sliced out by the slicer!") + # print("Warning, gradients_X may not be working, I believe X has already been sliced out by the slicer!") values = np.unique(X[:,self.index_dim]) slices = [X[:,self.index_dim]==i for i in values] [target.__setitem__(s, kern.gradients_X(dL_dK[s,s],X[s],None)) diff --git a/GPy/kern/_src/kern.py b/GPy/kern/_src/kern.py index e63ddad4..1cc0c0ba 100644 --- a/GPy/kern/_src/kern.py +++ b/GPy/kern/_src/kern.py @@ -58,20 +58,9 @@ class Kern(Parameterized): self._sliced_X = 0 self.useGPU = self._support_GPU and useGPU - self._return_psi2_n_flag = ObsAr(np.zeros(1)).astype(bool) - @property - def return_psi2_n(self): - """ - Flag whether to pass back psi2 as NxMxM or MxM, by summing out N. - """ - return self._return_psi2_n_flag[0] - @return_psi2_n.setter - def return_psi2_n(self, val): - def visit(self): - if isinstance(self, Kern): - self._return_psi2_n_flag[0]=val - self.traverse(visit) + from .psi_comp import PSICOMP_GH + self.psicomp = PSICOMP_GH() @Cache_this(limit=20) def _slice_X(self, X): @@ -81,6 +70,9 @@ class Kern(Parameterized): """ Compute the kernel function. + .. math:: + K_{ij} = k(X_i, X_j) + :param X: the first set of inputs to the kernel :param X2: (optional) the second set of arguments to the kernel. If X2 is None, this is passed throgh to the 'part' object, which @@ -88,16 +80,64 @@ class Kern(Parameterized): """ raise NotImplementedError def Kdiag(self, X): + """ + The diagonal of the kernel matrix K + + .. math:: + Kdiag_{i} = k(X_i, X_i) + """ raise NotImplementedError def psi0(self, Z, variational_posterior): - raise NotImplementedError + """ + .. math:: + \psi_0 = \sum_{i=0}^{n}E_{q(X)}[k(X_i, X_i)] + """ + return self.psicomp.psicomputations(self, Z, variational_posterior)[0] def psi1(self, Z, variational_posterior): - raise NotImplementedError + """ + .. math:: + \psi_1^{n,m} = E_{q(X)}[k(X_n, Z_m)] + """ + return self.psicomp.psicomputations(self, Z, variational_posterior)[1] def psi2(self, Z, variational_posterior): - raise NotImplementedError + """ + .. math:: + \psi_2^{m,m'} = \sum_{i=0}^{n}E_{q(X)}[ k(Z_m, X_i) k(X_i, Z_{m'})] + """ + return self.psicomp.psicomputations(self, Z, variational_posterior, return_psi2_n=False)[2] + def psi2n(self, Z, variational_posterior): + """ + .. math:: + \psi_2^{n,m,m'} = E_{q(X)}[ k(Z_m, X_n) k(X_n, Z_{m'})] + + Thus, we do not sum out n, compared to psi2 + """ + return self.psicomp.psicomputations(self, Z, variational_posterior, return_psi2_n=True)[2] def gradients_X(self, dL_dK, X, X2): + """ + .. math:: + + \\frac{\partial L}{\partial X} = \\frac{\partial L}{\partial K}\\frac{\partial K}{\partial X} + """ raise NotImplementedError + def gradients_X_X2(self, dL_dK, X, X2): + return self.gradients_X(dL_dK, X, X2), self.gradients_X(dL_dK.T, X2, X) + def gradients_XX(self, dL_dK, X, X2): + """ + .. math:: + + \\frac{\partial^2 L}{\partial X\partial X_2} = \\frac{\partial L}{\partial K}\\frac{\partial^2 K}{\partial X\partial X_2} + """ + raise(NotImplementedError, "This is the second derivative of K wrt X and X2, and not implemented for this kernel") + def gradients_XX_diag(self, dL_dKdiag, X): + """ + The diagonal of the second derivative w.r.t. X and X2 + """ + raise(NotImplementedError, "This is the diagonal of the second derivative of K wrt X and X2, and not implemented for this kernel") def gradients_X_diag(self, dL_dKdiag, X): + """ + The diagonal of the derivative w.r.t. X + """ raise NotImplementedError def update_gradients_diag(self, dL_dKdiag, X): @@ -113,27 +153,35 @@ class Kern(Parameterized): Set the gradients of all parameters when doing inference with uncertain inputs, using expectations of the kernel. - The esential maths is + The essential maths is - dL_d{theta_i} = dL_dpsi0 * dpsi0_d{theta_i} + - dL_dpsi1 * dpsi1_d{theta_i} + - dL_dpsi2 * dpsi2_d{theta_i} + .. math:: + + \\frac{\partial L}{\partial \\theta_i} & = \\frac{\partial L}{\partial \psi_0}\\frac{\partial \psi_0}{\partial \\theta_i}\\ + & \quad + \\frac{\partial L}{\partial \psi_1}\\frac{\partial \psi_1}{\partial \\theta_i}\\ + & \quad + \\frac{\partial L}{\partial \psi_2}\\frac{\partial \psi_2}{\partial \\theta_i} + + Thus, we push the different derivatives through the gradients of the psi + statistics. Be sure to set the gradients for all kernel + parameters here. """ - raise NotImplementedError + dtheta = self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[0] + self.gradient[:] = dtheta - def gradients_Z_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + def gradients_Z_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior, + psi0=None, psi1=None, psi2=None): """ Returns the derivative of the objective wrt Z, using the chain rule through the expectation variables. """ - raise NotImplementedError + return self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[1] def gradients_qX_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): """ Compute the gradients wrt the parameters of the variational distruibution q(X), chain-ruling via the expectations of the kernel """ - raise NotImplementedError + return self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[2:] def plot(self, x=None, fignum=None, ax=None, title=None, plot_limits=None, resolution=None, **mpl_kwargs): """ @@ -172,7 +220,7 @@ class Kern(Parameterized): def __iadd__(self, other): return self.add(other) - def add(self, other, name='add'): + def add(self, other, name='sum'): """ Add another kernel to this one. @@ -208,8 +256,6 @@ class Kern(Parameterized): :param other: the other kernel to be added :type other: GPy.kern - :param tensor: whether or not to use the tensor space (default is false). - :type tensor: bool """ assert isinstance(other, Kern), "only kernels can be multiplied to kernels..." diff --git a/GPy/kern/_src/kernel_slice_operations.py b/GPy/kern/_src/kernel_slice_operations.py index 3473ffce..719d6b56 100644 --- a/GPy/kern/_src/kernel_slice_operations.py +++ b/GPy/kern/_src/kernel_slice_operations.py @@ -1,7 +1,11 @@ ''' Created on 11 Mar 2014 -@author: maxz +@author: @mzwiessele + +This module provides a meta class for the kernels. The meta class is for +slicing the inputs (X, X2) for the kernels, before K (or any other method involving X) +gets calls. The `active_dims` of a kernel decide which dimensions the kernel works on. ''' from ...core.parameterization.parameterized import ParametersChangedMeta import numpy as np @@ -19,20 +23,27 @@ class KernCallsViaSlicerMeta(ParametersChangedMeta): put_clean(dct, 'update_gradients_full', _slice_update_gradients_full) put_clean(dct, 'update_gradients_diag', _slice_update_gradients_diag) put_clean(dct, 'gradients_X', _slice_gradients_X) + put_clean(dct, 'gradients_X_X2', _slice_gradients_X) + put_clean(dct, 'gradients_XX', _slice_gradients_XX) + put_clean(dct, 'gradients_XX_diag', _slice_gradients_X_diag) put_clean(dct, 'gradients_X_diag', _slice_gradients_X_diag) put_clean(dct, 'psi0', _slice_psi) put_clean(dct, 'psi1', _slice_psi) put_clean(dct, 'psi2', _slice_psi) + put_clean(dct, 'psi2n', _slice_psi) put_clean(dct, 'update_gradients_expectations', _slice_update_gradients_expectations) put_clean(dct, 'gradients_Z_expectations', _slice_gradients_Z_expectations) put_clean(dct, 'gradients_qX_expectations', _slice_gradients_qX_expectations) return super(KernCallsViaSlicerMeta, cls).__new__(cls, name, bases, dct) class _Slice_wrap(object): - def __init__(self, k, X, X2=None): + def __init__(self, k, X, X2=None, ret_shape=None): self.k = k - self.shape = X.shape + if ret_shape is None: + self.shape = X.shape + else: + self.shape = ret_shape assert X.ndim == 2, "only matrices are allowed as inputs to kernels for now, given X.shape={!s}".format(X.shape) if X2 is not None: assert X2.ndim == 2, "only matrices are allowed as inputs to kernels for now, given X2.shape={!s}".format(X2.shape) @@ -54,7 +65,10 @@ class _Slice_wrap(object): def handle_return_array(self, return_val): if self.ret: ret = np.zeros(self.shape) - ret[:, self.k.active_dims] = return_val + if len(self.shape) == 2: + ret[:, self.k.active_dims] = return_val + elif len(self.shape) == 3: + ret[:, :, self.k.active_dims] = return_val return ret return return_val @@ -98,6 +112,19 @@ def _slice_gradients_X(f): return ret return wrap +def _slice_gradients_XX(f): + @wraps(f) + def wrap(self, dL_dK, X, X2=None): + if X2 is None: + N, M = X.shape[0], X.shape[0] + else: + N, M = X.shape[0], X2.shape[0] + with _Slice_wrap(self, X, X2, ret_shape=(N, M, X.shape[1])) as s: + #with _Slice_wrap(self, X, X2, ret_shape=None) as s: + ret = s.handle_return_array(f(self, dL_dK, s.X, s.X2)) + return ret + return wrap + def _slice_gradients_X_diag(f): @wraps(f) def wrap(self, dL_dKdiag, X): @@ -124,7 +151,8 @@ def _slice_update_gradients_expectations(f): def _slice_gradients_Z_expectations(f): @wraps(f) - def wrap(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + def wrap(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior, + psi0=None, psi1=None, psi2=None, Lpsi0=None, Lpsi1=None, Lpsi2=None): with _Slice_wrap(self, Z, variational_posterior) as s: ret = s.handle_return_array(f(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, s.X, s.X2)) return ret @@ -132,7 +160,8 @@ def _slice_gradients_Z_expectations(f): def _slice_gradients_qX_expectations(f): @wraps(f) - def wrap(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + def wrap(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior, + psi0=None, psi1=None, psi2=None, Lpsi0=None, Lpsi1=None, Lpsi2=None): with _Slice_wrap(self, variational_posterior, Z) as s: ret = list(f(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, s.X2, s.X)) r2 = ret[:2] diff --git a/GPy/kern/_src/linear.py b/GPy/kern/_src/linear.py index e3a45c67..0a582ac8 100644 --- a/GPy/kern/_src/linear.py +++ b/GPy/kern/_src/linear.py @@ -17,7 +17,7 @@ class Linear(Kern): .. math:: - k(x,y) = \sum_{i=1}^input_dim \sigma^2_i x_iy_i + k(x,y) = \sum_{i=1}^{\\text{input_dim}} \sigma^2_i x_iy_i :param input_dim: the number of input dimensions :type input_dim: int @@ -100,6 +100,12 @@ class Linear(Kern): #return (((X2[None,:, :] * self.variances)) * dL_dK[:, :, None]).sum(1) return np.einsum('jq,q,ij->iq', X2, self.variances, dL_dK) + def gradients_XX(self, dL_dK, X, X2=None): + if X2 is None: + return 2*np.ones(X.shape)*self.variances + else: + return np.ones(X.shape)*self.variances + def gradients_X_diag(self, dL_dKdiag, X): return 2.*self.variances*dL_dKdiag[:,None]*X @@ -111,26 +117,29 @@ class Linear(Kern): #---------------------------------------# def psi0(self, Z, variational_posterior): - return self.psicomp.psicomputations(self.variances, Z, variational_posterior)[0] + return self.psicomp.psicomputations(self, Z, variational_posterior)[0] def psi1(self, Z, variational_posterior): - return self.psicomp.psicomputations(self.variances, Z, variational_posterior)[1] + return self.psicomp.psicomputations(self, Z, variational_posterior)[1] def psi2(self, Z, variational_posterior): - return self.psicomp.psicomputations(self.variances, Z, variational_posterior)[2] + return self.psicomp.psicomputations(self, Z, variational_posterior)[2] + + def psi2n(self, Z, variational_posterior): + return self.psicomp.psicomputations(self, Z, variational_posterior, return_psi2_n=True)[2] def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): - dL_dvar = self.psicomp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, self.variances, Z, variational_posterior)[0] + dL_dvar = self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[0] if self.ARD: self.variances.gradient = dL_dvar else: self.variances.gradient = dL_dvar.sum() def gradients_Z_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): - return self.psicomp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, self.variances, Z, variational_posterior)[1] + return self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[1] def gradients_qX_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): - return self.psicomp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, self.variances, Z, variational_posterior)[2:] + return self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[2:] class LinearFull(Kern): def __init__(self, input_dim, rank, W=None, kappa=None, active_dims=None, name='linear_full'): diff --git a/GPy/kern/_src/mlp.py b/GPy/kern/_src/mlp.py index e319b8b4..40a8d2d7 100644 --- a/GPy/kern/_src/mlp.py +++ b/GPy/kern/_src/mlp.py @@ -5,6 +5,8 @@ from .kern import Kern from ...core.parameterization import Param from ...core.parameterization.transformations import Logexp import numpy as np +from ...util.linalg import tdot +from ...util.caching import Cache_this four_over_tau = 2./np.pi class MLP(Kern): @@ -31,105 +33,116 @@ class MLP(Kern): """ - def __init__(self, input_dim, variance=1., weight_variance=1., bias_variance=100., active_dims=None, name='mlp'): + def __init__(self, input_dim, variance=1., weight_variance=1., bias_variance=1., ARD=False, active_dims=None, name='mlp'): super(MLP, self).__init__(input_dim, active_dims, name) self.variance = Param('variance', variance, Logexp()) + self.ARD= ARD + if ARD: + wv = np.empty((input_dim,)) + wv[:] = weight_variance + weight_variance = wv self.weight_variance = Param('weight_variance', weight_variance, Logexp()) self.bias_variance = Param('bias_variance', bias_variance, Logexp()) self.link_parameters(self.variance, self.weight_variance, self.bias_variance) + @Cache_this(limit=20, ignore_args=()) def K(self, X, X2=None): - self._K_computations(X, X2) - return self.variance*self._K_dvar + if X2 is None: + X_denom = np.sqrt(self._comp_prod(X)+1.) + X2_denom = X_denom + X2 = X + else: + X_denom = np.sqrt(self._comp_prod(X)+1.) + X2_denom = np.sqrt(self._comp_prod(X2)+1.) + XTX = self._comp_prod(X,X2)/X_denom[:,None]/X2_denom[None,:] + return self.variance*four_over_tau*np.arcsin(XTX) + @Cache_this(limit=20, ignore_args=()) def Kdiag(self, X): """Compute the diagonal of the covariance matrix for X.""" - self._K_diag_computations(X) - return self.variance*self._K_diag_dvar + X_prod = self._comp_prod(X) + return self.variance*four_over_tau*np.arcsin(X_prod/(X_prod+1.)) def update_gradients_full(self, dL_dK, X, X2=None): """Derivative of the covariance with respect to the parameters.""" - self._K_computations(X, X2) - self.variance.gradient = np.sum(self._K_dvar*dL_dK) - - denom3 = self._K_denom**3 - base = four_over_tau*self.variance/np.sqrt(1-self._K_asin_arg*self._K_asin_arg) - base_cov_grad = base*dL_dK - - if X2 is None: - vec = np.diag(self._K_inner_prod) - self.weight_variance.gradient = ((self._K_inner_prod/self._K_denom - -.5*self._K_numer/denom3 - *(np.outer((self.weight_variance*vec+self.bias_variance+1.), vec) - +np.outer(vec,(self.weight_variance*vec+self.bias_variance+1.))))*base_cov_grad).sum() - self.bias_variance.gradient = ((1./self._K_denom - -.5*self._K_numer/denom3 - *((vec[None, :]+vec[:, None])*self.weight_variance - +2.*self.bias_variance + 2.))*base_cov_grad).sum() - else: - vec1 = (X*X).sum(1) - vec2 = (X2*X2).sum(1) - self.weight_variance.gradient = ((self._K_inner_prod/self._K_denom - -.5*self._K_numer/denom3 - *(np.outer((self.weight_variance*vec1+self.bias_variance+1.), vec2) + np.outer(vec1, self.weight_variance*vec2 + self.bias_variance+1.)))*base_cov_grad).sum() - self.bias_variance.gradient = ((1./self._K_denom - -.5*self._K_numer/denom3 - *((vec1[:, None]+vec2[None, :])*self.weight_variance - + 2*self.bias_variance + 2.))*base_cov_grad).sum() + dvar, dw, db = self._comp_grads(dL_dK, X, X2)[:3] + self.variance.gradient = dvar + self.weight_variance.gradient = dw + self.bias_variance.gradient = db def update_gradients_diag(self, dL_dKdiag, X): - self._K_diag_computations(X) - self.variance.gradient = np.sum(self._K_diag_dvar*dL_dKdiag) + dvar, dw, db = self._comp_grads_diag(dL_dKdiag, X)[:3] + self.variance.gradient = dvar + self.weight_variance.gradient = dw + self.bias_variance.gradient = db - base = four_over_tau*self.variance/np.sqrt(1-self._K_diag_asin_arg*self._K_diag_asin_arg) - base_cov_grad = base*dL_dKdiag/np.square(self._K_diag_denom) - - self.weight_variance.gradient = (base_cov_grad*np.square(X).sum(axis=1)).sum() - self.bias_variance.gradient = base_cov_grad.sum() - def gradients_X(self, dL_dK, X, X2): """Derivative of the covariance matrix with respect to X""" - self._K_computations(X, X2) - arg = self._K_asin_arg - numer = self._K_numer - denom = self._K_denom - denom3 = denom*denom*denom - if X2 is not None: - vec2 = (X2*X2).sum(1)*self.weight_variance+self.bias_variance + 1. - return four_over_tau*self.weight_variance*self.variance*((X2[None, :, :]/denom[:, :, None] - vec2[None, :, None]*X[:, None, :]*(numer/denom3)[:, :, None])*(dL_dK/np.sqrt(1-arg*arg))[:, :, None]).sum(1) - else: - vec = (X*X).sum(1)*self.weight_variance+self.bias_variance + 1. - return 2*four_over_tau*self.weight_variance*self.variance*((X[None, :, :]/denom[:, :, None] - vec[None, :, None]*X[:, None, :]*(numer/denom3)[:, :, None])*(dL_dK/np.sqrt(1-arg*arg))[:, :, None]).sum(1) + return self._comp_grads(dL_dK, X, X2)[3] + + def gradients_X_X2(self, dL_dK, X, X2): + """Derivative of the covariance matrix with respect to X""" + return self._comp_grads(dL_dK, X, X2)[3:] def gradients_X_diag(self, dL_dKdiag, X): """Gradient of diagonal of covariance with respect to X""" - self._K_diag_computations(X) - arg = self._K_diag_asin_arg - denom = self._K_diag_denom - #numer = self._K_diag_numer - return four_over_tau*2.*self.weight_variance*self.variance*X*(1./denom*(1. - arg)*dL_dKdiag/(np.sqrt(1-arg*arg)))[:, None] + return self._comp_grads_diag(dL_dKdiag, X)[3] - - def _K_computations(self, X, X2): - """Pre-computations for the covariance matrix (used for computing the covariance and its gradients.""" + @Cache_this(limit=50, ignore_args=()) + def _comp_prod(self, X, X2=None): if X2 is None: - self._K_inner_prod = np.dot(X,X.T) - self._K_numer = self._K_inner_prod*self.weight_variance + self.bias_variance - vec = np.diag(self._K_numer) + 1. - self._K_denom = np.sqrt(np.outer(vec,vec)) + return (np.square(X)*self.weight_variance).sum(axis=1)+self.bias_variance else: - self._K_inner_prod = np.dot(X,X2.T) - self._K_numer = self._K_inner_prod*self.weight_variance + self.bias_variance - vec1 = (X*X).sum(1)*self.weight_variance + self.bias_variance + 1. - vec2 = (X2*X2).sum(1)*self.weight_variance + self.bias_variance + 1. - self._K_denom = np.sqrt(np.outer(vec1,vec2)) - self._K_asin_arg = self._K_numer/self._K_denom - self._K_dvar = four_over_tau*np.arcsin(self._K_asin_arg) - - def _K_diag_computations(self, X): - """Pre-computations concerning the diagonal terms (used for computation of diagonal and its gradients).""" - self._K_diag_numer = (X*X).sum(1)*self.weight_variance + self.bias_variance - self._K_diag_denom = self._K_diag_numer+1. - self._K_diag_asin_arg = self._K_diag_numer/self._K_diag_denom - self._K_diag_dvar = four_over_tau*np.arcsin(self._K_diag_asin_arg) + return (X*self.weight_variance).dot(X2.T)+self.bias_variance + + @Cache_this(limit=20, ignore_args=(1,)) + def _comp_grads(self, dL_dK, X, X2=None): + var,w,b = self.variance, self.weight_variance, self.bias_variance + K = self.K(X, X2) + dvar = (dL_dK*K).sum()/var + X_prod = self._comp_prod(X) + X2_prod = self._comp_prod(X2) if X2 is not None else X_prod + XTX = self._comp_prod(X,X2) if X2 is not None else self._comp_prod(X, X) + common = var*four_over_tau/np.sqrt((X_prod[:,None]+1.)*(X2_prod[None,:]+1.)-np.square(XTX))*dL_dK + if self.ARD: + if X2 is not None: + XX2 = X[:,None,:]*X2[None,:,:] if X2 is not None else X[:,None,:]*X[None,:,:] + XX = np.square(X) + X2X2 = np.square(X2) + Q = self.weight_variance.shape[0] + common_XTX = common*XTX + dw = np.dot(common.flat,XX2.reshape(-1,Q)) -( (common_XTX.sum(1)/(X_prod+1.)).T.dot(XX)+(common_XTX.sum(0)/(X2_prod+1.)).dot(X2X2))/2 + else: + XX2 = X[:,None,:]*X[None,:,:] + XX = np.square(X) + Q = self.weight_variance.shape[0] + common_XTX = common*XTX + dw = np.dot(common.flat,XX2.reshape(-1,Q)) - ((common_XTX.sum(0)+common_XTX.sum(1))/(X_prod+1.)).dot(XX)/2 + else: + dw = (common*((XTX-b)/w-XTX*(((X_prod-b)/(w*(X_prod+1.)))[:,None]+((X2_prod-b)/(w*(X2_prod+1.)))[None,:])/2.)).sum() + db = (common*(1.-XTX*(1./(X_prod[:,None]+1.)+1./(X2_prod[None,:]+1.))/2.)).sum() + if X2 is None: + common = common+common.T + dX = common.dot(X)*w-((common*XTX).sum(axis=1)/(X_prod+1.))[:,None]*X*w + dX2 = dX + else: + dX = common.dot(X2)*w-((common*XTX).sum(axis=1)/(X_prod+1.))[:,None]*X*w + dX2 = common.T.dot(X)*w-((common*XTX).sum(axis=0)/(X2_prod+1.))[:,None]*X2*w + return dvar, dw, db, dX, dX2 + + @Cache_this(limit=20, ignore_args=(1,)) + def _comp_grads_diag(self, dL_dKdiag, X): + var,w,b = self.variance, self.weight_variance, self.bias_variance + K = self.Kdiag(X) + dvar = (dL_dKdiag*K).sum()/var + X_prod = self._comp_prod(X) + common = var*four_over_tau/(np.sqrt(1-np.square(X_prod/(X_prod+1)))*np.square(X_prod+1))*dL_dKdiag + if self.ARD: + XX = np.square(X) + dw = np.dot(common,XX) + else: + dw = (common*(X_prod-b)).sum()/w + db = common.sum() + dX = common[:,None]*X*w*2 + return dvar, dw, db, dX diff --git a/GPy/kern/_src/prod.py b/GPy/kern/_src/prod.py index ff7cf140..b47e663d 100644 --- a/GPy/kern/_src/prod.py +++ b/GPy/kern/_src/prod.py @@ -27,8 +27,6 @@ class Prod(CombinationKernel): :param k1, k2: the kernels to multiply :type k1, k2: Kern - :param tensor: The kernels are either multiply as functions defined on the same input space (default) or on the product of the input spaces - :type tensor: Boolean :rtype: kernel object """ diff --git a/GPy/kern/_src/psi_comp/__init__.py b/GPy/kern/_src/psi_comp/__init__.py index 5041da50..1e0a9b72 100644 --- a/GPy/kern/_src/psi_comp/__init__.py +++ b/GPy/kern/_src/psi_comp/__init__.py @@ -9,18 +9,34 @@ from . import ssrbf_psi_comp from . import sslinear_psi_comp from . import linear_psi_comp -class PSICOMP_RBF(Pickleable): - @Cache_this(limit=2, ignore_args=(0,)) - def psicomputations(self, variance, lengthscale, Z, variational_posterior): + +class PSICOMP(Pickleable): + + def psicomputations(self, kern, Z, qX, return_psi2_n=False): + raise NotImplementedError("Abstract method!") + + def psiDerivativecomputations(self, kern, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, qX): + raise NotImplementedError("Abstract method!") + + def _setup_observers(self): + pass + +from .gaussherm import PSICOMP_GH + +class PSICOMP_RBF(PSICOMP): + @Cache_this(limit=5, ignore_args=(0,)) + def psicomputations(self, kern, Z, variational_posterior, return_psi2_n=False): + variance, lengthscale = kern.variance, kern.lengthscale if isinstance(variational_posterior, variational.NormalPosterior): - return rbf_psi_comp.psicomputations(variance, lengthscale, Z, variational_posterior) + return rbf_psi_comp.psicomputations(variance, lengthscale, Z, variational_posterior, return_psi2_n=return_psi2_n) elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): return ssrbf_psi_comp.psicomputations(variance, lengthscale, Z, variational_posterior) else: raise ValueError("unknown distriubtion received for psi-statistics") - @Cache_this(limit=2, ignore_args=(0,1,2,3)) - def psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): + @Cache_this(limit=5, ignore_args=(0,2,3,4)) + def psiDerivativecomputations(self, kern, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + variance, lengthscale = kern.variance, kern.lengthscale if isinstance(variational_posterior, variational.NormalPosterior): return rbf_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior) elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): @@ -28,28 +44,26 @@ class PSICOMP_RBF(Pickleable): else: raise ValueError("unknown distriubtion received for psi-statistics") - def _setup_observers(self): - pass +class PSICOMP_Linear(PSICOMP): -class PSICOMP_Linear(Pickleable): - - @Cache_this(limit=2, ignore_args=(0,)) - def psicomputations(self, variance, Z, variational_posterior): + @Cache_this(limit=5, ignore_args=(0,)) + def psicomputations(self, kern, Z, variational_posterior, return_psi2_n=False): + variances = kern.variances if isinstance(variational_posterior, variational.NormalPosterior): - return linear_psi_comp.psicomputations(variance, Z, variational_posterior) + return linear_psi_comp.psicomputations(variances, Z, variational_posterior, return_psi2_n=return_psi2_n) elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): - return sslinear_psi_comp.psicomputations(variance, Z, variational_posterior) + return sslinear_psi_comp.psicomputations(variances, Z, variational_posterior) else: raise ValueError("unknown distriubtion received for psi-statistics") - @Cache_this(limit=2, ignore_args=(0,1,2,3)) - def psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variational_posterior): + @Cache_this(limit=2, ignore_args=(0,2,3,4)) + def psiDerivativecomputations(self, kern, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + variances = kern.variances if isinstance(variational_posterior, variational.NormalPosterior): - return linear_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variational_posterior) + return linear_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variances, Z, variational_posterior) elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): - return sslinear_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variational_posterior) + return sslinear_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variances, Z, variational_posterior) else: raise ValueError("unknown distriubtion received for psi-statistics") - def _setup_observers(self): - pass \ No newline at end of file + diff --git a/GPy/kern/_src/psi_comp/gaussherm.py b/GPy/kern/_src/psi_comp/gaussherm.py new file mode 100644 index 00000000..923b3eb0 --- /dev/null +++ b/GPy/kern/_src/psi_comp/gaussherm.py @@ -0,0 +1,100 @@ +# Copyright (c) 2012, GPy authors (see AUTHORS.txt). +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +""" +An approximated psi-statistics implementation based on Gauss-Hermite Quadrature +""" + +import numpy as np + +from ....core.parameterization import Param +from GPy.util.caching import Cache_this +from ....util.linalg import tdot +from . import PSICOMP + +class PSICOMP_GH(PSICOMP): + """ + TODO: support Psi2 with shape NxMxM + """ + + def __init__(self, degree=5, cache_K=True): + self.degree = degree + self.cache_K = cache_K + self.locs, self.weights = np.polynomial.hermite.hermgauss(degree) + self.locs *= np.sqrt(2.) + self.weights*= 1./np.sqrt(np.pi) + self.Xs = None + + def _setup_observers(self): + pass + + @Cache_this(limit=10, ignore_args=(0,)) + def comp_K(self, Z, qX): + if self.Xs is None or self.Xs.shape != qX.mean.shape: + from ....core.parameterization import ObsAr + self.Xs = ObsAr(np.empty((self.degree,)+qX.mean.shape)) + mu, S = qX.mean.values, qX.variance.values + S_sq = np.sqrt(S) + for i in xrange(self.degree): + self.Xs[i] = self.locs[i]*S_sq+mu + return self.Xs + + @Cache_this(limit=10, ignore_args=(0,)) + def psicomputations(self, kern, Z, qX, return_psi2_n=False): + mu, S = qX.mean.values, qX.variance.values + N,M,Q = mu.shape[0],Z.shape[0],mu.shape[1] + if self.cache_K: Xs = self.comp_K(Z, qX) + else: S_sq = np.sqrt(S) + + psi0 = np.zeros((N,)) + psi1 = np.zeros((N,M)) + psi2 = np.zeros((M,M)) + for i in xrange(self.degree): + if self.cache_K: + X = Xs[i] + else: + X = self.locs[i]*S_sq+mu + psi0 += self.weights[i]* kern.Kdiag(X) + Kfu = kern.K(X,Z) + psi1 += self.weights[i]* Kfu + psi2 += self.weights[i]* tdot(Kfu.T) + return psi0, psi1, psi2 + + @Cache_this(limit=10, ignore_args=(0, 2,3,4)) + def psiDerivativecomputations(self, kern, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, qX): + mu, S = qX.mean.values, qX.variance.values + if self.cache_K: Xs = self.comp_K(Z, qX) + S_sq = np.sqrt(S) + + dtheta_old = kern.gradient.copy() + dtheta = np.zeros_like(kern.gradient) + if isinstance(Z, Param): + dZ = np.zeros_like(Z.values) + else: + dZ = np.zeros_like(Z) + dmu = np.zeros_like(mu) + dS = np.zeros_like(S) + for i in xrange(self.degree): + if self.cache_K: + X = Xs[i] + else: + X = self.locs[i]*S_sq+mu + dL_dpsi0_i = dL_dpsi0*self.weights[i] + kern.update_gradients_diag(dL_dpsi0_i, X) + dtheta += kern.gradient + dX = kern.gradients_X_diag(dL_dpsi0_i, X) + Kfu = kern.K(X,Z) + dL_dkfu = (dL_dpsi1+ 2.*Kfu.dot(dL_dpsi2))*self.weights[i] + kern.update_gradients_full(dL_dkfu, X, Z) + dtheta += kern.gradient + dX_i, dZ_i = kern.gradients_X_X2(dL_dkfu, X, Z) + dX += dX_i + dZ += dZ_i + dmu += dX + dS += dX*self.locs[i]/(2.*S_sq) + kern.gradient[:] = dtheta_old + return dtheta, dZ, dmu, dS + + + + diff --git a/GPy/kern/_src/psi_comp/linear_psi_comp.py b/GPy/kern/_src/psi_comp/linear_psi_comp.py index 50090428..aeb0479a 100644 --- a/GPy/kern/_src/psi_comp/linear_psi_comp.py +++ b/GPy/kern/_src/psi_comp/linear_psi_comp.py @@ -8,7 +8,7 @@ The package for the Psi statistics computation of the linear kernel for Bayesian import numpy as np from ....util.linalg import tdot -def psicomputations(variance, Z, variational_posterior): +def psicomputations(variance, Z, variational_posterior, return_psi2_n=False): """ Compute psi-statistics for ss-linear kernel """ @@ -21,8 +21,12 @@ def psicomputations(variance, Z, variational_posterior): S = variational_posterior.variance psi0 = (variance*(np.square(mu)+S)).sum(axis=1) - psi1 = np.dot(mu,(variance*Z).T) - psi2 = np.dot(S.sum(axis=0)*np.square(variance)*Z,Z.T)+ tdot(psi1.T) + Zv = variance * Z + psi1 = np.dot(mu,Zv.T) + if return_psi2_n: + psi2 = psi1[:,:,None] * psi1[:,None,:] + np.dot(S[:,None,:] * Zv[None,:,:], Zv.T) + else: + psi2 = np.dot(S.sum(axis=0) * Zv, Zv.T) + tdot(psi1.T) return psi0, psi1, psi2 @@ -40,7 +44,7 @@ def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variati dL_dmu += 2.*dL_dpsi0_var*mu+np.dot(dL_dpsi1,Z)*variance dL_dS += dL_dpsi0_var dL_dZ += dL_dpsi1_mu*variance - + return dL_dvar, dL_dZ, dL_dmu, dL_dS def _psi2computations(dL_dpsi2, variance, Z, mu, S): @@ -56,22 +60,42 @@ def _psi2computations(dL_dpsi2, variance, Z, mu, S): # _psi2_dZ MxQ # _psi2_dmu NxQ # _psi2_dS NxQ - + variance2 = np.square(variance) common_sum = np.dot(mu,(variance*Z).T) - Z_expect = (np.dot(dL_dpsi2,Z)*Z).sum(axis=0) - dL_dpsi2T = dL_dpsi2+dL_dpsi2.T - common_expect = np.dot(common_sum,np.dot(dL_dpsi2T,Z)) - Z2_expect = np.inner(common_sum,dL_dpsi2T) - Z1_expect = np.dot(dL_dpsi2T,Z) - - dL_dvar = 2.*S.sum(axis=0)*variance*Z_expect+(common_expect*mu).sum(axis=0) - - dL_dmu = common_expect*variance + if len(dL_dpsi2.shape)==2: + Z_expect = (np.dot(dL_dpsi2,Z)*Z).sum(axis=0) + dL_dpsi2T = dL_dpsi2+dL_dpsi2.T + common_expect = np.dot(common_sum,np.dot(dL_dpsi2T,Z)) + Z2_expect = np.inner(common_sum,dL_dpsi2T) + Z1_expect = np.dot(dL_dpsi2T,Z) - dL_dS = np.empty(S.shape) - dL_dS[:] = Z_expect*variance2 + dL_dvar = 2.*S.sum(axis=0)*variance*Z_expect+(common_expect*mu).sum(axis=0) - dL_dZ = variance2*S.sum(axis=0)*Z1_expect+np.dot(Z2_expect.T,variance*mu) + dL_dmu = common_expect*variance + + dL_dS = np.empty(S.shape) + dL_dS[:] = Z_expect*variance2 + + dL_dZ = variance2*S.sum(axis=0)*Z1_expect+np.dot(Z2_expect.T,variance*mu) + else: + N,M,Q = mu.shape[0],Z.shape[0],mu.shape[1] + dL_dpsi2_ = dL_dpsi2.sum(axis=0) + Z_expect = (np.dot(dL_dpsi2.reshape(N*M,M),Z).reshape(N,M,Q)*Z[None,:,:]).sum(axis=1) + dL_dpsi2T = dL_dpsi2_+dL_dpsi2_.T + dL_dpsi2T_ = dL_dpsi2+np.swapaxes(dL_dpsi2, 1, 2) + common_expect = np.dot(common_sum,np.dot(dL_dpsi2T,Z)) + common_expect_ = (common_sum[:,:,None]*np.dot(dL_dpsi2T_.reshape(N*M,M),Z).reshape(N,M,Q)).sum(axis=1) + Z2_expect = (common_sum[:,:,None]*dL_dpsi2T_).sum(axis=1) + Z1_expect = np.dot(dL_dpsi2T_.reshape(N*M,M),Z).reshape(N,M,Q) + + dL_dvar = 2.*variance*(S*Z_expect).sum(axis=0)+(common_expect_*mu).sum(axis=0) + + dL_dmu = common_expect_*variance + + dL_dS = np.empty(S.shape) + dL_dS[:] = variance2* Z_expect + + dL_dZ = variance2*(S[:,None,:]*Z1_expect).sum(axis=0)+np.dot(Z2_expect.T,variance*mu) return dL_dvar, dL_dmu, dL_dS, dL_dZ diff --git a/GPy/kern/_src/psi_comp/rbf_psi_comp.py b/GPy/kern/_src/psi_comp/rbf_psi_comp.py index e7a67d16..735a354d 100644 --- a/GPy/kern/_src/psi_comp/rbf_psi_comp.py +++ b/GPy/kern/_src/psi_comp/rbf_psi_comp.py @@ -5,13 +5,7 @@ The module for psi-statistics for RBF kernel import numpy as np from GPy.util.caching import Cacher -def psicomputations(variance, lengthscale, Z, variational_posterior): - """ - Z - MxQ - mu - NxQ - S - NxQ - gamma - NxQ - """ +def psicomputations(variance, lengthscale, Z, variational_posterior, return_psi2_n=False): # here are the "statistics" for psi0, psi1 and psi2 # Produced intermediate results: # _psi1 NxM @@ -21,16 +15,11 @@ def psicomputations(variance, lengthscale, Z, variational_posterior): psi0 = np.empty(mu.shape[0]) psi0[:] = variance psi1 = _psi1computations(variance, lengthscale, Z, mu, S) - psi2 = _psi2computations(variance, lengthscale, Z, mu, S).sum(axis=0) + psi2 = _psi2computations(variance, lengthscale, Z, mu, S) + if not return_psi2_n: psi2 = psi2.sum(axis=0) return psi0, psi1, psi2 def __psi1computations(variance, lengthscale, Z, mu, S): - """ - Z - MxQ - mu - NxQ - S - NxQ - gamma - NxQ - """ # here are the "statistics" for psi1 # Produced intermediate results: # _psi1 NxM @@ -45,26 +34,19 @@ def __psi1computations(variance, lengthscale, Z, mu, S): return _psi1 def __psi2computations(variance, lengthscale, Z, mu, S): - """ - Z - MxQ - mu - NxQ - S - NxQ - gamma - NxQ - """ # here are the "statistics" for psi2 # Produced intermediate results: # _psi2 MxM + N,M,Q = mu.shape[0], Z.shape[0], mu.shape[1] lengthscale2 = np.square(lengthscale) _psi2_logdenom = np.log(2.*S/lengthscale2+1.).sum(axis=-1)/(-2.) # N _psi2_exp1 = (np.square(Z[:,None,:]-Z[None,:,:])/lengthscale2).sum(axis=-1)/(-4.) #MxM Z_hat = (Z[:,None,:]+Z[None,:,:])/2. #MxMxQ denom = 1./(2.*S+lengthscale2) - _psi2_exp2 = -(np.square(mu)*denom).sum(axis=-1)[:,None,None]+2.*np.einsum('nq,moq,nq->nmo',mu,Z_hat,denom)-np.einsum('moq,nq->nmo',np.square(Z_hat),denom) + _psi2_exp2 = -(np.square(mu)*denom).sum(axis=-1)[:,None,None]+(2*(mu*denom).dot(Z_hat.reshape(M*M,Q).T) - denom.dot(np.square(Z_hat).reshape(M*M,Q).T)).reshape(N,M,M) _psi2 = variance*variance*np.exp(_psi2_logdenom[:,None,None]+_psi2_exp1[None,:,:]+_psi2_exp2) - - return _psi2 def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): @@ -86,13 +68,6 @@ def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscal return dL_dvar, dL_dlengscale, dL_dZ, dL_dmu, dL_dS def _psi1compDer(dL_dpsi1, variance, lengthscale, Z, mu, S): - """ - dL_dpsi1 - NxM - Z - MxQ - mu - NxQ - S - NxQ - gamma - NxQ - """ # here are the "statistics" for psi1 # Produced intermediate results: dL_dparams w.r.t. psi1 # _dL_dvariance 1 @@ -118,13 +93,6 @@ def _psi1compDer(dL_dpsi1, variance, lengthscale, Z, mu, S): return _dL_dvar, _dL_dl, _dL_dZ, _dL_dmu, _dL_dS def _psi2compDer(dL_dpsi2, variance, lengthscale, Z, mu, S): - """ - Z - MxQ - mu - NxQ - S - NxQ - gamma - NxQ - dL_dpsi2 - MxM - """ # here are the "statistics" for psi2 # Produced the derivatives w.r.t. psi2: # _dL_dvariance 1 @@ -157,5 +125,5 @@ def _psi2compDer(dL_dpsi2, variance, lengthscale, Z, mu, S): return _dL_dvar, _dL_dl, _dL_dZ, _dL_dmu, _dL_dS -_psi1computations = Cacher(__psi1computations, limit=1) -_psi2computations = Cacher(__psi2computations, limit=1) +_psi1computations = Cacher(__psi1computations, limit=5) +_psi2computations = Cacher(__psi2computations, limit=5) diff --git a/GPy/kern/_src/psi_comp/rbf_psi_gpucomp.py b/GPy/kern/_src/psi_comp/rbf_psi_gpucomp.py index dda68bdf..b3de8363 100644 --- a/GPy/kern/_src/psi_comp/rbf_psi_gpucomp.py +++ b/GPy/kern/_src/psi_comp/rbf_psi_gpucomp.py @@ -7,13 +7,6 @@ from ....util.caching import Cache_this from . import PSICOMP_RBF from ....util import gpu_init -try: - import pycuda.gpuarray as gpuarray - from pycuda.compiler import SourceModule - from ....util.linalg_gpu import sum_axis -except: - pass - gpu_code = """ // define THREADNUM @@ -241,7 +234,11 @@ gpu_code = """ class PSICOMP_RBF_GPU(PSICOMP_RBF): - def __init__(self, threadnum=128, blocknum=15, GPU_direct=False): + def __init__(self, threadnum=256, blocknum=30, GPU_direct=False): + from pycuda.compiler import SourceModule + from ....util.gpu_init import initGPU + initGPU() + self.GPU_direct = GPU_direct self.gpuCache = None @@ -264,7 +261,8 @@ class PSICOMP_RBF_GPU(PSICOMP_RBF): memo[id(self)] = s return s - def _initGPUCache(self, N, M, Q): + def _initGPUCache(self, N, M, Q): + import pycuda.gpuarray as gpuarray if self.gpuCache == None: self.gpuCache = { 'l_gpu' :gpuarray.empty((Q,),np.float64,order='F'), @@ -320,13 +318,14 @@ class PSICOMP_RBF_GPU(PSICOMP_RBF): def get_dimensions(self, Z, variational_posterior): return variational_posterior.mean.shape[0], Z.shape[0], Z.shape[1] - @Cache_this(limit=1, ignore_args=(0,)) - def psicomputations(self, variance, lengthscale, Z, variational_posterior): + @Cache_this(limit=5, ignore_args=(0,)) + def psicomputations(self, kern, Z, variational_posterior, return_psi2_n=False): """ Z - MxQ mu - NxQ S - NxQ """ + variance, lengthscale = kern.variance, kern.lengthscale N,M,Q = self.get_dimensions(Z, variational_posterior) self._initGPUCache(N,M,Q) self.sync_params(lengthscale, Z, variational_posterior.mean, variational_posterior.variance) @@ -355,8 +354,10 @@ class PSICOMP_RBF_GPU(PSICOMP_RBF): else: return psi0, psi1_gpu.get(), psi2_gpu.get() - @Cache_this(limit=1, ignore_args=(0,1,2,3)) - def psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): + @Cache_this(limit=5, ignore_args=(0,2,3,4)) + def psiDerivativecomputations(self, kern, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + variance, lengthscale = kern.variance, kern.lengthscale + from ....util.linalg_gpu import sum_axis ARD = (len(lengthscale)!=1) N,M,Q = self.get_dimensions(Z, variational_posterior) diff --git a/GPy/kern/_src/psi_comp/sslinear_psi_comp.py b/GPy/kern/_src/psi_comp/sslinear_psi_comp.py index d431cd61..7e9b4fdc 100644 --- a/GPy/kern/_src/psi_comp/sslinear_psi_comp.py +++ b/GPy/kern/_src/psi_comp/sslinear_psi_comp.py @@ -9,7 +9,7 @@ from ....util.linalg import tdot import numpy as np -def psicomputations(variance, Z, variational_posterior): +def psicomputations(variance, Z, variational_posterior, return_psi2_n=False): """ Compute psi-statistics for ss-linear kernel """ diff --git a/GPy/kern/_src/psi_comp/ssrbf_psi_comp.py b/GPy/kern/_src/psi_comp/ssrbf_psi_comp.py index f6a24c86..10ea95e4 100644 --- a/GPy/kern/_src/psi_comp/ssrbf_psi_comp.py +++ b/GPy/kern/_src/psi_comp/ssrbf_psi_comp.py @@ -9,7 +9,7 @@ import numpy as np try: from scipy import weave - + def _psicomputations(variance, lengthscale, Z, variational_posterior): """ Z - MxQ @@ -23,7 +23,7 @@ try: mu = variational_posterior.mean S = variational_posterior.variance gamma = variational_posterior.binary_prob - + N,M,Q = mu.shape[0],Z.shape[0],mu.shape[1] l2 = np.square(lengthscale) log_denom1 = np.log(S/l2+1) @@ -35,13 +35,13 @@ try: psi0[:] = variance psi1 = np.empty((N,M)) psi2n = np.empty((N,M,M)) - + from ....util.misc import param_to_array S = param_to_array(S) mu = param_to_array(mu) gamma = param_to_array(gamma) Z = param_to_array(Z) - + support_code = """ #include """ @@ -56,11 +56,11 @@ try: double lq = l2(q); double Zm1q = Z(m1,q); double Zm2q = Z(m2,q); - + if(m2==0) { // Compute Psi_1 double muZ = mu(n,q)-Z(m1,q); - + double psi1_exp1 = log_gamma(n,q) - (muZ*muZ/(Snq+lq) +log_denom1(n,q))/2.; double psi1_exp2 = log_gamma1(n,q) -Zm1q*Zm1q/(2.*lq); log_psi1 += (psi1_exp1>psi1_exp2)?psi1_exp1+log1p(exp(psi1_exp2-psi1_exp1)):psi1_exp2+log1p(exp(psi1_exp1-psi1_exp2)); @@ -69,10 +69,10 @@ try: double muZhat = mu(n,q) - (Zm1q+Zm2q)/2.; double Z2 = Zm1q*Zm1q+ Zm2q*Zm2q; double dZ = Zm1q - Zm2q; - + double psi2_exp1 = dZ*dZ/(-4.*lq)-muZhat*muZhat/(2.*Snq+lq) - log_denom2(n,q)/2. + log_gamma(n,q); double psi2_exp2 = log_gamma1(n,q) - Z2/(2.*lq); - log_psi2_n += (psi2_exp1>psi2_exp2)?psi2_exp1+log1p(exp(psi2_exp2-psi2_exp1)):psi2_exp2+log1p(exp(psi2_exp1-psi2_exp2)); + log_psi2_n += (psi2_exp1>psi2_exp2)?psi2_exp1+log1p(exp(psi2_exp2-psi2_exp1)):psi2_exp2+log1p(exp(psi2_exp1-psi2_exp2)); } double exp_psi2_n = exp(log_psi2_n); psi2n(n,m1,m2) = variance*variance*exp_psi2_n; @@ -83,18 +83,18 @@ try: } """ weave.inline(code, support_code=support_code, arg_names=['psi1','psi2n','N','M','Q','variance','l2','Z','mu','S','gamma','log_denom1','log_denom2','log_gamma','log_gamma1'], type_converters=weave.converters.blitz) - + psi2 = psi2n.sum(axis=0) return psi0,psi1,psi2,psi2n - + from GPy.util.caching import Cacher psicomputations = Cacher(_psicomputations, limit=1) - + def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): ARD = (len(lengthscale)!=1) - + _,psi1,_,psi2n = psicomputations(variance, lengthscale, Z, variational_posterior) - + mu = variational_posterior.mean S = variational_posterior.variance gamma = variational_posterior.binary_prob @@ -105,7 +105,7 @@ try: log_gamma = np.log(gamma) log_gamma1 = np.log(1.-gamma) variance = float(variance) - + dvar = np.zeros(1) dmu = np.zeros((N,Q)) dS = np.zeros((N,Q)) @@ -113,13 +113,13 @@ try: dl = np.zeros(Q) dZ = np.zeros((M,Q)) dvar += np.sum(dL_dpsi0) - + from ....util.misc import param_to_array S = param_to_array(S) mu = param_to_array(mu) gamma = param_to_array(gamma) Z = param_to_array(Z) - + support_code = """ #include """ @@ -136,16 +136,16 @@ try: double Zm2q = Z(m2,q); double gnq = gamma(n,q); double mu_nq = mu(n,q); - + if(m2==0) { - // Compute Psi_1 + // Compute Psi_1 double lpsi1 = psi1(n,m1)*dL_dpsi1(n,m1); if(q==0) {dvar(0) += lpsi1/variance;} - + double Zmu = Zm1q - mu_nq; double denom = Snq+lq; double Zmu2_denom = Zmu*Zmu/denom; - + double exp1 = log_gamma(n,q)-(Zmu*Zmu/(Snq+lq)+log_denom1(n,q))/(2.); double exp2 = log_gamma1(n,q)-Zm1q*Zm1q/(2.*lq); double d_exp1,d_exp2; @@ -157,7 +157,7 @@ try: d_exp2 = 1.; } double exp_sum = d_exp1+d_exp2; - + dmu(n,q) += lpsi1*Zmu*d_exp1/(denom*exp_sum); dS(n,q) += lpsi1*(Zmu2_denom-1.)*d_exp1/(denom*exp_sum)/2.; dgamma(n,q) += lpsi1*(d_exp1/gnq-d_exp2/(1.-gnq))/exp_sum; @@ -167,13 +167,13 @@ try: // Compute Psi_2 double lpsi2 = psi2n(n,m1,m2)*dL_dpsi2(m1,m2); if(q==0) {dvar(0) += lpsi2*2/variance;} - + double dZm1m2 = Zm1q - Zm2q; double Z2 = Zm1q*Zm1q+Zm2q*Zm2q; double muZhat = mu_nq - (Zm1q + Zm2q)/2.; double denom = 2.*Snq+lq; double muZhat2_denom = muZhat*muZhat/denom; - + double exp1 = dZm1m2*dZm1m2/(-4.*lq)-muZhat*muZhat/(2.*Snq+lq) - log_denom2(n,q)/2. + log_gamma(n,q); double exp2 = log_gamma1(n,q) - Z2/(2.*lq); double d_exp1,d_exp2; @@ -185,23 +185,23 @@ try: d_exp2 = 1.; } double exp_sum = d_exp1+d_exp2; - + dmu(n,q) += -2.*lpsi2*muZhat/denom*d_exp1/exp_sum; dS(n,q) += lpsi2*(2.*muZhat2_denom-1.)/denom*d_exp1/exp_sum; dgamma(n,q) += lpsi2*(d_exp1/gnq-d_exp2/(1.-gnq))/exp_sum; dl(q) += lpsi2*(((Snq/lq+muZhat2_denom)/denom+dZm1m2*dZm1m2/(4.*lq*lq))*d_exp1+Z2/(2.*lq*lq)*d_exp2)/exp_sum; - dZ(m1,q) += 2.*lpsi2*((muZhat/denom-dZm1m2/(2*lq))*d_exp1-Zm1q/lq*d_exp2)/exp_sum; + dZ(m1,q) += 2.*lpsi2*((muZhat/denom-dZm1m2/(2*lq))*d_exp1-Zm1q/lq*d_exp2)/exp_sum; } } } } """ weave.inline(code, support_code=support_code, arg_names=['dL_dpsi1','dL_dpsi2','psi1','psi2n','N','M','Q','variance','l2','Z','mu','S','gamma','log_denom1','log_denom2','log_gamma','log_gamma1','dvar','dl','dmu','dS','dgamma','dZ'], type_converters=weave.converters.blitz) - + dl *= 2.*lengthscale if not ARD: dl = dl.sum() - + return dvar, dl, dZ, dmu, dS, dgamma except: @@ -219,13 +219,13 @@ except: mu = variational_posterior.mean S = variational_posterior.variance gamma = variational_posterior.binary_prob - + psi0 = np.empty(mu.shape[0]) psi0[:] = variance psi1 = _psi1computations(variance, lengthscale, Z, mu, S, gamma) psi2 = _psi2computations(variance, lengthscale, Z, mu, S, gamma) return psi0, psi1, psi2 - + def _psi1computations(variance, lengthscale, Z, mu, S, gamma): """ Z - MxQ @@ -236,9 +236,9 @@ except: # here are the "statistics" for psi1 # Produced intermediate results: # _psi1 NxM - + lengthscale2 = np.square(lengthscale) - + # psi1 _psi1_denom = S[:, None, :] / lengthscale2 + 1. # Nx1xQ _psi1_denom_sqrt = np.sqrt(_psi1_denom) #Nx1xQ @@ -251,9 +251,9 @@ except: _psi1_exponent = _psi1_exponent_max+np.log(np.exp(_psi1_exponent1-_psi1_exponent_max) + np.exp(_psi1_exponent2-_psi1_exponent_max)) #NxMxQ _psi1_exp_sum = _psi1_exponent.sum(axis=-1) #NxM _psi1 = variance * np.exp(_psi1_exp_sum) # NxM - + return _psi1 - + def _psi2computations(variance, lengthscale, Z, mu, S, gamma): """ Z - MxQ @@ -264,14 +264,14 @@ except: # here are the "statistics" for psi2 # Produced intermediate results: # _psi2 MxM - + lengthscale2 = np.square(lengthscale) - + _psi2_Zhat = 0.5 * (Z[:, None, :] + Z[None, :, :]) # M,M,Q _psi2_Zdist = 0.5 * (Z[:, None, :] - Z[None, :, :]) # M,M,Q _psi2_Zdist_sq = np.square(_psi2_Zdist / lengthscale) # M,M,Q _psi2_Z_sq_sum = (np.square(Z[:,None,:])+np.square(Z[None,:,:]))/lengthscale2 # MxMxQ - + # psi2 _psi2_denom = 2.*S[:, None, None, :] / lengthscale2 + 1. # Nx1x1xQ _psi2_denom_sqrt = np.sqrt(_psi2_denom) @@ -284,28 +284,28 @@ except: _psi2_exponent = _psi2_exponent_max+np.log(np.exp(_psi2_exponent1-_psi2_exponent_max) + np.exp(_psi2_exponent2-_psi2_exponent_max)) _psi2_exp_sum = _psi2_exponent.sum(axis=-1) #NxM _psi2 = variance*variance * (np.exp(_psi2_exp_sum).sum(axis=0)) # MxM - + return _psi2 - + def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): ARD = (len(lengthscale)!=1) - + dvar_psi1, dl_psi1, dZ_psi1, dmu_psi1, dS_psi1, dgamma_psi1 = _psi1compDer(dL_dpsi1, variance, lengthscale, Z, variational_posterior.mean, variational_posterior.variance, variational_posterior.binary_prob) dvar_psi2, dl_psi2, dZ_psi2, dmu_psi2, dS_psi2, dgamma_psi2 = _psi2compDer(dL_dpsi2, variance, lengthscale, Z, variational_posterior.mean, variational_posterior.variance, variational_posterior.binary_prob) - + dL_dvar = np.sum(dL_dpsi0) + dvar_psi1 + dvar_psi2 - + dL_dlengscale = dl_psi1 + dl_psi2 if not ARD: dL_dlengscale = dL_dlengscale.sum() - + dL_dgamma = dgamma_psi1 + dgamma_psi2 dL_dmu = dmu_psi1 + dmu_psi2 dL_dS = dS_psi1 + dS_psi2 dL_dZ = dZ_psi1 + dZ_psi2 - + return dL_dvar, dL_dlengscale, dL_dZ, dL_dmu, dL_dS, dL_dgamma - + def _psi1compDer(dL_dpsi1, variance, lengthscale, Z, mu, S, gamma): """ dL_dpsi1 - NxM @@ -322,9 +322,9 @@ except: # _dL_dgamma NxQ # _dL_dmu NxQ # _dL_dS NxQ - + lengthscale2 = np.square(lengthscale) - + # psi1 _psi1_denom = S / lengthscale2 + 1. # NxQ _psi1_denom_sqrt = np.sqrt(_psi1_denom) #NxQ @@ -346,9 +346,9 @@ except: _dL_dS = np.einsum('nm,nmq,nmq,nq,nmq->nq',dL_dpsi1,_psi1_q,_psi1_exp_dist_sq,_psi1_common,(_psi1_dist_sq-1.))/2. # NxQ _dL_dZ = np.einsum('nm,nmq,nmq->mq',dL_dpsi1,_psi1_q, (- _psi1_common[:,None,:] * _psi1_dist * _psi1_exp_dist_sq - (1-gamma[:,None,:])/lengthscale2*Z[None,:,:]*_psi1_exp_Z)) _dL_dlengthscale = lengthscale* np.einsum('nm,nmq,nmq->q',dL_dpsi1,_psi1_q,(_psi1_common[:,None,:]*(S[:,None,:]/lengthscale2+_psi1_dist_sq)*_psi1_exp_dist_sq + (1-gamma[:,None,:])*np.square(Z[None,:,:]/lengthscale2)*_psi1_exp_Z)) - - return _dL_dvariance, _dL_dlengthscale, _dL_dZ, _dL_dmu, _dL_dS, _dL_dgamma - + + return _dL_dvariance, _dL_dlengthscale, _dL_dZ, _dL_dmu, _dL_dS, _dL_dgamma + def _psi2compDer(dL_dpsi2, variance, lengthscale, Z, mu, S, gamma): """ Z - MxQ @@ -365,14 +365,14 @@ except: # _dL_dgamma NxQ # _dL_dmu NxQ # _dL_dS NxQ - + lengthscale2 = np.square(lengthscale) - + _psi2_Zhat = 0.5 * (Z[:, None, :] + Z[None, :, :]) # M,M,Q _psi2_Zdist = 0.5 * (Z[:, None, :] - Z[None, :, :]) # M,M,Q _psi2_Zdist_sq = np.square(_psi2_Zdist / lengthscale) # M,M,Q _psi2_Z_sq_sum = (np.square(Z[:,None,:])+np.square(Z[None,:,:]))/lengthscale2 # MxMxQ - + # psi2 _psi2_denom = 2.*S / lengthscale2 + 1. # NxQ _psi2_denom_sqrt = np.sqrt(_psi2_denom) @@ -384,7 +384,7 @@ except: _psi2_exponent_max = np.maximum(_psi2_exponent1, _psi2_exponent2) _psi2_exponent = _psi2_exponent_max+np.log(np.exp(_psi2_exponent1-_psi2_exponent_max) + np.exp(_psi2_exponent2-_psi2_exponent_max)) _psi2_exp_sum = _psi2_exponent.sum(axis=-1) #NxM - _psi2_q = variance*variance * np.exp(_psi2_exp_sum[:,:,:,None]-_psi2_exponent) # NxMxMxQ + _psi2_q = variance*variance * np.exp(_psi2_exp_sum[:,:,:,None]-_psi2_exponent) # NxMxMxQ _psi2_exp_dist_sq = np.exp(-_psi2_Zdist_sq -_psi2_mudist_sq) # NxMxMxQ _psi2_exp_Z = np.exp(-0.5*_psi2_Z_sq_sum) # MxMxQ _psi2 = variance*variance * (np.exp(_psi2_exp_sum).sum(axis=0)) # MxM @@ -394,5 +394,5 @@ except: _dL_dS = np.einsum('mo,nmoq,nq,nmoq,nmoq->nq',dL_dpsi2,_psi2_q, _psi2_common, (2.*_psi2_mudist_sq-1.), _psi2_exp_dist_sq) _dL_dZ = 2.*np.einsum('mo,nmoq,nmoq->mq',dL_dpsi2,_psi2_q,(_psi2_common[:,None,None,:]*(-_psi2_Zdist*_psi2_denom[:,None,None,:]+_psi2_mudist)*_psi2_exp_dist_sq - (1-gamma[:,None,None,:])*Z[:,None,:]/lengthscale2*_psi2_exp_Z)) _dL_dlengthscale = 2.*lengthscale* np.einsum('mo,nmoq,nmoq->q',dL_dpsi2,_psi2_q,(_psi2_common[:,None,None,:]*(S[:,None,None,:]/lengthscale2+_psi2_Zdist_sq*_psi2_denom[:,None,None,:]+_psi2_mudist_sq)*_psi2_exp_dist_sq+(1-gamma[:,None,None,:])*_psi2_Z_sq_sum*0.5/lengthscale2*_psi2_exp_Z)) - + return _dL_dvariance, _dL_dlengthscale, _dL_dZ, _dL_dmu, _dL_dS, _dL_dgamma diff --git a/GPy/kern/_src/psi_comp/ssrbf_psi_gpucomp.py b/GPy/kern/_src/psi_comp/ssrbf_psi_gpucomp.py index 1a9d2058..46f4a06e 100644 --- a/GPy/kern/_src/psi_comp/ssrbf_psi_gpucomp.py +++ b/GPy/kern/_src/psi_comp/ssrbf_psi_gpucomp.py @@ -6,14 +6,7 @@ The module for psi-statistics for RBF kernel for Spike-and-Slab GPLVM import numpy as np from ....util.caching import Cache_this from . import PSICOMP_RBF -from ....util import gpu_init -try: - import pycuda.gpuarray as gpuarray - from pycuda.compiler import SourceModule - from ....util.linalg_gpu import sum_axis -except: - pass gpu_code = """ // define THREADNUM @@ -292,6 +285,11 @@ gpu_code = """ class PSICOMP_SSRBF_GPU(PSICOMP_RBF): def __init__(self, threadnum=128, blocknum=15, GPU_direct=False): + + from pycuda.compiler import SourceModule + from ....util.gpu_init import initGPU + initGPU() + self.GPU_direct = GPU_direct self.gpuCache = None @@ -314,7 +312,8 @@ class PSICOMP_SSRBF_GPU(PSICOMP_RBF): memo[id(self)] = s return s - def _initGPUCache(self, N, M, Q): + def _initGPUCache(self, N, M, Q): + import pycuda.gpuarray as gpuarray if self.gpuCache == None: self.gpuCache = { 'l_gpu' :gpuarray.empty((Q,),np.float64,order='F'), @@ -377,12 +376,13 @@ class PSICOMP_SSRBF_GPU(PSICOMP_RBF): return variational_posterior.mean.shape[0], Z.shape[0], Z.shape[1] @Cache_this(limit=1, ignore_args=(0,)) - def psicomputations(self, variance, lengthscale, Z, variational_posterior): + def psicomputations(self, kern, Z, variational_posterior, return_psi2_n=False): """ Z - MxQ mu - NxQ S - NxQ """ + variance, lengthscale = kern.variance, kern.lengthscale N,M,Q = self.get_dimensions(Z, variational_posterior) self._initGPUCache(N,M,Q) self.sync_params(lengthscale, Z, variational_posterior.mean, variational_posterior.variance, variational_posterior.binary_prob) @@ -409,8 +409,10 @@ class PSICOMP_SSRBF_GPU(PSICOMP_RBF): else: return psi0, psi1_gpu.get(), psi2_gpu.get() - @Cache_this(limit=1, ignore_args=(0,1,2,3)) - def psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): + @Cache_this(limit=1, ignore_args=(0,2,3,4)) + def psiDerivativecomputations(self, kern, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): + variance, lengthscale = kern.variance, kern.lengthscale + from ....util.linalg_gpu import sum_axis ARD = (len(lengthscale)!=1) N,M,Q = self.get_dimensions(Z, variational_posterior) diff --git a/GPy/kern/_src/rbf.py b/GPy/kern/_src/rbf.py index 73f2d0a4..cb34738a 100644 --- a/GPy/kern/_src/rbf.py +++ b/GPy/kern/_src/rbf.py @@ -31,6 +31,9 @@ class RBF(Stationary): def dK_dr(self, r): return -r*self.K_of_r(r) + def dK2_drdr(self, r): + return (r**2-1)*self.K_of_r(r) + def __getstate__(self): dc = super(RBF, self).__getstate__() if self.useGPU: @@ -50,22 +53,25 @@ class RBF(Stationary): #---------------------------------------# def psi0(self, Z, variational_posterior): - return self.psicomp.psicomputations(self.variance, self.lengthscale, Z, variational_posterior)[0] + return self.psicomp.psicomputations(self, Z, variational_posterior)[0] def psi1(self, Z, variational_posterior): - return self.psicomp.psicomputations(self.variance, self.lengthscale, Z, variational_posterior)[1] + return self.psicomp.psicomputations(self, Z, variational_posterior)[1] def psi2(self, Z, variational_posterior): - return self.psicomp.psicomputations(self.variance, self.lengthscale, Z, variational_posterior)[2] + return self.psicomp.psicomputations(self, Z, variational_posterior, return_psi2_n=False)[2] + + def psi2n(self, Z, variational_posterior): + return self.psicomp.psicomputations(self, Z, variational_posterior, return_psi2_n=True)[2] def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): - dL_dvar, dL_dlengscale = self.psicomp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, self.variance, self.lengthscale, Z, variational_posterior)[:2] + dL_dvar, dL_dlengscale = self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[:2] self.variance.gradient = dL_dvar self.lengthscale.gradient = dL_dlengscale def gradients_Z_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): - return self.psicomp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, self.variance, self.lengthscale, Z, variational_posterior)[2] + return self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[2] def gradients_qX_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): - return self.psicomp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, self.variance, self.lengthscale, Z, variational_posterior)[3:] + return self.psicomp.psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)[3:] diff --git a/GPy/kern/_src/spline.py b/GPy/kern/_src/spline.py new file mode 100644 index 00000000..233cf7e8 --- /dev/null +++ b/GPy/kern/_src/spline.py @@ -0,0 +1,52 @@ +# Copyright (c) 2015, Thomas Hornung +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +import numpy as np +from .kern import Kern +from ...core.parameterization import Param +from ...core.parameterization.transformations import Logexp +class Spline(Kern): + """ + Linear spline kernel. You need to specify 2 parameters: the variance and c. + The variance is defined in powers of 10. Thus specifying -2 means 10^-2. + The parameter c allows to define the stiffness of the spline fit. A very stiff + spline equals linear regression. + See https://www.youtube.com/watch?v=50Vgw11qn0o starting at minute 1:17:28 + Lit: Wahba, 1990 + """ + + def __init__(self, input_dim, variance=1., c=1., active_dims=None, name='spline'): + super(Spline, self).__init__(input_dim, active_dims, name) + self.variance = Param('variance', variance, Logexp()) + self.c = Param('c', c) + self.link_parameters(self.variance,self.c) + + + def K(self, X, X2=None): + if X2 is None: X2=X + term1 = (X+8.)*(X2.T+8.)/16. + term2 = abs((X-X2.T)/16.)**3 + term3 = ((X+8.)/16.)**3 + ((X2.T+8.)/16.)**3 + return (self.variance**2 * (1. + (1.+self.c) * term1 + self.c/3. * (term2 - term3))) + + def Kdiag(self, X): + term1 = np.square(X+8.,X+8.)/16. + term3 = 2. * ((X+8.)/16.)**3 + return (self.variance**2 * (1. + (1.+self.c) * term1 - self.c/3. * term3))[:,0] + + def update_gradients_full(self, dL_dK, X, X2=None): + if X2 is None: X2=X + term1 = (X+8.)*(X2.T+8.)/16. + term2 = abs((X-X2.T)/16.)**3 + term3 = ((X+8.)/16.)**3 + ((X2.T+8.)/16.)**3 + self.variance.gradient = np.sum(dL_dK * (2*self.variance * (1. + (1.+self.c) * term1 + self.c/3. * ( term2 - term3)))) + self.c.gradient = np.sum(dL_dK * (self.variance**2* (term1 + 1./3.*(term2 - term3)))) + + def update_gradients_diag(self, dL_dKdiag, X): + raise NotImplementedError + + def gradients_X(self, dL_dK, X, X2=None): + raise NotImplementedError + + def gradients_X_diag(self, dL_dKdiag, X): + raise NotImplementedError diff --git a/GPy/kern/_src/standard_periodic.py b/GPy/kern/_src/standard_periodic.py new file mode 100644 index 00000000..3da7a124 --- /dev/null +++ b/GPy/kern/_src/standard_periodic.py @@ -0,0 +1,166 @@ +# -*- coding: utf-8 -*- + +# Copyright (c) 2014, GPy authors (see AUTHORS.txt). +# Licensed under the BSD 3-clause license (see LICENSE.txt) +""" +The standard periodic kernel which mentioned in: + +[1] Gaussian Processes for Machine Learning, C. E. Rasmussen, C. K. I. Williams. +The MIT Press, 2005. + + +[2] Introduction to Gaussian processes. D. J. C. MacKay. In C. M. Bishop, editor, +Neural Networks and Machine Learning, pages 133-165. Springer, 1998. +""" + +from .kern import Kern +from ...core.parameterization import Param +from ...core.parameterization.transformations import Logexp + +import numpy as np + +class StdPeriodic(Kern): + """ + Standart periodic kernel + + .. math:: + + k(x,y) = \theta_1 \exp \left[ - \frac{1}{2} {}\sum_{i=1}^{input\_dim} + \left( \frac{\sin(\frac{\pi}{\lambda_i} (x_i - y_i) )}{l_i} \right)^2 \right] } + + :param input_dim: the number of input dimensions + :type input_dim: int + :param variance: the variance :math:`\theta_1` in the formula above + :type variance: float + :param wavelength: the vector of wavelengths :math:`\lambda_i`. If None then 1.0 is assumed. + :type wavelength: array or list of the appropriate size (or float if there is only one wavelength parameter) + :param lengthscale: the vector of lengthscale :math:`\l_i`. If None then 1.0 is assumed. + :type lengthscale: array or list of the appropriate size (or float if there is only one lengthscale parameter) + :param ARD1: Auto Relevance Determination with respect to wavelength. + If equal to "False" one single wavelength parameter :math:`\lambda_i` for + each dimension is assumed, otherwise there is one lengthscale + parameter per dimension. + :type ARD1: Boolean + :param ARD2: Auto Relevance Determination with respect to lengthscale. + If equal to "False" one single wavelength parameter :math:`l_i` for + each dimension is assumed, otherwise there is one lengthscale + parameter per dimension. + :type ARD2: Boolean + :param active_dims: indices of dimensions which are used in the computation of the kernel + :type wavelength: array or list of the appropriate size + :param name: Name of the kernel for output + :type String + :param useGPU: whether of not use GPU + :type Boolean + """ + + def __init__(self, input_dim, variance=1., wavelength=None, lengthscale=None, ARD1=False, ARD2=False, active_dims=None, name='std_periodic',useGPU=False): + super(StdPeriodic, self).__init__(input_dim, active_dims, name, useGPU=useGPU) + self.input_dim = input_dim + self.ARD1 = ARD1 # correspond to wavelengths + self.ARD2 = ARD2 # correspond to lengthscales + + self.name = name + + if self.ARD1 == False: + if wavelength is not None: + wavelength = np.asarray(wavelength) + assert wavelength.size == 1, "Only one wavelength needed for non-ARD kernel" + else: + wavelength = np.ones(1) + else: + if wavelength is not None: + wavelength = np.asarray(wavelength) + assert wavelength.size == input_dim, "bad number of wavelengths" + else: + wavelength = np.ones(input_dim) + + if self.ARD2 == False: + if lengthscale is not None: + lengthscale = np.asarray(lengthscale) + assert lengthscale.size == 1, "Only one lengthscale needed for non-ARD kernel" + else: + lengthscale = np.ones(1) + else: + if lengthscale is not None: + lengthscale = np.asarray(lengthscale) + assert lengthscale.size == input_dim, "bad number of lengthscales" + else: + lengthscale = np.ones(input_dim) + + self.variance = Param('variance', variance, Logexp()) + assert self.variance.size==1, "Variance size must be one" + self.wavelengths = Param('wavelengths', wavelength, Logexp()) + self.lengthscales = Param('lengthscales', lengthscale, Logexp()) + + self.link_parameters(self.variance, self.wavelengths, self.lengthscales) + + def parameters_changed(self): + """ + This functions deals as a callback for each optimization iteration. + If one optimization step was successfull and the parameters + this callback function will be called to be able to update any + precomputations for the kernel. + """ + + pass + + + def K(self, X, X2=None): + """Compute the covariance matrix between X and X2.""" + if X2 is None: + X2 = X + + base = np.pi * (X[:, None, :] - X2[None, :, :]) / self.wavelengths + exp_dist = np.exp( -0.5* np.sum( np.square( np.sin( base ) / self.lengthscales ), axis = -1 ) ) + + return self.variance * exp_dist + + + def Kdiag(self, X): + """Compute the diagonal of the covariance matrix associated to X.""" + ret = np.empty(X.shape[0]) + ret[:] = self.variance + return ret + + def update_gradients_full(self, dL_dK, X, X2=None): + """derivative of the covariance matrix with respect to the parameters.""" + if X2 is None: + X2 = X + + base = np.pi * (X[:, None, :] - X2[None, :, :]) / self.wavelengths + + sin_base = np.sin( base ) + exp_dist = np.exp( -0.5* np.sum( np.square( sin_base / self.lengthscales ), axis = -1 ) ) + + dwl = self.variance * (1.0/np.square(self.lengthscales)) * sin_base*np.cos(base) * (base / self.wavelengths) + + dl = self.variance * np.square( sin_base) / np.power( self.lengthscales, 3) + + self.variance.gradient = np.sum(exp_dist * dL_dK) + #target[0] += np.sum( exp_dist * dL_dK) + + if self.ARD1: # different wavelengths + self.wavelengths.gradient = (dwl * exp_dist[:,:,None] * dL_dK[:, :, None]).sum(0).sum(0) + else: # same wavelengths + self.wavelengths.gradient = np.sum(dwl.sum(-1) * exp_dist * dL_dK) + + if self.ARD2: # different lengthscales + self.lengthscales.gradient = (dl * exp_dist[:,:,None] * dL_dK[:, :, None]).sum(0).sum(0) + else: # same lengthscales + self.lengthscales.gradient = np.sum(dl.sum(-1) * exp_dist * dL_dK) + + def update_gradients_diag(self, dL_dKdiag, X): + """derivative of the diagonal of the covariance matrix with respect to the parameters.""" + self.variance.gradient = np.sum(dL_dKdiag) + self.wavelengths.gradient = 0 + self.lengthscales.gradient = 0 + +# def gradients_X(self, dL_dK, X, X2=None): +# """derivative of the covariance matrix with respect to X.""" +# +# raise NotImplemented("Periodic kernel: dK_dX not implemented") +# +# def gradients_X_diag(self, dL_dKdiag, X): +# +# raise NotImplemented("Periodic kernel: dKdiag_dX not implemented") diff --git a/GPy/kern/_src/static.py b/GPy/kern/_src/static.py index 64d14018..c7f7b118 100644 --- a/GPy/kern/_src/static.py +++ b/GPy/kern/_src/static.py @@ -24,6 +24,13 @@ class Static(Kern): def gradients_X_diag(self, dL_dKdiag, X): return np.zeros(X.shape) + def gradients_XX(self, dL_dK, X, X2): + if X2 is None: + X2 = X + return np.zeros((X.shape[0], X2.shape[0], X.shape[1]), dtype=np.float64) + def gradients_XX_diag(self, dL_dKdiag, X): + return np.zeros(X.shape) + def gradients_Z_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): return np.zeros(Z.shape) @@ -59,6 +66,9 @@ class White(Static): def psi2(self, Z, variational_posterior): return np.zeros((Z.shape[0], Z.shape[0]), dtype=np.float64) + def psi2n(self, Z, variational_posterior): + return np.zeros((1, Z.shape[0], Z.shape[0]), dtype=np.float64) + def update_gradients_full(self, dL_dK, X, X2=None): if X2 is None: self.variance.gradient = np.trace(dL_dK) @@ -92,6 +102,11 @@ class Bias(Static): ret[:] = self.variance*self.variance*variational_posterior.shape[0] return ret + def psi2n(self, Z, variational_posterior): + ret = np.empty((1, Z.shape[0], Z.shape[0]), dtype=np.float64) + ret[:] = self.variance*self.variance + return ret + def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): self.variance.gradient = dL_dpsi0.sum() + dL_dpsi1.sum() + 2.*self.variance*dL_dpsi2.sum()*variational_posterior.shape[0] @@ -120,6 +135,9 @@ class Fixed(Static): def psi2(self, Z, variational_posterior): return np.zeros((Z.shape[0], Z.shape[0]), dtype=np.float64) + def psi2n(self, Z, variational_posterior): + return np.zeros((1, Z.shape[0], Z.shape[0]), dtype=np.float64) + def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): self.variance.gradient = dL_dpsi0.sum() diff --git a/GPy/kern/_src/stationary.py b/GPy/kern/_src/stationary.py index e69e316b..d5f26798 100644 --- a/GPy/kern/_src/stationary.py +++ b/GPy/kern/_src/stationary.py @@ -15,7 +15,7 @@ from ...util.caching import Cache_this try: from . import stationary_cython except ImportError: - print('warning in sationary: failed to import cython module: falling back to numpy') + print('warning in stationary: failed to import cython module: falling back to numpy') config.set('cython', 'working', 'false') @@ -25,13 +25,16 @@ class Stationary(Kern): Stationary covariance fucntion depend only on r, where r is defined as - r = \sqrt{ \sum_{q=1}^Q (x_q - x'_q)^2 } + .. math:: + r(x, x') = \\sqrt{ \\sum_{q=1}^Q (x_q - x'_q)^2 } The covariance function k(x, x' can then be written k(r). In this implementation, r is scaled by the lengthscales parameter(s): - r = \sqrt{ \sum_{q=1}^Q \frac{(x_q - x'_q)^2}{\ell_q^2} }. + .. math:: + + r(x, x') = \\sqrt{ \\sum_{q=1}^Q \\frac{(x_q - x'_q)^2}{\ell_q^2} }. By default, there's only one lengthscale: seaprate lengthscales for each dimension can be enables by setting ARD=True. @@ -39,11 +42,12 @@ class Stationary(Kern): To implement a stationary covariance function using this class, one need only define the covariance function k(r), and it derivative. - ... - def K_of_r(self, r): - return foo - def dK_dr(self, r): - return bar + ``` + def K_of_r(self, r): + return foo + def dK_dr(self, r): + return bar + ``` The lengthscale(s) and variance parameters are added to the structure automatically. @@ -77,6 +81,10 @@ class Stationary(Kern): def dK_dr(self, r): raise NotImplementedError("implement derivative of the covariance function wrt r to use this class") + @Cache_this(limit=20, ignore_args=()) + def dK2_drdr(self, r): + raise NotImplementedError("implement second derivative of covariance wrt r to use this method") + @Cache_this(limit=5, ignore_args=()) def K(self, X, X2=None): """ @@ -89,11 +97,16 @@ class Stationary(Kern): r = self._scaled_dist(X, X2) return self.K_of_r(r) - @Cache_this(limit=3, ignore_args=()) + @Cache_this(limit=20, ignore_args=()) def dK_dr_via_X(self, X, X2): #a convenience function, so we can cache dK_dr return self.dK_dr(self._scaled_dist(X, X2)) + @Cache_this(limit=3, ignore_args=()) + def dK2_drdr_via_X(self, X, X2): + #a convenience function, so we can cache dK_dr + return self.dK2_drdr(self._scaled_dist(X, X2)) + def _unscaled_dist(self, X, X2=None): """ Compute the Euclidean distance between each row of X and X2, or between @@ -114,12 +127,13 @@ class Stationary(Kern): r2 = np.clip(r2, 0, np.inf) return np.sqrt(r2) - @Cache_this(limit=5, ignore_args=()) + @Cache_this(limit=20, ignore_args=()) def _scaled_dist(self, X, X2=None): """ Efficiently compute the scaled distance, r. - r = \sqrt( \sum_{q=1}^Q (x_q - x'q)^2/l_q^2 ) + ..math:: + r = \sqrt( \sum_{q=1}^Q (x_q - x'q)^2/l_q^2 ) Note that if thre is only one lengthscale, l comes outside the sum. In this case we compute the unscaled distance first (in a separate @@ -201,6 +215,59 @@ class Stationary(Kern): else: return self._gradients_X_pure(dL_dK, X, X2) + def gradients_XX(self, dL_dK, X, X2=None): + """ + Given the derivative of the objective K(dL_dK), compute the second derivative of K wrt X and X2: + + ..math: + \frac{\partial^2 K}{\partial X\partial X2} + + ..returns: + dL2_dXdX2: NxMxQ, for X [NxQ] and X2[MxQ] (X2 is X if, X2 is None) + Thus, we return the second derivative in X2. + """ + # The off diagonals in Q are always zero, this should also be true for the Linear kernel... + # According to multivariable chain rule, we can chain the second derivative through r: + # d2K_dXdX2 = dK_dr*d2r_dXdX2 + d2K_drdr * dr_dX * dr_dX2: + invdist = self._inv_dist(X, X2) + invdist2 = invdist**2 + + dL_dr = self.dK_dr_via_X(X, X2) * dL_dK + tmp1 = dL_dr * invdist + + dL_drdr = self.dK2_drdr_via_X(X, X2) * dL_dK + tmp2 = dL_drdr * invdist2 + + l2 = np.ones(X.shape[1]) * self.lengthscale**2 + + if X2 is None: + X2 = X + tmp1 -= np.eye(X.shape[0])*self.variance + else: + tmp1[X==X2.T] -= self.variance + + grad = np.empty((X.shape[0], X2.shape[0], X.shape[1]), dtype=np.float64) + #grad = np.empty(X.shape, dtype=np.float64) + for q in range(self.input_dim): + tmpdist2 = (X[:,[q]]-X2[:,[q]].T) ** 2 + grad[:, :, q] = ((tmp1*invdist2 - tmp2)*tmpdist2/l2[q] - tmp1)/l2[q] + #grad[:, :, q] = ((tmp1*(((tmpdist2)*invdist2/l2[q])-1)) - (tmp2*(tmpdist2))/l2[q])/l2[q] + #np.sum(((tmp1*(((tmpdist2)*invdist2/l2[q])-1)) - (tmp2*(tmpdist2))/l2[q])/l2[q], axis=1, out=grad[:,q]) + #np.sum( - (tmp2*(tmpdist**2)), axis=1, out=grad[:,q]) + return grad + + def gradients_XX_diag(self, dL_dK, X): + """ + Given the derivative of the objective K(dL_dK), compute the second derivative of K wrt X and X2: + + ..math: + \frac{\partial^2 K}{\partial X\partial X2} + + ..returns: + dL2_dXdX2: NxMxQ, for X [NxQ] and X2[MxQ] + """ + return np.ones(X.shape) * self.variance/self.lengthscale**2 + def _gradients_X_pure(self, dL_dK, X, X2=None): invdist = self._inv_dist(X, X2) dL_dr = self.dK_dr_via_X(X, X2) * dL_dK @@ -259,7 +326,7 @@ class OU(Stationary): .. math:: - k(r) = \\sigma^2 \exp(- r) \\ \\ \\ \\ \\text{ where } r = \sqrt{\sum_{i=1}^input_dim \\frac{(x_i-y_i)^2}{\ell_i^2} } + k(r) = \\sigma^2 \exp(- r) \\ \\ \\ \\ \\text{ where } r = \sqrt{\sum_{i=1}^{\text{input_dim}} \\frac{(x_i-y_i)^2}{\ell_i^2} } """ @@ -279,7 +346,7 @@ class Matern32(Stationary): .. math:: - k(r) = \\sigma^2 (1 + \\sqrt{3} r) \exp(- \sqrt{3} r) \\ \\ \\ \\ \\text{ where } r = \sqrt{\sum_{i=1}^input_dim \\frac{(x_i-y_i)^2}{\ell_i^2} } + k(r) = \\sigma^2 (1 + \\sqrt{3} r) \exp(- \sqrt{3} r) \\ \\ \\ \\ \\text{ where } r = \sqrt{\sum_{i=1}^{\\text{input_dim}} \\frac{(x_i-y_i)^2}{\ell_i^2} } """ @@ -326,7 +393,7 @@ class Matern52(Stationary): .. math:: k(r) = \sigma^2 (1 + \sqrt{5} r + \\frac53 r^2) \exp(- \sqrt{5} r) - """ + """ def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='Mat52'): super(Matern52, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) diff --git a/GPy/kern/_src/stationary_cython.c b/GPy/kern/_src/stationary_cython.c index 36a782a9..25351fd0 100644 --- a/GPy/kern/_src/stationary_cython.c +++ b/GPy/kern/_src/stationary_cython.c @@ -1,25 +1,13 @@ -/* Generated by Cython 0.21 */ +/* Generated by Cython 0.23 */ #define PY_SSIZE_T_CLEAN -#ifndef CYTHON_USE_PYLONG_INTERNALS -#ifdef PYLONG_BITS_IN_DIGIT -#define CYTHON_USE_PYLONG_INTERNALS 0 -#else -#include "pyconfig.h" -#ifdef PYLONG_BITS_IN_DIGIT -#define CYTHON_USE_PYLONG_INTERNALS 1 -#else -#define CYTHON_USE_PYLONG_INTERNALS 0 -#endif -#endif -#endif #include "Python.h" #ifndef Py_PYTHON_H #error Python headers needed to compile C extensions, please install development version of Python. #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else -#define CYTHON_ABI "0_21" +#define CYTHON_ABI "0_23" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) @@ -54,35 +42,40 @@ #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #endif -#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 +#if !defined(CYTHON_USE_PYLONG_INTERNALS) && CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x02070000 +#define CYTHON_USE_PYLONG_INTERNALS 1 +#endif +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" #define CYTHON_FORMAT_SSIZE_T "z" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif -#if PY_MAJOR_VERSION >= 3 +#ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif -#if PY_MAJOR_VERSION >= 3 +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif -#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE) +#ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 - #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \ + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) @@ -103,9 +96,12 @@ #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \ + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 @@ -151,6 +147,11 @@ #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong @@ -160,18 +161,22 @@ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif -#ifndef CYTHON_INLINE - #if defined(__GNUC__) - #define CYTHON_INLINE __inline__ - #elif defined(_MSC_VER) - #define CYTHON_INLINE __inline - #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L - #define CYTHON_INLINE inline - #else - #define CYTHON_INLINE - #endif +#if PY_VERSION_HEX >= 0x030500B1 +#define __Pyx_PyAsyncMethodsStruct PyAsyncMethods +#define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) +#elif CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 +typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; +} __Pyx_PyAsyncMethodsStruct; +#define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) +#else +#define __Pyx_PyType_AsAsync(obj) NULL #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) @@ -184,24 +189,33 @@ #define CYTHON_RESTRICT #endif #endif +#define __Pyx_void_to_None(void_result) (void_result, Py_INCREF(Py_None), Py_None) + +#ifndef CYTHON_INLINE + #if defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include #ifdef NAN #define __PYX_NAN() ((float) NAN) #else static CYTHON_INLINE float __PYX_NAN() { - /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and - a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is - a quiet NaN. */ float value; memset(&value, 0xFF, sizeof(value)); return value; } #endif -#ifdef __cplusplus -template -void __Pyx_call_destructor(T* x) { - x->~T(); -} -#endif #if PY_MAJOR_VERSION >= 3 @@ -220,10 +234,6 @@ void __Pyx_call_destructor(T* x) { #endif #endif -#if defined(WIN32) || defined(MS_WINDOWS) -#define _USE_MATH_DEFINES -#endif -#include #define __PYX_HAVE__GPy__kern___src__stationary_cython #define __PYX_HAVE_API__GPy__kern___src__stationary_cython #include "string.h" @@ -255,6 +265,13 @@ void __Pyx_call_destructor(T* x) { # define CYTHON_UNUSED # endif #endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; @@ -263,16 +280,34 @@ typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding; #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize -#define __Pyx_fits_Py_ssize_t(v, type, is_signed) ( \ - (sizeof(type) < sizeof(Py_ssize_t)) || \ - (sizeof(type) > sizeof(Py_ssize_t) && \ - likely(v < (type)PY_SSIZE_T_MAX || \ - v == (type)PY_SSIZE_T_MAX) && \ - (!is_signed || likely(v > (type)PY_SSIZE_T_MIN || \ - v == (type)PY_SSIZE_T_MIN))) || \ - (sizeof(type) == sizeof(Py_ssize_t) && \ - (is_signed || likely(v < (type)PY_SSIZE_T_MAX || \ +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX))) ) +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (_MSC_VER) && defined (_M_X64) + #define __Pyx_sst_abs(value) _abs64(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*); static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); #define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) @@ -289,11 +324,11 @@ static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { @@ -307,8 +342,9 @@ static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) #define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) #define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode #define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode -#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None) -#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False)) +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +#define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False)) static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x); static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); @@ -329,7 +365,7 @@ static int __Pyx_init_sys_getdefaultencoding_params(void) { const char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); @@ -491,21 +527,22 @@ typedef struct { #define CYTHON_ATOMICS 1 #endif #define __pyx_atomic_int_type int -#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 || \ - (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \ +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ !defined(__i386__) #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) #ifdef __PYX_DEBUG_ATOMICS #warning "Using GNU atomics" #endif -#elif CYTHON_ATOMICS && MSC_VER +#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 #include + #undef __pyx_atomic_int_type #define __pyx_atomic_int_type LONG #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS - #warning "Using MSVC atomics" + #pragma message ("Using MSVC atomics") #endif #elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) @@ -522,19 +559,19 @@ typedef struct { #endif typedef volatile __pyx_atomic_int_type __pyx_atomic_int; #if CYTHON_ATOMICS - #define __pyx_add_acquisition_count(memview) \ + #define __pyx_add_acquisition_count(memview)\ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) - #define __pyx_sub_acquisition_count(memview) \ + #define __pyx_sub_acquisition_count(memview)\ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #else - #define __pyx_add_acquisition_count(memview) \ + #define __pyx_add_acquisition_count(memview)\ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) - #define __pyx_sub_acquisition_count(memview) \ + #define __pyx_sub_acquisition_count(memview)\ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #endif -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -543,7 +580,7 @@ typedef volatile __pyx_atomic_int_type __pyx_atomic_int; */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -552,7 +589,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -561,7 +598,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -570,7 +607,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -579,7 +616,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -588,7 +625,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -597,7 +634,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -606,7 +643,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":739 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -615,7 +652,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -624,7 +661,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -633,7 +670,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -642,7 +679,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -651,7 +688,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -660,7 +697,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -669,7 +706,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -678,7 +715,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":757 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -687,7 +724,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -696,7 +733,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -705,7 +742,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -714,7 +751,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -723,8 +760,8 @@ typedef npy_double __pyx_t_5numpy_double_t; */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; -/* "GPy/kern/_src/stationary_cython.pyx":8 - * from cython.parallel import prange +/* "GPy/kern/_src/stationary_cython.pyx":9 + * cimport cython * * ctypedef np.float64_t DTYPE_t # <<<<<<<<<<<<<< * @@ -758,7 +795,7 @@ struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -767,7 +804,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":765 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -776,7 +813,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -785,7 +822,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -794,7 +831,7 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; */ typedef npy_cdouble __pyx_t_5numpy_complex_t; -/* "View.MemoryView":99 +/* "View.MemoryView":101 * * @cname("__pyx_array") * cdef class array: # <<<<<<<<<<<<<< @@ -818,7 +855,7 @@ struct __pyx_array_obj { }; -/* "View.MemoryView":269 +/* "View.MemoryView":271 * * @cname('__pyx_MemviewEnum') * cdef class Enum(object): # <<<<<<<<<<<<<< @@ -831,7 +868,7 @@ struct __pyx_MemviewEnum_obj { }; -/* "View.MemoryView":302 +/* "View.MemoryView":304 * * @cname('__pyx_memoryview') * cdef class memoryview(object): # <<<<<<<<<<<<<< @@ -854,7 +891,7 @@ struct __pyx_memoryview_obj { }; -/* "View.MemoryView":922 +/* "View.MemoryView":923 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -871,7 +908,7 @@ struct __pyx_memoryviewslice_obj { -/* "View.MemoryView":302 +/* "View.MemoryView":304 * * @cname('__pyx_memoryview') * cdef class memoryview(object): # <<<<<<<<<<<<<< @@ -891,7 +928,7 @@ struct __pyx_vtabstruct_memoryview { static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; -/* "View.MemoryView":922 +/* "View.MemoryView":923 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -903,6 +940,8 @@ struct __pyx_vtabstruct__memoryviewslice { struct __pyx_vtabstruct_memoryview __pyx_base; }; static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice; + +/* --- Runtime support code (head) --- */ #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -919,19 +958,19 @@ static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice; 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#define __Pyx_XGOTREF(r) #define __Pyx_XGIVEREF(r) #endif -#define __Pyx_XDECREF_SET(r, v) do { \ - PyObject *tmp = (PyObject *) r; \ - r = v; __Pyx_XDECREF(tmp); \ +#define __Pyx_XDECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_XDECREF(tmp);\ } while (0) -#define __Pyx_DECREF_SET(r, v) do { \ - PyObject *tmp = (PyObject *) r; \ - r = v; __Pyx_DECREF(tmp); \ +#define __Pyx_DECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_DECREF(tmp);\ } while (0) #define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0) #define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0) @@ -987,8 +1026,8 @@ static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); -static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \ - PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ const char* function_name); static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, @@ -1001,16 +1040,6 @@ static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); -static CYTHON_INLINE int __Pyx_div_int(int, int); /* proto */ - -#ifndef __PYX_FORCE_INIT_THREADS - #define __PYX_FORCE_INIT_THREADS 0 -#endif - -#define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) - -static CYTHON_INLINE int __Pyx_mod_int(int, int); /* proto */ - #define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d #define __Pyx_MEMVIEW_DIRECT 1 #define __Pyx_MEMVIEW_PTR 2 @@ -1044,6 +1073,26 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) + PyErr_SetObject(PyExc_KeyError, args); + Py_XDECREF(args); + } + return NULL; + } + Py_INCREF(value); + return value; +} +#else + #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#endif + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); @@ -1064,7 +1113,10 @@ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int #define __Pyx_PyString_Equals __Pyx_PyBytes_Equals #endif -static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */ +static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); + +#define UNARY_NEG_WOULD_OVERFLOW(x)\ + (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/ @@ -1082,20 +1134,22 @@ static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); -#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ - __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \ - (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ __Pyx_GetItemInt_Generic(o, to_py_func(i)))) -#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ - __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \ +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); -#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ - __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \ +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); @@ -1129,6 +1183,13 @@ static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/ static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/ static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/ static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { #if CYTHON_COMPILING_IN_CPYTHON PyObject* none = _PyList_Extend((PyListObject*)L, v); @@ -1159,12 +1220,16 @@ static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); -static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +static CYTHON_INLINE long __Pyx_div_long(long, long); static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/ static void __Pyx_WriteUnraisable(const char *name, int clineno, int lineno, const char *filename, - int full_traceback); + int full_traceback, int nogil); #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); @@ -1216,8 +1281,6 @@ typedef struct { static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0}; static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); - static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); @@ -1336,6 +1399,8 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do #endif #endif +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); + static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs, char order, int ndim); @@ -1385,19 +1450,21 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo /* Module declarations from 'cpython.buffer' */ -/* Module declarations from 'cpython.ref' */ - /* Module declarations from 'libc.string' */ /* Module declarations from 'libc.stdio' */ -/* Module declarations from 'cpython.object' */ - /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.type' */ static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + /* Module declarations from 'libc.stdlib' */ /* Module declarations from 'numpy' */ @@ -1410,6 +1477,10 @@ static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ +/* Module declarations from 'cython.view' */ + +/* Module declarations from 'cython' */ + /* Module declarations from 'GPy.kern._src.stationary_cython' */ static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; @@ -1465,51 +1536,8 @@ static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_Ellipsis; static PyObject *__pyx_builtin_TypeError; -static PyObject *__pyx_builtin_xrange; static PyObject *__pyx_builtin_id; static PyObject *__pyx_builtin_IndexError; -static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_D, int __pyx_v_M, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__grad); /* proto */ -static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED int __pyx_v_N, int __pyx_v_D, int __pyx_v_M, __Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_X2, __Pyx_memviewslice __pyx_v_tmp, __Pyx_memviewslice __pyx_v_grad); /* proto */ -static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grads_in_c(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__grad); /* proto */ -static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_6lengthscale_grads(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, __Pyx_memviewslice __pyx_v_tmp, __Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_X2, __Pyx_memviewslice __pyx_v_grad); /* proto */ -static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ -static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ -static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ -static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ -static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ -static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ -static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ -static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ -static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ -static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static char __pyx_k_B[] = "B"; static char __pyx_k_D[] = "D"; static char __pyx_k_H[] = "H"; @@ -1554,6 +1582,7 @@ static char __pyx_k_size[] = "size"; static char __pyx_k_step[] = "step"; static char __pyx_k_stop[] = "stop"; static char __pyx_k_test[] = "__test__"; +static char __pyx_k_ASCII[] = "ASCII"; static char __pyx_k_class[] = "__class__"; static char __pyx_k_error[] = "error"; static char __pyx_k_flags[] = "flags"; @@ -1563,6 +1592,7 @@ static char __pyx_k_range[] = "range"; static char __pyx_k_shape[] = "shape"; static char __pyx_k_start[] = "start"; static char __pyx_k_tmp_2[] = "tmp"; +static char __pyx_k_encode[] = "encode"; static char __pyx_k_format[] = "format"; static char __pyx_k_grad_2[] = "grad"; static char __pyx_k_grad_X[] = "grad_X"; @@ -1570,7 +1600,6 @@ static char __pyx_k_import[] = "__import__"; static char __pyx_k_name_2[] = "__name__"; static char __pyx_k_struct[] = "struct"; static char __pyx_k_unpack[] = "unpack"; -static char __pyx_k_xrange[] = "xrange"; static char __pyx_k_fortran[] = "fortran"; static char __pyx_k_memview[] = "memview"; static char __pyx_k_Ellipsis[] = "Ellipsis"; @@ -1605,7 +1634,7 @@ static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static char __pyx_k_strided_and_direct_or_indirect[] = ""; static char __pyx_k_GPy_kern__src_stationary_cython[] = "GPy.kern._src.stationary_cython"; -static char __pyx_k_home_james_work_GPy_GPy_kern__s[] = "/home/james/work/GPy/GPy/kern/_src/stationary_cython.pyx"; +static char __pyx_k_home_david_gits_GPy_GPy_kern__s[] = "/home/david/gits/GPy/GPy/kern/_src/stationary_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced"; static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; @@ -1622,6 +1651,7 @@ static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents static char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; static char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; +static PyObject *__pyx_n_s_ASCII; static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; static PyObject *__pyx_kp_s_Cannot_index_with_type_s; @@ -1662,6 +1692,7 @@ static PyObject *__pyx_kp_s_contiguous_and_indirect; static PyObject *__pyx_n_s_d; static PyObject *__pyx_n_s_dist; static PyObject *__pyx_n_s_dtype_is_object; +static PyObject *__pyx_n_s_encode; static PyObject *__pyx_n_s_enumerate; static PyObject *__pyx_n_s_error; static PyObject *__pyx_n_s_flags; @@ -1674,7 +1705,7 @@ static PyObject *__pyx_n_s_grad_2; static PyObject *__pyx_n_s_grad_X; static PyObject *__pyx_n_s_grad_X_cython; static PyObject *__pyx_n_s_gradq; -static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_kern__s; +static PyObject *__pyx_kp_s_home_david_gits_GPy_GPy_kern__s; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_itemsize; @@ -1716,7 +1747,48 @@ static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; static PyObject *__pyx_n_s_unpack; -static PyObject *__pyx_n_s_xrange; +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_D, int __pyx_v_M, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__grad); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED int __pyx_v_N, int __pyx_v_D, int __pyx_v_M, __Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_X2, __Pyx_memviewslice __pyx_v_tmp, __Pyx_memviewslice __pyx_v_grad); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grads_in_c(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__grad); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_6lengthscale_grads(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, __Pyx_memviewslice __pyx_v_tmp, __Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_X2, __Pyx_memviewslice __pyx_v_grad); /* proto */ +static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_int_0; static PyObject *__pyx_int_1; static PyObject *__pyx_int_neg_1; @@ -1729,30 +1801,32 @@ static PyObject *__pyx_tuple__6; static PyObject *__pyx_tuple__7; static PyObject *__pyx_tuple__8; static PyObject *__pyx_tuple__9; -static PyObject *__pyx_slice__14; -static PyObject *__pyx_slice__15; static PyObject *__pyx_slice__16; +static PyObject *__pyx_slice__17; +static PyObject *__pyx_slice__18; static PyObject *__pyx_tuple__10; static PyObject *__pyx_tuple__11; static PyObject *__pyx_tuple__12; static PyObject *__pyx_tuple__13; -static PyObject *__pyx_tuple__17; -static PyObject *__pyx_tuple__18; +static PyObject *__pyx_tuple__14; +static PyObject *__pyx_tuple__15; +static PyObject *__pyx_tuple__19; static PyObject *__pyx_tuple__20; static PyObject *__pyx_tuple__22; static PyObject *__pyx_tuple__24; static PyObject *__pyx_tuple__26; -static PyObject *__pyx_tuple__27; static PyObject *__pyx_tuple__28; static PyObject *__pyx_tuple__29; static PyObject *__pyx_tuple__30; -static PyObject *__pyx_codeobj__19; +static PyObject *__pyx_tuple__31; +static PyObject *__pyx_tuple__32; static PyObject *__pyx_codeobj__21; static PyObject *__pyx_codeobj__23; static PyObject *__pyx_codeobj__25; +static PyObject *__pyx_codeobj__27; -/* "GPy/kern/_src/stationary_cython.pyx":16 - * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) +/* "GPy/kern/_src/stationary_cython.pyx":17 + * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) nogil * * def grad_X(int N, int D, int M, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _X, @@ -1801,36 +1875,36 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_1grad_X(PyObject case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_D)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 4: if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 5: if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_tmp)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 6: if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_grad)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "grad_X") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "grad_X") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 7) { goto __pyx_L5_argtuple_error; @@ -1843,9 +1917,9 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_1grad_X(PyObject values[5] = PyTuple_GET_ITEM(__pyx_args, 5); values[6] = PyTuple_GET_ITEM(__pyx_args, 6); } - __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_D = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_M = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_D = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_M = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_v__X = ((PyArrayObject *)values[3]); __pyx_v__X2 = ((PyArrayObject *)values[4]); __pyx_v__tmp = ((PyArrayObject *)values[5]); @@ -1853,16 +1927,16 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_1grad_X(PyObject } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.stationary_cython.grad_X", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X), __pyx_ptype_5numpy_ndarray, 1, "_X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X2), __pyx_ptype_5numpy_ndarray, 1, "_X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__tmp), __pyx_ptype_5numpy_ndarray, 1, "_tmp", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 19; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__grad), __pyx_ptype_5numpy_ndarray, 1, "_grad", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X), __pyx_ptype_5numpy_ndarray, 1, "_X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X2), __pyx_ptype_5numpy_ndarray, 1, "_X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 19; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__tmp), __pyx_ptype_5numpy_ndarray, 1, "_tmp", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__grad), __pyx_ptype_5numpy_ndarray, 1, "_grad", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(__pyx_self, __pyx_v_N, __pyx_v_D, __pyx_v_M, __pyx_v__X, __pyx_v__X2, __pyx_v__tmp, __pyx_v__grad); /* function exit code */ @@ -1911,26 +1985,26 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU __pyx_pybuffernd__grad.rcbuffer = &__pyx_pybuffer__grad; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X.rcbuffer->pybuffer, (PyObject*)__pyx_v__X, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X.rcbuffer->pybuffer, (PyObject*)__pyx_v__X, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__X.diminfo[0].strides = __pyx_pybuffernd__X.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__X.diminfo[0].shape = __pyx_pybuffernd__X.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__X.diminfo[1].strides = __pyx_pybuffernd__X.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__X.diminfo[1].shape = __pyx_pybuffernd__X.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X2.rcbuffer->pybuffer, (PyObject*)__pyx_v__X2, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X2.rcbuffer->pybuffer, (PyObject*)__pyx_v__X2, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__X2.diminfo[0].strides = __pyx_pybuffernd__X2.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__X2.diminfo[0].shape = __pyx_pybuffernd__X2.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__X2.diminfo[1].strides = __pyx_pybuffernd__X2.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__X2.diminfo[1].shape = __pyx_pybuffernd__X2.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__tmp.rcbuffer->pybuffer, (PyObject*)__pyx_v__tmp, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__tmp.rcbuffer->pybuffer, (PyObject*)__pyx_v__tmp, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__tmp.diminfo[0].strides = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__tmp.diminfo[0].shape = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__tmp.diminfo[1].strides = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__tmp.diminfo[1].shape = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__grad.diminfo[0].strides = __pyx_pybuffernd__grad.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__grad.diminfo[0].shape = __pyx_pybuffernd__grad.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__grad.diminfo[1].strides = __pyx_pybuffernd__grad.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__grad.diminfo[1].shape = __pyx_pybuffernd__grad.rcbuffer->pybuffer.shape[1]; - /* "GPy/kern/_src/stationary_cython.pyx":21 + /* "GPy/kern/_src/stationary_cython.pyx":22 * np.ndarray[DTYPE_t, ndim=2] _tmp, * np.ndarray[DTYPE_t, ndim=2] _grad): * cdef double *X = _X.data # <<<<<<<<<<<<<< @@ -1939,7 +2013,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU */ __pyx_v_X = ((double *)__pyx_v__X->data); - /* "GPy/kern/_src/stationary_cython.pyx":22 + /* "GPy/kern/_src/stationary_cython.pyx":23 * np.ndarray[DTYPE_t, ndim=2] _grad): * cdef double *X = _X.data * cdef double *X2 = _X2.data # <<<<<<<<<<<<<< @@ -1948,35 +2022,68 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU */ __pyx_v_X2 = ((double *)__pyx_v__X2->data); - /* "GPy/kern/_src/stationary_cython.pyx":23 + /* "GPy/kern/_src/stationary_cython.pyx":24 * cdef double *X = _X.data * cdef double *X2 = _X2.data * cdef double *tmp = _tmp.data # <<<<<<<<<<<<<< * cdef double *grad = _grad.data - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + * with nogil: */ __pyx_v_tmp = ((double *)__pyx_v__tmp->data); - /* "GPy/kern/_src/stationary_cython.pyx":24 + /* "GPy/kern/_src/stationary_cython.pyx":25 * cdef double *X2 = _X2.data * cdef double *tmp = _tmp.data * cdef double *grad = _grad.data # <<<<<<<<<<<<<< - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. - * + * with nogil: + * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. */ __pyx_v_grad = ((double *)__pyx_v__grad->data); - /* "GPy/kern/_src/stationary_cython.pyx":25 + /* "GPy/kern/_src/stationary_cython.pyx":26 * cdef double *tmp = _tmp.data * cdef double *grad = _grad.data - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. # <<<<<<<<<<<<<< + * with nogil: # <<<<<<<<<<<<<< + * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. * - * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): */ - _grad_X(__pyx_v_N, __pyx_v_D, __pyx_v_M, __pyx_v_X, __pyx_v_X2, __pyx_v_tmp, __pyx_v_grad); + { + #ifdef WITH_THREAD + PyThreadState *_save; + Py_UNBLOCK_THREADS + #endif + /*try:*/ { - /* "GPy/kern/_src/stationary_cython.pyx":16 - * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) + /* "GPy/kern/_src/stationary_cython.pyx":27 + * cdef double *grad = _grad.data + * with nogil: + * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. # <<<<<<<<<<<<<< + * + * @cython.cdivision(True) + */ + _grad_X(__pyx_v_N, __pyx_v_D, __pyx_v_M, __pyx_v_X, __pyx_v_X2, __pyx_v_tmp, __pyx_v_grad); + } + + /* "GPy/kern/_src/stationary_cython.pyx":26 + * cdef double *tmp = _tmp.data + * cdef double *grad = _grad.data + * with nogil: # <<<<<<<<<<<<<< + * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + * + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; + } + } + + /* "GPy/kern/_src/stationary_cython.pyx":17 + * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) nogil * * def grad_X(int N, int D, int M, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _X, @@ -2008,12 +2115,12 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU return __pyx_r; } -/* "GPy/kern/_src/stationary_cython.pyx":27 - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. +/* "GPy/kern/_src/stationary_cython.pyx":30 * + * @cython.cdivision(True) * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): # <<<<<<<<<<<<<< * cdef int n,d,nd,m - * for nd in prange(N*D, nogil=True): + * for nd in prange(N * D, nogil=True): */ /* Python wrapper */ @@ -2058,36 +2165,36 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_3grad_X_cython(Py case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_D)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 4: if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 5: if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_tmp_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 6: if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_grad_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "grad_X_cython") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "grad_X_cython") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 7) { goto __pyx_L5_argtuple_error; @@ -2100,17 +2207,17 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_3grad_X_cython(Py values[5] = PyTuple_GET_ITEM(__pyx_args, 5); values[6] = PyTuple_GET_ITEM(__pyx_args, 6); } - __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_D = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_M = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_X = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[3]); if (unlikely(!__pyx_v_X.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_X2 = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[4]); if (unlikely(!__pyx_v_X2.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_tmp = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[5]); if (unlikely(!__pyx_v_tmp.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_grad = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[6]); if (unlikely(!__pyx_v_grad.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_D = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_M = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_X = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[3]); if (unlikely(!__pyx_v_X.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_X2 = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[4]); if (unlikely(!__pyx_v_X2.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_tmp = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[5]); if (unlikely(!__pyx_v_tmp.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_grad = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[6]); if (unlikely(!__pyx_v_grad.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X_cython", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.stationary_cython.grad_X_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); @@ -2133,29 +2240,26 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; - int __pyx_t_4; - int __pyx_t_5; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; int __pyx_t_6; int __pyx_t_7; - int __pyx_t_8; - int __pyx_t_9; - int __pyx_t_10; - int __pyx_t_11; - int __pyx_t_12; - int __pyx_t_13; - int __pyx_t_14; - int __pyx_t_15; - int __pyx_lineno = 0; - const char *__pyx_filename = NULL; - int __pyx_clineno = 0; + Py_ssize_t __pyx_t_8; + Py_ssize_t __pyx_t_9; + Py_ssize_t __pyx_t_10; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + Py_ssize_t __pyx_t_13; + Py_ssize_t __pyx_t_14; + Py_ssize_t __pyx_t_15; __Pyx_RefNannySetupContext("grad_X_cython", 0); - /* "GPy/kern/_src/stationary_cython.pyx":29 + /* "GPy/kern/_src/stationary_cython.pyx":32 * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): * cdef int n,d,nd,m - * for nd in prange(N*D, nogil=True): # <<<<<<<<<<<<<< - * n = nd/D - * d = nd%D + * for nd in prange(N * D, nogil=True): # <<<<<<<<<<<<<< + * n = nd / D + * d = nd % D */ { #ifdef WITH_THREAD @@ -2166,14 +2270,6 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY __pyx_t_1 = (__pyx_v_N * __pyx_v_D); if (1 == 0) abort(); { - int __pyx_parallel_temp0 = 0xbad0bad0; - int __pyx_parallel_temp1 = 0xbad0bad0; - int __pyx_parallel_temp2 = 0xbad0bad0; - int __pyx_parallel_temp3 = 0xbad0bad0; - const char *__pyx_parallel_filename = NULL; int __pyx_parallel_lineno = 0, __pyx_parallel_clineno = 0; - PyObject *__pyx_parallel_exc_type = NULL, *__pyx_parallel_exc_value = NULL, *__pyx_parallel_exc_tb = NULL; - int __pyx_parallel_why; - __pyx_parallel_why = 0; #if ((defined(__APPLE__) || defined(__OSX__)) && (defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))))) #undef likely #undef unlikely @@ -2184,20 +2280,13 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY if (__pyx_t_3 > 0) { #ifdef _OPENMP - #pragma omp parallel private(__pyx_t_5, __pyx_t_4, __pyx_t_13, __pyx_t_12, __pyx_t_7, __pyx_t_6, __pyx_t_11, __pyx_t_9, __pyx_t_10, __pyx_t_15, __pyx_t_8, __pyx_t_14) private(__pyx_filename, __pyx_lineno, __pyx_clineno) shared(__pyx_parallel_why, __pyx_parallel_exc_type, __pyx_parallel_exc_value, __pyx_parallel_exc_tb) + #pragma omp parallel private(__pyx_t_15, __pyx_t_11, __pyx_t_9, __pyx_t_10, __pyx_t_7, __pyx_t_8, __pyx_t_14, __pyx_t_5, __pyx_t_4, __pyx_t_13, __pyx_t_12, __pyx_t_6) #endif /* _OPENMP */ { - #ifdef _OPENMP - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - Py_BEGIN_ALLOW_THREADS - #endif /* _OPENMP */ #ifdef _OPENMP #pragma omp for lastprivate(__pyx_v_d) lastprivate(__pyx_v_m) firstprivate(__pyx_v_nd) lastprivate(__pyx_v_nd) lastprivate(__pyx_v_n) #endif /* _OPENMP */ for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_3; __pyx_t_2++){ - if (__pyx_parallel_why < 2) { __pyx_v_nd = 0 + 1 * __pyx_t_2; /* Initialize private variables to invalid values */ @@ -2205,82 +2294,52 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY __pyx_v_m = ((int)0xbad0bad0); __pyx_v_n = ((int)0xbad0bad0); - /* "GPy/kern/_src/stationary_cython.pyx":30 + /* "GPy/kern/_src/stationary_cython.pyx":33 * cdef int n,d,nd,m - * for nd in prange(N*D, nogil=True): - * n = nd/D # <<<<<<<<<<<<<< - * d = nd%D + * for nd in prange(N * D, nogil=True): + * n = nd / D # <<<<<<<<<<<<<< + * d = nd % D * grad[n,d] = 0.0 */ - if (unlikely(__pyx_v_D == 0)) { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero"); - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L8_error;} - } - else if (sizeof(int) == sizeof(long) && (!(((int)-1) > 0)) && unlikely(__pyx_v_D == (int)-1) && unlikely(UNARY_NEG_WOULD_OVERFLOW(__pyx_v_nd))) { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - PyErr_SetString(PyExc_OverflowError, "value too large to perform division"); - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L8_error;} - } - __pyx_v_n = __Pyx_div_int(__pyx_v_nd, __pyx_v_D); + __pyx_v_n = (__pyx_v_nd / __pyx_v_D); - /* "GPy/kern/_src/stationary_cython.pyx":31 - * for nd in prange(N*D, nogil=True): - * n = nd/D - * d = nd%D # <<<<<<<<<<<<<< + /* "GPy/kern/_src/stationary_cython.pyx":34 + * for nd in prange(N * D, nogil=True): + * n = nd / D + * d = nd % D # <<<<<<<<<<<<<< * grad[n,d] = 0.0 * for m in range(M): */ - if (unlikely(__pyx_v_D == 0)) { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero"); - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 31; __pyx_clineno = __LINE__; goto __pyx_L8_error;} - } - __pyx_v_d = __Pyx_mod_int(__pyx_v_nd, __pyx_v_D); + __pyx_v_d = (__pyx_v_nd % __pyx_v_D); - /* "GPy/kern/_src/stationary_cython.pyx":32 - * n = nd/D - * d = nd%D + /* "GPy/kern/_src/stationary_cython.pyx":35 + * n = nd / D + * d = nd % D * grad[n,d] = 0.0 # <<<<<<<<<<<<<< * for m in range(M): - * grad[n,d] += tmp[n,m]*(X[n,d]-X2[m,d]) + * grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) */ __pyx_t_4 = __pyx_v_n; __pyx_t_5 = __pyx_v_d; *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_grad.data + __pyx_t_4 * __pyx_v_grad.strides[0]) ) + __pyx_t_5 * __pyx_v_grad.strides[1]) )) = 0.0; - /* "GPy/kern/_src/stationary_cython.pyx":33 - * d = nd%D + /* "GPy/kern/_src/stationary_cython.pyx":36 + * d = nd % D * grad[n,d] = 0.0 * for m in range(M): # <<<<<<<<<<<<<< - * grad[n,d] += tmp[n,m]*(X[n,d]-X2[m,d]) + * grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) * */ __pyx_t_6 = __pyx_v_M; for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) { __pyx_v_m = __pyx_t_7; - /* "GPy/kern/_src/stationary_cython.pyx":34 + /* "GPy/kern/_src/stationary_cython.pyx":37 * grad[n,d] = 0.0 * for m in range(M): - * grad[n,d] += tmp[n,m]*(X[n,d]-X2[m,d]) # <<<<<<<<<<<<<< - * + * grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) # <<<<<<<<<<<<<< * + * def lengthscale_grads_in_c(int N, int M, int Q, */ __pyx_t_8 = __pyx_v_n; __pyx_t_9 = __pyx_v_m; @@ -2292,85 +2351,10 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY __pyx_t_15 = __pyx_v_d; *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_grad.data + __pyx_t_14 * __pyx_v_grad.strides[0]) ) + __pyx_t_15 * __pyx_v_grad.strides[1]) )) += ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_tmp.data + __pyx_t_8 * __pyx_v_tmp.strides[0]) ) + __pyx_t_9 * __pyx_v_tmp.strides[1]) ))) * ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X.data + __pyx_t_10 * __pyx_v_X.strides[0]) ) + __pyx_t_11 * __pyx_v_X.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X2.data + __pyx_t_12 * __pyx_v_X2.strides[0]) ) + __pyx_t_13 * __pyx_v_X2.strides[1]) ))))); } - goto __pyx_L13; - __pyx_L8_error:; - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - #ifdef _OPENMP - #pragma omp flush(__pyx_parallel_exc_type) - #endif /* _OPENMP */ - if (!__pyx_parallel_exc_type) { - __Pyx_ErrFetch(&__pyx_parallel_exc_type, &__pyx_parallel_exc_value, &__pyx_parallel_exc_tb); - __pyx_parallel_filename = __pyx_filename; __pyx_parallel_lineno = __pyx_lineno; __pyx_parallel_clineno = __pyx_clineno; - __Pyx_GOTREF(__pyx_parallel_exc_type); - } - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - } - __pyx_parallel_why = 4; - goto __pyx_L12; - __pyx_L12:; - #ifdef _OPENMP - #pragma omp critical(__pyx_parallel_lastprivates0) - #endif /* _OPENMP */ - { - __pyx_parallel_temp0 = __pyx_v_d; - __pyx_parallel_temp1 = __pyx_v_m; - __pyx_parallel_temp2 = __pyx_v_nd; - __pyx_parallel_temp3 = __pyx_v_n; - } - __pyx_L13:; - #ifdef _OPENMP - #pragma omp flush(__pyx_parallel_why) - #endif /* _OPENMP */ } } - #ifdef _OPENMP - Py_END_ALLOW_THREADS - #else -{ -#ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - #endif /* _OPENMP */ - /* Clean up any temporaries */ - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - #ifndef _OPENMP -} -#endif /* _OPENMP */ } } - if (__pyx_parallel_exc_type) { - /* This may have been overridden by a continue, break or return in another thread. Prefer the error. */ - __pyx_parallel_why = 4; - } - if (__pyx_parallel_why) { - __pyx_v_d = __pyx_parallel_temp0; - __pyx_v_m = __pyx_parallel_temp1; - __pyx_v_nd = __pyx_parallel_temp2; - __pyx_v_n = __pyx_parallel_temp3; - switch (__pyx_parallel_why) { - case 3: goto __pyx_L3_return; - case 4: - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif - __Pyx_GIVEREF(__pyx_parallel_exc_type); - __Pyx_ErrRestore(__pyx_parallel_exc_type, __pyx_parallel_exc_value, __pyx_parallel_exc_tb); - __pyx_filename = __pyx_parallel_filename; __pyx_lineno = __pyx_parallel_lineno; __pyx_clineno = __pyx_parallel_clineno; - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - } - goto __pyx_L4_error; - } - } } #if ((defined(__APPLE__) || defined(__OSX__)) && (defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))))) #undef likely @@ -2380,12 +2364,12 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY #endif } - /* "GPy/kern/_src/stationary_cython.pyx":29 + /* "GPy/kern/_src/stationary_cython.pyx":32 * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): * cdef int n,d,nd,m - * for nd in prange(N*D, nogil=True): # <<<<<<<<<<<<<< - * n = nd/D - * d = nd%D + * for nd in prange(N * D, nogil=True): # <<<<<<<<<<<<<< + * n = nd / D + * d = nd % D */ /*finally:*/ { /*normal exit:*/{ @@ -2394,37 +2378,20 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY #endif goto __pyx_L5; } - __pyx_L3_return: { - #ifdef WITH_THREAD - Py_BLOCK_THREADS - #endif - goto __pyx_L0; - } - __pyx_L4_error: { - #ifdef WITH_THREAD - Py_BLOCK_THREADS - #endif - goto __pyx_L1_error; - } __pyx_L5:; } } - /* "GPy/kern/_src/stationary_cython.pyx":27 - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + /* "GPy/kern/_src/stationary_cython.pyx":30 * + * @cython.cdivision(True) * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): # <<<<<<<<<<<<<< * cdef int n,d,nd,m - * for nd in prange(N*D, nogil=True): + * for nd in prange(N * D, nogil=True): */ /* function exit code */ __pyx_r = Py_None; __Pyx_INCREF(Py_None); - goto __pyx_L0; - __pyx_L1_error:; - __Pyx_AddTraceback("GPy.kern._src.stationary_cython.grad_X_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); - __pyx_r = NULL; - __pyx_L0:; __PYX_XDEC_MEMVIEW(&__pyx_v_X, 1); __PYX_XDEC_MEMVIEW(&__pyx_v_X2, 1); __PYX_XDEC_MEMVIEW(&__pyx_v_tmp, 1); @@ -2434,8 +2401,8 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CY return __pyx_r; } -/* "GPy/kern/_src/stationary_cython.pyx":38 - * +/* "GPy/kern/_src/stationary_cython.pyx":39 + * grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) * * def lengthscale_grads_in_c(int N, int M, int Q, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _tmp, @@ -2484,36 +2451,36 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_5lengthscale_grad case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_Q)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_tmp)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 4: if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 5: if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 6: if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_grad)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "lengthscale_grads_in_c") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "lengthscale_grads_in_c") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 7) { goto __pyx_L5_argtuple_error; @@ -2526,9 +2493,9 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_5lengthscale_grad values[5] = PyTuple_GET_ITEM(__pyx_args, 5); values[6] = PyTuple_GET_ITEM(__pyx_args, 6); } - __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_M = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_Q = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_Q == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_M = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_Q = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_Q == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_v__tmp = ((PyArrayObject *)values[3]); __pyx_v__X = ((PyArrayObject *)values[4]); __pyx_v__X2 = ((PyArrayObject *)values[5]); @@ -2536,16 +2503,16 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_5lengthscale_grad } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.stationary_cython.lengthscale_grads_in_c", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__tmp), __pyx_ptype_5numpy_ndarray, 1, "_tmp", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X), __pyx_ptype_5numpy_ndarray, 1, "_X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 40; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X2), __pyx_ptype_5numpy_ndarray, 1, "_X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 41; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__grad), __pyx_ptype_5numpy_ndarray, 1, "_grad", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__tmp), __pyx_ptype_5numpy_ndarray, 1, "_tmp", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 40; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X), __pyx_ptype_5numpy_ndarray, 1, "_X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 41; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X2), __pyx_ptype_5numpy_ndarray, 1, "_X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__grad), __pyx_ptype_5numpy_ndarray, 1, "_grad", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 43; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grads_in_c(__pyx_self, __pyx_v_N, __pyx_v_M, __pyx_v_Q, __pyx_v__tmp, __pyx_v__X, __pyx_v__X2, __pyx_v__grad); /* function exit code */ @@ -2594,26 +2561,26 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grad __pyx_pybuffernd__grad.rcbuffer = &__pyx_pybuffer__grad; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__tmp.rcbuffer->pybuffer, (PyObject*)__pyx_v__tmp, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__tmp.rcbuffer->pybuffer, (PyObject*)__pyx_v__tmp, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__tmp.diminfo[0].strides = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__tmp.diminfo[0].shape = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__tmp.diminfo[1].strides = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__tmp.diminfo[1].shape = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X.rcbuffer->pybuffer, (PyObject*)__pyx_v__X, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X.rcbuffer->pybuffer, (PyObject*)__pyx_v__X, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__X.diminfo[0].strides = __pyx_pybuffernd__X.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__X.diminfo[0].shape = __pyx_pybuffernd__X.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__X.diminfo[1].strides = __pyx_pybuffernd__X.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__X.diminfo[1].shape = __pyx_pybuffernd__X.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X2.rcbuffer->pybuffer, (PyObject*)__pyx_v__X2, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X2.rcbuffer->pybuffer, (PyObject*)__pyx_v__X2, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__X2.diminfo[0].strides = __pyx_pybuffernd__X2.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__X2.diminfo[0].shape = __pyx_pybuffernd__X2.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__X2.diminfo[1].strides = __pyx_pybuffernd__X2.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__X2.diminfo[1].shape = __pyx_pybuffernd__X2.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__grad.diminfo[0].strides = __pyx_pybuffernd__grad.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__grad.diminfo[0].shape = __pyx_pybuffernd__grad.rcbuffer->pybuffer.shape[0]; - /* "GPy/kern/_src/stationary_cython.pyx":43 + /* "GPy/kern/_src/stationary_cython.pyx":44 * np.ndarray[DTYPE_t, ndim=2] _X2, * np.ndarray[DTYPE_t, ndim=1] _grad): * cdef double *tmp = _tmp.data # <<<<<<<<<<<<<< @@ -2622,7 +2589,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grad */ __pyx_v_tmp = ((double *)__pyx_v__tmp->data); - /* "GPy/kern/_src/stationary_cython.pyx":44 + /* "GPy/kern/_src/stationary_cython.pyx":45 * np.ndarray[DTYPE_t, ndim=1] _grad): * cdef double *tmp = _tmp.data * cdef double *X = _X.data # <<<<<<<<<<<<<< @@ -2631,35 +2598,68 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grad */ __pyx_v_X = ((double *)__pyx_v__X->data); - /* "GPy/kern/_src/stationary_cython.pyx":45 + /* "GPy/kern/_src/stationary_cython.pyx":46 * cdef double *tmp = _tmp.data * cdef double *X = _X.data * cdef double *X2 = _X2.data # <<<<<<<<<<<<<< * cdef double *grad = _grad.data - * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. + * with nogil: */ __pyx_v_X2 = ((double *)__pyx_v__X2->data); - /* "GPy/kern/_src/stationary_cython.pyx":46 + /* "GPy/kern/_src/stationary_cython.pyx":47 * cdef double *X = _X.data * cdef double *X2 = _X2.data * cdef double *grad = _grad.data # <<<<<<<<<<<<<< - * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. - * + * with nogil: + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. */ __pyx_v_grad = ((double *)__pyx_v__grad->data); - /* "GPy/kern/_src/stationary_cython.pyx":47 + /* "GPy/kern/_src/stationary_cython.pyx":48 * cdef double *X2 = _X2.data * cdef double *grad = _grad.data - * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. # <<<<<<<<<<<<<< + * with nogil: # <<<<<<<<<<<<<< + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. + * + */ + { + #ifdef WITH_THREAD + PyThreadState *_save; + Py_UNBLOCK_THREADS + #endif + /*try:*/ { + + /* "GPy/kern/_src/stationary_cython.pyx":49 + * cdef double *grad = _grad.data + * with nogil: + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. # <<<<<<<<<<<<<< * * def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): */ - _lengthscale_grads(__pyx_v_N, __pyx_v_M, __pyx_v_Q, __pyx_v_tmp, __pyx_v_X, __pyx_v_X2, __pyx_v_grad); + _lengthscale_grads(__pyx_v_N, __pyx_v_M, __pyx_v_Q, __pyx_v_tmp, __pyx_v_X, __pyx_v_X2, __pyx_v_grad); + } - /* "GPy/kern/_src/stationary_cython.pyx":38 + /* "GPy/kern/_src/stationary_cython.pyx":48 + * cdef double *X2 = _X2.data + * cdef double *grad = _grad.data + * with nogil: # <<<<<<<<<<<<<< + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. * + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; + } + } + + /* "GPy/kern/_src/stationary_cython.pyx":39 + * grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) * * def lengthscale_grads_in_c(int N, int M, int Q, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _tmp, @@ -2691,8 +2691,8 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grad return __pyx_r; } -/* "GPy/kern/_src/stationary_cython.pyx":49 - * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. +/* "GPy/kern/_src/stationary_cython.pyx":51 + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. * * def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): # <<<<<<<<<<<<<< * cdef int q, n, m @@ -2741,36 +2741,36 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_7lengthscale_grad case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_Q)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_tmp_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 4: if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 5: if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 6: if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_grad_2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "lengthscale_grads") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "lengthscale_grads") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 7) { goto __pyx_L5_argtuple_error; @@ -2783,17 +2783,17 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_7lengthscale_grad values[5] = PyTuple_GET_ITEM(__pyx_args, 5); 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__pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_tmp = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[3]); if (unlikely(!__pyx_v_tmp.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_X = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[4]); if (unlikely(!__pyx_v_X.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_X2 = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[5]); if (unlikely(!__pyx_v_X2.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_grad = __Pyx_PyObject_to_MemoryviewSlice_ds_double(values[6]); if (unlikely(!__pyx_v_grad.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.stationary_cython.lengthscale_grads", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); @@ -2815,93 +2815,123 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_6lengthscale_grad __Pyx_RefNannyDeclarations int __pyx_t_1; int __pyx_t_2; - int __pyx_t_3; + Py_ssize_t __pyx_t_3; int __pyx_t_4; int __pyx_t_5; int __pyx_t_6; int __pyx_t_7; - int __pyx_t_8; - int __pyx_t_9; - int __pyx_t_10; - int __pyx_t_11; - int __pyx_t_12; - int __pyx_t_13; - int __pyx_t_14; + Py_ssize_t __pyx_t_8; + Py_ssize_t __pyx_t_9; + Py_ssize_t __pyx_t_10; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + Py_ssize_t __pyx_t_13; + Py_ssize_t __pyx_t_14; __Pyx_RefNannySetupContext("lengthscale_grads", 0); - /* "GPy/kern/_src/stationary_cython.pyx":52 + /* "GPy/kern/_src/stationary_cython.pyx":54 * cdef int q, n, m * cdef double gradq, dist - * for q in range(Q): # <<<<<<<<<<<<<< - * grad[q] = 0.0 - * for n in range(N): + * with nogil: # <<<<<<<<<<<<<< + * for q in range(Q): + * grad[q] = 0.0 */ - __pyx_t_1 = __pyx_v_Q; - for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { - __pyx_v_q = __pyx_t_2; + { + #ifdef WITH_THREAD + PyThreadState *_save; + Py_UNBLOCK_THREADS + #endif + /*try:*/ { - /* "GPy/kern/_src/stationary_cython.pyx":53 + /* "GPy/kern/_src/stationary_cython.pyx":55 * cdef double gradq, dist - * for q in range(Q): - * grad[q] = 0.0 # <<<<<<<<<<<<<< - * for n in range(N): - * for m in range(M): + * with nogil: + * for q in range(Q): # <<<<<<<<<<<<<< + * grad[q] = 0.0 + * for n in range(N): */ - __pyx_t_3 = __pyx_v_q; - *((double *) ( /* dim=0 */ (__pyx_v_grad.data + __pyx_t_3 * __pyx_v_grad.strides[0]) )) = 0.0; + __pyx_t_1 = __pyx_v_Q; + for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { + __pyx_v_q = __pyx_t_2; - /* "GPy/kern/_src/stationary_cython.pyx":54 - * for q in range(Q): - * grad[q] = 0.0 - * for n in range(N): # <<<<<<<<<<<<<< - * for m in range(M): - * dist = X[n,q] - X2[m,q] + /* "GPy/kern/_src/stationary_cython.pyx":56 + * with nogil: + * for q in range(Q): + * grad[q] = 0.0 # <<<<<<<<<<<<<< + * for n in range(N): + * for m in range(M): */ - __pyx_t_4 = __pyx_v_N; - for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { - __pyx_v_n = __pyx_t_5; + __pyx_t_3 = __pyx_v_q; + *((double *) ( /* dim=0 */ (__pyx_v_grad.data + __pyx_t_3 * __pyx_v_grad.strides[0]) )) = 0.0; - /* "GPy/kern/_src/stationary_cython.pyx":55 - * grad[q] = 0.0 - * for n in range(N): - * for m in range(M): # <<<<<<<<<<<<<< - * dist = X[n,q] - X2[m,q] - * grad[q] += tmp[n,m]*dist*dist + /* "GPy/kern/_src/stationary_cython.pyx":57 + * for q in range(Q): + * grad[q] = 0.0 + * for n in range(N): # <<<<<<<<<<<<<< + * for m in range(M): + * dist = X[n,q] - X2[m,q] */ - __pyx_t_6 = __pyx_v_M; - for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) { - __pyx_v_m = __pyx_t_7; + __pyx_t_4 = __pyx_v_N; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_n = __pyx_t_5; - /* "GPy/kern/_src/stationary_cython.pyx":56 - * for n in range(N): - * for m in range(M): - * dist = X[n,q] - X2[m,q] # <<<<<<<<<<<<<< - * grad[q] += tmp[n,m]*dist*dist - * + /* "GPy/kern/_src/stationary_cython.pyx":58 + * grad[q] = 0.0 + * for n in range(N): + * for m in range(M): # <<<<<<<<<<<<<< + * dist = X[n,q] - X2[m,q] + * grad[q] += tmp[n, m] * dist * dist */ - __pyx_t_8 = __pyx_v_n; - __pyx_t_9 = __pyx_v_q; - __pyx_t_10 = __pyx_v_m; - __pyx_t_11 = __pyx_v_q; - __pyx_v_dist = ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X.data + __pyx_t_8 * __pyx_v_X.strides[0]) ) + __pyx_t_9 * __pyx_v_X.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X2.data + __pyx_t_10 * __pyx_v_X2.strides[0]) ) + __pyx_t_11 * __pyx_v_X2.strides[1]) )))); + __pyx_t_6 = __pyx_v_M; + for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) { + __pyx_v_m = __pyx_t_7; - /* "GPy/kern/_src/stationary_cython.pyx":57 - * for m in range(M): - * dist = X[n,q] - X2[m,q] - * grad[q] += tmp[n,m]*dist*dist # <<<<<<<<<<<<<< - * - * + /* "GPy/kern/_src/stationary_cython.pyx":59 + * for n in range(N): + * for m in range(M): + * dist = X[n,q] - X2[m,q] # <<<<<<<<<<<<<< + * grad[q] += tmp[n, m] * dist * dist */ - __pyx_t_12 = __pyx_v_n; - __pyx_t_13 = __pyx_v_m; - __pyx_t_14 = __pyx_v_q; - *((double *) ( /* dim=0 */ (__pyx_v_grad.data + __pyx_t_14 * __pyx_v_grad.strides[0]) )) += (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_tmp.data + __pyx_t_12 * __pyx_v_tmp.strides[0]) ) + __pyx_t_13 * __pyx_v_tmp.strides[1]) ))) * __pyx_v_dist) * __pyx_v_dist); + __pyx_t_8 = __pyx_v_n; + __pyx_t_9 = __pyx_v_q; + __pyx_t_10 = __pyx_v_m; + __pyx_t_11 = __pyx_v_q; + __pyx_v_dist = ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X.data + __pyx_t_8 * __pyx_v_X.strides[0]) ) + __pyx_t_9 * __pyx_v_X.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X2.data + __pyx_t_10 * __pyx_v_X2.strides[0]) ) + __pyx_t_11 * __pyx_v_X2.strides[1]) )))); + + /* "GPy/kern/_src/stationary_cython.pyx":60 + * for m in range(M): + * dist = X[n,q] - X2[m,q] + * grad[q] += tmp[n, m] * dist * dist # <<<<<<<<<<<<<< + */ + __pyx_t_12 = __pyx_v_n; + __pyx_t_13 = __pyx_v_m; + __pyx_t_14 = __pyx_v_q; + *((double *) ( /* dim=0 */ (__pyx_v_grad.data + __pyx_t_14 * __pyx_v_grad.strides[0]) )) += (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_tmp.data + __pyx_t_12 * __pyx_v_tmp.strides[0]) ) + __pyx_t_13 * __pyx_v_tmp.strides[1]) ))) * __pyx_v_dist) * __pyx_v_dist); + } + } + } + } + + /* "GPy/kern/_src/stationary_cython.pyx":54 + * cdef int q, n, m + * cdef double gradq, dist + * with nogil: # <<<<<<<<<<<<<< + * for q in range(Q): + * grad[q] = 0.0 + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; } - } } - /* "GPy/kern/_src/stationary_cython.pyx":49 - * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. + /* "GPy/kern/_src/stationary_cython.pyx":51 + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. * * def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): # <<<<<<<<<<<<<< * cdef int q, n, m @@ -2919,7 +2949,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_6lengthscale_grad return __pyx_r; } -/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 +/* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":197 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -2969,7 +2999,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GIVEREF(__pyx_v_info->obj); } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":200 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 * # of flags * * if info == NULL: return # <<<<<<<<<<<<<< @@ -2982,7 +3012,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P goto __pyx_L0; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 * * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 # <<<<<<<<<<<<<< @@ -2991,7 +3021,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_endian_detector = 1; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":204 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":207 * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< @@ -3000,7 +3030,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 * cdef bint little_endian = ((&endian_detector)[0] != 0) * * ndim = PyArray_NDIM(self) # <<<<<<<<<<<<<< @@ -3009,7 +3039,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_ndim = PyArray_NDIM(__pyx_v_self); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":208 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 * ndim = PyArray_NDIM(self) * * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -3019,7 +3049,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (((sizeof(npy_intp)) != (sizeof(Py_ssize_t))) != 0); if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":212 * * if sizeof(npy_intp) != sizeof(Py_ssize_t): * copy_shape = 1 # <<<<<<<<<<<<<< @@ -3027,22 +3057,30 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P * copy_shape = 0 */ __pyx_v_copy_shape = 1; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 + * ndim = PyArray_NDIM(self) + * + * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< + * copy_shape = 1 + * else: + */ goto __pyx_L4; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 * copy_shape = 1 * else: * copy_shape = 0 # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) */ + /*else*/ { __pyx_v_copy_shape = 0; } __pyx_L4:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":213 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 * copy_shape = 0 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -3051,14 +3089,12 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_C_CONTIGUOUS) == PyBUF_C_CONTIGUOUS) != 0); if (__pyx_t_2) { - goto __pyx_L7_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L6_bool_binop_done; } - __pyx_L7_next_and:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -3068,23 +3104,39 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_2 = ((!(PyArray_CHKFLAGS(__pyx_v_self, NPY_C_CONTIGUOUS) != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L6_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 + * copy_shape = 0 + * + * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): + * raise ValueError(u"ndarray is not C contiguous") + */ if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 + * copy_shape = 0 + * + * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): + * raise ValueError(u"ndarray is not C contiguous") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 * raise ValueError(u"ndarray is not C contiguous") * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -3093,14 +3145,12 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS) != 0); if (__pyx_t_2) { - goto __pyx_L10_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L9_bool_binop_done; } - __pyx_L10_next_and:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -3110,23 +3160,39 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_2 = ((!(PyArray_CHKFLAGS(__pyx_v_self, NPY_F_CONTIGUOUS) != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L9_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + * raise ValueError(u"ndarray is not C contiguous") + * + * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): + * raise ValueError(u"ndarray is not Fortran contiguous") + */ if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< * * info.buf = PyArray_DATA(self) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + * raise ValueError(u"ndarray is not C contiguous") + * + * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): + * raise ValueError(u"ndarray is not Fortran contiguous") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":224 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -3135,7 +3201,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->buf = PyArray_DATA(__pyx_v_self); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":225 * * info.buf = PyArray_DATA(self) * info.ndim = ndim # <<<<<<<<<<<<<< @@ -3144,7 +3210,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->ndim = __pyx_v_ndim; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":223 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 * info.buf = PyArray_DATA(self) * info.ndim = ndim * if copy_shape: # <<<<<<<<<<<<<< @@ -3154,7 +3220,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (__pyx_v_copy_shape != 0); if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 * # Allocate new buffer for strides and shape info. * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) # <<<<<<<<<<<<<< @@ -3163,7 +3229,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * ((size_t)__pyx_v_ndim)) * 2))); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":227 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim # <<<<<<<<<<<<<< @@ -3172,7 +3238,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":228 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":231 * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -3183,7 +3249,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -3192,7 +3258,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -3201,20 +3267,28 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->shape[__pyx_v_i]) = (PyArray_DIMS(__pyx_v_self)[__pyx_v_i]); } + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + * info.buf = PyArray_DATA(self) + * info.ndim = ndim + * if copy_shape: # <<<<<<<<<<<<<< + * # Allocate new buffer for strides and shape info. + * # This is allocated as one block, strides first. + */ goto __pyx_L11; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL */ + /*else*/ { __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self)); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -3225,7 +3299,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L11:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":237 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -3234,7 +3308,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->suboffsets = NULL; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":238 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -3243,7 +3317,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -3252,28 +3326,28 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->readonly = (!(PyArray_ISWRITEABLE(__pyx_v_self) != 0)); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":242 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< * cdef dtype descr = self.descr - * cdef list stack + * cdef int offset */ __pyx_v_f = NULL; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":243 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< - * cdef list stack * cdef int offset + * */ __pyx_t_3 = ((PyObject *)__pyx_v_self->descr); __Pyx_INCREF(__pyx_t_3); __pyx_v_descr = ((PyArray_Descr *)__pyx_t_3); __pyx_t_3 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -3282,7 +3356,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -3291,18 +3365,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_2) { - goto __pyx_L16_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L15_bool_binop_done; } - __pyx_L16_next_and:; __pyx_t_2 = ((!(__pyx_v_copy_shape != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L15_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":250 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -3314,17 +3386,25 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GOTREF(__pyx_v_info->obj); __Pyx_DECREF(__pyx_v_info->obj); __pyx_v_info->obj = Py_None; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + * cdef bint hasfields = PyDataType_HASFIELDS(descr) + * + * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< + * # do not call releasebuffer + * info.obj = None + */ goto __pyx_L14; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< * * if not hasfields: */ + /*else*/ { __Pyx_INCREF(((PyObject *)__pyx_v_self)); __Pyx_GIVEREF(((PyObject *)__pyx_v_self)); __Pyx_GOTREF(__pyx_v_info->obj); @@ -3333,7 +3413,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L14:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -3343,7 +3423,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -3353,7 +3433,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_4 = __pyx_v_descr->type_num; __pyx_v_t = __pyx_t_4; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -3364,19 +3444,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P if (!__pyx_t_2) { goto __pyx_L20_next_or; } else { - goto __pyx_L21_next_and; } - __pyx_L21_next_and:; __pyx_t_2 = (__pyx_v_little_endian != 0); if (!__pyx_t_2) { - goto __pyx_L20_next_or; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } __pyx_L20_next_or:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -3385,52 +3462,58 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((__pyx_v_descr->byteorder == '<') != 0); if (__pyx_t_2) { - goto __pyx_L22_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } - __pyx_L22_next_and:; __pyx_t_2 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L19_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + * if not hasfields: + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (descr.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ if (__pyx_t_1) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + * if not hasfields: + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (descr.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 - * elif t == NPY_CDOUBLE: f = "Zd" - * elif t == NPY_CLONGDOUBLE: f = "Zg" - * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< - * else: - * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) - */ - switch (__pyx_v_t) { - - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" */ + switch (__pyx_v_t) { case NPY_BYTE: __pyx_v_f = __pyx_k_b; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -3441,7 +3524,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_B; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -3452,7 +3535,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_h; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -3463,7 +3546,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_H; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -3474,7 +3557,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_i; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -3485,7 +3568,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_I; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -3496,7 +3579,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_l; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -3507,7 +3590,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_L; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -3518,7 +3601,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_q; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -3529,7 +3612,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Q; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -3540,7 +3623,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_f; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -3551,7 +3634,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_d; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -3562,7 +3645,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_g; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -3573,7 +3656,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zf; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -3584,7 +3667,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zd; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":275 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -3595,7 +3678,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zg; break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -3607,33 +3690,33 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P break; default: - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 * elif t == NPY_OBJECT: f = "O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< * info.format = f * return */ - __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_6 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_6); __Pyx_GIVEREF(__pyx_t_6); + PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_Raise(__pyx_t_6, 0, 0, 0); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} break; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":279 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f # <<<<<<<<<<<<<< @@ -3642,7 +3725,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->format = __pyx_v_f; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f * return # <<<<<<<<<<<<<< @@ -3651,19 +3734,27 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_r = 0; goto __pyx_L0; - } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + * info.obj = self + * + * if not hasfields: # <<<<<<<<<<<<<< + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or + */ + } + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":282 * return * else: * info.format = stdlib.malloc(_buffer_format_string_len) # <<<<<<<<<<<<<< * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 */ + /*else*/ { __pyx_v_info->format = ((char *)malloc(255)); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 * else: * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment # <<<<<<<<<<<<<< @@ -3672,7 +3763,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->format[0]) = '^'; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":282 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":284 * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 # <<<<<<<<<<<<<< @@ -3681,17 +3772,17 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_offset = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":285 * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 * f = _util_dtypestring(descr, info.format + 1, # <<<<<<<<<<<<<< * info.format + _buffer_format_string_len, * &offset) */ - __pyx_t_7 = __pyx_f_5numpy__util_dtypestring(__pyx_v_descr, (__pyx_v_info->format + 1), (__pyx_v_info->format + 255), (&__pyx_v_offset)); 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if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + if (unlikely(__pyx_v_descr->fields == Py_None)) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not subscriptable"); + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_t_3 = __Pyx_PyDict_GetItem(__pyx_v_descr->fields, __pyx_v_childname); if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; __Pyx_GOTREF(__pyx_t_3); if (!(likely(PyTuple_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "tuple", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_XDECREF_SET(__pyx_v_fields, ((PyObject*)__pyx_t_3)); __pyx_t_3 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 * for childname in descr.names: * fields = descr.fields[childname] * child, new_offset = fields # <<<<<<<<<<<<<< @@ -4187,7 +4295,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_new_offset, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 * child, new_offset = fields * * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< @@ -4204,7 +4312,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = ((((__pyx_v_end - __pyx_v_f) - ((int)__pyx_t_5)) < 15) != 0); if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< @@ -4216,9 +4324,17 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + * child, new_offset = fields + * + * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") * * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -4229,19 +4345,16 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx if (!__pyx_t_7) { goto __pyx_L8_next_or; } else { - goto __pyx_L9_next_and; } - __pyx_L9_next_and:; __pyx_t_7 = (__pyx_v_little_endian != 0); if (!__pyx_t_7) { - goto __pyx_L8_next_or; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L7_bool_binop_done; } __pyx_L8_next_or:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 * * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -4250,18 +4363,24 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_t_7 = ((__pyx_v_child->byteorder == '<') != 0); if (__pyx_t_7) { - goto __pyx_L10_next_and; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L7_bool_binop_done; } - __pyx_L10_next_and:; __pyx_t_7 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_6 = __pyx_t_7; __pyx_L7_bool_binop_done:; + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (child.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -4273,9 +4392,17 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (child.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 * * # Output padding bytes * while offset[0] < new_offset: # <<<<<<<<<<<<<< @@ -4291,7 +4418,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; if (!__pyx_t_6) break; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 * # Output padding bytes * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte # <<<<<<<<<<<<<< @@ -4300,7 +4427,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ (__pyx_v_f[0]) = 120; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte * f += 1 # <<<<<<<<<<<<<< @@ -4309,7 +4436,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_v_f = (__pyx_v_f + 1); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 * f[0] = 120 # "x"; pad byte * f += 1 * offset[0] += 1 # <<<<<<<<<<<<<< @@ -4320,7 +4447,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + 1); } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 * offset[0] += 1 * * offset[0] += child.itemsize # <<<<<<<<<<<<<< @@ -4330,7 +4457,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_8 = 0; (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + __pyx_v_child->elsize); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 * offset[0] += child.itemsize * * if not PyDataType_HASFIELDS(child): # <<<<<<<<<<<<<< @@ -4340,7 +4467,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = ((!(PyDataType_HASFIELDS(__pyx_v_child) != 0)) != 0); if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":821 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":821 * * if not PyDataType_HASFIELDS(child): * t = child.type_num # <<<<<<<<<<<<<< @@ -4352,7 +4479,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_t, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 * if not PyDataType_HASFIELDS(child): * t = child.type_num * if end - f < 5: # <<<<<<<<<<<<<< @@ -4362,7 +4489,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = (((__pyx_v_end - __pyx_v_f) < 5) != 0); if (__pyx_t_6) { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 * t = child.type_num * if end - f < 5: * raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<< @@ -4374,16 +4501,24 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_4, 0, 0, 0); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 + * if not PyDataType_HASFIELDS(child): + * t = child.type_num + * if end - f < 5: # <<<<<<<<<<<<<< + * raise RuntimeError(u"Format string allocated too short.") + * + */ } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 * * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" # <<<<<<<<<<<<<< * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" */ - __pyx_t_4 = PyInt_FromLong(NPY_BYTE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_BYTE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4394,14 +4529,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" # <<<<<<<<<<<<<< * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" */ - __pyx_t_3 = PyInt_FromLong(NPY_UBYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_UBYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -4412,14 +4547,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" # <<<<<<<<<<<<<< * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" */ - __pyx_t_4 = PyInt_FromLong(NPY_SHORT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_SHORT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4430,14 +4565,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" # <<<<<<<<<<<<<< * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" */ - __pyx_t_3 = PyInt_FromLong(NPY_USHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_USHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -4448,14 +4583,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" # <<<<<<<<<<<<<< * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" */ - __pyx_t_4 = PyInt_FromLong(NPY_INT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_INT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4466,14 +4601,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" # <<<<<<<<<<<<<< * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" */ - __pyx_t_3 = PyInt_FromLong(NPY_UINT); 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if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_LONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4502,14 +4637,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" # <<<<<<<<<<<<<< * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" */ - __pyx_t_3 = PyInt_FromLong(NPY_ULONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_ULONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -4520,14 +4655,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" # <<<<<<<<<<<<<< * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" */ - __pyx_t_4 = PyInt_FromLong(NPY_LONGLONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_LONGLONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4538,14 +4673,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" # <<<<<<<<<<<<<< * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" */ - __pyx_t_3 = PyInt_FromLong(NPY_ULONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_ULONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -4556,14 +4691,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" # <<<<<<<<<<<<<< * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" */ - __pyx_t_4 = PyInt_FromLong(NPY_FLOAT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_FLOAT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4574,14 +4709,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":837 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":837 * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" # <<<<<<<<<<<<<< * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf */ - __pyx_t_3 = PyInt_FromLong(NPY_DOUBLE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_DOUBLE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -4592,14 +4727,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":838 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":838 * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" # <<<<<<<<<<<<<< * elif t == NPY_CFLOAT: f[0] = 90; 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f[1] = 100; f += 1 # Zd * elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg * elif t == NPY_OBJECT: f[0] = 79 #"O" # <<<<<<<<<<<<<< * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) */ - __pyx_t_4 = PyInt_FromLong(NPY_OBJECT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 842; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_OBJECT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 842; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 842; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -4687,21 +4822,21 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx (__pyx_v_f[0]) = 79; goto __pyx_L15; } - /*else*/ { - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":844 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":844 * elif t == NPY_OBJECT: f[0] = 79 #"O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< * f += 1 * else: */ + /*else*/ { __pyx_t_3 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); + PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __pyx_t_3 = 0; __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); @@ -4712,7 +4847,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } __pyx_L15:; - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":845 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":845 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * f += 1 # <<<<<<<<<<<<<< @@ -4720,23 +4855,31 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx * # Cython ignores struct boundary information ("T{...}"), */ __pyx_v_f = (__pyx_v_f + 1); 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} -/* "View.MemoryView":116 +/* "View.MemoryView":118 * cdef bint dtype_is_object * * def __cinit__(array self, tuple shape, Py_ssize_t itemsize, format not None, # <<<<<<<<<<<<<< @@ -4979,12 +5138,12 @@ static int __pyx_array___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, P case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_itemsize)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 3, 5, 1); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 116; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 3, 5, 1); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 118; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_format)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 3, 5, 2); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 116; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 3, 5, 2); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 118; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (kw_args > 0) { @@ -4998,7 +5157,7 @@ static int __pyx_array___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, P } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__cinit__") < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 116; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__cinit__") < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 118; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else { switch (PyTuple_GET_SIZE(__pyx_args)) { @@ -5012,14 +5171,14 @@ static int __pyx_array___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, P } } __pyx_v_shape = ((PyObject*)values[0]); - __pyx_v_itemsize = __Pyx_PyIndex_AsSsize_t(values[1]); if (unlikely((__pyx_v_itemsize == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 116; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_itemsize = __Pyx_PyIndex_AsSsize_t(values[1]); if (unlikely((__pyx_v_itemsize == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 118; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_v_format = values[2]; __pyx_v_mode = values[3]; if (values[4]) { - __pyx_v_allocate_buffer = __Pyx_PyObject_IsTrue(values[4]); if (unlikely((__pyx_v_allocate_buffer == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 117; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_allocate_buffer = __Pyx_PyObject_IsTrue(values[4]); if (unlikely((__pyx_v_allocate_buffer == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 119; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } else { - /* "View.MemoryView":117 + /* "View.MemoryView":119 * * def __cinit__(array self, tuple shape, Py_ssize_t itemsize, format not None, * mode="c", bint allocate_buffer=True): # <<<<<<<<<<<<<< @@ -5031,19 +5190,19 @@ static int __pyx_array___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, P } goto __pyx_L4_argument_unpacking_done; 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if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 241; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyObject_Call(((PyObject *)__pyx_array_type), __pyx_t_2, __pyx_t_3); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __pyx_v_result = ((struct __pyx_array_obj *)__pyx_t_5); __pyx_t_5 = 0; - /* "View.MemoryView":243 + /* "View.MemoryView":245 * result = array(shape, itemsize, format, mode.decode('ASCII'), * allocate_buffer=False) * result.data = buf # <<<<<<<<<<<<<< @@ -6410,7 +6691,7 @@ static struct __pyx_array_obj *__pyx_array_new(PyObject *__pyx_v_shape, Py_ssize } __pyx_L3:; - /* "View.MemoryView":245 + /* "View.MemoryView":247 * result.data = buf * * return result # <<<<<<<<<<<<<< @@ -6422,7 +6703,7 @@ static struct __pyx_array_obj *__pyx_array_new(PyObject *__pyx_v_shape, Py_ssize __pyx_r = __pyx_v_result; goto __pyx_L0; - /* "View.MemoryView":234 + /* "View.MemoryView":236 * * @cname("__pyx_array_new") * cdef array array_cwrapper(tuple shape, Py_ssize_t itemsize, char *format, # <<<<<<<<<<<<<< @@ -6445,7 +6726,7 @@ static struct __pyx_array_obj *__pyx_array_new(PyObject *__pyx_v_shape, Py_ssize return __pyx_r; } -/* "View.MemoryView":271 +/* "View.MemoryView":273 * cdef class Enum(object): * cdef object name * def __init__(self, name): # <<<<<<<<<<<<<< @@ -6481,7 +6762,7 @@ static int __pyx_MemviewEnum___init__(PyObject *__pyx_v_self, PyObject *__pyx_ar else goto __pyx_L5_argtuple_error; } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 273; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 1) { goto __pyx_L5_argtuple_error; @@ -6492,25 +6773,25 @@ static int __pyx_MemviewEnum___init__(PyObject *__pyx_v_self, PyObject *__pyx_ar } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("__init__", 1, 1, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 1, 1, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 273; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("View.MemoryView.Enum.__init__", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return -1; __pyx_L4_argument_unpacking_done:; - __pyx_r = __pyx_MemviewEnum_MemoryView_4Enum___init__(((struct __pyx_MemviewEnum_obj *)__pyx_v_self), __pyx_v_name); + __pyx_r = __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(((struct __pyx_MemviewEnum_obj *)__pyx_v_self), __pyx_v_name); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name) { +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name) { int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__init__", 0); - /* "View.MemoryView":272 + /* "View.MemoryView":274 * cdef object name * def __init__(self, name): * self.name = name # <<<<<<<<<<<<<< @@ -6523,7 +6804,7 @@ static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_ __Pyx_DECREF(__pyx_v_self->name); __pyx_v_self->name = __pyx_v_name; - /* "View.MemoryView":271 + /* "View.MemoryView":273 * cdef class Enum(object): * cdef object name * def __init__(self, name): # <<<<<<<<<<<<<< @@ -6537,7 +6818,7 @@ static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_ return __pyx_r; } -/* "View.MemoryView":273 +/* "View.MemoryView":275 * def __init__(self, name): * self.name = name * def __repr__(self): # <<<<<<<<<<<<<< @@ -6551,19 +6832,19 @@ static PyObject *__pyx_MemviewEnum___repr__(PyObject *__pyx_v_self) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__repr__ (wrapper)", 0); - __pyx_r = __pyx_MemviewEnum_MemoryView_4Enum_2__repr__(((struct __pyx_MemviewEnum_obj *)__pyx_v_self)); + __pyx_r = __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(((struct __pyx_MemviewEnum_obj *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self) { +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__repr__", 0); - /* "View.MemoryView":274 + /* "View.MemoryView":276 * self.name = name * def __repr__(self): * return self.name # <<<<<<<<<<<<<< @@ -6575,7 +6856,7 @@ static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_Memvi __pyx_r = __pyx_v_self->name; goto __pyx_L0; - /* "View.MemoryView":273 + /* "View.MemoryView":275 * def __init__(self, name): * self.name = name * def __repr__(self): # <<<<<<<<<<<<<< @@ -6590,7 +6871,7 @@ static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_Memvi return __pyx_r; } -/* "View.MemoryView":288 +/* "View.MemoryView":290 * * @cname('__pyx_align_pointer') * cdef void *align_pointer(void *memory, size_t alignment) nogil: # <<<<<<<<<<<<<< @@ -6604,7 +6885,7 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) void *__pyx_r; int __pyx_t_1; - /* "View.MemoryView":290 + /* "View.MemoryView":292 * cdef void *align_pointer(void *memory, size_t alignment) nogil: * "Align pointer memory on a given boundary" * cdef Py_intptr_t aligned_p = memory # <<<<<<<<<<<<<< @@ -6613,7 +6894,7 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) */ __pyx_v_aligned_p = ((Py_intptr_t)__pyx_v_memory); - /* "View.MemoryView":294 + /* "View.MemoryView":296 * * with cython.cdivision(True): * offset = aligned_p % alignment # <<<<<<<<<<<<<< @@ -6622,7 +6903,7 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) */ __pyx_v_offset = (__pyx_v_aligned_p % __pyx_v_alignment); - /* "View.MemoryView":296 + /* "View.MemoryView":298 * offset = aligned_p % alignment * * if offset > 0: # <<<<<<<<<<<<<< @@ -6632,7 +6913,7 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) __pyx_t_1 = ((__pyx_v_offset > 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":297 + /* "View.MemoryView":299 * * if offset > 0: * aligned_p += alignment - offset # <<<<<<<<<<<<<< @@ -6640,11 +6921,17 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) * return aligned_p */ __pyx_v_aligned_p = (__pyx_v_aligned_p + (__pyx_v_alignment - __pyx_v_offset)); - goto __pyx_L3; - } - __pyx_L3:; - /* "View.MemoryView":299 + /* "View.MemoryView":298 + * offset = aligned_p % alignment + * + * if offset > 0: # <<<<<<<<<<<<<< + * aligned_p += alignment - offset + * + */ + } + + /* "View.MemoryView":301 * aligned_p += alignment - offset * * return aligned_p # <<<<<<<<<<<<<< @@ -6654,7 +6941,7 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) __pyx_r = ((void *)__pyx_v_aligned_p); goto __pyx_L0; - /* "View.MemoryView":288 + /* "View.MemoryView":290 * * @cname('__pyx_align_pointer') * cdef void *align_pointer(void *memory, size_t alignment) nogil: # <<<<<<<<<<<<<< @@ -6667,7 +6954,7 @@ static void *__pyx_align_pointer(void *__pyx_v_memory, size_t __pyx_v_alignment) return __pyx_r; } -/* "View.MemoryView":317 +/* "View.MemoryView":319 * cdef __Pyx_TypeInfo *typeinfo * * def __cinit__(memoryview self, object obj, int flags, bint dtype_is_object=False): # <<<<<<<<<<<<<< @@ -6708,7 +6995,7 @@ static int __pyx_memoryview___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_ar case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_flags)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 2, 3, 1); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 317; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 2, 3, 1); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 319; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (kw_args > 0) { @@ -6717,7 +7004,7 @@ static int __pyx_memoryview___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_ar } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__cinit__") < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 317; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__cinit__") < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 319; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else { switch (PyTuple_GET_SIZE(__pyx_args)) { @@ -6729,29 +7016,29 @@ static int __pyx_memoryview___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_ar } } __pyx_v_obj = values[0]; - __pyx_v_flags = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_flags == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 317; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_flags = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_flags == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 319; __pyx_clineno = __LINE__; goto __pyx_L3_error;} if (values[2]) { - __pyx_v_dtype_is_object = __Pyx_PyObject_IsTrue(values[2]); if (unlikely((__pyx_v_dtype_is_object == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 317; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_dtype_is_object = __Pyx_PyObject_IsTrue(values[2]); if (unlikely((__pyx_v_dtype_is_object == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 319; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } else { __pyx_v_dtype_is_object = ((int)0); } } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 2, 3, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 317; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__cinit__", 0, 2, 3, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 319; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("View.MemoryView.memoryview.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return -1; __pyx_L4_argument_unpacking_done:; - __pyx_r = __pyx_memoryview_MemoryView_10memoryview___cinit__(((struct __pyx_memoryview_obj *)__pyx_v_self), __pyx_v_obj, __pyx_v_flags, __pyx_v_dtype_is_object); + __pyx_r = __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(((struct __pyx_memoryview_obj *)__pyx_v_self), __pyx_v_obj, __pyx_v_flags, __pyx_v_dtype_is_object); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object) { +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object) { int __pyx_r; __Pyx_RefNannyDeclarations int __pyx_t_1; @@ -6765,7 +7052,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__cinit__", 0); - /* "View.MemoryView":318 + /* "View.MemoryView":320 * * def __cinit__(memoryview self, object obj, int flags, bint dtype_is_object=False): * self.obj = obj # <<<<<<<<<<<<<< @@ -6778,7 +7065,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor __Pyx_DECREF(__pyx_v_self->obj); __pyx_v_self->obj = __pyx_v_obj; - /* "View.MemoryView":319 + /* "View.MemoryView":321 * def __cinit__(memoryview self, object obj, int flags, bint dtype_is_object=False): * self.obj = obj * self.flags = flags # <<<<<<<<<<<<<< @@ -6787,38 +7074,36 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor */ __pyx_v_self->flags = __pyx_v_flags; - /* "View.MemoryView":320 + /* "View.MemoryView":322 * self.obj = obj * self.flags = flags * if type(self) is memoryview or obj is not None: # <<<<<<<<<<<<<< * __Pyx_GetBuffer(obj, &self.view, flags) * if self.view.obj == NULL: */ - __pyx_t_2 = (((PyObject *)Py_TYPE(((PyObject *)__pyx_v_self))) == ((PyObject *)((PyObject *)__pyx_memoryview_type))); + __pyx_t_2 = (((PyObject *)Py_TYPE(((PyObject *)__pyx_v_self))) == ((PyObject *)__pyx_memoryview_type)); __pyx_t_3 = (__pyx_t_2 != 0); if (!__pyx_t_3) { - goto __pyx_L5_next_or; } else { __pyx_t_1 = __pyx_t_3; goto __pyx_L4_bool_binop_done; } - __pyx_L5_next_or:; __pyx_t_3 = (__pyx_v_obj != Py_None); __pyx_t_2 = (__pyx_t_3 != 0); __pyx_t_1 = __pyx_t_2; __pyx_L4_bool_binop_done:; if (__pyx_t_1) { - /* "View.MemoryView":321 + /* "View.MemoryView":323 * self.flags = flags * if type(self) is memoryview or obj is not None: * __Pyx_GetBuffer(obj, &self.view, flags) # <<<<<<<<<<<<<< * if self.view.obj == NULL: * (<__pyx_buffer *> &self.view).obj = Py_None */ - __pyx_t_4 = __Pyx_GetBuffer(__pyx_v_obj, (&__pyx_v_self->view), __pyx_v_flags); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 321; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_GetBuffer(__pyx_v_obj, (&__pyx_v_self->view), __pyx_v_flags); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 323; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":322 + /* "View.MemoryView":324 * if type(self) is memoryview or obj is not None: * __Pyx_GetBuffer(obj, &self.view, flags) * if self.view.obj == NULL: # <<<<<<<<<<<<<< @@ -6828,7 +7113,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor __pyx_t_1 = ((((PyObject *)__pyx_v_self->view.obj) == NULL) != 0); if (__pyx_t_1) { - /* "View.MemoryView":323 + /* "View.MemoryView":325 * __Pyx_GetBuffer(obj, &self.view, flags) * if self.view.obj == NULL: * (<__pyx_buffer *> &self.view).obj = Py_None # <<<<<<<<<<<<<< @@ -6837,7 +7122,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor */ ((Py_buffer *)(&__pyx_v_self->view))->obj = Py_None; - /* "View.MemoryView":324 + /* "View.MemoryView":326 * if self.view.obj == NULL: * (<__pyx_buffer *> &self.view).obj = Py_None * Py_INCREF(Py_None) # <<<<<<<<<<<<<< @@ -6845,14 +7130,26 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor * self.lock = PyThread_allocate_lock() */ Py_INCREF(Py_None); - goto __pyx_L6; - } - __pyx_L6:; - goto __pyx_L3; - } - __pyx_L3:; - /* "View.MemoryView":326 + /* "View.MemoryView":324 + * if type(self) is memoryview or obj is not None: + * __Pyx_GetBuffer(obj, &self.view, flags) + * if self.view.obj == NULL: # <<<<<<<<<<<<<< + * (<__pyx_buffer *> &self.view).obj = Py_None + * Py_INCREF(Py_None) + */ + } + + /* "View.MemoryView":322 + * self.obj = obj + * self.flags = flags + * if type(self) is memoryview or obj is not None: # <<<<<<<<<<<<<< + * __Pyx_GetBuffer(obj, &self.view, flags) + * if self.view.obj == NULL: + */ + } + + /* "View.MemoryView":328 * Py_INCREF(Py_None) * * self.lock = PyThread_allocate_lock() # <<<<<<<<<<<<<< @@ -6861,7 +7158,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor */ __pyx_v_self->lock = PyThread_allocate_lock(); 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if (__pyx_t_1) { - /* "View.MemoryView":331 + /* "View.MemoryView":333 * * if flags & PyBUF_FORMAT: * self.dtype_is_object = self.view.format == b'O' # <<<<<<<<<<<<<< * else: * self.dtype_is_object = dtype_is_object */ - __pyx_t_5 = __Pyx_PyBytes_FromString(__pyx_v_self->view.format); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 331; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyBytes_FromString(__pyx_v_self->view.format); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 333; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_6 = PyObject_RichCompare(__pyx_t_5, __pyx_n_b_O, Py_EQ); __Pyx_XGOTREF(__pyx_t_6); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 331; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_RichCompare(__pyx_t_5, __pyx_n_b_O, Py_EQ); __Pyx_XGOTREF(__pyx_t_6); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 333; 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} __pyx_L8:; - /* "View.MemoryView":335 + /* "View.MemoryView":337 * self.dtype_is_object = dtype_is_object * * self.acquisition_count_aligned_p = <__pyx_atomic_int *> align_pointer( # <<<<<<<<<<<<<< @@ -6929,7 +7242,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor */ __pyx_v_self->acquisition_count_aligned_p = ((__pyx_atomic_int *)__pyx_align_pointer(((void *)(&(__pyx_v_self->acquisition_count[0]))), (sizeof(__pyx_atomic_int)))); - /* "View.MemoryView":337 + /* "View.MemoryView":339 * self.acquisition_count_aligned_p = <__pyx_atomic_int *> align_pointer( * &self.acquisition_count[0], sizeof(__pyx_atomic_int)) * self.typeinfo = NULL # <<<<<<<<<<<<<< @@ -6938,7 +7251,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor */ __pyx_v_self->typeinfo = NULL; - /* "View.MemoryView":317 + /* "View.MemoryView":319 * cdef __Pyx_TypeInfo *typeinfo * * def __cinit__(memoryview self, object obj, int flags, bint dtype_is_object=False): # <<<<<<<<<<<<<< @@ -6959,7 +7272,7 @@ static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memor return __pyx_r; 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__pyx_t_3++; if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 350; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 352; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_5); #endif } } else { @@ -7115,7 +7442,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py PyObject* exc_type = PyErr_Occurred(); if (exc_type) { if (likely(exc_type == PyExc_StopIteration || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) PyErr_Clear(); - else {__pyx_filename = __pyx_f[2]; __pyx_lineno = 350; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + else {__pyx_filename = __pyx_f[2]; __pyx_lineno = 352; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } break; } @@ -7126,18 +7453,18 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py __pyx_v_dim = __pyx_t_1; __pyx_t_1 = (__pyx_t_1 + 1); - /* "View.MemoryView":351 + /* "View.MemoryView":353 * * for dim, idx in enumerate(index): * itemp = pybuffer_index(&self.view, itemp, idx, dim) # <<<<<<<<<<<<<< * * return itemp */ - __pyx_t_6 = __Pyx_PyIndex_AsSsize_t(__pyx_v_idx); if (unlikely((__pyx_t_6 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 351; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_t_7 = __pyx_pybuffer_index((&__pyx_v_self->view), __pyx_v_itemp, __pyx_t_6, __pyx_v_dim); if (unlikely(__pyx_t_7 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 351; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_PyIndex_AsSsize_t(__pyx_v_idx); if (unlikely((__pyx_t_6 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 353; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __pyx_pybuffer_index((&__pyx_v_self->view), __pyx_v_itemp, __pyx_t_6, __pyx_v_dim); if (unlikely(__pyx_t_7 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 353; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_itemp = __pyx_t_7; - /* "View.MemoryView":350 + /* "View.MemoryView":352 * cdef char *itemp = self.view.buf * * for dim, idx in enumerate(index): # <<<<<<<<<<<<<< @@ -7147,7 +7474,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py } __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "View.MemoryView":353 + /* "View.MemoryView":355 * itemp = pybuffer_index(&self.view, itemp, idx, dim) * * return itemp # <<<<<<<<<<<<<< @@ -7157,7 +7484,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py __pyx_r = __pyx_v_itemp; goto __pyx_L0; - /* "View.MemoryView":346 + /* "View.MemoryView":348 * PyThread_free_lock(self.lock) * * cdef char *get_item_pointer(memoryview self, object index) except NULL: # <<<<<<<<<<<<<< @@ -7177,7 +7504,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py return __pyx_r; } -/* "View.MemoryView":356 +/* "View.MemoryView":358 * * * def __getitem__(memoryview self, object index): # <<<<<<<<<<<<<< @@ -7191,14 +7518,14 @@ static PyObject *__pyx_memoryview___getitem__(PyObject *__pyx_v_self, PyObject * PyObject *__pyx_r = 0; 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__pyx_lineno = 366; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + /*else*/ { + __pyx_t_6 = ((struct __pyx_vtabstruct_memoryview *)__pyx_v_self->__pyx_vtab)->get_item_pointer(__pyx_v_self, __pyx_v_indices); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 368; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_itemp = __pyx_t_6; - /* "View.MemoryView":367 + /* "View.MemoryView":369 * else: * itemp = self.get_item_pointer(indices) * return self.convert_item_to_object(itemp) # <<<<<<<<<<<<<< @@ -7324,14 +7667,14 @@ static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __ * def __setitem__(memoryview self, object index, object value): */ __Pyx_XDECREF(__pyx_r); - __pyx_t_3 = ((struct __pyx_vtabstruct_memoryview *)__pyx_v_self->__pyx_vtab)->convert_item_to_object(__pyx_v_self, __pyx_v_itemp); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 367; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = ((struct __pyx_vtabstruct_memoryview *)__pyx_v_self->__pyx_vtab)->convert_item_to_object(__pyx_v_self, __pyx_v_itemp); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 369; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_r = __pyx_t_3; __pyx_t_3 = 0; goto __pyx_L0; } - /* "View.MemoryView":356 + /* "View.MemoryView":358 * * * def __getitem__(memoryview self, object index): # <<<<<<<<<<<<<< @@ -7354,7 +7697,7 @@ static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __ return __pyx_r; } -/* "View.MemoryView":369 +/* "View.MemoryView":371 * return self.convert_item_to_object(itemp) * * def __setitem__(memoryview self, object index, object value): # <<<<<<<<<<<<<< @@ -7368,14 +7711,14 @@ static int __pyx_memoryview___setitem__(PyObject *__pyx_v_self, PyObject *__pyx_ int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__setitem__ (wrapper)", 0); - __pyx_r = __pyx_memoryview_MemoryView_10memoryview_6__setitem__(((struct __pyx_memoryview_obj *)__pyx_v_self), ((PyObject *)__pyx_v_index), ((PyObject *)__pyx_v_value)); + __pyx_r = __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(((struct __pyx_memoryview_obj *)__pyx_v_self), ((PyObject *)__pyx_v_index), ((PyObject *)__pyx_v_value)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value) { +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value) { PyObject *__pyx_v_have_slices = NULL; PyObject *__pyx_v_obj = NULL; int __pyx_r; @@ -7390,14 +7733,14 @@ static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_me __Pyx_RefNannySetupContext("__setitem__", 0); __Pyx_INCREF(__pyx_v_index); - /* "View.MemoryView":370 + /* "View.MemoryView":372 * * def __setitem__(memoryview self, object index, object value): * have_slices, index = _unellipsify(index, self.view.ndim) # <<<<<<<<<<<<<< * * if have_slices: */ - __pyx_t_1 = _unellipsify(__pyx_v_index, __pyx_v_self->view.ndim); 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if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 384; __pyx_clineno = __LINE__; goto __pyx_L4_error;} + __pyx_t_6 = __Pyx_PyInt_From_int((__pyx_v_self->flags | PyBUF_ANY_CONTIGUOUS)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L4_error;} __Pyx_GOTREF(__pyx_t_6); - /* "View.MemoryView":385 + /* "View.MemoryView":387 * try: * obj = memoryview(obj, self.flags|PyBUF_ANY_CONTIGUOUS, * self.dtype_is_object) # <<<<<<<<<<<<<< * except TypeError: * return None */ - __pyx_t_7 = __Pyx_PyBool_FromLong(__pyx_v_self->dtype_is_object); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 385; __pyx_clineno = __LINE__; goto __pyx_L4_error;} + __pyx_t_7 = __Pyx_PyBool_FromLong(__pyx_v_self->dtype_is_object); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 387; __pyx_clineno = __LINE__; goto __pyx_L4_error;} __Pyx_GOTREF(__pyx_t_7); - /* "View.MemoryView":384 + /* "View.MemoryView":386 * if not isinstance(obj, memoryview): * try: * obj = memoryview(obj, self.flags|PyBUF_ANY_CONTIGUOUS, # <<<<<<<<<<<<<< * self.dtype_is_object) * except TypeError: */ - __pyx_t_8 = PyTuple_New(3); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 384; __pyx_clineno = __LINE__; goto __pyx_L4_error;} + __pyx_t_8 = PyTuple_New(3); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L4_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_INCREF(__pyx_v_obj); - PyTuple_SET_ITEM(__pyx_t_8, 0, __pyx_v_obj); __Pyx_GIVEREF(__pyx_v_obj); - PyTuple_SET_ITEM(__pyx_t_8, 1, __pyx_t_6); + PyTuple_SET_ITEM(__pyx_t_8, 0, __pyx_v_obj); __Pyx_GIVEREF(__pyx_t_6); - PyTuple_SET_ITEM(__pyx_t_8, 2, __pyx_t_7); + PyTuple_SET_ITEM(__pyx_t_8, 1, __pyx_t_6); __Pyx_GIVEREF(__pyx_t_7); + PyTuple_SET_ITEM(__pyx_t_8, 2, __pyx_t_7); __pyx_t_6 = 0; __pyx_t_7 = 0; - __pyx_t_7 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_memoryview_type)), __pyx_t_8, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 384; __pyx_clineno = __LINE__; goto __pyx_L4_error;} + __pyx_t_7 = __Pyx_PyObject_Call(((PyObject *)__pyx_memoryview_type), __pyx_t_8, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L4_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; __Pyx_DECREF_SET(__pyx_v_obj, __pyx_t_7); __pyx_t_7 = 0; + + /* "View.MemoryView":385 + * cdef is_slice(self, obj): + * if not isinstance(obj, memoryview): + * try: # <<<<<<<<<<<<<< + * obj = memoryview(obj, self.flags|PyBUF_ANY_CONTIGUOUS, + * self.dtype_is_object) + */ } __Pyx_XDECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_XDECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -7642,7 +8009,7 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ __Pyx_XDECREF(__pyx_t_8); __pyx_t_8 = 0; __Pyx_XDECREF(__pyx_t_7); __pyx_t_7 = 0; - /* "View.MemoryView":386 + /* "View.MemoryView":388 * obj = memoryview(obj, self.flags|PyBUF_ANY_CONTIGUOUS, * self.dtype_is_object) * except TypeError: # <<<<<<<<<<<<<< @@ -7652,12 +8019,12 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ __pyx_t_9 = PyErr_ExceptionMatches(__pyx_builtin_TypeError); if (__pyx_t_9) { __Pyx_AddTraceback("View.MemoryView.memoryview.is_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); - if (__Pyx_GetException(&__pyx_t_7, &__pyx_t_8, &__pyx_t_6) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L6_except_error;} + if (__Pyx_GetException(&__pyx_t_7, &__pyx_t_8, &__pyx_t_6) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 388; __pyx_clineno = __LINE__; goto __pyx_L6_except_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_GOTREF(__pyx_t_8); __Pyx_GOTREF(__pyx_t_6); - /* "View.MemoryView":387 + /* "View.MemoryView":389 * self.dtype_is_object) * except TypeError: * return None # <<<<<<<<<<<<<< @@ -7674,6 +8041,14 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ } goto __pyx_L6_except_error; __pyx_L6_except_error:; + + /* "View.MemoryView":385 + * cdef is_slice(self, obj): + * if not isinstance(obj, memoryview): + * try: # <<<<<<<<<<<<<< + * obj = memoryview(obj, self.flags|PyBUF_ANY_CONTIGUOUS, + * self.dtype_is_object) + */ __Pyx_XGIVEREF(__pyx_t_3); __Pyx_XGIVEREF(__pyx_t_4); __Pyx_XGIVEREF(__pyx_t_5); @@ -7687,11 +8062,17 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ goto __pyx_L0; __pyx_L11_try_end:; } - goto __pyx_L3; - } - __pyx_L3:; - /* "View.MemoryView":389 + /* "View.MemoryView":384 + * + * cdef is_slice(self, obj): + * if not isinstance(obj, memoryview): # <<<<<<<<<<<<<< + * try: + * obj = memoryview(obj, self.flags|PyBUF_ANY_CONTIGUOUS, + */ + } + + /* "View.MemoryView":391 * return None * * return obj # <<<<<<<<<<<<<< @@ -7703,7 +8084,7 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ __pyx_r = __pyx_v_obj; goto __pyx_L0; - /* "View.MemoryView":381 + /* "View.MemoryView":383 * self.setitem_indexed(index, value) * * cdef is_slice(self, obj): # <<<<<<<<<<<<<< @@ -7725,7 +8106,7 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ return __pyx_r; } -/* "View.MemoryView":391 +/* "View.MemoryView":393 * return obj * * cdef setitem_slice_assignment(self, dst, src): # <<<<<<<<<<<<<< @@ -7747,50 +8128,50 @@ static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryvi int __pyx_clineno = 0; 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__pyx_lineno = 396; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_dst) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_dst, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 398; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":397 + /* "View.MemoryView":399 * memoryview_copy_contents(get_slice_from_memview(src, &src_slice)[0], * get_slice_from_memview(dst, &dst_slice)[0], * src.ndim, dst.ndim, self.dtype_is_object) # <<<<<<<<<<<<<< * * cdef setitem_slice_assign_scalar(self, memoryview dst, value): */ - __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_src, __pyx_n_s_ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 397; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_src, __pyx_n_s_ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 399; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = __Pyx_PyInt_As_int(__pyx_t_1); 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if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 399; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":395 + /* "View.MemoryView":397 * cdef __Pyx_memviewslice src_slice * * memoryview_copy_contents(get_slice_from_memview(src, &src_slice)[0], # <<<<<<<<<<<<<< * get_slice_from_memview(dst, &dst_slice)[0], * src.ndim, dst.ndim, self.dtype_is_object) */ - __pyx_t_4 = __pyx_memoryview_copy_contents((__pyx_memoryview_get_slice_from_memoryview(((struct __pyx_memoryview_obj *)__pyx_v_src), (&__pyx_v_src_slice))[0]), (__pyx_memoryview_get_slice_from_memoryview(((struct __pyx_memoryview_obj *)__pyx_v_dst), (&__pyx_v_dst_slice))[0]), __pyx_t_2, __pyx_t_3, __pyx_v_self->dtype_is_object); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 395; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __pyx_memoryview_copy_contents((__pyx_memoryview_get_slice_from_memoryview(((struct __pyx_memoryview_obj *)__pyx_v_src), (&__pyx_v_src_slice))[0]), (__pyx_memoryview_get_slice_from_memoryview(((struct __pyx_memoryview_obj *)__pyx_v_dst), (&__pyx_v_dst_slice))[0]), __pyx_t_2, __pyx_t_3, __pyx_v_self->dtype_is_object); 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- /* "View.MemoryView":406 + /* "View.MemoryView":408 * cdef __Pyx_memviewslice *dst_slice * cdef __Pyx_memviewslice tmp_slice * dst_slice = get_slice_from_memview(dst, &tmp_slice) # <<<<<<<<<<<<<< @@ -7861,7 +8242,7 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor */ __pyx_v_dst_slice = __pyx_memoryview_get_slice_from_memoryview(__pyx_v_dst, (&__pyx_v_tmp_slice)); - /* "View.MemoryView":408 + /* "View.MemoryView":410 * dst_slice = get_slice_from_memview(dst, &tmp_slice) * * if self.view.itemsize > sizeof(array): # <<<<<<<<<<<<<< @@ -7871,7 +8252,7 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor __pyx_t_1 = ((((size_t)__pyx_v_self->view.itemsize) > (sizeof(__pyx_v_array))) != 0); if (__pyx_t_1) { - /* "View.MemoryView":409 + /* "View.MemoryView":411 * * if self.view.itemsize > sizeof(array): * tmp = PyMem_Malloc(self.view.itemsize) # <<<<<<<<<<<<<< @@ -7880,7 +8261,7 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor */ __pyx_v_tmp = PyMem_Malloc(__pyx_v_self->view.itemsize); - /* "View.MemoryView":410 + /* "View.MemoryView":412 * if self.view.itemsize > sizeof(array): * tmp = PyMem_Malloc(self.view.itemsize) * if tmp == NULL: # <<<<<<<<<<<<<< @@ -7890,17 +8271,25 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor __pyx_t_1 = ((__pyx_v_tmp == NULL) != 0); if (__pyx_t_1) { - /* "View.MemoryView":411 + /* "View.MemoryView":413 * tmp = PyMem_Malloc(self.view.itemsize) * if tmp == NULL: * raise MemoryError # <<<<<<<<<<<<<< * item = tmp * else: */ - PyErr_NoMemory(); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 411; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + PyErr_NoMemory(); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 413; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":412 + * if self.view.itemsize > sizeof(array): + * tmp = PyMem_Malloc(self.view.itemsize) + * if tmp == NULL: # <<<<<<<<<<<<<< + * raise MemoryError + * item = tmp + */ } - /* "View.MemoryView":412 + /* "View.MemoryView":414 * if tmp == NULL: * raise MemoryError * item = tmp # <<<<<<<<<<<<<< @@ -7908,22 +8297,30 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor * item = array */ __pyx_v_item = __pyx_v_tmp; + + /* "View.MemoryView":410 + * dst_slice = get_slice_from_memview(dst, &tmp_slice) + * + * if self.view.itemsize > sizeof(array): # <<<<<<<<<<<<<< + * tmp = PyMem_Malloc(self.view.itemsize) + * if tmp == NULL: + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":414 + /* "View.MemoryView":416 * item = tmp * else: * item = array # <<<<<<<<<<<<<< * * try: */ + /*else*/ { __pyx_v_item = ((void *)__pyx_v_array); } __pyx_L3:; - /* "View.MemoryView":416 + /* "View.MemoryView":418 * item = array * * try: # <<<<<<<<<<<<<< @@ -7932,7 +8329,7 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor */ /*try:*/ { - /* "View.MemoryView":417 + /* "View.MemoryView":419 * * try: * if self.dtype_is_object: # <<<<<<<<<<<<<< @@ -7942,7 +8339,7 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor __pyx_t_1 = (__pyx_v_self->dtype_is_object != 0); if (__pyx_t_1) { - /* "View.MemoryView":418 + /* "View.MemoryView":420 * try: * if self.dtype_is_object: * ( item)[0] = value # <<<<<<<<<<<<<< @@ -7950,24 +8347,32 @@ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memor * self.assign_item_from_object( item, value) */ (((PyObject **)__pyx_v_item)[0]) = ((PyObject *)__pyx_v_value); 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if (unlikely(__pyx_t_1 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 432; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = ((struct __pyx_vtabstruct_memoryview *)__pyx_v_self->__pyx_vtab)->get_item_pointer(__pyx_v_self, __pyx_v_index); if (unlikely(__pyx_t_1 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 434; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_itemp = __pyx_t_1; - /* "View.MemoryView":433 + /* "View.MemoryView":435 * cdef setitem_indexed(self, index, value): * cdef char *itemp = self.get_item_pointer(index) * self.assign_item_from_object(itemp, value) # <<<<<<<<<<<<<< * * cdef convert_item_to_object(self, char *itemp): */ - __pyx_t_2 = ((struct __pyx_vtabstruct_memoryview *)__pyx_v_self->__pyx_vtab)->assign_item_from_object(__pyx_v_self, __pyx_v_itemp, __pyx_v_value); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 433; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = ((struct __pyx_vtabstruct_memoryview *)__pyx_v_self->__pyx_vtab)->assign_item_from_object(__pyx_v_self, __pyx_v_itemp, __pyx_v_value); 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if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 438; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_Import(__pyx_n_s_struct, 0, 0); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 440; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_v_struct = __pyx_t_1; __pyx_t_1 = 0; - /* "View.MemoryView":441 + /* "View.MemoryView":443 * cdef bytes bytesitem * * bytesitem = itemp[:self.view.itemsize] # <<<<<<<<<<<<<< * try: * result = struct.unpack(self.view.format, bytesitem) */ - __pyx_t_1 = __Pyx_PyBytes_FromStringAndSize(__pyx_v_itemp + 0, __pyx_v_self->view.itemsize - 0); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 441; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyBytes_FromStringAndSize(__pyx_v_itemp + 0, __pyx_v_self->view.itemsize - 0); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 443; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_v_bytesitem = ((PyObject*)__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":442 + /* "View.MemoryView":444 * * bytesitem = itemp[:self.view.itemsize] * try: # <<<<<<<<<<<<<< @@ -8197,16 +8608,16 @@ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview __Pyx_XGOTREF(__pyx_t_4); /*try:*/ { - /* "View.MemoryView":443 + /* "View.MemoryView":445 * bytesitem = itemp[:self.view.itemsize] * try: * result = struct.unpack(self.view.format, bytesitem) # <<<<<<<<<<<<<< * except struct.error: * raise ValueError("Unable to convert item to object") */ - __pyx_t_5 = __Pyx_PyObject_GetAttrStr(__pyx_v_struct, __pyx_n_s_unpack); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 443; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_t_5 = __Pyx_PyObject_GetAttrStr(__pyx_v_struct, __pyx_n_s_unpack); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 445; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_6 = __Pyx_PyBytes_FromString(__pyx_v_self->view.format); 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__pyx_t_7 = NULL; } - PyTuple_SET_ITEM(__pyx_t_9, 0+__pyx_t_8, __pyx_t_6); __Pyx_GIVEREF(__pyx_t_6); + PyTuple_SET_ITEM(__pyx_t_9, 0+__pyx_t_8, __pyx_t_6); __Pyx_INCREF(__pyx_v_bytesitem); - PyTuple_SET_ITEM(__pyx_t_9, 1+__pyx_t_8, __pyx_v_bytesitem); __Pyx_GIVEREF(__pyx_v_bytesitem); + PyTuple_SET_ITEM(__pyx_t_9, 1+__pyx_t_8, __pyx_v_bytesitem); __pyx_t_6 = 0; - __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_5, __pyx_t_9, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 443; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_5, __pyx_t_9, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 445; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __pyx_v_result = __pyx_t_1; __pyx_t_1 = 0; - } - /*else:*/ { - /* "View.MemoryView":447 + /* "View.MemoryView":444 + * + * bytesitem = itemp[:self.view.itemsize] + * try: # <<<<<<<<<<<<<< + * result = struct.unpack(self.view.format, bytesitem) + * except struct.error: + */ + } + + /* "View.MemoryView":449 * raise ValueError("Unable to convert item to object") * else: * if len(self.view.format) == 1: # <<<<<<<<<<<<<< * return result[0] * return result */ + /*else:*/ { __pyx_t_10 = strlen(__pyx_v_self->view.format); __pyx_t_11 = ((__pyx_t_10 == 1) != 0); if (__pyx_t_11) { - /* "View.MemoryView":448 + /* "View.MemoryView":450 * else: * if len(self.view.format) == 1: * return result[0] # <<<<<<<<<<<<<< @@ -8259,14 +8678,22 @@ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview * */ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = __Pyx_GetItemInt(__pyx_v_result, 0, long, 1, __Pyx_PyInt_From_long, 0, 0, 0); if (unlikely(__pyx_t_1 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 448; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;}; + __pyx_t_1 = __Pyx_GetItemInt(__pyx_v_result, 0, long, 1, __Pyx_PyInt_From_long, 0, 0, 0); if (unlikely(__pyx_t_1 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 450; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;}; __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L6_except_return; + + /* "View.MemoryView":449 + * raise ValueError("Unable to convert item to object") + * else: + * if len(self.view.format) == 1: # <<<<<<<<<<<<<< + * return result[0] + * return result + */ } - /* "View.MemoryView":449 + /* "View.MemoryView":451 * if len(self.view.format) == 1: * return result[0] * return result # <<<<<<<<<<<<<< @@ -8285,39 +8712,47 @@ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview __Pyx_XDECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_XDECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":444 + /* "View.MemoryView":446 * try: * result = struct.unpack(self.view.format, bytesitem) * except struct.error: # <<<<<<<<<<<<<< * raise ValueError("Unable to convert item to object") * else: */ - __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_struct, __pyx_n_s_error); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 444; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} + __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_struct, __pyx_n_s_error); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 446; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_t_12 = PyErr_ExceptionMatches(__pyx_t_1); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; if (__pyx_t_12) { __Pyx_AddTraceback("View.MemoryView.memoryview.convert_item_to_object", __pyx_clineno, __pyx_lineno, __pyx_filename); - if (__Pyx_GetException(&__pyx_t_1, &__pyx_t_5, &__pyx_t_9) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 444; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} + if (__Pyx_GetException(&__pyx_t_1, &__pyx_t_5, &__pyx_t_9) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 446; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_GOTREF(__pyx_t_5); __Pyx_GOTREF(__pyx_t_9); - /* "View.MemoryView":445 + /* "View.MemoryView":447 * result = struct.unpack(self.view.format, bytesitem) * except struct.error: * raise ValueError("Unable to convert item to object") # <<<<<<<<<<<<<< * else: * if len(self.view.format) == 1: */ - __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__12, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 445; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} + __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__13, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 447; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_Raise(__pyx_t_6, 0, 0, 0); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 445; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 447; __pyx_clineno = __LINE__; goto __pyx_L5_except_error;} } goto __pyx_L5_except_error; __pyx_L5_except_error:; + + /* "View.MemoryView":444 + * + * bytesitem = itemp[:self.view.itemsize] + * try: # <<<<<<<<<<<<<< + * result = struct.unpack(self.view.format, bytesitem) + * except struct.error: + */ __Pyx_XGIVEREF(__pyx_t_2); __Pyx_XGIVEREF(__pyx_t_3); __Pyx_XGIVEREF(__pyx_t_4); @@ -8331,7 +8766,7 @@ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview goto __pyx_L0; } - /* "View.MemoryView":435 + /* "View.MemoryView":437 * self.assign_item_from_object(itemp, value) * * cdef convert_item_to_object(self, char *itemp): # <<<<<<<<<<<<<< @@ -8357,7 +8792,7 @@ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview return __pyx_r; 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+ __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type); __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":682 + /* "View.MemoryView":683 * * if isinstance(memview, _memoryviewslice): * memviewsliceobj = memview # <<<<<<<<<<<<<< * p_src = &memviewsliceobj.from_slice * else: */ - if (!(likely(((((PyObject *)__pyx_v_memview)) == Py_None) || likely(__Pyx_TypeTest(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 682; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((((PyObject *)__pyx_v_memview)) == Py_None) || likely(__Pyx_TypeTest(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 683; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_3 = ((PyObject *)__pyx_v_memview); __Pyx_INCREF(__pyx_t_3); __pyx_v_memviewsliceobj = ((struct __pyx_memoryviewslice_obj *)__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":683 + /* "View.MemoryView":684 * if isinstance(memview, _memoryviewslice): * memviewsliceobj = memview * p_src = &memviewsliceobj.from_slice # <<<<<<<<<<<<<< @@ -10975,20 +11481,28 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ * slice_copy(memview, &src) */ __pyx_v_p_src = (&__pyx_v_memviewsliceobj->from_slice); + + /* "View.MemoryView":682 + * assert memview.view.ndim > 0 + * + * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< + * memviewsliceobj = memview + * p_src = &memviewsliceobj.from_slice + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":685 + /* "View.MemoryView":686 * p_src = &memviewsliceobj.from_slice * else: * slice_copy(memview, &src) # <<<<<<<<<<<<<< * p_src = &src * */ + /*else*/ { __pyx_memoryview_slice_copy(__pyx_v_memview, (&__pyx_v_src)); - /* "View.MemoryView":686 + /* "View.MemoryView":687 * else: * slice_copy(memview, &src) * p_src = &src # <<<<<<<<<<<<<< @@ -10999,7 +11513,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __pyx_L3:; - /* "View.MemoryView":692 + /* "View.MemoryView":693 * * * dst.memview = p_src.memview # <<<<<<<<<<<<<< @@ -11009,7 +11523,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_4 = __pyx_v_p_src->memview; __pyx_v_dst.memview = __pyx_t_4; - /* "View.MemoryView":693 + /* "View.MemoryView":694 * * dst.memview = p_src.memview * dst.data = p_src.data # <<<<<<<<<<<<<< @@ -11019,7 +11533,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_5 = __pyx_v_p_src->data; __pyx_v_dst.data = __pyx_t_5; - /* "View.MemoryView":698 + /* "View.MemoryView":699 * * * cdef __Pyx_memviewslice *p_dst = &dst # <<<<<<<<<<<<<< @@ -11028,7 +11542,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __pyx_v_p_dst = (&__pyx_v_dst); - /* "View.MemoryView":699 + /* "View.MemoryView":700 * * cdef __Pyx_memviewslice *p_dst = &dst * cdef int *p_suboffset_dim = &suboffset_dim # <<<<<<<<<<<<<< @@ -11037,7 +11551,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __pyx_v_p_suboffset_dim = (&__pyx_v_suboffset_dim); - /* "View.MemoryView":703 + /* "View.MemoryView":704 * cdef bint have_start, have_stop, have_step * * for dim, index in enumerate(indices): # <<<<<<<<<<<<<< @@ -11049,25 +11563,27 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_3 = __pyx_v_indices; __Pyx_INCREF(__pyx_t_3); __pyx_t_7 = 0; __pyx_t_8 = NULL; } else { - __pyx_t_7 = -1; __pyx_t_3 = PyObject_GetIter(__pyx_v_indices); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = -1; __pyx_t_3 = PyObject_GetIter(__pyx_v_indices); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_8 = Py_TYPE(__pyx_t_3)->tp_iternext; if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = Py_TYPE(__pyx_t_3)->tp_iternext; if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } for (;;) { if (likely(!__pyx_t_8)) { if (likely(PyList_CheckExact(__pyx_t_3))) { if (__pyx_t_7 >= PyList_GET_SIZE(__pyx_t_3)) break; #if CYTHON_COMPILING_IN_CPYTHON - __pyx_t_9 = PyList_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyList_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #else - __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_9); #endif } else { if (__pyx_t_7 >= PyTuple_GET_SIZE(__pyx_t_3)) break; #if CYTHON_COMPILING_IN_CPYTHON - __pyx_t_9 = PyTuple_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyTuple_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #else - __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_9); #endif } } else { @@ -11076,7 +11592,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ PyObject* exc_type = PyErr_Occurred(); if (exc_type) { if (likely(exc_type == PyExc_StopIteration || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) PyErr_Clear(); - else {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + else {__pyx_filename = __pyx_f[2]; __pyx_lineno = 704; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } break; } @@ -11087,7 +11603,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_v_dim = __pyx_t_6; __pyx_t_6 = (__pyx_t_6 + 1); - /* "View.MemoryView":704 + /* "View.MemoryView":705 * * for dim, index in enumerate(indices): * if PyIndex_Check(index): # <<<<<<<<<<<<<< @@ -11097,27 +11613,35 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_2 = (PyIndex_Check(__pyx_v_index) != 0); if (__pyx_t_2) { - /* "View.MemoryView":708 + /* "View.MemoryView":709 * p_dst, p_src.shape[dim], p_src.strides[dim], p_src.suboffsets[dim], * dim, new_ndim, p_suboffset_dim, * index, 0, 0, # start, stop, step # <<<<<<<<<<<<<< * 0, 0, 0, # have_{start,stop,step} * False) */ - __pyx_t_10 = __Pyx_PyIndex_AsSsize_t(__pyx_v_index); if (unlikely((__pyx_t_10 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 708; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = __Pyx_PyIndex_AsSsize_t(__pyx_v_index); if (unlikely((__pyx_t_10 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 709; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":705 + /* "View.MemoryView":706 * for dim, index in enumerate(indices): * if PyIndex_Check(index): * slice_memviewslice( # <<<<<<<<<<<<<< * p_dst, p_src.shape[dim], p_src.strides[dim], p_src.suboffsets[dim], * dim, new_ndim, p_suboffset_dim, */ - __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_t_10, 0, 0, 0, 0, 0, 0); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 705; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_t_10, 0, 0, 0, 0, 0, 0); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 706; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":705 + * + * for dim, index in enumerate(indices): + * if PyIndex_Check(index): # <<<<<<<<<<<<<< + * slice_memviewslice( + * p_dst, p_src.shape[dim], p_src.strides[dim], p_src.suboffsets[dim], + */ goto __pyx_L6; } - /* "View.MemoryView":711 + /* "View.MemoryView":712 * 0, 0, 0, # have_{start,stop,step} * False) * elif index is None: # <<<<<<<<<<<<<< @@ -11128,7 +11652,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_1 = (__pyx_t_2 != 0); if (__pyx_t_1) { - /* "View.MemoryView":712 + /* "View.MemoryView":713 * False) * elif index is None: * p_dst.shape[new_ndim] = 1 # <<<<<<<<<<<<<< @@ -11137,7 +11661,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ (__pyx_v_p_dst->shape[__pyx_v_new_ndim]) = 1; - /* "View.MemoryView":713 + /* "View.MemoryView":714 * elif index is None: * p_dst.shape[new_ndim] = 1 * p_dst.strides[new_ndim] = 0 # <<<<<<<<<<<<<< @@ -11146,7 +11670,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ (__pyx_v_p_dst->strides[__pyx_v_new_ndim]) = 0; 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if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 717; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + /*else*/ { + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); - __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 717; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} if (!__pyx_t_1) { __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - goto __pyx_L8_next_or; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 717; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L7_bool_binop_done; } - __pyx_L8_next_or:; __pyx_t_10 = 0; __pyx_L7_bool_binop_done:; __pyx_v_start = __pyx_t_10; - /* "View.MemoryView":718 + /* "View.MemoryView":719 * else: * start = index.start or 0 * stop = index.stop or 0 # <<<<<<<<<<<<<< * step = index.step or 0 * */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); - __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} if (!__pyx_t_1) { __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - goto __pyx_L10_next_or; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L9_bool_binop_done; } - __pyx_L10_next_or:; __pyx_t_10 = 0; __pyx_L9_bool_binop_done:; __pyx_v_stop = __pyx_t_10; - /* "View.MemoryView":719 + /* "View.MemoryView":720 * start = index.start or 0 * stop = index.stop or 0 * step = index.step or 0 # <<<<<<<<<<<<<< * * have_start = index.start is not None */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 720; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); - __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 720; __pyx_clineno = __LINE__; goto __pyx_L1_error;} if (!__pyx_t_1) { __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - goto __pyx_L12_next_or; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 720; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L11_bool_binop_done; } - __pyx_L12_next_or:; __pyx_t_10 = 0; __pyx_L11_bool_binop_done:; __pyx_v_step = __pyx_t_10; - /* "View.MemoryView":721 + /* "View.MemoryView":722 * step = index.step or 0 * * have_start = index.start is not None # <<<<<<<<<<<<<< * have_stop = index.stop is not None * have_step = index.step is not None */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 721; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 722; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __pyx_t_1 = (__pyx_t_9 != Py_None); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __pyx_v_have_start = __pyx_t_1; - /* "View.MemoryView":722 + /* "View.MemoryView":723 * * have_start = index.start is not None * have_stop = index.stop is not None # <<<<<<<<<<<<<< * have_step = index.step is not None * */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 722; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 723; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __pyx_t_1 = (__pyx_t_9 != Py_None); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __pyx_v_have_stop = __pyx_t_1; - /* "View.MemoryView":723 + /* "View.MemoryView":724 * have_start = index.start is not None * have_stop = index.stop is not None * have_step = index.step is not None # <<<<<<<<<<<<<< * * slice_memviewslice( */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 723; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 724; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __pyx_t_1 = (__pyx_t_9 != Py_None); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __pyx_v_have_step = __pyx_t_1; - /* "View.MemoryView":725 + /* "View.MemoryView":726 * have_step = index.step is not None * * slice_memviewslice( # <<<<<<<<<<<<<< * p_dst, p_src.shape[dim], p_src.strides[dim], p_src.suboffsets[dim], * dim, new_ndim, p_suboffset_dim, */ - __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_v_start, __pyx_v_stop, __pyx_v_step, __pyx_v_have_start, __pyx_v_have_stop, __pyx_v_have_step, 1); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 725; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_v_start, __pyx_v_stop, __pyx_v_step, __pyx_v_have_start, __pyx_v_have_stop, __pyx_v_have_step, 1); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 726; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":731 + /* "View.MemoryView":732 * have_start, have_stop, have_step, * True) * new_ndim += 1 # <<<<<<<<<<<<<< @@ -11298,7 +11824,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __pyx_L6:; - /* "View.MemoryView":703 + /* "View.MemoryView":704 * cdef bint have_start, have_stop, have_step * * for dim, index in enumerate(indices): # <<<<<<<<<<<<<< @@ -11308,18 +11834,18 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":733 + /* "View.MemoryView":734 * new_ndim += 1 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * return memoryview_fromslice(dst, new_ndim, * memviewsliceobj.to_object_func, */ - __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), ((PyObject *)__pyx_memoryviewslice_type)); + __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type); __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":734 + /* "View.MemoryView":735 * * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< @@ -11328,73 +11854,81 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":735 + /* "View.MemoryView":736 * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, * memviewsliceobj.to_object_func, # <<<<<<<<<<<<<< * memviewsliceobj.to_dtype_func, * memview.dtype_is_object) */ - if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 736; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "View.MemoryView":736 + /* "View.MemoryView":737 * return memoryview_fromslice(dst, new_ndim, * memviewsliceobj.to_object_func, * memviewsliceobj.to_dtype_func, # <<<<<<<<<<<<<< * memview.dtype_is_object) * else: */ - if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 736; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 737; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "View.MemoryView":734 + /* "View.MemoryView":735 * * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< * memviewsliceobj.to_object_func, * memviewsliceobj.to_dtype_func, */ - __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; - } - /*else*/ { - /* "View.MemoryView":739 + /* "View.MemoryView":734 + * new_ndim += 1 + * + * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< + * return memoryview_fromslice(dst, new_ndim, + * memviewsliceobj.to_object_func, + */ + } + + /* "View.MemoryView":740 * memview.dtype_is_object) * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< * memview.dtype_is_object) * */ + /*else*/ { __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":740 + /* "View.MemoryView":741 * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, * memview.dtype_is_object) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 739; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 740; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - /* "View.MemoryView":739 + /* "View.MemoryView":740 * memview.dtype_is_object) * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< * memview.dtype_is_object) * */ - if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 739; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 740; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; } - /* "View.MemoryView":667 + /* "View.MemoryView":668 * * @cname('__pyx_memview_slice') * cdef memoryview memview_slice(memoryview memview, object indices): # <<<<<<<<<<<<<< @@ -11416,7 +11950,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ return __pyx_r; } -/* "View.MemoryView":764 +/* "View.MemoryView":765 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -11435,7 +11969,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "View.MemoryView":784 + /* "View.MemoryView":785 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< @@ -11445,7 +11979,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); if (__pyx_t_1) { - /* "View.MemoryView":786 + /* "View.MemoryView":787 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< @@ -11455,7 +11989,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_1 = ((__pyx_v_start < 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":787 + /* "View.MemoryView":788 * * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -11463,11 +11997,17 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - goto __pyx_L4; - } - __pyx_L4:; - /* "View.MemoryView":788 + /* "View.MemoryView":787 + * if not is_slice: + * + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if not 0 <= start < shape: + */ + } + + /* "View.MemoryView":789 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< @@ -11481,42 +12021,54 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":789 + /* "View.MemoryView":790 * start += shape * if not 0 <= start < shape: * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<< * else: * */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - goto __pyx_L5; + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 790; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":789 + * if start < 0: + * start += shape + * if not 0 <= start < shape: # <<<<<<<<<<<<<< + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + * else: + */ } - __pyx_L5:; + + /* "View.MemoryView":785 + * cdef bint negative_step + * + * if not is_slice: # <<<<<<<<<<<<<< + * + * if start < 0: + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":792 + /* "View.MemoryView":793 * else: * * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< * * if have_step and step == 0: */ + /*else*/ { __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); if (__pyx_t_1) { - goto __pyx_L7_next_and; } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L6_bool_binop_done; } - __pyx_L7_next_and:; __pyx_t_1 = ((__pyx_v_step < 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L6_bool_binop_done:; __pyx_v_negative_step = __pyx_t_2; - /* "View.MemoryView":794 + /* "View.MemoryView":795 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< @@ -11525,30 +12077,34 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_t_1 = (__pyx_v_have_step != 0); if (__pyx_t_1) { - goto __pyx_L10_next_and; } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L9_bool_binop_done; } - __pyx_L10_next_and:; __pyx_t_1 = ((__pyx_v_step == 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L9_bool_binop_done:; if (__pyx_t_2) { - /* "View.MemoryView":795 + /* "View.MemoryView":796 * * if have_step and step == 0: * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - goto __pyx_L8; - } - __pyx_L8:; + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":798 + /* "View.MemoryView":795 + * negative_step = have_step != 0 and step < 0 + * + * if have_step and step == 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) + * + */ + } + + /* "View.MemoryView":799 * * * if have_start: # <<<<<<<<<<<<<< @@ -11558,7 +12114,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_have_start != 0); if (__pyx_t_2) { - /* "View.MemoryView":799 + /* "View.MemoryView":800 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< @@ -11568,7 +12124,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":800 + /* "View.MemoryView":801 * if have_start: * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -11577,7 +12133,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - /* "View.MemoryView":801 + /* "View.MemoryView":802 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< @@ -11587,7 +12143,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":802 + /* "View.MemoryView":803 * start += shape * if start < 0: * start = 0 # <<<<<<<<<<<<<< @@ -11595,13 +12151,27 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * if negative_step: */ __pyx_v_start = 0; - goto __pyx_L13; + + /* "View.MemoryView":802 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ } - __pyx_L13:; + + /* "View.MemoryView":800 + * + * if have_start: + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if start < 0: + */ goto __pyx_L12; } - /* "View.MemoryView":803 + /* "View.MemoryView":804 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< @@ -11611,7 +12181,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); if (__pyx_t_2) { - /* "View.MemoryView":804 + /* "View.MemoryView":805 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< @@ -11621,7 +12191,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { - /* "View.MemoryView":805 + /* "View.MemoryView":806 * elif start >= shape: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -11629,38 +12199,61 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * start = shape */ __pyx_v_start = (__pyx_v_shape - 1); + + /* "View.MemoryView":805 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ goto __pyx_L14; } - /*else*/ { - /* "View.MemoryView":807 + /* "View.MemoryView":808 * start = shape - 1 * else: * start = shape # <<<<<<<<<<<<<< * else: * if negative_step: */ + /*else*/ { __pyx_v_start = __pyx_v_shape; } __pyx_L14:; - goto __pyx_L12; + + /* "View.MemoryView":804 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ } __pyx_L12:; + + /* "View.MemoryView":799 + * + * + * if have_start: # <<<<<<<<<<<<<< + * if start < 0: + * start += shape + */ goto __pyx_L11; } - /*else*/ { - /* "View.MemoryView":809 + /* "View.MemoryView":810 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< * start = shape - 1 * else: */ + /*else*/ { __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { - /* "View.MemoryView":810 + /* "View.MemoryView":811 * else: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -11668,24 +12261,32 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * start = 0 */ __pyx_v_start = (__pyx_v_shape - 1); + + /* "View.MemoryView":810 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ goto __pyx_L15; } - /*else*/ { - /* "View.MemoryView":812 + /* "View.MemoryView":813 * start = shape - 1 * else: * start = 0 # <<<<<<<<<<<<<< * * if have_stop: */ + /*else*/ { __pyx_v_start = 0; } __pyx_L15:; } __pyx_L11:; - /* "View.MemoryView":814 + /* "View.MemoryView":815 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< @@ -11695,7 +12296,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_have_stop != 0); if (__pyx_t_2) { - /* "View.MemoryView":815 + /* "View.MemoryView":816 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< @@ -11705,7 +12306,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_stop < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":816 + /* "View.MemoryView":817 * if have_stop: * if stop < 0: * stop += shape # <<<<<<<<<<<<<< @@ -11714,7 +12315,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); - /* "View.MemoryView":817 + /* "View.MemoryView":818 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< @@ -11724,7 +12325,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_stop < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":818 + /* "View.MemoryView":819 * stop += shape * if stop < 0: * stop = 0 # <<<<<<<<<<<<<< @@ -11732,13 +12333,27 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * stop = shape */ __pyx_v_stop = 0; - goto __pyx_L18; + + /* "View.MemoryView":818 + * if stop < 0: + * stop += shape + * if stop < 0: # <<<<<<<<<<<<<< + * stop = 0 + * elif stop > shape: + */ } - __pyx_L18:; + + /* "View.MemoryView":816 + * + * if have_stop: + * if stop < 0: # <<<<<<<<<<<<<< + * stop += shape + * if stop < 0: + */ goto __pyx_L17; } - /* "View.MemoryView":819 + /* "View.MemoryView":820 * if stop < 0: * stop = 0 * elif stop > shape: # <<<<<<<<<<<<<< @@ -11748,7 +12363,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); if (__pyx_t_2) { - /* "View.MemoryView":820 + /* "View.MemoryView":821 * stop = 0 * elif stop > shape: * stop = shape # <<<<<<<<<<<<<< @@ -11756,24 +12371,39 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * if negative_step: */ __pyx_v_stop = __pyx_v_shape; - goto __pyx_L17; + + /* "View.MemoryView":820 + * if stop < 0: + * stop = 0 + * elif stop > shape: # <<<<<<<<<<<<<< + * stop = shape + * else: + */ } __pyx_L17:; + + /* "View.MemoryView":815 + * start = 0 + * + * if have_stop: # <<<<<<<<<<<<<< + * if stop < 0: + * stop += shape + */ goto __pyx_L16; } - /*else*/ { - /* "View.MemoryView":822 + /* "View.MemoryView":823 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< * stop = -1 * else: */ + /*else*/ { __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { - /* "View.MemoryView":823 + /* "View.MemoryView":824 * else: * if negative_step: * stop = -1 # <<<<<<<<<<<<<< @@ -11781,24 +12411,32 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * stop = shape */ __pyx_v_stop = -1; + + /* "View.MemoryView":823 + * stop = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * stop = -1 + * else: + */ goto __pyx_L19; } - /*else*/ { - /* "View.MemoryView":825 + /* "View.MemoryView":826 * stop = -1 * else: * stop = shape # <<<<<<<<<<<<<< * * if not have_step: */ + /*else*/ { __pyx_v_stop = __pyx_v_shape; } __pyx_L19:; } __pyx_L16:; - /* "View.MemoryView":827 + /* "View.MemoryView":828 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< @@ -11808,7 +12446,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":828 + /* "View.MemoryView":829 * * if not have_step: * step = 1 # <<<<<<<<<<<<<< @@ -11816,11 +12454,17 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * */ __pyx_v_step = 1; - goto __pyx_L20; - } - __pyx_L20:; - /* "View.MemoryView":832 + /* "View.MemoryView":828 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + } + + /* "View.MemoryView":833 * * with cython.cdivision(True): * new_shape = (stop - start) // step # <<<<<<<<<<<<<< @@ -11829,7 +12473,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); - /* "View.MemoryView":834 + /* "View.MemoryView":835 * new_shape = (stop - start) // step * * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< @@ -11839,7 +12483,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":835 + /* "View.MemoryView":836 * * if (stop - start) - step * new_shape: * new_shape += 1 # <<<<<<<<<<<<<< @@ -11847,11 +12491,17 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * if new_shape < 0: */ __pyx_v_new_shape = (__pyx_v_new_shape + 1); - goto __pyx_L21; - } - __pyx_L21:; - /* "View.MemoryView":837 + /* "View.MemoryView":835 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + } + + /* "View.MemoryView":838 * new_shape += 1 * * if new_shape < 0: # <<<<<<<<<<<<<< @@ -11861,7 +12511,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":838 + /* "View.MemoryView":839 * * if new_shape < 0: * new_shape = 0 # <<<<<<<<<<<<<< @@ -11869,11 +12519,17 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * */ __pyx_v_new_shape = 0; - goto __pyx_L22; - } - __pyx_L22:; - /* "View.MemoryView":841 + /* "View.MemoryView":838 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + } + + /* "View.MemoryView":842 * * * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< @@ -11882,7 +12538,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step); - /* "View.MemoryView":842 + /* "View.MemoryView":843 * * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< @@ -11891,7 +12547,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape; - /* "View.MemoryView":843 + /* "View.MemoryView":844 * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< @@ -11902,7 +12558,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L3:; - /* "View.MemoryView":846 + /* "View.MemoryView":847 * * * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< @@ -11912,7 +12568,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":847 + /* "View.MemoryView":848 * * if suboffset_dim[0] < 0: * dst.data += start * stride # <<<<<<<<<<<<<< @@ -11920,23 +12576,31 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * dst.suboffsets[suboffset_dim[0]] += start * stride */ __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride)); + + /* "View.MemoryView":847 + * + * + * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< + * dst.data += start * stride + * else: + */ goto __pyx_L23; } - /*else*/ { - /* "View.MemoryView":849 + /* "View.MemoryView":850 * dst.data += start * stride * else: * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< * * if suboffset >= 0: */ + /*else*/ { __pyx_t_3 = (__pyx_v_suboffset_dim[0]); (__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride)); } __pyx_L23:; - /* "View.MemoryView":851 + /* "View.MemoryView":852 * dst.suboffsets[suboffset_dim[0]] += start * stride * * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -11946,7 +12610,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":852 + /* "View.MemoryView":853 * * if suboffset >= 0: * if not is_slice: # <<<<<<<<<<<<<< @@ -11956,7 +12620,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":853 + /* "View.MemoryView":854 * if suboffset >= 0: * if not is_slice: * if new_ndim == 0: # <<<<<<<<<<<<<< @@ -11966,7 +12630,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":854 + /* "View.MemoryView":855 * if not is_slice: * if new_ndim == 0: * dst.data = ( dst.data)[0] + suboffset # <<<<<<<<<<<<<< @@ -11974,39 +12638,69 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, * _err_dim(IndexError, "All dimensions preceding dimension %d " */ __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset); + + /* "View.MemoryView":854 + * if suboffset >= 0: + * if not is_slice: + * if new_ndim == 0: # <<<<<<<<<<<<<< + * dst.data = ( dst.data)[0] + suboffset + * else: + */ goto __pyx_L26; } - /*else*/ { - /* "View.MemoryView":856 + /* "View.MemoryView":857 * dst.data = ( dst.data)[0] + suboffset * else: * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<< * "must be indexed and not sliced", dim) * else: */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 856; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + /*else*/ { + + /* "View.MemoryView":858 + * else: + * _err_dim(IndexError, "All dimensions preceding dimension %d " + * "must be indexed and not sliced", dim) # <<<<<<<<<<<<<< + * else: + * suboffset_dim[0] = new_ndim + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 857; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_L26:; + + /* "View.MemoryView":853 + * + * if suboffset >= 0: + * if not is_slice: # <<<<<<<<<<<<<< + * if new_ndim == 0: + * dst.data = ( dst.data)[0] + suboffset + */ goto __pyx_L25; } - /*else*/ { - /* "View.MemoryView":859 + /* "View.MemoryView":860 * "must be indexed and not sliced", dim) * else: * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< * * return 0 */ + /*else*/ { (__pyx_v_suboffset_dim[0]) = __pyx_v_new_ndim; } __pyx_L25:; - goto __pyx_L24; - } - __pyx_L24:; - /* "View.MemoryView":861 + /* "View.MemoryView":852 + * dst.suboffsets[suboffset_dim[0]] += start * stride + * + * if suboffset >= 0: # <<<<<<<<<<<<<< + * if not is_slice: + * if new_ndim == 0: + */ + } + + /* "View.MemoryView":862 * suboffset_dim[0] = new_ndim * * return 0 # <<<<<<<<<<<<<< @@ -12016,7 +12710,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":764 + /* "View.MemoryView":765 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -12040,7 +12734,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, return __pyx_r; } -/* "View.MemoryView":867 +/* "View.MemoryView":868 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -12065,7 +12759,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P int __pyx_clineno = 0; __Pyx_RefNannySetupContext("pybuffer_index", 0); - /* "View.MemoryView":869 + /* "View.MemoryView":870 * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, * Py_ssize_t dim) except NULL: * cdef Py_ssize_t shape, stride, suboffset = -1 # <<<<<<<<<<<<<< @@ -12074,7 +12768,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_suboffset = -1; - /* "View.MemoryView":870 + /* "View.MemoryView":871 * Py_ssize_t dim) except NULL: * cdef Py_ssize_t shape, stride, suboffset = -1 * cdef Py_ssize_t itemsize = view.itemsize # <<<<<<<<<<<<<< @@ -12084,7 +12778,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_1 = __pyx_v_view->itemsize; __pyx_v_itemsize = __pyx_t_1; - /* "View.MemoryView":873 + /* "View.MemoryView":874 * cdef char *resultp * * if view.ndim == 0: # <<<<<<<<<<<<<< @@ -12094,7 +12788,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_view->ndim == 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":874 + /* "View.MemoryView":875 * * if view.ndim == 0: * shape = view.len / itemsize # <<<<<<<<<<<<<< @@ -12102,28 +12796,16 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P * else: */ if (unlikely(__pyx_v_itemsize == 0)) { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero"); - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 875; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - else if (sizeof(Py_ssize_t) == sizeof(long) && unlikely(__pyx_v_itemsize == -1) && unlikely(UNARY_NEG_WOULD_OVERFLOW(__pyx_v_view->len))) { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); - #endif + else if (sizeof(Py_ssize_t) == sizeof(long) && (!(((Py_ssize_t)-1) > 0)) && unlikely(__pyx_v_itemsize == (Py_ssize_t)-1) && unlikely(UNARY_NEG_WOULD_OVERFLOW(__pyx_v_view->len))) { PyErr_SetString(PyExc_OverflowError, "value too large to perform division"); - #ifdef WITH_THREAD - PyGILState_Release(__pyx_gilstate_save); - #endif - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 875; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_v_shape = __Pyx_div_Py_ssize_t(__pyx_v_view->len, __pyx_v_itemsize); - /* "View.MemoryView":875 + /* "View.MemoryView":876 * if view.ndim == 0: * shape = view.len / itemsize * stride = itemsize # <<<<<<<<<<<<<< @@ -12131,20 +12813,28 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P * shape = view.shape[dim] */ __pyx_v_stride = __pyx_v_itemsize; + + /* "View.MemoryView":874 + * cdef char *resultp + * + * if view.ndim == 0: # <<<<<<<<<<<<<< + * shape = view.len / itemsize + * stride = itemsize + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":877 + /* "View.MemoryView":878 * stride = itemsize * else: * shape = view.shape[dim] # <<<<<<<<<<<<<< * stride = view.strides[dim] * if view.suboffsets != NULL: */ + /*else*/ { __pyx_v_shape = (__pyx_v_view->shape[__pyx_v_dim]); - /* "View.MemoryView":878 + /* "View.MemoryView":879 * else: * shape = view.shape[dim] * stride = view.strides[dim] # <<<<<<<<<<<<<< @@ -12153,7 +12843,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_stride = (__pyx_v_view->strides[__pyx_v_dim]); - /* "View.MemoryView":879 + /* "View.MemoryView":880 * shape = view.shape[dim] * stride = view.strides[dim] * if view.suboffsets != NULL: # <<<<<<<<<<<<<< @@ -12163,7 +12853,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_view->suboffsets != NULL) != 0); if (__pyx_t_2) { - /* "View.MemoryView":880 + /* "View.MemoryView":881 * stride = view.strides[dim] * if view.suboffsets != NULL: * suboffset = view.suboffsets[dim] # <<<<<<<<<<<<<< @@ -12171,13 +12861,19 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P * if index < 0: */ __pyx_v_suboffset = (__pyx_v_view->suboffsets[__pyx_v_dim]); - goto __pyx_L4; + + /* "View.MemoryView":880 + * shape = view.shape[dim] + * stride = view.strides[dim] + * if view.suboffsets != NULL: # <<<<<<<<<<<<<< + * suboffset = view.suboffsets[dim] + * + */ } - __pyx_L4:; } __pyx_L3:; - /* "View.MemoryView":882 + /* "View.MemoryView":883 * suboffset = view.suboffsets[dim] * * if index < 0: # <<<<<<<<<<<<<< @@ -12187,7 +12883,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_index < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":883 + /* "View.MemoryView":884 * * if index < 0: * index += view.shape[dim] # <<<<<<<<<<<<<< @@ -12196,7 +12892,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_index = (__pyx_v_index + (__pyx_v_view->shape[__pyx_v_dim])); - /* "View.MemoryView":884 + /* "View.MemoryView":885 * if index < 0: * index += view.shape[dim] * if index < 0: # <<<<<<<<<<<<<< @@ -12206,35 +12902,49 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_index < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":885 + /* "View.MemoryView":886 * index += view.shape[dim] * if index < 0: * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) # <<<<<<<<<<<<<< * * if index >= shape: */ - __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 886; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_4 = __Pyx_PyString_Format(__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_t_3); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyString_Format(__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_t_3); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 886; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 886; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_4); __Pyx_GIVEREF(__pyx_t_4); + PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = __Pyx_PyObject_Call(__pyx_builtin_IndexError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_Call(__pyx_builtin_IndexError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 886; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_Raise(__pyx_t_4, 0, 0, 0); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - } - goto __pyx_L5; - } - __pyx_L5:; + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 886; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":887 + /* "View.MemoryView":885 + * if index < 0: + * index += view.shape[dim] + * if index < 0: # <<<<<<<<<<<<<< + * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) + * + */ + } + + /* "View.MemoryView":883 + * suboffset = view.suboffsets[dim] + * + * if index < 0: # <<<<<<<<<<<<<< + * index += view.shape[dim] + * if index < 0: + */ + } + + /* "View.MemoryView":888 * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) * * if index >= shape: # <<<<<<<<<<<<<< @@ -12244,32 +12954,40 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_index >= __pyx_v_shape) != 0); if (__pyx_t_2) { - /* "View.MemoryView":888 + /* "View.MemoryView":889 * * if index >= shape: * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) # <<<<<<<<<<<<<< * * resultp = bufp + index * stride */ - __pyx_t_4 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 888; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 889; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - __pyx_t_3 = __Pyx_PyString_Format(__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_t_4); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 888; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyString_Format(__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_t_4); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 889; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 888; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 889; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); + PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_IndexError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 888; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_IndexError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 889; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 888; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 889; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":888 + * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) + * + * if index >= shape: # <<<<<<<<<<<<<< + * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) + * + */ } - /* "View.MemoryView":890 + /* "View.MemoryView":891 * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) * * resultp = bufp + index * stride # <<<<<<<<<<<<<< @@ -12278,7 +12996,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_resultp = (__pyx_v_bufp + (__pyx_v_index * __pyx_v_stride)); - /* "View.MemoryView":891 + /* "View.MemoryView":892 * * resultp = bufp + index * stride * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -12288,7 +13006,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":892 + /* "View.MemoryView":893 * resultp = bufp + index * stride * if suboffset >= 0: * resultp = ( resultp)[0] + suboffset # <<<<<<<<<<<<<< @@ -12296,11 +13014,17 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P * return resultp */ __pyx_v_resultp = ((((char **)__pyx_v_resultp)[0]) + __pyx_v_suboffset); - goto __pyx_L8; - } - __pyx_L8:; - /* "View.MemoryView":894 + /* "View.MemoryView":892 + * + * resultp = bufp + index * stride + * if suboffset >= 0: # <<<<<<<<<<<<<< + * resultp = ( resultp)[0] + suboffset + * + */ + } + + /* "View.MemoryView":895 * resultp = ( resultp)[0] + suboffset * * return resultp # <<<<<<<<<<<<<< @@ -12310,7 +13034,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_r = __pyx_v_resultp; goto __pyx_L0; - /* "View.MemoryView":867 + /* "View.MemoryView":868 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -12329,7 +13053,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P return __pyx_r; } -/* "View.MemoryView":900 +/* "View.MemoryView":901 * * @cname('__pyx_memslice_transpose') * cdef int transpose_memslice(__Pyx_memviewslice *memslice) nogil except 0: # <<<<<<<<<<<<<< @@ -12356,7 +13080,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "View.MemoryView":901 + /* "View.MemoryView":902 * @cname('__pyx_memslice_transpose') * cdef int transpose_memslice(__Pyx_memviewslice *memslice) nogil except 0: * cdef int ndim = memslice.memview.view.ndim # <<<<<<<<<<<<<< @@ -12366,7 +13090,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { __pyx_t_1 = __pyx_v_memslice->memview->view.ndim; __pyx_v_ndim = __pyx_t_1; - /* "View.MemoryView":903 + /* "View.MemoryView":904 * cdef int ndim = memslice.memview.view.ndim * * cdef Py_ssize_t *shape = memslice.shape # <<<<<<<<<<<<<< @@ -12376,7 +13100,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { __pyx_t_2 = __pyx_v_memslice->shape; __pyx_v_shape = __pyx_t_2; - /* "View.MemoryView":904 + /* "View.MemoryView":905 * * cdef Py_ssize_t *shape = memslice.shape * cdef Py_ssize_t *strides = memslice.strides # <<<<<<<<<<<<<< @@ -12386,7 +13110,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { __pyx_t_2 = __pyx_v_memslice->strides; __pyx_v_strides = __pyx_t_2; - /* "View.MemoryView":908 + /* "View.MemoryView":909 * * cdef int i, j * for i in range(ndim / 2): # <<<<<<<<<<<<<< @@ -12397,7 +13121,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_3; __pyx_t_1+=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":909 + /* "View.MemoryView":910 * cdef int i, j * for i in range(ndim / 2): * j = ndim - 1 - i # <<<<<<<<<<<<<< @@ -12406,7 +13130,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { */ __pyx_v_j = ((__pyx_v_ndim - 1) - __pyx_v_i); - /* "View.MemoryView":910 + /* "View.MemoryView":911 * for i in range(ndim / 2): * j = ndim - 1 - i * strides[i], strides[j] = strides[j], strides[i] # <<<<<<<<<<<<<< @@ -12418,7 +13142,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { (__pyx_v_strides[__pyx_v_i]) = __pyx_t_4; (__pyx_v_strides[__pyx_v_j]) = __pyx_t_5; - /* "View.MemoryView":911 + /* "View.MemoryView":912 * j = ndim - 1 - i * strides[i], strides[j] = strides[j], strides[i] * shape[i], shape[j] = shape[j], shape[i] # <<<<<<<<<<<<<< @@ -12430,7 +13154,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { (__pyx_v_shape[__pyx_v_i]) = __pyx_t_5; (__pyx_v_shape[__pyx_v_j]) = __pyx_t_4; - /* "View.MemoryView":913 + /* "View.MemoryView":914 * shape[i], shape[j] = shape[j], shape[i] * * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: # <<<<<<<<<<<<<< @@ -12439,31 +13163,35 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { */ __pyx_t_7 = (((__pyx_v_memslice->suboffsets[__pyx_v_i]) >= 0) != 0); if (!__pyx_t_7) { - goto __pyx_L7_next_or; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L6_bool_binop_done; } - __pyx_L7_next_or:; __pyx_t_7 = (((__pyx_v_memslice->suboffsets[__pyx_v_j]) >= 0) != 0); __pyx_t_6 = __pyx_t_7; __pyx_L6_bool_binop_done:; if (__pyx_t_6) { - /* "View.MemoryView":914 + /* "View.MemoryView":915 * * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: * _err(ValueError, "Cannot transpose memoryview with indirect dimensions") # <<<<<<<<<<<<<< * * return 1 */ - __pyx_t_8 = __pyx_memoryview_err(__pyx_builtin_ValueError, __pyx_k_Cannot_transpose_memoryview_with); if (unlikely(__pyx_t_8 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 914; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - goto __pyx_L5; + __pyx_t_8 = __pyx_memoryview_err(__pyx_builtin_ValueError, __pyx_k_Cannot_transpose_memoryview_with); if (unlikely(__pyx_t_8 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 915; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":914 + * shape[i], shape[j] = shape[j], shape[i] + * + * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: # <<<<<<<<<<<<<< + * _err(ValueError, "Cannot transpose memoryview with indirect dimensions") + * + */ } - __pyx_L5:; 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- __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(((struct __pyx_memoryviewslice_obj *)__pyx_v_self)); + __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(((struct __pyx_memoryviewslice_obj *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); } -static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self) { +static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self) { __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__dealloc__", 0); - /* "View.MemoryView":934 + /* "View.MemoryView":935 * * def __dealloc__(self): * __PYX_XDEC_MEMVIEW(&self.from_slice, 1) # <<<<<<<<<<<<<< @@ -12529,7 +13257,7 @@ static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(stru */ __PYX_XDEC_MEMVIEW((&__pyx_v_self->from_slice), 1); - /* "View.MemoryView":933 + /* "View.MemoryView":934 * cdef int (*to_dtype_func)(char *, object) except 0 * * def __dealloc__(self): # <<<<<<<<<<<<<< @@ -12541,7 +13269,7 @@ static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(stru __Pyx_RefNannyFinishContext(); 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if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 940; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __pyx_memoryview_convert_item_to_object(((struct __pyx_memoryview_obj *)__pyx_v_self), __pyx_v_itemp); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 941; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __pyx_r = __pyx_t_2; __pyx_t_2 = 0; goto __pyx_L0; } - /* "View.MemoryView":936 + /* "View.MemoryView":937 * __PYX_XDEC_MEMVIEW(&self.from_slice, 1) * * cdef convert_item_to_object(self, char *itemp): # <<<<<<<<<<<<<< @@ -12619,7 +13355,7 @@ static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memor return __pyx_r; } -/* "View.MemoryView":942 +/* "View.MemoryView":943 * return memoryview.convert_item_to_object(self, itemp) * * cdef assign_item_from_object(self, char *itemp, object value): # <<<<<<<<<<<<<< @@ -12638,7 +13374,7 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo int __pyx_clineno = 0; 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__pyx_lineno = 945; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":944 + * + * cdef assign_item_from_object(self, char *itemp, object value): + * if self.to_dtype_func != NULL: # <<<<<<<<<<<<<< + * self.to_dtype_func(itemp, value) + * else: + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":946 + /* "View.MemoryView":947 * self.to_dtype_func(itemp, value) * else: * memoryview.assign_item_from_object(self, itemp, value) # <<<<<<<<<<<<<< * * property base: */ - __pyx_t_3 = __pyx_memoryview_assign_item_from_object(((struct __pyx_memoryview_obj *)__pyx_v_self), __pyx_v_itemp, __pyx_v_value); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 946; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + /*else*/ { + __pyx_t_3 = __pyx_memoryview_assign_item_from_object(((struct __pyx_memoryview_obj *)__pyx_v_self), __pyx_v_itemp, __pyx_v_value); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 947; __pyx_clineno = __LINE__; 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+ __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_result->__pyx_base.view.len); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1000; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_2); + __pyx_t_3 = PyNumber_InPlaceMultiply(__pyx_t_2, __pyx_v_length); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1000; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_3); + __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; + __pyx_t_9 = __Pyx_PyIndex_AsSsize_t(__pyx_t_3); if (unlikely((__pyx_t_9 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1000; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; + __pyx_v_result->__pyx_base.view.len = __pyx_t_9; } - /* "View.MemoryView":996 - * result.view.len *= result.view.shape[i] + /* "View.MemoryView":1002 + * result.view.len *= length * * result.to_object_func = to_object_func # <<<<<<<<<<<<<< * result.to_dtype_func = to_dtype_func @@ -12987,7 +13803,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_object_func = __pyx_v_to_object_func; 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__Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "View.MemoryView":1002 +/* "View.MemoryView":1008 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< @@ -13049,31 +13866,31 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p int __pyx_clineno = 0; __Pyx_RefNannySetupContext("get_slice_from_memview", 0); - /* "View.MemoryView":1005 + /* "View.MemoryView":1011 * __Pyx_memviewslice *mslice): * cdef _memoryviewslice obj * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * obj = memview * return &obj.from_slice */ - __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), ((PyObject *)__pyx_memoryviewslice_type)); + __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type); __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1006 + /* "View.MemoryView":1012 * cdef _memoryviewslice obj * if isinstance(memview, _memoryviewslice): * obj = memview # <<<<<<<<<<<<<< * return &obj.from_slice * else: */ - if (!(likely(((((PyObject *)__pyx_v_memview)) == Py_None) || likely(__Pyx_TypeTest(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1006; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((((PyObject *)__pyx_v_memview)) == Py_None) || likely(__Pyx_TypeTest(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1012; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_3 = ((PyObject *)__pyx_v_memview); __Pyx_INCREF(__pyx_t_3); __pyx_v_obj = ((struct __pyx_memoryviewslice_obj *)__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":1007 + /* "View.MemoryView":1013 * if isinstance(memview, _memoryviewslice): * obj = memview * return &obj.from_slice # <<<<<<<<<<<<<< @@ -13082,19 +13899,27 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p */ __pyx_r = (&__pyx_v_obj->from_slice); goto __pyx_L0; - } - /*else*/ { - /* "View.MemoryView":1009 + /* "View.MemoryView":1011 + * __Pyx_memviewslice *mslice): + * cdef _memoryviewslice obj + * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< + * obj = memview + * return &obj.from_slice + */ + } + + /* "View.MemoryView":1015 * return &obj.from_slice * else: * slice_copy(memview, mslice) # <<<<<<<<<<<<<< * return mslice * */ + /*else*/ { __pyx_memoryview_slice_copy(__pyx_v_memview, __pyx_v_mslice); - /* "View.MemoryView":1010 + /* "View.MemoryView":1016 * else: * slice_copy(memview, mslice) * return mslice # <<<<<<<<<<<<<< @@ -13105,7 +13930,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p goto __pyx_L0; } - /* "View.MemoryView":1002 + /* "View.MemoryView":1008 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< @@ -13116,7 +13941,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_3); - __Pyx_WriteUnraisable("View.MemoryView.get_slice_from_memview", __pyx_clineno, __pyx_lineno, __pyx_filename, 0); + __Pyx_WriteUnraisable("View.MemoryView.get_slice_from_memview", __pyx_clineno, __pyx_lineno, __pyx_filename, 0, 0); __pyx_r = 0; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_obj); @@ -13124,7 +13949,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p return __pyx_r; } -/* "View.MemoryView":1013 +/* "View.MemoryView":1019 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -13141,10 +13966,10 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem Py_ssize_t *__pyx_t_1; int __pyx_t_2; int __pyx_t_3; - int __pyx_t_4; + Py_ssize_t __pyx_t_4; __Pyx_RefNannySetupContext("slice_copy", 0); - /* "View.MemoryView":1017 + /* "View.MemoryView":1023 * cdef (Py_ssize_t*) shape, strides, suboffsets * * shape = memview.view.shape # <<<<<<<<<<<<<< @@ -13154,7 +13979,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __pyx_t_1 = __pyx_v_memview->view.shape; __pyx_v_shape = __pyx_t_1; - /* "View.MemoryView":1018 + /* "View.MemoryView":1024 * * shape = memview.view.shape * strides = memview.view.strides # <<<<<<<<<<<<<< @@ -13164,7 +13989,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __pyx_t_1 = __pyx_v_memview->view.strides; __pyx_v_strides = __pyx_t_1; - /* "View.MemoryView":1019 + /* "View.MemoryView":1025 * shape = memview.view.shape * strides = memview.view.strides * suboffsets = memview.view.suboffsets # <<<<<<<<<<<<<< @@ -13174,7 +13999,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __pyx_t_1 = __pyx_v_memview->view.suboffsets; __pyx_v_suboffsets = __pyx_t_1; - /* "View.MemoryView":1021 + /* "View.MemoryView":1027 * suboffsets = memview.view.suboffsets * * dst.memview = <__pyx_memoryview *> memview # <<<<<<<<<<<<<< @@ -13183,7 +14008,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ __pyx_v_dst->memview = ((struct __pyx_memoryview_obj *)__pyx_v_memview); - /* "View.MemoryView":1022 + /* "View.MemoryView":1028 * * dst.memview = <__pyx_memoryview *> memview * dst.data = memview.view.buf # <<<<<<<<<<<<<< @@ -13192,7 +14017,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ __pyx_v_dst->data = ((char *)__pyx_v_memview->view.buf); - /* "View.MemoryView":1024 + /* "View.MemoryView":1030 * dst.data = memview.view.buf * * for dim in range(memview.view.ndim): # <<<<<<<<<<<<<< @@ -13203,59 +14028,40 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_dim = __pyx_t_3; - /* "View.MemoryView":1025 + /* "View.MemoryView":1031 * * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] # <<<<<<<<<<<<<< * dst.strides[dim] = strides[dim] - * if suboffsets == NULL: + * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 */ (__pyx_v_dst->shape[__pyx_v_dim]) = (__pyx_v_shape[__pyx_v_dim]); - /* "View.MemoryView":1026 + /* "View.MemoryView":1032 * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] # <<<<<<<<<<<<<< - * if suboffsets == NULL: - * dst.suboffsets[dim] = -1 + * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 + * */ (__pyx_v_dst->strides[__pyx_v_dim]) = (__pyx_v_strides[__pyx_v_dim]); - /* "View.MemoryView":1027 + /* "View.MemoryView":1033 * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] - * if suboffsets == NULL: # <<<<<<<<<<<<<< - * dst.suboffsets[dim] = -1 - * else: - */ - __pyx_t_4 = ((__pyx_v_suboffsets == NULL) != 0); - if (__pyx_t_4) { - - /* "View.MemoryView":1028 - * dst.strides[dim] = strides[dim] - * if suboffsets == NULL: - * dst.suboffsets[dim] = -1 # <<<<<<<<<<<<<< - * else: - * dst.suboffsets[dim] = suboffsets[dim] - */ - (__pyx_v_dst->suboffsets[__pyx_v_dim]) = -1; - goto __pyx_L5; - } - /*else*/ { - - /* "View.MemoryView":1030 - * dst.suboffsets[dim] = -1 - * else: - * dst.suboffsets[dim] = suboffsets[dim] # <<<<<<<<<<<<<< + * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_copy_object') */ - (__pyx_v_dst->suboffsets[__pyx_v_dim]) = (__pyx_v_suboffsets[__pyx_v_dim]); + if ((__pyx_v_suboffsets != 0)) { + __pyx_t_4 = (__pyx_v_suboffsets[__pyx_v_dim]); + } else { + __pyx_t_4 = -1; } - __pyx_L5:; + (__pyx_v_dst->suboffsets[__pyx_v_dim]) = __pyx_t_4; } - /* "View.MemoryView":1013 + /* "View.MemoryView":1019 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -13267,7 +14073,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1033 +/* "View.MemoryView":1036 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -13285,7 +14091,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy", 0); - /* "View.MemoryView":1036 + /* "View.MemoryView":1039 * "Create a new memoryview object" * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -13294,7 +14100,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx */ __pyx_memoryview_slice_copy(__pyx_v_memview, (&__pyx_v_memviewslice)); - /* "View.MemoryView":1037 + /* "View.MemoryView":1040 * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) * return memoryview_copy_from_slice(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -13302,13 +14108,13 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx * @cname('__pyx_memoryview_copy_object_from_slice') */ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1037; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1040; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; - /* "View.MemoryView":1033 + /* "View.MemoryView":1036 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -13327,7 +14133,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx return __pyx_r; } -/* "View.MemoryView":1040 +/* "View.MemoryView":1043 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -13350,18 +14156,18 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy_from_slice", 0); - /* "View.MemoryView":1047 + /* "View.MemoryView":1050 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * to_object_func = (<_memoryviewslice> memview).to_object_func * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func */ - __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), ((PyObject *)__pyx_memoryviewslice_type)); + __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type); __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1048 + /* "View.MemoryView":1051 * * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func # <<<<<<<<<<<<<< @@ -13371,7 +14177,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview __pyx_t_3 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_object_func; __pyx_v_to_object_func = __pyx_t_3; - /* "View.MemoryView":1049 + /* "View.MemoryView":1052 * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func # <<<<<<<<<<<<<< @@ -13380,20 +14186,28 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview */ __pyx_t_4 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_dtype_func; __pyx_v_to_dtype_func = __pyx_t_4; + + /* "View.MemoryView":1050 + * cdef int (*to_dtype_func)(char *, object) except 0 + * + * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< + * to_object_func = (<_memoryviewslice> memview).to_object_func + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":1051 + /* "View.MemoryView":1054 * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func * else: * to_object_func = NULL # <<<<<<<<<<<<<< * to_dtype_func = NULL * */ + /*else*/ { __pyx_v_to_object_func = NULL; - /* "View.MemoryView":1052 + /* "View.MemoryView":1055 * else: * to_object_func = NULL * to_dtype_func = NULL # <<<<<<<<<<<<<< @@ -13404,7 +14218,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview } __pyx_L3:; - /* "View.MemoryView":1054 + /* "View.MemoryView":1057 * to_dtype_func = NULL * * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< @@ -13413,20 +14227,20 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview */ __Pyx_XDECREF(__pyx_r); - /* "View.MemoryView":1056 + /* "View.MemoryView":1059 * return memoryview_fromslice(memviewslice[0], memview.view.ndim, * to_object_func, to_dtype_func, * memview.dtype_is_object) # <<<<<<<<<<<<<< * * */ - __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1054; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1057; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __pyx_r = __pyx_t_5; __pyx_t_5 = 0; goto __pyx_L0; - /* "View.MemoryView":1040 + /* "View.MemoryView":1043 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -13445,7 +14259,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview return __pyx_r; } -/* "View.MemoryView":1062 +/* "View.MemoryView":1065 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -13457,7 +14271,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { Py_ssize_t __pyx_r; int __pyx_t_1; - /* "View.MemoryView":1063 + /* "View.MemoryView":1066 * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: # <<<<<<<<<<<<<< @@ -13467,7 +14281,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { __pyx_t_1 = ((__pyx_v_arg < 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1064 + /* "View.MemoryView":1067 * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: * return -arg # <<<<<<<<<<<<<< @@ -13476,21 +14290,29 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { */ __pyx_r = (-__pyx_v_arg); goto __pyx_L0; - } - /*else*/ { /* "View.MemoryView":1066 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + } + + /* "View.MemoryView":1069 * return -arg * else: * return arg # <<<<<<<<<<<<<< * * @cname('__pyx_get_best_slice_order') */ + /*else*/ { __pyx_r = __pyx_v_arg; goto __pyx_L0; } - /* "View.MemoryView":1062 + /* "View.MemoryView":1065 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -13503,7 +14325,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { return __pyx_r; } -/* "View.MemoryView":1069 +/* "View.MemoryView":1072 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -13520,7 +14342,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1074 + /* "View.MemoryView":1077 * """ * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< @@ -13529,7 +14351,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_c_stride = 0; - /* "View.MemoryView":1075 + /* "View.MemoryView":1078 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< @@ -13538,7 +14360,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_f_stride = 0; - /* "View.MemoryView":1077 + /* "View.MemoryView":1080 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -13548,7 +14370,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":1078 + /* "View.MemoryView":1081 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -13558,7 +14380,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1079 + /* "View.MemoryView":1082 * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -13567,7 +14389,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1080 + /* "View.MemoryView":1083 * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -13575,11 +14397,19 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ * for i in range(ndim): */ goto __pyx_L4_break; + + /* "View.MemoryView":1081 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ } } __pyx_L4_break:; - /* "View.MemoryView":1082 + /* "View.MemoryView":1085 * break * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -13590,7 +14420,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1083 + /* "View.MemoryView":1086 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -13600,7 +14430,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1084 + /* "View.MemoryView":1087 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -13609,7 +14439,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1085 + /* "View.MemoryView":1088 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -13617,11 +14447,19 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): */ goto __pyx_L7_break; + + /* "View.MemoryView":1086 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ } } __pyx_L7_break:; - /* "View.MemoryView":1087 + /* "View.MemoryView":1090 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< @@ -13631,7 +14469,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1088 + /* "View.MemoryView":1091 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< @@ -13640,21 +14478,29 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_r = 'C'; goto __pyx_L0; - } - /*else*/ { /* "View.MemoryView":1090 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + } + + /* "View.MemoryView":1093 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< * * @cython.cdivision(True) */ + /*else*/ { __pyx_r = 'F'; goto __pyx_L0; } - /* "View.MemoryView":1069 + /* "View.MemoryView":1072 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -13667,7 +14513,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ return __pyx_r; } -/* "View.MemoryView":1093 +/* "View.MemoryView":1096 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -13687,7 +14533,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v Py_ssize_t __pyx_t_4; Py_ssize_t __pyx_t_5; - /* "View.MemoryView":1100 + /* "View.MemoryView":1103 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< @@ -13696,7 +14542,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_extent = (__pyx_v_src_shape[0]); - /* "View.MemoryView":1101 + /* "View.MemoryView":1104 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< @@ -13705,7 +14551,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); - /* "View.MemoryView":1102 + /* "View.MemoryView":1105 * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< @@ -13714,7 +14560,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_stride = (__pyx_v_src_strides[0]); - /* "View.MemoryView":1103 + /* "View.MemoryView":1106 * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< @@ -13723,7 +14569,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); - /* "View.MemoryView":1105 + /* "View.MemoryView":1108 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -13733,7 +14579,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1106 + /* "View.MemoryView":1109 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -13742,22 +14588,18 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); if (__pyx_t_2) { - goto __pyx_L6_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } - __pyx_L6_next_and:; __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); if (__pyx_t_2) { - goto __pyx_L7_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } - __pyx_L7_next_and:; - /* "View.MemoryView":1107 + /* "View.MemoryView":1110 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< @@ -13771,9 +14613,17 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v __pyx_t_3 = (__pyx_t_2 != 0); __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; + + /* "View.MemoryView":1109 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ if (__pyx_t_1) { - /* "View.MemoryView":1108 + /* "View.MemoryView":1111 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< @@ -13781,22 +14631,30 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v * for i in range(dst_extent): */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent)); + + /* "View.MemoryView":1109 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ goto __pyx_L4; } - /*else*/ { - /* "View.MemoryView":1110 + /* "View.MemoryView":1113 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize) * src_data += src_stride */ + /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":1111 + /* "View.MemoryView":1114 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< @@ -13805,7 +14663,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize); - /* "View.MemoryView":1112 + /* "View.MemoryView":1115 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -13814,7 +14672,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - /* "View.MemoryView":1113 + /* "View.MemoryView":1116 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -13825,22 +14683,30 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } } __pyx_L4:; + + /* "View.MemoryView":1108 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":1115 + /* "View.MemoryView":1118 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * _copy_strided_to_strided(src_data, src_strides + 1, * dst_data, dst_strides + 1, */ + /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":1116 + /* "View.MemoryView":1119 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< @@ -13849,7 +14715,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); - /* "View.MemoryView":1120 + /* "View.MemoryView":1123 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -13858,7 +14724,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - /* "View.MemoryView":1121 + /* "View.MemoryView":1124 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -13870,7 +14736,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } __pyx_L3:; - /* "View.MemoryView":1093 + /* "View.MemoryView":1096 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -13881,7 +14747,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v /* function exit code */ } -/* "View.MemoryView":1123 +/* "View.MemoryView":1126 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -13891,7 +14757,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { - /* "View.MemoryView":1126 + /* "View.MemoryView":1129 * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< @@ -13900,7 +14766,7 @@ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memvi */ _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); - /* "View.MemoryView":1123 + /* "View.MemoryView":1126 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -13911,7 +14777,7 @@ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memvi /* function exit code */ } -/* "View.MemoryView":1130 +/* "View.MemoryView":1133 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< @@ -13927,7 +14793,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1133 + /* "View.MemoryView":1136 * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -13937,7 +14803,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_size = __pyx_t_1; - /* "View.MemoryView":1135 + /* "View.MemoryView":1138 * cdef Py_ssize_t size = src.memview.view.itemsize * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -13948,7 +14814,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1136 + /* "View.MemoryView":1139 * * for i in range(ndim): * size *= src.shape[i] # <<<<<<<<<<<<<< @@ -13958,7 +14824,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); } - /* "View.MemoryView":1138 + /* "View.MemoryView":1141 * size *= src.shape[i] * * return size # <<<<<<<<<<<<<< @@ -13968,7 +14834,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_r = __pyx_v_size; goto __pyx_L0; - /* "View.MemoryView":1130 + /* "View.MemoryView":1133 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< @@ -13981,7 +14847,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr return __pyx_r; } -/* "View.MemoryView":1141 +/* "View.MemoryView":1144 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -13996,7 +14862,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1150 + /* "View.MemoryView":1153 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< @@ -14006,7 +14872,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ __pyx_t_1 = ((__pyx_v_order == 'F') != 0); if (__pyx_t_1) { - /* "View.MemoryView":1151 + /* "View.MemoryView":1154 * * if order == 'F': * for idx in range(ndim): # <<<<<<<<<<<<<< @@ -14017,7 +14883,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_idx = __pyx_t_3; - /* "View.MemoryView":1152 + /* "View.MemoryView":1155 * if order == 'F': * for idx in range(ndim): * strides[idx] = stride # <<<<<<<<<<<<<< @@ -14026,7 +14892,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1153 + /* "View.MemoryView":1156 * for idx in range(ndim): * strides[idx] = stride * stride = stride * shape[idx] # <<<<<<<<<<<<<< @@ -14035,21 +14901,29 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ */ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); } + + /* "View.MemoryView":1153 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":1155 + /* "View.MemoryView":1158 * stride = stride * shape[idx] * else: * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * strides[idx] = stride * stride = stride * shape[idx] */ + /*else*/ { for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { __pyx_v_idx = __pyx_t_2; - /* "View.MemoryView":1156 + /* "View.MemoryView":1159 * else: * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride # <<<<<<<<<<<<<< @@ -14058,7 +14932,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1157 + /* "View.MemoryView":1160 * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride * stride = stride * shape[idx] # <<<<<<<<<<<<<< @@ -14070,7 +14944,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ } __pyx_L3:; - /* "View.MemoryView":1159 + /* "View.MemoryView":1162 * stride = stride * shape[idx] * * return stride # <<<<<<<<<<<<<< @@ -14080,7 +14954,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ __pyx_r = __pyx_v_stride; goto __pyx_L0; - /* "View.MemoryView":1141 + /* "View.MemoryView":1144 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -14093,7 +14967,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ return __pyx_r; } -/* "View.MemoryView":1162 +/* "View.MemoryView":1165 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -14116,7 +14990,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "View.MemoryView":1173 + /* "View.MemoryView":1176 * cdef void *result * * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -14126,7 +15000,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_itemsize = __pyx_t_1; - /* "View.MemoryView":1174 + /* "View.MemoryView":1177 * * cdef size_t itemsize = src.memview.view.itemsize * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< @@ -14135,7 +15009,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); - /* "View.MemoryView":1176 + /* "View.MemoryView":1179 * cdef size_t size = slice_get_size(src, ndim) * * result = malloc(size) # <<<<<<<<<<<<<< @@ -14144,7 +15018,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_result = malloc(__pyx_v_size); 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+ + /* "View.MemoryView":1241 + * cdef __Pyx_memviewslice tmp + * + * if src_ndim < dst_ndim: # <<<<<<<<<<<<<< + * broadcast_leading(&src, src_ndim, dst_ndim) + * elif dst_ndim < src_ndim: + */ goto __pyx_L3; } - /* "View.MemoryView":1240 + /* "View.MemoryView":1243 * if src_ndim < dst_ndim: * broadcast_leading(&src, src_ndim, dst_ndim) * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< @@ -14734,7 +15644,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((__pyx_v_dst_ndim < __pyx_v_src_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1241 + /* "View.MemoryView":1244 * broadcast_leading(&src, src_ndim, dst_ndim) * elif dst_ndim < src_ndim: * broadcast_leading(&dst, dst_ndim, src_ndim) # <<<<<<<<<<<<<< @@ -14742,11 +15652,18 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * cdef int ndim = max(src_ndim, dst_ndim) */ __pyx_memoryview_broadcast_leading((&__pyx_v_dst), __pyx_v_dst_ndim, __pyx_v_src_ndim); - goto __pyx_L3; + + /* "View.MemoryView":1243 + * if src_ndim < dst_ndim: + * broadcast_leading(&src, src_ndim, dst_ndim) + * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< + * broadcast_leading(&dst, dst_ndim, src_ndim) + * + */ } __pyx_L3:; - /* "View.MemoryView":1243 + /* "View.MemoryView":1246 * broadcast_leading(&dst, dst_ndim, src_ndim) * * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< @@ -14762,7 +15679,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_v_ndim = __pyx_t_5; - /* "View.MemoryView":1245 + /* "View.MemoryView":1248 * cdef int ndim = max(src_ndim, dst_ndim) * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -14773,7 +15690,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_5; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1246 + /* "View.MemoryView":1249 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< @@ -14783,7 +15700,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1247 + /* "View.MemoryView":1250 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< @@ -14793,7 +15710,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1248 + /* "View.MemoryView":1251 * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: * broadcasting = True # <<<<<<<<<<<<<< @@ -14802,7 +15719,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_broadcasting = 1; - /* "View.MemoryView":1249 + /* "View.MemoryView":1252 * if src.shape[i] == 1: * broadcasting = True * src.strides[i] = 0 # <<<<<<<<<<<<<< @@ -14810,25 +15727,39 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * _err_extents(i, dst.shape[i], src.shape[i]) */ (__pyx_v_src.strides[__pyx_v_i]) = 0; + + /* "View.MemoryView":1250 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ goto __pyx_L7; } - /*else*/ { - /* "View.MemoryView":1251 + /* "View.MemoryView":1254 * src.strides[i] = 0 * else: * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< * * if src.suboffsets[i] >= 0: */ - __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1251; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + /*else*/ { + __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1254; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_L7:; - goto __pyx_L6; - } - __pyx_L6:; - /* "View.MemoryView":1253 + /* "View.MemoryView":1249 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + } + + /* "View.MemoryView":1256 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< @@ -14838,20 +15769,26 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1254 + /* "View.MemoryView":1257 * * if src.suboffsets[i] >= 0: * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< * * if slices_overlap(&src, &dst, ndim, itemsize): */ - __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Dimension_d_is_not_direct, __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1254; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - goto __pyx_L8; + __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Dimension_d_is_not_direct, __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":1256 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ } - __pyx_L8:; } - /* "View.MemoryView":1256 + /* "View.MemoryView":1259 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< @@ -14861,7 +15798,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1258 + /* "View.MemoryView":1261 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(&src, order, ndim): # <<<<<<<<<<<<<< @@ -14871,7 +15808,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((!(__pyx_memviewslice_is_contig((&__pyx_v_src), __pyx_v_order, __pyx_v_ndim) != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1259 + /* "View.MemoryView":1262 * * if not slice_is_contig(&src, order, ndim): * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< @@ -14879,21 +15816,27 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) */ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); - goto __pyx_L10; - } - __pyx_L10:; - /* "View.MemoryView":1261 + /* "View.MemoryView":1261 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(&src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + } + + /* "View.MemoryView":1264 * order = get_best_order(&dst, ndim) * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< * src = tmp * */ - __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1261; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1264; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_tmpdata = __pyx_t_6; - /* "View.MemoryView":1262 + /* "View.MemoryView":1265 * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) * src = tmp # <<<<<<<<<<<<<< @@ -14901,11 +15844,17 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * if not broadcasting: */ __pyx_v_src = __pyx_v_tmp; - goto __pyx_L9; - } - __pyx_L9:; - /* "View.MemoryView":1264 + /* "View.MemoryView":1259 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(&src, order, ndim): + */ + } + + /* "View.MemoryView":1267 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< @@ -14915,7 +15864,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1267 + /* "View.MemoryView":1270 * * * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<< @@ -14925,7 +15874,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1268 + /* "View.MemoryView":1271 * * if slice_is_contig(&src, 'C', ndim): * direct_copy = slice_is_contig(&dst, 'C', ndim) # <<<<<<<<<<<<<< @@ -14933,10 +15882,18 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * direct_copy = slice_is_contig(&dst, 'F', ndim) */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'C', __pyx_v_ndim); + + /* "View.MemoryView":1270 + * + * + * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): + */ goto __pyx_L12; } - /* "View.MemoryView":1269 + /* "View.MemoryView":1272 * if slice_is_contig(&src, 'C', ndim): * direct_copy = slice_is_contig(&dst, 'C', ndim) * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<< @@ -14946,7 +15903,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1270 + /* "View.MemoryView":1273 * direct_copy = slice_is_contig(&dst, 'C', ndim) * elif slice_is_contig(&src, 'F', ndim): * direct_copy = slice_is_contig(&dst, 'F', ndim) # <<<<<<<<<<<<<< @@ -14954,11 +15911,18 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * if direct_copy: */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'F', __pyx_v_ndim); - goto __pyx_L12; + + /* "View.MemoryView":1272 + * if slice_is_contig(&src, 'C', ndim): + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(&dst, 'F', ndim) + * + */ } __pyx_L12:; - /* "View.MemoryView":1272 + /* "View.MemoryView":1275 * direct_copy = slice_is_contig(&dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< @@ -14968,7 +15932,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_v_direct_copy != 0); if (__pyx_t_2) { - /* "View.MemoryView":1274 + /* "View.MemoryView":1277 * if direct_copy: * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -14977,7 +15941,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - /* "View.MemoryView":1275 + /* "View.MemoryView":1278 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< @@ -14986,7 +15950,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); - /* "View.MemoryView":1276 + /* "View.MemoryView":1279 * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -14995,7 +15959,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - /* "View.MemoryView":1277 + /* "View.MemoryView":1280 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< @@ -15004,7 +15968,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1278 + /* "View.MemoryView":1281 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -15013,12 +15977,26 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_r = 0; goto __pyx_L0; - } - goto __pyx_L11; - } - __pyx_L11:; - /* "View.MemoryView":1280 + /* "View.MemoryView":1275 + * direct_copy = slice_is_contig(&dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + } + + /* "View.MemoryView":1267 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1283 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< @@ -15032,28 +16010,34 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_7 = (__pyx_t_2 != 0); if (__pyx_t_7) { - /* "View.MemoryView":1283 + /* "View.MemoryView":1286 * * * transpose_memslice(&src) # <<<<<<<<<<<<<< * transpose_memslice(&dst) * */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1286; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":1284 + /* "View.MemoryView":1287 * * transpose_memslice(&src) * transpose_memslice(&dst) # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - goto __pyx_L14; - } - __pyx_L14:; + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1287; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":1286 + /* "View.MemoryView":1283 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1289 * transpose_memslice(&dst) * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -15062,7 +16046,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - /* "View.MemoryView":1287 + /* "View.MemoryView":1290 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< @@ -15071,7 +16055,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); - /* "View.MemoryView":1288 + /* "View.MemoryView":1291 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -15080,7 +16064,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - /* "View.MemoryView":1290 + /* "View.MemoryView":1293 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< @@ -15089,7 +16073,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1291 + /* "View.MemoryView":1294 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -15099,7 +16083,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":1222 + /* "View.MemoryView":1225 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< @@ -15123,21 +16107,21 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ return __pyx_r; } -/* "View.MemoryView":1294 +/* "View.MemoryView":1297 * * @cname('__pyx_memoryview_broadcast_leading') - * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<< + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ -static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice, int __pyx_v_ndim, int __pyx_v_ndim_other) { +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { int __pyx_v_i; int __pyx_v_offset; int __pyx_t_1; int __pyx_t_2; - /* "View.MemoryView":1298 + /* "View.MemoryView":1301 * int ndim_other) nogil: * cdef int i * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< @@ -15146,87 +16130,87 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice */ __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); - /* "View.MemoryView":1300 + /* "View.MemoryView":1303 * cdef int offset = ndim_other - ndim * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< - * slice.shape[i + offset] = slice.shape[i] - * slice.strides[i + offset] = slice.strides[i] + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] */ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":1301 + /* "View.MemoryView":1304 * * for i in range(ndim - 1, -1, -1): - * slice.shape[i + offset] = slice.shape[i] # <<<<<<<<<<<<<< - * slice.strides[i + offset] = slice.strides[i] - * slice.suboffsets[i + offset] = slice.suboffsets[i] + * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] */ - (__pyx_v_slice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->shape[__pyx_v_i]); + (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); - /* "View.MemoryView":1302 + /* "View.MemoryView":1305 * for i in range(ndim - 1, -1, -1): - * slice.shape[i + offset] = slice.shape[i] - * slice.strides[i + offset] = slice.strides[i] # <<<<<<<<<<<<<< - * slice.suboffsets[i + offset] = slice.suboffsets[i] + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * */ - (__pyx_v_slice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->strides[__pyx_v_i]); + (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1303 - * slice.shape[i + offset] = slice.shape[i] - * slice.strides[i + offset] = slice.strides[i] - * slice.suboffsets[i + offset] = slice.suboffsets[i] # <<<<<<<<<<<<<< + /* "View.MemoryView":1306 + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< * * for i in range(offset): */ - (__pyx_v_slice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->suboffsets[__pyx_v_i]); + (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); } - /* "View.MemoryView":1305 - * slice.suboffsets[i + offset] = slice.suboffsets[i] + /* "View.MemoryView":1308 + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * * for i in range(offset): # <<<<<<<<<<<<<< - * slice.shape[i] = 1 - * slice.strides[i] = slice.strides[0] + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] */ __pyx_t_1 = __pyx_v_offset; for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { __pyx_v_i = __pyx_t_2; - /* "View.MemoryView":1306 + /* "View.MemoryView":1309 * * for i in range(offset): - * slice.shape[i] = 1 # <<<<<<<<<<<<<< - * slice.strides[i] = slice.strides[0] - * slice.suboffsets[i] = -1 + * mslice.shape[i] = 1 # <<<<<<<<<<<<<< + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 */ - (__pyx_v_slice->shape[__pyx_v_i]) = 1; + (__pyx_v_mslice->shape[__pyx_v_i]) = 1; - /* "View.MemoryView":1307 + /* "View.MemoryView":1310 * for i in range(offset): - * slice.shape[i] = 1 - * slice.strides[i] = slice.strides[0] # <<<<<<<<<<<<<< - * slice.suboffsets[i] = -1 + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< + * mslice.suboffsets[i] = -1 * */ - (__pyx_v_slice->strides[__pyx_v_i]) = (__pyx_v_slice->strides[0]); + (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); - /* "View.MemoryView":1308 - * slice.shape[i] = 1 - * slice.strides[i] = slice.strides[0] - * slice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + /* "View.MemoryView":1311 + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< * * */ - (__pyx_v_slice->suboffsets[__pyx_v_i]) = -1; + (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1; } - /* "View.MemoryView":1294 + /* "View.MemoryView":1297 * * @cname('__pyx_memoryview_broadcast_leading') - * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<< + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ @@ -15234,7 +16218,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice /* function exit code */ } -/* "View.MemoryView":1316 +/* "View.MemoryView":1319 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -15245,7 +16229,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) { int __pyx_t_1; - /* "View.MemoryView":1320 + /* "View.MemoryView":1323 * * * if dtype_is_object: # <<<<<<<<<<<<<< @@ -15255,7 +16239,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i __pyx_t_1 = (__pyx_v_dtype_is_object != 0); if (__pyx_t_1) { - /* "View.MemoryView":1321 + /* "View.MemoryView":1324 * * if dtype_is_object: * refcount_objects_in_slice_with_gil(dst.data, dst.shape, # <<<<<<<<<<<<<< @@ -15263,11 +16247,17 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i * */ __pyx_memoryview_refcount_objects_in_slice_with_gil(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_inc); - goto __pyx_L3; - } - __pyx_L3:; - /* "View.MemoryView":1316 + /* "View.MemoryView":1323 + * + * + * if dtype_is_object: # <<<<<<<<<<<<<< + * refcount_objects_in_slice_with_gil(dst.data, dst.shape, + * dst.strides, ndim, inc) + */ + } + + /* "View.MemoryView":1319 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -15278,7 +16268,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i /* function exit code */ } -/* "View.MemoryView":1325 +/* "View.MemoryView":1328 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -15293,7 +16283,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da #endif __Pyx_RefNannySetupContext("refcount_objects_in_slice_with_gil", 0); - /* "View.MemoryView":1328 + /* "View.MemoryView":1331 * Py_ssize_t *strides, int ndim, * bint inc) with gil: * refcount_objects_in_slice(data, shape, strides, ndim, inc) # <<<<<<<<<<<<<< @@ -15302,7 +16292,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da */ __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, __pyx_v_shape, __pyx_v_strides, __pyx_v_ndim, __pyx_v_inc); - /* "View.MemoryView":1325 + /* "View.MemoryView":1328 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -15317,7 +16307,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da #endif } -/* "View.MemoryView":1331 +/* "View.MemoryView":1334 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -15333,7 +16323,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss int __pyx_t_3; __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0); - /* "View.MemoryView":1335 + /* "View.MemoryView":1338 * cdef Py_ssize_t i * * for i in range(shape[0]): # <<<<<<<<<<<<<< @@ -15344,7 +16334,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { __pyx_v_i = __pyx_t_2; - /* "View.MemoryView":1336 + /* "View.MemoryView":1339 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< @@ -15354,7 +16344,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_3 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_3) { - /* "View.MemoryView":1337 + /* "View.MemoryView":1340 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< @@ -15364,7 +16354,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_3 = (__pyx_v_inc != 0); if (__pyx_t_3) { - /* "View.MemoryView":1338 + /* "View.MemoryView":1341 * if ndim == 1: * if inc: * Py_INCREF(( data)[0]) # <<<<<<<<<<<<<< @@ -15372,36 +16362,60 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss * Py_DECREF(( data)[0]) */ Py_INCREF((((PyObject **)__pyx_v_data)[0])); - goto __pyx_L6; - } - /*else*/ { /* "View.MemoryView":1340 + * for i in range(shape[0]): + * if ndim == 1: + * if inc: # <<<<<<<<<<<<<< + * Py_INCREF(( data)[0]) + * else: + */ + goto __pyx_L6; + } + + /* "View.MemoryView":1343 * Py_INCREF(( data)[0]) * else: * Py_DECREF(( data)[0]) # <<<<<<<<<<<<<< * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, */ + /*else*/ { Py_DECREF((((PyObject **)__pyx_v_data)[0])); } __pyx_L6:; + + /* "View.MemoryView":1339 + * + * for i in range(shape[0]): + * if ndim == 1: # <<<<<<<<<<<<<< + * if inc: + * Py_INCREF(( data)[0]) + */ goto __pyx_L5; } - /*else*/ { - /* "View.MemoryView":1342 + /* "View.MemoryView":1345 * Py_DECREF(( data)[0]) * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< * ndim - 1, inc) * + */ + /*else*/ { + + /* "View.MemoryView":1346 + * else: + * refcount_objects_in_slice(data, shape + 1, strides + 1, + * ndim - 1, inc) # <<<<<<<<<<<<<< + * + * data += strides[0] */ __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_inc); } __pyx_L5:; - /* "View.MemoryView":1345 + /* "View.MemoryView":1348 * ndim - 1, inc) * * data += strides[0] # <<<<<<<<<<<<<< @@ -15411,7 +16425,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_v_data = (__pyx_v_data + (__pyx_v_strides[0])); } - /* "View.MemoryView":1331 + /* "View.MemoryView":1334 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -15423,7 +16437,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1351 +/* "View.MemoryView":1354 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -15433,7 +16447,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) { - /* "View.MemoryView":1354 + /* "View.MemoryView":1357 * size_t itemsize, void *item, * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -15442,7 +16456,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - /* "View.MemoryView":1355 + /* "View.MemoryView":1358 * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<< @@ -15451,7 +16465,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst */ __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item); - /* "View.MemoryView":1357 + /* "View.MemoryView":1360 * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -15460,7 +16474,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - /* "View.MemoryView":1351 + /* "View.MemoryView":1354 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -15471,7 +16485,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst /* function exit code */ } -/* "View.MemoryView":1361 +/* "View.MemoryView":1364 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -15487,7 +16501,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t Py_ssize_t __pyx_t_2; Py_ssize_t __pyx_t_3; - /* "View.MemoryView":1365 + /* "View.MemoryView":1368 * size_t itemsize, void *item) nogil: * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< @@ -15496,7 +16510,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_stride = (__pyx_v_strides[0]); - /* "View.MemoryView":1366 + /* "View.MemoryView":1369 * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< @@ -15505,7 +16519,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_extent = (__pyx_v_shape[0]); - /* "View.MemoryView":1368 + /* "View.MemoryView":1371 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -15515,7 +16529,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1369 + /* "View.MemoryView":1372 * * if ndim == 1: * for i in range(extent): # <<<<<<<<<<<<<< @@ -15526,7 +16540,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1370 + /* "View.MemoryView":1373 * if ndim == 1: * for i in range(extent): * memcpy(data, item, itemsize) # <<<<<<<<<<<<<< @@ -15535,7 +16549,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize); - /* "View.MemoryView":1371 + /* "View.MemoryView":1374 * for i in range(extent): * memcpy(data, item, itemsize) * data += stride # <<<<<<<<<<<<<< @@ -15544,22 +16558,30 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_data = (__pyx_v_data + __pyx_v_stride); } + + /* "View.MemoryView":1371 + * cdef Py_ssize_t extent = shape[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * for i in range(extent): + * memcpy(data, item, itemsize) + */ goto __pyx_L3; } - /*else*/ { - /* "View.MemoryView":1373 + /* "View.MemoryView":1376 * data += stride * else: * for i in range(extent): # <<<<<<<<<<<<<< * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) */ + /*else*/ { __pyx_t_2 = __pyx_v_extent; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1374 + /* "View.MemoryView":1377 * else: * for i in range(extent): * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -15568,7 +16590,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item); - /* "View.MemoryView":1376 + /* "View.MemoryView":1379 * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) * data += stride # <<<<<<<<<<<<<< @@ -15580,7 +16602,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t } __pyx_L3:; - /* "View.MemoryView":1361 + /* "View.MemoryView":1364 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -15717,8 +16739,9 @@ static PyTypeObject __pyx_type___pyx_array = { 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ - #else - 0, /*reserved*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ @@ -15822,8 +16845,9 @@ static PyTypeObject __pyx_type___pyx_MemviewEnum = { 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ - #else - 0, /*reserved*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ #endif __pyx_MemviewEnum___repr__, /*tp_repr*/ 0, /*tp_as_number*/ @@ -16068,8 +17092,9 @@ static PyTypeObject __pyx_type___pyx_memoryview = { 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ - #else - 0, /*reserved*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ #endif __pyx_memoryview___repr__, /*tp_repr*/ 0, /*tp_as_number*/ @@ -16192,8 +17217,9 @@ static PyTypeObject __pyx_type___pyx_memoryviewslice = { 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ - #else - 0, /*reserved*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ #endif #if CYTHON_COMPILING_IN_PYPY __pyx_memoryview___repr__, /*tp_repr*/ @@ -16269,6 +17295,7 @@ static struct PyModuleDef __pyx_moduledef = { #endif static __Pyx_StringTabEntry __pyx_string_tab[] = { + {&__pyx_n_s_ASCII, __pyx_k_ASCII, sizeof(__pyx_k_ASCII), 0, 0, 1, 1}, {&__pyx_kp_s_Buffer_view_does_not_expose_stri, __pyx_k_Buffer_view_does_not_expose_stri, sizeof(__pyx_k_Buffer_view_does_not_expose_stri), 0, 0, 1, 0}, {&__pyx_kp_s_Can_only_create_a_buffer_that_is, __pyx_k_Can_only_create_a_buffer_that_is, sizeof(__pyx_k_Can_only_create_a_buffer_that_is), 0, 0, 1, 0}, {&__pyx_kp_s_Cannot_index_with_type_s, __pyx_k_Cannot_index_with_type_s, sizeof(__pyx_k_Cannot_index_with_type_s), 0, 0, 1, 0}, @@ -16309,6 +17336,7 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_n_s_d, __pyx_k_d, sizeof(__pyx_k_d), 0, 0, 1, 1}, {&__pyx_n_s_dist, __pyx_k_dist, sizeof(__pyx_k_dist), 0, 0, 1, 1}, {&__pyx_n_s_dtype_is_object, __pyx_k_dtype_is_object, sizeof(__pyx_k_dtype_is_object), 0, 0, 1, 1}, + {&__pyx_n_s_encode, __pyx_k_encode, sizeof(__pyx_k_encode), 0, 0, 1, 1}, {&__pyx_n_s_enumerate, __pyx_k_enumerate, sizeof(__pyx_k_enumerate), 0, 0, 1, 1}, {&__pyx_n_s_error, __pyx_k_error, sizeof(__pyx_k_error), 0, 0, 1, 1}, {&__pyx_n_s_flags, __pyx_k_flags, sizeof(__pyx_k_flags), 0, 0, 1, 1}, @@ -16321,7 +17349,7 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_n_s_grad_X, __pyx_k_grad_X, sizeof(__pyx_k_grad_X), 0, 0, 1, 1}, {&__pyx_n_s_grad_X_cython, __pyx_k_grad_X_cython, sizeof(__pyx_k_grad_X_cython), 0, 0, 1, 1}, {&__pyx_n_s_gradq, __pyx_k_gradq, sizeof(__pyx_k_gradq), 0, 0, 1, 1}, - {&__pyx_kp_s_home_james_work_GPy_GPy_kern__s, __pyx_k_home_james_work_GPy_GPy_kern__s, sizeof(__pyx_k_home_james_work_GPy_GPy_kern__s), 0, 0, 1, 0}, + {&__pyx_kp_s_home_david_gits_GPy_GPy_kern__s, __pyx_k_home_david_gits_GPy_GPy_kern__s, sizeof(__pyx_k_home_david_gits_GPy_GPy_kern__s), 0, 0, 1, 0}, {&__pyx_n_s_id, __pyx_k_id, sizeof(__pyx_k_id), 0, 0, 1, 1}, {&__pyx_n_s_import, __pyx_k_import, sizeof(__pyx_k_import), 0, 0, 1, 1}, {&__pyx_n_s_itemsize, __pyx_k_itemsize, sizeof(__pyx_k_itemsize), 0, 0, 1, 1}, @@ -16363,24 +17391,18 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_kp_s_unable_to_allocate_shape_and_str, __pyx_k_unable_to_allocate_shape_and_str, sizeof(__pyx_k_unable_to_allocate_shape_and_str), 0, 0, 1, 0}, {&__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_k_unknown_dtype_code_in_numpy_pxd, sizeof(__pyx_k_unknown_dtype_code_in_numpy_pxd), 0, 1, 0, 0}, {&__pyx_n_s_unpack, __pyx_k_unpack, sizeof(__pyx_k_unpack), 0, 0, 1, 1}, - {&__pyx_n_s_xrange, __pyx_k_xrange, sizeof(__pyx_k_xrange), 0, 0, 1, 1}, {0, 0, 0, 0, 0, 0, 0} }; static int __Pyx_InitCachedBuiltins(void) { - __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 33; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 36; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_RuntimeError = __Pyx_GetBuiltinName(__pyx_n_s_RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_MemoryError = __Pyx_GetBuiltinName(__pyx_n_s_MemoryError); if (!__pyx_builtin_MemoryError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_Ellipsis = __Pyx_GetBuiltinName(__pyx_n_s_Ellipsis); if (!__pyx_builtin_Ellipsis) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 357; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_TypeError = __Pyx_GetBuiltinName(__pyx_n_s_TypeError); if (!__pyx_builtin_TypeError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - #if PY_MAJOR_VERSION >= 3 - __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - #else - __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - #endif - __pyx_builtin_id = __Pyx_GetBuiltinName(__pyx_n_s_id); if (!__pyx_builtin_id) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 569; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_IndexError = __Pyx_GetBuiltinName(__pyx_n_s_IndexError); if (!__pyx_builtin_IndexError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_MemoryError = __Pyx_GetBuiltinName(__pyx_n_s_MemoryError); if (!__pyx_builtin_MemoryError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_Ellipsis = __Pyx_GetBuiltinName(__pyx_n_s_Ellipsis); if (!__pyx_builtin_Ellipsis) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 359; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_TypeError = __Pyx_GetBuiltinName(__pyx_n_s_TypeError); if (!__pyx_builtin_TypeError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 388; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_id = __Pyx_GetBuiltinName(__pyx_n_s_id); if (!__pyx_builtin_id) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 571; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_IndexError = __Pyx_GetBuiltinName(__pyx_n_s_IndexError); if (!__pyx_builtin_IndexError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 790; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; __pyx_L1_error:; return -1; @@ -16390,40 +17412,40 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__Pyx_InitCachedConstants", 0); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) */ - __pyx_tuple_ = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_C_contiguous); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple_ = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_C_contiguous); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple_); __Pyx_GIVEREF(__pyx_tuple_); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< * * info.buf = PyArray_DATA(self) */ - __pyx_tuple__2 = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_Fortran_contiguou); if (unlikely(!__pyx_tuple__2)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__2 = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_Fortran_contiguou); if (unlikely(!__pyx_tuple__2)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__2); __Pyx_GIVEREF(__pyx_tuple__2); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_u_Non_native_byte_order_not_suppor); if (unlikely(!__pyx_tuple__3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_u_Non_native_byte_order_not_suppor); if (unlikely(!__pyx_tuple__3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__3); __Pyx_GIVEREF(__pyx_tuple__3); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< @@ -16434,7 +17456,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__4); __Pyx_GIVEREF(__pyx_tuple__4); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -16445,7 +17467,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__5); __Pyx_GIVEREF(__pyx_tuple__5); - /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 + /* "../../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 * t = child.type_num * if end - f < 5: * raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<< @@ -16456,229 +17478,254 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__6); __Pyx_GIVEREF(__pyx_tuple__6); - /* "View.MemoryView":127 + /* "View.MemoryView":129 * * if not self.ndim: * raise ValueError("Empty shape tuple for cython.array") # <<<<<<<<<<<<<< * * if itemsize <= 0: */ - __pyx_tuple__7 = PyTuple_Pack(1, __pyx_kp_s_Empty_shape_tuple_for_cython_arr); if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__7 = PyTuple_Pack(1, __pyx_kp_s_Empty_shape_tuple_for_cython_arr); if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 129; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__7); __Pyx_GIVEREF(__pyx_tuple__7); - /* "View.MemoryView":130 + /* "View.MemoryView":132 * * if itemsize <= 0: * raise ValueError("itemsize <= 0 for cython.array") # <<<<<<<<<<<<<< * - * if isinstance(format, unicode): + * if not isinstance(format, bytes): */ - __pyx_tuple__8 = PyTuple_Pack(1, __pyx_kp_s_itemsize_0_for_cython_array); if (unlikely(!__pyx_tuple__8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 130; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__8 = PyTuple_Pack(1, __pyx_kp_s_itemsize_0_for_cython_array); if (unlikely(!__pyx_tuple__8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__8); __Pyx_GIVEREF(__pyx_tuple__8); - /* "View.MemoryView":142 + /* "View.MemoryView":135 + * + * if not isinstance(format, bytes): + * format = format.encode('ASCII') # <<<<<<<<<<<<<< + * self._format = format # keep a reference to the byte string + * self.format = self._format + */ + __pyx_tuple__9 = PyTuple_Pack(1, __pyx_n_s_ASCII); 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if (unlikely(!__pyx_tuple__28)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_tuple__28); - __Pyx_GIVEREF(__pyx_tuple__28); + __pyx_tuple__30 = PyTuple_Pack(1, __pyx_kp_s_strided_and_indirect); if (unlikely(!__pyx_tuple__30)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 280; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__30); + __Pyx_GIVEREF(__pyx_tuple__30); - /* "View.MemoryView":281 + /* "View.MemoryView":283 * * * cdef contiguous = Enum("") # <<<<<<<<<<<<<< * cdef indirect_contiguous = Enum("") * */ - __pyx_tuple__29 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_direct); if (unlikely(!__pyx_tuple__29)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_tuple__29); - __Pyx_GIVEREF(__pyx_tuple__29); + __pyx_tuple__31 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_direct); if (unlikely(!__pyx_tuple__31)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__31); + __Pyx_GIVEREF(__pyx_tuple__31); - /* "View.MemoryView":282 + /* "View.MemoryView":284 * * cdef contiguous = Enum("") * cdef indirect_contiguous = Enum("") # <<<<<<<<<<<<<< * * */ - __pyx_tuple__30 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_indirect); if (unlikely(!__pyx_tuple__30)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_tuple__30); - __Pyx_GIVEREF(__pyx_tuple__30); + __pyx_tuple__32 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_indirect); if (unlikely(!__pyx_tuple__32)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__32); + __Pyx_GIVEREF(__pyx_tuple__32); __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -16726,18 +17773,24 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) } #endif __Pyx_RefNannySetupContext("PyMODINIT_FUNC PyInit_stationary_cython(void)", 0); - if ( __Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_empty_tuple = PyTuple_New(0); if (unlikely(!__pyx_empty_tuple)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_empty_bytes = PyBytes_FromStringAndSize("", 0); if (unlikely(!__pyx_empty_bytes)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #ifdef __Pyx_CyFunction_USED - if (__Pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif #ifdef __Pyx_FusedFunction_USED if (__pyx_FusedFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif + #ifdef __Pyx_Coroutine_USED + if (__pyx_Coroutine_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif #ifdef __Pyx_Generator_USED if (__pyx_Generator_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif + #ifdef __Pyx_StopAsyncIteration_USED + if (__pyx_StopAsyncIteration_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif /*--- Library function declarations ---*/ /*--- Threads initialization code ---*/ #if defined(__PYX_FORCE_INIT_THREADS) && __PYX_FORCE_INIT_THREADS @@ -16760,12 +17813,12 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) #endif if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; /*--- Initialize various global constants etc. ---*/ - if (unlikely(__Pyx_InitGlobals() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitGlobals() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #if PY_MAJOR_VERSION < 3 && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if (__Pyx_init_sys_getdefaultencoding_params() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif if (__pyx_module_is_main_GPy__kern___src__stationary_cython) { - if (PyObject_SetAttrString(__pyx_m, "__name__", __pyx_n_s_main) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + if (PyObject_SetAttrString(__pyx_m, "__name__", __pyx_n_s_main) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } #if PY_MAJOR_VERSION >= 3 { @@ -16776,9 +17829,9 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) } #endif /*--- Builtin init code ---*/ - if (unlikely(__Pyx_InitCachedBuiltins() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitCachedBuiltins() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Constants init code ---*/ - if (unlikely(__Pyx_InitCachedConstants() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitCachedConstants() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Global init code ---*/ generic = Py_None; Py_INCREF(Py_None); strided = Py_None; Py_INCREF(Py_None); @@ -16788,10 +17841,10 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) /*--- Variable export code ---*/ /*--- Function export code ---*/ /*--- Type init code ---*/ - if (PyType_Ready(&__pyx_type___pyx_array) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 99; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyType_Ready(&__pyx_type___pyx_array) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_type___pyx_array.tp_print = 0; __pyx_array_type = &__pyx_type___pyx_array; - if (PyType_Ready(&__pyx_type___pyx_MemviewEnum) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 269; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyType_Ready(&__pyx_type___pyx_MemviewEnum) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_type___pyx_MemviewEnum.tp_print = 0; __pyx_MemviewEnum_type = &__pyx_type___pyx_MemviewEnum; __pyx_vtabptr_memoryview = &__pyx_vtable_memoryview; @@ -16802,18 +17855,18 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) __pyx_vtable_memoryview.setitem_indexed = (PyObject *(*)(struct __pyx_memoryview_obj *, PyObject *, PyObject *))__pyx_memoryview_setitem_indexed; __pyx_vtable_memoryview.convert_item_to_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *))__pyx_memoryview_convert_item_to_object; __pyx_vtable_memoryview.assign_item_from_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *, PyObject *))__pyx_memoryview_assign_item_from_object; - if (PyType_Ready(&__pyx_type___pyx_memoryview) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 302; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyType_Ready(&__pyx_type___pyx_memoryview) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 304; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_type___pyx_memoryview.tp_print = 0; - if (__Pyx_SetVtable(__pyx_type___pyx_memoryview.tp_dict, __pyx_vtabptr_memoryview) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 302; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_SetVtable(__pyx_type___pyx_memoryview.tp_dict, __pyx_vtabptr_memoryview) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 304; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_memoryview_type = &__pyx_type___pyx_memoryview; __pyx_vtabptr__memoryviewslice = &__pyx_vtable__memoryviewslice; __pyx_vtable__memoryviewslice.__pyx_base = *__pyx_vtabptr_memoryview; __pyx_vtable__memoryviewslice.__pyx_base.convert_item_to_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *))__pyx_memoryviewslice_convert_item_to_object; __pyx_vtable__memoryviewslice.__pyx_base.assign_item_from_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *, PyObject *))__pyx_memoryviewslice_assign_item_from_object; __pyx_type___pyx_memoryviewslice.tp_base = __pyx_memoryview_type; - if (PyType_Ready(&__pyx_type___pyx_memoryviewslice) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 922; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyType_Ready(&__pyx_type___pyx_memoryviewslice) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 923; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_type___pyx_memoryviewslice.tp_print = 0; - if (__Pyx_SetVtable(__pyx_type___pyx_memoryviewslice.tp_dict, __pyx_vtabptr__memoryviewslice) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 922; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_SetVtable(__pyx_type___pyx_memoryviewslice.tp_dict, __pyx_vtabptr__memoryviewslice) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 923; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_memoryviewslice_type = &__pyx_type___pyx_memoryviewslice; /*--- Type import code ---*/ __pyx_ptype_7cpython_4type_type = __Pyx_ImportType(__Pyx_BUILTIN_MODULE_NAME, "type", @@ -16824,13 +17877,16 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) #endif 0); if (unlikely(!__pyx_ptype_7cpython_4type_type)) {__pyx_filename = __pyx_f[3]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr), 0); if (unlikely(!__pyx_ptype_5numpy_dtype)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 155; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 169; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 168; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 172; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 861; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Variable import code ---*/ /*--- Function import code ---*/ /*--- Execution code ---*/ + #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) + if (__Pyx_patch_abc() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif /* "GPy/kern/_src/stationary_cython.pyx":4 * #cython: nonecheck=False @@ -16844,52 +17900,52 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) if (PyDict_SetItem(__pyx_d, __pyx_n_s_np, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/stationary_cython.pyx":16 - * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) + /* "GPy/kern/_src/stationary_cython.pyx":17 + * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) nogil * * def grad_X(int N, int D, int M, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _X, * np.ndarray[DTYPE_t, ndim=2] _X2, */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_1grad_X, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_1grad_X, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_grad_X, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_grad_X, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/stationary_cython.pyx":27 - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + /* "GPy/kern/_src/stationary_cython.pyx":30 * + * @cython.cdivision(True) * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): # <<<<<<<<<<<<<< * cdef int n,d,nd,m - * for nd in prange(N*D, nogil=True): + * for nd in prange(N * D, nogil=True): */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_3grad_X_cython, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_3grad_X_cython, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_grad_X_cython, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_grad_X_cython, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/stationary_cython.pyx":38 - * + /* "GPy/kern/_src/stationary_cython.pyx":39 + * grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) * * def lengthscale_grads_in_c(int N, int M, int Q, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _tmp, * np.ndarray[DTYPE_t, ndim=2] _X, */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_5lengthscale_grads_in_c, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_5lengthscale_grads_in_c, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_lengthscale_grads_in_c, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_lengthscale_grads_in_c, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/kern/_src/stationary_cython.pyx":49 - * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. + /* "GPy/kern/_src/stationary_cython.pyx":51 + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. * * def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): # <<<<<<<<<<<<<< * cdef int q, n, m * cdef double gradq, dist */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_7lengthscale_grads, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4kern_4_src_17stationary_cython_7lengthscale_grads, NULL, __pyx_n_s_GPy_kern__src_stationary_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_lengthscale_grads, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_lengthscale_grads, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 51; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/kern/_src/stationary_cython.pyx":1 @@ -16902,116 +17958,116 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":203 + /* "View.MemoryView":205 * info.obj = self * * __pyx_getbuffer = capsule( &__pyx_array_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * def __dealloc__(array self): */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_array_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_array_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 205; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_array_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_array_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 205; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_array_type); - /* "View.MemoryView":276 + /* "View.MemoryView":278 * return self.name * * cdef generic = Enum("") # <<<<<<<<<<<<<< * cdef strided = Enum("") # default * cdef indirect = Enum("") */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__26, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__28, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(generic); __Pyx_DECREF_SET(generic, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":277 + /* "View.MemoryView":279 * * cdef generic = Enum("") * cdef strided = Enum("") # default # <<<<<<<<<<<<<< * cdef indirect = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__27, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 277; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__29, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(strided); __Pyx_DECREF_SET(strided, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":278 + /* "View.MemoryView":280 * cdef generic = Enum("") * cdef strided = Enum("") # default * cdef indirect = Enum("") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__28, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 280; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(indirect); __Pyx_DECREF_SET(indirect, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":281 + /* "View.MemoryView":283 * * * cdef contiguous = Enum("") # <<<<<<<<<<<<<< * cdef indirect_contiguous = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__29, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__31, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(contiguous); __Pyx_DECREF_SET(contiguous, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":282 + /* "View.MemoryView":284 * * cdef contiguous = Enum("") * cdef indirect_contiguous = Enum("") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__32, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(indirect_contiguous); __Pyx_DECREF_SET(indirect_contiguous, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - /* "View.MemoryView":496 + /* "View.MemoryView":498 * info.obj = self * * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 498; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 498; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_memoryview_type); - /* "View.MemoryView":953 + /* "View.MemoryView":954 * return self.from_object * * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 954; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 954; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_memoryviewslice_type); - /* "View.MemoryView":1361 + /* "View.MemoryView":1364 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -17027,7 +18083,6 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) if (__pyx_m) { if (__pyx_d) { __Pyx_AddTraceback("init GPy.kern._src.stationary_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); - Py_DECREF(__pyx_d); __pyx_d = 0; } Py_DECREF(__pyx_m); __pyx_m = 0; } else if (!PyErr_Occurred()) { @@ -17042,7 +18097,7 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) #endif } -/* Runtime support code */ +/* --- Runtime support code --- */ #if CYTHON_REFNANNY static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { PyObject *m = NULL, *p = NULL; @@ -17817,19 +18872,6 @@ static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyOb #endif } -static CYTHON_INLINE int __Pyx_div_int(int a, int b) { - int q = a / b; - int r = a - q*b; - q -= ((r != 0) & ((r ^ b) < 0)); - return q; -} - -static CYTHON_INLINE int __Pyx_mod_int(int a, int b) { - int r = a % b; - r += ((r != 0) & ((r ^ b) < 0)) * b; - return r; -} - static int __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int ndim, @@ -17886,7 +18928,6 @@ no_fail: static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) { va_list vargs; char msg[200]; - va_start(vargs, fmt); #ifdef HAVE_STDARG_PROTOTYPES va_start(vargs, fmt); #else @@ -18058,10 +19099,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject if (value && PyExceptionInstance_Check(value)) { instance_class = (PyObject*) Py_TYPE(value); if (instance_class != type) { - if (PyObject_IsSubclass(instance_class, type)) { - type = instance_class; - } else { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; } } } @@ -18119,6 +19163,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject } PyErr_SetObject(type, value); if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { @@ -18126,6 +19177,7 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } +#endif } bad: Py_XDECREF(owned_instance); @@ -18432,6 +19484,79 @@ static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, *tb = tmp_tb; } +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_VERSION_HEX < 0x03030000 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if (strchr(__Pyx_MODULE_NAME, '.')) { + #if PY_VERSION_HEX < 0x03030000 + PyObject *py_level = PyInt_FromLong(1); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + #endif + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_VERSION_HEX < 0x03030000 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_VERSION_HEX < 0x03030000 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { PyObject *r; if (!j) return NULL; @@ -18440,7 +19565,8 @@ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j return r; } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, - int wraparound, int boundscheck) { + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) { @@ -18454,7 +19580,8 @@ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_ #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, - int wraparound, int boundscheck) { + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) { @@ -18467,8 +19594,9 @@ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize return PySequence_GetItem(o, i); #endif } -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, - int is_list, int wraparound, int boundscheck) { +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); @@ -18510,6 +19638,107 @@ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); } +#if CYTHON_USE_PYLONG_INTERNALS + #include "longintrepr.h" +#endif + +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) { + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + const long b = intval; + long x; + long a = PyInt_AS_LONG(op1); + x = (long)((unsigned long)a + b); + if (likely((x^a) >= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS && PY_MAJOR_VERSION >= 3 + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0])); + break; + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | digits[0])); + goto long_long; + } + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0])); + break; + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | digits[0])); + goto long_long; + } + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + break; + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + goto long_long; + } + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + break; + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + goto long_long; + } + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + break; + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + goto long_long; + } + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + break; + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + goto long_long; + } + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); } @@ -18523,9 +19752,14 @@ static CYTHON_INLINE long __Pyx_div_long(long a, long b) { static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, - int full_traceback) { + int full_traceback, CYTHON_UNUSED int nogil) { PyObject *old_exc, *old_val, *old_tb; PyObject *ctx; +#ifdef WITH_THREAD + PyGILState_STATE state; + if (nogil) + state = PyGILState_Ensure(); +#endif __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); if (full_traceback) { Py_XINCREF(old_exc); @@ -18546,6 +19780,10 @@ static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, PyErr_WriteUnraisable(ctx); Py_DECREF(ctx); } +#ifdef WITH_THREAD + if (nogil) + PyGILState_Release(state); +#endif } #if CYTHON_COMPILING_IN_CPYTHON @@ -18620,7 +19858,7 @@ static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int co return count; } while (start < end) { - mid = (start + end) / 2; + mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { @@ -18796,102 +20034,29 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { - PyObject *empty_list = 0; - PyObject *module = 0; - PyObject *global_dict = 0; - PyObject *empty_dict = 0; - PyObject *list; - #if PY_VERSION_HEX < 0x03030000 - PyObject *py_import; - py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); - if (!py_import) - goto bad; - #endif - if (from_list) - list = from_list; - else { - empty_list = PyList_New(0); - if (!empty_list) - goto bad; - list = empty_list; + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ } - global_dict = PyModule_GetDict(__pyx_m); - if (!global_dict) - goto bad; - empty_dict = PyDict_New(); - if (!empty_dict) - goto bad; - { - #if PY_MAJOR_VERSION >= 3 - if (level == -1) { - if (strchr(__Pyx_MODULE_NAME, '.')) { - #if PY_VERSION_HEX < 0x03030000 - PyObject *py_level = PyInt_FromLong(1); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, 1); - #endif - if (!module) { - if (!PyErr_ExceptionMatches(PyExc_ImportError)) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - #endif - if (!module) { - #if PY_VERSION_HEX < 0x03030000 - PyObject *py_level = PyInt_FromLong(level); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, level); - #endif - } - } -bad: - #if PY_VERSION_HEX < 0x03030000 - Py_XDECREF(py_import); - #endif - Py_XDECREF(empty_list); - Py_XDECREF(empty_dict); - return module; -} - -#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \ - { \ - func_type value = func_value; \ - if (sizeof(target_type) < sizeof(func_type)) { \ - if (unlikely(value != (func_type) (target_type) value)) { \ - func_type zero = 0; \ - if (is_unsigned && unlikely(value < zero)) \ - goto raise_neg_overflow; \ - else \ - goto raise_overflow; \ - } \ - } \ - return (target_type) value; \ - } - -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - #include "longintrepr.h" - #endif -#endif static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { - const int neg_one = (int) -1, const_zero = 0; + const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -18908,36 +20073,125 @@ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(int) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) -(((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) -(((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) -(((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x)) - } else if (sizeof(int) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -19251,21 +20505,21 @@ __pyx_fail: } static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { - const int neg_one = (int) -1, const_zero = 0; + const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(int) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); } } { @@ -19516,6 +20770,32 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { #endif #endif +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { + const enum NPY_TYPES neg_one = (enum NPY_TYPES) -1, const_zero = (enum NPY_TYPES) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(enum NPY_TYPES) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); + } + } else { + if (sizeof(enum NPY_TYPES) <= sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES), + little, !is_unsigned); + } +} + static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs, char order, int ndim) @@ -19652,21 +20932,21 @@ __pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) } static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { - const long neg_one = (long) -1, const_zero = 0; + const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(long) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); } } { @@ -19678,7 +20958,7 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { } static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { - const char neg_one = (char) -1, const_zero = 0; + const char neg_one = (char) -1, const_zero = (char) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -19695,36 +20975,125 @@ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (char) 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (char) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(char) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(char) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(char, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (char) 0; + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) + case -2: + if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) -(((((char)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) -(((((((char)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) -(((((((((char)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(char) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x)) - } else if (sizeof(char) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) + } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -19773,7 +21142,7 @@ raise_neg_overflow: } static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { - const long neg_one = (long) -1, const_zero = 0; + const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -19790,36 +21159,125 @@ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(long) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) -(((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) -(((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) -(((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x)) - } else if (sizeof(long) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -20001,7 +21459,7 @@ static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && @@ -20042,7 +21500,7 @@ static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_ #endif } else #endif -#if !CYTHON_COMPILING_IN_PYPY +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); @@ -20072,7 +21530,7 @@ static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) { #else if (PyLong_Check(x)) #endif - return Py_INCREF(x), x; + return __Pyx_NewRef(x); m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { @@ -20112,18 +21570,55 @@ static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(b))) - return PyInt_AS_LONG(b); + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(x); + } #endif if (likely(PyLong_CheckExact(b))) { - #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - switch (Py_SIZE(b)) { - case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0]; - case 0: return 0; - case 1: return ((PyLongObject*)b)->ob_digit[0]; - } - #endif + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + } + } #endif return PyLong_AsSsize_t(b); } diff --git a/GPy/kern/_src/stationary_cython.pyx b/GPy/kern/_src/stationary_cython.pyx index c550fc91..75319aa3 100644 --- a/GPy/kern/_src/stationary_cython.pyx +++ b/GPy/kern/_src/stationary_cython.pyx @@ -4,14 +4,15 @@ import numpy as np cimport numpy as np from cython.parallel import prange +cimport cython ctypedef np.float64_t DTYPE_t cdef extern from "stationary_utils.h": - void _grad_X "_grad_X" (int N, int D, int M, double* X, double* X2, double* tmp, double* grad) + void _grad_X "_grad_X" (int N, int D, int M, double* X, double* X2, double* tmp, double* grad) nogil cdef extern from "stationary_utils.h": - void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) + void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) nogil def grad_X(int N, int D, int M, np.ndarray[DTYPE_t, ndim=2] _X, @@ -22,18 +23,18 @@ def grad_X(int N, int D, int M, cdef double *X2 = _X2.data cdef double *tmp = _tmp.data cdef double *grad = _grad.data - _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + with nogil: + _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. +@cython.cdivision(True) def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): cdef int n,d,nd,m - for nd in prange(N*D, nogil=True): - n = nd/D - d = nd%D + for nd in prange(N * D, nogil=True): + n = nd / D + d = nd % D grad[n,d] = 0.0 for m in range(M): - grad[n,d] += tmp[n,m]*(X[n,d]-X2[m,d]) - - + grad[n,d] += tmp[n, m] * (X[n, d] - X2[m, d]) def lengthscale_grads_in_c(int N, int M, int Q, np.ndarray[DTYPE_t, ndim=2] _tmp, @@ -44,16 +45,16 @@ def lengthscale_grads_in_c(int N, int M, int Q, cdef double *X = _X.data cdef double *X2 = _X2.data cdef double *grad = _grad.data - _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. + with nogil: + _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): cdef int q, n, m cdef double gradq, dist - for q in range(Q): - grad[q] = 0.0 - for n in range(N): - for m in range(M): - dist = X[n,q] - X2[m,q] - grad[q] += tmp[n,m]*dist*dist - - + with nogil: + for q in range(Q): + grad[q] = 0.0 + for n in range(N): + for m in range(M): + dist = X[n,q] - X2[m,q] + grad[q] += tmp[n, m] * dist * dist diff --git a/GPy/kern/_src/stationary_utils.h b/GPy/kern/_src/stationary_utils.h index 9c9745fb..948362ff 100644 --- a/GPy/kern/_src/stationary_utils.h +++ b/GPy/kern/_src/stationary_utils.h @@ -1,3 +1,5 @@ +#ifndef __APPLE__ #include +#endif void _grad_X(int N, int D, int M, double*X, double* X2, double* tmp, double* grad); void _lengthscale_grads(int N, int D, int M, double* X, double* X2, double* tmp, double* grad); diff --git a/GPy/kern/_src/trunclinear.py b/GPy/kern/_src/trunclinear.py index 8c48f134..af90c4a5 100644 --- a/GPy/kern/_src/trunclinear.py +++ b/GPy/kern/_src/trunclinear.py @@ -15,7 +15,7 @@ class TruncLinear(Kern): .. math:: - k(x,y) = \sum_{i=1}^input_dim \sigma^2_i \max(0, x_iy_i - \simga_q) + k(x,y) = \sum_{i=1}^input_dim \sigma^2_i \max(0, x_iy_i - \sigma_q) :param input_dim: the number of input dimensions :type input_dim: int @@ -54,7 +54,7 @@ class TruncLinear(Kern): self.delta = Param('delta', delta) self.add_parameter(self.variances) self.add_parameter(self.delta) - + @Cache_this(limit=2) def K(self, X, X2=None): XX = self.variances*self._product(X, X2) @@ -114,7 +114,7 @@ class TruncLinear_inf(Kern): .. math:: - k(x,y) = \sum_{i=1}^input_dim \sigma^2_i \max(0, x_iy_i - \simga_q) + k(x,y) = \sum_{i=1}^input_dim \sigma^2_i \max(0, x_iy_i - \sigma_q) :param input_dim: the number of input dimensions :type input_dim: int @@ -148,8 +148,8 @@ class TruncLinear_inf(Kern): self.variances = Param('variances', variances, Logexp()) self.add_parameter(self.variances) - - + + # @Cache_this(limit=2) def K(self, X, X2=None): tmp = self._product(X, X2) diff --git a/GPy/likelihoods/__init__.py b/GPy/likelihoods/__init__.py index 3157bd5b..627ef39f 100644 --- a/GPy/likelihoods/__init__.py +++ b/GPy/likelihoods/__init__.py @@ -1,6 +1,6 @@ from .bernoulli import Bernoulli from .exponential import Exponential -from .gaussian import Gaussian +from .gaussian import Gaussian, HeteroscedasticGaussian from .gamma import Gamma from .poisson import Poisson from .student_t import StudentT diff --git a/GPy/likelihoods/bernoulli.py b/GPy/likelihoods/bernoulli.py index e540f016..167daee8 100644 --- a/GPy/likelihoods/bernoulli.py +++ b/GPy/likelihoods/bernoulli.py @@ -85,6 +85,7 @@ class Bernoulli(Likelihood): gh_x, gh_w = gh_points + gh_w = gh_w / np.sqrt(np.pi) shape = m.shape m,v,Y = m.flatten(), v.flatten(), Y.flatten() Ysign = np.where(Y==1,1,-1) @@ -232,6 +233,17 @@ class Bernoulli(Likelihood): np.seterr(**state) return d3logpdf_dlink3 + def predictive_quantiles(self, mu, var, quantiles, Y_metadata=None): + """ + Get the "quantiles" of the binary labels (Bernoulli draws). all the + quantiles must be either 0 or 1, since those are the only values the + draw can take! + """ + p = self.predictive_mean(mu, var) + return [np.asarray(p>(q/100.), dtype=np.int32) for q in quantiles] + + + def samples(self, gp, Y_metadata=None): """ Returns a set of samples of observations based on a given value of the latent variable. diff --git a/GPy/likelihoods/exponential.py b/GPy/likelihoods/exponential.py index 0a6c543d..ecf0977e 100644 --- a/GPy/likelihoods/exponential.py +++ b/GPy/likelihoods/exponential.py @@ -124,7 +124,7 @@ class Exponential(Likelihood): #d3lik_dlink3 = 6*y/(link_f**4) - 2./(link_f**3) return d3lik_dlink3 - def samples(self, gp): + def samples(self, gp, Y_metadata=None): """ Returns a set of samples of observations based on a given value of the latent variable. diff --git a/GPy/likelihoods/gaussian.py b/GPy/likelihoods/gaussian.py index 9abb8cde..e1299f73 100644 --- a/GPy/likelihoods/gaussian.py +++ b/GPy/likelihoods/gaussian.py @@ -48,6 +48,7 @@ class Gaussian(Likelihood): def betaY(self,Y,Y_metadata=None): #TODO: ~Ricardo this does not live here + raise RuntimeError("Please notify the GPy developers, this should not happen") return Y/self.gaussian_variance(Y_metadata) def gaussian_variance(self, Y_metadata=None): @@ -315,9 +316,44 @@ class Gaussian(Likelihood): return -0.5*np.log(2*np.pi) -0.5*np.log(v) - 0.5*np.square(y_test - mu_star)/v def variational_expectations(self, Y, m, v, gh_points=None, Y_metadata=None): + if not isinstance(self.gp_link, link_functions.Identity): + return super(Gaussian, self).variational_expectations(Y=Y, m=m, v=v, gh_points=gh_points, Y_metadata=Y_metadata) + lik_var = float(self.variance) F = -0.5*np.log(2*np.pi) -0.5*np.log(lik_var) - 0.5*(np.square(Y) + np.square(m) + v - 2*m*Y)/lik_var dF_dmu = (Y - m)/lik_var dF_dv = np.ones_like(v)*(-0.5/lik_var) dF_dtheta = -0.5/lik_var + 0.5*(np.square(Y) + np.square(m) + v - 2*m*Y)/(lik_var**2) return F, dF_dmu, dF_dv, dF_dtheta.reshape(1, Y.shape[0], Y.shape[1]) + +class HeteroscedasticGaussian(Gaussian): + def __init__(self, Y_metadata, gp_link=None, variance=1., name='het_Gauss'): + if gp_link is None: + gp_link = link_functions.Identity() + + if not isinstance(gp_link, link_functions.Identity): + print("Warning, Exact inference is not implemeted for non-identity link functions,\ + if you are not already, ensure Laplace inference_method is used") + + super(HeteroscedasticGaussian, self).__init__(gp_link, np.ones(Y_metadata['output_index'].shape)*variance, name) + + def exact_inference_gradients(self, dL_dKdiag,Y_metadata=None): + return dL_dKdiag[Y_metadata['output_index']] + + def gaussian_variance(self, Y_metadata=None): + return self.variance[Y_metadata['output_index'].flatten()] + + def predictive_values(self, mu, var, full_cov=False, Y_metadata=None): + _s = self.variance[Y_metadata['output_index'].flatten()] + if full_cov: + if var.ndim == 2: + var += np.eye(var.shape[0])*_s + if var.ndim == 3: + var += np.atleast_3d(np.eye(var.shape[0])*_s) + else: + var += _s + return mu, var + + def predictive_quantiles(self, mu, var, quantiles, Y_metadata=None): + _s = self.variance[Y_metadata['output_index'].flatten()] + return [stats.norm.ppf(q/100.)*np.sqrt(var + _s) + mu for q in quantiles] diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index 67a6a3a3..74c4c6fd 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -607,7 +607,7 @@ class Likelihood(Parameterized): pred_mean = self.predictive_mean(mu, var, Y_metadata=Y_metadata) pred_var = self.predictive_variance(mu, var, pred_mean, Y_metadata=Y_metadata) except NotImplementedError: - print "Finding predictive mean and variance via sampling rather than quadrature" + print("Finding predictive mean and variance via sampling rather than quadrature") Nf_samp = 300 Ny_samp = 1 s = np.random.randn(mu.shape[0], Nf_samp)*np.sqrt(var) + mu @@ -622,7 +622,7 @@ class Likelihood(Parameterized): Nf_samp = 300 Ny_samp = 1 s = np.random.randn(mu.shape[0], Nf_samp)*np.sqrt(var) + mu - ss_y = self.samples(s, Y_metadata, samples=Ny_samp) + ss_y = self.samples(s, Y_metadata)#, samples=Ny_samp) #ss_y = ss_y.reshape(mu.shape[0], mu.shape[1], Nf_samp*Ny_samp) pred_quantiles = [np.percentile(ss_y, q, axis=1)[:,None] for q in quantiles] diff --git a/GPy/likelihoods/link_functions.py b/GPy/likelihoods/link_functions.py index 3d753395..4947fdb8 100644 --- a/GPy/likelihoods/link_functions.py +++ b/GPy/likelihoods/link_functions.py @@ -2,6 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np +import scipy from ..util.univariate_Gaussian import std_norm_cdf, std_norm_pdf import scipy as sp from ..util.misc import safe_exp, safe_square, safe_cube, safe_quad, safe_three_times @@ -67,7 +68,7 @@ class Probit(GPTransformation): .. math:: g(f) = \\Phi^{-1} (mu) - + """ def transf(self,f): return std_norm_cdf(f) @@ -140,7 +141,7 @@ class Log_ex_1(GPTransformation): """ def transf(self,f): - return np.log1p(safe_exp(f)) + return scipy.special.log1p(safe_exp(f)) def dtransf_df(self,f): ef = safe_exp(f) diff --git a/GPy/likelihoods/poisson.py b/GPy/likelihoods/poisson.py index 5aa85a91..cfe279bb 100644 --- a/GPy/likelihoods/poisson.py +++ b/GPy/likelihoods/poisson.py @@ -145,5 +145,7 @@ class Poisson(Likelihood): """ orig_shape = gp.shape gp = gp.flatten() + # Ysim = np.random.poisson(self.gp_link.transf(gp), [samples, gp.size]).T + # return Ysim.reshape(orig_shape+(samples,)) Ysim = np.random.poisson(self.gp_link.transf(gp)) return Ysim.reshape(orig_shape) diff --git a/GPy/models/bayesian_gplvm_minibatch.py b/GPy/models/bayesian_gplvm_minibatch.py index 7a7bb0e8..0394ff7e 100644 --- a/GPy/models/bayesian_gplvm_minibatch.py +++ b/GPy/models/bayesian_gplvm_minibatch.py @@ -9,6 +9,7 @@ from ..inference.latent_function_inference.var_dtc_parallel import VarDTC_miniba import logging from GPy.models.sparse_gp_minibatch import SparseGPMiniBatch from GPy.core.parameterization.param import Param +from GPy.core.parameterization.observable_array import ObsAr class BayesianGPLVMMiniBatch(SparseGPMiniBatch): """ @@ -80,46 +81,10 @@ class BayesianGPLVMMiniBatch(SparseGPMiniBatch): """Get the gradients of the posterior distribution of X in its specific form.""" return X.mean.gradient, X.variance.gradient - def _inner_parameters_changed(self, kern, X, Z, likelihood, Y, Y_metadata, Lm=None, dL_dKmm=None, subset_indices=None, **kw): - posterior, log_marginal_likelihood, grad_dict, current_values, value_indices = super(BayesianGPLVMMiniBatch, self)._inner_parameters_changed(kern, X, Z, likelihood, Y, Y_metadata, Lm=Lm, dL_dKmm=dL_dKmm, subset_indices=subset_indices, **kw) - - if self.has_uncertain_inputs(): - current_values['meangrad'], current_values['vargrad'] = self.kern.gradients_qX_expectations( - variational_posterior=X, - Z=Z, dL_dpsi0=grad_dict['dL_dpsi0'], - dL_dpsi1=grad_dict['dL_dpsi1'], - dL_dpsi2=grad_dict['dL_dpsi2']) - else: - current_values['Xgrad'] = self.kern.gradients_X(grad_dict['dL_dKnm'], X, Z) - current_values['Xgrad'] += self.kern.gradients_X_diag(grad_dict['dL_dKdiag'], X) - if subset_indices is not None: - value_indices['Xgrad'] = subset_indices['samples'] - - kl_fctr = self.kl_factr - if self.has_uncertain_inputs(): - if self.missing_data: - d = self.output_dim - log_marginal_likelihood -= kl_fctr*self.variational_prior.KL_divergence(X)/d - else: - log_marginal_likelihood -= kl_fctr*self.variational_prior.KL_divergence(X) - - # Subsetting Variational Posterior objects, makes the gradients - # empty. We need them to be 0 though: - X.mean.gradient[:] = 0 - X.variance.gradient[:] = 0 - - self.variational_prior.update_gradients_KL(X) - if self.missing_data: - current_values['meangrad'] += kl_fctr*X.mean.gradient/d - current_values['vargrad'] += kl_fctr*X.variance.gradient/d - else: - current_values['meangrad'] += kl_fctr*X.mean.gradient - current_values['vargrad'] += kl_fctr*X.variance.gradient - - if subset_indices is not None: - value_indices['meangrad'] = subset_indices['samples'] - value_indices['vargrad'] = subset_indices['samples'] - return posterior, log_marginal_likelihood, grad_dict, current_values, value_indices + def _inner_parameters_changed(self, kern, X, Z, likelihood, Y, Y_metadata, Lm=None, dL_dKmm=None, psi0=None, psi1=None, psi2=None, **kw): + posterior, log_marginal_likelihood, grad_dict = super(BayesianGPLVMMiniBatch, self)._inner_parameters_changed(kern, X, Z, likelihood, Y, Y_metadata, Lm=Lm, dL_dKmm=dL_dKmm, + psi0=psi0, psi1=psi1, psi2=psi2, **kw) + return posterior, log_marginal_likelihood, grad_dict def _outer_values_update(self, full_values): """ @@ -128,22 +93,47 @@ class BayesianGPLVMMiniBatch(SparseGPMiniBatch): """ super(BayesianGPLVMMiniBatch, self)._outer_values_update(full_values) if self.has_uncertain_inputs(): - self.X.mean.gradient = full_values['meangrad'] - self.X.variance.gradient = full_values['vargrad'] + meangrad_tmp, vargrad_tmp = self.kern.gradients_qX_expectations( + variational_posterior=self.X, + Z=self.Z, dL_dpsi0=full_values['dL_dpsi0'], + dL_dpsi1=full_values['dL_dpsi1'], + dL_dpsi2=full_values['dL_dpsi2'], + psi0=self.psi0, psi1=self.psi1, psi2=self.psi2) + + self.X.mean.gradient = meangrad_tmp + self.X.variance.gradient = vargrad_tmp else: - self.X.gradient = full_values['Xgrad'] + self.X.gradient = self.kern.gradients_X(full_values['dL_dKnm'], self.X, self.Z) + self.X.gradient += self.kern.gradients_X_diag(full_values['dL_dKdiag'], self.X) def _outer_init_full_values(self): - if self.has_uncertain_inputs(): - return dict(meangrad=np.zeros(self.X.mean.shape), - vargrad=np.zeros(self.X.variance.shape)) - else: - return dict(Xgrad=np.zeros(self.X.shape)) + return super(BayesianGPLVMMiniBatch, self)._outer_init_full_values() def parameters_changed(self): super(BayesianGPLVMMiniBatch,self).parameters_changed() - if isinstance(self.inference_method, VarDTC_minibatch): - return + + kl_fctr = self.kl_factr + if kl_fctr > 0: + Xgrad = self.X.gradient.copy() + self.X.gradient[:] = 0 + self.variational_prior.update_gradients_KL(self.X) + + if self.missing_data or not self.stochastics: + self.X.mean.gradient = kl_fctr*self.X.mean.gradient + self.X.variance.gradient = kl_fctr*self.X.variance.gradient + else: + d = self.output_dim + self.X.mean.gradient = kl_fctr*self.X.mean.gradient*self.stochastics.batchsize/d + self.X.variance.gradient = kl_fctr*self.X.variance.gradient*self.stochastics.batchsize/d + self.X.gradient += Xgrad + + if self.missing_data or not self.stochastics: + self._log_marginal_likelihood -= kl_fctr*self.variational_prior.KL_divergence(self.X) + elif self.stochastics: + d = self.output_dim + self._log_marginal_likelihood -= kl_fctr*self.variational_prior.KL_divergence(self.X)*self.stochastics.batchsize/d + + self._Xgrad = self.X.gradient.copy() def plot_latent(self, labels=None, which_indices=None, resolution=50, ax=None, marker='o', s=40, diff --git a/GPy/models/bcgplvm.py b/GPy/models/bcgplvm.py index 899bb2f8..7462fa27 100644 --- a/GPy/models/bcgplvm.py +++ b/GPy/models/bcgplvm.py @@ -1,11 +1,11 @@ -# Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt). +# Copyright (c) 2015 James Hensman # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np from ..core import GP -from ..models import GPLVM -from ..mappings import * +from . import GPLVM +from .. import mappings class BCGPLVM(GPLVM): @@ -16,33 +16,31 @@ class BCGPLVM(GPLVM): :type Y: np.ndarray :param input_dim: latent dimensionality :type input_dim: int - :param init: initialisation method for the latent space - :type init: 'PCA'|'random' :param mapping: mapping for back constraint :type mapping: GPy.core.Mapping object """ - def __init__(self, Y, input_dim, init='PCA', X=None, kernel=None, normalize_Y=False, mapping=None): - + def __init__(self, Y, input_dim, kernel=None, mapping=None): + + if mapping is None: - mapping = Kernel(X=Y, output_dim=input_dim) + mapping = mappings.MLP(input_dim=Y.shape[1], + output_dim=input_dim, + hidden_dim=10) + else: + assert mapping.input_dim==Y.shape[1], "mapping input dim does not work for Y dimension" + assert mapping.output_dim==input_dim, "mapping output dim does not work for self.input_dim" + GPLVM.__init__(self, Y, input_dim, X=mapping.f(Y), kernel=kernel, name="bcgplvm") + self.unlink_parameter(self.X) self.mapping = mapping - GPLVM.__init__(self, Y, input_dim, init, X, kernel, normalize_Y) - self.X = self.mapping.f(self.likelihood.Y) + self.link_parameter(self.mapping) - def _get_param_names(self): - return self.mapping._get_param_names() + GP._get_param_names(self) + self.X = self.mapping.f(self.Y) - def _get_params(self): - return np.hstack((self.mapping._get_params(), GP._get_params(self))) + def parameters_changed(self): + self.X = self.mapping.f(self.Y) + GP.parameters_changed(self) + Xgradient = self.kern.gradients_X(self.grad_dict['dL_dK'], self.X, None) + self.mapping.update_gradients(Xgradient, self.Y) - def _set_params(self, x): - self.mapping._set_params(x[:self.mapping.num_params]) - self.X = self.mapping.f(self.likelihood.Y) - GP._set_params(self, x[self.mapping.num_params:]) - - def _log_likelihood_gradients(self): - dL_df = self.kern.gradients_X(self.dL_dK, self.X) - dL_dtheta = self.mapping.df_dtheta(dL_df, self.likelihood.Y) - return np.hstack((dL_dtheta.flatten(), GP._log_likelihood_gradients(self))) diff --git a/GPy/models/gp_heteroscedastic_regression.py b/GPy/models/gp_heteroscedastic_regression.py index 19cb18d8..63c6352a 100644 --- a/GPy/models/gp_heteroscedastic_regression.py +++ b/GPy/models/gp_heteroscedastic_regression.py @@ -16,6 +16,8 @@ class GPHeteroscedasticRegression(GP): :param X: input observations :param Y: observed values :param kernel: a GPy kernel, defaults to rbf + + NB: This model does not make inference on the noise outside the training set """ def __init__(self, X, Y, kernel=None, Y_metadata=None): @@ -30,10 +32,7 @@ class GPHeteroscedasticRegression(GP): kernel = kern.RBF(X.shape[1]) #Likelihood - #likelihoods_list = [likelihoods.Gaussian(name="Gaussian_noise_%s" %j) for j in range(Ny)] - noise_terms = np.unique(Y_metadata['output_index'].flatten()) - likelihoods_list = [likelihoods.Gaussian(name="Gaussian_noise_%s" %j) for j in noise_terms] - likelihood = likelihoods.MixedNoise(likelihoods_list=likelihoods_list) + likelihood = likelihoods.HeteroscedasticGaussian(Y_metadata) super(GPHeteroscedasticRegression, self).__init__(X,Y,kernel,likelihood, Y_metadata=Y_metadata) diff --git a/GPy/models/gp_kronecker_gaussian_regression.py b/GPy/models/gp_kronecker_gaussian_regression.py index 434661d2..5b2fb41c 100644 --- a/GPy/models/gp_kronecker_gaussian_regression.py +++ b/GPy/models/gp_kronecker_gaussian_regression.py @@ -1,5 +1,5 @@ # Copyright (c) 2014, James Hensman, Alan Saul -# Distributed under the terms of the GNU General public License, see LICENSE.txt +# Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np from ..core.model import Model diff --git a/GPy/models/gp_regression.py b/GPy/models/gp_regression.py index 7266ae92..157c0dc8 100644 --- a/GPy/models/gp_regression.py +++ b/GPy/models/gp_regression.py @@ -26,12 +26,12 @@ class GPRegression(GP): """ - def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None, noise_var=1.): + def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None, noise_var=1., mean_function=None): if kernel is None: kernel = kern.RBF(X.shape[1]) - + likelihood = likelihoods.Gaussian(variance=noise_var) - super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer) + super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer, mean_function=mean_function) diff --git a/GPy/models/gp_var_gauss.py b/GPy/models/gp_var_gauss.py index 729b6bb8..6cce8640 100644 --- a/GPy/models/gp_var_gauss.py +++ b/GPy/models/gp_var_gauss.py @@ -1,20 +1,17 @@ # Copyright (c) 2014, James Hensman, Alan Saul -# Distributed under the terms of the GNU General public License, see LICENSE.txt +# Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np -from scipy import stats -from scipy.special import erf -from ..core.model import Model +from ..core import GP from ..core.parameterization import ObsAr from .. import kern from ..core.parameterization.param import Param -from ..util.linalg import pdinv -from ..likelihoods import Gaussian +from ..inference.latent_function_inference import VarGauss log_2_pi = np.log(2*np.pi) -class GPVariationalGaussianApproximation(Model): +class GPVariationalGaussianApproximation(GP): """ The Variational Gaussian Approximation revisited @@ -26,70 +23,14 @@ class GPVariationalGaussianApproximation(Model): pages = {786--792}, } """ - def __init__(self, X, Y, kernel, likelihood=None, Y_metadata=None): - Model.__init__(self,'Variational GP') - if likelihood is None: - likelihood = Gaussian() - # accept the construction arguments - self.X = ObsAr(X) - self.Y = Y - self.num_data, self.input_dim = self.X.shape - self.Y_metadata = Y_metadata + def __init__(self, X, Y, kernel, likelihood, Y_metadata=None): - self.kern = kernel - self.likelihood = likelihood - self.link_parameter(self.kern) - self.link_parameter(self.likelihood) + num_data = Y.shape[0] + self.alpha = Param('alpha', np.zeros((num_data,1))) # only one latent fn for now. + self.beta = Param('beta', np.ones(num_data)) + + inf = VarGauss(self.alpha, self.beta) + super(GPVariationalGaussianApproximation, self).__init__(X, Y, kernel, likelihood, name='VarGP', inference_method=inf) - self.alpha = Param('alpha', np.zeros((self.num_data,1))) # only one latent fn for now. - self.beta = Param('beta', np.ones(self.num_data)) self.link_parameter(self.alpha) self.link_parameter(self.beta) - - def log_likelihood(self): - return self._log_lik - - def parameters_changed(self): - K = self.kern.K(self.X) - m = K.dot(self.alpha) - KB = K*self.beta[:, None] - BKB = KB*self.beta[None, :] - A = np.eye(self.num_data) + BKB - Ai, LA, _, Alogdet = pdinv(A) - Sigma = np.diag(self.beta**-2) - Ai/self.beta[:, None]/self.beta[None, :] # posterior coavairance: need full matrix for gradients - var = np.diag(Sigma).reshape(-1,1) - - F, dF_dm, dF_dv, dF_dthetaL = self.likelihood.variational_expectations(self.Y, m, var, Y_metadata=self.Y_metadata) - self.likelihood.gradient = dF_dthetaL.sum(1).sum(1) - dF_da = np.dot(K, dF_dm) - SigmaB = Sigma*self.beta - dF_db = -np.diag(Sigma.dot(np.diag(dF_dv.flatten())).dot(SigmaB))*2 - KL = 0.5*(Alogdet + np.trace(Ai) - self.num_data + np.sum(m*self.alpha)) - dKL_da = m - A_A2 = Ai - Ai.dot(Ai) - dKL_db = np.diag(np.dot(KB.T, A_A2)) - self._log_lik = F.sum() - KL - self.alpha.gradient = dF_da - dKL_da - self.beta.gradient = dF_db - dKL_db - - # K-gradients - dKL_dK = 0.5*(self.alpha*self.alpha.T + self.beta[:, None]*self.beta[None, :]*A_A2) - tmp = Ai*self.beta[:, None]/self.beta[None, :] - dF_dK = self.alpha*dF_dm.T + np.dot(tmp*dF_dv, tmp.T) - self.kern.update_gradients_full(dF_dK - dKL_dK, self.X) - - def _raw_predict(self, Xnew): - """ - Predict the function(s) at the new point(s) Xnew. - - :param Xnew: The points at which to make a prediction - :type Xnew: np.ndarray, Nnew x self.input_dim - """ - Wi, _, _, _ = pdinv(self.kern.K(self.X) + np.diag(self.beta**-2)) - Kux = self.kern.K(self.X, Xnew) - mu = np.dot(Kux.T, self.alpha) - WiKux = np.dot(Wi, Kux) - Kxx = self.kern.Kdiag(Xnew) - var = Kxx - np.sum(WiKux*Kux, 0) - - return mu, var.reshape(-1,1) diff --git a/GPy/models/gplvm.py b/GPy/models/gplvm.py index 6318829d..5bef5be5 100644 --- a/GPy/models/gplvm.py +++ b/GPy/models/gplvm.py @@ -36,6 +36,7 @@ class GPLVM(GP): likelihood = Gaussian() super(GPLVM, self).__init__(X, Y, kernel, likelihood, name='GPLVM') + self.X = Param('latent_mean', X) self.link_parameter(self.X, index=0) @@ -43,27 +44,30 @@ class GPLVM(GP): super(GPLVM, self).parameters_changed() self.X.gradient = self.kern.gradients_X(self.grad_dict['dL_dK'], self.X, None) - def jacobian(self,X): - J = np.zeros((X.shape[0],X.shape[1],self.output_dim)) - for i in range(self.output_dim): - J[:,:,i] = self.kern.gradients_X(self.posterior.woodbury_vector[:,i:i+1], X, self.X) - return J + #def jacobian(self,X): + # J = np.zeros((X.shape[0],X.shape[1],self.output_dim)) + # for i in range(self.output_dim): + # J[:,:,i] = self.kern.gradients_X(self.posterior.woodbury_vector[:,i:i+1], X, self.X) + # return J - def magnification(self,X): - target=np.zeros(X.shape[0]) - #J = np.zeros((X.shape[0],X.shape[1],self.output_dim)) - J = self.jacobian(X) - for i in range(X.shape[0]): - target[i]=np.sqrt(np.linalg.det(np.dot(J[i,:,:],np.transpose(J[i,:,:])))) - return target + #def magnification(self,X): + # target=np.zeros(X.shape[0]) + # #J = np.zeros((X.shape[0],X.shape[1],self.output_dim)) + ## J = self.jacobian(X) + # for i in range(X.shape[0]): + # target[i]=np.sqrt(np.linalg.det(np.dot(J[i,:,:],np.transpose(J[i,:,:])))) + # return target def plot(self): - assert self.likelihood.Y.shape[1] == 2 - pb.scatter(self.likelihood.Y[:, 0], self.likelihood.Y[:, 1], 40, self.X[:, 0].copy(), linewidth=0, cmap=pb.cm.jet) # @UndefinedVariable + assert self.Y.shape[1] == 2, "too high dimensional to plot. Try plot_latent" + from matplotlib import pyplot as plt + plt.scatter(self.Y[:, 0], + self.Y[:, 1], + 40, self.X[:, 0].copy(), + linewidth=0, cmap=plt.cm.jet) Xnew = np.linspace(self.X.min(), self.X.max(), 200)[:, None] mu, _ = self.predict(Xnew) - import pylab as pb - pb.plot(mu[:, 0], mu[:, 1], 'k', linewidth=1.5) + plt.plot(mu[:, 0], mu[:, 1], 'k', linewidth=1.5) def plot_latent(self, labels=None, which_indices=None, resolution=50, ax=None, marker='o', s=40, @@ -78,6 +82,3 @@ class GPLVM(GP): resolution, ax, marker, s, fignum, False, legend, plot_limits, aspect, updates, **kwargs) - - def plot_magnification(self, *args, **kwargs): - return util.plot_latent.plot_magnification(self, *args, **kwargs) diff --git a/GPy/models/gradient_checker.py b/GPy/models/gradient_checker.py index 728f3e23..42d41e60 100644 --- a/GPy/models/gradient_checker.py +++ b/GPy/models/gradient_checker.py @@ -251,7 +251,7 @@ class HessianChecker(GradientChecker): print(grad_string) if plot: - import pylab as pb + from matplotlib import pyplot as pb fig, axes = pb.subplots(2, 2) max_lim = numpy.max(numpy.vstack((analytic_hess, numeric_hess))) min_lim = numpy.min(numpy.vstack((analytic_hess, numeric_hess))) diff --git a/GPy/models/mrd.py b/GPy/models/mrd.py index be01b769..cb98e1a8 100644 --- a/GPy/models/mrd.py +++ b/GPy/models/mrd.py @@ -170,20 +170,19 @@ class MRD(BayesianGPLVMMiniBatch): self._log_marginal_likelihood += b._log_marginal_likelihood self.logger.info('working on im <{}>'.format(hex(id(i)))) - self.Z.gradient[:] += b.full_values['Zgrad'] - grad_dict = b.full_values + self.Z.gradient[:] += b.Z.gradient#full_values['Zgrad'] + #grad_dict = b.full_values if self.has_uncertain_inputs(): - self.X.mean.gradient += grad_dict['meangrad'] - self.X.variance.gradient += grad_dict['vargrad'] + self.X.gradient += b._Xgrad else: - self.X.gradient += grad_dict['Xgrad'] + self.X.gradient += b._Xgrad - if self.has_uncertain_inputs(): - # update for the KL divergence - self.variational_prior.update_gradients_KL(self.X) - self._log_marginal_likelihood -= self.variational_prior.KL_divergence(self.X) - pass + #if self.has_uncertain_inputs(): + # # update for the KL divergence + # self.variational_prior.update_gradients_KL(self.X) + # self._log_marginal_likelihood -= self.variational_prior.KL_divergence(self.X) + # pass def log_likelihood(self): return self._log_marginal_likelihood diff --git a/GPy/models/sparse_gp_minibatch.py b/GPy/models/sparse_gp_minibatch.py index 07295255..adb92b30 100644 --- a/GPy/models/sparse_gp_minibatch.py +++ b/GPy/models/sparse_gp_minibatch.py @@ -44,7 +44,7 @@ class SparseGPMiniBatch(SparseGP): def __init__(self, X, Y, Z, kernel, likelihood, inference_method=None, name='sparse gp', Y_metadata=None, normalizer=False, missing_data=False, stochastic=False, batchsize=1): - + # pick a sensible inference method if inference_method is None: if isinstance(likelihood, likelihoods.Gaussian): @@ -63,10 +63,10 @@ class SparseGPMiniBatch(SparseGP): if stochastic and missing_data: self.missing_data = True - self.stochastics = SparseGPStochastics(self, batchsize) + self.stochastics = SparseGPStochastics(self, batchsize, self.missing_data) elif stochastic and not missing_data: self.missing_data = False - self.stochastics = SparseGPStochastics(self, batchsize) + self.stochastics = SparseGPStochastics(self, batchsize, self.missing_data) elif missing_data: self.missing_data = True self.stochastics = SparseGPMissing(self) @@ -80,7 +80,7 @@ class SparseGPMiniBatch(SparseGP): def has_uncertain_inputs(self): return isinstance(self.X, VariationalPosterior) - def _inner_parameters_changed(self, kern, X, Z, likelihood, Y, Y_metadata, Lm=None, dL_dKmm=None, subset_indices=None, **kwargs): + def _inner_parameters_changed(self, kern, X, Z, likelihood, Y, Y_metadata, Lm=None, dL_dKmm=None, psi0=None, psi1=None, psi2=None, **kwargs): """ This is the standard part, which usually belongs in parameters_changed. @@ -99,47 +99,13 @@ class SparseGPMiniBatch(SparseGP): like them into this dictionary for inner use of the indices inside the algorithm. """ - try: - posterior, log_marginal_likelihood, grad_dict = self.inference_method.inference(kern, X, Z, likelihood, Y, Y_metadata, Lm=Lm, dL_dKmm=None, **kwargs) - except: - posterior, log_marginal_likelihood, grad_dict = self.inference_method.inference(kern, X, Z, likelihood, Y, Y_metadata) - current_values = {} - likelihood.update_gradients(grad_dict['dL_dthetaL']) - current_values['likgrad'] = likelihood.gradient.copy() - if subset_indices is None: - subset_indices = {} - if isinstance(X, VariationalPosterior): - #gradients wrt kernel - dL_dKmm = grad_dict['dL_dKmm'] - kern.update_gradients_full(dL_dKmm, Z, None) - current_values['kerngrad'] = kern.gradient.copy() - kern.update_gradients_expectations(variational_posterior=X, - Z=Z, - dL_dpsi0=grad_dict['dL_dpsi0'], - dL_dpsi1=grad_dict['dL_dpsi1'], - dL_dpsi2=grad_dict['dL_dpsi2']) - current_values['kerngrad'] += kern.gradient - - #gradients wrt Z - current_values['Zgrad'] = kern.gradients_X(dL_dKmm, Z) - current_values['Zgrad'] += kern.gradients_Z_expectations( - grad_dict['dL_dpsi0'], - grad_dict['dL_dpsi1'], - grad_dict['dL_dpsi2'], - Z=Z, - variational_posterior=X) + if psi2 is None: + psi2_sum_n = None else: - #gradients wrt kernel - kern.update_gradients_diag(grad_dict['dL_dKdiag'], X) - current_values['kerngrad'] = kern.gradient.copy() - kern.update_gradients_full(grad_dict['dL_dKnm'], X, Z) - current_values['kerngrad'] += kern.gradient - kern.update_gradients_full(grad_dict['dL_dKmm'], Z, None) - current_values['kerngrad'] += kern.gradient - #gradients wrt Z - current_values['Zgrad'] = kern.gradients_X(grad_dict['dL_dKmm'], Z) - current_values['Zgrad'] += kern.gradients_X(grad_dict['dL_dKnm'].T, Z, X) - return posterior, log_marginal_likelihood, grad_dict, current_values, subset_indices + psi2_sum_n = psi2.sum(axis=0) + posterior, log_marginal_likelihood, grad_dict = self.inference_method.inference(kern, X, Z, likelihood, Y, Y_metadata, Lm=Lm, + dL_dKmm=dL_dKmm, psi0=psi0, psi1=psi1, psi2=psi2_sum_n, **kwargs) + return posterior, log_marginal_likelihood, grad_dict def _inner_take_over_or_update(self, full_values=None, current_values=None, value_indices=None): """ @@ -173,7 +139,10 @@ class SparseGPMiniBatch(SparseGP): else: index = slice(None) if key in full_values: - full_values[key][index] += current_values[key] + try: + full_values[key][index] += current_values[key] + except: + full_values[key] += current_values[key] else: full_values[key] = current_values[key] @@ -192,9 +161,41 @@ class SparseGPMiniBatch(SparseGP): Here you put the values, which were collected before in the right places. E.g. set the gradients of parameters, etc. """ - self.likelihood.gradient = full_values['likgrad'] - self.kern.gradient = full_values['kerngrad'] - self.Z.gradient = full_values['Zgrad'] + if self.has_uncertain_inputs(): + #gradients wrt kernel + dL_dKmm = full_values['dL_dKmm'] + self.kern.update_gradients_full(dL_dKmm, self.Z, None) + kgrad = self.kern.gradient.copy() + self.kern.update_gradients_expectations( + variational_posterior=self.X, + Z=self.Z, dL_dpsi0=full_values['dL_dpsi0'], + dL_dpsi1=full_values['dL_dpsi1'], + dL_dpsi2=full_values['dL_dpsi2']) + self.kern.gradient += kgrad + + + #gradients wrt Z + self.Z.gradient = self.kern.gradients_X(dL_dKmm, self.Z) + self.Z.gradient += self.kern.gradients_Z_expectations( + variational_posterior=self.X, + Z=self.Z, dL_dpsi0=full_values['dL_dpsi0'], + dL_dpsi1=full_values['dL_dpsi1'], + dL_dpsi2=full_values['dL_dpsi2']) + else: + #gradients wrt kernel + self.kern.update_gradients_diag(full_values['dL_dKdiag'], self.X) + kgrad = self.kern.gradient.copy() + self.kern.update_gradients_full(full_values['dL_dKnm'], self.X, self.Z) + kgrad += self.kern.gradient + self.kern.update_gradients_full(full_values['dL_dKmm'], self.Z, None) + self.kern.gradient += kgrad + #kgrad += self.kern.gradient + + #gradients wrt Z + self.Z.gradient = self.kern.gradients_X(full_values['dL_dKmm'], self.Z) + self.Z.gradient += self.kern.gradients_X(full_values['dL_dKnm'].T, self.Z, self.X) + + self.likelihood.update_gradients(full_values['dL_dthetaL']) def _outer_init_full_values(self): """ @@ -209,7 +210,15 @@ class SparseGPMiniBatch(SparseGP): to initialize the gradients for the mean and the variance in order to have the full gradient for indexing) """ - return {} + retd = dict(dL_dKmm=np.zeros((self.Z.shape[0], self.Z.shape[0]))) + if self.has_uncertain_inputs(): + retd.update(dict(dL_dpsi0=np.zeros(self.X.shape[0]), + dL_dpsi1=np.zeros((self.X.shape[0], self.Z.shape[0])), + dL_dpsi2=np.zeros((self.X.shape[0], self.Z.shape[0], self.Z.shape[0])))) + else: + retd.update({'dL_dKdiag': np.zeros(self.X.shape[0]), + 'dL_dKnm': np.zeros((self.X.shape[0], self.Z.shape[0]))}) + return retd def _outer_loop_for_missing_data(self): Lm = None @@ -231,28 +240,36 @@ class SparseGPMiniBatch(SparseGP): print(message, end=' ') for d, ninan in self.stochastics.d: - if not self.stochastics: print(' '*(len(message)) + '\r', end=' ') message = m_f(d) print(message, end=' ') - posterior, log_marginal_likelihood, \ - grad_dict, current_values, value_indices = self._inner_parameters_changed( + psi0ni = self.psi0[ninan] + psi1ni = self.psi1[ninan] + if self.has_uncertain_inputs(): + psi2ni = self.psi2[ninan] + value_indices = dict(outputs=d, samples=ninan, dL_dpsi0=ninan, dL_dpsi1=ninan, dL_dpsi2=ninan) + else: + psi2ni = None + value_indices = dict(outputs=d, samples=ninan, dL_dKdiag=ninan, dL_dKnm=ninan) + + posterior, log_marginal_likelihood, grad_dict = self._inner_parameters_changed( self.kern, self.X[ninan], self.Z, self.likelihood, self.Y_normalized[ninan][:, d], self.Y_metadata, Lm, dL_dKmm, - subset_indices=dict(outputs=d, samples=ninan)) + psi0=psi0ni, psi1=psi1ni, psi2=psi2ni) - self._inner_take_over_or_update(self.full_values, current_values, value_indices) - self._inner_values_update(current_values) + # Fill out the full values by adding in the apporpriate grad_dict + # values + self._inner_take_over_or_update(self.full_values, grad_dict, value_indices) + self._inner_values_update(grad_dict) # What is this for? -> MRD - Lm = posterior.K_chol - dL_dKmm = grad_dict['dL_dKmm'] woodbury_inv[:, :, d] = posterior.woodbury_inv[:,:,None] woodbury_vector[:, d] = posterior.woodbury_vector self._log_marginal_likelihood += log_marginal_likelihood + if not self.stochastics: print('') @@ -260,10 +277,10 @@ class SparseGPMiniBatch(SparseGP): self.posterior = Posterior(woodbury_inv=woodbury_inv, woodbury_vector=woodbury_vector, K=posterior._K, mean=None, cov=None, K_chol=posterior.K_chol) self._outer_values_update(self.full_values) + if self.has_uncertain_inputs(): + self.kern.return_psi2_n = False def _outer_loop_without_missing_data(self): - self._log_marginal_likelihood = 0 - if self.posterior is None: woodbury_inv = np.zeros((self.num_inducing, self.num_inducing, self.output_dim)) woodbury_vector = np.zeros((self.num_inducing, self.output_dim)) @@ -271,17 +288,16 @@ class SparseGPMiniBatch(SparseGP): woodbury_inv = self.posterior._woodbury_inv woodbury_vector = self.posterior._woodbury_vector - d = self.stochastics.d - posterior, log_marginal_likelihood, \ - grad_dict, self.full_values, _ = self._inner_parameters_changed( + d = self.stochastics.d[0][0] + posterior, log_marginal_likelihood, grad_dict= self._inner_parameters_changed( self.kern, self.X, self.Z, self.likelihood, self.Y_normalized[:, d], self.Y_metadata) self.grad_dict = grad_dict - self._log_marginal_likelihood += log_marginal_likelihood + self._log_marginal_likelihood = log_marginal_likelihood - self._outer_values_update(self.full_values) + self._outer_values_update(self.grad_dict) woodbury_inv[:, :, d] = posterior.woodbury_inv[:, :, None] woodbury_vector[:, d] = posterior.woodbury_vector @@ -290,10 +306,23 @@ class SparseGPMiniBatch(SparseGP): K=posterior._K, mean=None, cov=None, K_chol=posterior.K_chol) def parameters_changed(self): + #Compute the psi statistics for N once, but don't sum out N in psi2 + if self.has_uncertain_inputs(): + #psi0 = ObsAr(self.kern.psi0(self.Z, self.X)) + #psi1 = ObsAr(self.kern.psi1(self.Z, self.X)) + #psi2 = ObsAr(self.kern.psi2(self.Z, self.X)) + self.psi0 = self.kern.psi0(self.Z, self.X) + self.psi1 = self.kern.psi1(self.Z, self.X) + self.psi2 = self.kern.psi2n(self.Z, self.X) + else: + self.psi0 = self.kern.Kdiag(self.X) + self.psi1 = self.kern.K(self.X, self.Z) + self.psi2 = None + if self.missing_data: self._outer_loop_for_missing_data() elif self.stochastics: self._outer_loop_without_missing_data() else: - self.posterior, self._log_marginal_likelihood, self.grad_dict, self.full_values, _ = self._inner_parameters_changed(self.kern, self.X, self.Z, self.likelihood, self.Y_normalized, self.Y_metadata) - self._outer_values_update(self.full_values) + self.posterior, self._log_marginal_likelihood, self.grad_dict = self._inner_parameters_changed(self.kern, self.X, self.Z, self.likelihood, self.Y_normalized, self.Y_metadata) + self._outer_values_update(self.grad_dict) diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py index 9dd84441..7172543d 100644 --- a/GPy/plotting/__init__.py +++ b/GPy/plotting/__init__.py @@ -4,4 +4,8 @@ try: from . import matplot_dep except (ImportError, NameError): - print('Fail to load GPy.plotting.matplot_dep.') \ No newline at end of file + # Matplotlib not available + import warnings + warnings.warn(ImportWarning("Matplotlib not available, install newest version of Matplotlib for plotting")) + #sys.modules['matplotlib'] = + #sys.modules[__name__+'.matplot_dep'] = ImportWarning("Matplotlib not available, install newest version of Matplotlib for plotting") \ No newline at end of file diff --git a/GPy/plotting/matplot_dep/Tango.py b/GPy/plotting/matplot_dep/Tango.py index eeb2e075..5c004519 100644 --- a/GPy/plotting/matplot_dep/Tango.py +++ b/GPy/plotting/matplot_dep/Tango.py @@ -3,7 +3,7 @@ import matplotlib as mpl -import pylab as pb +from matplotlib import pyplot as pb import sys #sys.path.append('/home/james/mlprojects/sitran_cluster/') #from switch_pylab_backend import * @@ -159,7 +159,7 @@ cdict_Alu = {'red' :((0./5,colorsRGB['Aluminium1'][0]/256.,colorsRGB['Aluminium1 # cmap_BGR = mpl.colors.LinearSegmentedColormap('TangoRedBlue',cdict_BGR,256) # cmap_RB = mpl.colors.LinearSegmentedColormap('TangoRedBlue',cdict_RB,256) if __name__=='__main__': - import pylab as pb + from matplotlib import pyplot as pb pb.figure() pb.pcolor(pb.rand(10,10),cmap=cmap_RB) pb.colorbar() diff --git a/GPy/plotting/matplot_dep/base_plots.py b/GPy/plotting/matplot_dep/base_plots.py index f25aee49..45597628 100644 --- a/GPy/plotting/matplot_dep/base_plots.py +++ b/GPy/plotting/matplot_dep/base_plots.py @@ -3,8 +3,8 @@ try: - import Tango - import pylab as pb + #import Tango + from matplotlib import pyplot as pb except: pass import numpy as np @@ -17,11 +17,11 @@ def ax_default(fignum, ax): fig = ax.figure return fig, ax -def meanplot(x, mu, color=Tango.colorsHex['darkBlue'], ax=None, fignum=None, linewidth=2,**kw): +def meanplot(x, mu, color='#3300FF', ax=None, fignum=None, linewidth=2,**kw): _, axes = ax_default(fignum, ax) return axes.plot(x,mu,color=color,linewidth=linewidth,**kw) -def gpplot(x, mu, lower, upper, edgecol=Tango.colorsHex['darkBlue'], fillcol=Tango.colorsHex['lightBlue'], ax=None, fignum=None, **kwargs): +def gpplot(x, mu, lower, upper, edgecol='#3300FF', fillcol='#33CCFF', ax=None, fignum=None, **kwargs): _, axes = ax_default(fignum, ax) mu = mu.flatten() @@ -47,6 +47,32 @@ def gpplot(x, mu, lower, upper, edgecol=Tango.colorsHex['darkBlue'], fillcol=Tan return plots +def gperrors(x, mu, lower, upper, edgecol=None, ax=None, fignum=None, **kwargs): + _, axes = ax_default(fignum, ax) + + mu = mu.flatten() + x = x.flatten() + lower = lower.flatten() + upper = upper.flatten() + + plots = [] + + if edgecol is None: + edgecol='#3300FF' + + if not 'alpha' in kwargs.keys(): + kwargs['alpha'] = 1. + + + if not 'lw' in kwargs.keys(): + kwargs['lw'] = 1. + + + plots.append(axes.errorbar(x,mu,yerr=np.vstack([mu-lower,upper-mu]),color=edgecol,**kwargs)) + plots[-1][0].remove() + return plots + + def removeRightTicks(ax=None): ax = ax or pb.gca() for i, line in enumerate(ax.get_yticklines()): diff --git a/GPy/plotting/matplot_dep/dim_reduction_plots.py b/GPy/plotting/matplot_dep/dim_reduction_plots.py index 2c243e13..f428537d 100644 --- a/GPy/plotting/matplot_dep/dim_reduction_plots.py +++ b/GPy/plotting/matplot_dep/dim_reduction_plots.py @@ -9,7 +9,8 @@ import itertools try: import Tango from matplotlib.cm import get_cmap - import pylab as pb + from matplotlib import pyplot as pb + from matplotlib import cm except: pass @@ -114,7 +115,7 @@ def plot_latent(model, labels=None, which_indices=None, # create a function which computes the shading of latent space according to the output variance def plot_function(x): - Xtest_full = np.zeros((x.shape[0], model.X.shape[1])) + Xtest_full = np.zeros((x.shape[0], X.shape[1])) Xtest_full[:, [input_1, input_2]] = x _, var = model.predict(Xtest_full, **predict_kwargs) var = var[:, :1] @@ -137,7 +138,7 @@ def plot_latent(model, labels=None, which_indices=None, view = ImshowController(ax, plot_function, (xmin, ymin, xmax, ymax), resolution, aspect=aspect, interpolation='bilinear', - cmap=pb.cm.binary, **imshow_kwargs) + cmap=cm.binary, **imshow_kwargs) # make sure labels are in order of input: labels = np.asarray(labels) @@ -192,17 +193,18 @@ def plot_latent(model, labels=None, which_indices=None, if updates: try: - ax.figure.canvas.show() + fig.canvas.show() except Exception as e: print("Could not invoke show: {}".format(e)) - raw_input('Enter to continue') - view.deactivate() + #raw_input('Enter to continue') + return view return ax def plot_magnification(model, labels=None, which_indices=None, resolution=60, ax=None, marker='o', s=40, fignum=None, plot_inducing=False, legend=True, - aspect='auto', updates=False): + plot_limits=None, + aspect='auto', updates=False, mean=True, covariance=True, kern=None): """ :param labels: a np.array of size model.num_data containing labels for the points (can be number, strings, etc) :param resolution: the resolution of the grid on which to evaluate the predictive variance @@ -210,6 +212,8 @@ def plot_magnification(model, labels=None, which_indices=None, if ax is None: fig = pb.figure(num=fignum) ax = fig.add_subplot(111) + else: + fig = ax.figure Tango.reset() if labels is None: @@ -217,19 +221,90 @@ def plot_magnification(model, labels=None, which_indices=None, input_1, input_2 = most_significant_input_dimensions(model, which_indices) - # first, plot the output variance as a function of the latent space - Xtest, xx, yy, xmin, xmax = x_frame2D(model.X[:, [input_1, input_2]], resolution=resolution) - Xtest_full = np.zeros((Xtest.shape[0], model.X.shape[1])) + #fethch the data points X that we'd like to plot + X = model.X + if isinstance(X, VariationalPosterior): + X = X.mean + else: + X = X + + if X.shape[0] > 1000: + print("Warning: subsampling X, as it has more samples then 1000. X.shape={!s}".format(X.shape)) + subsample = np.random.choice(X.shape[0], size=1000, replace=False) + X = X[subsample] + labels = labels[subsample] + #======================================================================= + # <<>> + # <<>> + # plt.close('all') + # fig, ax = plt.subplots(1,1) + # from GPy.plotting.matplot_dep.dim_reduction_plots import most_significant_input_dimensions + # import matplotlib.patches as mpatches + # i1, i2 = most_significant_input_dimensions(m, None) + # xmin, xmax = 100, -100 + # ymin, ymax = 100, -100 + # legend_handles = [] + # + # X = m.X.mean[:, [i1, i2]] + # X = m.X.variance[:, [i1, i2]] + # + # xmin = X[:,0].min(); xmax = X[:,0].max() + # ymin = X[:,1].min(); ymax = X[:,1].max() + # range_ = [[xmin, xmax], [ymin, ymax]] + # ul = np.unique(labels) + # + # for i, l in enumerate(ul): + # #cdict = dict(red =[(0., colors[i][0], colors[i][0]), (1., colors[i][0], colors[i][0])], + # # green=[(0., colors[i][0], colors[i][1]), (1., colors[i][1], colors[i][1])], + # # blue =[(0., colors[i][0], colors[i][2]), (1., colors[i][2], colors[i][2])], + # # alpha=[(0., 0., .0), (.5, .5, .5), (1., .5, .5)]) + # #cmap = LinearSegmentedColormap('{}'.format(l), cdict) + # cmap = LinearSegmentedColormap.from_list('cmap_{}'.format(str(l)), [colors[i], colors[i]], 255) + # cmap._init() + # #alphas = .5*(1+scipy.special.erf(np.linspace(-2,2, cmap.N+3)))#np.log(np.linspace(np.exp(0), np.exp(1.), cmap.N+3)) + # alphas = (scipy.special.erf(np.linspace(0,2.4, cmap.N+3)))#np.log(np.linspace(np.exp(0), np.exp(1.), cmap.N+3)) + # cmap._lut[:, -1] = alphas + # print l + # x, y = X[labels==l].T + # + # heatmap, xedges, yedges = np.histogram2d(x, y, bins=300, range=range_) + # #heatmap, xedges, yedges = np.histogram2d(x, y, bins=100) + # + # im = ax.imshow(heatmap, extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]], cmap=cmap, aspect='auto', interpolation='nearest', label=str(l)) + # legend_handles.append(mpatches.Patch(color=colors[i], label=l)) + # ax.set_xlim(xmin, xmax) + # ax.set_ylim(ymin, ymax) + # plt.legend(legend_handles, [l.get_label() for l in legend_handles]) + # plt.draw() + # plt.show() + #======================================================================= + + #Create an IMshow controller that can re-plot the latent space shading at a good resolution + if plot_limits is None: + xmin, ymin = X[:, [input_1, input_2]].min(0) + xmax, ymax = X[:, [input_1, input_2]].max(0) + x_r, y_r = xmax-xmin, ymax-ymin + xmin -= .1*x_r + xmax += .1*x_r + ymin -= .1*y_r + ymax += .1*y_r + else: + try: + xmin, xmax, ymin, ymax = plot_limits + except (TypeError, ValueError) as e: + raise e.__class__("Wrong plot limits: {} given -> need (xmin, xmax, ymin, ymax)".format(plot_limits)) + def plot_function(x): + Xtest_full = np.zeros((x.shape[0], X.shape[1])) Xtest_full[:, [input_1, input_2]] = x - mf=model.magnification(Xtest_full) + mf = model.predict_magnification(Xtest_full, kern=kern, mean=mean, covariance=covariance) return mf view = ImshowController(ax, plot_function, - tuple(model.X.min(0)[:, [input_1, input_2]]) + tuple(model.X.max(0)[:, [input_1, input_2]]), + (xmin, ymin, xmax, ymax), resolution, aspect=aspect, interpolation='bilinear', - cmap=pb.cm.gray) + cmap=cm.get_cmap('Greys')) # make sure labels are in order of input: ulabels = [] @@ -245,17 +320,17 @@ def plot_magnification(model, labels=None, which_indices=None, elif type(ul) is np.int64: this_label = 'class %i' % ul else: - this_label = 'class %i' % i + this_label = unicode(ul) m = marker.next() index = np.nonzero(labels == ul)[0] if model.input_dim == 1: - x = model.X[index, input_1] + x = X[index, input_1] y = np.zeros(index.size) else: - x = model.X[index, input_1] - y = model.X[index, input_2] - ax.scatter(x, y, marker=m, s=s, color=Tango.nextMedium(), label=this_label) + x = X[index, input_1] + y = X[index, input_2] + ax.scatter(x, y, marker=m, s=s, c=Tango.nextMedium(), label=this_label, linewidth=.2, edgecolor='k', alpha=.9) ax.set_xlabel('latent dimension %i' % input_1) ax.set_ylabel('latent dimension %i' % input_2) @@ -263,19 +338,29 @@ def plot_magnification(model, labels=None, which_indices=None, if not np.all(labels == 1.) and legend: ax.legend(loc=0, numpoints=1) - ax.set_xlim(xmin[0], xmax[0]) - ax.set_ylim(xmin[1], xmax[1]) - ax.grid(b=False) # remove the grid if present, it doesn't look good - ax.set_aspect('auto') # set a nice aspect ratio + ax.set_xlim((xmin, xmax)) + ax.set_ylim((ymin, ymax)) - if plot_inducing: - ax.plot(model.Z[:, input_1], model.Z[:, input_2], '^w') + if plot_inducing and hasattr(model, 'Z'): + Z = model.Z + ax.scatter(Z[:, input_1], Z[:, input_2], c='w', s=18, marker="^", edgecolor='k', linewidth=.3, alpha=.7) + + try: + fig.canvas.draw() + fig.tight_layout() + fig.canvas.draw() + except Exception as e: + print("Could not invoke tight layout: {}".format(e)) + pass if updates: - fig.canvas.show() - raw_input('Enter to continue') - - pb.title('Magnification Factor') + try: + fig.canvas.draw() + fig.canvas.show() + except Exception as e: + print("Could not invoke show: {}".format(e)) + #raw_input('Enter to continue') + return view return ax @@ -314,8 +399,8 @@ def plot_steepest_gradient_map(model, fignum=None, ax=None, which_indices=None, this_label = 'class %i' % i m = marker.next() index = np.nonzero(data_labels == ul)[0] - x = model.X[index, input_1] - y = model.X[index, input_2] + x = X[index, input_1] + y = X[index, input_2] ax.scatter(x, y, marker=m, s=data_s, color=Tango.nextMedium(), label=this_label) ax.set_xlabel('latent dimension %i' % input_1) @@ -323,7 +408,7 @@ def plot_steepest_gradient_map(model, fignum=None, ax=None, which_indices=None, controller = ImAnnotateController(ax, plot_function, - tuple(model.X.min(0)[:, significant_dims]) + tuple(model.X.max(0)[:, significant_dims]), + tuple(X.min(0)[:, significant_dims]) + tuple(X.max(0)[:, significant_dims]), resolution=resolution, aspect=aspect, cmap=get_cmap('jet'), diff --git a/GPy/plotting/matplot_dep/inference_plots.py b/GPy/plotting/matplot_dep/inference_plots.py index 02007390..ab6e5eaf 100644 --- a/GPy/plotting/matplot_dep/inference_plots.py +++ b/GPy/plotting/matplot_dep/inference_plots.py @@ -2,7 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) try: - import pylab as pb + from matplotlib import pyplot as pb except: pass #import numpy as np diff --git a/GPy/plotting/matplot_dep/kernel_plots.py b/GPy/plotting/matplot_dep/kernel_plots.py index aa015009..c8977cef 100644 --- a/GPy/plotting/matplot_dep/kernel_plots.py +++ b/GPy/plotting/matplot_dep/kernel_plots.py @@ -2,7 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np -import pylab as pb +from matplotlib import pyplot as pb import Tango from matplotlib.textpath import TextPath from matplotlib.transforms import offset_copy diff --git a/GPy/plotting/matplot_dep/latent_space_visualizations/controllers/axis_event_controller.py b/GPy/plotting/matplot_dep/latent_space_visualizations/controllers/axis_event_controller.py index 62b622c5..15fcd098 100644 --- a/GPy/plotting/matplot_dep/latent_space_visualizations/controllers/axis_event_controller.py +++ b/GPy/plotting/matplot_dep/latent_space_visualizations/controllers/axis_event_controller.py @@ -9,6 +9,9 @@ class AxisEventController(object): def __init__(self, ax): self.ax = ax self.activate() + def __del__(self): + self.deactivate() + return self def deactivate(self): for cb_class in self.ax.callbacks.callbacks.values(): for cb_num in cb_class.keys(): @@ -81,9 +84,9 @@ class BufferedAxisChangedController(AxisChangedController): def __init__(self, ax, plot_function, plot_limits, resolution=50, update_lim=None, **kwargs): """ Buffered axis changed controller. Controls the buffer and handles update events for when the axes changed. - + Updated plotting will be after first reload (first time will be within plot limits, after that the limits will be buffered) - + :param plot_function: function to use for creating image for plotting (return ndarray-like) plot_function gets called with (2D!) Xtest grid if replotting required diff --git a/GPy/plotting/matplot_dep/mapping_plots.py b/GPy/plotting/matplot_dep/mapping_plots.py index 53bc1de2..641b3fae 100644 --- a/GPy/plotting/matplot_dep/mapping_plots.py +++ b/GPy/plotting/matplot_dep/mapping_plots.py @@ -4,7 +4,7 @@ import numpy as np try: import Tango - import pylab as pb + from matplotlib import pyplot as pb except: pass from base_plots import x_frame1D, x_frame2D diff --git a/GPy/plotting/matplot_dep/maps.py b/GPy/plotting/matplot_dep/maps.py index f38c5d93..faec9eb3 100644 --- a/GPy/plotting/matplot_dep/maps.py +++ b/GPy/plotting/matplot_dep/maps.py @@ -2,7 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np try: - import pylab as pb + from matplotlib import pyplot as pb from matplotlib.patches import Polygon from matplotlib.collections import PatchCollection #from matplotlib import cm diff --git a/GPy/plotting/matplot_dep/models_plots.py b/GPy/plotting/matplot_dep/models_plots.py index e3bef675..0986c20e 100644 --- a/GPy/plotting/matplot_dep/models_plots.py +++ b/GPy/plotting/matplot_dep/models_plots.py @@ -1,25 +1,82 @@ # Copyright (c) 2012-2015, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) -try: - import Tango - import pylab as pb -except: - pass import numpy as np -from base_plots import gpplot, x_frame1D, x_frame2D +from . import Tango +from .base_plots import gpplot, x_frame1D, x_frame2D,gperrors from ...models.gp_coregionalized_regression import GPCoregionalizedRegression from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression from ...models.warped_gp import WarpedGP from scipy import sparse from ...core.parameterization.variational import VariationalPosterior +from matplotlib import pyplot as plt + + +def plot_data(model, which_data_rows='all', + which_data_ycols='all', visible_dims=None, + fignum=None, ax=None, data_symbol='kx',mew=1.5): + """ + Plot the training data + - For higher dimensions than two, use fixed_inputs to plot the data points with some of the inputs fixed. + + Can plot only part of the data + using which_data_rows and which_data_ycols. + + :param which_data_rows: which of the training data to plot (default all) + :type which_data_rows: 'all' or a slice object to slice model.X, model.Y + :param which_data_ycols: when the data has several columns (independant outputs), only plot these + :type which_data_rows: 'all' or a list of integers + :param visible_dims: an array specifying the input dimensions to plot (maximum two) + :type visible_dims: a numpy array + :param fignum: figure to plot on. + :type fignum: figure number + :param ax: axes to plot on. + :type ax: axes handle + """ + #deal with optional arguments + if which_data_rows == 'all': + which_data_rows = slice(None) + if which_data_ycols == 'all': + which_data_ycols = np.arange(model.output_dim) + + if ax is None: + fig = plt.figure(num=fignum) + ax = fig.add_subplot(111) + + #data + X = model.X + Y = model.Y + + #work out what the inputs are for plotting (1D or 2D) + if visible_dims is None: + visible_dims = np.arange(model.input_dim) + assert visible_dims.size <= 2, "Visible inputs cannot be larger than two" + free_dims = visible_dims + plots = {} + #one dimensional plotting + if len(free_dims) == 1: + + for d in which_data_ycols: + plots['dataplot'] = ax.plot(X[which_data_rows,free_dims], Y[which_data_rows, d], data_symbol, mew=mew) + + #2D plotting + elif len(free_dims) == 2: + + for d in which_data_ycols: + plots['dataplot'] = ax.scatter(X[which_data_rows, free_dims[0]], X[which_data_rows, free_dims[1]], 40, + Y[which_data_rows, d], cmap=plt.cm.jet, vmin=Y.min(), vmax=Y.max(), linewidth=0.) + + else: + raise NotImplementedError("Cannot define a frame with more than two input dimensions") + return plots + def plot_fit(model, plot_limits=None, which_data_rows='all', which_data_ycols='all', fixed_inputs=[], levels=20, samples=0, fignum=None, ax=None, resolution=None, plot_raw=False, linecol=Tango.colorsHex['darkBlue'],fillcol=Tango.colorsHex['lightBlue'], Y_metadata=None, data_symbol='kx', - apply_link=False, samples_f=0, plot_uncertain_inputs=True, predict_kw=None): + apply_link=False, samples_y=0, plot_uncertain_inputs=True, predict_kw=None, plot_training_data=True): """ Plot the posterior of the GP. - In one dimension, the function is plotted with a shaded region identifying two standard deviations. @@ -37,25 +94,32 @@ def plot_fit(model, plot_limits=None, which_data_rows='all', :type which_data_rows: 'all' or a list of integers :param fixed_inputs: a list of tuple [(i,v), (i,v)...], specifying that input index i should be set to value v. :type fixed_inputs: a list of tuples - :param resolution: the number of intervals to sample the GP on. Defaults to 200 in 1D and 50 (a 50x50 grid) in 2D - :type resolution: int - :param levels: number of levels to plot in a contour plot. + :param levels: for 2D plotting, the number of contour levels to use is ax is None, create a new figure :type levels: int - :param samples: the number of a posteriori samples to plot p(y*|y) + :param samples: the number of a posteriori samples to plot p(f*|y) :type samples: int :param fignum: figure to plot on. :type fignum: figure number :param ax: axes to plot on. :type ax: axes handle - :type output: integer (first output is 0) + :param resolution: the number of intervals to sample the GP on. Defaults to 200 in 1D and 50 (a 50x50 grid) in 2D + :type resolution: int + :param plot_raw: Whether to plot the raw function p(f|y) + :type plot_raw: boolean :param linecol: color of line to plot. - :type linecol: + :type linecol: hex or color :param fillcol: color of fill - :param levels: for 2D plotting, the number of contour levels to use is ax is None, create a new figure - :param apply_link: apply the link function if plotting f (default false) + :type fillcol: hex or color + :param apply_link: apply the link function if plotting f (default false), as well as posterior samples if requested :type apply_link: boolean - :param samples_f: the number of posteriori f samples to plot p(f*|y) - :type samples_f: int + :param samples_y: the number of posteriori f samples to plot p(y*|y) + :type samples_y: int + :param plot_uncertain_inputs: plot the uncertainty of the inputs as error bars if they have uncertainty (BGPLVM etc.) + :type plot_uncertain_inputs: boolean + :param predict_kw: keyword args for _raw_predict and predict functions if required + :type predict_kw: dict + :param plot_training_data: whether or not to plot the training points + :type plot_training_data: boolean """ #deal with optional arguments if which_data_rows == 'all': @@ -65,7 +129,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all', #if len(which_data_ycols)==0: #raise ValueError('No data selected for plotting') if ax is None: - fig = pb.figure(num=fignum) + fig = plt.figure(num=fignum) ax = fig.add_subplot(111) if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs(): @@ -117,31 +181,38 @@ def plot_fit(model, plot_limits=None, which_data_rows='all', Y_metadata = {'output_index': extra_data} else: Y_metadata['output_index'] = extra_data + if isinstance(model, WarpedGP): m, v = model.predict(Xgrid, full_cov=False, median=True, Y_metadata=Y_metadata, **predict_kw) #print np.concatenate((Xgrid, m), axis=1) else: m, v = model.predict(Xgrid, full_cov=False, Y_metadata=Y_metadata, **predict_kw) - lower, upper = model.predict_quantiles(Xgrid, Y_metadata=Y_metadata) + fmu, fv = model._raw_predict(Xgrid, full_cov=False, **predict_kw) + lower, upper = model.likelihood.predictive_quantiles(fmu, fv, (2.5, 97.5), Y_metadata=Y_metadata) + for d in which_data_ycols: plots['gpplot'] = gpplot(Xnew, m[:, d], lower[:, d], upper[:, d], ax=ax, edgecol=linecol, fillcol=fillcol) - if not plot_raw: plots['dataplot'] = ax.plot(X[which_data_rows,free_dims], Y[which_data_rows, d], data_symbol, mew=1.5) + #if not plot_raw: plots['dataplot'] = ax.plot(X[which_data_rows,free_dims], Y[which_data_rows, d], data_symbol, mew=1.5) + if not plot_raw and plot_training_data: + plots['dataplot'] = plot_data(model=model, which_data_rows=which_data_rows, + visible_dims=free_dims, data_symbol=data_symbol, mew=1.5, ax=ax, fignum=fignum) + #optionally plot some samples if samples: #NOTE not tested with fixed_inputs - Ysim = model.posterior_samples(Xgrid, samples, Y_metadata=Y_metadata) - print Ysim.shape - print Xnew.shape - for yi in Ysim.T: - plots['posterior_samples'] = ax.plot(Xnew, yi[:,None], Tango.colorsHex['darkBlue'], linewidth=0.25) - #ax.plot(Xnew, yi[:,None], marker='x', linestyle='--',color=Tango.colorsHex['darkBlue']) #TODO apply this line for discrete outputs. - - if samples_f: #NOTE not tested with fixed_inputs - Fsim = model.posterior_samples_f(Xgrid, samples_f) + Fsim = model.posterior_samples_f(Xgrid, samples) + if apply_link: + Fsim = model.likelihood.gp_link.transf(Fsim) for fi in Fsim.T: - plots['posterior_samples_f'] = ax.plot(Xnew, fi[:,None], Tango.colorsHex['darkBlue'], linewidth=0.25) + plots['posterior_samples'] = ax.plot(Xnew, fi[:,None], '#3300FF', linewidth=0.25) + #ax.plot(Xnew, fi[:,None], marker='x', linestyle='--',color=Tango.colorsHex['darkBlue']) #TODO apply this line for discrete outputs. + + if samples_y: #NOTE not tested with fixed_inputs + Ysim = model.posterior_samples(Xgrid, samples_y, Y_metadata=Y_metadata) + for yi in Ysim.T: + plots['posterior_samples_y'] = ax.scatter(Xnew, yi[:,None], s=5, c=Tango.colorsHex['darkBlue'], marker='o', alpha=0.5) #ax.plot(Xnew, yi[:,None], marker='x', linestyle='--',color=Tango.colorsHex['darkBlue']) #TODO apply this line for discrete outputs. @@ -206,8 +277,10 @@ def plot_fit(model, plot_limits=None, which_data_rows='all', m, v = model.predict(Xgrid, full_cov=False, Y_metadata=Y_metadata, **predict_kw) for d in which_data_ycols: m_d = m[:,d].reshape(resolution, resolution).T - plots['contour'] = ax.contour(x, y, m_d, levels, vmin=m.min(), vmax=m.max(), cmap=pb.cm.jet) - if not plot_raw: plots['dataplot'] = ax.scatter(X[which_data_rows, free_dims[0]], X[which_data_rows, free_dims[1]], 40, Y[which_data_rows, d], cmap=pb.cm.jet, vmin=m.min(), vmax=m.max(), linewidth=0.) + plots['contour'] = ax.contour(x, y, m_d, levels, vmin=m.min(), vmax=m.max(), cmap=plt.cm.jet) + #if not plot_raw: plots['dataplot'] = ax.scatter(X[which_data_rows, free_dims[0]], X[which_data_rows, free_dims[1]], 40, Y[which_data_rows, d], cmap=plt.cm.jet, vmin=m.min(), vmax=m.max(), linewidth=0.) + if not plot_raw and plot_training_data: + plots['dataplot'] = ax.scatter(X[which_data_rows, free_dims[0]], X[which_data_rows, free_dims[1]], 40, Y[which_data_rows, d], cmap=plt.cm.jet, vmin=m.min(), vmax=m.max(), linewidth=0.) #set the limits of the plot to some sensible values ax.set_xlim(xmin[0], xmax[0]) @@ -272,3 +345,82 @@ def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True, X_ return f_inputs else: return X + + +def errorbars_trainset(model, which_data_rows='all', + which_data_ycols='all', fixed_inputs=[], + fignum=None, ax=None, + linecol='red', data_symbol='kx', + predict_kw=None, plot_training_data=True, **kwargs): + + """ + Plot the posterior error bars corresponding to the training data + - For higher dimensions than two, use fixed_inputs to plot the data points with some of the inputs fixed. + + Can plot only part of the data + using which_data_rows and which_data_ycols. + + :param which_data_rows: which of the training data to plot (default all) + :type which_data_rows: 'all' or a slice object to slice model.X, model.Y + :param which_data_ycols: when the data has several columns (independant outputs), only plot these + :type which_data_rows: 'all' or a list of integers + :param fixed_inputs: a list of tuple [(i,v), (i,v)...], specifying that input index i should be set to value v. + :type fixed_inputs: a list of tuples + :param fignum: figure to plot on. + :type fignum: figure number + :param ax: axes to plot on. + :type ax: axes handle + :param plot_training_data: whether or not to plot the training points + :type plot_training_data: boolean + """ + + #deal with optional arguments + if which_data_rows == 'all': + which_data_rows = slice(None) + if which_data_ycols == 'all': + which_data_ycols = np.arange(model.output_dim) + + if ax is None: + fig = plt.figure(num=fignum) + ax = fig.add_subplot(111) + + X = model.X + Y = model.Y + + if predict_kw is None: + predict_kw = {} + + + #work out what the inputs are for plotting (1D or 2D) + fixed_dims = np.array([i for i,v in fixed_inputs]) + free_dims = np.setdiff1d(np.arange(model.input_dim),fixed_dims) + plots = {} + + #one dimensional plotting + if len(free_dims) == 1: + + m, v = model.predict(X, full_cov=False, Y_metadata=model.Y_metadata, **predict_kw) + fmu, fv = model._raw_predict(X, full_cov=False, **predict_kw) + lower, upper = model.likelihood.predictive_quantiles(fmu, fv, (2.5, 97.5), Y_metadata=model.Y_metadata) + + for d in which_data_ycols: + plots['gperrors'] = gperrors(X, m[:, d], lower[:, d], upper[:, d], edgecol=linecol, ax=ax, fignum=fignum, **kwargs ) + if plot_training_data: + plots['dataplot'] = plot_data(model=model, which_data_rows=which_data_rows, + visible_dims=free_dims, data_symbol=data_symbol, mew=1.5, ax=ax, fignum=fignum) + + + #set the limits of the plot to some sensible values + ymin, ymax = min(np.append(Y[which_data_rows, which_data_ycols].flatten(), lower)), max(np.append(Y[which_data_rows, which_data_ycols].flatten(), upper)) + ymin, ymax = ymin - 0.1 * (ymax - ymin), ymax + 0.1 * (ymax - ymin) + ax.set_xlim(X[:,free_dims].min(), X[:,free_dims].max()) + ax.set_ylim(ymin, ymax) + + + elif len(free_dims) == 2: + raise NotImplementedError("Not implemented yet") + + + else: + raise NotImplementedError("Cannot define a frame with more than two input dimensions") + return plots diff --git a/GPy/plotting/matplot_dep/priors_plots.py b/GPy/plotting/matplot_dep/priors_plots.py index 39dad631..51d84f86 100644 --- a/GPy/plotting/matplot_dep/priors_plots.py +++ b/GPy/plotting/matplot_dep/priors_plots.py @@ -4,7 +4,7 @@ import numpy as np try: - import pylab as pb + from matplotlib import pyplot as pb except: pass diff --git a/GPy/plotting/matplot_dep/svig_plots.py b/GPy/plotting/matplot_dep/svig_plots.py index 95344643..7152e8a6 100644 --- a/GPy/plotting/matplot_dep/svig_plots.py +++ b/GPy/plotting/matplot_dep/svig_plots.py @@ -2,7 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np -import pylab as pb +from matplotlib import pyplot as pb def plot(model, ax=None, fignum=None, Z_height=None, **kwargs): diff --git a/GPy/plotting/matplot_dep/variational_plots.py b/GPy/plotting/matplot_dep/variational_plots.py index 5a62e5d8..24e613aa 100644 --- a/GPy/plotting/matplot_dep/variational_plots.py +++ b/GPy/plotting/matplot_dep/variational_plots.py @@ -1,4 +1,4 @@ -import pylab as pb, numpy as np +from matplotlib import pyplot as pb, numpy as np def plot(parameterized, fignum=None, ax=None, colors=None, figsize=(12, 6)): """ diff --git a/GPy/testing/bgplvm_minibatch_tests.py b/GPy/testing/bgplvm_minibatch_tests.py new file mode 100644 index 00000000..4a824368 --- /dev/null +++ b/GPy/testing/bgplvm_minibatch_tests.py @@ -0,0 +1,109 @@ +''' +Created on 4 Sep 2015 + +@author: maxz +''' +import unittest +import numpy as np +import GPy + +class BGPLVMTest(unittest.TestCase): + + + def setUp(self): + np.random.seed(12345) + X, W = np.random.normal(0,1,(100,6)), np.random.normal(0,1,(6,13)) + Y = X.dot(W) + np.random.normal(0, .1, (X.shape[0], W.shape[1])) + self.inan = np.random.binomial(1, .1, Y.shape).astype(bool) + self.X, self.W, self.Y = X,W,Y + self.Q = 3 + self.m_full = GPy.models.BayesianGPLVM(Y, self.Q) + + def test_lik_comparisons_m1_s0(self): + # Test if the different implementations give the exact same likelihood as the full model. + # All of the following settings should give the same likelihood and gradients as the full model: + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=False) + m[:] = self.m_full[:] + np.testing.assert_almost_equal(m.log_likelihood(), self.m_full.log_likelihood(), 7) + np.testing.assert_allclose(m.gradient, self.m_full.gradient) + assert(m.checkgrad()) + + def test_predict_missing_data(self): + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=True, batchsize=self.Y.shape[1]) + m[:] = self.m_full[:] + np.testing.assert_almost_equal(m.log_likelihood(), self.m_full.log_likelihood(), 7) + np.testing.assert_allclose(m.gradient, self.m_full.gradient) + + self.assertRaises(NotImplementedError, m.predict, m.X, full_cov=True) + + mu1, var1 = m.predict(m.X, full_cov=False) + mu2, var2 = self.m_full.predict(self.m_full.X, full_cov=False) + np.testing.assert_allclose(mu1, mu2) + np.testing.assert_allclose(var1, var2) + + mu1, var1 = m.predict(m.X.mean, full_cov=True) + mu2, var2 = self.m_full.predict(self.m_full.X.mean, full_cov=True) + np.testing.assert_allclose(mu1, mu2) + np.testing.assert_allclose(var1[:,:,0], var2) + + mu1, var1 = m.predict(m.X.mean, full_cov=False) + mu2, var2 = self.m_full.predict(self.m_full.X.mean, full_cov=False) + np.testing.assert_allclose(mu1, mu2) + np.testing.assert_allclose(var1[:,[0]], var2) + + def test_lik_comparisons_m0_s0(self): + # Test if the different implementations give the exact same likelihood as the full model. + # All of the following settings should give the same likelihood and gradients as the full model: + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=False, stochastic=False) + m[:] = self.m_full[:] + np.testing.assert_almost_equal(m.log_likelihood(), self.m_full.log_likelihood(), 7) + np.testing.assert_allclose(m.gradient, self.m_full.gradient) + assert(m.checkgrad()) + + def test_lik_comparisons_m1_s1(self): + # Test if the different implementations give the exact same likelihood as the full model. + # All of the following settings should give the same likelihood and gradients as the full model: + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=True, batchsize=self.Y.shape[1]) + m[:] = self.m_full[:] + np.testing.assert_almost_equal(m.log_likelihood(), self.m_full.log_likelihood(), 7) + np.testing.assert_allclose(m.gradient, self.m_full.gradient) + assert(m.checkgrad()) + + def test_lik_comparisons_m0_s1(self): + # Test if the different implementations give the exact same likelihood as the full model. + # All of the following settings should give the same likelihood and gradients as the full model: + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=False, stochastic=True, batchsize=self.Y.shape[1]) + m[:] = self.m_full[:] + np.testing.assert_almost_equal(m.log_likelihood(), self.m_full.log_likelihood(), 7) + np.testing.assert_allclose(m.gradient, self.m_full.gradient) + assert(m.checkgrad()) + + def test_gradients_missingdata(self): + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=False, batchsize=self.Y.shape[1]) + assert(m.checkgrad()) + + def test_gradients_missingdata_stochastics(self): + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=True, batchsize=1) + assert(m.checkgrad()) + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=True, batchsize=4) + assert(m.checkgrad()) + + def test_gradients_stochastics(self): + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=False, stochastic=True, batchsize=1) + assert(m.checkgrad()) + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=False, stochastic=True, batchsize=4) + assert(m.checkgrad()) + + def test_predict(self): + # Test if the different implementations give the exact same likelihood as the full model. + # All of the following settings should give the same likelihood and gradients as the full model: + m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, missing_data=True, stochastic=True, batchsize=self.Y.shape[1]) + m[:] = self.m_full[:] + np.testing.assert_almost_equal(m.log_likelihood(), self.m_full.log_likelihood(), 7) + np.testing.assert_allclose(m.gradient, self.m_full.gradient) + assert(m.checkgrad()) + + +if __name__ == "__main__": + #import sys;sys.argv = ['', 'Test.testName'] + unittest.main() \ No newline at end of file diff --git a/GPy/testing/cacher_tests.py b/GPy/testing/cacher_tests.py new file mode 100644 index 00000000..60f79ba2 --- /dev/null +++ b/GPy/testing/cacher_tests.py @@ -0,0 +1,37 @@ +''' +Created on 4 Sep 2015 + +@author: maxz +''' +import unittest +from GPy.util.caching import Cacher +from pickle import PickleError + + +class Test(unittest.TestCase): + def setUp(self): + def op(x): + return x + self.cache = Cacher(op, 1) + + def test_pickling(self): + self.assertRaises(PickleError, self.cache.__getstate__) + self.assertRaises(PickleError, self.cache.__setstate__) + + def test_copy(self): + tmp = self.cache.__deepcopy__() + assert(tmp.operation is self.cache.operation) + self.assertEqual(tmp.limit, self.cache.limit) + + def test_reset(self): + self.cache.reset() + self.assertDictEqual(self.cache.cached_input_ids, {}, ) + self.assertDictEqual(self.cache.cached_outputs, {}, ) + self.assertDictEqual(self.cache.inputs_changed, {}, ) + + def test_name(self): + assert(self.cache.__name__ == self.cache.operation.__name__) + +if __name__ == "__main__": + #import sys;sys.argv = ['', 'Test.testName'] + unittest.main() \ No newline at end of file diff --git a/GPy/testing/cython_tests.py b/GPy/testing/cython_tests.py index f88f12f3..c4bca5cd 100644 --- a/GPy/testing/cython_tests.py +++ b/GPy/testing/cython_tests.py @@ -2,11 +2,21 @@ import numpy as np import scipy as sp from GPy.util import choleskies import GPy +from ..util.config import config +import unittest + +try: + from ..util import linalg_cython + from ..util import choleskies_cython + config.set('cython', 'working', 'True') +except ImportError: + config.set('cython', 'working', 'False') """ -These tests make sure that the opure python and cython codes work the same +These tests make sure that the pure python and cython codes work the same """ +@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") class CythonTestChols(np.testing.TestCase): def setUp(self): self.flat = np.random.randn(45,5) @@ -20,6 +30,7 @@ class CythonTestChols(np.testing.TestCase): A2 = choleskies._triang_to_flat_cython(self.triang) np.testing.assert_allclose(A1, A2) +@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") class test_stationary(np.testing.TestCase): def setUp(self): self.k = GPy.kern.RBF(10) @@ -49,17 +60,16 @@ class test_stationary(np.testing.TestCase): g2 = self.k._lengthscale_grads_cython(self.dKxz, self.X, self.Z) np.testing.assert_allclose(g1, g2) +@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") class test_choleskies_backprop(np.testing.TestCase): def setUp(self): - self.dL, self.L = np.random.randn(2, 100, 100) + a =np.random.randn(10,12) + A = a.dot(a.T) + self.L = GPy.util.linalg.jitchol(A) + self.dL = np.random.randn(10,10) def test(self): - r1 = GPy.util.choleskies._backprop_gradient_pure(self.dL, self.L) - r2 = GPy.util.choleskies.choleskies_cython.backprop_gradient(self.dL, self.L) + r1 = choleskies._backprop_gradient_pure(self.dL, self.L) + r2 = choleskies_cython.backprop_gradient(self.dL, self.L) + r3 = choleskies_cython.backprop_gradient_par_c(self.dL, self.L) np.testing.assert_allclose(r1, r2) - - - - - - - + np.testing.assert_allclose(r1, r3) diff --git a/GPy/testing/gp_tests.py b/GPy/testing/gp_tests.py new file mode 100644 index 00000000..63345c18 --- /dev/null +++ b/GPy/testing/gp_tests.py @@ -0,0 +1,99 @@ +''' +Created on 4 Sep 2015 + +@author: maxz +''' +import unittest +import numpy as np, GPy +from GPy.core.parameterization.variational import NormalPosterior + +class Test(unittest.TestCase): + + + def setUp(self): + np.random.seed(12345) + self.N = 20 + self.N_new = 50 + self.D = 1 + self.X = np.random.uniform(-3., 3., (self.N, 1)) + self.Y = np.sin(self.X) + np.random.randn(self.N, self.D) * 0.05 + self.X_new = np.random.uniform(-3., 3., (self.N_new, 1)) + + + def test_setxy_bgplvm(self): + k = GPy.kern.RBF(1) + m = GPy.models.BayesianGPLVM(self.Y, 2, kernel=k) + mu, var = m.predict(m.X) + X = m.X.copy() + Xnew = NormalPosterior(m.X.mean[:10].copy(), m.X.variance[:10].copy()) + m.set_XY(Xnew, m.Y[:10]) + assert(m.checkgrad()) + m.set_XY(X, self.Y) + mu2, var2 = m.predict(m.X) + np.testing.assert_allclose(mu, mu2) + np.testing.assert_allclose(var, var2) + + def test_setxy_gplvm(self): + k = GPy.kern.RBF(1) + m = GPy.models.GPLVM(self.Y, 2, kernel=k) + mu, var = m.predict(m.X) + X = m.X.copy() + Xnew = X[:10].copy() + m.set_XY(Xnew, m.Y[:10]) + assert(m.checkgrad()) + m.set_XY(X, self.Y) + mu2, var2 = m.predict(m.X) + np.testing.assert_allclose(mu, mu2) + np.testing.assert_allclose(var, var2) + + def test_setxy_gp(self): + k = GPy.kern.RBF(1) + m = GPy.models.GPRegression(self.X, self.Y, kernel=k) + mu, var = m.predict(m.X) + X = m.X.copy() + m.set_XY(m.X[:10], m.Y[:10]) + assert(m.checkgrad()) + m.set_XY(X, self.Y) + mu2, var2 = m.predict(m.X) + np.testing.assert_allclose(mu, mu2) + np.testing.assert_allclose(var, var2) + + def test_mean_function(self): + from GPy.core.parameterization.param import Param + from GPy.core.mapping import Mapping + class Parabola(Mapping): + def __init__(self, variance, degree=2, name='parabola'): + super(Parabola, self).__init__(1, 1, name) + self.variance = Param('variance', np.ones(degree+1) * variance) + self.degree = degree + self.link_parameter(self.variance) + + def f(self, X): + p = self.variance[0] * np.ones(X.shape) + for i in range(1, self.degree+1): + p += self.variance[i] * X**(i) + return p + + def gradients_X(self, dL_dF, X): + grad = np.zeros(X.shape) + for i in range(1, self.degree+1): + grad += (i) * self.variance[i] * X**(i-1) + return grad + + def update_gradients(self, dL_dF, X): + for i in range(self.degree+1): + self.variance.gradient[i] = (dL_dF * X**(i)).sum(0) + X = np.linspace(-2, 2, 100)[:, None] + k = GPy.kern.RBF(1) + k.randomize() + p = Parabola(.3) + p.randomize() + Y = p.f(X) + np.random.multivariate_normal(np.zeros(X.shape[0]), k.K(X)+np.eye(X.shape[0])*1e-8)[:,None] + np.random.normal(0, .1, (X.shape[0], 1)) + m = GPy.models.GPRegression(X, Y, mean_function=p) + m.randomize() + assert(m.checkgrad()) + _ = m.predict(m.X) + +if __name__ == "__main__": + #import sys;sys.argv = ['', 'Test.testName'] + unittest.main() \ No newline at end of file diff --git a/GPy/testing/inference_tests.py b/GPy/testing/inference_tests.py index e09df1fe..c1fce8b9 100644 --- a/GPy/testing/inference_tests.py +++ b/GPy/testing/inference_tests.py @@ -8,11 +8,12 @@ The test cases for various inference algorithms import unittest, itertools import numpy as np import GPy - +#np.seterr(invalid='raise') class InferenceXTestCase(unittest.TestCase): def genData(self): + np.random.seed(1) D1,D2,N = 12,12,50 x = np.linspace(0, 4 * np.pi, N)[:, None] diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index 043d5e9a..cf102f99 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -6,9 +6,16 @@ import numpy as np import GPy import sys from GPy.core.parameterization.param import Param +from ..util.config import config verbose = 0 +try: + from ..util import linalg_cython + config.set('cython', 'working', 'True') +except ImportError: + config.set('cython', 'working', 'False') + class Kern_check_model(GPy.core.Model): """ @@ -245,6 +252,11 @@ class KernelGradientTestsContinuous(unittest.TestCase): continuous_kerns = ['RBF', 'Linear'] self.kernclasses = [getattr(GPy.kern, s) for s in continuous_kerns] + def test_MLP(self): + k = GPy.kern.MLP(self.D,ARD=True) + k.randomize() + self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + def test_Matern32(self): k = GPy.kern.Matern32(self.D) k.randomize() @@ -313,6 +325,11 @@ class KernelGradientTestsContinuous(unittest.TestCase): k.randomize() self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + def test_standard_periodic(self): + k = GPy.kern.StdPeriodic(self.D, self.D-1) + k.randomize() + self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + class KernelTestsMiscellaneous(unittest.TestCase): def setUp(self): N, D = 100, 10 @@ -366,6 +383,7 @@ class KernelTestsNonContinuous(unittest.TestCase): X2 = self.X2[self.X2[:,-1]!=2] self.assertTrue(check_kernel_gradient_functions(kern, X=X, X2=X2, verbose=verbose, fixed_X_dims=-1)) +@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") class Coregionalize_cython_test(unittest.TestCase): """ Make sure that the coregionalize kernel work with and without cython enabled @@ -432,6 +450,104 @@ class KernelTestsProductWithZeroValues(unittest.TestCase): self.assertFalse(np.any(np.isnan(target)), "Gradient resulted in NaN") +class Kernel_Psi_statistics_GradientTests(unittest.TestCase): + + def setUp(self): + from GPy.core.parameterization.variational import NormalPosterior + N,M,Q = 100,20,3 + + X = np.random.randn(N,Q) + X_var = np.random.rand(N,Q)+0.01 + self.Z = np.random.randn(M,Q) + self.qX = NormalPosterior(X, X_var) + + self.w1 = np.random.randn(N) + self.w2 = np.random.randn(N,M) + self.w3 = np.random.randn(M,M) + self.w3 = self.w3+self.w3.T + self.w3n = np.random.randn(N,M,M) + self.w3n = self.w3n+np.swapaxes(self.w3n, 1,2) + + def test_kernels(self): + from GPy.kern import RBF,Linear,MLP + Q = self.Z.shape[1] + kernels = [RBF(Q,ARD=True), Linear(Q,ARD=True)] + + for k in kernels: + k.randomize() + self._test_kernel_param(k) + self._test_Z(k) + self._test_qX(k) + self._test_kernel_param(k, psi2n=True) + self._test_Z(k, psi2n=True) + self._test_qX(k, psi2n=True) + + def _test_kernel_param(self, kernel, psi2n=False): + + def f(p): + kernel.param_array[:] = p + psi0 = kernel.psi0(self.Z, self.qX) + psi1 = kernel.psi1(self.Z, self.qX) + if not psi2n: + psi2 = kernel.psi2(self.Z, self.qX) + return (self.w1*psi0).sum() + (self.w2*psi1).sum() + (self.w3*psi2).sum() + else: + psi2 = kernel.psi2n(self.Z, self.qX) + return (self.w1*psi0).sum() + (self.w2*psi1).sum() + (self.w3n*psi2).sum() + + def df(p): + kernel.param_array[:] = p + kernel.update_gradients_expectations(self.w1, self.w2, self.w3 if not psi2n else self.w3n, self.Z, self.qX) + return kernel.gradient.copy() + + from GPy.models import GradientChecker + m = GradientChecker(f, df, kernel.param_array.copy()) + self.assertTrue(m.checkgrad()) + + def _test_Z(self, kernel, psi2n=False): + + def f(p): + psi0 = kernel.psi0(p, self.qX) + psi1 = kernel.psi1(p, self.qX) + psi2 = kernel.psi2(p, self.qX) + if not psi2n: + psi2 = kernel.psi2(p, self.qX) + return (self.w1*psi0).sum() + (self.w2*psi1).sum() + (self.w3*psi2).sum() + else: + psi2 = kernel.psi2n(p, self.qX) + return (self.w1*psi0).sum() + (self.w2*psi1).sum() + (self.w3n*psi2).sum() + + def df(p): + return kernel.gradients_Z_expectations(self.w1, self.w2, self.w3 if not psi2n else self.w3n, p, self.qX) + + from GPy.models import GradientChecker + m = GradientChecker(f, df, self.Z.copy()) + self.assertTrue(m.checkgrad()) + + def _test_qX(self, kernel, psi2n=False): + + def f(p): + self.qX.param_array[:] = p + self.qX._trigger_params_changed() + psi0 = kernel.psi0(self.Z, self.qX) + psi1 = kernel.psi1(self.Z, self.qX) + if not psi2n: + psi2 = kernel.psi2(self.Z, self.qX) + return (self.w1*psi0).sum() + (self.w2*psi1).sum() + (self.w3*psi2).sum() + else: + psi2 = kernel.psi2n(self.Z, self.qX) + return (self.w1*psi0).sum() + (self.w2*psi1).sum() + (self.w3n*psi2).sum() + + def df(p): + self.qX.param_array[:] = p + self.qX._trigger_params_changed() + grad = kernel.gradients_qX_expectations(self.w1, self.w2, self.w3 if not psi2n else self.w3n, self.Z, self.qX) + self.qX.set_gradients(grad) + return self.qX.gradient.copy() + + from GPy.models import GradientChecker + m = GradientChecker(f, df, self.qX.param_array.copy()) + self.assertTrue(m.checkgrad()) if __name__ == "__main__": print("Running unit tests, please be (very) patient...") diff --git a/GPy/testing/likelihood_tests.py b/GPy/testing/likelihood_tests.py index 27b27892..1f634848 100644 --- a/GPy/testing/likelihood_tests.py +++ b/GPy/testing/likelihood_tests.py @@ -7,10 +7,8 @@ from GPy.models import GradientChecker import functools import inspect from GPy.likelihoods import link_functions -from GPy.core.parameterization import Param from functools import partial -#np.random.seed(300) -#np.random.seed(4) +fixed_seed = 7 #np.seterr(divide='raise') def dparam_partial(inst_func, *args): @@ -105,6 +103,7 @@ class TestNoiseModels(object): Generic model checker """ def setUp(self): + np.random.seed(fixed_seed) self.N = 15 self.D = 3 self.X = np.random.rand(self.N, self.D)*10 @@ -218,7 +217,8 @@ class TestNoiseModels(object): "constraints": [(".*variance", self.constrain_positive)] }, "laplace": True, - "ep": False # FIXME: Should be True when we have it working again + "ep": False, # FIXME: Should be True when we have it working again + "variational_expectations": True, }, "Gaussian_log": { "model": GPy.likelihoods.Gaussian(gp_link=link_functions.Log(), variance=self.var), @@ -227,7 +227,8 @@ class TestNoiseModels(object): "vals": [self.var], "constraints": [(".*variance", self.constrain_positive)] }, - "laplace": True + "laplace": True, + "variational_expectations": True }, #"Gaussian_probit": { #"model": GPy.likelihoods.gaussian(gp_link=link_functions.Probit(), variance=self.var, D=self.D, N=self.N), @@ -252,7 +253,8 @@ class TestNoiseModels(object): "link_f_constraints": [partial(self.constrain_bounded, lower=0, upper=1)], "laplace": True, "Y": self.binary_Y, - "ep": False # FIXME: Should be True when we have it working again + "ep": False, # FIXME: Should be True when we have it working again + "variational_expectations": True }, "Exponential_default": { "model": GPy.likelihoods.Exponential(), @@ -347,6 +349,10 @@ class TestNoiseModels(object): ep = attributes["ep"] else: ep = False + if "variational_expectations" in attributes: + var_exp = attributes["variational_expectations"] + else: + var_exp = False #if len(param_vals) > 1: #raise NotImplementedError("Cannot support multiple params in likelihood yet!") @@ -377,6 +383,11 @@ class TestNoiseModels(object): if ep: #ep likelihood gradcheck yield self.t_ep_fit_rbf_white, model, self.X, Y, f, Y_metadata, self.step, param_vals, param_names, param_constraints + if var_exp: + #Need to specify mu and var! + yield self.t_varexp, model, Y, Y_metadata + yield self.t_dexp_dmu, model, Y, Y_metadata + yield self.t_dexp_dvar, model, Y, Y_metadata self.tearDown() @@ -603,6 +614,87 @@ class TestNoiseModels(object): print(m) assert m.checkgrad(verbose=1, step=step) + ################ + # variational expectations # + ################ + @with_setup(setUp, tearDown) + def t_varexp(self, model, Y, Y_metadata): + #Test that the analytic implementation (if it exists) matches the generic gauss + #hermite implementation + print("\n{}".format(inspect.stack()[0][3])) + #Make mu and var (marginal means and variances of q(f)) draws from a GP + k = GPy.kern.RBF(1).K(np.linspace(0,1,Y.shape[0])[:, None]) + L = GPy.util.linalg.jitchol(k) + mu = L.dot(np.random.randn(*Y.shape)) + #Variance must be positive + var = np.abs(L.dot(np.random.randn(*Y.shape))) + 0.01 + + expectation = model.variational_expectations(Y=Y, m=mu, v=var, gh_points=None, Y_metadata=Y_metadata)[0] + + #Implementation of gauss hermite integration + shape = mu.shape + gh_x, gh_w= np.polynomial.hermite.hermgauss(50) + m,v,Y = mu.flatten(), var.flatten(), Y.flatten() + #make a grid of points + X = gh_x[None,:]*np.sqrt(2.*v[:,None]) + m[:,None] + #evaluate the likelhood for the grid. First ax indexes the data (and mu, var) and the second indexes the grid. + # broadcast needs to be handled carefully. + logp = model.logpdf(X, Y[:,None], Y_metadata=Y_metadata) + #average over the gird to get derivatives of the Gaussian's parameters + #division by pi comes from fact that for each quadrature we need to scale by 1/sqrt(pi) + expectation_gh = np.dot(logp, gh_w)/np.sqrt(np.pi) + expectation_gh = expectation_gh.reshape(*shape) + + np.testing.assert_almost_equal(expectation, expectation_gh, decimal=5) + + @with_setup(setUp, tearDown) + def t_dexp_dmu(self, model, Y, Y_metadata): + print("\n{}".format(inspect.stack()[0][3])) + #Make mu and var (marginal means and variances of q(f)) draws from a GP + k = GPy.kern.RBF(1).K(np.linspace(0,1,Y.shape[0])[:, None]) + L = GPy.util.linalg.jitchol(k) + mu = L.dot(np.random.randn(*Y.shape)) + #Variance must be positive + var = np.abs(L.dot(np.random.randn(*Y.shape))) + 0.01 + expectation = functools.partial(model.variational_expectations, Y=Y, v=var, gh_points=None, Y_metadata=Y_metadata) + + #Function to get the nth returned value + def F(mu): + return expectation(m=mu)[0] + def dmu(mu): + return expectation(m=mu)[1] + + grad = GradientChecker(F, dmu, mu.copy(), 'm') + + grad.randomize() + print(grad) + print(model) + assert grad.checkgrad(verbose=1) + + @with_setup(setUp, tearDown) + def t_dexp_dvar(self, model, Y, Y_metadata): + print("\n{}".format(inspect.stack()[0][3])) + #Make mu and var (marginal means and variances of q(f)) draws from a GP + k = GPy.kern.RBF(1).K(np.linspace(0,1,Y.shape[0])[:, None]) + L = GPy.util.linalg.jitchol(k) + mu = L.dot(np.random.randn(*Y.shape)) + #Variance must be positive + var = np.abs(L.dot(np.random.randn(*Y.shape))) + 0.01 + expectation = functools.partial(model.variational_expectations, Y=Y, m=mu, gh_points=None, Y_metadata=Y_metadata) + + #Function to get the nth returned value + def F(var): + return expectation(v=var)[0] + def dvar(var): + return expectation(v=var)[2] + + grad = GradientChecker(F, dvar, var.copy(), 'v') + + self.constrain_positive('v', grad) + #grad.randomize() + print(grad) + print(model) + assert grad.checkgrad(verbose=1) class LaplaceTests(unittest.TestCase): """ @@ -610,6 +702,7 @@ class LaplaceTests(unittest.TestCase): """ def setUp(self): + np.random.seed(fixed_seed) self.N = 15 self.D = 1 self.X = np.random.rand(self.N, self.D)*10 @@ -705,7 +798,7 @@ class LaplaceTests(unittest.TestCase): post_mean_approx, post_var_approx, = m2.predict(X) if debug: - import pylab as pb + from matplotlib import pyplot as pb pb.figure(5) pb.title('posterior means') pb.scatter(X, post_mean, c='g') diff --git a/GPy/testing/linalg_test.py b/GPy/testing/linalg_test.py index ec3aca5a..fd818433 100644 --- a/GPy/testing/linalg_test.py +++ b/GPy/testing/linalg_test.py @@ -1,7 +1,6 @@ import numpy as np import scipy as sp -from GPy.util.linalg import jitchol -import GPy +from ..util.linalg import jitchol,trace_dot, ijk_jlk_to_il, ijk_ljk_to_ilk class LinalgTests(np.testing.TestCase): def setUp(self): @@ -37,18 +36,19 @@ class LinalgTests(np.testing.TestCase): except sp.linalg.LinAlgError: return True - def test_einsum_ijk_jlk_to_il(self): - A = np.random.randn(50, 150, 5) - B = np.random.randn(150, 100, 5) - pure = np.einsum('ijk,jlk->il', A, B) - quick = GPy.util.linalg.ijk_jlk_to_il(A, B) - np.testing.assert_allclose(pure, quick) + def test_trace_dot(self): + N = 5 + A = np.random.rand(N,N) + B = np.random.rand(N,N) + trace = np.trace(A.dot(B)) + test_trace = trace_dot(A,B) + np.testing.assert_allclose(trace,test_trace,atol=1e-13) def test_einsum_ij_jlk_to_ilk(self): A = np.random.randn(15, 150, 5) B = np.random.randn(150, 50, 5) pure = np.einsum('ijk,jlk->il', A, B) - quick = GPy.util.linalg.ijk_jlk_to_il(A,B) + quick = ijk_jlk_to_il(A,B) np.testing.assert_allclose(pure, quick) def test_einsum_ijk_ljk_to_ilk(self): @@ -56,5 +56,5 @@ class LinalgTests(np.testing.TestCase): B = np.random.randn(150, 20, 5) #B = A.copy() pure = np.einsum('ijk,ljk->ilk', A, B) - quick = GPy.util.linalg.ijk_ljk_to_ilk(A,B) + quick = ijk_ljk_to_ilk(A,B) np.testing.assert_allclose(pure, quick) diff --git a/GPy/testing/link_function_tests.py b/GPy/testing/link_function_tests.py index e8cbbf66..9f41f736 100644 --- a/GPy/testing/link_function_tests.py +++ b/GPy/testing/link_function_tests.py @@ -1,5 +1,5 @@ import numpy as np -import scipy as sp +import scipy from scipy.special import cbrt from GPy.models import GradientChecker _lim_val = np.finfo(np.float64).max @@ -79,8 +79,7 @@ class LinkFunctionTests(np.testing.TestCase): assert np.isinf(np.exp(np.log(self.f_upper_lim))) #Check the clipping works np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5) - #Need to look at most significant figures here rather than the decimals - np.testing.assert_approx_equal(link.transf(self.f_upper_lim), _lim_val, significant=5) + self.assertTrue(np.isfinite(link.transf(self.f_upper_lim))) self.check_overflow(link, lim_of_inf) #Check that it would otherwise fail @@ -93,18 +92,18 @@ class LinkFunctionTests(np.testing.TestCase): link = Log_ex_1() lim_of_inf = _lim_val_exp - np.testing.assert_almost_equal(np.log1p(np.exp(self.mid_f)), link.transf(self.mid_f)) - assert np.isinf(np.log1p(np.exp(np.log(self.f_upper_lim)))) + np.testing.assert_almost_equal(scipy.special.log1p(np.exp(self.mid_f)), link.transf(self.mid_f)) + assert np.isinf(scipy.special.log1p(np.exp(np.log(self.f_upper_lim)))) #Check the clipping works np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5) #Need to look at most significant figures here rather than the decimals - np.testing.assert_approx_equal(link.transf(self.f_upper_lim), np.log1p(_lim_val), significant=5) + np.testing.assert_approx_equal(link.transf(self.f_upper_lim), scipy.special.log1p(_lim_val), significant=5) self.check_overflow(link, lim_of_inf) #Check that it would otherwise fail beyond_lim_of_inf = lim_of_inf + 10.0 old_err_state = np.seterr(over='ignore') - self.assertTrue(np.isinf(np.log1p(np.exp(beyond_lim_of_inf)))) + self.assertTrue(np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf)))) np.seterr(**old_err_state) diff --git a/GPy/testing/misc_tests.py b/GPy/testing/misc_tests.py index e620fa7e..8f418565 100644 --- a/GPy/testing/misc_tests.py +++ b/GPy/testing/misc_tests.py @@ -1,6 +1,8 @@ +from __future__ import print_function import numpy as np import scipy as sp import GPy +import warnings class MiscTests(np.testing.TestCase): """ @@ -11,8 +13,15 @@ class MiscTests(np.testing.TestCase): self._lim_val_exp = np.log(self._lim_val) def test_safe_exp_upper(self): - assert np.exp(self._lim_val_exp + 1) == np.inf - assert GPy.util.misc.safe_exp(self._lim_val_exp + 1) < np.inf + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') # always print + assert np.isfinite(np.exp(self._lim_val_exp)) + assert np.isinf(np.exp(self._lim_val_exp + 1)) + assert np.isfinite(GPy.util.misc.safe_exp(self._lim_val_exp + 1)) + + print(w) + print(len(w)) + assert len(w)<=1 # should have one overflow warning def test_safe_exp_lower(self): assert GPy.util.misc.safe_exp(1e-10) < np.inf diff --git a/GPy/testing/model_tests.py b/GPy/testing/model_tests.py index ca2dce07..39022aff 100644 --- a/GPy/testing/model_tests.py +++ b/GPy/testing/model_tests.py @@ -15,6 +15,13 @@ class MiscTests(unittest.TestCase): self.Y = np.sin(self.X) + np.random.randn(self.N, self.D) * 0.05 self.X_new = np.random.uniform(-3., 3., (self.N_new, 1)) + def test_setXY(self): + m = GPy.models.GPRegression(self.X, self.Y) + m.set_XY(np.vstack([self.X, np.random.rand(1,self.X.shape[1])]), np.vstack([self.Y, np.random.rand(1,self.Y.shape[1])])) + m._trigger_params_changed() + self.assertTrue(m.checkgrad()) + m.predict(m.X) + def test_raw_predict(self): k = GPy.kern.RBF(1) m = GPy.models.GPRegression(self.X, self.Y, kernel=k) @@ -36,12 +43,78 @@ class MiscTests(unittest.TestCase): np.testing.assert_almost_equal(np.diag(K_hat)[:, None], var) np.testing.assert_almost_equal(mu_hat, mu) + def test_normalizer(self): + k = GPy.kern.RBF(1) + Y = self.Y + mu, std = Y.mean(0), Y.std(0) + m = GPy.models.GPRegression(self.X, Y, kernel=k, normalizer=True) + m.optimize() + assert(m.checkgrad()) + k = GPy.kern.RBF(1) + m2 = GPy.models.GPRegression(self.X, (Y-mu)/std, kernel=k, normalizer=False) + m2[:] = m[:] + mu1, var1 = m.predict(m.X, full_cov=True) + mu2, var2 = m2.predict(m2.X, full_cov=True) + np.testing.assert_allclose(mu1, (mu2*std)+mu) + np.testing.assert_allclose(var1, var2) + mu1, var1 = m.predict(m.X, full_cov=False) + mu2, var2 = m2.predict(m2.X, full_cov=False) + np.testing.assert_allclose(mu1, (mu2*std)+mu) + np.testing.assert_allclose(var1, var2) + + q50n = m.predict_quantiles(m.X, (50,)) + q50 = m2.predict_quantiles(m2.X, (50,)) + np.testing.assert_allclose(q50n[0], (q50[0]*std)+mu) + + def check_jacobian(self): + try: + import autograd.numpy as np, autograd as ag, GPy, matplotlib.pyplot as plt + from GPy.models import GradientChecker, GPRegression + except: + raise self.skipTest("autograd not available to check gradients") + def k(X, X2, alpha=1., lengthscale=None): + if lengthscale is None: + lengthscale = np.ones(X.shape[1]) + exp = 0. + for q in range(X.shape[1]): + exp += ((X[:, [q]] - X2[:, [q]].T)/lengthscale[q])**2 + #exp = np.sqrt(exp) + return alpha * np.exp(-.5*exp) + dk = ag.elementwise_grad(lambda x, x2: k(x, x2, alpha=ke.variance.values, lengthscale=ke.lengthscale.values)) + dkdk = ag.elementwise_grad(dk, argnum=1) + + ke = GPy.kern.RBF(1, ARD=True) + #ke.randomize() + ke.variance = .2#.randomize() + ke.lengthscale[:] = .5 + ke.randomize() + X = np.linspace(-1, 1, 1000)[:,None] + X2 = np.array([[0.]]).T + np.testing.assert_allclose(ke.gradients_X([[1.]], X, X), dk(X, X)) + np.testing.assert_allclose(ke.gradients_XX([[1.]], X, X).sum(0), dkdk(X, X)) + np.testing.assert_allclose(ke.gradients_X([[1.]], X, X2), dk(X, X2)) + np.testing.assert_allclose(ke.gradients_XX([[1.]], X, X2).sum(0), dkdk(X, X2)) + + m = GPRegression(self.X, self.Y) + def f(x): + m.X[:] = x + return m.log_likelihood() + def df(x): + m.X[:] = x + return m.kern.gradients_X(m.grad_dict['dL_dK'], X) + def ddf(x): + m.X[:] = x + return m.kern.gradients_XX(m.grad_dict['dL_dK'], X).sum(0) + gc = GradientChecker(f, df, self.X) + gc2 = GradientChecker(df, ddf, self.X) + assert(gc.checkgrad()) + assert(gc2.checkgrad()) + def test_sparse_raw_predict(self): k = GPy.kern.RBF(1) m = GPy.models.SparseGPRegression(self.X, self.Y, kernel=k) m.randomize() Z = m.Z[:] - X = self.X[:] # Not easy to check if woodbury_inv is correct in itself as it requires a large derivation and expression Kinv = m.posterior.woodbury_inv @@ -127,11 +200,24 @@ class MiscTests(unittest.TestCase): m = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing, kernel=k, missing_data=True) assert(m.checkgrad()) + mul, varl = m.predict(m.X) k = kern.RBF(Q, ARD=True) + kern.White(Q, np.exp(-2)) # + kern.bias(Q) - m = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing, + m2 = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing, kernel=k, missing_data=True) assert(m.checkgrad()) + m2.kern.rbf.lengthscale[:] = 1e6 + m2.X[:] = m.X.param_array + m2.likelihood[:] = m.likelihood[:] + m2.kern.white[:] = m.kern.white[:] + mu, var = m.predict(m.X) + np.testing.assert_allclose(mul, mu) + np.testing.assert_allclose(varl, var) + + q50 = m.predict_quantiles(m.X, (50,)) + np.testing.assert_allclose(mul, q50[0]) + + def test_likelihood_replicate_kern(self): m = GPy.models.GPRegression(self.X, self.Y) @@ -410,8 +496,8 @@ class GradientTests(np.testing.TestCase): self.check_model(rbf, model_type='SparseGPRegression', dimension=2) def test_SparseGPRegression_rbf_linear_white_kern_1D(self): - ''' Testing the sparse GP regression with rbf kernel on 2d data ''' - rbflin = GPy.kern.RBF(1) + GPy.kern.Linear(1) + ''' Testing the sparse GP regression with rbf kernel on 1d data ''' + rbflin = GPy.kern.RBF(1) + GPy.kern.Linear(1) + GPy.kern.White(1, 1e-5) self.check_model(rbflin, model_type='SparseGPRegression', dimension=1) def test_SparseGPRegression_rbf_linear_white_kern_2D(self): @@ -419,14 +505,12 @@ class GradientTests(np.testing.TestCase): rbflin = GPy.kern.RBF(2) + GPy.kern.Linear(2) self.check_model(rbflin, model_type='SparseGPRegression', dimension=2) - # @unittest.expectedFailure def test_SparseGPRegression_rbf_linear_white_kern_2D_uncertain_inputs(self): ''' Testing the sparse GP regression with rbf, linear kernel on 2d data with uncertain inputs''' rbflin = GPy.kern.RBF(2) + GPy.kern.Linear(2) raise unittest.SkipTest("This is not implemented yet!") self.check_model(rbflin, model_type='SparseGPRegression', dimension=2, uncertain_inputs=1) - # @unittest.expectedFailure def test_SparseGPRegression_rbf_linear_white_kern_1D_uncertain_inputs(self): ''' Testing the sparse GP regression with rbf, linear kernel on 1d data with uncertain inputs''' rbflin = GPy.kern.RBF(1) + GPy.kern.Linear(1) @@ -443,6 +527,16 @@ class GradientTests(np.testing.TestCase): m = GPy.models.GPLVM(Y, input_dim, kernel=k) self.assertTrue(m.checkgrad()) + def test_BCGPLVM_rbf_bias_white_kern_2D(self): + """ Testing GPLVM with rbf + bias kernel """ + N, input_dim, D = 50, 1, 2 + X = np.random.rand(N, input_dim) + k = GPy.kern.RBF(input_dim, 0.5, 0.9 * np.ones((1,))) + GPy.kern.Bias(input_dim, 0.1) + GPy.kern.White(input_dim, 0.05) + K = k.K(X) + Y = np.random.multivariate_normal(np.zeros(N), K, input_dim).T + m = GPy.models.BCGPLVM(Y, input_dim, kernel=k) + self.assertTrue(m.checkgrad()) + def test_GPLVM_rbf_linear_white_kern_2D(self): """ Testing GPLVM with rbf + bias kernel """ N, input_dim, D = 50, 1, 2 @@ -468,23 +562,8 @@ class GradientTests(np.testing.TestCase): Z = np.linspace(0, 15, 4)[:, None] kernel = GPy.kern.RBF(1) m = GPy.models.SparseGPClassification(X, Y, kernel=kernel, Z=Z) - # distribution = GPy.likelihoods.likelihood_functions.Bernoulli() - # likelihood = GPy.likelihoods.EP(Y, distribution) - # m = GPy.core.SparseGP(X, likelihood, kernel, Z) - # m.ensure_default_constraints() self.assertTrue(m.checkgrad()) - @unittest.expectedFailure - def test_generalized_FITC(self): - N = 20 - X = np.hstack([np.random.rand(N / 2) + 1, np.random.rand(N / 2) - 1])[:, None] - k = GPy.kern.RBF(1) + GPy.kern.White(1) - Y = np.hstack([np.ones(N / 2), np.zeros(N / 2)])[:, None] - m = GPy.models.FITCClassification(X, Y, kernel=k) - m.update_likelihood_approximation() - self.assertTrue(m.checkgrad()) - - @unittest.expectedFailure def test_multioutput_regression_1D(self): X1 = np.random.rand(50, 1) * 8 X2 = np.random.rand(30, 1) * 5 @@ -494,12 +573,11 @@ class GradientTests(np.testing.TestCase): Y = np.vstack((Y1, Y2)) k1 = GPy.kern.RBF(1) - m = GPy.models.GPMultioutputRegression(X_list=[X1, X2], Y_list=[Y1, Y2], kernel_list=[k1]) - import ipdb;ipdb.set_trace() - m.constrain_fixed('.*rbf_var', 1.) + m = GPy.models.GPCoregionalizedRegression(X_list=[X1, X2], Y_list=[Y1, Y2], kernel=k1) + #import ipdb;ipdb.set_trace() + #m.constrain_fixed('.*rbf_var', 1.) self.assertTrue(m.checkgrad()) - @unittest.expectedFailure def test_multioutput_sparse_regression_1D(self): X1 = np.random.rand(500, 1) * 8 X2 = np.random.rand(300, 1) * 5 @@ -509,8 +587,7 @@ class GradientTests(np.testing.TestCase): Y = np.vstack((Y1, Y2)) k1 = GPy.kern.RBF(1) - m = GPy.models.SparseGPMultioutputRegression(X_list=[X1, X2], Y_list=[Y1, Y2], kernel_list=[k1]) - m.constrain_fixed('.*rbf_var', 1.) + m = GPy.models.SparseGPCoregionalizedRegression(X_list=[X1, X2], Y_list=[Y1, Y2], kernel=k1) self.assertTrue(m.checkgrad()) def test_gp_heteroscedastic_regression(self): @@ -539,6 +616,7 @@ class GradientTests(np.testing.TestCase): self.assertTrue(m.checkgrad()) def test_gp_kronecker_gaussian(self): + np.random.seed(0) N1, N2 = 30, 20 X1 = np.random.randn(N1, 1) X2 = np.random.randn(N2, 1) @@ -559,16 +637,16 @@ class GradientTests(np.testing.TestCase): m.randomize() mm[:] = m[:] - assert np.allclose(m.log_likelihood(), mm.log_likelihood()) - assert np.allclose(m.gradient, mm.gradient) + self.assertTrue(np.allclose(m.log_likelihood(), mm.log_likelihood())) + self.assertTrue(np.allclose(m.gradient, mm.gradient)) X1test = np.random.randn(100, 1) X2test = np.random.randn(100, 1) mean1, var1 = m.predict(X1test, X2test) yy, xx = np.meshgrid(X2test, X1test) Xgrid = np.vstack((xx.flatten(order='F'), yy.flatten(order='F'))).T mean2, var2 = mm.predict(Xgrid) - assert np.allclose(mean1, mean2) - assert np.allclose(var1, var2) + self.assertTrue( np.allclose(mean1, mean2) ) + self.assertTrue( np.allclose(var1, var2) ) def test_gp_VGPC(self): num_obs = 25 @@ -576,7 +654,8 @@ class GradientTests(np.testing.TestCase): X = X[:, None] Y = 25. + np.sin(X / 20.) * 2. + np.random.rand(num_obs)[:, None] kern = GPy.kern.Bias(1) + GPy.kern.RBF(1) - m = GPy.models.GPVariationalGaussianApproximation(X, Y, kern) + lik = GPy.likelihoods.Gaussian() + m = GPy.models.GPVariationalGaussianApproximation(X, Y, kernel=kern, likelihood=lik) self.assertTrue(m.checkgrad()) diff --git a/GPy/testing/parameterized_tests.py b/GPy/testing/parameterized_tests.py index 0fb129ff..762a82a1 100644 --- a/GPy/testing/parameterized_tests.py +++ b/GPy/testing/parameterized_tests.py @@ -248,10 +248,16 @@ class ParameterizedTest(unittest.TestCase): m.randomize() self.assertEqual(m.p1, val) + def test_checkgrad(self): + assert(self.testmodel.kern.checkgrad()) + assert(self.testmodel.kern.lengthscale.checkgrad()) + assert(self.testmodel.likelihood.checkgrad()) + def test_printing(self): print(self.test1) print(self.param) print(self.test1['']) + print(self.testmodel.hierarchy_name(False)) if __name__ == "__main__": #import sys;sys.argv = ['', 'Test.test_add_parameter'] diff --git a/GPy/testing/pickle_tests.py b/GPy/testing/pickle_tests.py index fd1bf93c..64357b39 100644 --- a/GPy/testing/pickle_tests.py +++ b/GPy/testing/pickle_tests.py @@ -20,6 +20,8 @@ from GPy.examples.dimensionality_reduction import mrd_simulation from GPy.core.parameterization.variational import NormalPosterior from GPy.models.gp_regression import GPRegression from functools import reduce +from GPy.util.caching import Cacher +from pickle import PicklingError def toy_model(): X = np.linspace(0,1,50)[:, None] @@ -205,23 +207,6 @@ class Test(ListDictTestCase): def _callback(self, what, which): what.count += 1 - @unittest.skip - def test_add_observer(self): - par = toy_model() - par.name = "original" - par.count = 0 - par.add_observer(self, self._callback, 1) - pcopy = GPRegression(par.X.copy(), par.Y.copy(), kernel=par.kern.copy()) - self.assertNotIn(par.observers[0], pcopy.observers) - pcopy = par.copy() - pcopy.name = "copy" - self.assertTrue(par.checkgrad()) - self.assertTrue(pcopy.checkgrad()) - self.assertTrue(pcopy.kern.checkgrad()) - import ipdb;ipdb.set_trace() - self.assertIn(par.observers[0], pcopy.observers) - self.assertEqual(par.count, 3) - self.assertEqual(pcopy.count, 6) # 3 of each call to checkgrad if __name__ == "__main__": #import sys;sys.argv = ['', 'Test.test_parameter_index_operations'] diff --git a/GPy/testing/run_coverage.sh b/GPy/testing/run_coverage.sh new file mode 100755 index 00000000..f2e52230 --- /dev/null +++ b/GPy/testing/run_coverage.sh @@ -0,0 +1 @@ +nosetests . --with-coverage --logging-level=INFO --cover-html --cover-html-dir=coverage --cover-package=GPy --cover-erase diff --git a/GPy/testing/rv_transformation_tests.py b/GPy/testing/rv_transformation_tests.py new file mode 100644 index 00000000..44d8710d --- /dev/null +++ b/GPy/testing/rv_transformation_tests.py @@ -0,0 +1,101 @@ +# Written by Ilias Bilionis +""" +Test if hyperparameters in models are properly transformed. +""" + + +import unittest +import numpy as np +import scipy.stats as st +import GPy + + +class TestModel(GPy.core.Model): + """ + A simple GPy model with one parameter. + """ + def __init__(self): + GPy.core.Model.__init__(self, 'test_model') + theta = GPy.core.Param('theta', 1.) + self.link_parameter(theta) + + def log_likelihood(self): + return 0. + + +class RVTransformationTestCase(unittest.TestCase): + + def _test_trans(self, trans): + m = TestModel() + prior = GPy.priors.LogGaussian(.5, 0.1) + m.theta.set_prior(prior) + m.theta.unconstrain() + m.theta.constrain(trans) + # The PDF of the transformed variables + p_phi = lambda phi : np.exp(-m._objective_grads(phi)[0]) + # To the empirical PDF of: + theta_s = prior.rvs(100000) + phi_s = trans.finv(theta_s) + # which is essentially a kernel density estimation + kde = st.gaussian_kde(phi_s) + # We will compare the PDF here: + phi = np.linspace(phi_s.min(), phi_s.max(), 100) + # The transformed PDF of phi should be this: + pdf_phi = np.array([p_phi(p) for p in phi]) + # UNCOMMENT TO SEE GRAPHICAL COMPARISON + #import matplotlib.pyplot as plt + #fig, ax = plt.subplots() + #ax.hist(phi_s, normed=True, bins=100, alpha=0.25, label='Histogram') + #ax.plot(phi, kde(phi), '--', linewidth=2, label='Kernel Density Estimation') + #ax.plot(phi, pdf_phi, ':', linewidth=2, label='Transformed PDF') + #ax.set_xlabel(r'transformed $\theta$', fontsize=16) + #ax.set_ylabel('PDF', fontsize=16) + #plt.legend(loc='best') + #plt.show(block=True) + # END OF PLOT + # The following test cannot be very accurate + self.assertTrue(np.linalg.norm(pdf_phi - kde(phi)) / np.linalg.norm(kde(phi)) <= 1e-1) + # Check the gradients at a few random points + for i in range(10): + m.theta = theta_s[i] + self.assertTrue(m.checkgrad(verbose=True)) + + def test_Logexp(self): + self._test_trans(GPy.constraints.Logexp()) + self._test_trans(GPy.constraints.Exponent()) + + +if __name__ == '__main__': + unittest.main() + quit() + m = TestModel() + prior = GPy.priors.LogGaussian(0., .9) + m.theta.set_prior(prior) + + # The following should return the PDF in terms of the transformed quantities + p_phi = lambda phi : np.exp(-m._objective_grads(phi)[0]) + + # Let's look at the transformation phi = log(exp(theta - 1)) + trans = GPy.constraints.Exponent() + m.theta.constrain(trans) + # Plot the transformed probability density + phi = np.linspace(-8, 8, 100) + fig, ax = plt.subplots() + # Let's draw some samples of theta and transform them so that we see + # which one is right + theta_s = prior.rvs(10000) + # Transform it to the new variables + phi_s = trans.finv(theta_s) + # And draw their histogram + ax.hist(phi_s, normed=True, bins=100, alpha=0.25, label='Empirical') + # This is to be compared to the PDF of the model expressed in terms of these new + # variables + ax.plot(phi, [p_phi(p) for p in phi], label='Transformed PDF', linewidth=2) + ax.set_xlim(-3, 10) + ax.set_xlabel(r'transformed $\theta$', fontsize=16) + ax.set_ylabel('PDF', fontsize=16) + plt.legend(loc='best') + # Now let's test the gradients + m.checkgrad(verbose=True) + # And show the plot + plt.show(block=True) diff --git a/GPy/util/__init__.py b/GPy/util/__init__.py index e8d2456e..6919f1a8 100644 --- a/GPy/util/__init__.py +++ b/GPy/util/__init__.py @@ -15,5 +15,5 @@ from . import caching from . import diag from . import initialization from . import multioutput -from . import linalg_gpu +from . import parallel diff --git a/GPy/util/caching.py b/GPy/util/caching.py index 196ce343..cbc1f3f1 100644 --- a/GPy/util/caching.py +++ b/GPy/util/caching.py @@ -3,6 +3,7 @@ from ..core.parameterization.observable import Observable import collections, weakref from functools import reduce +from pickle import PickleError class Cacher(object): def __init__(self, operation, limit=5, ignore_args=(), force_kwargs=()): @@ -76,7 +77,7 @@ class Cacher(object): self.order.append(cache_id) self.cached_inputs[cache_id] = inputs for a in inputs: - if a is not None: + if a is not None and not isinstance(a, int): ind_id = self.id(a) v = self.cached_input_ids.get(ind_id, [weakref.ref(a), []]) v[1].append(cache_id) @@ -103,9 +104,9 @@ class Cacher(object): inputs = self.combine_inputs(args, kw, self.ignore_args) cache_id = self.prepare_cache_id(inputs) # 2: if anything is not cachable, we will just return the operation, without caching - if reduce(lambda a, b: a or (not (isinstance(b, Observable) or b is None)), inputs, False): - #print 'WARNING: '+self.operation.__name__ + ' not cacheable!' - #print [not (isinstance(b, Observable)) for b in inputs] + if reduce(lambda a, b: a or (not (isinstance(b, Observable) or b is None or isinstance(b,int))), inputs, False): +# print 'WARNING: '+self.operation.__name__ + ' not cacheable!' +# print [not (isinstance(b, Observable)) for b in inputs] return self.operation(*args, **kw) # 3&4: check whether this cache_id has been cached, then has it changed? try: @@ -149,10 +150,10 @@ class Cacher(object): return Cacher(self.operation, self.limit, self.ignore_args, self.force_kwargs) def __getstate__(self, memo=None): - raise NotImplementedError("Trying to pickle Cacher object with function {}, pickling functions not possible.".format(str(self.operation))) + raise PickleError("Trying to pickle Cacher object with function {}, pickling functions not possible.".format(str(self.operation))) def __setstate__(self, memo=None): - raise NotImplementedError("Trying to pickle Cacher object with function {}, pickling functions not possible.".format(str(self.operation))) + raise PickleError("Trying to pickle Cacher object with function {}, pickling functions not possible.".format(str(self.operation))) @property def __name__(self): diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index f079cabd..e245d988 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -1,11 +1,14 @@ # Copyright James Hensman and Max Zwiessele 2014, 2015 -# Licensed under the GNU GPL version 3.0 +# Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np from . import linalg from .config import config - -from . import choleskies_cython +try: + from . import choleskies_cython + config.set('cython', 'working', 'True') +except ImportError: + config.set('cython', 'working', 'False') def safe_root(N): i = np.sqrt(N) diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index 21492a88..8205c62b 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.21 */ +/* Generated by Cython 0.22 */ #define PY_SSIZE_T_CLEAN #ifndef CYTHON_USE_PYLONG_INTERNALS @@ -19,7 +19,7 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else -#define CYTHON_ABI "0_21" +#define CYTHON_ABI "0_22" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) @@ -54,7 +54,7 @@ #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #endif -#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" @@ -73,8 +73,6 @@ #if PY_MAJOR_VERSION >= 3 #define Py_TPFLAGS_CHECKTYPES 0 #define Py_TPFLAGS_HAVE_INDEX 0 -#endif -#if PY_MAJOR_VERSION >= 3 #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE) @@ -101,10 +99,12 @@ #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) + #define __Pyx_PyFrozenSet_Size(s) PyObject_Size(s) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) + #define __Pyx_PyFrozenSet_Size(s) PySet_Size(s) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) @@ -151,6 +151,11 @@ #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong @@ -160,7 +165,9 @@ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif #ifndef CYTHON_INLINE #if defined(__GNUC__) @@ -196,11 +203,22 @@ static CYTHON_INLINE float __PYX_NAN() { return value; } #endif +#define __Pyx_void_to_None(void_result) (void_result, Py_INCREF(Py_None), Py_None) #ifdef __cplusplus template void __Pyx_call_destructor(T* x) { x->~T(); } +template +class __Pyx_FakeReference { + public: + __Pyx_FakeReference() : ptr(NULL) { } + __Pyx_FakeReference(T& ref) : ptr(&ref) { } + T *operator->() { return ptr; } + operator T&() { return *ptr; } + private: + T *ptr; +}; #endif @@ -231,7 +249,6 @@ void __Pyx_call_destructor(T* x) { #include "stdlib.h" #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" -#include "cholesky_backprop.h" #include "pythread.h" #include "pystate.h" #ifdef _OPENMP @@ -289,11 +306,11 @@ static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { @@ -329,7 +346,7 @@ static int __Pyx_init_sys_getdefaultencoding_params(void) { const char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); @@ -442,6 +459,15 @@ static const char *__pyx_f[] = { "GPy/util/stringsource", "type.pxd", }; +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; + #define IS_UNSIGNED(type) (((type) -1) > 0) struct __Pyx_StructField_; #define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) @@ -477,15 +503,6 @@ typedef struct { char is_valid_array; } __Pyx_BufFmt_Context; -struct __pyx_memoryview_obj; -typedef struct { - struct __pyx_memoryview_obj *memview; - char *data; - Py_ssize_t shape[8]; - Py_ssize_t strides[8]; - Py_ssize_t suboffsets[8]; -} __Pyx_memviewslice; - #include #ifndef CYTHON_ATOMICS #define CYTHON_ATOMICS 1 @@ -534,7 +551,7 @@ typedef volatile __pyx_atomic_int_type __pyx_atomic_int; #endif -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -543,7 +560,7 @@ typedef volatile __pyx_atomic_int_type __pyx_atomic_int; */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -552,7 +569,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -561,7 +578,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":729 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -570,7 +587,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -579,7 +596,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -588,7 +605,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -597,7 +614,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":736 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -606,7 +623,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -615,7 +632,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":741 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -624,7 +641,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -633,7 +650,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -642,7 +659,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -651,7 +668,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -660,7 +677,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -669,7 +686,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -678,7 +695,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -687,7 +704,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -696,7 +713,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -705,7 +722,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -714,7 +731,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -722,6 +739,24 @@ typedef npy_double __pyx_t_5numpy_double_t; * ctypedef npy_cfloat cfloat_t */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "scipy/linalg/cython_blas.pxd":15 + * # The original libraries should be linked directly. + * + * ctypedef float s # <<<<<<<<<<<<<< + * ctypedef double d + * ctypedef float complex c + */ +typedef float __pyx_t_5scipy_6linalg_11cython_blas_s; + +/* "scipy/linalg/cython_blas.pxd":16 + * + * ctypedef float s + * ctypedef double d # <<<<<<<<<<<<<< + * ctypedef float complex c + * ctypedef double complex z + */ +typedef double __pyx_t_5scipy_6linalg_11cython_blas_d; #if CYTHON_CCOMPLEX #ifdef __cplusplus typedef ::std::complex< float > __pyx_t_float_complex; @@ -749,7 +784,7 @@ struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":765 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -758,7 +793,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -767,7 +802,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":767 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -776,7 +811,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":769 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -845,7 +880,7 @@ struct __pyx_memoryview_obj { }; -/* "View.MemoryView":922 +/* "View.MemoryView":921 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -882,7 +917,7 @@ struct __pyx_vtabstruct_memoryview { static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; -/* "View.MemoryView":922 +/* "View.MemoryView":921 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -894,6 +929,8 @@ struct __pyx_vtabstruct__memoryviewslice { struct __pyx_vtabstruct_memoryview __pyx_base; }; static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice; + +/* --- Runtime support code (head) --- */ #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -982,13 +1019,6 @@ static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \ PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \ const char* function_name); -static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, - const char *name, int exact); - -static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj, - __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); -static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); - static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name); #if CYTHON_COMPILING_IN_CPYTHON @@ -1003,20 +1033,9 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); - -#define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1) -#define __Pyx_BufPtrStrided3d(type, buf, i0, s0, i1, s1, i2, s2) (type)((char*)buf + i0 * s0 + i1 * s1 + i2 * s2) -static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); -static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); - -static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */ - -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); -#else -#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) -#endif +static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj, + __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); +static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); #define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d #define __Pyx_MEMVIEW_DIRECT 1 @@ -1043,14 +1062,52 @@ static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */ + +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); + +static void __Pyx_WriteUnraisable(const char *name, int clineno, + int lineno, const char *filename, + int full_traceback); + static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); +#if PY_MAJOR_VERSION >= 3 +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) + PyErr_SetObject(PyExc_KeyError, args); + Py_XDECREF(args); + } + return NULL; + } + Py_INCREF(value); + return value; +} +#else + #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#endif + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, + const char *name, int exact); + #include static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); @@ -1065,10 +1122,6 @@ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */ -#ifndef __PYX_FORCE_INIT_THREADS - #define __PYX_FORCE_INIT_THREADS 0 -#endif - #define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ @@ -1165,10 +1218,6 @@ static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/ -static void __Pyx_WriteUnraisable(const char *name, int clineno, - int lineno, const char *filename, - int full_traceback); - static int __Pyx_SetVtable(PyObject *dict, void *vtable); typedef struct { @@ -1215,8 +1264,6 @@ static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); -static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); - static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); static int __Pyx_ValidateAndInit_memviewslice( @@ -1231,6 +1278,10 @@ static int __Pyx_ValidateAndInit_memviewslice( static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *); +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsdsds_double(PyObject *); + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); @@ -1355,6 +1406,10 @@ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_d_dc_double(PyObject *); + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_double(PyObject *); + static int __Pyx_check_binary_version(void); #if !defined(__Pyx_PyIdentifier_FromString) @@ -1369,6 +1424,8 @@ static PyObject *__Pyx_ImportModule(const char *name); static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict); +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ @@ -1408,6 +1465,11 @@ static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ +/* Module declarations from 'scipy.linalg.cython_blas' */ +static __pyx_t_5scipy_6linalg_11cython_blas_d (*__pyx_f_5scipy_6linalg_11cython_blas_ddot)(int *, __pyx_t_5scipy_6linalg_11cython_blas_d *, int *, __pyx_t_5scipy_6linalg_11cython_blas_d *, int *); /*proto*/ +static void (*__pyx_f_5scipy_6linalg_11cython_blas_dscal)(int *, __pyx_t_5scipy_6linalg_11cython_blas_d *, __pyx_t_5scipy_6linalg_11cython_blas_d *, int *); /*proto*/ +static void (*__pyx_f_5scipy_6linalg_11cython_blas_dsymv)(char *, int *, __pyx_t_5scipy_6linalg_11cython_blas_d *, __pyx_t_5scipy_6linalg_11cython_blas_d *, int *, __pyx_t_5scipy_6linalg_11cython_blas_d *, int *, __pyx_t_5scipy_6linalg_11cython_blas_d *, __pyx_t_5scipy_6linalg_11cython_blas_d *, int *); /*proto*/ + /* Module declarations from 'GPy.util.choleskies_cython' */ static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; @@ -1418,6 +1480,7 @@ static PyObject *strided = 0; static PyObject *indirect = 0; static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; +static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int, __Pyx_memviewslice, __Pyx_memviewslice); /*proto*/ static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ @@ -1456,55 +1519,54 @@ int __pyx_module_is_main_GPy__util__choleskies_cython = 0; /* Implementation of 'GPy.util.choleskies_cython' */ static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_xrange; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_Ellipsis; static PyObject *__pyx_builtin_TypeError; -static PyObject *__pyx_builtin_xrange; static PyObject *__pyx_builtin_id; static PyObject *__pyx_builtin_IndexError; -static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_flat, int __pyx_v_M); /* proto */ -static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_L); /* proto */ -static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_flat, int __pyx_v_M); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ -static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_c(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ -static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_10backprop_gradient_par_c_old(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_c(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ -static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ -static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ -static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ -static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ -static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ -static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ -static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ -static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ -static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ @@ -1530,6 +1592,7 @@ static char __pyx_k_k[] = "k"; static char __pyx_k_l[] = "l"; static char __pyx_k_m[] = "m"; static char __pyx_k_q[] = "q"; +static char __pyx_k_u[] = "u"; static char __pyx_k_Zd[] = "Zd"; static char __pyx_k_Zf[] = "Zf"; static char __pyx_k_Zg[] = "Zg"; @@ -1540,7 +1603,6 @@ static char __pyx_k_np[] = "np"; static char __pyx_k_obj[] = "obj"; static char __pyx_k_ret[] = "ret"; static char __pyx_k_base[] = "base"; -static char __pyx_k_copy[] = "copy"; static char __pyx_k_flat[] = "flat"; static char __pyx_k_main[] = "__main__"; static char __pyx_k_mode[] = "mode"; @@ -1563,12 +1625,14 @@ static char __pyx_k_range[] = "range"; static char __pyx_k_shape[] = "shape"; static char __pyx_k_start[] = "start"; static char __pyx_k_zeros[] = "zeros"; +static char __pyx_k_L_cont[] = "L_cont"; static char __pyx_k_format[] = "format"; static char __pyx_k_import[] = "__import__"; static char __pyx_k_name_2[] = "__name__"; static char __pyx_k_struct[] = "struct"; static char __pyx_k_unpack[] = "unpack"; static char __pyx_k_xrange[] = "xrange"; +static char __pyx_k_asarray[] = "asarray"; static char __pyx_k_fortran[] = "fortran"; static char __pyx_k_memview[] = "memview"; static char __pyx_k_Ellipsis[] = "Ellipsis"; @@ -1585,6 +1649,7 @@ static char __pyx_k_flat_to_triang[] = "flat_to_triang"; static char __pyx_k_triang_to_flat[] = "triang_to_flat"; static char __pyx_k_allocate_buffer[] = "allocate_buffer"; static char __pyx_k_dtype_is_object[] = "dtype_is_object"; +static char __pyx_k_ascontiguousarray[] = "ascontiguousarray"; static char __pyx_k_backprop_gradient[] = "backprop_gradient"; static char __pyx_k_strided_and_direct[] = ""; static char __pyx_k_strided_and_indirect[] = ""; @@ -1601,7 +1666,6 @@ static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d. static char __pyx_k_GPy_util_choleskies_cython[] = "GPy.util.choleskies_cython"; static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)"; static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)"; -static char __pyx_k_backprop_gradient_par_c_old[] = "backprop_gradient_par_c_old"; static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; @@ -1637,6 +1701,7 @@ static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_L; +static PyObject *__pyx_n_s_L_cont; static PyObject *__pyx_n_s_M; static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; @@ -1650,17 +1715,17 @@ static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_asarray; +static PyObject *__pyx_n_s_ascontiguousarray; static PyObject *__pyx_n_s_backprop_gradient; static PyObject *__pyx_n_s_backprop_gradient_par; static PyObject *__pyx_n_s_backprop_gradient_par_c; -static PyObject *__pyx_n_s_backprop_gradient_par_c_old; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_u_c; static PyObject *__pyx_n_s_class; static PyObject *__pyx_kp_s_contiguous_and_direct; static PyObject *__pyx_kp_s_contiguous_and_indirect; -static PyObject *__pyx_n_s_copy; static PyObject *__pyx_n_s_count; static PyObject *__pyx_n_s_d; static PyObject *__pyx_n_s_dL; @@ -1732,36 +1797,35 @@ static PyObject *__pyx_tuple__6; static PyObject *__pyx_tuple__7; static PyObject *__pyx_tuple__8; static PyObject *__pyx_tuple__9; -static PyObject *__pyx_slice__14; static PyObject *__pyx_slice__15; static PyObject *__pyx_slice__16; +static PyObject *__pyx_slice__17; static PyObject *__pyx_tuple__10; static PyObject *__pyx_tuple__11; static PyObject *__pyx_tuple__12; static PyObject *__pyx_tuple__13; -static PyObject *__pyx_tuple__17; +static PyObject *__pyx_tuple__14; static PyObject *__pyx_tuple__18; -static PyObject *__pyx_tuple__20; -static PyObject *__pyx_tuple__22; -static PyObject *__pyx_tuple__24; -static PyObject *__pyx_tuple__26; -static PyObject *__pyx_tuple__28; +static PyObject *__pyx_tuple__19; +static PyObject *__pyx_tuple__21; +static PyObject *__pyx_tuple__23; +static PyObject *__pyx_tuple__25; +static PyObject *__pyx_tuple__27; +static PyObject *__pyx_tuple__29; static PyObject *__pyx_tuple__30; static PyObject *__pyx_tuple__31; static PyObject *__pyx_tuple__32; static PyObject *__pyx_tuple__33; -static PyObject *__pyx_tuple__34; -static PyObject *__pyx_codeobj__19; -static PyObject *__pyx_codeobj__21; -static PyObject *__pyx_codeobj__23; -static PyObject *__pyx_codeobj__25; -static PyObject *__pyx_codeobj__27; -static PyObject *__pyx_codeobj__29; +static PyObject *__pyx_codeobj__20; +static PyObject *__pyx_codeobj__22; +static PyObject *__pyx_codeobj__24; +static PyObject *__pyx_codeobj__26; +static PyObject *__pyx_codeobj__28; -/* "GPy/util/choleskies_cython.pyx":11 - * cimport numpy as np +/* "GPy/util/choleskies_cython.pyx":12 + * cimport scipy.linalg.cython_blas as cblas * - * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< + * def flat_to_triang(double[:, :] flat, int M): # <<<<<<<<<<<<<< * """take a matrix N x D and return a D X M x M array where * */ @@ -1771,7 +1835,7 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObjec static char __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang[] = "take a matrix N x D and return a D X M x M array where\n\n N = M(M+1)/2\n\n the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat.\n "; static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang = {"flat_to_triang", (PyCFunction)__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang, METH_VARARGS|METH_KEYWORDS, __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang}; static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - PyArrayObject *__pyx_v_flat = 0; + __Pyx_memviewslice __pyx_v_flat = { 0, 0, { 0 }, { 0 }, { 0 } }; int __pyx_v_M; int __pyx_lineno = 0; const char *__pyx_filename = NULL; @@ -1799,11 +1863,11 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObjec case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "flat_to_triang") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "flat_to_triang") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 2) { goto __pyx_L5_argtuple_error; @@ -1811,41 +1875,32 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObjec values[0] = PyTuple_GET_ITEM(__pyx_args, 0); values[1] = PyTuple_GET_ITEM(__pyx_args, 1); } - __pyx_v_flat = ((PyArrayObject *)values[0]); - __pyx_v_M = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_flat = __Pyx_PyObject_to_MemoryviewSlice_dsds_double(values[0]); if (unlikely(!__pyx_v_flat.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_M = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.util.choleskies_cython.flat_to_triang", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_flat), __pyx_ptype_5numpy_ndarray, 1, "flat", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;} 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__pyx_v_L.shape[0]; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_L.shape[1]; + __pyx_t_16 = __pyx_v_i; + __pyx_t_17 = __pyx_v_k; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_16 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_17)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_12 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_13)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_14 * __pyx_v_L.strides[0]) ) + __pyx_t_15 * __pyx_v_L.strides[1]) )))); - /* "GPy/util/choleskies_cython.pyx":58 - * for j in range(k + 1, N): - * dL_dK[j, k] /= L[k, k] - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] # <<<<<<<<<<<<<< - * dL_dK[k, k] /= (2. * L[k, k]) + /* "GPy/util/choleskies_cython.pyx":58 + * for i in range(j, N): + * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + * dL_dK[j, k] -= dL_dK[i, j] * L[i, k] # <<<<<<<<<<<<<< + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] + */ + __pyx_t_18 = __pyx_v_i; + __pyx_t_19 = __pyx_v_j; + if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_19 < 0) __pyx_t_19 += __pyx_v_dL_dK.shape[1]; + __pyx_t_20 = __pyx_v_i; + __pyx_t_21 = __pyx_v_k; + if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_L.shape[0]; + if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_L.shape[1]; + __pyx_t_22 = __pyx_v_j; + __pyx_t_23 = __pyx_v_k; + if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_22 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_23)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_18 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_19)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_20 * __pyx_v_L.strides[0]) ) + __pyx_t_21 * __pyx_v_L.strides[1]) )))); + } + } + + /* "GPy/util/choleskies_cython.pyx":59 + * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + * dL_dK[j, k] -= dL_dK[i, j] * L[i, k] + * for j in range(k + 1, N): # <<<<<<<<<<<<<< + * dL_dK[j, k] /= L[k, k] + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + */ + __pyx_t_8 = __pyx_v_N; + for (__pyx_t_9 = (__pyx_v_k + 1); __pyx_t_9 < __pyx_t_8; __pyx_t_9+=1) { + __pyx_v_j = __pyx_t_9; + + /* "GPy/util/choleskies_cython.pyx":60 + * dL_dK[j, k] -= dL_dK[i, j] * L[i, k] + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] # <<<<<<<<<<<<<< + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + * dL_dK[k, k] /= (2. * L[k, k]) + */ + __pyx_t_10 = __pyx_v_k; + __pyx_t_11 = __pyx_v_k; + if (__pyx_t_10 < 0) __pyx_t_10 += __pyx_v_L.shape[0]; + if (__pyx_t_11 < 0) __pyx_t_11 += __pyx_v_L.shape[1]; + __pyx_t_24 = __pyx_v_j; + __pyx_t_25 = __pyx_v_k; + if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_24 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_25)) )) /= (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_10 * __pyx_v_L.strides[0]) ) + __pyx_t_11 * __pyx_v_L.strides[1]) ))); + + /* "GPy/util/choleskies_cython.pyx":61 + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] # <<<<<<<<<<<<<< + * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK */ - __pyx_t_26 = __pyx_v_j; - __pyx_t_27 = __pyx_v_k; - if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_pybuffernd_L.diminfo[0].shape; - if (__pyx_t_27 < 0) __pyx_t_27 += __pyx_pybuffernd_L.diminfo[1].shape; - __pyx_t_28 = __pyx_v_j; - __pyx_t_29 = __pyx_v_k; - if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_pybuffernd_dL_dK.diminfo[0].shape; - if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_pybuffernd_dL_dK.diminfo[1].shape; - __pyx_t_30 = __pyx_v_k; - __pyx_t_31 = __pyx_v_k; - if (__pyx_t_30 < 0) __pyx_t_30 += __pyx_pybuffernd_dL_dK.diminfo[0].shape; - if (__pyx_t_31 < 0) __pyx_t_31 += __pyx_pybuffernd_dL_dK.diminfo[1].shape; - *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_30, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_31, __pyx_pybuffernd_dL_dK.diminfo[1].strides) -= ((*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_27, __pyx_pybuffernd_L.diminfo[1].strides)) * (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_28, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_29, __pyx_pybuffernd_dL_dK.diminfo[1].strides))); - } + __pyx_t_26 = __pyx_v_j; + __pyx_t_27 = __pyx_v_k; + if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_L.shape[0]; + if (__pyx_t_27 < 0) __pyx_t_27 += __pyx_v_L.shape[1]; + __pyx_t_28 = __pyx_v_j; + __pyx_t_29 = __pyx_v_k; + if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_v_dL_dK.shape[1]; + __pyx_t_30 = __pyx_v_k; + __pyx_t_31 = __pyx_v_k; + if (__pyx_t_30 < 0) __pyx_t_30 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_31 < 0) __pyx_t_31 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_30 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_31)) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_26 * __pyx_v_L.strides[0]) ) + __pyx_t_27 * __pyx_v_L.strides[1]) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_28 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_29)) )))); + } - /* "GPy/util/choleskies_cython.pyx":59 - * dL_dK[j, k] /= L[k, k] - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - * dL_dK[k, k] /= (2. * L[k, k]) # <<<<<<<<<<<<<< + /* "GPy/util/choleskies_cython.pyx":62 + * dL_dK[j, k] /= L[k, k] + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + * dL_dK[k, k] /= (2. * L[k, k]) # <<<<<<<<<<<<<< * return dL_dK * */ - __pyx_t_8 = __pyx_v_k; - __pyx_t_9 = __pyx_v_k; - if (__pyx_t_8 < 0) __pyx_t_8 += __pyx_pybuffernd_L.diminfo[0].shape; - if (__pyx_t_9 < 0) __pyx_t_9 += __pyx_pybuffernd_L.diminfo[1].shape; - __pyx_t_32 = __pyx_v_k; - __pyx_t_33 = __pyx_v_k; - if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_pybuffernd_dL_dK.diminfo[0].shape; - if (__pyx_t_33 < 0) __pyx_t_33 += __pyx_pybuffernd_dL_dK.diminfo[1].shape; - *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_32, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_33, __pyx_pybuffernd_dL_dK.diminfo[1].strides) /= (2. * (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_8, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_9, __pyx_pybuffernd_L.diminfo[1].strides))); + __pyx_t_8 = __pyx_v_k; + __pyx_t_9 = __pyx_v_k; + if (__pyx_t_8 < 0) __pyx_t_8 += __pyx_v_L.shape[0]; + if (__pyx_t_9 < 0) __pyx_t_9 += __pyx_v_L.shape[1]; + __pyx_t_32 = __pyx_v_k; + __pyx_t_33 = __pyx_v_k; + if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_33 < 0) __pyx_t_33 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_32 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_33)) )) /= (2. * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_8 * __pyx_v_L.strides[0]) ) + __pyx_t_9 * __pyx_v_L.strides[1]) )))); + } + } + + /* "GPy/util/choleskies_cython.pyx":53 + * cdef int N = L.shape[0] + * cdef int k, j, i + * with nogil: # <<<<<<<<<<<<<< + * for k in range(N - 1, -1, -1): + * for j in range(k + 1, N): + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; + } } - /* "GPy/util/choleskies_cython.pyx":60 - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - * dL_dK[k, k] /= (2. * L[k, k]) + /* "GPy/util/choleskies_cython.pyx":63 + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK # <<<<<<<<<<<<<< * * def backprop_gradient_par(double[:,:] dL, double[:,:] L): */ __Pyx_XDECREF(__pyx_r); - __Pyx_INCREF(((PyObject *)__pyx_v_dL_dK)); - __pyx_r = ((PyObject *)__pyx_v_dL_dK); + __pyx_t_1 = __pyx_memoryview_fromslice(__pyx_v_dL_dK, 2, (PyObject *(*)(char *)) __pyx_memview_get_double, (int (*)(char *, PyObject *)) __pyx_memview_set_double, 0);; if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 63; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __pyx_r = __pyx_t_1; + __pyx_t_1 = 0; goto __pyx_L0; - /* "GPy/util/choleskies_cython.pyx":47 + /* "GPy/util/choleskies_cython.pyx":49 + * return flat * - * - * def backprop_gradient(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< - * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL).copy() + * def backprop_gradient(double[:, :] dL, double[:, :] L): # <<<<<<<<<<<<<< + * cdef double[:, ::1] dL_dK = np.tril(dL) * cdef int N = L.shape[0] */ @@ -2799,31 +2847,23 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); __Pyx_XDECREF(__pyx_t_5); - { PyObject *__pyx_type, *__pyx_value, *__pyx_tb; - __Pyx_ErrFetch(&__pyx_type, &__pyx_value, &__pyx_tb); - __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_L.rcbuffer->pybuffer); - __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_dL.rcbuffer->pybuffer); - __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_dL_dK.rcbuffer->pybuffer); - __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} + __PYX_XDEC_MEMVIEW(&__pyx_t_6, 1); __Pyx_AddTraceback("GPy.util.choleskies_cython.backprop_gradient", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; - goto __pyx_L2; __pyx_L0:; - __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_L.rcbuffer->pybuffer); - __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_dL.rcbuffer->pybuffer); - __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_dL_dK.rcbuffer->pybuffer); - __pyx_L2:; - __Pyx_XDECREF((PyObject *)__pyx_v_dL_dK); + __PYX_XDEC_MEMVIEW(&__pyx_v_dL_dK, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_dL, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_L, 1); __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "GPy/util/choleskies_cython.pyx":62 +/* "GPy/util/choleskies_cython.pyx":65 * return dL_dK * * def backprop_gradient_par(double[:,:] dL, double[:,:] L): # <<<<<<<<<<<<<< - * cdef double[:,:] dL_dK = np.tril(dL).copy() + * cdef double[:,::1] dL_dK = np.tril(dL) * cdef int N = L.shape[0] */ @@ -2859,11 +2899,11 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_7backprop_gradient_par( case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_L)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("backprop_gradient_par", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("backprop_gradient_par", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 65; __pyx_clineno = 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= __pyx_v_j; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_dL_dK.shape[1]; __pyx_t_16 = __pyx_v_j; - if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL_dK.shape[1]; - __pyx_t_17 = __pyx_v_j; - __pyx_t_18 = __pyx_v_k; - if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_L.shape[0]; - if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_v_L.shape[1]; - __pyx_t_19 = __pyx_v_i; - __pyx_t_20 = __pyx_v_k; - if (__pyx_t_19 < 0) __pyx_t_19 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_19 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_20 * __pyx_v_dL_dK.strides[1]) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_15 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_16 * __pyx_v_dL_dK.strides[1]) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_17 * __pyx_v_L.strides[0]) ) + __pyx_t_18 * __pyx_v_L.strides[1]) )))); + __pyx_t_17 = __pyx_v_k; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_L.shape[0]; + if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_L.shape[1]; + __pyx_t_18 = __pyx_v_i; + __pyx_t_19 = __pyx_v_k; + if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_19 < 0) __pyx_t_19 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_18 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_19)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_14 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_15)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_16 * __pyx_v_L.strides[0]) ) + __pyx_t_17 * __pyx_v_L.strides[1]) )))); } - /* "GPy/util/choleskies_cython.pyx":71 - * for j in range(k+1, i+1): - * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] - * for j in range(i, N): # <<<<<<<<<<<<<< - * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] - * for j in range(k + 1, N): + /* "GPy/util/choleskies_cython.pyx":75 + * for j in range(k+1, i+1): + * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + * for j in range(i, N): # <<<<<<<<<<<<<< + * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] + * for j in range(k + 1, N): */ - __pyx_t_14 = __pyx_v_N; - for (__pyx_t_21 = __pyx_v_i; __pyx_t_21 < __pyx_t_14; __pyx_t_21+=1) { - __pyx_v_j = __pyx_t_21; + __pyx_t_13 = __pyx_v_N; + for (__pyx_t_20 = __pyx_v_i; __pyx_t_20 < __pyx_t_13; __pyx_t_20+=1) { + __pyx_v_j = __pyx_t_20; - /* "GPy/util/choleskies_cython.pyx":72 - * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] - * for j in range(i, N): - * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] # <<<<<<<<<<<<<< - * for j in range(k + 1, N): - * dL_dK[j, k] /= L[k, k] + /* "GPy/util/choleskies_cython.pyx":76 + * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + * for j in range(i, N): + * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] # <<<<<<<<<<<<<< + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] */ - __pyx_t_22 = __pyx_v_j; - __pyx_t_23 = __pyx_v_i; - if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_dL_dK.shape[1]; - __pyx_t_24 = __pyx_v_j; - __pyx_t_25 = __pyx_v_k; - if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_L.shape[0]; - if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_L.shape[1]; - __pyx_t_26 = __pyx_v_i; - __pyx_t_27 = __pyx_v_k; - if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_27 < 0) __pyx_t_27 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_26 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_27 * __pyx_v_dL_dK.strides[1]) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_22 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_23 * __pyx_v_dL_dK.strides[1]) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_24 * __pyx_v_L.strides[0]) ) + __pyx_t_25 * __pyx_v_L.strides[1]) )))); + __pyx_t_21 = __pyx_v_j; + __pyx_t_22 = __pyx_v_i; + if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_dL_dK.shape[1]; + __pyx_t_23 = __pyx_v_j; + __pyx_t_24 = __pyx_v_k; + if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_L.shape[0]; + if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_L.shape[1]; + __pyx_t_25 = __pyx_v_i; + __pyx_t_26 = __pyx_v_k; + if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_25 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_26)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_21 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_22)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_23 * __pyx_v_L.strides[0]) ) + __pyx_t_24 * __pyx_v_L.strides[1]) )))); } } } @@ -3152,113 +3178,113 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( #define likely(x) __builtin_expect(!!(x), 1) #define unlikely(x) __builtin_expect(!!(x), 0) #endif - } - /* "GPy/util/choleskies_cython.pyx":67 - * cdef int k, j, i - * for k in range(N - 1, -1, -1): - * with nogil, parallel(): # <<<<<<<<<<<<<< - * for i in prange(k + 1, N): - * for j in range(k+1, i+1): + /* "GPy/util/choleskies_cython.pyx":77 + * for j in range(i, N): + * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] + * for j in range(k + 1, N): # <<<<<<<<<<<<<< + * dL_dK[j, k] /= L[k, k] + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] */ - /*finally:*/ { - /*normal exit:*/{ - #ifdef WITH_THREAD - Py_BLOCK_THREADS - #endif - goto __pyx_L9; - } - __pyx_L9:; - } - } + __pyx_t_9 = __pyx_v_N; + for (__pyx_t_13 = (__pyx_v_k + 1); __pyx_t_13 < __pyx_t_9; __pyx_t_13+=1) { + __pyx_v_j = __pyx_t_13; - /* "GPy/util/choleskies_cython.pyx":73 - * for j in range(i, N): - * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] - * for j in range(k + 1, N): # <<<<<<<<<<<<<< - * dL_dK[j, k] /= L[k, k] - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + /* "GPy/util/choleskies_cython.pyx":78 + * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] # <<<<<<<<<<<<<< + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + * dL_dK[k, k] /= (2. * L[k, k]) */ - __pyx_t_10 = __pyx_v_N; - for (__pyx_t_14 = (__pyx_v_k + 1); __pyx_t_14 < __pyx_t_10; __pyx_t_14+=1) { - __pyx_v_j = __pyx_t_14; + __pyx_t_20 = __pyx_v_k; + __pyx_t_27 = __pyx_v_k; + if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_L.shape[0]; + if (__pyx_t_27 < 0) __pyx_t_27 += __pyx_v_L.shape[1]; + __pyx_t_28 = __pyx_v_j; + __pyx_t_29 = __pyx_v_k; + if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_28 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_29)) )) /= (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_20 * __pyx_v_L.strides[0]) ) + __pyx_t_27 * __pyx_v_L.strides[1]) ))); - /* "GPy/util/choleskies_cython.pyx":74 - * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] - * for j in range(k + 1, N): - * dL_dK[j, k] /= L[k, k] # <<<<<<<<<<<<<< - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - * dL_dK[k, k] /= (2. * L[k, k]) - */ - __pyx_t_21 = __pyx_v_k; - __pyx_t_28 = __pyx_v_k; - if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_L.shape[0]; - if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_L.shape[1]; - __pyx_t_29 = __pyx_v_j; - __pyx_t_30 = __pyx_v_k; - if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_30 < 0) __pyx_t_30 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_29 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_30 * __pyx_v_dL_dK.strides[1]) )) /= (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_21 * __pyx_v_L.strides[0]) ) + __pyx_t_28 * __pyx_v_L.strides[1]) ))); - - /* "GPy/util/choleskies_cython.pyx":75 - * for j in range(k + 1, N): - * dL_dK[j, k] /= L[k, k] - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] # <<<<<<<<<<<<<< - * dL_dK[k, k] /= (2. * L[k, k]) + /* "GPy/util/choleskies_cython.pyx":79 + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] # <<<<<<<<<<<<<< + * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK */ - __pyx_t_31 = __pyx_v_j; - __pyx_t_32 = __pyx_v_k; - if (__pyx_t_31 < 0) __pyx_t_31 += __pyx_v_L.shape[0]; - if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_v_L.shape[1]; - __pyx_t_33 = __pyx_v_j; - __pyx_t_34 = __pyx_v_k; - if (__pyx_t_33 < 0) __pyx_t_33 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_34 < 0) __pyx_t_34 += __pyx_v_dL_dK.shape[1]; - __pyx_t_35 = __pyx_v_k; - __pyx_t_36 = __pyx_v_k; - if (__pyx_t_35 < 0) __pyx_t_35 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_36 < 0) __pyx_t_36 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_35 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_36 * __pyx_v_dL_dK.strides[1]) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_31 * __pyx_v_L.strides[0]) ) + __pyx_t_32 * __pyx_v_L.strides[1]) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_33 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_34 * __pyx_v_dL_dK.strides[1]) )))); - } + __pyx_t_30 = __pyx_v_j; + __pyx_t_31 = __pyx_v_k; + if (__pyx_t_30 < 0) __pyx_t_30 += __pyx_v_L.shape[0]; + if (__pyx_t_31 < 0) __pyx_t_31 += __pyx_v_L.shape[1]; + __pyx_t_32 = __pyx_v_j; + __pyx_t_33 = __pyx_v_k; + if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_33 < 0) __pyx_t_33 += __pyx_v_dL_dK.shape[1]; + __pyx_t_34 = __pyx_v_k; + __pyx_t_35 = __pyx_v_k; + if (__pyx_t_34 < 0) __pyx_t_34 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_35 < 0) __pyx_t_35 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_34 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_35)) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_30 * __pyx_v_L.strides[0]) ) + __pyx_t_31 * __pyx_v_L.strides[1]) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_32 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_33)) )))); + } - /* "GPy/util/choleskies_cython.pyx":76 - * dL_dK[j, k] /= L[k, k] - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - * dL_dK[k, k] /= (2. * L[k, k]) # <<<<<<<<<<<<<< + /* "GPy/util/choleskies_cython.pyx":80 + * dL_dK[j, k] /= L[k, k] + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + * dL_dK[k, k] /= (2. * L[k, k]) # <<<<<<<<<<<<<< * return dL_dK * */ - __pyx_t_10 = __pyx_v_k; - __pyx_t_14 = __pyx_v_k; - if (__pyx_t_10 < 0) __pyx_t_10 += __pyx_v_L.shape[0]; - if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[1]; - __pyx_t_37 = __pyx_v_k; - __pyx_t_38 = __pyx_v_k; - if (__pyx_t_37 < 0) __pyx_t_37 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_38 < 0) __pyx_t_38 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_37 * __pyx_v_dL_dK.strides[0]) ) + __pyx_t_38 * __pyx_v_dL_dK.strides[1]) )) /= (2. * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_10 * __pyx_v_L.strides[0]) ) + __pyx_t_14 * __pyx_v_L.strides[1]) )))); + __pyx_t_9 = __pyx_v_k; + __pyx_t_13 = __pyx_v_k; + if (__pyx_t_9 < 0) __pyx_t_9 += __pyx_v_L.shape[0]; + if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_v_L.shape[1]; + __pyx_t_36 = __pyx_v_k; + __pyx_t_37 = __pyx_v_k; + if (__pyx_t_36 < 0) __pyx_t_36 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_37 < 0) __pyx_t_37 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_36 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_37)) )) /= (2. * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_9 * __pyx_v_L.strides[0]) ) + __pyx_t_13 * __pyx_v_L.strides[1]) )))); + } + } + + /* "GPy/util/choleskies_cython.pyx":69 + * cdef int N = L.shape[0] + * cdef int k, j, i + * with nogil: # <<<<<<<<<<<<<< + * for k in range(N - 1, -1, -1): + * with parallel(): + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L5:; + } } - /* "GPy/util/choleskies_cython.pyx":77 - * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - * dL_dK[k, k] /= (2. * L[k, k]) + /* "GPy/util/choleskies_cython.pyx":81 + * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK # <<<<<<<<<<<<<< * - * #here's a pure C version... + * cdef void chol_backprop(int N, double[:, ::1] dL, double[:, ::1] L) nogil: */ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = __pyx_memoryview_fromslice(__pyx_v_dL_dK, 2, (PyObject *(*)(char *)) __pyx_memview_get_double, (int (*)(char *, PyObject *)) __pyx_memview_set_double, 0);; if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_memoryview_fromslice(__pyx_v_dL_dK, 2, (PyObject *(*)(char *)) __pyx_memview_get_double, (int (*)(char *, PyObject *)) __pyx_memview_set_double, 0);; if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; - /* "GPy/util/choleskies_cython.pyx":62 + /* "GPy/util/choleskies_cython.pyx":65 * return dL_dK * * def backprop_gradient_par(double[:,:] dL, double[:,:] L): # <<<<<<<<<<<<<< - * cdef double[:,:] dL_dK = np.tril(dL).copy() + * cdef double[:,::1] dL_dK = np.tril(dL) * cdef int N = L.shape[0] */ @@ -3269,8 +3295,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); __Pyx_XDECREF(__pyx_t_5); - __Pyx_XDECREF(__pyx_t_6); - __PYX_XDEC_MEMVIEW(&__pyx_t_7, 1); + __PYX_XDEC_MEMVIEW(&__pyx_t_6, 1); __Pyx_AddTraceback("GPy.util.choleskies_cython.backprop_gradient_par", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; @@ -3283,19 +3308,287 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( } /* "GPy/util/choleskies_cython.pyx":83 - * void chol_backprop(int N, double* dL, double* L) + * return dL_dK * - * def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< - * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig - * cdef int N = L.shape[0] + * cdef void chol_backprop(int N, double[:, ::1] dL, double[:, ::1] L) nogil: # <<<<<<<<<<<<<< + * cdef int i, k, n + * + */ + +static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L) { + int __pyx_v_i; + int __pyx_v_k; + int __pyx_v_n; + double __pyx_v_alpha; + double __pyx_v_beta; + int __pyx_v_incx; + double __pyx_v_scale; + long __pyx_t_1; + long __pyx_t_2; + long __pyx_t_3; + long __pyx_t_4; + int __pyx_t_5; + long __pyx_t_6; + long __pyx_t_7; + long __pyx_t_8; + int __pyx_t_9; + long __pyx_t_10; + int __pyx_t_11; + long __pyx_t_12; + int __pyx_t_13; + long __pyx_t_14; + long __pyx_t_15; + long __pyx_t_16; + int __pyx_t_17; + long __pyx_t_18; + int __pyx_t_19; + int __pyx_t_20; + double __pyx_t_21; + int __pyx_t_22; + long __pyx_t_23; + int __pyx_t_24; + long __pyx_t_25; + int __pyx_t_26; + int __pyx_t_27; + int __pyx_t_28; + int __pyx_t_29; + int __pyx_t_30; + int __pyx_t_31; + int __pyx_t_32; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "GPy/util/choleskies_cython.pyx":87 + * + * # DSYMV required constant arguments + * cdef double alpha=-1, beta=1 # <<<<<<<<<<<<<< + * cdef int incx=N + * + */ + __pyx_v_alpha = -1.0; + __pyx_v_beta = 1.0; + + /* "GPy/util/choleskies_cython.pyx":88 + * # DSYMV required constant arguments + * cdef double alpha=-1, beta=1 + * cdef int incx=N # <<<<<<<<<<<<<< + * + * # DSCAL required arguments + */ + __pyx_v_incx = __pyx_v_N; + + /* "GPy/util/choleskies_cython.pyx":93 + * cdef double scale + * + * dL[N - 1, N - 1] /= (2. * L[N - 1, N - 1]) # <<<<<<<<<<<<<< + * for k in range(N-2, -1, -1): + * n = N-k-1 + */ + __pyx_t_1 = (__pyx_v_N - 1); + __pyx_t_2 = (__pyx_v_N - 1); + if (__pyx_t_1 < 0) __pyx_t_1 += __pyx_v_L.shape[0]; + if (__pyx_t_2 < 0) __pyx_t_2 += __pyx_v_L.shape[1]; + __pyx_t_3 = (__pyx_v_N - 1); + __pyx_t_4 = (__pyx_v_N - 1); + if (__pyx_t_3 < 0) __pyx_t_3 += __pyx_v_dL.shape[0]; + if (__pyx_t_4 < 0) __pyx_t_4 += __pyx_v_dL.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_3 * __pyx_v_dL.strides[0]) )) + __pyx_t_4)) )) /= (2. * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_1 * __pyx_v_L.strides[0]) )) + __pyx_t_2)) )))); + + /* "GPy/util/choleskies_cython.pyx":94 + * + * dL[N - 1, N - 1] /= (2. * L[N - 1, N - 1]) + * for k in range(N-2, -1, -1): # <<<<<<<<<<<<<< + * n = N-k-1 + * cblas.dsymv(uplo='u', n=&n, alpha=&alpha, a=&dL[k + 1, k + 1], lda=&N, x=&L[k + 1, k], incx=&incx, + */ + for (__pyx_t_5 = (__pyx_v_N - 2); __pyx_t_5 > -1; __pyx_t_5-=1) { + __pyx_v_k = __pyx_t_5; + + /* "GPy/util/choleskies_cython.pyx":95 + * dL[N - 1, N - 1] /= (2. * L[N - 1, N - 1]) + * for k in range(N-2, -1, -1): + * n = N-k-1 # <<<<<<<<<<<<<< + * cblas.dsymv(uplo='u', n=&n, alpha=&alpha, a=&dL[k + 1, k + 1], lda=&N, x=&L[k + 1, k], incx=&incx, + * beta=&beta, y=&dL[k + 1, k], incy=&N) + */ + __pyx_v_n = ((__pyx_v_N - __pyx_v_k) - 1); + + /* "GPy/util/choleskies_cython.pyx":96 + * for k in range(N-2, -1, -1): + * n = N-k-1 + * cblas.dsymv(uplo='u', n=&n, alpha=&alpha, a=&dL[k + 1, k + 1], lda=&N, x=&L[k + 1, k], incx=&incx, # <<<<<<<<<<<<<< + * beta=&beta, y=&dL[k + 1, k], incy=&N) + * + */ + __pyx_t_6 = (__pyx_v_k + 1); + __pyx_t_7 = (__pyx_v_k + 1); + if (__pyx_t_6 < 0) __pyx_t_6 += __pyx_v_dL.shape[0]; + if (__pyx_t_7 < 0) __pyx_t_7 += __pyx_v_dL.shape[1]; + __pyx_t_8 = (__pyx_v_k + 1); + __pyx_t_9 = __pyx_v_k; + if (__pyx_t_8 < 0) __pyx_t_8 += __pyx_v_L.shape[0]; + if (__pyx_t_9 < 0) __pyx_t_9 += __pyx_v_L.shape[1]; + + /* "GPy/util/choleskies_cython.pyx":97 + * n = N-k-1 + * cblas.dsymv(uplo='u', n=&n, alpha=&alpha, a=&dL[k + 1, k + 1], lda=&N, x=&L[k + 1, k], incx=&incx, + * beta=&beta, y=&dL[k + 1, k], incy=&N) # <<<<<<<<<<<<<< + * + * for i in xrange(0, N - k - 1): + */ + __pyx_t_10 = (__pyx_v_k + 1); + __pyx_t_11 = __pyx_v_k; + if (__pyx_t_10 < 0) __pyx_t_10 += __pyx_v_dL.shape[0]; + if (__pyx_t_11 < 0) __pyx_t_11 += __pyx_v_dL.shape[1]; + + /* "GPy/util/choleskies_cython.pyx":96 + * for k in range(N-2, -1, -1): + * n = N-k-1 + * cblas.dsymv(uplo='u', n=&n, alpha=&alpha, a=&dL[k + 1, k + 1], lda=&N, x=&L[k + 1, k], incx=&incx, # <<<<<<<<<<<<<< + * beta=&beta, y=&dL[k + 1, k], incy=&N) + * + */ + __pyx_f_5scipy_6linalg_11cython_blas_dsymv(__pyx_k_u, (&__pyx_v_n), (&__pyx_v_alpha), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_6 * __pyx_v_dL.strides[0]) )) + __pyx_t_7)) )))), (&__pyx_v_N), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_8 * __pyx_v_L.strides[0]) )) + __pyx_t_9)) )))), (&__pyx_v_incx), (&__pyx_v_beta), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_10 * __pyx_v_dL.strides[0]) )) + __pyx_t_11)) )))), (&__pyx_v_N)); + + /* "GPy/util/choleskies_cython.pyx":99 + * beta=&beta, y=&dL[k + 1, k], incy=&N) + * + * for i in xrange(0, N - k - 1): # <<<<<<<<<<<<<< + * dL[k + 1 + i, k] -= dL[k + i+ 1, k + i + 1] * L[k + 1 + i, k] + * + */ + __pyx_t_12 = ((__pyx_v_N - __pyx_v_k) - 1); + for (__pyx_t_13 = 0; __pyx_t_13 < __pyx_t_12; __pyx_t_13+=1) { + __pyx_v_i = __pyx_t_13; + + /* "GPy/util/choleskies_cython.pyx":100 + * + * for i in xrange(0, N - k - 1): + * dL[k + 1 + i, k] -= dL[k + i+ 1, k + i + 1] * L[k + 1 + i, k] # <<<<<<<<<<<<<< + * + * scale = 1.0 / L[k, k] + */ + __pyx_t_14 = ((__pyx_v_k + __pyx_v_i) + 1); + __pyx_t_15 = ((__pyx_v_k + __pyx_v_i) + 1); + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_dL.shape[0]; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_dL.shape[1]; + __pyx_t_16 = ((__pyx_v_k + 1) + __pyx_v_i); + __pyx_t_17 = __pyx_v_k; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_L.shape[0]; + if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_L.shape[1]; + __pyx_t_18 = ((__pyx_v_k + 1) + __pyx_v_i); + __pyx_t_19 = __pyx_v_k; + if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_v_dL.shape[0]; + if (__pyx_t_19 < 0) __pyx_t_19 += __pyx_v_dL.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_18 * __pyx_v_dL.strides[0]) )) + __pyx_t_19)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_14 * __pyx_v_dL.strides[0]) )) + __pyx_t_15)) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_16 * __pyx_v_L.strides[0]) )) + __pyx_t_17)) )))); + } + + /* "GPy/util/choleskies_cython.pyx":102 + * dL[k + 1 + i, k] -= dL[k + i+ 1, k + i + 1] * L[k + 1 + i, k] + * + * scale = 1.0 / L[k, k] # <<<<<<<<<<<<<< + * cblas.dscal(&n, &scale , &dL[k + 1, k], &N) + * # + */ + __pyx_t_13 = __pyx_v_k; + __pyx_t_20 = __pyx_v_k; + if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_v_L.shape[0]; + if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_L.shape[1]; + __pyx_t_21 = (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_13 * __pyx_v_L.strides[0]) )) + __pyx_t_20)) ))); + if (unlikely(__pyx_t_21 == 0)) { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); + #endif + PyErr_SetString(PyExc_ZeroDivisionError, "float division"); + #ifdef WITH_THREAD + PyGILState_Release(__pyx_gilstate_save); + #endif + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 102; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_v_scale = (1.0 / __pyx_t_21); + + /* "GPy/util/choleskies_cython.pyx":103 + * + * scale = 1.0 / L[k, k] + * cblas.dscal(&n, &scale , &dL[k + 1, k], &N) # <<<<<<<<<<<<<< + * # + * dL[k, k] -= cblas.ddot(&n, &dL[k + 1, k], &N, &L[k+1, k], &incx) + */ + __pyx_t_12 = (__pyx_v_k + 1); + __pyx_t_22 = __pyx_v_k; + if (__pyx_t_12 < 0) __pyx_t_12 += __pyx_v_dL.shape[0]; + if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_dL.shape[1]; + __pyx_f_5scipy_6linalg_11cython_blas_dscal((&__pyx_v_n), (&__pyx_v_scale), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_12 * __pyx_v_dL.strides[0]) )) + __pyx_t_22)) )))), (&__pyx_v_N)); + + /* "GPy/util/choleskies_cython.pyx":105 + * cblas.dscal(&n, &scale , &dL[k + 1, k], &N) + * # + * dL[k, k] -= cblas.ddot(&n, &dL[k + 1, k], &N, &L[k+1, k], &incx) # <<<<<<<<<<<<<< + * dL[k, k] /= (2.0 * L[k, k]) + * + */ + __pyx_t_23 = (__pyx_v_k + 1); + __pyx_t_24 = __pyx_v_k; + if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_dL.shape[0]; + if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_dL.shape[1]; + __pyx_t_25 = (__pyx_v_k + 1); + __pyx_t_26 = __pyx_v_k; + if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_L.shape[0]; + if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_L.shape[1]; + __pyx_t_27 = __pyx_v_k; + __pyx_t_28 = __pyx_v_k; + if (__pyx_t_27 < 0) __pyx_t_27 += __pyx_v_dL.shape[0]; + if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_dL.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_27 * __pyx_v_dL.strides[0]) )) + __pyx_t_28)) )) -= __pyx_f_5scipy_6linalg_11cython_blas_ddot((&__pyx_v_n), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_23 * __pyx_v_dL.strides[0]) )) + __pyx_t_24)) )))), (&__pyx_v_N), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_25 * __pyx_v_L.strides[0]) )) + __pyx_t_26)) )))), (&__pyx_v_incx)); + + /* "GPy/util/choleskies_cython.pyx":106 + * # + * dL[k, k] -= cblas.ddot(&n, &dL[k + 1, k], &N, &L[k+1, k], &incx) + * dL[k, k] /= (2.0 * L[k, k]) # <<<<<<<<<<<<<< + * + * def backprop_gradient_par_c(double[:, :] dL, double[:, :] L): + */ + __pyx_t_29 = __pyx_v_k; + __pyx_t_30 = __pyx_v_k; + if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_v_L.shape[0]; + if (__pyx_t_30 < 0) __pyx_t_30 += __pyx_v_L.shape[1]; + __pyx_t_31 = __pyx_v_k; + __pyx_t_32 = __pyx_v_k; + if (__pyx_t_31 < 0) __pyx_t_31 += __pyx_v_dL.shape[0]; + if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_v_dL.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_31 * __pyx_v_dL.strides[0]) )) + __pyx_t_32)) )) /= (2.0 * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_29 * __pyx_v_L.strides[0]) )) + __pyx_t_30)) )))); + } + + /* "GPy/util/choleskies_cython.pyx":83 + * return dL_dK + * + * cdef void chol_backprop(int N, double[:, ::1] dL, double[:, ::1] L) nogil: # <<<<<<<<<<<<<< + * cdef int i, k, n + * + */ + + /* function exit code */ + goto __pyx_L0; + __pyx_L1_error:; + __Pyx_WriteUnraisable("GPy.util.choleskies_cython.chol_backprop", __pyx_clineno, __pyx_lineno, __pyx_filename, 0); + __pyx_L0:; +} + +/* "GPy/util/choleskies_cython.pyx":108 + * dL[k, k] /= (2.0 * L[k, k]) + * + * def backprop_gradient_par_c(double[:, :] dL, double[:, :] L): # <<<<<<<<<<<<<< + * cdef double[:, ::1] dL_dK = np.tril(dL) # makes a copy, c-contig + * cdef double[:, ::1] L_cont = np.ascontiguousarray(L) */ /* Python wrapper */ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c = {"backprop_gradient_par_c", (PyCFunction)__pyx_pw_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c, METH_VARARGS|METH_KEYWORDS, 0}; static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - PyArrayObject *__pyx_v_dL = 0; - PyArrayObject *__pyx_v_L = 0; + __Pyx_memviewslice __pyx_v_dL = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_memviewslice __pyx_v_L = { 0, 0, { 0 }, { 0 }, { 0 } }; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -3322,11 +3615,11 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_9backprop_gradient_par_ case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_L)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("backprop_gradient_par_c", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("backprop_gradient_par_c", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 108; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "backprop_gradient_par_c") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if 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pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -3948,14 +4009,12 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_C_CONTIGUOUS) == PyBUF_C_CONTIGUOUS) != 0); if (__pyx_t_2) { - goto __pyx_L7_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L6_bool_binop_done; } - __pyx_L7_next_and:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -3967,21 +4026,21 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L6_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":224 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -4032,7 +4089,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->buf = PyArray_DATA(__pyx_v_self); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":225 * * 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info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -4080,7 +4137,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -4089,7 +4146,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -4102,7 +4159,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< @@ -4111,7 +4168,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self)); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -4122,7 +4179,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L11:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":237 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -4131,7 +4188,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->suboffsets = NULL; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":238 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -4140,7 +4197,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -4149,7 +4206,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->readonly = (!(PyArray_ISWRITEABLE(__pyx_v_self) != 0)); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":242 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< @@ -4158,7 +4215,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_f = NULL; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":243 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< @@ -4170,7 +4227,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_descr = ((PyArray_Descr *)__pyx_t_3); __pyx_t_3 = 0; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":247 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -4179,7 +4236,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":249 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -4188,18 +4245,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_2) { - goto __pyx_L16_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L15_bool_binop_done; } - __pyx_L16_next_and:; __pyx_t_2 = ((!(__pyx_v_copy_shape != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L15_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -4215,7 +4270,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< @@ -4230,7 +4285,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L14:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -4240,7 +4295,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -4250,7 +4305,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_4 = __pyx_v_descr->type_num; __pyx_v_t = __pyx_t_4; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -4261,19 +4316,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P if (!__pyx_t_2) { goto __pyx_L20_next_or; } else { - goto __pyx_L21_next_and; } - __pyx_L21_next_and:; __pyx_t_2 = (__pyx_v_little_endian != 0); if (!__pyx_t_2) { - goto __pyx_L20_next_or; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } __pyx_L20_next_or:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -4282,32 +4334,30 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((__pyx_v_descr->byteorder == '<') != 0); if (__pyx_t_2) { - goto __pyx_L22_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } - __pyx_L22_next_and:; __pyx_t_2 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L19_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -4316,7 +4366,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ switch (__pyx_v_t) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< @@ -4327,7 +4377,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_b; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -4338,7 +4388,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_B; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -4349,7 +4399,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_h; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -4360,7 +4410,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_H; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -4371,7 +4421,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_i; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -4382,7 +4432,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_I; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -4393,7 +4443,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_l; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -4404,7 +4454,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_L; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -4415,7 +4465,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_q; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -4426,7 +4476,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Q; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -4437,7 +4487,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_f; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -4448,7 +4498,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_d; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -4459,7 +4509,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_g; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -4470,7 +4520,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zf; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":275 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -4481,7 +4531,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zd; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -4492,7 +4542,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zg; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -4504,33 +4554,33 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P break; default: - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":279 * elif t == NPY_OBJECT: f = "O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< * info.format = f * return */ - __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_t); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_6 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyUnicode_Format(__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_6); __Pyx_GIVEREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_Raise(__pyx_t_6, 0, 0, 0); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L1_error;} break; } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f # <<<<<<<<<<<<<< @@ -4539,7 +4589,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->format = __pyx_v_f; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281 * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f * return # <<<<<<<<<<<<<< @@ -4551,7 +4601,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 * return * else: * info.format = stdlib.malloc(_buffer_format_string_len) # <<<<<<<<<<<<<< @@ -4560,7 +4610,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->format = ((char *)malloc(255)); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":284 * else: * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment # <<<<<<<<<<<<<< @@ -4569,7 +4619,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->format[0]) = '^'; - /* 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__pyx_t_3 = __Pyx_PyDict_GetItem(__pyx_v_descr->fields, __pyx_v_childname); if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; __Pyx_GOTREF(__pyx_t_3); - if (!(likely(PyTuple_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "tuple", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(PyTuple_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "tuple", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_XDECREF_SET(__pyx_v_fields, ((PyObject*)__pyx_t_3)); __pyx_t_3 = 0; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 + /* 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PySequence_ITEM(sequence, 0); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_4 = PySequence_ITEM(sequence, 1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PySequence_ITEM(sequence, 1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); #endif } else { - __Pyx_RaiseNoneNotIterableError(); {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_RaiseNoneNotIterableError(); {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_ptype_5numpy_dtype))))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_ptype_5numpy_dtype))))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_XDECREF_SET(__pyx_v_child, ((PyArray_Descr *)__pyx_t_3)); __pyx_t_3 = 0; __Pyx_XDECREF_SET(__pyx_v_new_offset, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 * child, new_offset = fields * * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") * */ - __pyx_t_4 = __Pyx_PyInt_From_int((__pyx_v_offset[0])); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto 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__pyx_v_memviewsliceobj = ((struct __pyx_memoryviewslice_obj *)__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":683 + /* "View.MemoryView":682 * if isinstance(memview, _memoryviewslice): * memviewsliceobj = memview * p_src = &memviewsliceobj.from_slice # <<<<<<<<<<<<<< @@ -11876,7 +11876,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } /*else*/ { - /* "View.MemoryView":685 + /* "View.MemoryView":684 * p_src = &memviewsliceobj.from_slice * else: * slice_copy(memview, &src) # <<<<<<<<<<<<<< @@ -11885,7 +11885,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __pyx_memoryview_slice_copy(__pyx_v_memview, (&__pyx_v_src)); - /* "View.MemoryView":686 + /* "View.MemoryView":685 * else: * slice_copy(memview, &src) * p_src = &src # <<<<<<<<<<<<<< @@ -11896,7 +11896,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __pyx_L3:; - /* "View.MemoryView":692 + /* "View.MemoryView":691 * 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = Py_TYPE(__pyx_t_3)->tp_iternext; if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 702; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } for (;;) { if (likely(!__pyx_t_8)) { if (likely(PyList_CheckExact(__pyx_t_3))) { if (__pyx_t_7 >= PyList_GET_SIZE(__pyx_t_3)) break; #if CYTHON_COMPILING_IN_CPYTHON - __pyx_t_9 = PyList_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyList_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 702; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #else - __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 702; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif } else { if (__pyx_t_7 >= PyTuple_GET_SIZE(__pyx_t_3)) break; #if CYTHON_COMPILING_IN_CPYTHON - __pyx_t_9 = PyTuple_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyTuple_GET_ITEM(__pyx_t_3, __pyx_t_7); __Pyx_INCREF(__pyx_t_9); __pyx_t_7++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 702; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #else - __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 703; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if 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(unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); - __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} if (!__pyx_t_1) { __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - goto __pyx_L12_next_or; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 719; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 718; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L11_bool_binop_done; } - __pyx_L12_next_or:; __pyx_t_10 = 0; __pyx_L11_bool_binop_done:; __pyx_v_step = __pyx_t_10; - /* "View.MemoryView":721 + /* "View.MemoryView":720 * step = index.step or 0 * * have_start = index.start is not None # <<<<<<<<<<<<<< * have_stop = index.stop is not None * have_step = index.step is not None */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 721; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 720; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __pyx_t_1 = (__pyx_t_9 != Py_None); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __pyx_v_have_start = __pyx_t_1; - /* "View.MemoryView":722 + /* "View.MemoryView":721 * * have_start = index.start is not None * have_stop = index.stop is not None # <<<<<<<<<<<<<< * have_step = index.step is not None * */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 722; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 721; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __pyx_t_1 = (__pyx_t_9 != Py_None); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __pyx_v_have_stop = __pyx_t_1; - /* "View.MemoryView":723 + /* "View.MemoryView":722 * have_start = index.start is not None * have_stop = index.stop is not None * have_step = index.step is not None # <<<<<<<<<<<<<< * * slice_memviewslice( */ - __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 723; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 722; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __pyx_t_1 = (__pyx_t_9 != Py_None); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __pyx_v_have_step = __pyx_t_1; - /* "View.MemoryView":725 + /* "View.MemoryView":724 * have_step = index.step is not None * * slice_memviewslice( # <<<<<<<<<<<<<< * p_dst, p_src.shape[dim], p_src.strides[dim], p_src.suboffsets[dim], * dim, new_ndim, p_suboffset_dim, */ - __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_v_start, __pyx_v_stop, __pyx_v_step, __pyx_v_have_start, __pyx_v_have_stop, __pyx_v_have_step, 1); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 725; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_v_start, __pyx_v_stop, __pyx_v_step, __pyx_v_have_start, __pyx_v_have_stop, __pyx_v_have_step, 1); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 724; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":731 + /* "View.MemoryView":730 * have_start, have_stop, have_step, * True) * new_ndim += 1 # <<<<<<<<<<<<<< @@ -12195,7 +12189,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __pyx_L6:; - /* "View.MemoryView":703 + /* "View.MemoryView":702 * cdef bint have_start, have_stop, have_step * * for dim, index in enumerate(indices): # <<<<<<<<<<<<<< @@ -12205,7 +12199,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":733 + /* "View.MemoryView":732 * new_ndim += 1 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -12216,7 +12210,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":734 + /* "View.MemoryView":733 * * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< @@ -12225,41 +12219,41 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":735 + /* "View.MemoryView":734 * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, * memviewsliceobj.to_object_func, # <<<<<<<<<<<<<< * memviewsliceobj.to_dtype_func, * memview.dtype_is_object) */ - if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "View.MemoryView":736 + /* "View.MemoryView":735 * return memoryview_fromslice(dst, new_ndim, * memviewsliceobj.to_object_func, * memviewsliceobj.to_dtype_func, # <<<<<<<<<<<<<< * memview.dtype_is_object) * else: */ - if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 736; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "View.MemoryView":734 + /* "View.MemoryView":733 * * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< * memviewsliceobj.to_object_func, * memviewsliceobj.to_dtype_func, */ - __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 733; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 733; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; } /*else*/ { - /* "View.MemoryView":739 + /* "View.MemoryView":738 * memview.dtype_is_object) * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< @@ -12268,30 +12262,30 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":740 + /* "View.MemoryView":739 * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, * memview.dtype_is_object) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 739; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 738; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - /* "View.MemoryView":739 + /* "View.MemoryView":738 * memview.dtype_is_object) * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< * memview.dtype_is_object) * */ - if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 739; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 738; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; } - /* "View.MemoryView":667 + /* "View.MemoryView":666 * * @cname('__pyx_memview_slice') * cdef memoryview memview_slice(memoryview memview, object indices): # <<<<<<<<<<<<<< @@ -12313,7 +12307,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ return __pyx_r; } -/* "View.MemoryView":764 +/* "View.MemoryView":763 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -12332,7 +12326,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "View.MemoryView":784 + /* "View.MemoryView":783 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< @@ -12342,7 +12336,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); if (__pyx_t_1) { - /* "View.MemoryView":786 + /* "View.MemoryView":785 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< @@ -12352,7 +12346,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_1 = ((__pyx_v_start < 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":787 + /* "View.MemoryView":786 * * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -12364,7 +12358,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L4:; - /* "View.MemoryView":788 + /* "View.MemoryView":787 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< @@ -12378,14 +12372,14 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":789 + /* "View.MemoryView":788 * start += shape * if not 0 <= start < shape: * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<< * else: * */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 788; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L5; } __pyx_L5:; @@ -12393,7 +12387,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":792 + /* "View.MemoryView":791 * else: * * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< @@ -12402,18 +12396,16 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); if (__pyx_t_1) { - goto __pyx_L7_next_and; } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L6_bool_binop_done; } - __pyx_L7_next_and:; __pyx_t_1 = ((__pyx_v_step < 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L6_bool_binop_done:; __pyx_v_negative_step = __pyx_t_2; - /* "View.MemoryView":794 + /* "View.MemoryView":793 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< @@ -12422,30 +12414,28 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_t_1 = (__pyx_v_have_step != 0); if (__pyx_t_1) { - goto __pyx_L10_next_and; } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L9_bool_binop_done; } - __pyx_L10_next_and:; __pyx_t_1 = ((__pyx_v_step == 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L9_bool_binop_done:; if (__pyx_t_2) { - /* "View.MemoryView":795 + /* "View.MemoryView":794 * * if have_step and step == 0: * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 794; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L8; } __pyx_L8:; - /* "View.MemoryView":798 + /* "View.MemoryView":797 * * * if have_start: # <<<<<<<<<<<<<< @@ -12455,7 +12445,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_have_start != 0); if (__pyx_t_2) { - /* "View.MemoryView":799 + /* "View.MemoryView":798 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< @@ -12465,7 +12455,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":800 + /* "View.MemoryView":799 * if have_start: * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -12474,7 +12464,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - /* "View.MemoryView":801 + /* "View.MemoryView":800 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< @@ -12484,7 +12474,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":802 + /* "View.MemoryView":801 * start += shape * if start < 0: * start = 0 # <<<<<<<<<<<<<< @@ -12498,7 +12488,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L12; } - /* "View.MemoryView":803 + /* "View.MemoryView":802 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< @@ -12508,7 +12498,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); if (__pyx_t_2) { - /* "View.MemoryView":804 + /* "View.MemoryView":803 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< @@ -12518,7 +12508,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { - /* "View.MemoryView":805 + /* "View.MemoryView":804 * elif start >= shape: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -12530,7 +12520,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":807 + /* "View.MemoryView":806 * start = shape - 1 * else: * start = shape # <<<<<<<<<<<<<< @@ -12547,7 +12537,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":809 + /* "View.MemoryView":808 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -12557,7 +12547,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { - /* "View.MemoryView":810 + /* "View.MemoryView":809 * else: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -12569,7 +12559,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":812 + /* "View.MemoryView":811 * start = shape - 1 * else: * start = 0 # <<<<<<<<<<<<<< @@ -12582,7 +12572,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L11:; - /* "View.MemoryView":814 + /* "View.MemoryView":813 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< @@ -12592,7 +12582,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_have_stop != 0); if (__pyx_t_2) { - /* "View.MemoryView":815 + /* "View.MemoryView":814 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< @@ -12602,7 +12592,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_stop < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":816 + /* "View.MemoryView":815 * if have_stop: * if stop < 0: * stop += shape # <<<<<<<<<<<<<< @@ -12611,7 +12601,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); - /* "View.MemoryView":817 + /* "View.MemoryView":816 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< @@ -12621,7 +12611,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_stop < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":818 + /* "View.MemoryView":817 * stop += shape * if stop < 0: * stop = 0 # <<<<<<<<<<<<<< @@ -12635,7 +12625,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L17; } - /* "View.MemoryView":819 + /* "View.MemoryView":818 * if stop < 0: * stop = 0 * elif stop > shape: # <<<<<<<<<<<<<< @@ -12645,7 +12635,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); if (__pyx_t_2) { - /* "View.MemoryView":820 + /* "View.MemoryView":819 * stop = 0 * elif stop > shape: * stop = shape # <<<<<<<<<<<<<< @@ -12660,7 +12650,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":822 + /* "View.MemoryView":821 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -12670,7 +12660,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { - /* "View.MemoryView":823 + /* "View.MemoryView":822 * else: * if negative_step: * stop = -1 # <<<<<<<<<<<<<< @@ -12682,7 +12672,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":825 + /* "View.MemoryView":824 * stop = -1 * else: * stop = shape # <<<<<<<<<<<<<< @@ -12695,7 +12685,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L16:; - /* "View.MemoryView":827 + /* "View.MemoryView":826 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< @@ -12705,7 +12695,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":828 + /* "View.MemoryView":827 * * if not have_step: * step = 1 # <<<<<<<<<<<<<< @@ -12717,7 +12707,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L20:; - /* "View.MemoryView":832 + /* "View.MemoryView":831 * * with cython.cdivision(True): * new_shape = (stop - start) // step # <<<<<<<<<<<<<< @@ -12726,7 +12716,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); - /* "View.MemoryView":834 + /* "View.MemoryView":833 * new_shape = (stop - start) // step * * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< @@ -12736,7 +12726,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":835 + /* "View.MemoryView":834 * * if (stop - start) - step * new_shape: * new_shape += 1 # <<<<<<<<<<<<<< @@ -12748,7 +12738,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L21:; - /* "View.MemoryView":837 + /* "View.MemoryView":836 * new_shape += 1 * * if new_shape < 0: # <<<<<<<<<<<<<< @@ -12758,7 +12748,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":838 + /* "View.MemoryView":837 * * if new_shape < 0: * new_shape = 0 # <<<<<<<<<<<<<< @@ -12770,7 +12760,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L22:; - /* "View.MemoryView":841 + /* "View.MemoryView":840 * * * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< @@ -12779,7 +12769,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step); - /* "View.MemoryView":842 + /* "View.MemoryView":841 * * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< @@ -12788,7 +12778,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape; - /* "View.MemoryView":843 + /* "View.MemoryView":842 * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< @@ -12799,7 +12789,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L3:; - /* "View.MemoryView":846 + /* "View.MemoryView":845 * * * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< @@ -12809,7 +12799,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":847 + /* "View.MemoryView":846 * * if suboffset_dim[0] < 0: * dst.data += start * stride # <<<<<<<<<<<<<< @@ -12821,7 +12811,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":849 + /* "View.MemoryView":848 * dst.data += start * stride * else: * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< @@ -12833,7 +12823,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L23:; - /* "View.MemoryView":851 + /* "View.MemoryView":850 * dst.suboffsets[suboffset_dim[0]] += start * stride * * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -12843,7 +12833,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":852 + /* "View.MemoryView":851 * * if suboffset >= 0: * if not is_slice: # <<<<<<<<<<<<<< @@ -12853,7 +12843,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":853 + /* "View.MemoryView":852 * if suboffset >= 0: * if not is_slice: * if new_ndim == 0: # <<<<<<<<<<<<<< @@ -12863,7 +12853,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":854 + /* "View.MemoryView":853 * if not is_slice: * if new_ndim == 0: * dst.data = ( dst.data)[0] + suboffset # <<<<<<<<<<<<<< @@ -12875,21 +12865,21 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } /*else*/ { - /* "View.MemoryView":856 + /* "View.MemoryView":855 * dst.data = ( dst.data)[0] + suboffset * else: * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<< * "must be indexed and not sliced", dim) * else: */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 856; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 855; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_L26:; goto __pyx_L25; } /*else*/ { - /* "View.MemoryView":859 + /* "View.MemoryView":858 * "must be indexed and not sliced", dim) * else: * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< @@ -12903,7 +12893,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L24:; - /* "View.MemoryView":861 + /* "View.MemoryView":860 * suboffset_dim[0] = new_ndim * * return 0 # <<<<<<<<<<<<<< @@ -12913,7 +12903,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":764 + /* "View.MemoryView":763 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -12937,7 +12927,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, return __pyx_r; } -/* "View.MemoryView":867 +/* "View.MemoryView":866 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -12962,7 +12952,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P int __pyx_clineno = 0; __Pyx_RefNannySetupContext("pybuffer_index", 0); - /* "View.MemoryView":869 + /* "View.MemoryView":868 * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, * Py_ssize_t dim) except NULL: * cdef Py_ssize_t shape, stride, suboffset = -1 # <<<<<<<<<<<<<< @@ -12971,7 +12961,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_suboffset = -1; - /* "View.MemoryView":870 + /* "View.MemoryView":869 * Py_ssize_t dim) except NULL: * cdef Py_ssize_t shape, stride, suboffset = -1 * cdef Py_ssize_t itemsize = view.itemsize # <<<<<<<<<<<<<< @@ -12981,7 +12971,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_1 = __pyx_v_view->itemsize; __pyx_v_itemsize = __pyx_t_1; - /* "View.MemoryView":873 + /* "View.MemoryView":872 * cdef char *resultp * * if view.ndim == 0: # <<<<<<<<<<<<<< @@ -12991,7 +12981,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_view->ndim == 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":874 + /* "View.MemoryView":873 * * if view.ndim == 0: * shape = view.len / itemsize # <<<<<<<<<<<<<< @@ -13006,7 +12996,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P #ifdef WITH_THREAD PyGILState_Release(__pyx_gilstate_save); #endif - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 873; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else if (sizeof(Py_ssize_t) == sizeof(long) && unlikely(__pyx_v_itemsize == -1) && unlikely(UNARY_NEG_WOULD_OVERFLOW(__pyx_v_view->len))) { #ifdef WITH_THREAD @@ -13016,11 +13006,11 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P #ifdef WITH_THREAD PyGILState_Release(__pyx_gilstate_save); #endif - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 873; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_v_shape = __Pyx_div_Py_ssize_t(__pyx_v_view->len, __pyx_v_itemsize); - /* "View.MemoryView":875 + /* "View.MemoryView":874 * if view.ndim == 0: * shape = view.len / itemsize * stride = itemsize # <<<<<<<<<<<<<< @@ -13032,7 +13022,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P } /*else*/ { - /* "View.MemoryView":877 + /* "View.MemoryView":876 * stride = itemsize * else: * shape = view.shape[dim] # <<<<<<<<<<<<<< @@ -13041,7 +13031,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_shape = (__pyx_v_view->shape[__pyx_v_dim]); - /* "View.MemoryView":878 + /* "View.MemoryView":877 * else: * shape = view.shape[dim] * stride = view.strides[dim] # <<<<<<<<<<<<<< @@ -13050,7 +13040,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_stride = (__pyx_v_view->strides[__pyx_v_dim]); - /* "View.MemoryView":879 + /* "View.MemoryView":878 * shape = view.shape[dim] * stride = view.strides[dim] * if view.suboffsets != NULL: # <<<<<<<<<<<<<< @@ -13060,7 +13050,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_view->suboffsets != NULL) != 0); if (__pyx_t_2) { - /* "View.MemoryView":880 + /* "View.MemoryView":879 * stride = view.strides[dim] * if view.suboffsets != NULL: * suboffset = view.suboffsets[dim] # <<<<<<<<<<<<<< @@ -13074,7 +13064,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P } __pyx_L3:; - /* "View.MemoryView":882 + /* "View.MemoryView":881 * suboffset = view.suboffsets[dim] * * if index < 0: # <<<<<<<<<<<<<< @@ -13084,7 +13074,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_index < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":883 + /* "View.MemoryView":882 * * if index < 0: * index += view.shape[dim] # <<<<<<<<<<<<<< @@ -13093,7 +13083,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_index = (__pyx_v_index + (__pyx_v_view->shape[__pyx_v_dim])); - /* "View.MemoryView":884 + /* "View.MemoryView":883 * if index < 0: * index += view.shape[dim] * if index < 0: # <<<<<<<<<<<<<< @@ -13103,35 +13093,35 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P __pyx_t_2 = ((__pyx_v_index < 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":885 + /* "View.MemoryView":884 * index += view.shape[dim] * if index < 0: * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) # <<<<<<<<<<<<<< * * if index >= shape: */ - __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 884; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_4 = __Pyx_PyString_Format(__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_t_3); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyString_Format(__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_t_3); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 884; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 884; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_4); __Pyx_GIVEREF(__pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = __Pyx_PyObject_Call(__pyx_builtin_IndexError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_Call(__pyx_builtin_IndexError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 884; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_Raise(__pyx_t_4, 0, 0, 0); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 884; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } goto __pyx_L5; } __pyx_L5:; - /* "View.MemoryView":887 + /* "View.MemoryView":886 * raise IndexError("Out of bounds on buffer access (axis %d)" % 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{__pyx_filename = __pyx_f[2]; __pyx_lineno = 946; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_assign_item_from_object(((struct __pyx_memoryview_obj *)__pyx_v_self), __pyx_v_itemp, __pyx_v_value); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 945; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; } __pyx_L3:; - /* "View.MemoryView":942 + /* "View.MemoryView":941 * return memoryview.convert_item_to_object(self, itemp) * * cdef assign_item_from_object(self, char *itemp, object value): # <<<<<<<<<<<<<< @@ -13591,7 +13579,7 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo return __pyx_r; } -/* "View.MemoryView":950 +/* "View.MemoryView":949 * property base: * @cname('__pyx_memoryviewslice__get__base') * def __get__(self): # <<<<<<<<<<<<<< @@ -13605,19 +13593,19 @@ static PyObject *__pyx_memoryviewslice__get__base(PyObject 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= __pyx_f[2]; __pyx_lineno = 977; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_memviewslice.memview), __pyx_n_s_base); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); __Pyx_GOTREF(__pyx_v_result->from_object); @@ -13752,7 +13742,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_v_result->from_object = __pyx_t_2; __pyx_t_2 = 0; - /* "View.MemoryView":978 + /* "View.MemoryView":976 * * result.from_object = ( memviewslice.memview).base * result.typeinfo = memviewslice.memview.typeinfo # <<<<<<<<<<<<<< @@ -13762,7 +13752,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_4 = __pyx_v_memviewslice.memview->typeinfo; __pyx_v_result->__pyx_base.typeinfo = __pyx_t_4; - /* "View.MemoryView":980 + /* "View.MemoryView":978 * 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break + * + */ + __pyx_v_result->__pyx_base.view.suboffsets = ((Py_ssize_t *)__pyx_v_result->from_slice.suboffsets); + + /* "View.MemoryView":994 + * if suboffset >= 0: + * result.view.suboffsets = result.from_slice.suboffsets + * break # <<<<<<<<<<<<<< * * result.view.len = result.view.itemsize */ - __pyx_v_result->__pyx_base.view.suboffsets = ((Py_ssize_t *)__pyx_v_result->from_slice.suboffsets); + goto __pyx_L5_break; + } + } + __pyx_L5_break:; - /* "View.MemoryView":992 - * result.view.suboffsets = result.from_slice.suboffsets + /* "View.MemoryView":996 + * break * * result.view.len = result.view.itemsize # <<<<<<<<<<<<<< - * for i in range(ndim): - * result.view.len *= result.view.shape[i] + * for length in result.view.shape[:ndim]: + * result.view.len *= length */ - __pyx_t_6 = __pyx_v_result->__pyx_base.view.itemsize; - __pyx_v_result->__pyx_base.view.len = __pyx_t_6; + __pyx_t_9 = __pyx_v_result->__pyx_base.view.itemsize; + __pyx_v_result->__pyx_base.view.len = __pyx_t_9; - /* 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+ __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; + __pyx_v_result->__pyx_base.view.len = __pyx_t_9; } - /* "View.MemoryView":996 - * result.view.len *= result.view.shape[i] + /* "View.MemoryView":1000 + * result.view.len *= length * * result.to_object_func = to_object_func # <<<<<<<<<<<<<< * result.to_dtype_func = to_dtype_func @@ -13884,7 +13928,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_object_func = __pyx_v_to_object_func; - /* "View.MemoryView":997 + /* "View.MemoryView":1001 * * result.to_object_func = to_object_func * result.to_dtype_func = to_dtype_func # <<<<<<<<<<<<<< @@ -13893,7 +13937,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_dtype_func = __pyx_v_to_dtype_func; - /* "View.MemoryView":999 + /* "View.MemoryView":1003 * result.to_dtype_func = to_dtype_func * * return result # <<<<<<<<<<<<<< @@ -13905,7 +13949,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_r = ((PyObject *)__pyx_v_result); goto __pyx_L0; - /* "View.MemoryView":957 + /* "View.MemoryView":956 * * @cname('__pyx_memoryview_fromslice') * cdef memoryview_fromslice(__Pyx_memviewslice memviewslice, # <<<<<<<<<<<<<< @@ -13921,12 +13965,13 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_r = 0; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_result); + __Pyx_XDECREF(__pyx_v_length); __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "View.MemoryView":1002 +/* "View.MemoryView":1006 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< @@ -13946,7 +13991,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p int __pyx_clineno = 0; __Pyx_RefNannySetupContext("get_slice_from_memview", 0); - /* "View.MemoryView":1005 + /* 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((PyObject *)__pyx_v_memview); __Pyx_INCREF(__pyx_t_3); __pyx_v_obj = ((struct __pyx_memoryviewslice_obj *)__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":1007 + /* "View.MemoryView":1011 * if isinstance(memview, _memoryviewslice): * obj = memview * return &obj.from_slice # <<<<<<<<<<<<<< @@ -13982,7 +14027,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p } /*else*/ { - /* "View.MemoryView":1009 + /* "View.MemoryView":1013 * return &obj.from_slice * else: * slice_copy(memview, mslice) # <<<<<<<<<<<<<< @@ -13991,7 +14036,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p */ __pyx_memoryview_slice_copy(__pyx_v_memview, __pyx_v_mslice); - /* "View.MemoryView":1010 + /* "View.MemoryView":1014 * else: * slice_copy(memview, mslice) * return mslice # <<<<<<<<<<<<<< @@ -14002,7 +14047,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p goto __pyx_L0; } - /* "View.MemoryView":1002 + /* "View.MemoryView":1006 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< @@ -14021,7 +14066,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p return __pyx_r; } -/* "View.MemoryView":1013 +/* "View.MemoryView":1017 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -14038,10 +14083,10 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem Py_ssize_t *__pyx_t_1; int __pyx_t_2; int __pyx_t_3; - int __pyx_t_4; + Py_ssize_t __pyx_t_4; __Pyx_RefNannySetupContext("slice_copy", 0); - /* "View.MemoryView":1017 + /* "View.MemoryView":1021 * cdef (Py_ssize_t*) shape, strides, suboffsets * * shape = memview.view.shape # <<<<<<<<<<<<<< @@ -14051,7 +14096,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __pyx_t_1 = __pyx_v_memview->view.shape; __pyx_v_shape = __pyx_t_1; - /* "View.MemoryView":1018 + /* "View.MemoryView":1022 * * shape = memview.view.shape * strides = memview.view.strides # <<<<<<<<<<<<<< @@ -14061,7 +14106,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __pyx_t_1 = __pyx_v_memview->view.strides; __pyx_v_strides = __pyx_t_1; - /* "View.MemoryView":1019 + /* "View.MemoryView":1023 * shape = memview.view.shape * strides = memview.view.strides * suboffsets = memview.view.suboffsets # <<<<<<<<<<<<<< @@ -14071,7 +14116,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __pyx_t_1 = __pyx_v_memview->view.suboffsets; __pyx_v_suboffsets = __pyx_t_1; - /* "View.MemoryView":1021 + /* "View.MemoryView":1025 * suboffsets = memview.view.suboffsets * * dst.memview = <__pyx_memoryview *> memview # <<<<<<<<<<<<<< @@ -14080,7 +14125,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ __pyx_v_dst->memview = ((struct __pyx_memoryview_obj *)__pyx_v_memview); - /* "View.MemoryView":1022 + /* "View.MemoryView":1026 * * dst.memview = <__pyx_memoryview *> memview * dst.data = memview.view.buf # <<<<<<<<<<<<<< @@ -14089,7 +14134,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ __pyx_v_dst->data = ((char *)__pyx_v_memview->view.buf); - /* "View.MemoryView":1024 + /* "View.MemoryView":1028 * dst.data = memview.view.buf * * for dim in range(memview.view.ndim): # <<<<<<<<<<<<<< @@ -14100,59 +14145,40 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_dim = __pyx_t_3; - /* "View.MemoryView":1025 + /* "View.MemoryView":1029 * * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] # <<<<<<<<<<<<<< * dst.strides[dim] = strides[dim] - * if suboffsets == NULL: + * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 */ (__pyx_v_dst->shape[__pyx_v_dim]) = (__pyx_v_shape[__pyx_v_dim]); - /* "View.MemoryView":1026 + /* "View.MemoryView":1030 * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] # <<<<<<<<<<<<<< - * if suboffsets == NULL: - * dst.suboffsets[dim] = -1 + * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 + * */ (__pyx_v_dst->strides[__pyx_v_dim]) = (__pyx_v_strides[__pyx_v_dim]); - /* "View.MemoryView":1027 + /* "View.MemoryView":1031 * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] - * if suboffsets == NULL: # <<<<<<<<<<<<<< - * dst.suboffsets[dim] = -1 - * else: - */ - __pyx_t_4 = ((__pyx_v_suboffsets == NULL) != 0); - if (__pyx_t_4) { - - /* "View.MemoryView":1028 - * dst.strides[dim] = strides[dim] - * if suboffsets == NULL: - * dst.suboffsets[dim] = -1 # <<<<<<<<<<<<<< - * else: - * dst.suboffsets[dim] = suboffsets[dim] - */ - (__pyx_v_dst->suboffsets[__pyx_v_dim]) = -1; - goto __pyx_L5; - } - /*else*/ { - - /* "View.MemoryView":1030 - * dst.suboffsets[dim] = -1 - * else: - * dst.suboffsets[dim] = suboffsets[dim] # <<<<<<<<<<<<<< + * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_copy_object') */ - (__pyx_v_dst->suboffsets[__pyx_v_dim]) = (__pyx_v_suboffsets[__pyx_v_dim]); + if ((__pyx_v_suboffsets != 0)) { + __pyx_t_4 = (__pyx_v_suboffsets[__pyx_v_dim]); + } else { + __pyx_t_4 = -1; } - __pyx_L5:; + (__pyx_v_dst->suboffsets[__pyx_v_dim]) = __pyx_t_4; } - /* "View.MemoryView":1013 + /* "View.MemoryView":1017 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -14164,7 +14190,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1033 +/* "View.MemoryView":1034 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -14182,7 +14208,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy", 0); - /* "View.MemoryView":1036 + /* "View.MemoryView":1037 * "Create a new memoryview object" * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -14191,7 +14217,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx */ __pyx_memoryview_slice_copy(__pyx_v_memview, (&__pyx_v_memviewslice)); - /* "View.MemoryView":1037 + /* "View.MemoryView":1038 * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) * return memoryview_copy_from_slice(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -14199,13 +14225,13 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx * @cname('__pyx_memoryview_copy_object_from_slice') */ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1037; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1038; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; - /* "View.MemoryView":1033 + /* "View.MemoryView":1034 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -14224,7 +14250,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx return __pyx_r; } -/* "View.MemoryView":1040 +/* "View.MemoryView":1041 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -14247,7 +14273,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy_from_slice", 0); - /* "View.MemoryView":1047 + /* "View.MemoryView":1048 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -14258,7 +14284,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1048 + /* "View.MemoryView":1049 * * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func # <<<<<<<<<<<<<< @@ -14268,7 +14294,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview __pyx_t_3 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_object_func; __pyx_v_to_object_func = __pyx_t_3; - /* "View.MemoryView":1049 + /* "View.MemoryView":1050 * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func # <<<<<<<<<<<<<< @@ -14281,7 +14307,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview } /*else*/ { - /* "View.MemoryView":1051 + /* "View.MemoryView":1052 * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func * else: * to_object_func = NULL # <<<<<<<<<<<<<< @@ -14290,7 +14316,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview */ __pyx_v_to_object_func = NULL; - /* "View.MemoryView":1052 + /* "View.MemoryView":1053 * else: * to_object_func = NULL * to_dtype_func = NULL # <<<<<<<<<<<<<< @@ -14301,7 +14327,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview } __pyx_L3:; - /* "View.MemoryView":1054 + /* "View.MemoryView":1055 * to_dtype_func = NULL * * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< @@ -14310,20 +14336,20 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview */ __Pyx_XDECREF(__pyx_r); - /* "View.MemoryView":1056 + /* "View.MemoryView":1057 * return memoryview_fromslice(memviewslice[0], memview.view.ndim, * to_object_func, to_dtype_func, * memview.dtype_is_object) # <<<<<<<<<<<<<< * * */ - __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1054; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1055; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __pyx_r = __pyx_t_5; __pyx_t_5 = 0; goto __pyx_L0; - /* "View.MemoryView":1040 + /* "View.MemoryView":1041 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -14342,7 +14368,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview return __pyx_r; } -/* "View.MemoryView":1062 +/* "View.MemoryView":1063 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -14354,7 +14380,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { Py_ssize_t __pyx_r; int __pyx_t_1; - /* "View.MemoryView":1063 + /* "View.MemoryView":1064 * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: # <<<<<<<<<<<<<< @@ -14364,7 +14390,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { __pyx_t_1 = ((__pyx_v_arg < 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1064 + /* "View.MemoryView":1065 * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: * return -arg # <<<<<<<<<<<<<< @@ -14376,7 +14402,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { } /*else*/ { - /* "View.MemoryView":1066 + /* "View.MemoryView":1067 * return -arg * else: * return arg # <<<<<<<<<<<<<< @@ -14387,7 +14413,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { goto __pyx_L0; } - /* "View.MemoryView":1062 + /* "View.MemoryView":1063 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -14400,7 +14426,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { return __pyx_r; } -/* "View.MemoryView":1069 +/* "View.MemoryView":1070 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -14417,7 +14443,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1074 + /* "View.MemoryView":1075 * """ * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< @@ -14426,7 +14452,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_c_stride = 0; - /* "View.MemoryView":1075 + /* "View.MemoryView":1076 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< @@ -14435,7 +14461,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_f_stride = 0; - /* "View.MemoryView":1077 + /* "View.MemoryView":1078 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -14445,7 +14471,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":1078 + /* "View.MemoryView":1079 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -14455,7 +14481,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1079 + /* "View.MemoryView":1080 * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -14464,7 +14490,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1080 + /* "View.MemoryView":1081 * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -14476,7 +14502,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } __pyx_L4_break:; - /* "View.MemoryView":1082 + /* "View.MemoryView":1083 * break * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -14487,7 +14513,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1083 + /* "View.MemoryView":1084 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -14497,7 +14523,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1084 + /* "View.MemoryView":1085 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -14506,7 +14532,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1085 + /* "View.MemoryView":1086 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -14518,7 +14544,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } __pyx_L7_break:; - /* "View.MemoryView":1087 + /* "View.MemoryView":1088 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< @@ -14528,7 +14554,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1088 + /* "View.MemoryView":1089 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< @@ -14540,7 +14566,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } /*else*/ { - /* "View.MemoryView":1090 + /* "View.MemoryView":1091 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< @@ -14551,7 +14577,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ goto __pyx_L0; } - /* "View.MemoryView":1069 + /* "View.MemoryView":1070 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -14564,7 +14590,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ return __pyx_r; } -/* "View.MemoryView":1093 +/* "View.MemoryView":1094 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -14584,7 +14610,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v Py_ssize_t __pyx_t_4; Py_ssize_t __pyx_t_5; - /* "View.MemoryView":1100 + /* "View.MemoryView":1101 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< @@ -14593,7 +14619,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_extent = (__pyx_v_src_shape[0]); - /* "View.MemoryView":1101 + /* "View.MemoryView":1102 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< @@ -14602,7 +14628,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); - /* "View.MemoryView":1102 + /* "View.MemoryView":1103 * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< @@ -14611,7 +14637,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_stride = (__pyx_v_src_strides[0]); - /* "View.MemoryView":1103 + /* "View.MemoryView":1104 * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< @@ -14620,7 +14646,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); - /* "View.MemoryView":1105 + /* "View.MemoryView":1106 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -14630,7 +14656,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1106 + /* "View.MemoryView":1107 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -14639,22 +14665,18 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); if (__pyx_t_2) { - goto __pyx_L6_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } - __pyx_L6_next_and:; __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); if (__pyx_t_2) { - goto __pyx_L7_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } - __pyx_L7_next_and:; - /* "View.MemoryView":1107 + /* "View.MemoryView":1108 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< @@ -14670,7 +14692,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v __pyx_L5_bool_binop_done:; if (__pyx_t_1) { - /* "View.MemoryView":1108 + /* "View.MemoryView":1109 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< @@ -14682,7 +14704,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } /*else*/ { - /* "View.MemoryView":1110 + /* "View.MemoryView":1111 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< @@ -14693,7 +14715,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":1111 + /* "View.MemoryView":1112 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< @@ -14702,7 +14724,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize); - /* "View.MemoryView":1112 + /* "View.MemoryView":1113 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -14711,7 +14733,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - /* "View.MemoryView":1113 + /* "View.MemoryView":1114 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -14726,7 +14748,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } /*else*/ { - /* "View.MemoryView":1115 + /* "View.MemoryView":1116 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< @@ -14737,7 +14759,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":1116 + /* "View.MemoryView":1117 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< @@ -14746,7 +14768,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); - /* "View.MemoryView":1120 + /* "View.MemoryView":1121 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -14755,7 +14777,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - /* "View.MemoryView":1121 + /* "View.MemoryView":1122 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -14767,7 +14789,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } __pyx_L3:; - /* "View.MemoryView":1093 + /* "View.MemoryView":1094 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -14778,7 +14800,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v /* function exit code */ } -/* "View.MemoryView":1123 +/* "View.MemoryView":1124 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -14788,7 +14810,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { - /* "View.MemoryView":1126 + /* "View.MemoryView":1127 * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< @@ -14797,7 +14819,7 @@ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memvi */ _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); - /* "View.MemoryView":1123 + /* "View.MemoryView":1124 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -14808,7 +14830,7 @@ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memvi /* function exit code */ } -/* "View.MemoryView":1130 +/* "View.MemoryView":1131 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< @@ -14824,7 +14846,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1133 + /* "View.MemoryView":1134 * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -14834,7 +14856,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_size = __pyx_t_1; - /* "View.MemoryView":1135 + /* "View.MemoryView":1136 * cdef Py_ssize_t size = src.memview.view.itemsize * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -14845,7 +14867,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1136 + /* "View.MemoryView":1137 * * for i in range(ndim): * size *= src.shape[i] # <<<<<<<<<<<<<< @@ -14855,7 +14877,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); } - /* "View.MemoryView":1138 + /* "View.MemoryView":1139 * size *= src.shape[i] * * return size # <<<<<<<<<<<<<< @@ -14865,7 +14887,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_r = __pyx_v_size; goto __pyx_L0; - /* "View.MemoryView":1130 + /* "View.MemoryView":1131 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< @@ -14878,7 +14900,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr return __pyx_r; } -/* "View.MemoryView":1141 +/* "View.MemoryView":1142 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -14893,7 +14915,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1150 + /* "View.MemoryView":1151 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< @@ -14903,7 +14925,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ __pyx_t_1 = ((__pyx_v_order == 'F') != 0); if (__pyx_t_1) { - /* "View.MemoryView":1151 + /* "View.MemoryView":1152 * * if order == 'F': * for idx in range(ndim): # <<<<<<<<<<<<<< @@ -14914,7 +14936,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_idx = __pyx_t_3; - /* "View.MemoryView":1152 + /* "View.MemoryView":1153 * if order == 'F': * for idx in range(ndim): * strides[idx] = stride # <<<<<<<<<<<<<< @@ -14923,7 +14945,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1153 + /* "View.MemoryView":1154 * for idx in range(ndim): * strides[idx] = stride * stride = stride * shape[idx] # <<<<<<<<<<<<<< @@ -14936,7 +14958,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ } /*else*/ { - /* "View.MemoryView":1155 + /* "View.MemoryView":1156 * stride = stride * shape[idx] * else: * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -14946,7 +14968,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { __pyx_v_idx = __pyx_t_2; - /* "View.MemoryView":1156 + /* "View.MemoryView":1157 * else: * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride # <<<<<<<<<<<<<< @@ -14955,7 +14977,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1157 + /* "View.MemoryView":1158 * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride * stride = stride * shape[idx] # <<<<<<<<<<<<<< @@ -14967,7 +14989,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ } __pyx_L3:; - /* "View.MemoryView":1159 + /* "View.MemoryView":1160 * stride = stride * shape[idx] * * return stride # <<<<<<<<<<<<<< @@ -14977,7 +14999,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ __pyx_r = __pyx_v_stride; goto __pyx_L0; - /* "View.MemoryView":1141 + /* "View.MemoryView":1142 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -14990,7 +15012,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ return __pyx_r; } -/* "View.MemoryView":1162 +/* "View.MemoryView":1163 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -15013,7 +15035,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "View.MemoryView":1173 + /* "View.MemoryView":1174 * cdef void *result * * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -15023,7 +15045,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_itemsize = __pyx_t_1; - /* "View.MemoryView":1174 + /* "View.MemoryView":1175 * * cdef size_t itemsize = src.memview.view.itemsize * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< @@ -15032,7 +15054,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); - /* "View.MemoryView":1176 + /* "View.MemoryView":1177 * cdef size_t size = slice_get_size(src, ndim) * * result = malloc(size) # <<<<<<<<<<<<<< @@ -15041,7 +15063,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_result = malloc(__pyx_v_size); - /* "View.MemoryView":1177 + /* "View.MemoryView":1178 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< @@ -15051,19 +15073,19 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1178 + /* "View.MemoryView":1179 * result = malloc(size) * if not result: * _err(MemoryError, NULL) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L3; } __pyx_L3:; - /* "View.MemoryView":1181 + /* "View.MemoryView":1182 * * * tmpslice.data = result # <<<<<<<<<<<<<< @@ -15072,7 +15094,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_tmpslice->data = ((char *)__pyx_v_result); - /* "View.MemoryView":1182 + /* "View.MemoryView":1183 * * tmpslice.data = result * tmpslice.memview = src.memview # <<<<<<<<<<<<<< @@ -15082,7 +15104,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_4 = __pyx_v_src->memview; __pyx_v_tmpslice->memview = __pyx_t_4; - /* "View.MemoryView":1183 + /* "View.MemoryView":1184 * tmpslice.data = result * tmpslice.memview = src.memview * for i in range(ndim): # <<<<<<<<<<<<<< @@ -15093,7 +15115,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_3; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":1184 + /* "View.MemoryView":1185 * tmpslice.memview = src.memview * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< @@ -15102,7 +15124,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]); - /* "View.MemoryView":1185 + /* "View.MemoryView":1186 * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] * 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_t_5); __Pyx_GIVEREF(__pyx_t_5); __pyx_t_5 = NULL; PyTuple_SET_ITEM(__pyx_t_6, 0+1, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_2 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1217; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; } __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_Raise(__pyx_t_2, 0, 0, 0); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1217; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } /*else*/ { - /* "View.MemoryView":1219 + /* "View.MemoryView":1220 * raise error(msg.decode('ascii')) * else: * raise error # <<<<<<<<<<<<<< @@ -15497,10 +15519,10 @@ static int __pyx_memoryview_err(PyObject *__pyx_v_error, char *__pyx_v_msg) { * @cname('__pyx_memoryview_copy_contents') */ __Pyx_Raise(__pyx_v_error, 0, 0, 0); - {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1220; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "View.MemoryView":1215 + /* "View.MemoryView":1216 * * @cname('__pyx_memoryview_err') * cdef int _err(object error, char *msg) except -1 with gil: # <<<<<<<<<<<<<< @@ -15525,7 +15547,7 @@ static int __pyx_memoryview_err(PyObject *__pyx_v_error, char *__pyx_v_msg) { return __pyx_r; } -/* "View.MemoryView":1222 +/* "View.MemoryView":1223 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< @@ -15554,7 +15576,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "View.MemoryView":1230 + /* "View.MemoryView":1231 * Check for overlapping memory and verify the shapes. * """ * cdef void *tmpdata = NULL # <<<<<<<<<<<<<< @@ -15563,7 +15585,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_tmpdata = NULL; - /* "View.MemoryView":1231 + /* "View.MemoryView":1232 * """ * cdef void *tmpdata = NULL * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -15573,7 +15595,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_1 = __pyx_v_src.memview->view.itemsize; __pyx_v_itemsize = __pyx_t_1; - /* "View.MemoryView":1233 + /* "View.MemoryView":1234 * cdef size_t itemsize = src.memview.view.itemsize * cdef int i * cdef char order = get_best_order(&src, src_ndim) # <<<<<<<<<<<<<< @@ -15582,7 +15604,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_src), __pyx_v_src_ndim); - /* "View.MemoryView":1234 + /* "View.MemoryView":1235 * cdef int i * cdef char order = get_best_order(&src, src_ndim) * cdef bint broadcasting = False # <<<<<<<<<<<<<< @@ -15591,7 +15613,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_broadcasting = 0; - /* "View.MemoryView":1235 + /* "View.MemoryView":1236 * cdef char order = get_best_order(&src, src_ndim) * cdef bint broadcasting = False * cdef bint direct_copy = False # <<<<<<<<<<<<<< @@ -15600,7 +15622,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_direct_copy = 0; - /* "View.MemoryView":1238 + /* "View.MemoryView":1239 * cdef __Pyx_memviewslice tmp * * if src_ndim < dst_ndim: # <<<<<<<<<<<<<< @@ -15610,7 +15632,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((__pyx_v_src_ndim < __pyx_v_dst_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1239 + /* "View.MemoryView":1240 * * if src_ndim < dst_ndim: * broadcast_leading(&src, src_ndim, dst_ndim) # <<<<<<<<<<<<<< @@ -15621,7 +15643,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ goto __pyx_L3; } - /* "View.MemoryView":1240 + /* "View.MemoryView":1241 * if src_ndim < dst_ndim: * broadcast_leading(&src, src_ndim, dst_ndim) * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< @@ -15631,7 +15653,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((__pyx_v_dst_ndim < __pyx_v_src_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1241 + /* "View.MemoryView":1242 * broadcast_leading(&src, src_ndim, dst_ndim) * elif dst_ndim < src_ndim: * broadcast_leading(&dst, dst_ndim, src_ndim) # <<<<<<<<<<<<<< @@ -15643,7 +15665,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L3:; - /* "View.MemoryView":1243 + /* "View.MemoryView":1244 * broadcast_leading(&dst, dst_ndim, src_ndim) * * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< @@ -15659,7 +15681,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_v_ndim = __pyx_t_5; - /* "View.MemoryView":1245 + /* "View.MemoryView":1246 * cdef int ndim = max(src_ndim, dst_ndim) * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -15670,7 +15692,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_5; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1246 + /* "View.MemoryView":1247 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< @@ -15680,7 +15702,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1247 + /* "View.MemoryView":1248 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< @@ -15690,7 +15712,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1248 + /* "View.MemoryView":1249 * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: * broadcasting = True # <<<<<<<<<<<<<< @@ -15699,7 +15721,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_broadcasting = 1; - /* "View.MemoryView":1249 + /* "View.MemoryView":1250 * if src.shape[i] == 1: * broadcasting = True * src.strides[i] = 0 # <<<<<<<<<<<<<< @@ -15711,21 +15733,21 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } /*else*/ { - /* "View.MemoryView":1251 + /* "View.MemoryView":1252 * src.strides[i] = 0 * else: * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< * * if src.suboffsets[i] >= 0: */ - __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1251; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1252; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_L7:; goto __pyx_L6; } __pyx_L6:; - /* "View.MemoryView":1253 + /* "View.MemoryView":1254 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< @@ -15735,20 +15757,20 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1254 + /* "View.MemoryView":1255 * * if src.suboffsets[i] >= 0: * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< * * if slices_overlap(&src, &dst, ndim, itemsize): */ - __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Dimension_d_is_not_direct, __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1254; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Dimension_d_is_not_direct, __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1255; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L8; } __pyx_L8:; } - /* "View.MemoryView":1256 + /* "View.MemoryView":1257 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< @@ -15758,7 +15780,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1258 + /* "View.MemoryView":1259 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(&src, order, ndim): # <<<<<<<<<<<<<< @@ -15768,7 +15790,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((!(__pyx_memviewslice_is_contig((&__pyx_v_src), __pyx_v_order, __pyx_v_ndim) != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1259 + /* "View.MemoryView":1260 * * if not slice_is_contig(&src, order, ndim): * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< @@ -15780,17 +15802,17 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L10:; - /* "View.MemoryView":1261 + /* "View.MemoryView":1262 * order = get_best_order(&dst, ndim) * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< * src = tmp * */ - __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1261; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1262; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_tmpdata = __pyx_t_6; - /* "View.MemoryView":1262 + /* "View.MemoryView":1263 * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) * src = tmp # <<<<<<<<<<<<<< @@ -15802,7 +15824,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L9:; - /* "View.MemoryView":1264 + /* "View.MemoryView":1265 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< @@ -15812,7 +15834,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1267 + /* "View.MemoryView":1268 * * * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<< @@ -15822,7 +15844,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1268 + /* "View.MemoryView":1269 * * if slice_is_contig(&src, 'C', ndim): * direct_copy = slice_is_contig(&dst, 'C', ndim) # <<<<<<<<<<<<<< @@ -15833,7 +15855,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ goto __pyx_L12; } - /* "View.MemoryView":1269 + /* "View.MemoryView":1270 * if slice_is_contig(&src, 'C', ndim): * direct_copy = slice_is_contig(&dst, 'C', ndim) * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<< @@ -15843,7 +15865,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1270 + /* "View.MemoryView":1271 * direct_copy = slice_is_contig(&dst, 'C', ndim) * elif slice_is_contig(&src, 'F', ndim): * direct_copy = slice_is_contig(&dst, 'F', ndim) # <<<<<<<<<<<<<< @@ -15855,7 +15877,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L12:; - /* "View.MemoryView":1272 + /* "View.MemoryView":1273 * direct_copy = slice_is_contig(&dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< @@ -15865,7 +15887,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_2 = (__pyx_v_direct_copy != 0); if (__pyx_t_2) { - /* "View.MemoryView":1274 + /* "View.MemoryView":1275 * if direct_copy: * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -15874,7 +15896,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - /* "View.MemoryView":1275 + /* "View.MemoryView":1276 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< @@ -15883,7 +15905,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); - /* "View.MemoryView":1276 + /* "View.MemoryView":1277 * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -15892,7 +15914,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - /* "View.MemoryView":1277 + /* "View.MemoryView":1278 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< @@ -15901,7 +15923,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1278 + /* "View.MemoryView":1279 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -15915,7 +15937,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L11:; - /* "View.MemoryView":1280 + /* "View.MemoryView":1281 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< @@ -15929,28 +15951,28 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_7 = (__pyx_t_2 != 0); if (__pyx_t_7) { - /* "View.MemoryView":1283 + /* "View.MemoryView":1284 * * * transpose_memslice(&src) # <<<<<<<<<<<<<< * transpose_memslice(&dst) * */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - /* "View.MemoryView":1284 + /* "View.MemoryView":1285 * * transpose_memslice(&src) * transpose_memslice(&dst) # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1285; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L14; } __pyx_L14:; - /* "View.MemoryView":1286 + /* "View.MemoryView":1287 * transpose_memslice(&dst) * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -15959,7 +15981,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - /* "View.MemoryView":1287 + /* "View.MemoryView":1288 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< @@ -15968,7 +15990,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); - /* "View.MemoryView":1288 + /* "View.MemoryView":1289 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -15977,7 +15999,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - /* "View.MemoryView":1290 + /* "View.MemoryView":1291 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< @@ -15986,7 +16008,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1291 + /* "View.MemoryView":1292 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -15996,7 +16018,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":1222 + /* "View.MemoryView":1223 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< @@ -16020,21 +16042,21 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ return __pyx_r; } -/* "View.MemoryView":1294 +/* "View.MemoryView":1295 * * @cname('__pyx_memoryview_broadcast_leading') - * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<< + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ -static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice, int __pyx_v_ndim, int __pyx_v_ndim_other) { +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { int __pyx_v_i; int __pyx_v_offset; int __pyx_t_1; int __pyx_t_2; - /* "View.MemoryView":1298 + /* "View.MemoryView":1299 * int ndim_other) nogil: * cdef int i * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< @@ -16043,87 +16065,87 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice */ __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); - /* "View.MemoryView":1300 + /* "View.MemoryView":1301 * cdef int offset = ndim_other - ndim * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< - * slice.shape[i + offset] = slice.shape[i] - * slice.strides[i + offset] = slice.strides[i] + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] */ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":1301 - * - * for i in range(ndim - 1, -1, -1): - * slice.shape[i + offset] = slice.shape[i] # <<<<<<<<<<<<<< - * slice.strides[i + offset] = slice.strides[i] - * slice.suboffsets[i + offset] = slice.suboffsets[i] - */ - (__pyx_v_slice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->shape[__pyx_v_i]); - /* "View.MemoryView":1302 - * for i in range(ndim - 1, -1, -1): - * slice.shape[i + offset] = slice.shape[i] - * slice.strides[i + offset] = slice.strides[i] # <<<<<<<<<<<<<< - * slice.suboffsets[i + offset] = slice.suboffsets[i] * + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] */ - (__pyx_v_slice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->strides[__pyx_v_i]); + (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); /* "View.MemoryView":1303 - * slice.shape[i + offset] = slice.shape[i] - * slice.strides[i + offset] = slice.strides[i] - * slice.suboffsets[i + offset] = slice.suboffsets[i] # <<<<<<<<<<<<<< + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + */ + (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1304 + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< * * for i in range(offset): */ - (__pyx_v_slice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->suboffsets[__pyx_v_i]); + (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); } - /* "View.MemoryView":1305 - * slice.suboffsets[i + offset] = slice.suboffsets[i] + /* "View.MemoryView":1306 + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * * for i in range(offset): # <<<<<<<<<<<<<< - * slice.shape[i] = 1 - * slice.strides[i] = slice.strides[0] + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] */ __pyx_t_1 = __pyx_v_offset; for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { __pyx_v_i = __pyx_t_2; - /* "View.MemoryView":1306 - * - * for i in range(offset): - * slice.shape[i] = 1 # <<<<<<<<<<<<<< - * slice.strides[i] = slice.strides[0] - * slice.suboffsets[i] = -1 - */ - (__pyx_v_slice->shape[__pyx_v_i]) = 1; - /* "View.MemoryView":1307 - * for i in range(offset): - * slice.shape[i] = 1 - * slice.strides[i] = slice.strides[0] # <<<<<<<<<<<<<< - * slice.suboffsets[i] = -1 * + * for i in range(offset): + * mslice.shape[i] = 1 # <<<<<<<<<<<<<< + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 */ - (__pyx_v_slice->strides[__pyx_v_i]) = (__pyx_v_slice->strides[0]); + (__pyx_v_mslice->shape[__pyx_v_i]) = 1; /* "View.MemoryView":1308 - * slice.shape[i] = 1 - * slice.strides[i] = slice.strides[0] - * slice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * for i in range(offset): + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< + * mslice.suboffsets[i] = -1 + * + */ + (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); + + /* "View.MemoryView":1309 + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< * * */ - (__pyx_v_slice->suboffsets[__pyx_v_i]) = -1; + (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1; } - /* "View.MemoryView":1294 + /* "View.MemoryView":1295 * * @cname('__pyx_memoryview_broadcast_leading') - * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<< + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ @@ -16131,7 +16153,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice /* function exit code */ } -/* "View.MemoryView":1316 +/* "View.MemoryView":1317 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -16142,7 +16164,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) { int __pyx_t_1; - /* "View.MemoryView":1320 + /* "View.MemoryView":1321 * * * if dtype_is_object: # <<<<<<<<<<<<<< @@ -16152,7 +16174,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i __pyx_t_1 = (__pyx_v_dtype_is_object != 0); if (__pyx_t_1) { - /* "View.MemoryView":1321 + /* "View.MemoryView":1322 * * if dtype_is_object: * refcount_objects_in_slice_with_gil(dst.data, dst.shape, # <<<<<<<<<<<<<< @@ -16164,7 +16186,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i } __pyx_L3:; - /* "View.MemoryView":1316 + /* "View.MemoryView":1317 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -16175,7 +16197,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i /* function exit code */ } -/* "View.MemoryView":1325 +/* "View.MemoryView":1326 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -16190,7 +16212,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da #endif __Pyx_RefNannySetupContext("refcount_objects_in_slice_with_gil", 0); - /* "View.MemoryView":1328 + /* "View.MemoryView":1329 * Py_ssize_t *strides, int ndim, * bint inc) with gil: * refcount_objects_in_slice(data, shape, strides, ndim, inc) # <<<<<<<<<<<<<< @@ -16199,7 +16221,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da */ __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, __pyx_v_shape, __pyx_v_strides, __pyx_v_ndim, __pyx_v_inc); - /* "View.MemoryView":1325 + /* "View.MemoryView":1326 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -16214,7 +16236,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da #endif } -/* "View.MemoryView":1331 +/* "View.MemoryView":1332 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -16230,7 +16252,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss int __pyx_t_3; __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0); - /* "View.MemoryView":1335 + /* "View.MemoryView":1336 * cdef Py_ssize_t i * * for i in range(shape[0]): # <<<<<<<<<<<<<< @@ -16241,7 +16263,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { __pyx_v_i = __pyx_t_2; - /* "View.MemoryView":1336 + /* "View.MemoryView":1337 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< @@ -16251,7 +16273,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_3 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_3) { - /* "View.MemoryView":1337 + /* "View.MemoryView":1338 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< @@ -16261,7 +16283,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_3 = (__pyx_v_inc != 0); if (__pyx_t_3) { - /* "View.MemoryView":1338 + /* "View.MemoryView":1339 * if ndim == 1: * if inc: * Py_INCREF(( data)[0]) # <<<<<<<<<<<<<< @@ -16273,7 +16295,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } /*else*/ { - /* "View.MemoryView":1340 + /* "View.MemoryView":1341 * Py_INCREF(( data)[0]) * else: * Py_DECREF(( data)[0]) # <<<<<<<<<<<<<< @@ -16287,7 +16309,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } /*else*/ { - /* "View.MemoryView":1342 + /* "View.MemoryView":1343 * Py_DECREF(( data)[0]) * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -16298,7 +16320,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } __pyx_L5:; - /* "View.MemoryView":1345 + /* "View.MemoryView":1346 * ndim - 1, inc) * * data += strides[0] # <<<<<<<<<<<<<< @@ -16308,7 +16330,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_v_data = (__pyx_v_data + (__pyx_v_strides[0])); } - /* "View.MemoryView":1331 + /* "View.MemoryView":1332 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -16320,7 +16342,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1351 +/* "View.MemoryView":1352 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -16330,7 +16352,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) { - /* "View.MemoryView":1354 + /* "View.MemoryView":1355 * size_t itemsize, void *item, * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -16339,7 +16361,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - /* "View.MemoryView":1355 + /* "View.MemoryView":1356 * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<< @@ -16348,7 +16370,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst */ __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item); - /* "View.MemoryView":1357 + /* "View.MemoryView":1358 * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -16357,7 +16379,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - /* "View.MemoryView":1351 + /* "View.MemoryView":1352 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -16368,7 +16390,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst /* function exit code */ } -/* "View.MemoryView":1361 +/* "View.MemoryView":1362 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -16384,7 +16406,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t Py_ssize_t __pyx_t_2; Py_ssize_t __pyx_t_3; - /* "View.MemoryView":1365 + /* "View.MemoryView":1366 * size_t itemsize, void *item) nogil: * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< @@ -16393,7 +16415,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_stride = (__pyx_v_strides[0]); - /* "View.MemoryView":1366 + /* "View.MemoryView":1367 * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< @@ -16402,7 +16424,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_extent = (__pyx_v_shape[0]); - /* "View.MemoryView":1368 + /* "View.MemoryView":1369 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -16412,7 +16434,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1369 + /* "View.MemoryView":1370 * * if ndim == 1: * for i in range(extent): # <<<<<<<<<<<<<< @@ -16423,7 +16445,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1370 + /* "View.MemoryView":1371 * if ndim == 1: * for i in range(extent): * memcpy(data, item, itemsize) # <<<<<<<<<<<<<< @@ -16432,7 +16454,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize); - /* "View.MemoryView":1371 + /* "View.MemoryView":1372 * for i in range(extent): * memcpy(data, item, itemsize) * data += stride # <<<<<<<<<<<<<< @@ -16445,7 +16467,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t } /*else*/ { - /* "View.MemoryView":1373 + /* "View.MemoryView":1374 * data += stride * else: * for i in range(extent): # <<<<<<<<<<<<<< @@ -16456,7 +16478,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1374 + /* "View.MemoryView":1375 * else: * for i in range(extent): * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -16465,7 +16487,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item); - /* "View.MemoryView":1376 + /* "View.MemoryView":1377 * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) * data += stride # <<<<<<<<<<<<<< @@ -16477,7 +16499,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t } __pyx_L3:; - /* "View.MemoryView":1361 + /* "View.MemoryView":1362 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void 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{&__pyx_n_s_c, __pyx_k_c, sizeof(__pyx_k_c), 0, 0, 1, 1}, {&__pyx_n_u_c, __pyx_k_c, sizeof(__pyx_k_c), 0, 1, 0, 1}, {&__pyx_n_s_class, __pyx_k_class, sizeof(__pyx_k_class), 0, 0, 1, 1}, {&__pyx_kp_s_contiguous_and_direct, __pyx_k_contiguous_and_direct, sizeof(__pyx_k_contiguous_and_direct), 0, 0, 1, 0}, {&__pyx_kp_s_contiguous_and_indirect, __pyx_k_contiguous_and_indirect, sizeof(__pyx_k_contiguous_and_indirect), 0, 0, 1, 0}, - {&__pyx_n_s_copy, __pyx_k_copy, sizeof(__pyx_k_copy), 0, 0, 1, 1}, {&__pyx_n_s_count, __pyx_k_count, sizeof(__pyx_k_count), 0, 0, 1, 1}, {&__pyx_n_s_d, __pyx_k_d, sizeof(__pyx_k_d), 0, 0, 1, 1}, {&__pyx_n_s_dL, __pyx_k_dL, sizeof(__pyx_k_dL), 0, 0, 1, 1}, @@ -17266,20 +17289,20 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {0, 0, 0, 0, 0, 0, 0} }; static int __Pyx_InitCachedBuiltins(void) { - __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 23; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_RuntimeError = __Pyx_GetBuiltinName(__pyx_n_s_RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #if PY_MAJOR_VERSION >= 3 + __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 99; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #else + __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 99; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif + __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_RuntimeError = __Pyx_GetBuiltinName(__pyx_n_s_RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 802; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_MemoryError = __Pyx_GetBuiltinName(__pyx_n_s_MemoryError); if (!__pyx_builtin_MemoryError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_Ellipsis = __Pyx_GetBuiltinName(__pyx_n_s_Ellipsis); if (!__pyx_builtin_Ellipsis) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 357; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_TypeError = __Pyx_GetBuiltinName(__pyx_n_s_TypeError); if (!__pyx_builtin_TypeError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - #if PY_MAJOR_VERSION >= 3 - __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - #else - __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - #endif __pyx_builtin_id = __Pyx_GetBuiltinName(__pyx_n_s_id); if (!__pyx_builtin_id) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 569; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_IndexError = __Pyx_GetBuiltinName(__pyx_n_s_IndexError); if (!__pyx_builtin_IndexError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_IndexError = __Pyx_GetBuiltinName(__pyx_n_s_IndexError); if (!__pyx_builtin_IndexError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 788; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; __pyx_L1_error:; return -1; @@ -17289,69 +17312,69 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__Pyx_InitCachedConstants", 0); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) */ - __pyx_tuple_ = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_C_contiguous); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple_ = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_C_contiguous); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple_); __Pyx_GIVEREF(__pyx_tuple_); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< * * info.buf = PyArray_DATA(self) */ - __pyx_tuple__2 = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_Fortran_contiguou); if (unlikely(!__pyx_tuple__2)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__2 = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_Fortran_contiguou); if (unlikely(!__pyx_tuple__2)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__2); __Pyx_GIVEREF(__pyx_tuple__2); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_u_Non_native_byte_order_not_suppor); if (unlikely(!__pyx_tuple__3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_u_Non_native_byte_order_not_suppor); if (unlikely(!__pyx_tuple__3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__3); __Pyx_GIVEREF(__pyx_tuple__3); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< * * if ((child.byteorder == c'>' and little_endian) or */ - __pyx_tuple__4 = PyTuple_Pack(1, __pyx_kp_u_Format_string_allocated_too_shor); if (unlikely(!__pyx_tuple__4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__4 = PyTuple_Pack(1, __pyx_kp_u_Format_string_allocated_too_shor); if (unlikely(!__pyx_tuple__4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno 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__Pyx_InitCachedConstants(void) { * * raise ValueError("Buffer view does not expose strides") # <<<<<<<<<<<<<< * - * return tuple([self.view.strides[i] for i in xrange(self.view.ndim)]) + * return tuple([stride for stride in self.view.strides[:self.view.ndim]]) */ __pyx_tuple__13 = PyTuple_Pack(1, __pyx_kp_s_Buffer_view_does_not_expose_stri); if (unlikely(!__pyx_tuple__13)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 521; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__13); __Pyx_GIVEREF(__pyx_tuple__13); + /* "View.MemoryView":529 + * def __get__(self): + * if self.view.suboffsets == NULL: + * return (-1,) * self.view.ndim # <<<<<<<<<<<<<< + * + * return tuple([suboffset for suboffset in self.view.suboffsets[:self.view.ndim]]) + */ + __pyx_tuple__14 = PyTuple_New(1); if (unlikely(!__pyx_tuple__14)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 529; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__14); + __Pyx_INCREF(__pyx_int_neg_1); + PyTuple_SET_ITEM(__pyx_tuple__14, 0, __pyx_int_neg_1); + __Pyx_GIVEREF(__pyx_int_neg_1); + __Pyx_GIVEREF(__pyx_tuple__14); + /* "View.MemoryView":638 * if item is Ellipsis: * if not seen_ellipsis: @@ -17439,9 +17476,9 @@ static int __Pyx_InitCachedConstants(void) { * seen_ellipsis = True * else: */ - __pyx_slice__14 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_slice__14)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 638; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_slice__14); - __Pyx_GIVEREF(__pyx_slice__14); + __pyx_slice__15 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_slice__15)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 638; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_slice__15); + __Pyx_GIVEREF(__pyx_slice__15); /* "View.MemoryView":641 * seen_ellipsis = True @@ -17450,9 +17487,9 @@ static int __Pyx_InitCachedConstants(void) { * have_slices = True * else: */ - 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__pyx_lineno = 108; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__27); + __Pyx_GIVEREF(__pyx_tuple__27); + __pyx_codeobj__28 = (PyObject*)__Pyx_PyCode_New(2, 0, 5, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__27, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_util_ch, __pyx_n_s_backprop_gradient_par_c, 108, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__28)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 108; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /* "View.MemoryView":276 * return self.name @@ -17555,9 +17580,9 @@ static int __Pyx_InitCachedConstants(void) { * cdef strided = Enum("") # default * cdef indirect = Enum("") */ - __pyx_tuple__30 = PyTuple_Pack(1, __pyx_kp_s_strided_and_direct_or_indirect); if (unlikely(!__pyx_tuple__30)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_tuple__30); - 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__pyx_f[2]; __pyx_lineno = 921; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_type___pyx_memoryviewslice.tp_print = 0; - if (__Pyx_SetVtable(__pyx_type___pyx_memoryviewslice.tp_dict, __pyx_vtabptr__memoryviewslice) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 922; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_SetVtable(__pyx_type___pyx_memoryviewslice.tp_dict, __pyx_vtabptr__memoryviewslice) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 921; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_memoryviewslice_type = &__pyx_type___pyx_memoryviewslice; /*--- Type import code ---*/ __pyx_ptype_7cpython_4type_type = __Pyx_ImportType(__Pyx_BUILTIN_MODULE_NAME, "type", @@ -17747,12 +17773,17 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) #endif 0); if (unlikely(!__pyx_ptype_7cpython_4type_type)) {__pyx_filename = __pyx_f[3]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", 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__Pyx_RaiseArgumentTypeInvalid(name, obj, type); - return 0; + return result; } +#endif + +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + 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PyThreadState_GET(); - tmp_type = tstate->curexc_type; - tmp_value = tstate->curexc_value; - tmp_tb = tstate->curexc_traceback; - tstate->curexc_type = type; - tstate->curexc_value = value; - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_Restore(type, value, tb); -#endif -} -static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) { -#if CYTHON_COMPILING_IN_CPYTHON - PyThreadState *tstate = PyThreadState_GET(); - *type = tstate->curexc_type; - *value = tstate->curexc_value; - *tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(type, value, tb); -#endif -} - -static CYTHON_INLINE long __Pyx_div_long(long a, long b) { - long q = a / b; - long r = a - q*b; - q -= ((r != 0) & ((r ^ b) < 0)); - return q; -} - -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { -#ifdef __Pyx_CyFunction_USED - if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) { -#else - if (likely(PyCFunction_Check(func))) { -#endif - if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { - return __Pyx_PyObject_CallMethO(func, NULL); - } - } - return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); -} -#endif - static int __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int ndim, @@ -19018,6 +18946,71 @@ static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, } } +static CYTHON_INLINE long __Pyx_div_long(long a, long b) { + long q = a / b; + long r = a - q*b; + q -= ((r != 0) & ((r ^ b) < 0)); + return q; +} + +static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_Restore(type, value, tb); +#endif +} +static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyThreadState *tstate = PyThreadState_GET(); + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(type, value, tb); +#endif +} + +static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +} + #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, CYTHON_UNUSED PyObject *cause) { @@ -19153,6 +19146,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject } PyErr_SetObject(type, value); if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(tmp_type, tmp_value, tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { @@ -19160,6 +19160,7 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } +#endif } bad: Py_XDECREF(owned_instance); @@ -19182,6 +19183,44 @@ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); } +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(PyObject_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) { + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); +} +static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, + const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (none_allowed && obj == Py_None) return 1; + else if (exact) { + if (likely(Py_TYPE(obj) == type)) return 1; + #if PY_MAJOR_VERSION == 2 + else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(PyObject_TypeCheck(obj, type))) return 1; + } + __Pyx_RaiseArgumentTypeInvalid(name, obj, type); + return 0; +} + static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); @@ -19536,33 +19575,6 @@ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); } -static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, - CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, - int full_traceback) { - PyObject *old_exc, *old_val, *old_tb; - PyObject *ctx; - __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); - if (full_traceback) { - Py_XINCREF(old_exc); - Py_XINCREF(old_val); - Py_XINCREF(old_tb); - __Pyx_ErrRestore(old_exc, old_val, old_tb); - PyErr_PrintEx(1); - } - #if PY_MAJOR_VERSION < 3 - ctx = PyString_FromString(name); - #else - ctx = PyUnicode_FromString(name); - #endif - __Pyx_ErrRestore(old_exc, old_val, old_tb); - if (!ctx) { - PyErr_WriteUnraisable(Py_None); - } else { - PyErr_WriteUnraisable(ctx); - Py_DECREF(ctx); - } -} - static int __Pyx_SetVtable(PyObject *dict, void *vtable) { #if PY_VERSION_HEX >= 0x02070000 PyObject *ob = PyCapsule_New(vtable, 0, 0); @@ -19762,7 +19774,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { PyObject *empty_list = 0; PyObject *module = 0; PyObject *global_dict = 0; @@ -19835,122 +19847,6 @@ bad: return module; } -#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \ - { \ - func_type value = func_value; \ - if (sizeof(target_type) < sizeof(func_type)) { \ - if (unlikely(value != (func_type) (target_type) value)) { \ - func_type zero = 0; \ - if (is_unsigned && unlikely(value < zero)) \ - goto raise_neg_overflow; \ - else \ - goto raise_overflow; \ - } \ - } \ - return (target_type) value; \ - } - -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - #include "longintrepr.h" - #endif -#endif - -static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { - const int neg_one = (int) -1, const_zero = 0; - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(int) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (int) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]); - } - #endif -#endif - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } - if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(int) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x)) - } - } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); - } - #endif -#endif - if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x)) - } else if (sizeof(int) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x)) - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - int val; - PyObject *v = __Pyx_PyNumber_Int(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (int) -1; - } - } else { - int val; - PyObject *tmp = __Pyx_PyNumber_Int(x); - if (!tmp) return (int) -1; - val = __Pyx_PyInt_As_int(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to int"); - return (int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to int"); - return (int) -1; -} - static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) { @@ -20194,6 +20090,144 @@ __pyx_fail: return result; } +#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \ + { \ + func_type value = func_value; \ + if (sizeof(target_type) < sizeof(func_type)) { \ + if (unlikely(value != (func_type) (target_type) value)) { \ + func_type zero = 0; \ + if (is_unsigned && unlikely(value < zero)) \ + goto raise_neg_overflow; \ + else \ + goto raise_overflow; \ + } \ + } \ + return (target_type) value; \ + } + +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + #include "longintrepr.h" + #endif +#endif + +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { + const int neg_one = (int) -1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + switch (Py_SIZE(x)) { + case 0: return 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]); + } + #endif +#endif + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(int) <= sizeof(unsigned long long)) { + __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x)) + } + } else { +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + switch (Py_SIZE(x)) { + case 0: return 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0])); + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + } + #endif +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x)) + } else if (sizeof(int) <= sizeof(long long)) { + __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x)) + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_Int(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsdsds_double(PyObject *obj) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS, 3, + &__Pyx_TypeInfo_double, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { const int neg_one = (int) -1, const_zero = 0; const int is_unsigned = neg_one > const_zero; @@ -20822,6 +20856,50 @@ raise_neg_overflow: return (long) -1; } +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_d_dc_double(PyObject *obj) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, + (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 3, + &__Pyx_TypeInfo_double, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_double(PyObject *obj) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, + (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2, + &__Pyx_TypeInfo_double, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); @@ -20918,6 +20996,59 @@ bad: } #endif +#ifndef __PYX_HAVE_RT_ImportFunction +#define __PYX_HAVE_RT_ImportFunction +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + union { + void (*fp)(void); + void *p; + } tmp; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, funcname); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C function %.200s", + PyModule_GetName(module), funcname); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); + goto bad; + } + tmp.p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, desc); + goto bad; + } + tmp.p = PyCObject_AsVoidPtr(cobj);} +#endif + *f = tmp.fp; + if (!(*f)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 diff --git a/GPy/util/choleskies_cython.pyx b/GPy/util/choleskies_cython.pyx index d85b19cf..081491d5 100644 --- a/GPy/util/choleskies_cython.pyx +++ b/GPy/util/choleskies_cython.pyx @@ -7,8 +7,9 @@ import numpy as np from cython.parallel import prange, parallel cimport numpy as np +cimport scipy.linalg.cython_blas as cblas -def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): +def flat_to_triang(double[:, :] flat, int M): """take a matrix N x D and return a D X M x M array where N = M(M+1)/2 @@ -18,90 +19,96 @@ def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): cdef int D = flat.shape[1] cdef int N = flat.shape[0] cdef int count = 0 - cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) + cdef double[:, :, ::1] ret = np.zeros((D, M, M)) cdef int d, m, mm - for d in range(D): - count = 0 - for m in range(M): - for mm in range(m+1): - ret[d, m, mm] = flat[count,d] - count += 1 + with nogil: + for d in range(D): + count = 0 + for m in range(M): + for mm in range(m+1): + ret[d, m, mm] = flat[count,d] + count += 1 return ret -def triang_to_flat(np.ndarray[double, ndim=3] L): +def triang_to_flat(double[:, :, :] L): cdef int D = L.shape[0] cdef int M = L.shape[1] cdef int N = M*(M+1)/2 cdef int count = 0 - cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) + cdef double[:, ::1] flat = np.empty((N, D)) cdef int d, m, mm - for d in range(D): - count = 0 - for m in range(M): - for mm in range(m+1): - flat[count,d] = L[d, m, mm] - count += 1 + with nogil: + for d in range(D): + count = 0 + for m in range(M): + for mm in range(m+1): + flat[count,d] = L[d, m, mm] + count += 1 return flat - -def backprop_gradient(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): - cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL).copy() +def backprop_gradient(double[:, :] dL, double[:, :] L): + cdef double[:, ::1] dL_dK = np.tril(dL) cdef int N = L.shape[0] cdef int k, j, i - for k in range(N - 1, -1, -1): - for j in range(k + 1, N): - for i in range(j, N): - dL_dK[i, k] -= dL_dK[i, j] * L[j, k] - dL_dK[j, k] -= dL_dK[i, j] * L[i, k] - for j in range(k + 1, N): - dL_dK[j, k] /= L[k, k] - dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - dL_dK[k, k] /= (2. * L[k, k]) + with nogil: + for k in range(N - 1, -1, -1): + for j in range(k + 1, N): + for i in range(j, N): + dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + dL_dK[j, k] -= dL_dK[i, j] * L[i, k] + for j in range(k + 1, N): + dL_dK[j, k] /= L[k, k] + dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + dL_dK[k, k] /= (2. * L[k, k]) return dL_dK def backprop_gradient_par(double[:,:] dL, double[:,:] L): - cdef double[:,:] dL_dK = np.tril(dL).copy() + cdef double[:,::1] dL_dK = np.tril(dL) cdef int N = L.shape[0] cdef int k, j, i - for k in range(N - 1, -1, -1): - with nogil, parallel(): - for i in prange(k + 1, N): - for j in range(k+1, i+1): - dL_dK[i, k] -= dL_dK[i, j] * L[j, k] - for j in range(i, N): - dL_dK[i, k] -= dL_dK[j, i] * L[j, k] - for j in range(k + 1, N): - dL_dK[j, k] /= L[k, k] - dL_dK[k, k] -= L[j, k] * dL_dK[j, k] - dL_dK[k, k] /= (2. * L[k, k]) + with nogil: + for k in range(N - 1, -1, -1): + with parallel(): + for i in prange(k + 1, N): + for j in range(k+1, i+1): + dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + for j in range(i, N): + dL_dK[i, k] -= dL_dK[j, i] * L[j, k] + for j in range(k + 1, N): + dL_dK[j, k] /= L[k, k] + dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + dL_dK[k, k] /= (2. * L[k, k]) return dL_dK -#here's a pure C version... -cdef extern from "cholesky_backprop.h" nogil: - void chol_backprop(int N, double* dL, double* L) +cdef void chol_backprop(int N, double[:, ::1] dL, double[:, ::1] L) nogil: + cdef int i, k, n -def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): - cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig + # DSYMV required constant arguments + cdef double alpha=-1, beta=1 + cdef int incx=N + + # DSCAL required arguments + cdef double scale + + dL[N - 1, N - 1] /= (2. * L[N - 1, N - 1]) + for k in range(N-2, -1, -1): + n = N-k-1 + cblas.dsymv(uplo='u', n=&n, alpha=&alpha, a=&dL[k + 1, k + 1], lda=&N, x=&L[k + 1, k], incx=&incx, + beta=&beta, y=&dL[k + 1, k], incy=&N) + + for i in xrange(0, N - k - 1): + dL[k + 1 + i, k] -= dL[k + i+ 1, k + i + 1] * L[k + 1 + i, k] + + scale = 1.0 / L[k, k] + cblas.dscal(&n, &scale , &dL[k + 1, k], &N) +# + dL[k, k] -= cblas.ddot(&n, &dL[k + 1, k], &N, &L[k+1, k], &incx) + dL[k, k] /= (2.0 * L[k, k]) + +def backprop_gradient_par_c(double[:, :] dL, double[:, :] L): + cdef double[:, ::1] dL_dK = np.tril(dL) # makes a copy, c-contig + cdef double[:, ::1] L_cont = np.ascontiguousarray(L) cdef int N = L.shape[0] with nogil: - chol_backprop(N, dL_dK.data, L.data) - return dL_dK - -cdef extern from "cholesky_backprop.h" nogil: - void old_chol_backprop(int N, double* dL, double* L) - -def backprop_gradient_par_c_old(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): - cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig - cdef int N = L.shape[0] - with nogil: - old_chol_backprop(N, dL_dK.data, L.data) - return dL_dK - - - - - - - - - + chol_backprop(N, dL_dK, L_cont) + return np.asarray(dL_dK) diff --git a/GPy/util/cholesky_backprop.c b/GPy/util/cholesky_backprop.c deleted file mode 100644 index 0a4a2f03..00000000 --- a/GPy/util/cholesky_backprop.c +++ /dev/null @@ -1,51 +0,0 @@ -#include -void chol_backprop(int N, double* dL, double* L){ - //at the input to this fn, dL is df_dL. after this fn is complet, dL is df_dK - int i,k; - - dL[N*N - 1] /= (2. * L[N*N - 1]); - for(k=N-2;k>(-1);k--){ - cblas_dsymv(CblasRowMajor, CblasLower, - N-k-1, -1, - &dL[(N*(k+1) + k+1)],N, - &L[k*N+k+1],1, - 1, &dL[N*(k+1)+k], N); - for(i=0;i<(N-k-1); i++){ - dL[N*(k+1+i)+k] -= dL[N*(k+1)+k+i*(N+1)+1] * L[k*N+k+1+i]; - } - - cblas_dscal(N-k-1, 1.0/L[k*N+k], &dL[(k+1)*N+k], N); - dL[k*N + k] -= cblas_ddot(N-k-1, &dL[(k+1)*N+k], N, &L[k*N+k+1], 1); - dL[k*N + k] /= (2.0 * L[k*N + k]); - } -} - -double mydot(int n, double* a, int stride_a, double* b, int stride_b){ - double ret = 0; - for(int i=0; i(-1);k--){ - kN = k*N; - #pragma omp parallel for private(i,iN) - for(i=k+1; i - -void dsymv(int N, double*A, double*b, double*y); -double mydot(int n, double* a, int stride_a, double* b, int stride_b); -void chol_backprop(int N, double* dL, double* L); diff --git a/GPy/util/datasets.py b/GPy/util/datasets.py index 57755ea9..f9173365 100644 --- a/GPy/util/datasets.py +++ b/GPy/util/datasets.py @@ -374,7 +374,7 @@ def football_data(season='1314', data_set='football_data'): data_resources[data_set_season]['files'] = [files] if not data_available(data_set_season): download_data(data_set_season) - import pylab as pb + from matplotlib import pyplot as pb for file in reversed(files): filename = os.path.join(data_path, data_set_season, file) # rewrite files removing blank rows. diff --git a/GPy/util/diag.py b/GPy/util/diag.py index e7c332e2..9a3343f0 100644 --- a/GPy/util/diag.py +++ b/GPy/util/diag.py @@ -46,6 +46,8 @@ def offdiag_view(A, offset=0): return as_strided(Af[(1+offset):], shape=(A.shape[0]-1, A.shape[1]), strides=(A.strides[0] + A.itemsize, A.strides[1])) def _diag_ufunc(A,b,offset,func): + b = np.squeeze(b) + assert b.ndim <= 1, "only implemented for one dimensional arrays" dA = view(A, offset); func(dA,b,dA) return A diff --git a/GPy/util/erfcx.py b/GPy/util/erfcx.py deleted file mode 100644 index f42e49f3..00000000 --- a/GPy/util/erfcx.py +++ /dev/null @@ -1,63 +0,0 @@ -## Copyright (C) 2010 Soren Hauberg -## -## Copyright James Hensman 2011 -## -## This program is free software; you can redistribute it and/or modify it -## under the terms of the GNU General Public License as published by -## the Free Software Foundation; either version 3 of the License, or (at -## your option) any later version. -## -## This program is distributed in the hope that it will be useful, but -## WITHOUT ANY WARRANTY; without even the implied warranty of -## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU -## General Public License for more details. -## -## You should have received a copy of the GNU General Public License -## along with this program; see the file COPYING. If not, see -## . - -import numpy as np - -def erfcx (arg): - arg = np.atleast_1d(arg) - assert(np.all(np.isreal(arg)),"erfcx: input must be real") - - ## Get precision dependent thresholds -- or not :p - xneg = -26.628; - xmax = 2.53e+307; - - ## Allocate output - result = np.zeros (arg.shape) - - ## Find values where erfcx can be evaluated - idx_neg = (arg < xneg); - idx_max = (arg > xmax); - idx = ~(idx_neg | idx_max); - - arg = arg [idx]; - - ## Perform the actual computation - t = 3.97886080735226 / (np.abs (arg) + 3.97886080735226); - u = t - 0.5; - y = (((((((((u * 0.00127109764952614092 + 1.19314022838340944e-4) * u \ - - 0.003963850973605135) * u - 8.70779635317295828e-4) * u + \ - 0.00773672528313526668) * u + 0.00383335126264887303) * u - \ - 0.0127223813782122755) * u - 0.0133823644533460069) * u + \ - 0.0161315329733252248) * u + 0.0390976845588484035) * u + \ - 0.00249367200053503304; - y = ((((((((((((y * u - 0.0838864557023001992) * u - \ - 0.119463959964325415) * u + 0.0166207924969367356) * u + \ - 0.357524274449531043) * u + 0.805276408752910567) * u + \ - 1.18902982909273333) * u + 1.37040217682338167) * u + \ - 1.31314653831023098) * u + 1.07925515155856677) * u + \ - 0.774368199119538609) * u + 0.490165080585318424) * u + \ - 0.275374741597376782) * t; - - y [arg < 0] = 2 * np.exp (arg [arg < 0]**2) - y [arg < 0]; - - ## Put the results back into something with the same size is the original input - result [idx] = y; - result [idx_neg] = np.inf; - ## result (idx_max) = 0; # not needed as we initialise with zeros - return(result) - diff --git a/GPy/util/gpu_init.py b/GPy/util/gpu_init.py index 26dff0b3..0c496db3 100644 --- a/GPy/util/gpu_init.py +++ b/GPy/util/gpu_init.py @@ -16,33 +16,27 @@ try: except: pass -try: - if MPI_enabled and MPI.COMM_WORLD.size>1: - from .parallel import get_id_within_node - gpuid = get_id_within_node() - import pycuda.driver - pycuda.driver.init() - if gpuid>=pycuda.driver.Device.count(): - print('['+MPI.Get_processor_name()+'] more processes than the GPU numbers!') - #MPI.COMM_WORLD.Abort() - raise - gpu_device = pycuda.driver.Device(gpuid) - gpu_context = gpu_device.make_context() - gpu_initialized = True - else: - import pycuda.autoinit - gpu_initialized = True -except: - pass -try: - from scikits.cuda import cublas - import scikits.cuda.linalg as culinalg - culinalg.init() - cublas_handle = cublas.cublasCreate() -except: - pass +def initGPU(): + try: + if MPI_enabled and MPI.COMM_WORLD.size>1: + from .parallel import get_id_within_node + gpuid = get_id_within_node() + import pycuda.driver + pycuda.driver.init() + if gpuid>=pycuda.driver.Device.count(): + print('['+MPI.Get_processor_name()+'] more processes than the GPU numbers!') + raise + gpu_device = pycuda.driver.Device(gpuid) + gpu_context = gpu_device.make_context() + gpu_initialized = True + else: + import pycuda.autoinit + gpu_initialized = True + except: + pass + def closeGPU(): if gpu_context is not None: gpu_context.detach() diff --git a/GPy/util/linalg.py b/GPy/util/linalg.py index ed73d133..b4ffd1b0 100644 --- a/GPy/util/linalg.py +++ b/GPy/util/linalg.py @@ -7,47 +7,16 @@ import numpy as np from scipy import linalg -import types -import ctypes -from ctypes import byref, c_char, c_int, c_double # TODO -import scipy -import warnings -import os +from scipy.linalg import lapack, blas from .config import config import logging -from . import linalg_cython +try: + from . import linalg_cython + config.set('cython', 'working', 'True') +except ImportError: + config.set('cython', 'working', 'False') -_scipyversion = np.float64((scipy.__version__).split('.')[:2]) -_fix_dpotri_scipy_bug = True -if np.all(_scipyversion >= np.array([0, 14])): - from scipy.linalg import lapack - _fix_dpotri_scipy_bug = False -elif np.all(_scipyversion >= np.array([0, 12])): - #import scipy.linalg.lapack.clapack as lapack - from scipy.linalg import lapack -else: - from scipy.linalg.lapack import flapack as lapack - -if config.getboolean('anaconda', 'installed') and config.getboolean('anaconda', 'MKL'): - try: - anaconda_path = str(config.get('anaconda', 'location')) - mkl_rt = ctypes.cdll.LoadLibrary(os.path.join(anaconda_path, 'DLLs', 'mkl_rt.dll')) - dsyrk = mkl_rt.dsyrk - dsyr = mkl_rt.dsyr - _blas_available = True - print('anaconda installed and mkl is loaded') - except: - _blas_available = False -else: - try: - _blaslib = ctypes.cdll.LoadLibrary(np.core._dotblas.__file__) # @UndefinedVariable - dsyrk = _blaslib.dsyrk_ - dsyr = _blaslib.dsyr_ - _blas_available = True - except AttributeError as e: - _blas_available = False - warnings.warn("warning: caught this exception:" + str(e)) def force_F_ordered_symmetric(A): """ @@ -169,9 +138,6 @@ def dpotri(A, lower=1): :returns: A inverse """ - if _fix_dpotri_scipy_bug: - assert lower==1, "scipy linalg behaviour is very weird. please use lower, fortran ordered arrays" - lower = 0 A = force_F_ordered(A) R, info = lapack.dpotri(A, lower=lower) #needs to be zero here, seems to be a scipy bug @@ -191,7 +157,7 @@ def trace_dot(a, b): """ Efficiently compute the trace of the matrix product of a and b """ - return np.sum(a * b) + return np.einsum('ij,ji->', a, b) def mdot(*args): """ @@ -300,8 +266,8 @@ def pca(Y, input_dim): Z = linalg.svd(Y - Y.mean(axis=0), full_matrices=False) [X, W] = [Z[0][:, 0:input_dim], np.dot(np.diag(Z[1]), Z[2]).T[:, 0:input_dim]] v = X.std(axis=0) - X /= v; - W *= v; + X /= v + W *= v return X, W.T def ppca(Y, Q, iterations=100): @@ -347,34 +313,15 @@ def tdot_blas(mat, out=None): out[:] = 0.0 # # Call to DSYRK from BLAS - # If already in Fortran order (rare), and has the right sorts of strides I - # could avoid the copy. I also thought swapping to cblas API would allow use - # of C order. However, I tried that and had errors with large matrices: - # http://homepages.inf.ed.ac.uk/imurray2/code/tdot/tdot_broken.py mat = np.asfortranarray(mat) - TRANS = c_char('n'.encode('ascii')) - N = c_int(mat.shape[0]) - K = c_int(mat.shape[1]) - LDA = c_int(mat.shape[0]) - UPLO = c_char('l'.encode('ascii')) - ALPHA = c_double(1.0) - A = mat.ctypes.data_as(ctypes.c_void_p) - BETA = c_double(0.0) - C = out.ctypes.data_as(ctypes.c_void_p) - LDC = c_int(np.max(out.strides) // 8) - dsyrk(byref(UPLO), byref(TRANS), byref(N), byref(K), - byref(ALPHA), A, byref(LDA), byref(BETA), C, byref(LDC)) + out = blas.dsyrk(alpha=1.0, a=mat, beta=0.0, c=out, overwrite_c=1, + trans=0, lower=0) symmetrify(out, upper=True) - - return np.ascontiguousarray(out) def tdot(*args, **kwargs): - if _blas_available: - return tdot_blas(*args, **kwargs) - else: - return tdot_numpy(*args, **kwargs) + return tdot_blas(*args, **kwargs) def DSYR_blas(A, x, alpha=1.): """ @@ -386,15 +333,7 @@ def DSYR_blas(A, x, alpha=1.): :param alpha: scalar """ - N = c_int(A.shape[0]) - LDA = c_int(A.shape[0]) - UPLO = c_char('l'.encode('ascii')) - ALPHA = c_double(alpha) - A_ = A.ctypes.data_as(ctypes.c_void_p) - x_ = x.ctypes.data_as(ctypes.c_void_p) - INCX = c_int(1) - dsyr(byref(UPLO), byref(N), byref(ALPHA), - x_, byref(INCX), A_, byref(LDA)) + A = blas.dsyr(lower=0, x=x, a=A, alpha=alpha, overwrite_a=True) symmetrify(A, upper=True) def DSYR_numpy(A, x, alpha=1.): @@ -411,10 +350,8 @@ def DSYR_numpy(A, x, alpha=1.): def DSYR(*args, **kwargs): - if _blas_available: - return DSYR_blas(*args, **kwargs) - else: - return DSYR_numpy(*args, **kwargs) + return DSYR_blas(*args, **kwargs) + def symmetrify(A, upper=False): """ diff --git a/GPy/util/linalg_cython.c b/GPy/util/linalg_cython.c index 1374b233..0c6097c2 100644 --- a/GPy/util/linalg_cython.c +++ b/GPy/util/linalg_cython.c @@ -1,25 +1,13 @@ -/* Generated by Cython 0.21 */ +/* Generated by Cython 0.23 */ #define PY_SSIZE_T_CLEAN -#ifndef CYTHON_USE_PYLONG_INTERNALS -#ifdef PYLONG_BITS_IN_DIGIT -#define CYTHON_USE_PYLONG_INTERNALS 0 -#else -#include "pyconfig.h" -#ifdef PYLONG_BITS_IN_DIGIT -#define CYTHON_USE_PYLONG_INTERNALS 1 -#else -#define CYTHON_USE_PYLONG_INTERNALS 0 -#endif -#endif -#endif #include "Python.h" #ifndef Py_PYTHON_H #error Python headers needed to compile C extensions, please install development version of Python. #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else -#define CYTHON_ABI "0_21" +#define CYTHON_ABI "0_23" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) @@ -54,35 +42,40 @@ #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #endif -#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 +#if !defined(CYTHON_USE_PYLONG_INTERNALS) && CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x02070000 +#define CYTHON_USE_PYLONG_INTERNALS 1 +#endif +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" #define CYTHON_FORMAT_SSIZE_T "z" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif -#if PY_MAJOR_VERSION >= 3 +#ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif -#if PY_MAJOR_VERSION >= 3 +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif -#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE) +#ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 - #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \ + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) @@ -103,9 +96,12 @@ #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \ + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 @@ -151,6 +147,11 @@ #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong @@ -160,18 +161,22 @@ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif -#ifndef CYTHON_INLINE - #if defined(__GNUC__) - #define CYTHON_INLINE __inline__ - #elif defined(_MSC_VER) - #define CYTHON_INLINE __inline - #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L - #define CYTHON_INLINE inline - #else - #define CYTHON_INLINE - #endif +#if PY_VERSION_HEX >= 0x030500B1 +#define __Pyx_PyAsyncMethodsStruct PyAsyncMethods +#define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) +#elif CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 +typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; +} __Pyx_PyAsyncMethodsStruct; +#define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) +#else +#define __Pyx_PyType_AsAsync(obj) NULL #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) @@ -184,24 +189,33 @@ #define CYTHON_RESTRICT #endif #endif +#define __Pyx_void_to_None(void_result) (void_result, Py_INCREF(Py_None), Py_None) + +#ifndef CYTHON_INLINE + #if defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include #ifdef NAN #define __PYX_NAN() ((float) NAN) #else static CYTHON_INLINE float __PYX_NAN() { - /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and - a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is - a quiet NaN. */ float value; memset(&value, 0xFF, sizeof(value)); return value; } #endif -#ifdef __cplusplus -template -void __Pyx_call_destructor(T* x) { - x->~T(); -} -#endif #if PY_MAJOR_VERSION >= 3 @@ -220,12 +234,9 @@ void __Pyx_call_destructor(T* x) { #endif #endif -#if defined(WIN32) || defined(MS_WINDOWS) -#define _USE_MATH_DEFINES -#endif -#include #define __PYX_HAVE__GPy__util__linalg_cython #define __PYX_HAVE_API__GPy__util__linalg_cython +#include "math.h" #include "string.h" #include "stdio.h" #include "stdlib.h" @@ -253,6 +264,13 @@ void __Pyx_call_destructor(T* x) { # define CYTHON_UNUSED # endif #endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; @@ -261,16 +279,34 @@ typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding; #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize -#define __Pyx_fits_Py_ssize_t(v, type, is_signed) ( \ - (sizeof(type) < sizeof(Py_ssize_t)) || \ - (sizeof(type) > sizeof(Py_ssize_t) && \ - likely(v < (type)PY_SSIZE_T_MAX || \ - v == (type)PY_SSIZE_T_MAX) && \ - (!is_signed || likely(v > (type)PY_SSIZE_T_MIN || \ - v == (type)PY_SSIZE_T_MIN))) || \ - (sizeof(type) == sizeof(Py_ssize_t) && \ - (is_signed || likely(v < (type)PY_SSIZE_T_MAX || \ +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX))) ) +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (_MSC_VER) && defined (_M_X64) + #define __Pyx_sst_abs(value) _abs64(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*); static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); #define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) @@ -287,11 +323,11 @@ static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { @@ -305,8 +341,9 @@ static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) #define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) #define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode #define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode -#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None) -#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False)) +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +#define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False)) static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x); static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); @@ -327,7 +364,7 @@ static int __Pyx_init_sys_getdefaultencoding_params(void) { const char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); @@ -477,7 +514,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -486,7 +523,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -495,7 +532,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -504,7 +541,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -513,7 +550,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -522,7 +559,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -531,7 +568,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -540,7 +577,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -549,7 +586,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":739 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -558,7 +595,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -567,7 +604,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -576,7 +613,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -585,7 +622,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -594,7 +631,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -603,7 +640,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -612,7 +649,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -621,7 +658,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":757 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -630,7 +667,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -639,7 +676,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -648,7 +685,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -657,7 +694,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -688,7 +725,7 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; /*--- Type declarations ---*/ -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -697,7 +734,7 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":765 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -706,7 +743,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -715,7 +752,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -723,6 +760,8 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; + +/* --- Runtime support code (head) --- */ #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -739,19 +778,19 @@ typedef npy_cdouble __pyx_t_5numpy_complex_t; static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname); #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL; #ifdef WITH_THREAD - #define __Pyx_RefNannySetupContext(name, acquire_gil) \ - if (acquire_gil) { \ - PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); \ - __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \ - PyGILState_Release(__pyx_gilstate_save); \ - } else { \ - __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \ + #define __Pyx_RefNannySetupContext(name, acquire_gil)\ + if (acquire_gil) {\ + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();\ + __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__);\ + PyGILState_Release(__pyx_gilstate_save);\ + } else {\ + __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__);\ } #else - #define __Pyx_RefNannySetupContext(name, acquire_gil) \ + #define __Pyx_RefNannySetupContext(name, acquire_gil)\ __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__) #endif - #define __Pyx_RefNannyFinishContext() \ + #define __Pyx_RefNannyFinishContext()\ __Pyx_RefNanny->FinishContext(&__pyx_refnanny) #define __Pyx_INCREF(r) __Pyx_RefNanny->INCREF(__pyx_refnanny, (PyObject *)(r), __LINE__) #define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__) @@ -774,13 +813,13 @@ typedef npy_cdouble __pyx_t_5numpy_complex_t; #define __Pyx_XGOTREF(r) #define __Pyx_XGIVEREF(r) #endif -#define __Pyx_XDECREF_SET(r, v) do { \ - PyObject *tmp = (PyObject *) r; \ - r = v; __Pyx_XDECREF(tmp); \ +#define __Pyx_XDECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_XDECREF(tmp);\ } while (0) -#define __Pyx_DECREF_SET(r, v) do { \ - PyObject *tmp = (PyObject *) r; \ - r = v; __Pyx_DECREF(tmp); \ +#define __Pyx_DECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_DECREF(tmp);\ } while (0) #define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0) #define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0) @@ -807,8 +846,8 @@ static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); -static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \ - PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ const char* function_name); static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, @@ -822,8 +861,6 @@ static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); -static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name); - #define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); @@ -831,18 +868,28 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg #define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) #endif -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); -#endif - -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); - -#ifndef __PYX_FORCE_INIT_THREADS - #define __PYX_FORCE_INIT_THREADS 0 -#endif - static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) + PyErr_SetObject(PyExc_KeyError, args); + Py_XDECREF(args); + } + return NULL; + } + Py_INCREF(value); + return value; +} +#else + #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#endif + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); @@ -897,6 +944,10 @@ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) @@ -995,6 +1046,8 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do #endif #endif +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); @@ -1016,33 +1069,19 @@ static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); -/* Module declarations from 'cpython.buffer' */ +/* Module declarations from 'libc.math' */ -/* Module declarations from 'cpython.ref' */ +/* Module declarations from 'cpython.buffer' */ /* Module declarations from 'libc.string' */ /* Module declarations from 'libc.stdio' */ -/* Module declarations from 'cpython.object' */ - /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.type' */ static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; -/* Module declarations from 'libc.stdlib' */ - -/* Module declarations from 'numpy' */ - -/* Module declarations from 'numpy' */ -static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; -static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; -static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; -static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; -static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; -static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ - /* Module declarations from 'cpython.version' */ /* Module declarations from 'cpython.exc' */ @@ -1111,6 +1150,22 @@ static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0; /* Module declarations from 'cpython' */ +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'libc.stdlib' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ + /* Module declarations from 'cython' */ /* Module declarations from 'GPy.util.linalg_cython' */ @@ -1123,10 +1178,6 @@ static PyObject *__pyx_builtin_xrange; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_RuntimeError; -static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_A, PyBoolObject *__pyx_v_upper); /* proto */ -static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_x, PyArrayObject *__pyx_v_L, int __pyx_v_N); /* proto */ -static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static char __pyx_k_A[] = "A"; static char __pyx_k_B[] = "B"; static char __pyx_k_H[] = "H"; @@ -1151,9 +1202,7 @@ static char __pyx_k_x[] = "x"; static char __pyx_k_Zd[] = "Zd"; static char __pyx_k_Zf[] = "Zf"; static char __pyx_k_Zg[] = "Zg"; -static char __pyx_k_np[] = "np"; static char __pyx_k_main[] = "__main__"; -static char __pyx_k_sqrt[] = "sqrt"; static char __pyx_k_test[] = "__test__"; static char __pyx_k_range[] = "range"; static char __pyx_k_upper[] = "upper"; @@ -1164,7 +1213,7 @@ static char __pyx_k_symmetrify[] = "symmetrify"; static char __pyx_k_RuntimeError[] = "RuntimeError"; static char __pyx_k_GPy_util_linalg_cython[] = "GPy.util.linalg_cython"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; -static char __pyx_k_home_james_work_GPy_GPy_util_li[] = "/home/james/work/GPy/GPy/util/linalg_cython.pyx"; +static char __pyx_k_home_david_gits_GPy_GPy_util_li[] = "/home/david/gits/GPy/GPy/util/linalg_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; @@ -1181,23 +1230,25 @@ static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_s_cholupdate; -static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_util_li; +static PyObject *__pyx_kp_s_home_david_gits_GPy_GPy_util_li; static PyObject *__pyx_n_s_i; static PyObject *__pyx_n_s_j; static PyObject *__pyx_n_s_main; static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; -static PyObject *__pyx_n_s_np; static PyObject *__pyx_n_s_r; static PyObject *__pyx_n_s_range; static PyObject *__pyx_n_s_s; -static PyObject *__pyx_n_s_sqrt; static PyObject *__pyx_n_s_symmetrify; static PyObject *__pyx_n_s_test; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; static PyObject *__pyx_n_s_upper; static PyObject *__pyx_n_s_x; static PyObject *__pyx_n_s_xrange; +static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_A, PyBoolObject *__pyx_v_upper); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_x, PyArrayObject *__pyx_v_L, int __pyx_v_N); /* proto */ +static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static PyObject *__pyx_tuple_; static PyObject *__pyx_tuple__2; static PyObject *__pyx_tuple__3; @@ -1209,7 +1260,7 @@ static PyObject *__pyx_tuple__9; static PyObject *__pyx_codeobj__8; static PyObject *__pyx_codeobj__10; -/* "GPy/util/linalg_cython.pyx":8 +/* "GPy/util/linalg_cython.pyx":9 * @cython.wraparound(False) * @cython.nonecheck(False) * def symmetrify(np.ndarray[double, ndim=2] A, bool upper): # <<<<<<<<<<<<<< @@ -1249,11 +1300,11 @@ static PyObject *__pyx_pw_3GPy_4util_13linalg_cython_1symmetrify(PyObject *__pyx case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_upper)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("symmetrify", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("symmetrify", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "symmetrify") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "symmetrify") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 2) { goto __pyx_L5_argtuple_error; @@ -1266,14 +1317,14 @@ static PyObject *__pyx_pw_3GPy_4util_13linalg_cython_1symmetrify(PyObject *__pyx } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("symmetrify", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("symmetrify", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.util.linalg_cython.symmetrify", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_A), __pyx_ptype_5numpy_ndarray, 1, "A", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_upper), __pyx_ptype_7cpython_4bool_bool, 1, "upper", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_A), __pyx_ptype_5numpy_ndarray, 1, "A", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_upper), __pyx_ptype_7cpython_4bool_bool, 1, "upper", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4util_13linalg_cython_symmetrify(__pyx_self, __pyx_v_A, __pyx_v_upper); /* function exit code */ @@ -1299,14 +1350,14 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py int __pyx_t_4; int __pyx_t_5; int __pyx_t_6; - int __pyx_t_7; - int __pyx_t_8; - int __pyx_t_9; - int __pyx_t_10; - int __pyx_t_11; - int __pyx_t_12; - int __pyx_t_13; - int __pyx_t_14; + Py_ssize_t __pyx_t_7; + Py_ssize_t __pyx_t_8; + Py_ssize_t __pyx_t_9; + Py_ssize_t __pyx_t_10; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + Py_ssize_t __pyx_t_13; + Py_ssize_t __pyx_t_14; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -1317,11 +1368,11 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py __pyx_pybuffernd_A.rcbuffer = &__pyx_pybuffer_A; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_A.rcbuffer->pybuffer, (PyObject*)__pyx_v_A, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES| PyBUF_WRITABLE, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_A.rcbuffer->pybuffer, (PyObject*)__pyx_v_A, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES| PyBUF_WRITABLE, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_A.diminfo[0].strides = __pyx_pybuffernd_A.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_A.diminfo[0].shape = __pyx_pybuffernd_A.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_A.diminfo[1].strides = __pyx_pybuffernd_A.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_A.diminfo[1].shape = __pyx_pybuffernd_A.rcbuffer->pybuffer.shape[1]; - /* "GPy/util/linalg_cython.pyx":9 + /* "GPy/util/linalg_cython.pyx":10 * @cython.nonecheck(False) * def symmetrify(np.ndarray[double, ndim=2] A, bool upper): * cdef int N = A.shape[0] # <<<<<<<<<<<<<< @@ -1330,18 +1381,18 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py */ __pyx_v_N = (__pyx_v_A->dimensions[0]); - /* "GPy/util/linalg_cython.pyx":10 + /* "GPy/util/linalg_cython.pyx":11 * def symmetrify(np.ndarray[double, ndim=2] A, bool upper): * cdef int N = A.shape[0] * if not upper: # <<<<<<<<<<<<<< * for i in xrange(N): * for j in xrange(i): */ - __pyx_t_1 = __Pyx_PyObject_IsTrue(((PyObject *)__pyx_v_upper)); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_IsTrue(((PyObject *)__pyx_v_upper)); if (unlikely(__pyx_t_1 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((!__pyx_t_1) != 0); if (__pyx_t_2) { - /* "GPy/util/linalg_cython.pyx":11 + /* "GPy/util/linalg_cython.pyx":12 * cdef int N = A.shape[0] * if not upper: * for i in xrange(N): # <<<<<<<<<<<<<< @@ -1352,7 +1403,7 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "GPy/util/linalg_cython.pyx":12 + /* "GPy/util/linalg_cython.pyx":13 * if not upper: * for i in xrange(N): * for j in xrange(i): # <<<<<<<<<<<<<< @@ -1363,7 +1414,7 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_j = __pyx_t_6; - /* "GPy/util/linalg_cython.pyx":13 + /* "GPy/util/linalg_cython.pyx":14 * for i in xrange(N): * for j in xrange(i): * A[j, i] = A[i, j] # <<<<<<<<<<<<<< @@ -1377,22 +1428,30 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_A.rcbuffer->pybuffer.buf, __pyx_t_9, __pyx_pybuffernd_A.diminfo[0].strides, __pyx_t_10, __pyx_pybuffernd_A.diminfo[1].strides) = (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_A.rcbuffer->pybuffer.buf, __pyx_t_7, __pyx_pybuffernd_A.diminfo[0].strides, __pyx_t_8, __pyx_pybuffernd_A.diminfo[1].strides)); } } + + /* "GPy/util/linalg_cython.pyx":11 + * def symmetrify(np.ndarray[double, ndim=2] A, bool upper): + * cdef int N = A.shape[0] + * if not upper: # <<<<<<<<<<<<<< + * for i in xrange(N): + * for j in xrange(i): + */ goto __pyx_L3; } - /*else*/ { - /* "GPy/util/linalg_cython.pyx":15 + /* "GPy/util/linalg_cython.pyx":16 * A[j, i] = A[i, j] * else: * for j in xrange(N): # <<<<<<<<<<<<<< * for i in xrange(j): * A[j, i] = A[i, j] */ + /*else*/ { __pyx_t_3 = __pyx_v_N; for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_j = __pyx_t_4; - /* "GPy/util/linalg_cython.pyx":16 + /* "GPy/util/linalg_cython.pyx":17 * else: * for j in xrange(N): * for i in xrange(j): # <<<<<<<<<<<<<< @@ -1403,7 +1462,7 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "GPy/util/linalg_cython.pyx":17 + /* "GPy/util/linalg_cython.pyx":18 * for j in xrange(N): * for i in xrange(j): * A[j, i] = A[i, j] # <<<<<<<<<<<<<< @@ -1420,7 +1479,7 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py } __pyx_L3:; - /* "GPy/util/linalg_cython.pyx":8 + /* "GPy/util/linalg_cython.pyx":9 * @cython.wraparound(False) * @cython.nonecheck(False) * def symmetrify(np.ndarray[double, ndim=2] A, bool upper): # <<<<<<<<<<<<<< @@ -1447,12 +1506,12 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_symmetrify(CYTHON_UNUSED Py return __pyx_r; } -/* "GPy/util/linalg_cython.pyx":22 - * @cython.wraparound(False) +/* "GPy/util/linalg_cython.pyx":24 * @cython.nonecheck(False) + * @cython.cdivision(True) * def cholupdate(np.ndarray[double, ndim=1] x, np.ndarray[double, ndim=2] L, int N): # <<<<<<<<<<<<<< - * cdef double r - * cdef double c + * cdef double r, c, s + * cdef int j, i */ /* Python wrapper */ @@ -1489,16 +1548,16 @@ static PyObject *__pyx_pw_3GPy_4util_13linalg_cython_3cholupdate(PyObject *__pyx case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_L)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("cholupdate", 1, 3, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("cholupdate", 1, 3, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_N)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("cholupdate", 1, 3, 3, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("cholupdate", 1, 3, 3, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "cholupdate") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "cholupdate") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 3) { goto __pyx_L5_argtuple_error; @@ -1509,18 +1568,18 @@ static PyObject *__pyx_pw_3GPy_4util_13linalg_cython_3cholupdate(PyObject *__pyx } __pyx_v_x = ((PyArrayObject *)values[0]); __pyx_v_L = ((PyArrayObject *)values[1]); - __pyx_v_N = __Pyx_PyInt_As_int(values[2]); 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__pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_L), __pyx_ptype_5numpy_ndarray, 1, "L", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_x), __pyx_ptype_5numpy_ndarray, 1, "x", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_L), __pyx_ptype_5numpy_ndarray, 1, "L", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(__pyx_self, __pyx_v_x, __pyx_v_L, __pyx_v_N); /* function exit code */ @@ -1546,37 +1605,32 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P __Pyx_RefNannyDeclarations int __pyx_t_1; int __pyx_t_2; - PyObject *__pyx_t_3 = NULL; - PyObject *__pyx_t_4 = NULL; - PyObject *__pyx_t_5 = NULL; - int __pyx_t_6; - int __pyx_t_7; - int __pyx_t_8; - int __pyx_t_9; - int __pyx_t_10; - int __pyx_t_11; - PyObject *__pyx_t_12 = NULL; - PyObject *__pyx_t_13 = NULL; - double __pyx_t_14; - int __pyx_t_15; + Py_ssize_t __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + Py_ssize_t __pyx_t_6; + Py_ssize_t __pyx_t_7; + Py_ssize_t __pyx_t_8; + Py_ssize_t __pyx_t_9; + Py_ssize_t __pyx_t_10; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + Py_ssize_t __pyx_t_13; + Py_ssize_t __pyx_t_14; + Py_ssize_t __pyx_t_15; int __pyx_t_16; int __pyx_t_17; - int __pyx_t_18; - int __pyx_t_19; - double __pyx_t_20; - int __pyx_t_21; - int __pyx_t_22; - int __pyx_t_23; - int __pyx_t_24; - int __pyx_t_25; - int __pyx_t_26; - int __pyx_t_27; - int __pyx_t_28; - int __pyx_t_29; - int __pyx_t_30; - int __pyx_t_31; - int __pyx_t_32; - int __pyx_t_33; + Py_ssize_t __pyx_t_18; + Py_ssize_t __pyx_t_19; + Py_ssize_t __pyx_t_20; + Py_ssize_t __pyx_t_21; + Py_ssize_t __pyx_t_22; + Py_ssize_t __pyx_t_23; + Py_ssize_t __pyx_t_24; + Py_ssize_t __pyx_t_25; + Py_ssize_t __pyx_t_26; + Py_ssize_t __pyx_t_27; + Py_ssize_t __pyx_t_28; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -1591,244 +1645,168 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P __pyx_pybuffernd_L.rcbuffer = &__pyx_pybuffer_L; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_x.rcbuffer->pybuffer, (PyObject*)__pyx_v_x, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES| PyBUF_WRITABLE, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_x.rcbuffer->pybuffer, (PyObject*)__pyx_v_x, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES| PyBUF_WRITABLE, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_x.diminfo[0].strides = __pyx_pybuffernd_x.rcbuffer->pybuffer.strides[0]; 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if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 + * copy_shape = 0 + * + * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): + * raise ValueError(u"ndarray is not C contiguous") + */ } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 * raise ValueError(u"ndarray is not C contiguous") * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -2020,14 +2020,12 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS) != 0); if (__pyx_t_2) { - goto __pyx_L10_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L9_bool_binop_done; } - __pyx_L10_next_and:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -2037,23 +2035,39 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_2 = ((!(PyArray_CHKFLAGS(__pyx_v_self, NPY_F_CONTIGUOUS) != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L9_bool_binop_done:; + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + * raise ValueError(u"ndarray is not C contiguous") + * + * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): + * raise ValueError(u"ndarray is not Fortran contiguous") + */ if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< * * info.buf = PyArray_DATA(self) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + * raise ValueError(u"ndarray is not C contiguous") + * + * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< + * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): + * raise ValueError(u"ndarray is not Fortran contiguous") + */ } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":224 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -2062,7 +2076,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->buf = PyArray_DATA(__pyx_v_self); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":225 * * info.buf = PyArray_DATA(self) * info.ndim = ndim # <<<<<<<<<<<<<< @@ -2071,7 +2085,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->ndim = __pyx_v_ndim; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":223 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 * info.buf = PyArray_DATA(self) * info.ndim = ndim * if copy_shape: # <<<<<<<<<<<<<< @@ -2081,7 +2095,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (__pyx_v_copy_shape != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 * # Allocate new buffer for strides and shape info. * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) # <<<<<<<<<<<<<< @@ -2090,7 +2104,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * ((size_t)__pyx_v_ndim)) * 2))); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":227 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim # <<<<<<<<<<<<<< @@ -2099,7 +2113,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":228 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":231 * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -2110,7 +2124,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -2119,7 +2133,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -2128,20 +2142,28 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->shape[__pyx_v_i]) = (PyArray_DIMS(__pyx_v_self)[__pyx_v_i]); } + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + * info.buf = PyArray_DATA(self) + * info.ndim = ndim + * if copy_shape: # <<<<<<<<<<<<<< + * # Allocate new buffer for strides and shape info. + * # This is allocated as one block, strides first. + */ goto __pyx_L11; } - /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL */ + /*else*/ { __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self)); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -2152,7 +2174,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L11:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":237 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -2161,7 +2183,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->suboffsets = NULL; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":238 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -2170,7 +2192,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -2179,28 +2201,28 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->readonly = (!(PyArray_ISWRITEABLE(__pyx_v_self) != 0)); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":242 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< * cdef dtype descr = self.descr - * cdef list stack + * cdef int offset */ __pyx_v_f = NULL; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":243 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< - * cdef list stack * cdef int offset + * */ __pyx_t_3 = ((PyObject *)__pyx_v_self->descr); __Pyx_INCREF(__pyx_t_3); __pyx_v_descr = ((PyArray_Descr *)__pyx_t_3); __pyx_t_3 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -2209,7 +2231,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -2218,18 +2240,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_2) { - goto __pyx_L16_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L15_bool_binop_done; } - __pyx_L16_next_and:; __pyx_t_2 = ((!(__pyx_v_copy_shape != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L15_bool_binop_done:; if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":250 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -2241,17 +2261,25 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GOTREF(__pyx_v_info->obj); __Pyx_DECREF(__pyx_v_info->obj); __pyx_v_info->obj = Py_None; + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + * cdef bint hasfields = PyDataType_HASFIELDS(descr) + * + * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< + * # do not call releasebuffer + * info.obj = None + */ goto __pyx_L14; } - /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< * * if not hasfields: */ + /*else*/ { __Pyx_INCREF(((PyObject *)__pyx_v_self)); __Pyx_GIVEREF(((PyObject *)__pyx_v_self)); __Pyx_GOTREF(__pyx_v_info->obj); @@ -2260,7 +2288,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L14:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -2270,7 +2298,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -2280,7 +2308,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_4 = __pyx_v_descr->type_num; __pyx_v_t = __pyx_t_4; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -2291,19 +2319,16 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P if (!__pyx_t_2) { goto __pyx_L20_next_or; } else { - goto __pyx_L21_next_and; } - __pyx_L21_next_and:; __pyx_t_2 = (__pyx_v_little_endian != 0); if (!__pyx_t_2) { - goto __pyx_L20_next_or; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } __pyx_L20_next_or:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -2312,52 +2337,58 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((__pyx_v_descr->byteorder == '<') != 0); if (__pyx_t_2) { - goto __pyx_L22_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } - __pyx_L22_next_and:; __pyx_t_2 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L19_bool_binop_done:; + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + * if not hasfields: + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (descr.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + * if not hasfields: + * t = descr.type_num + * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (descr.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 - * elif t == NPY_CDOUBLE: f = "Zd" - * elif t == NPY_CLONGDOUBLE: f = "Zg" - * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< - * else: - * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) - */ - switch (__pyx_v_t) { - - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" */ + switch (__pyx_v_t) { case NPY_BYTE: __pyx_v_f = __pyx_k_b; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -2368,7 +2399,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_B; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -2379,7 +2410,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_h; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -2390,7 +2421,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_H; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -2401,7 +2432,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_i; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -2412,7 +2443,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_I; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -2423,7 +2454,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_l; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -2434,7 +2465,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_L; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -2445,7 +2476,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_q; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -2456,7 +2487,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Q; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -2467,7 +2498,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_f; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -2478,7 +2509,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_d; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -2489,7 +2520,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_g; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -2500,7 +2531,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zf; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -2511,7 +2542,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zd; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":275 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -2522,7 +2553,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zg; 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} -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":780 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":782 * return PyArray_MultiIterNew(4, a, b, c, d) * * cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): # <<<<<<<<<<<<<< @@ -2957,7 +3008,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew5", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":781 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 * * cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): * return PyArray_MultiIterNew(5, a, b, c, d, e) # <<<<<<<<<<<<<< @@ -2965,13 +3016,13 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *__ * cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL: */ __Pyx_XDECREF(__pyx_r); 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if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + if (unlikely(__pyx_v_descr->fields == Py_None)) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not subscriptable"); + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_t_3 = __Pyx_PyDict_GetItem(__pyx_v_descr->fields, __pyx_v_childname); if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; __Pyx_GOTREF(__pyx_t_3); if (!(likely(PyTuple_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "tuple", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_XDECREF_SET(__pyx_v_fields, ((PyObject*)__pyx_t_3)); __pyx_t_3 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 * for childname in descr.names: * fields = descr.fields[childname] * child, new_offset = fields # <<<<<<<<<<<<<< @@ -3114,7 +3170,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_new_offset, __pyx_t_4); 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__pyx_t_3 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + * child, new_offset = fields + * + * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + */ } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") * * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -3156,19 +3220,16 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx if (!__pyx_t_7) { goto __pyx_L8_next_or; } else { - goto __pyx_L9_next_and; } - __pyx_L9_next_and:; __pyx_t_7 = (__pyx_v_little_endian != 0); if (!__pyx_t_7) { - goto __pyx_L8_next_or; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L7_bool_binop_done; } __pyx_L8_next_or:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 * * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -3177,18 +3238,24 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_t_7 = ((__pyx_v_child->byteorder == '<') != 0); if (__pyx_t_7) { - goto __pyx_L10_next_and; } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L7_bool_binop_done; } - __pyx_L10_next_and:; __pyx_t_7 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_6 = __pyx_t_7; __pyx_L7_bool_binop_done:; + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (child.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ if (__pyx_t_6) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -3200,9 +3267,17 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") + * + * if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< + * (child.byteorder == c'<' and not little_endian)): + * raise ValueError(u"Non-native byte order not supported") + */ } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 * * # Output padding bytes * while offset[0] < new_offset: # <<<<<<<<<<<<<< @@ -3218,7 +3293,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; if (!__pyx_t_6) break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 * # Output padding bytes * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte # <<<<<<<<<<<<<< @@ -3227,7 +3302,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ (__pyx_v_f[0]) = 120; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte * f += 1 # <<<<<<<<<<<<<< @@ -3236,7 +3311,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_v_f = (__pyx_v_f + 1); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 * f[0] = 120 # "x"; pad byte * f += 1 * offset[0] += 1 # <<<<<<<<<<<<<< @@ -3247,7 +3322,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + 1); } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 * offset[0] += 1 * * offset[0] += child.itemsize # <<<<<<<<<<<<<< @@ -3257,7 +3332,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_8 = 0; (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + __pyx_v_child->elsize); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 * offset[0] += child.itemsize * * if not PyDataType_HASFIELDS(child): # <<<<<<<<<<<<<< @@ -3267,7 +3342,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = ((!(PyDataType_HASFIELDS(__pyx_v_child) != 0)) != 0); if (__pyx_t_6) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":821 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":821 * * if not PyDataType_HASFIELDS(child): * t = child.type_num # <<<<<<<<<<<<<< @@ -3279,7 +3354,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_t, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 * if not PyDataType_HASFIELDS(child): * t = child.type_num * if end - f < 5: # <<<<<<<<<<<<<< @@ -3289,7 +3364,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = (((__pyx_v_end - __pyx_v_f) < 5) != 0); if (__pyx_t_6) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 * t = child.type_num * if end - f < 5: * raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<< @@ -3301,16 +3376,24 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_Raise(__pyx_t_4, 0, 0, 0); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; {__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":822 + * if not PyDataType_HASFIELDS(child): + * t = child.type_num + * if end - f < 5: # <<<<<<<<<<<<<< + * raise RuntimeError(u"Format string allocated too short.") + * + */ } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 * * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" # <<<<<<<<<<<<<< * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" */ - __pyx_t_4 = PyInt_FromLong(NPY_BYTE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_BYTE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3321,14 +3404,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" # <<<<<<<<<<<<<< * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" */ - __pyx_t_3 = PyInt_FromLong(NPY_UBYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_UBYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3339,14 +3422,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" # <<<<<<<<<<<<<< * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" */ - __pyx_t_4 = PyInt_FromLong(NPY_SHORT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_SHORT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3357,14 +3440,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" # <<<<<<<<<<<<<< * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" */ - __pyx_t_3 = PyInt_FromLong(NPY_USHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_USHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3375,14 +3458,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" # <<<<<<<<<<<<<< * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" */ - __pyx_t_4 = PyInt_FromLong(NPY_INT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_INT); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3393,14 +3476,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" # <<<<<<<<<<<<<< * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" */ - __pyx_t_3 = PyInt_FromLong(NPY_UINT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_UINT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3411,14 +3494,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":832 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":832 * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" # <<<<<<<<<<<<<< * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" */ - __pyx_t_4 = PyInt_FromLong(NPY_LONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_LONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3429,14 +3512,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" # <<<<<<<<<<<<<< * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" */ - __pyx_t_3 = PyInt_FromLong(NPY_ULONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_ULONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3447,14 +3530,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" # <<<<<<<<<<<<<< * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" */ - __pyx_t_4 = PyInt_FromLong(NPY_LONGLONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_LONGLONG); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_4, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -3465,14 +3548,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" # <<<<<<<<<<<<<< * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" */ - __pyx_t_3 = PyInt_FromLong(NPY_ULONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_From_enum__NPY_TYPES(NPY_ULONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_4); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -3483,14 +3566,14 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" # <<<<<<<<<<<<<< * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" */ - __pyx_t_4 = PyInt_FromLong(NPY_FLOAT); 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if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); + PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __pyx_t_3 = 0; __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); @@ -3639,7 +3722,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } __pyx_L15:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":845 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":845 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * f += 1 # <<<<<<<<<<<<<< @@ -3647,23 +3730,31 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx * # Cython ignores struct boundary information ("T{...}"), */ __pyx_v_f = (__pyx_v_f + 1); 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- /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":974 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":974 * baseptr = base * Py_XDECREF(arr.base) * arr.base = baseptr # <<<<<<<<<<<<<< @@ -3784,7 +3883,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a */ __pyx_v_arr->base = __pyx_v_baseptr; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":966 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":966 * * * cdef inline void set_array_base(ndarray arr, object base): # <<<<<<<<<<<<<< @@ -3796,7 +3895,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a __Pyx_RefNannyFinishContext(); } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 +/* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 * arr.base = baseptr * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -3810,7 +3909,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py int __pyx_t_1; 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goto __pyx_L1_error;} - __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 231; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_RuntimeError = __Pyx_GetBuiltinName(__pyx_n_s_RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; __pyx_L1_error:; @@ -3931,40 +4036,40 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__Pyx_InitCachedConstants", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) */ - __pyx_tuple_ = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_C_contiguous); 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if (unlikely(!__pyx_codeobj__10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -4057,18 +4162,24 @@ PyMODINIT_FUNC PyInit_linalg_cython(void) } #endif __Pyx_RefNannySetupContext("PyMODINIT_FUNC PyInit_linalg_cython(void)", 0); - if ( __Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_empty_tuple = PyTuple_New(0); if (unlikely(!__pyx_empty_tuple)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_empty_bytes = PyBytes_FromStringAndSize("", 0); if (unlikely(!__pyx_empty_bytes)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #ifdef __Pyx_CyFunction_USED - if (__Pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif #ifdef __Pyx_FusedFunction_USED if (__pyx_FusedFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif + #ifdef __Pyx_Coroutine_USED + if (__pyx_Coroutine_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif #ifdef __Pyx_Generator_USED if (__pyx_Generator_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif + #ifdef __Pyx_StopAsyncIteration_USED + if (__pyx_StopAsyncIteration_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif /*--- Library function declarations ---*/ /*--- Threads initialization code ---*/ #if defined(__PYX_FORCE_INIT_THREADS) && __PYX_FORCE_INIT_THREADS @@ -4091,12 +4202,12 @@ PyMODINIT_FUNC PyInit_linalg_cython(void) #endif if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; /*--- Initialize various global constants etc. ---*/ - if (unlikely(__Pyx_InitGlobals() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitGlobals() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #if PY_MAJOR_VERSION < 3 && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if (__Pyx_init_sys_getdefaultencoding_params() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif if (__pyx_module_is_main_GPy__util__linalg_cython) { - if (PyObject_SetAttrString(__pyx_m, "__name__", __pyx_n_s_main) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + if (PyObject_SetAttrString(__pyx_m, "__name__", __pyx_n_s_main) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } #if PY_MAJOR_VERSION >= 3 { @@ -4107,9 +4218,9 @@ PyMODINIT_FUNC PyInit_linalg_cython(void) } #endif /*--- Builtin init code ---*/ - if (unlikely(__Pyx_InitCachedBuiltins() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitCachedBuiltins() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Constants init code ---*/ - if (unlikely(__Pyx_InitCachedConstants() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitCachedConstants() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Global init code ---*/ /*--- Variable export code ---*/ /*--- Function export code ---*/ @@ -4122,52 +4233,55 @@ PyMODINIT_FUNC PyInit_linalg_cython(void) sizeof(PyHeapTypeObject), #endif 0); if (unlikely(!__pyx_ptype_7cpython_4type_type)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr), 0); if (unlikely(!__pyx_ptype_5numpy_dtype)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 155; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 169; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 861; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_7cpython_4bool_bool = __Pyx_ImportType(__Pyx_BUILTIN_MODULE_NAME, "bool", sizeof(PyBoolObject), 0); if (unlikely(!__pyx_ptype_7cpython_4bool_bool)) {__pyx_filename = __pyx_f[3]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_7cpython_7complex_complex = __Pyx_ImportType(__Pyx_BUILTIN_MODULE_NAME, "complex", sizeof(PyComplexObject), 0); if (unlikely(!__pyx_ptype_7cpython_7complex_complex)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr), 0); if (unlikely(!__pyx_ptype_5numpy_dtype)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 155; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 168; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 172; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 861; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Variable import code ---*/ /*--- Function import code ---*/ /*--- Execution code ---*/ + #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) + if (__Pyx_patch_abc() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif - /* "GPy/util/linalg_cython.pyx":8 + /* "GPy/util/linalg_cython.pyx":9 * @cython.wraparound(False) * @cython.nonecheck(False) * def symmetrify(np.ndarray[double, ndim=2] A, bool upper): # <<<<<<<<<<<<<< * cdef int N = A.shape[0] * if not upper: */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_13linalg_cython_1symmetrify, NULL, __pyx_n_s_GPy_util_linalg_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_13linalg_cython_1symmetrify, NULL, __pyx_n_s_GPy_util_linalg_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_symmetrify, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 8; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_symmetrify, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/linalg_cython.pyx":22 - * @cython.wraparound(False) + /* "GPy/util/linalg_cython.pyx":24 * @cython.nonecheck(False) + * @cython.cdivision(True) * def cholupdate(np.ndarray[double, ndim=1] x, np.ndarray[double, ndim=2] L, int N): # <<<<<<<<<<<<<< - * cdef double r - * cdef double c + * cdef double r, c, s + * cdef int j, i */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_13linalg_cython_3cholupdate, NULL, __pyx_n_s_GPy_util_linalg_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_13linalg_cython_3cholupdate, NULL, __pyx_n_s_GPy_util_linalg_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_cholupdate, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_cholupdate, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 24; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/util/linalg_cython.pyx":1 - * cimport numpy as np # <<<<<<<<<<<<<< + * from libc.math cimport sqrt # <<<<<<<<<<<<<< + * cimport numpy as np * from cpython cimport bool - * import cython */ __pyx_t_1 = PyDict_New(); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 + /* "../../../../.virtualenvs/py27/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 * arr.base = baseptr * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -4183,7 +4297,6 @@ PyMODINIT_FUNC PyInit_linalg_cython(void) if (__pyx_m) { if (__pyx_d) { __Pyx_AddTraceback("init GPy.util.linalg_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); - Py_DECREF(__pyx_d); __pyx_d = 0; } Py_DECREF(__pyx_m); __pyx_m = 0; } else if (!PyErr_Occurred()) { @@ -4198,7 +4311,7 @@ PyMODINIT_FUNC PyInit_linalg_cython(void) #endif } -/* Runtime support code */ +/* --- Runtime support code --- */ #if CYTHON_REFNANNY static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { PyObject *m = NULL, *p = NULL; @@ -4973,23 +5086,6 @@ static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyOb #endif } -static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) { - PyObject *result; -#if CYTHON_COMPILING_IN_CPYTHON - result = PyDict_GetItem(__pyx_d, name); - if (likely(result)) { - Py_INCREF(result); - } else { -#else - result = PyObject_GetItem(__pyx_d, name); - if (!result) { - PyErr_Clear(); -#endif - result = __Pyx_GetBuiltinName(name); - } - return result; -} - #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { PyObject *result; @@ -5009,55 +5105,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg } #endif -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { - PyObject *self, *result; - PyCFunction cfunc; - cfunc = PyCFunction_GET_FUNCTION(func); - self = PyCFunction_GET_SELF(func); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = cfunc(self, arg); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -#if CYTHON_COMPILING_IN_CPYTHON -static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_New(1); - if (unlikely(!args)) return NULL; - Py_INCREF(arg); - PyTuple_SET_ITEM(args, 0, arg); - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { -#ifdef __Pyx_CyFunction_USED - if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) { -#else - if (likely(PyCFunction_Check(func))) { -#endif - if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { - return __Pyx_PyObject_CallMethO(func, arg); - } - } - return __Pyx__PyObject_CallOneArg(func, arg); -} -#else -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject* args = PyTuple_Pack(1, arg); - return (likely(args)) ? __Pyx_PyObject_Call(func, args, NULL) : NULL; -} -#endif - #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, CYTHON_UNUSED PyObject *cause) { @@ -5132,10 +5179,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject if (value && PyExceptionInstance_Check(value)) { instance_class = (PyObject*) Py_TYPE(value); if (instance_class != type) { - if (PyObject_IsSubclass(instance_class, type)) { - type = instance_class; - } else { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; } } } @@ -5193,6 +5243,13 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject } PyErr_SetObject(type, value); if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { @@ -5200,6 +5257,7 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } +#endif } bad: Py_XDECREF(owned_instance); @@ -5240,7 +5298,7 @@ static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int co return count; } while (start < end) { - mid = (start + end) / 2; + mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { @@ -5414,29 +5472,33 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif - #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \ - { \ - func_type value = func_value; \ - if (sizeof(target_type) < sizeof(func_type)) { \ - if (unlikely(value != (func_type) (target_type) value)) { \ - func_type zero = 0; \ - if (is_unsigned && unlikely(value < zero)) \ - goto raise_neg_overflow; \ - else \ - goto raise_overflow; \ - } \ - } \ - return (target_type) value; \ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ } -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS #include "longintrepr.h" - #endif #endif static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { - const int neg_one = (int) -1, const_zero = 0; + const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -5453,36 +5515,125 @@ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(int) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) -(((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) -(((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) -(((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x)) - } else if (sizeof(int) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -5531,21 +5682,21 @@ raise_neg_overflow: } static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { - const int neg_one = (int) -1, const_zero = 0; + const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(int) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); } } { @@ -5796,22 +5947,48 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { #endif #endif +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { + const enum NPY_TYPES neg_one = (enum NPY_TYPES) -1, const_zero = (enum NPY_TYPES) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(enum NPY_TYPES) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); + } + } else { + if (sizeof(enum NPY_TYPES) <= sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES), + little, !is_unsigned); + } +} + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { - const long neg_one = (long) -1, const_zero = 0; + const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(long) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); } } { @@ -5823,7 +6000,7 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { } static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { - const long neg_one = (long) -1, const_zero = 0; + const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { @@ -5840,36 +6017,125 @@ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]); + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif +#if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x)) - } else if (sizeof(long) <= sizeof(unsigned long long)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { -#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { - case 0: return 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +(((PyLongObject*)x)->ob_digit[0])); - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) digits[0]) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) -(((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) -(((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) -(((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + } + break; } - #endif #endif if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x)) - } else if (sizeof(long) <= sizeof(long long)) { - __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x)) + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { @@ -6051,7 +6317,7 @@ static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && @@ -6092,7 +6358,7 @@ static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_ #endif } else #endif -#if !CYTHON_COMPILING_IN_PYPY +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); @@ -6122,7 +6388,7 @@ static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) { #else if (PyLong_Check(x)) #endif - return Py_INCREF(x), x; + return __Pyx_NewRef(x); m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { @@ -6162,18 +6428,55 @@ static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(b))) - return PyInt_AS_LONG(b); + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(x); + } #endif if (likely(PyLong_CheckExact(b))) { - #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 - #if CYTHON_USE_PYLONG_INTERNALS - switch (Py_SIZE(b)) { - case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0]; - case 0: return 0; - case 1: return ((PyLongObject*)b)->ob_digit[0]; - } - #endif + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | digits[2]) << PyLong_SHIFT) | digits[1]) << PyLong_SHIFT) | digits[0])); + } + break; + } + } #endif return PyLong_AsSsize_t(b); } diff --git a/GPy/util/linalg_cython.pyx b/GPy/util/linalg_cython.pyx index 72252bd9..748f45a8 100644 --- a/GPy/util/linalg_cython.pyx +++ b/GPy/util/linalg_cython.pyx @@ -1,3 +1,4 @@ +from libc.math cimport sqrt cimport numpy as np from cpython cimport bool import cython @@ -19,16 +20,18 @@ def symmetrify(np.ndarray[double, ndim=2] A, bool upper): @cython.boundscheck(False) @cython.wraparound(False) @cython.nonecheck(False) +@cython.cdivision(True) def cholupdate(np.ndarray[double, ndim=1] x, np.ndarray[double, ndim=2] L, int N): - cdef double r - cdef double c - cdef double s - for j in xrange(N): - r = np.sqrt(L[j,j]*L[j,j] + x[j]*x[j]) - c = r / L[j,j] - s = x[j] / L[j,j] - L[j,j] = r - for i in xrange(j): - L[i,j] = (L[i,j] + s*x[i])/c - x[i] = c*x[i] - s*L[i,j]; - r = np.sqrt(L[j,j]) + cdef double r, c, s + cdef int j, i + + with nogil: + for j in xrange(N): + r = sqrt(L[j, j] * L[j, j] + x[j] * x[j]) + c = r / L[j, j] + s = x[j] / L[j, j] + L[j, j] = r + for i in xrange(j): + L[i, j] = (L[i, j] + s * x[i]) / c + x[i] = c * x[i] - s * L[i, j] + r = sqrt(L[j, j]) diff --git a/GPy/util/linalg_gpu.py b/GPy/util/linalg_gpu.py index cba09dd3..db1c5317 100644 --- a/GPy/util/linalg_gpu.py +++ b/GPy/util/linalg_gpu.py @@ -61,12 +61,5 @@ try: except: pass -try: - import scikits.cuda.linalg as culinalg - from scikits.cuda import cublas - from scikits.cuda.cula import culaExceptions -except: - pass - diff --git a/GPy/util/ln_diff_erfs.py b/GPy/util/ln_diff_erfs.py index c1137283..77610c63 100644 --- a/GPy/util/ln_diff_erfs.py +++ b/GPy/util/ln_diff_erfs.py @@ -2,12 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) #Only works for scipy 0.12+ -try: - from scipy.special import erfcx, erf -except ImportError: - from scipy.special import erf - from .erfcx import erfcx - +from scipy.special import erfcx, erf import numpy as np def ln_diff_erfs(x1, x2, return_sign=False): @@ -17,7 +12,7 @@ def ln_diff_erfs(x1, x2, return_sign=False): :param x2 : argument of the negative erf :type x2: ndarray :return: tuple containing (log(abs(erf(x1) - erf(x2))), sign(erf(x1) - erf(x2))) - + Based on MATLAB code that was written by Antti Honkela and modified by David Luengo and originally derived from code by Neil Lawrence. """ x1 = np.require(x1).real @@ -26,7 +21,7 @@ def ln_diff_erfs(x1, x2, return_sign=False): x1 = np.reshape(x1, (1, 1)) if x2.size==1: x2 = np.reshape(x2, (1, 1)) - + if x1.shape==x2.shape: v = np.zeros_like(x1) else: @@ -36,7 +31,7 @@ def ln_diff_erfs(x1, x2, return_sign=False): v = np.zeros(x1.shape) else: raise ValueError("This function does not broadcast unless provided with a scalar.") - + if x1.size == 1: x1 = np.tile(x1, x2.shape) @@ -92,7 +87,7 @@ def ln_diff_erfs(x1, x2, return_sign=False): v[flags] = np.log(erfcx(-_x1) -erfcx(-_x2)*np.exp(_x1**2 -_x2**2))-_x1**2 - + # TODO: switch back on log of zero warnings. if return_sign: diff --git a/GPy/util/parallel.py b/GPy/util/parallel.py index 880dae58..a2211945 100644 --- a/GPy/util/parallel.py +++ b/GPy/util/parallel.py @@ -39,3 +39,22 @@ def divide_data(datanum, rank, size): size = datanum/size offset = size*rank+residue return offset, offset+size, datanum_list + +def optimize_parallel(model, optimizer=None, messages=True, max_iters=1000, outpath='.', interval=100, name=None): + from math import ceil + from datetime import datetime + import os + if name is None: name = model.name + stop = 0 + for iter in range(int(ceil(float(max_iters)/interval))): + model.optimize(optimizer=optimizer, messages= True if messages and model.mpi_comm.rank==model.mpi_root else False, max_iters=interval) + if model.mpi_comm.rank==model.mpi_root: + timenow = datetime.now() + timestr = timenow.strftime('%Y:%m:%d_%H:%M:%S') + model.save(os.path.join(outpath, name+'_'+timestr+'.h5')) + opt = model.optimization_runs[-1] + if opt.funct_eval Note: Right now the Ubuntu package index does not include scipy 0.16.0, and thus, cannot +> be used for GPy. We hope this gets fixed soon. + For the most part, the developers are using ubuntu. To install the required packages: sudo apt-get install python-numpy python-scipy python-matplotlib @@ -80,10 +76,29 @@ clone this git repository and add it to your path: ### OSX -Everything appears to work out-of-the box using ![enthought](http://www.enthought.com) on osx Mavericks. Download/clone GPy, and then add GPy to your PYTHONPATH - git clone git@github.com:SheffieldML/GPy.git ~/SheffieldML - echo 'PYTHONPATH=$PYTHONPATH:~/SheffieldML' >> ~/.profile +We were working hard to make pre-built distributions ready. +You can now install GPy via pip on MacOSX using +[anaconda python distribution](http://continuum.io/downloads): + + conda update scipy + pip install gpy + +If this does not work, then you need to build GPy yourself, +using the [development toolkits](https://developer.apple.com/xcode/). +Download/clone GPy and run the build process: + + conda update scipy + git clone git@github.com:SheffieldML/GPy.git ~/GPy + cd ~/GPy + python setup.py install + +If you do not wish to build the C extensions (10 times speedup), +you can run the pure python installations, by just adding GPy +to your python path. + + echo 'PYTHONPATH=$PYTHONPATH:~/SheffieldML' >> ~/.profile + ### Compiling documentation: @@ -134,7 +149,9 @@ Run nosetests from the root directory of the repository: or from within IPython import GPy; GPy.tests() - + + + ## Funding Acknowledgements @@ -142,15 +159,12 @@ Current support for the GPy software is coming through the following projects. * [EU FP7-PEOPLE Project Ref 316861](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/mlpm/) "MLPM2012: Machine Learning for Personalized Medicine" -* [BBSRC Project No BB/K011197/1](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/recombinant/) "Linking recombinant gene sequence to protein product manufacturability using CHO cell genomic resources" - * MRC Special Training Fellowship "Bayesian models of expression in the transcriptome for clinical RNA-seq" -* [EU FP7-KBBE Project Ref 289434](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/biopredyn/) "From Data to Models: New Bioinformatics Methods and Tools for Data-Driven Predictive Dynamic Modelling in Biotechnological Applications" - * [EU FP7-ICT Project Ref 612139](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/wysiwyd/) "WYSIWYD: What You Say is What You Did" Previous support for the GPy software came from the following projects: - +* [BBSRC Project No BB/K011197/1](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/recombinant/) "Linking recombinant gene sequence to protein product manufacturability using CHO cell genomic resources" +* [EU FP7-KBBE Project Ref 289434](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/biopredyn/) "From Data to Models: New Bioinformatics Methods and Tools for Data-Driven Predictive Dynamic Modelling in Biotechnological Applications" * [BBSRC Project No BB/H018123/2](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/iterative/) "An iterative pipeline of computational modelling and experimental design for uncovering gene regulatory networks in vertebrates" * [Erasysbio](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/synergy/) "SYNERGY: Systems approach to gene regulation biology through nuclear receptors" diff --git a/benchmarks/boston_housing.py b/benchmarks/boston_housing.py deleted file mode 100644 index 0dcff082..00000000 --- a/benchmarks/boston_housing.py +++ /dev/null @@ -1,44 +0,0 @@ -import numpy as np -import GPy - -def load_housing_data(): - X = np.loadtxt('housing.data') - X, Y = X[:,:-1], X[:,-1:] - - #scale the X data - xmax, xmin = X.max(0), X.min(0) - X = (X-xmin)/(xmax-xmin) - - #loy the response - Y = np.log(Y) - return X, Y - -def fit_full_GP(): - X, Y = load_housing_data() - k = GPy.kern.RBF(X.shape[1], ARD=True) + GPy.kern.Linear(X.shape[1]) - m = GPy.models.GPRegression(X, Y, kernel=k) - m.optimize('bfgs', max_iters=400, gtol=0) - return m - -def fit_svgp_st(): - np.random.seed(0) - X, Y = load_housing_data() - - Z = X[np.random.permutation(X.shape[0])[:100]] - k = GPy.kern.RBF(X.shape[1], ARD=True) + GPy.kern.Linear(X.shape[1], ARD=True) + GPy.kern.White(1,0.01) + GPy.kern.Bias(1) - - lik = GPy.likelihoods.StudentT(deg_free=3.) - m = GPy.core.SVGP(X, Y, Z=Z, kernel=k, likelihood=lik) - [m.optimize('scg', max_iters=40, gtol=0, messages=1, xtol=0, ftol=0) for i in range(10)] - m.optimize('bfgs', max_iters=4000, gtol=0, messages=1, xtol=0, ftol=0) - return m - - - - - - -if __name__=="__main__": - import timeit - - diff --git a/benchmarks/housing.data b/benchmarks/housing.data deleted file mode 100644 index f83ac564..00000000 --- a/benchmarks/housing.data +++ /dev/null @@ -1,506 +0,0 @@ - 0.00632 18.00 2.310 0 0.5380 6.5750 65.20 4.0900 1 296.0 15.30 396.90 4.98 24.00 - 0.02731 0.00 7.070 0 0.4690 6.4210 78.90 4.9671 2 242.0 17.80 396.90 9.14 21.60 - 0.02729 0.00 7.070 0 0.4690 7.1850 61.10 4.9671 2 242.0 17.80 392.83 4.03 34.70 - 0.03237 0.00 2.180 0 0.4580 6.9980 45.80 6.0622 3 222.0 18.70 394.63 2.94 33.40 - 0.06905 0.00 2.180 0 0.4580 7.1470 54.20 6.0622 3 222.0 18.70 396.90 5.33 36.20 - 0.02985 0.00 2.180 0 0.4580 6.4300 58.70 6.0622 3 222.0 18.70 394.12 5.21 28.70 - 0.08829 12.50 7.870 0 0.5240 6.0120 66.60 5.5605 5 311.0 15.20 395.60 12.43 22.90 - 0.14455 12.50 7.870 0 0.5240 6.1720 96.10 5.9505 5 311.0 15.20 396.90 19.15 27.10 - 0.21124 12.50 7.870 0 0.5240 5.6310 100.00 6.0821 5 311.0 15.20 386.63 29.93 16.50 - 0.17004 12.50 7.870 0 0.5240 6.0040 85.90 6.5921 5 311.0 15.20 386.71 17.10 18.90 - 0.22489 12.50 7.870 0 0.5240 6.3770 94.30 6.3467 5 311.0 15.20 392.52 20.45 15.00 - 0.11747 12.50 7.870 0 0.5240 6.0090 82.90 6.2267 5 311.0 15.20 396.90 13.27 18.90 - 0.09378 12.50 7.870 0 0.5240 5.8890 39.00 5.4509 5 311.0 15.20 390.50 15.71 21.70 - 0.62976 0.00 8.140 0 0.5380 5.9490 61.80 4.7075 4 307.0 21.00 396.90 8.26 20.40 - 0.63796 0.00 8.140 0 0.5380 6.0960 84.50 4.4619 4 307.0 21.00 380.02 10.26 18.20 - 0.62739 0.00 8.140 0 0.5380 5.8340 56.50 4.4986 4 307.0 21.00 395.62 8.47 19.90 - 1.05393 0.00 8.140 0 0.5380 5.9350 29.30 4.4986 4 307.0 21.00 386.85 6.58 23.10 - 0.78420 0.00 8.140 0 0.5380 5.9900 81.70 4.2579 4 307.0 21.00 386.75 14.67 17.50 - 0.80271 0.00 8.140 0 0.5380 5.4560 36.60 3.7965 4 307.0 21.00 288.99 11.69 20.20 - 0.72580 0.00 8.140 0 0.5380 5.7270 69.50 3.7965 4 307.0 21.00 390.95 11.28 18.20 - 1.25179 0.00 8.140 0 0.5380 5.5700 98.10 3.7979 4 307.0 21.00 376.57 21.02 13.60 - 0.85204 0.00 8.140 0 0.5380 5.9650 89.20 4.0123 4 307.0 21.00 392.53 13.83 19.60 - 1.23247 0.00 8.140 0 0.5380 6.1420 91.70 3.9769 4 307.0 21.00 396.90 18.72 15.20 - 0.98843 0.00 8.140 0 0.5380 5.8130 100.00 4.0952 4 307.0 21.00 394.54 19.88 14.50 - 0.75026 0.00 8.140 0 0.5380 5.9240 94.10 4.3996 4 307.0 21.00 394.33 16.30 15.60 - 0.84054 0.00 8.140 0 0.5380 5.5990 85.70 4.4546 4 307.0 21.00 303.42 16.51 13.90 - 0.67191 0.00 8.140 0 0.5380 5.8130 90.30 4.6820 4 307.0 21.00 376.88 14.81 16.60 - 0.95577 0.00 8.140 0 0.5380 6.0470 88.80 4.4534 4 307.0 21.00 306.38 17.28 14.80 - 0.77299 0.00 8.140 0 0.5380 6.4950 94.40 4.4547 4 307.0 21.00 387.94 12.80 18.40 - 1.00245 0.00 8.140 0 0.5380 6.6740 87.30 4.2390 4 307.0 21.00 380.23 11.98 21.00 - 1.13081 0.00 8.140 0 0.5380 5.7130 94.10 4.2330 4 307.0 21.00 360.17 22.60 12.70 - 1.35472 0.00 8.140 0 0.5380 6.0720 100.00 4.1750 4 307.0 21.00 376.73 13.04 14.50 - 1.38799 0.00 8.140 0 0.5380 5.9500 82.00 3.9900 4 307.0 21.00 232.60 27.71 13.20 - 1.15172 0.00 8.140 0 0.5380 5.7010 95.00 3.7872 4 307.0 21.00 358.77 18.35 13.10 - 1.61282 0.00 8.140 0 0.5380 6.0960 96.90 3.7598 4 307.0 21.00 248.31 20.34 13.50 - 0.06417 0.00 5.960 0 0.4990 5.9330 68.20 3.3603 5 279.0 19.20 396.90 9.68 18.90 - 0.09744 0.00 5.960 0 0.4990 5.8410 61.40 3.3779 5 279.0 19.20 377.56 11.41 20.00 - 0.08014 0.00 5.960 0 0.4990 5.8500 41.50 3.9342 5 279.0 19.20 396.90 8.77 21.00 - 0.17505 0.00 5.960 0 0.4990 5.9660 30.20 3.8473 5 279.0 19.20 393.43 10.13 24.70 - 0.02763 75.00 2.950 0 0.4280 6.5950 21.80 5.4011 3 252.0 18.30 395.63 4.32 30.80 - 0.03359 75.00 2.950 0 0.4280 7.0240 15.80 5.4011 3 252.0 18.30 395.62 1.98 34.90 - 0.12744 0.00 6.910 0 0.4480 6.7700 2.90 5.7209 3 233.0 17.90 385.41 4.84 26.60 - 0.14150 0.00 6.910 0 0.4480 6.1690 6.60 5.7209 3 233.0 17.90 383.37 5.81 25.30 - 0.15936 0.00 6.910 0 0.4480 6.2110 6.50 5.7209 3 233.0 17.90 394.46 7.44 24.70 - 0.12269 0.00 6.910 0 0.4480 6.0690 40.00 5.7209 3 233.0 17.90 389.39 9.55 21.20 - 0.17142 0.00 6.910 0 0.4480 5.6820 33.80 5.1004 3 233.0 17.90 396.90 10.21 19.30 - 0.18836 0.00 6.910 0 0.4480 5.7860 33.30 5.1004 3 233.0 17.90 396.90 14.15 20.00 - 0.22927 0.00 6.910 0 0.4480 6.0300 85.50 5.6894 3 233.0 17.90 392.74 18.80 16.60 - 0.25387 0.00 6.910 0 0.4480 5.3990 95.30 5.8700 3 233.0 17.90 396.90 30.81 14.40 - 0.21977 0.00 6.910 0 0.4480 5.6020 62.00 6.0877 3 233.0 17.90 396.90 16.20 19.40 - 0.08873 21.00 5.640 0 0.4390 5.9630 45.70 6.8147 4 243.0 16.80 395.56 13.45 19.70 - 0.04337 21.00 5.640 0 0.4390 6.1150 63.00 6.8147 4 243.0 16.80 393.97 9.43 20.50 - 0.05360 21.00 5.640 0 0.4390 6.5110 21.10 6.8147 4 243.0 16.80 396.90 5.28 25.00 - 0.04981 21.00 5.640 0 0.4390 5.9980 21.40 6.8147 4 243.0 16.80 396.90 8.43 23.40 - 0.01360 75.00 4.000 0 0.4100 5.8880 47.60 7.3197 3 469.0 21.10 396.90 14.80 18.90 - 0.01311 90.00 1.220 0 0.4030 7.2490 21.90 8.6966 5 226.0 17.90 395.93 4.81 35.40 - 0.02055 85.00 0.740 0 0.4100 6.3830 35.70 9.1876 2 313.0 17.30 396.90 5.77 24.70 - 0.01432 100.00 1.320 0 0.4110 6.8160 40.50 8.3248 5 256.0 15.10 392.90 3.95 31.60 - 0.15445 25.00 5.130 0 0.4530 6.1450 29.20 7.8148 8 284.0 19.70 390.68 6.86 23.30 - 0.10328 25.00 5.130 0 0.4530 5.9270 47.20 6.9320 8 284.0 19.70 396.90 9.22 19.60 - 0.14932 25.00 5.130 0 0.4530 5.7410 66.20 7.2254 8 284.0 19.70 395.11 13.15 18.70 - 0.17171 25.00 5.130 0 0.4530 5.9660 93.40 6.8185 8 284.0 19.70 378.08 14.44 16.00 - 0.11027 25.00 5.130 0 0.4530 6.4560 67.80 7.2255 8 284.0 19.70 396.90 6.73 22.20 - 0.12650 25.00 5.130 0 0.4530 6.7620 43.40 7.9809 8 284.0 19.70 395.58 9.50 25.00 - 0.01951 17.50 1.380 0 0.4161 7.1040 59.50 9.2229 3 216.0 18.60 393.24 8.05 33.00 - 0.03584 80.00 3.370 0 0.3980 6.2900 17.80 6.6115 4 337.0 16.10 396.90 4.67 23.50 - 0.04379 80.00 3.370 0 0.3980 5.7870 31.10 6.6115 4 337.0 16.10 396.90 10.24 19.40 - 0.05789 12.50 6.070 0 0.4090 5.8780 21.40 6.4980 4 345.0 18.90 396.21 8.10 22.00 - 0.13554 12.50 6.070 0 0.4090 5.5940 36.80 6.4980 4 345.0 18.90 396.90 13.09 17.40 - 0.12816 12.50 6.070 0 0.4090 5.8850 33.00 6.4980 4 345.0 18.90 396.90 8.79 20.90 - 0.08826 0.00 10.810 0 0.4130 6.4170 6.60 5.2873 4 305.0 19.20 383.73 6.72 24.20 - 0.15876 0.00 10.810 0 0.4130 5.9610 17.50 5.2873 4 305.0 19.20 376.94 9.88 21.70 - 0.09164 0.00 10.810 0 0.4130 6.0650 7.80 5.2873 4 305.0 19.20 390.91 5.52 22.80 - 0.19539 0.00 10.810 0 0.4130 6.2450 6.20 5.2873 4 305.0 19.20 377.17 7.54 23.40 - 0.07896 0.00 12.830 0 0.4370 6.2730 6.00 4.2515 5 398.0 18.70 394.92 6.78 24.10 - 0.09512 0.00 12.830 0 0.4370 6.2860 45.00 4.5026 5 398.0 18.70 383.23 8.94 21.40 - 0.10153 0.00 12.830 0 0.4370 6.2790 74.50 4.0522 5 398.0 18.70 373.66 11.97 20.00 - 0.08707 0.00 12.830 0 0.4370 6.1400 45.80 4.0905 5 398.0 18.70 386.96 10.27 20.80 - 0.05646 0.00 12.830 0 0.4370 6.2320 53.70 5.0141 5 398.0 18.70 386.40 12.34 21.20 - 0.08387 0.00 12.830 0 0.4370 5.8740 36.60 4.5026 5 398.0 18.70 396.06 9.10 20.30 - 0.04113 25.00 4.860 0 0.4260 6.7270 33.50 5.4007 4 281.0 19.00 396.90 5.29 28.00 - 0.04462 25.00 4.860 0 0.4260 6.6190 70.40 5.4007 4 281.0 19.00 395.63 7.22 23.90 - 0.03659 25.00 4.860 0 0.4260 6.3020 32.20 5.4007 4 281.0 19.00 396.90 6.72 24.80 - 0.03551 25.00 4.860 0 0.4260 6.1670 46.70 5.4007 4 281.0 19.00 390.64 7.51 22.90 - 0.05059 0.00 4.490 0 0.4490 6.3890 48.00 4.7794 3 247.0 18.50 396.90 9.62 23.90 - 0.05735 0.00 4.490 0 0.4490 6.6300 56.10 4.4377 3 247.0 18.50 392.30 6.53 26.60 - 0.05188 0.00 4.490 0 0.4490 6.0150 45.10 4.4272 3 247.0 18.50 395.99 12.86 22.50 - 0.07151 0.00 4.490 0 0.4490 6.1210 56.80 3.7476 3 247.0 18.50 395.15 8.44 22.20 - 0.05660 0.00 3.410 0 0.4890 7.0070 86.30 3.4217 2 270.0 17.80 396.90 5.50 23.60 - 0.05302 0.00 3.410 0 0.4890 7.0790 63.10 3.4145 2 270.0 17.80 396.06 5.70 28.70 - 0.04684 0.00 3.410 0 0.4890 6.4170 66.10 3.0923 2 270.0 17.80 392.18 8.81 22.60 - 0.03932 0.00 3.410 0 0.4890 6.4050 73.90 3.0921 2 270.0 17.80 393.55 8.20 22.00 - 0.04203 28.00 15.040 0 0.4640 6.4420 53.60 3.6659 4 270.0 18.20 395.01 8.16 22.90 - 0.02875 28.00 15.040 0 0.4640 6.2110 28.90 3.6659 4 270.0 18.20 396.33 6.21 25.00 - 0.04294 28.00 15.040 0 0.4640 6.2490 77.30 3.6150 4 270.0 18.20 396.90 10.59 20.60 - 0.12204 0.00 2.890 0 0.4450 6.6250 57.80 3.4952 2 276.0 18.00 357.98 6.65 28.40 - 0.11504 0.00 2.890 0 0.4450 6.1630 69.60 3.4952 2 276.0 18.00 391.83 11.34 21.40 - 0.12083 0.00 2.890 0 0.4450 8.0690 76.00 3.4952 2 276.0 18.00 396.90 4.21 38.70 - 0.08187 0.00 2.890 0 0.4450 7.8200 36.90 3.4952 2 276.0 18.00 393.53 3.57 43.80 - 0.06860 0.00 2.890 0 0.4450 7.4160 62.50 3.4952 2 276.0 18.00 396.90 6.19 33.20 - 0.14866 0.00 8.560 0 0.5200 6.7270 79.90 2.7778 5 384.0 20.90 394.76 9.42 27.50 - 0.11432 0.00 8.560 0 0.5200 6.7810 71.30 2.8561 5 384.0 20.90 395.58 7.67 26.50 - 0.22876 0.00 8.560 0 0.5200 6.4050 85.40 2.7147 5 384.0 20.90 70.80 10.63 18.60 - 0.21161 0.00 8.560 0 0.5200 6.1370 87.40 2.7147 5 384.0 20.90 394.47 13.44 19.30 - 0.13960 0.00 8.560 0 0.5200 6.1670 90.00 2.4210 5 384.0 20.90 392.69 12.33 20.10 - 0.13262 0.00 8.560 0 0.5200 5.8510 96.70 2.1069 5 384.0 20.90 394.05 16.47 19.50 - 0.17120 0.00 8.560 0 0.5200 5.8360 91.90 2.2110 5 384.0 20.90 395.67 18.66 19.50 - 0.13117 0.00 8.560 0 0.5200 6.1270 85.20 2.1224 5 384.0 20.90 387.69 14.09 20.40 - 0.12802 0.00 8.560 0 0.5200 6.4740 97.10 2.4329 5 384.0 20.90 395.24 12.27 19.80 - 0.26363 0.00 8.560 0 0.5200 6.2290 91.20 2.5451 5 384.0 20.90 391.23 15.55 19.40 - 0.10793 0.00 8.560 0 0.5200 6.1950 54.40 2.7778 5 384.0 20.90 393.49 13.00 21.70 - 0.10084 0.00 10.010 0 0.5470 6.7150 81.60 2.6775 6 432.0 17.80 395.59 10.16 22.80 - 0.12329 0.00 10.010 0 0.5470 5.9130 92.90 2.3534 6 432.0 17.80 394.95 16.21 18.80 - 0.22212 0.00 10.010 0 0.5470 6.0920 95.40 2.5480 6 432.0 17.80 396.90 17.09 18.70 - 0.14231 0.00 10.010 0 0.5470 6.2540 84.20 2.2565 6 432.0 17.80 388.74 10.45 18.50 - 0.17134 0.00 10.010 0 0.5470 5.9280 88.20 2.4631 6 432.0 17.80 344.91 15.76 18.30 - 0.13158 0.00 10.010 0 0.5470 6.1760 72.50 2.7301 6 432.0 17.80 393.30 12.04 21.20 - 0.15098 0.00 10.010 0 0.5470 6.0210 82.60 2.7474 6 432.0 17.80 394.51 10.30 19.20 - 0.13058 0.00 10.010 0 0.5470 5.8720 73.10 2.4775 6 432.0 17.80 338.63 15.37 20.40 - 0.14476 0.00 10.010 0 0.5470 5.7310 65.20 2.7592 6 432.0 17.80 391.50 13.61 19.30 - 0.06899 0.00 25.650 0 0.5810 5.8700 69.70 2.2577 2 188.0 19.10 389.15 14.37 22.00 - 0.07165 0.00 25.650 0 0.5810 6.0040 84.10 2.1974 2 188.0 19.10 377.67 14.27 20.30 - 0.09299 0.00 25.650 0 0.5810 5.9610 92.90 2.0869 2 188.0 19.10 378.09 17.93 20.50 - 0.15038 0.00 25.650 0 0.5810 5.8560 97.00 1.9444 2 188.0 19.10 370.31 25.41 17.30 - 0.09849 0.00 25.650 0 0.5810 5.8790 95.80 2.0063 2 188.0 19.10 379.38 17.58 18.80 - 0.16902 0.00 25.650 0 0.5810 5.9860 88.40 1.9929 2 188.0 19.10 385.02 14.81 21.40 - 0.38735 0.00 25.650 0 0.5810 5.6130 95.60 1.7572 2 188.0 19.10 359.29 27.26 15.70 - 0.25915 0.00 21.890 0 0.6240 5.6930 96.00 1.7883 4 437.0 21.20 392.11 17.19 16.20 - 0.32543 0.00 21.890 0 0.6240 6.4310 98.80 1.8125 4 437.0 21.20 396.90 15.39 18.00 - 0.88125 0.00 21.890 0 0.6240 5.6370 94.70 1.9799 4 437.0 21.20 396.90 18.34 14.30 - 0.34006 0.00 21.890 0 0.6240 6.4580 98.90 2.1185 4 437.0 21.20 395.04 12.60 19.20 - 1.19294 0.00 21.890 0 0.6240 6.3260 97.70 2.2710 4 437.0 21.20 396.90 12.26 19.60 - 0.59005 0.00 21.890 0 0.6240 6.3720 97.90 2.3274 4 437.0 21.20 385.76 11.12 23.00 - 0.32982 0.00 21.890 0 0.6240 5.8220 95.40 2.4699 4 437.0 21.20 388.69 15.03 18.40 - 0.97617 0.00 21.890 0 0.6240 5.7570 98.40 2.3460 4 437.0 21.20 262.76 17.31 15.60 - 0.55778 0.00 21.890 0 0.6240 6.3350 98.20 2.1107 4 437.0 21.20 394.67 16.96 18.10 - 0.32264 0.00 21.890 0 0.6240 5.9420 93.50 1.9669 4 437.0 21.20 378.25 16.90 17.40 - 0.35233 0.00 21.890 0 0.6240 6.4540 98.40 1.8498 4 437.0 21.20 394.08 14.59 17.10 - 0.24980 0.00 21.890 0 0.6240 5.8570 98.20 1.6686 4 437.0 21.20 392.04 21.32 13.30 - 0.54452 0.00 21.890 0 0.6240 6.1510 97.90 1.6687 4 437.0 21.20 396.90 18.46 17.80 - 0.29090 0.00 21.890 0 0.6240 6.1740 93.60 1.6119 4 437.0 21.20 388.08 24.16 14.00 - 1.62864 0.00 21.890 0 0.6240 5.0190 100.00 1.4394 4 437.0 21.20 396.90 34.41 14.40 - 3.32105 0.00 19.580 1 0.8710 5.4030 100.00 1.3216 5 403.0 14.70 396.90 26.82 13.40 - 4.09740 0.00 19.580 0 0.8710 5.4680 100.00 1.4118 5 403.0 14.70 396.90 26.42 15.60 - 2.77974 0.00 19.580 0 0.8710 4.9030 97.80 1.3459 5 403.0 14.70 396.90 29.29 11.80 - 2.37934 0.00 19.580 0 0.8710 6.1300 100.00 1.4191 5 403.0 14.70 172.91 27.80 13.80 - 2.15505 0.00 19.580 0 0.8710 5.6280 100.00 1.5166 5 403.0 14.70 169.27 16.65 15.60 - 2.36862 0.00 19.580 0 0.8710 4.9260 95.70 1.4608 5 403.0 14.70 391.71 29.53 14.60 - 2.33099 0.00 19.580 0 0.8710 5.1860 93.80 1.5296 5 403.0 14.70 356.99 28.32 17.80 - 2.73397 0.00 19.580 0 0.8710 5.5970 94.90 1.5257 5 403.0 14.70 351.85 21.45 15.40 - 1.65660 0.00 19.580 0 0.8710 6.1220 97.30 1.6180 5 403.0 14.70 372.80 14.10 21.50 - 1.49632 0.00 19.580 0 0.8710 5.4040 100.00 1.5916 5 403.0 14.70 341.60 13.28 19.60 - 1.12658 0.00 19.580 1 0.8710 5.0120 88.00 1.6102 5 403.0 14.70 343.28 12.12 15.30 - 2.14918 0.00 19.580 0 0.8710 5.7090 98.50 1.6232 5 403.0 14.70 261.95 15.79 19.40 - 1.41385 0.00 19.580 1 0.8710 6.1290 96.00 1.7494 5 403.0 14.70 321.02 15.12 17.00 - 3.53501 0.00 19.580 1 0.8710 6.1520 82.60 1.7455 5 403.0 14.70 88.01 15.02 15.60 - 2.44668 0.00 19.580 0 0.8710 5.2720 94.00 1.7364 5 403.0 14.70 88.63 16.14 13.10 - 1.22358 0.00 19.580 0 0.6050 6.9430 97.40 1.8773 5 403.0 14.70 363.43 4.59 41.30 - 1.34284 0.00 19.580 0 0.6050 6.0660 100.00 1.7573 5 403.0 14.70 353.89 6.43 24.30 - 1.42502 0.00 19.580 0 0.8710 6.5100 100.00 1.7659 5 403.0 14.70 364.31 7.39 23.30 - 1.27346 0.00 19.580 1 0.6050 6.2500 92.60 1.7984 5 403.0 14.70 338.92 5.50 27.00 - 1.46336 0.00 19.580 0 0.6050 7.4890 90.80 1.9709 5 403.0 14.70 374.43 1.73 50.00 - 1.83377 0.00 19.580 1 0.6050 7.8020 98.20 2.0407 5 403.0 14.70 389.61 1.92 50.00 - 1.51902 0.00 19.580 1 0.6050 8.3750 93.90 2.1620 5 403.0 14.70 388.45 3.32 50.00 - 2.24236 0.00 19.580 0 0.6050 5.8540 91.80 2.4220 5 403.0 14.70 395.11 11.64 22.70 - 2.92400 0.00 19.580 0 0.6050 6.1010 93.00 2.2834 5 403.0 14.70 240.16 9.81 25.00 - 2.01019 0.00 19.580 0 0.6050 7.9290 96.20 2.0459 5 403.0 14.70 369.30 3.70 50.00 - 1.80028 0.00 19.580 0 0.6050 5.8770 79.20 2.4259 5 403.0 14.70 227.61 12.14 23.80 - 2.30040 0.00 19.580 0 0.6050 6.3190 96.10 2.1000 5 403.0 14.70 297.09 11.10 23.80 - 2.44953 0.00 19.580 0 0.6050 6.4020 95.20 2.2625 5 403.0 14.70 330.04 11.32 22.30 - 1.20742 0.00 19.580 0 0.6050 5.8750 94.60 2.4259 5 403.0 14.70 292.29 14.43 17.40 - 2.31390 0.00 19.580 0 0.6050 5.8800 97.30 2.3887 5 403.0 14.70 348.13 12.03 19.10 - 0.13914 0.00 4.050 0 0.5100 5.5720 88.50 2.5961 5 296.0 16.60 396.90 14.69 23.10 - 0.09178 0.00 4.050 0 0.5100 6.4160 84.10 2.6463 5 296.0 16.60 395.50 9.04 23.60 - 0.08447 0.00 4.050 0 0.5100 5.8590 68.70 2.7019 5 296.0 16.60 393.23 9.64 22.60 - 0.06664 0.00 4.050 0 0.5100 6.5460 33.10 3.1323 5 296.0 16.60 390.96 5.33 29.40 - 0.07022 0.00 4.050 0 0.5100 6.0200 47.20 3.5549 5 296.0 16.60 393.23 10.11 23.20 - 0.05425 0.00 4.050 0 0.5100 6.3150 73.40 3.3175 5 296.0 16.60 395.60 6.29 24.60 - 0.06642 0.00 4.050 0 0.5100 6.8600 74.40 2.9153 5 296.0 16.60 391.27 6.92 29.90 - 0.05780 0.00 2.460 0 0.4880 6.9800 58.40 2.8290 3 193.0 17.80 396.90 5.04 37.20 - 0.06588 0.00 2.460 0 0.4880 7.7650 83.30 2.7410 3 193.0 17.80 395.56 7.56 39.80 - 0.06888 0.00 2.460 0 0.4880 6.1440 62.20 2.5979 3 193.0 17.80 396.90 9.45 36.20 - 0.09103 0.00 2.460 0 0.4880 7.1550 92.20 2.7006 3 193.0 17.80 394.12 4.82 37.90 - 0.10008 0.00 2.460 0 0.4880 6.5630 95.60 2.8470 3 193.0 17.80 396.90 5.68 32.50 - 0.08308 0.00 2.460 0 0.4880 5.6040 89.80 2.9879 3 193.0 17.80 391.00 13.98 26.40 - 0.06047 0.00 2.460 0 0.4880 6.1530 68.80 3.2797 3 193.0 17.80 387.11 13.15 29.60 - 0.05602 0.00 2.460 0 0.4880 7.8310 53.60 3.1992 3 193.0 17.80 392.63 4.45 50.00 - 0.07875 45.00 3.440 0 0.4370 6.7820 41.10 3.7886 5 398.0 15.20 393.87 6.68 32.00 - 0.12579 45.00 3.440 0 0.4370 6.5560 29.10 4.5667 5 398.0 15.20 382.84 4.56 29.80 - 0.08370 45.00 3.440 0 0.4370 7.1850 38.90 4.5667 5 398.0 15.20 396.90 5.39 34.90 - 0.09068 45.00 3.440 0 0.4370 6.9510 21.50 6.4798 5 398.0 15.20 377.68 5.10 37.00 - 0.06911 45.00 3.440 0 0.4370 6.7390 30.80 6.4798 5 398.0 15.20 389.71 4.69 30.50 - 0.08664 45.00 3.440 0 0.4370 7.1780 26.30 6.4798 5 398.0 15.20 390.49 2.87 36.40 - 0.02187 60.00 2.930 0 0.4010 6.8000 9.90 6.2196 1 265.0 15.60 393.37 5.03 31.10 - 0.01439 60.00 2.930 0 0.4010 6.6040 18.80 6.2196 1 265.0 15.60 376.70 4.38 29.10 - 0.01381 80.00 0.460 0 0.4220 7.8750 32.00 5.6484 4 255.0 14.40 394.23 2.97 50.00 - 0.04011 80.00 1.520 0 0.4040 7.2870 34.10 7.3090 2 329.0 12.60 396.90 4.08 33.30 - 0.04666 80.00 1.520 0 0.4040 7.1070 36.60 7.3090 2 329.0 12.60 354.31 8.61 30.30 - 0.03768 80.00 1.520 0 0.4040 7.2740 38.30 7.3090 2 329.0 12.60 392.20 6.62 34.60 - 0.03150 95.00 1.470 0 0.4030 6.9750 15.30 7.6534 3 402.0 17.00 396.90 4.56 34.90 - 0.01778 95.00 1.470 0 0.4030 7.1350 13.90 7.6534 3 402.0 17.00 384.30 4.45 32.90 - 0.03445 82.50 2.030 0 0.4150 6.1620 38.40 6.2700 2 348.0 14.70 393.77 7.43 24.10 - 0.02177 82.50 2.030 0 0.4150 7.6100 15.70 6.2700 2 348.0 14.70 395.38 3.11 42.30 - 0.03510 95.00 2.680 0 0.4161 7.8530 33.20 5.1180 4 224.0 14.70 392.78 3.81 48.50 - 0.02009 95.00 2.680 0 0.4161 8.0340 31.90 5.1180 4 224.0 14.70 390.55 2.88 50.00 - 0.13642 0.00 10.590 0 0.4890 5.8910 22.30 3.9454 4 277.0 18.60 396.90 10.87 22.60 - 0.22969 0.00 10.590 0 0.4890 6.3260 52.50 4.3549 4 277.0 18.60 394.87 10.97 24.40 - 0.25199 0.00 10.590 0 0.4890 5.7830 72.70 4.3549 4 277.0 18.60 389.43 18.06 22.50 - 0.13587 0.00 10.590 1 0.4890 6.0640 59.10 4.2392 4 277.0 18.60 381.32 14.66 24.40 - 0.43571 0.00 10.590 1 0.4890 5.3440 100.00 3.8750 4 277.0 18.60 396.90 23.09 20.00 - 0.17446 0.00 10.590 1 0.4890 5.9600 92.10 3.8771 4 277.0 18.60 393.25 17.27 21.70 - 0.37578 0.00 10.590 1 0.4890 5.4040 88.60 3.6650 4 277.0 18.60 395.24 23.98 19.30 - 0.21719 0.00 10.590 1 0.4890 5.8070 53.80 3.6526 4 277.0 18.60 390.94 16.03 22.40 - 0.14052 0.00 10.590 0 0.4890 6.3750 32.30 3.9454 4 277.0 18.60 385.81 9.38 28.10 - 0.28955 0.00 10.590 0 0.4890 5.4120 9.80 3.5875 4 277.0 18.60 348.93 29.55 23.70 - 0.19802 0.00 10.590 0 0.4890 6.1820 42.40 3.9454 4 277.0 18.60 393.63 9.47 25.00 - 0.04560 0.00 13.890 1 0.5500 5.8880 56.00 3.1121 5 276.0 16.40 392.80 13.51 23.30 - 0.07013 0.00 13.890 0 0.5500 6.6420 85.10 3.4211 5 276.0 16.40 392.78 9.69 28.70 - 0.11069 0.00 13.890 1 0.5500 5.9510 93.80 2.8893 5 276.0 16.40 396.90 17.92 21.50 - 0.11425 0.00 13.890 1 0.5500 6.3730 92.40 3.3633 5 276.0 16.40 393.74 10.50 23.00 - 0.35809 0.00 6.200 1 0.5070 6.9510 88.50 2.8617 8 307.0 17.40 391.70 9.71 26.70 - 0.40771 0.00 6.200 1 0.5070 6.1640 91.30 3.0480 8 307.0 17.40 395.24 21.46 21.70 - 0.62356 0.00 6.200 1 0.5070 6.8790 77.70 3.2721 8 307.0 17.40 390.39 9.93 27.50 - 0.61470 0.00 6.200 0 0.5070 6.6180 80.80 3.2721 8 307.0 17.40 396.90 7.60 30.10 - 0.31533 0.00 6.200 0 0.5040 8.2660 78.30 2.8944 8 307.0 17.40 385.05 4.14 44.80 - 0.52693 0.00 6.200 0 0.5040 8.7250 83.00 2.8944 8 307.0 17.40 382.00 4.63 50.00 - 0.38214 0.00 6.200 0 0.5040 8.0400 86.50 3.2157 8 307.0 17.40 387.38 3.13 37.60 - 0.41238 0.00 6.200 0 0.5040 7.1630 79.90 3.2157 8 307.0 17.40 372.08 6.36 31.60 - 0.29819 0.00 6.200 0 0.5040 7.6860 17.00 3.3751 8 307.0 17.40 377.51 3.92 46.70 - 0.44178 0.00 6.200 0 0.5040 6.5520 21.40 3.3751 8 307.0 17.40 380.34 3.76 31.50 - 0.53700 0.00 6.200 0 0.5040 5.9810 68.10 3.6715 8 307.0 17.40 378.35 11.65 24.30 - 0.46296 0.00 6.200 0 0.5040 7.4120 76.90 3.6715 8 307.0 17.40 376.14 5.25 31.70 - 0.57529 0.00 6.200 0 0.5070 8.3370 73.30 3.8384 8 307.0 17.40 385.91 2.47 41.70 - 0.33147 0.00 6.200 0 0.5070 8.2470 70.40 3.6519 8 307.0 17.40 378.95 3.95 48.30 - 0.44791 0.00 6.200 1 0.5070 6.7260 66.50 3.6519 8 307.0 17.40 360.20 8.05 29.00 - 0.33045 0.00 6.200 0 0.5070 6.0860 61.50 3.6519 8 307.0 17.40 376.75 10.88 24.00 - 0.52058 0.00 6.200 1 0.5070 6.6310 76.50 4.1480 8 307.0 17.40 388.45 9.54 25.10 - 0.51183 0.00 6.200 0 0.5070 7.3580 71.60 4.1480 8 307.0 17.40 390.07 4.73 31.50 - 0.08244 30.00 4.930 0 0.4280 6.4810 18.50 6.1899 6 300.0 16.60 379.41 6.36 23.70 - 0.09252 30.00 4.930 0 0.4280 6.6060 42.20 6.1899 6 300.0 16.60 383.78 7.37 23.30 - 0.11329 30.00 4.930 0 0.4280 6.8970 54.30 6.3361 6 300.0 16.60 391.25 11.38 22.00 - 0.10612 30.00 4.930 0 0.4280 6.0950 65.10 6.3361 6 300.0 16.60 394.62 12.40 20.10 - 0.10290 30.00 4.930 0 0.4280 6.3580 52.90 7.0355 6 300.0 16.60 372.75 11.22 22.20 - 0.12757 30.00 4.930 0 0.4280 6.3930 7.80 7.0355 6 300.0 16.60 374.71 5.19 23.70 - 0.20608 22.00 5.860 0 0.4310 5.5930 76.50 7.9549 7 330.0 19.10 372.49 12.50 17.60 - 0.19133 22.00 5.860 0 0.4310 5.6050 70.20 7.9549 7 330.0 19.10 389.13 18.46 18.50 - 0.33983 22.00 5.860 0 0.4310 6.1080 34.90 8.0555 7 330.0 19.10 390.18 9.16 24.30 - 0.19657 22.00 5.860 0 0.4310 6.2260 79.20 8.0555 7 330.0 19.10 376.14 10.15 20.50 - 0.16439 22.00 5.860 0 0.4310 6.4330 49.10 7.8265 7 330.0 19.10 374.71 9.52 24.50 - 0.19073 22.00 5.860 0 0.4310 6.7180 17.50 7.8265 7 330.0 19.10 393.74 6.56 26.20 - 0.14030 22.00 5.860 0 0.4310 6.4870 13.00 7.3967 7 330.0 19.10 396.28 5.90 24.40 - 0.21409 22.00 5.860 0 0.4310 6.4380 8.90 7.3967 7 330.0 19.10 377.07 3.59 24.80 - 0.08221 22.00 5.860 0 0.4310 6.9570 6.80 8.9067 7 330.0 19.10 386.09 3.53 29.60 - 0.36894 22.00 5.860 0 0.4310 8.2590 8.40 8.9067 7 330.0 19.10 396.90 3.54 42.80 - 0.04819 80.00 3.640 0 0.3920 6.1080 32.00 9.2203 1 315.0 16.40 392.89 6.57 21.90 - 0.03548 80.00 3.640 0 0.3920 5.8760 19.10 9.2203 1 315.0 16.40 395.18 9.25 20.90 - 0.01538 90.00 3.750 0 0.3940 7.4540 34.20 6.3361 3 244.0 15.90 386.34 3.11 44.00 - 0.61154 20.00 3.970 0 0.6470 8.7040 86.90 1.8010 5 264.0 13.00 389.70 5.12 50.00 - 0.66351 20.00 3.970 0 0.6470 7.3330 100.00 1.8946 5 264.0 13.00 383.29 7.79 36.00 - 0.65665 20.00 3.970 0 0.6470 6.8420 100.00 2.0107 5 264.0 13.00 391.93 6.90 30.10 - 0.54011 20.00 3.970 0 0.6470 7.2030 81.80 2.1121 5 264.0 13.00 392.80 9.59 33.80 - 0.53412 20.00 3.970 0 0.6470 7.5200 89.40 2.1398 5 264.0 13.00 388.37 7.26 43.10 - 0.52014 20.00 3.970 0 0.6470 8.3980 91.50 2.2885 5 264.0 13.00 386.86 5.91 48.80 - 0.82526 20.00 3.970 0 0.6470 7.3270 94.50 2.0788 5 264.0 13.00 393.42 11.25 31.00 - 0.55007 20.00 3.970 0 0.6470 7.2060 91.60 1.9301 5 264.0 13.00 387.89 8.10 36.50 - 0.76162 20.00 3.970 0 0.6470 5.5600 62.80 1.9865 5 264.0 13.00 392.40 10.45 22.80 - 0.78570 20.00 3.970 0 0.6470 7.0140 84.60 2.1329 5 264.0 13.00 384.07 14.79 30.70 - 0.57834 20.00 3.970 0 0.5750 8.2970 67.00 2.4216 5 264.0 13.00 384.54 7.44 50.00 - 0.54050 20.00 3.970 0 0.5750 7.4700 52.60 2.8720 5 264.0 13.00 390.30 3.16 43.50 - 0.09065 20.00 6.960 1 0.4640 5.9200 61.50 3.9175 3 223.0 18.60 391.34 13.65 20.70 - 0.29916 20.00 6.960 0 0.4640 5.8560 42.10 4.4290 3 223.0 18.60 388.65 13.00 21.10 - 0.16211 20.00 6.960 0 0.4640 6.2400 16.30 4.4290 3 223.0 18.60 396.90 6.59 25.20 - 0.11460 20.00 6.960 0 0.4640 6.5380 58.70 3.9175 3 223.0 18.60 394.96 7.73 24.40 - 0.22188 20.00 6.960 1 0.4640 7.6910 51.80 4.3665 3 223.0 18.60 390.77 6.58 35.20 - 0.05644 40.00 6.410 1 0.4470 6.7580 32.90 4.0776 4 254.0 17.60 396.90 3.53 32.40 - 0.09604 40.00 6.410 0 0.4470 6.8540 42.80 4.2673 4 254.0 17.60 396.90 2.98 32.00 - 0.10469 40.00 6.410 1 0.4470 7.2670 49.00 4.7872 4 254.0 17.60 389.25 6.05 33.20 - 0.06127 40.00 6.410 1 0.4470 6.8260 27.60 4.8628 4 254.0 17.60 393.45 4.16 33.10 - 0.07978 40.00 6.410 0 0.4470 6.4820 32.10 4.1403 4 254.0 17.60 396.90 7.19 29.10 - 0.21038 20.00 3.330 0 0.4429 6.8120 32.20 4.1007 5 216.0 14.90 396.90 4.85 35.10 - 0.03578 20.00 3.330 0 0.4429 7.8200 64.50 4.6947 5 216.0 14.90 387.31 3.76 45.40 - 0.03705 20.00 3.330 0 0.4429 6.9680 37.20 5.2447 5 216.0 14.90 392.23 4.59 35.40 - 0.06129 20.00 3.330 1 0.4429 7.6450 49.70 5.2119 5 216.0 14.90 377.07 3.01 46.00 - 0.01501 90.00 1.210 1 0.4010 7.9230 24.80 5.8850 1 198.0 13.60 395.52 3.16 50.00 - 0.00906 90.00 2.970 0 0.4000 7.0880 20.80 7.3073 1 285.0 15.30 394.72 7.85 32.20 - 0.01096 55.00 2.250 0 0.3890 6.4530 31.90 7.3073 1 300.0 15.30 394.72 8.23 22.00 - 0.01965 80.00 1.760 0 0.3850 6.2300 31.50 9.0892 1 241.0 18.20 341.60 12.93 20.10 - 0.03871 52.50 5.320 0 0.4050 6.2090 31.30 7.3172 6 293.0 16.60 396.90 7.14 23.20 - 0.04590 52.50 5.320 0 0.4050 6.3150 45.60 7.3172 6 293.0 16.60 396.90 7.60 22.30 - 0.04297 52.50 5.320 0 0.4050 6.5650 22.90 7.3172 6 293.0 16.60 371.72 9.51 24.80 - 0.03502 80.00 4.950 0 0.4110 6.8610 27.90 5.1167 4 245.0 19.20 396.90 3.33 28.50 - 0.07886 80.00 4.950 0 0.4110 7.1480 27.70 5.1167 4 245.0 19.20 396.90 3.56 37.30 - 0.03615 80.00 4.950 0 0.4110 6.6300 23.40 5.1167 4 245.0 19.20 396.90 4.70 27.90 - 0.08265 0.00 13.920 0 0.4370 6.1270 18.40 5.5027 4 289.0 16.00 396.90 8.58 23.90 - 0.08199 0.00 13.920 0 0.4370 6.0090 42.30 5.5027 4 289.0 16.00 396.90 10.40 21.70 - 0.12932 0.00 13.920 0 0.4370 6.6780 31.10 5.9604 4 289.0 16.00 396.90 6.27 28.60 - 0.05372 0.00 13.920 0 0.4370 6.5490 51.00 5.9604 4 289.0 16.00 392.85 7.39 27.10 - 0.14103 0.00 13.920 0 0.4370 5.7900 58.00 6.3200 4 289.0 16.00 396.90 15.84 20.30 - 0.06466 70.00 2.240 0 0.4000 6.3450 20.10 7.8278 5 358.0 14.80 368.24 4.97 22.50 - 0.05561 70.00 2.240 0 0.4000 7.0410 10.00 7.8278 5 358.0 14.80 371.58 4.74 29.00 - 0.04417 70.00 2.240 0 0.4000 6.8710 47.40 7.8278 5 358.0 14.80 390.86 6.07 24.80 - 0.03537 34.00 6.090 0 0.4330 6.5900 40.40 5.4917 7 329.0 16.10 395.75 9.50 22.00 - 0.09266 34.00 6.090 0 0.4330 6.4950 18.40 5.4917 7 329.0 16.10 383.61 8.67 26.40 - 0.10000 34.00 6.090 0 0.4330 6.9820 17.70 5.4917 7 329.0 16.10 390.43 4.86 33.10 - 0.05515 33.00 2.180 0 0.4720 7.2360 41.10 4.0220 7 222.0 18.40 393.68 6.93 36.10 - 0.05479 33.00 2.180 0 0.4720 6.6160 58.10 3.3700 7 222.0 18.40 393.36 8.93 28.40 - 0.07503 33.00 2.180 0 0.4720 7.4200 71.90 3.0992 7 222.0 18.40 396.90 6.47 33.40 - 0.04932 33.00 2.180 0 0.4720 6.8490 70.30 3.1827 7 222.0 18.40 396.90 7.53 28.20 - 0.49298 0.00 9.900 0 0.5440 6.6350 82.50 3.3175 4 304.0 18.40 396.90 4.54 22.80 - 0.34940 0.00 9.900 0 0.5440 5.9720 76.70 3.1025 4 304.0 18.40 396.24 9.97 20.30 - 2.63548 0.00 9.900 0 0.5440 4.9730 37.80 2.5194 4 304.0 18.40 350.45 12.64 16.10 - 0.79041 0.00 9.900 0 0.5440 6.1220 52.80 2.6403 4 304.0 18.40 396.90 5.98 22.10 - 0.26169 0.00 9.900 0 0.5440 6.0230 90.40 2.8340 4 304.0 18.40 396.30 11.72 19.40 - 0.26938 0.00 9.900 0 0.5440 6.2660 82.80 3.2628 4 304.0 18.40 393.39 7.90 21.60 - 0.36920 0.00 9.900 0 0.5440 6.5670 87.30 3.6023 4 304.0 18.40 395.69 9.28 23.80 - 0.25356 0.00 9.900 0 0.5440 5.7050 77.70 3.9450 4 304.0 18.40 396.42 11.50 16.20 - 0.31827 0.00 9.900 0 0.5440 5.9140 83.20 3.9986 4 304.0 18.40 390.70 18.33 17.80 - 0.24522 0.00 9.900 0 0.5440 5.7820 71.70 4.0317 4 304.0 18.40 396.90 15.94 19.80 - 0.40202 0.00 9.900 0 0.5440 6.3820 67.20 3.5325 4 304.0 18.40 395.21 10.36 23.10 - 0.47547 0.00 9.900 0 0.5440 6.1130 58.80 4.0019 4 304.0 18.40 396.23 12.73 21.00 - 0.16760 0.00 7.380 0 0.4930 6.4260 52.30 4.5404 5 287.0 19.60 396.90 7.20 23.80 - 0.18159 0.00 7.380 0 0.4930 6.3760 54.30 4.5404 5 287.0 19.60 396.90 6.87 23.10 - 0.35114 0.00 7.380 0 0.4930 6.0410 49.90 4.7211 5 287.0 19.60 396.90 7.70 20.40 - 0.28392 0.00 7.380 0 0.4930 5.7080 74.30 4.7211 5 287.0 19.60 391.13 11.74 18.50 - 0.34109 0.00 7.380 0 0.4930 6.4150 40.10 4.7211 5 287.0 19.60 396.90 6.12 25.00 - 0.19186 0.00 7.380 0 0.4930 6.4310 14.70 5.4159 5 287.0 19.60 393.68 5.08 24.60 - 0.30347 0.00 7.380 0 0.4930 6.3120 28.90 5.4159 5 287.0 19.60 396.90 6.15 23.00 - 0.24103 0.00 7.380 0 0.4930 6.0830 43.70 5.4159 5 287.0 19.60 396.90 12.79 22.20 - 0.06617 0.00 3.240 0 0.4600 5.8680 25.80 5.2146 4 430.0 16.90 382.44 9.97 19.30 - 0.06724 0.00 3.240 0 0.4600 6.3330 17.20 5.2146 4 430.0 16.90 375.21 7.34 22.60 - 0.04544 0.00 3.240 0 0.4600 6.1440 32.20 5.8736 4 430.0 16.90 368.57 9.09 19.80 - 0.05023 35.00 6.060 0 0.4379 5.7060 28.40 6.6407 1 304.0 16.90 394.02 12.43 17.10 - 0.03466 35.00 6.060 0 0.4379 6.0310 23.30 6.6407 1 304.0 16.90 362.25 7.83 19.40 - 0.05083 0.00 5.190 0 0.5150 6.3160 38.10 6.4584 5 224.0 20.20 389.71 5.68 22.20 - 0.03738 0.00 5.190 0 0.5150 6.3100 38.50 6.4584 5 224.0 20.20 389.40 6.75 20.70 - 0.03961 0.00 5.190 0 0.5150 6.0370 34.50 5.9853 5 224.0 20.20 396.90 8.01 21.10 - 0.03427 0.00 5.190 0 0.5150 5.8690 46.30 5.2311 5 224.0 20.20 396.90 9.80 19.50 - 0.03041 0.00 5.190 0 0.5150 5.8950 59.60 5.6150 5 224.0 20.20 394.81 10.56 18.50 - 0.03306 0.00 5.190 0 0.5150 6.0590 37.30 4.8122 5 224.0 20.20 396.14 8.51 20.60 - 0.05497 0.00 5.190 0 0.5150 5.9850 45.40 4.8122 5 224.0 20.20 396.90 9.74 19.00 - 0.06151 0.00 5.190 0 0.5150 5.9680 58.50 4.8122 5 224.0 20.20 396.90 9.29 18.70 - 0.01301 35.00 1.520 0 0.4420 7.2410 49.30 7.0379 1 284.0 15.50 394.74 5.49 32.70 - 0.02498 0.00 1.890 0 0.5180 6.5400 59.70 6.2669 1 422.0 15.90 389.96 8.65 16.50 - 0.02543 55.00 3.780 0 0.4840 6.6960 56.40 5.7321 5 370.0 17.60 396.90 7.18 23.90 - 0.03049 55.00 3.780 0 0.4840 6.8740 28.10 6.4654 5 370.0 17.60 387.97 4.61 31.20 - 0.03113 0.00 4.390 0 0.4420 6.0140 48.50 8.0136 3 352.0 18.80 385.64 10.53 17.50 - 0.06162 0.00 4.390 0 0.4420 5.8980 52.30 8.0136 3 352.0 18.80 364.61 12.67 17.20 - 0.01870 85.00 4.150 0 0.4290 6.5160 27.70 8.5353 4 351.0 17.90 392.43 6.36 23.10 - 0.01501 80.00 2.010 0 0.4350 6.6350 29.70 8.3440 4 280.0 17.00 390.94 5.99 24.50 - 0.02899 40.00 1.250 0 0.4290 6.9390 34.50 8.7921 1 335.0 19.70 389.85 5.89 26.60 - 0.06211 40.00 1.250 0 0.4290 6.4900 44.40 8.7921 1 335.0 19.70 396.90 5.98 22.90 - 0.07950 60.00 1.690 0 0.4110 6.5790 35.90 10.7103 4 411.0 18.30 370.78 5.49 24.10 - 0.07244 60.00 1.690 0 0.4110 5.8840 18.50 10.7103 4 411.0 18.30 392.33 7.79 18.60 - 0.01709 90.00 2.020 0 0.4100 6.7280 36.10 12.1265 5 187.0 17.00 384.46 4.50 30.10 - 0.04301 80.00 1.910 0 0.4130 5.6630 21.90 10.5857 4 334.0 22.00 382.80 8.05 18.20 - 0.10659 80.00 1.910 0 0.4130 5.9360 19.50 10.5857 4 334.0 22.00 376.04 5.57 20.60 - 8.98296 0.00 18.100 1 0.7700 6.2120 97.40 2.1222 24 666.0 20.20 377.73 17.60 17.80 - 3.84970 0.00 18.100 1 0.7700 6.3950 91.00 2.5052 24 666.0 20.20 391.34 13.27 21.70 - 5.20177 0.00 18.100 1 0.7700 6.1270 83.40 2.7227 24 666.0 20.20 395.43 11.48 22.70 - 4.26131 0.00 18.100 0 0.7700 6.1120 81.30 2.5091 24 666.0 20.20 390.74 12.67 22.60 - 4.54192 0.00 18.100 0 0.7700 6.3980 88.00 2.5182 24 666.0 20.20 374.56 7.79 25.00 - 3.83684 0.00 18.100 0 0.7700 6.2510 91.10 2.2955 24 666.0 20.20 350.65 14.19 19.90 - 3.67822 0.00 18.100 0 0.7700 5.3620 96.20 2.1036 24 666.0 20.20 380.79 10.19 20.80 - 4.22239 0.00 18.100 1 0.7700 5.8030 89.00 1.9047 24 666.0 20.20 353.04 14.64 16.80 - 3.47428 0.00 18.100 1 0.7180 8.7800 82.90 1.9047 24 666.0 20.20 354.55 5.29 21.90 - 4.55587 0.00 18.100 0 0.7180 3.5610 87.90 1.6132 24 666.0 20.20 354.70 7.12 27.50 - 3.69695 0.00 18.100 0 0.7180 4.9630 91.40 1.7523 24 666.0 20.20 316.03 14.00 21.90 -13.52220 0.00 18.100 0 0.6310 3.8630 100.00 1.5106 24 666.0 20.20 131.42 13.33 23.10 - 4.89822 0.00 18.100 0 0.6310 4.9700 100.00 1.3325 24 666.0 20.20 375.52 3.26 50.00 - 5.66998 0.00 18.100 1 0.6310 6.6830 96.80 1.3567 24 666.0 20.20 375.33 3.73 50.00 - 6.53876 0.00 18.100 1 0.6310 7.0160 97.50 1.2024 24 666.0 20.20 392.05 2.96 50.00 - 9.23230 0.00 18.100 0 0.6310 6.2160 100.00 1.1691 24 666.0 20.20 366.15 9.53 50.00 - 8.26725 0.00 18.100 1 0.6680 5.8750 89.60 1.1296 24 666.0 20.20 347.88 8.88 50.00 -11.10810 0.00 18.100 0 0.6680 4.9060 100.00 1.1742 24 666.0 20.20 396.90 34.77 13.80 -18.49820 0.00 18.100 0 0.6680 4.1380 100.00 1.1370 24 666.0 20.20 396.90 37.97 13.80 -19.60910 0.00 18.100 0 0.6710 7.3130 97.90 1.3163 24 666.0 20.20 396.90 13.44 15.00 -15.28800 0.00 18.100 0 0.6710 6.6490 93.30 1.3449 24 666.0 20.20 363.02 23.24 13.90 - 9.82349 0.00 18.100 0 0.6710 6.7940 98.80 1.3580 24 666.0 20.20 396.90 21.24 13.30 -23.64820 0.00 18.100 0 0.6710 6.3800 96.20 1.3861 24 666.0 20.20 396.90 23.69 13.10 -17.86670 0.00 18.100 0 0.6710 6.2230 100.00 1.3861 24 666.0 20.20 393.74 21.78 10.20 -88.97620 0.00 18.100 0 0.6710 6.9680 91.90 1.4165 24 666.0 20.20 396.90 17.21 10.40 -15.87440 0.00 18.100 0 0.6710 6.5450 99.10 1.5192 24 666.0 20.20 396.90 21.08 10.90 - 9.18702 0.00 18.100 0 0.7000 5.5360 100.00 1.5804 24 666.0 20.20 396.90 23.60 11.30 - 7.99248 0.00 18.100 0 0.7000 5.5200 100.00 1.5331 24 666.0 20.20 396.90 24.56 12.30 -20.08490 0.00 18.100 0 0.7000 4.3680 91.20 1.4395 24 666.0 20.20 285.83 30.63 8.80 -16.81180 0.00 18.100 0 0.7000 5.2770 98.10 1.4261 24 666.0 20.20 396.90 30.81 7.20 -24.39380 0.00 18.100 0 0.7000 4.6520 100.00 1.4672 24 666.0 20.20 396.90 28.28 10.50 -22.59710 0.00 18.100 0 0.7000 5.0000 89.50 1.5184 24 666.0 20.20 396.90 31.99 7.40 -14.33370 0.00 18.100 0 0.7000 4.8800 100.00 1.5895 24 666.0 20.20 372.92 30.62 10.20 - 8.15174 0.00 18.100 0 0.7000 5.3900 98.90 1.7281 24 666.0 20.20 396.90 20.85 11.50 - 6.96215 0.00 18.100 0 0.7000 5.7130 97.00 1.9265 24 666.0 20.20 394.43 17.11 15.10 - 5.29305 0.00 18.100 0 0.7000 6.0510 82.50 2.1678 24 666.0 20.20 378.38 18.76 23.20 -11.57790 0.00 18.100 0 0.7000 5.0360 97.00 1.7700 24 666.0 20.20 396.90 25.68 9.70 - 8.64476 0.00 18.100 0 0.6930 6.1930 92.60 1.7912 24 666.0 20.20 396.90 15.17 13.80 -13.35980 0.00 18.100 0 0.6930 5.8870 94.70 1.7821 24 666.0 20.20 396.90 16.35 12.70 - 8.71675 0.00 18.100 0 0.6930 6.4710 98.80 1.7257 24 666.0 20.20 391.98 17.12 13.10 - 5.87205 0.00 18.100 0 0.6930 6.4050 96.00 1.6768 24 666.0 20.20 396.90 19.37 12.50 - 7.67202 0.00 18.100 0 0.6930 5.7470 98.90 1.6334 24 666.0 20.20 393.10 19.92 8.50 -38.35180 0.00 18.100 0 0.6930 5.4530 100.00 1.4896 24 666.0 20.20 396.90 30.59 5.00 - 9.91655 0.00 18.100 0 0.6930 5.8520 77.80 1.5004 24 666.0 20.20 338.16 29.97 6.30 -25.04610 0.00 18.100 0 0.6930 5.9870 100.00 1.5888 24 666.0 20.20 396.90 26.77 5.60 -14.23620 0.00 18.100 0 0.6930 6.3430 100.00 1.5741 24 666.0 20.20 396.90 20.32 7.20 - 9.59571 0.00 18.100 0 0.6930 6.4040 100.00 1.6390 24 666.0 20.20 376.11 20.31 12.10 -24.80170 0.00 18.100 0 0.6930 5.3490 96.00 1.7028 24 666.0 20.20 396.90 19.77 8.30 -41.52920 0.00 18.100 0 0.6930 5.5310 85.40 1.6074 24 666.0 20.20 329.46 27.38 8.50 -67.92080 0.00 18.100 0 0.6930 5.6830 100.00 1.4254 24 666.0 20.20 384.97 22.98 5.00 -20.71620 0.00 18.100 0 0.6590 4.1380 100.00 1.1781 24 666.0 20.20 370.22 23.34 11.90 -11.95110 0.00 18.100 0 0.6590 5.6080 100.00 1.2852 24 666.0 20.20 332.09 12.13 27.90 - 7.40389 0.00 18.100 0 0.5970 5.6170 97.90 1.4547 24 666.0 20.20 314.64 26.40 17.20 -14.43830 0.00 18.100 0 0.5970 6.8520 100.00 1.4655 24 666.0 20.20 179.36 19.78 27.50 -51.13580 0.00 18.100 0 0.5970 5.7570 100.00 1.4130 24 666.0 20.20 2.60 10.11 15.00 -14.05070 0.00 18.100 0 0.5970 6.6570 100.00 1.5275 24 666.0 20.20 35.05 21.22 17.20 -18.81100 0.00 18.100 0 0.5970 4.6280 100.00 1.5539 24 666.0 20.20 28.79 34.37 17.90 -28.65580 0.00 18.100 0 0.5970 5.1550 100.00 1.5894 24 666.0 20.20 210.97 20.08 16.30 -45.74610 0.00 18.100 0 0.6930 4.5190 100.00 1.6582 24 666.0 20.20 88.27 36.98 7.00 -18.08460 0.00 18.100 0 0.6790 6.4340 100.00 1.8347 24 666.0 20.20 27.25 29.05 7.20 -10.83420 0.00 18.100 0 0.6790 6.7820 90.80 1.8195 24 666.0 20.20 21.57 25.79 7.50 -25.94060 0.00 18.100 0 0.6790 5.3040 89.10 1.6475 24 666.0 20.20 127.36 26.64 10.40 -73.53410 0.00 18.100 0 0.6790 5.9570 100.00 1.8026 24 666.0 20.20 16.45 20.62 8.80 -11.81230 0.00 18.100 0 0.7180 6.8240 76.50 1.7940 24 666.0 20.20 48.45 22.74 8.40 -11.08740 0.00 18.100 0 0.7180 6.4110 100.00 1.8589 24 666.0 20.20 318.75 15.02 16.70 - 7.02259 0.00 18.100 0 0.7180 6.0060 95.30 1.8746 24 666.0 20.20 319.98 15.70 14.20 -12.04820 0.00 18.100 0 0.6140 5.6480 87.60 1.9512 24 666.0 20.20 291.55 14.10 20.80 - 7.05042 0.00 18.100 0 0.6140 6.1030 85.10 2.0218 24 666.0 20.20 2.52 23.29 13.40 - 8.79212 0.00 18.100 0 0.5840 5.5650 70.60 2.0635 24 666.0 20.20 3.65 17.16 11.70 -15.86030 0.00 18.100 0 0.6790 5.8960 95.40 1.9096 24 666.0 20.20 7.68 24.39 8.30 -12.24720 0.00 18.100 0 0.5840 5.8370 59.70 1.9976 24 666.0 20.20 24.65 15.69 10.20 -37.66190 0.00 18.100 0 0.6790 6.2020 78.70 1.8629 24 666.0 20.20 18.82 14.52 10.90 - 7.36711 0.00 18.100 0 0.6790 6.1930 78.10 1.9356 24 666.0 20.20 96.73 21.52 11.00 - 9.33889 0.00 18.100 0 0.6790 6.3800 95.60 1.9682 24 666.0 20.20 60.72 24.08 9.50 - 8.49213 0.00 18.100 0 0.5840 6.3480 86.10 2.0527 24 666.0 20.20 83.45 17.64 14.50 -10.06230 0.00 18.100 0 0.5840 6.8330 94.30 2.0882 24 666.0 20.20 81.33 19.69 14.10 - 6.44405 0.00 18.100 0 0.5840 6.4250 74.80 2.2004 24 666.0 20.20 97.95 12.03 16.10 - 5.58107 0.00 18.100 0 0.7130 6.4360 87.90 2.3158 24 666.0 20.20 100.19 16.22 14.30 -13.91340 0.00 18.100 0 0.7130 6.2080 95.00 2.2222 24 666.0 20.20 100.63 15.17 11.70 -11.16040 0.00 18.100 0 0.7400 6.6290 94.60 2.1247 24 666.0 20.20 109.85 23.27 13.40 -14.42080 0.00 18.100 0 0.7400 6.4610 93.30 2.0026 24 666.0 20.20 27.49 18.05 9.60 -15.17720 0.00 18.100 0 0.7400 6.1520 100.00 1.9142 24 666.0 20.20 9.32 26.45 8.70 -13.67810 0.00 18.100 0 0.7400 5.9350 87.90 1.8206 24 666.0 20.20 68.95 34.02 8.40 - 9.39063 0.00 18.100 0 0.7400 5.6270 93.90 1.8172 24 666.0 20.20 396.90 22.88 12.80 -22.05110 0.00 18.100 0 0.7400 5.8180 92.40 1.8662 24 666.0 20.20 391.45 22.11 10.50 - 9.72418 0.00 18.100 0 0.7400 6.4060 97.20 2.0651 24 666.0 20.20 385.96 19.52 17.10 - 5.66637 0.00 18.100 0 0.7400 6.2190 100.00 2.0048 24 666.0 20.20 395.69 16.59 18.40 - 9.96654 0.00 18.100 0 0.7400 6.4850 100.00 1.9784 24 666.0 20.20 386.73 18.85 15.40 -12.80230 0.00 18.100 0 0.7400 5.8540 96.60 1.8956 24 666.0 20.20 240.52 23.79 10.80 -10.67180 0.00 18.100 0 0.7400 6.4590 94.80 1.9879 24 666.0 20.20 43.06 23.98 11.80 - 6.28807 0.00 18.100 0 0.7400 6.3410 96.40 2.0720 24 666.0 20.20 318.01 17.79 14.90 - 9.92485 0.00 18.100 0 0.7400 6.2510 96.60 2.1980 24 666.0 20.20 388.52 16.44 12.60 - 9.32909 0.00 18.100 0 0.7130 6.1850 98.70 2.2616 24 666.0 20.20 396.90 18.13 14.10 - 7.52601 0.00 18.100 0 0.7130 6.4170 98.30 2.1850 24 666.0 20.20 304.21 19.31 13.00 - 6.71772 0.00 18.100 0 0.7130 6.7490 92.60 2.3236 24 666.0 20.20 0.32 17.44 13.40 - 5.44114 0.00 18.100 0 0.7130 6.6550 98.20 2.3552 24 666.0 20.20 355.29 17.73 15.20 - 5.09017 0.00 18.100 0 0.7130 6.2970 91.80 2.3682 24 666.0 20.20 385.09 17.27 16.10 - 8.24809 0.00 18.100 0 0.7130 7.3930 99.30 2.4527 24 666.0 20.20 375.87 16.74 17.80 - 9.51363 0.00 18.100 0 0.7130 6.7280 94.10 2.4961 24 666.0 20.20 6.68 18.71 14.90 - 4.75237 0.00 18.100 0 0.7130 6.5250 86.50 2.4358 24 666.0 20.20 50.92 18.13 14.10 - 4.66883 0.00 18.100 0 0.7130 5.9760 87.90 2.5806 24 666.0 20.20 10.48 19.01 12.70 - 8.20058 0.00 18.100 0 0.7130 5.9360 80.30 2.7792 24 666.0 20.20 3.50 16.94 13.50 - 7.75223 0.00 18.100 0 0.7130 6.3010 83.70 2.7831 24 666.0 20.20 272.21 16.23 14.90 - 6.80117 0.00 18.100 0 0.7130 6.0810 84.40 2.7175 24 666.0 20.20 396.90 14.70 20.00 - 4.81213 0.00 18.100 0 0.7130 6.7010 90.00 2.5975 24 666.0 20.20 255.23 16.42 16.40 - 3.69311 0.00 18.100 0 0.7130 6.3760 88.40 2.5671 24 666.0 20.20 391.43 14.65 17.70 - 6.65492 0.00 18.100 0 0.7130 6.3170 83.00 2.7344 24 666.0 20.20 396.90 13.99 19.50 - 5.82115 0.00 18.100 0 0.7130 6.5130 89.90 2.8016 24 666.0 20.20 393.82 10.29 20.20 - 7.83932 0.00 18.100 0 0.6550 6.2090 65.40 2.9634 24 666.0 20.20 396.90 13.22 21.40 - 3.16360 0.00 18.100 0 0.6550 5.7590 48.20 3.0665 24 666.0 20.20 334.40 14.13 19.90 - 3.77498 0.00 18.100 0 0.6550 5.9520 84.70 2.8715 24 666.0 20.20 22.01 17.15 19.00 - 4.42228 0.00 18.100 0 0.5840 6.0030 94.50 2.5403 24 666.0 20.20 331.29 21.32 19.10 -15.57570 0.00 18.100 0 0.5800 5.9260 71.00 2.9084 24 666.0 20.20 368.74 18.13 19.10 -13.07510 0.00 18.100 0 0.5800 5.7130 56.70 2.8237 24 666.0 20.20 396.90 14.76 20.10 - 4.34879 0.00 18.100 0 0.5800 6.1670 84.00 3.0334 24 666.0 20.20 396.90 16.29 19.90 - 4.03841 0.00 18.100 0 0.5320 6.2290 90.70 3.0993 24 666.0 20.20 395.33 12.87 19.60 - 3.56868 0.00 18.100 0 0.5800 6.4370 75.00 2.8965 24 666.0 20.20 393.37 14.36 23.20 - 4.64689 0.00 18.100 0 0.6140 6.9800 67.60 2.5329 24 666.0 20.20 374.68 11.66 29.80 - 8.05579 0.00 18.100 0 0.5840 5.4270 95.40 2.4298 24 666.0 20.20 352.58 18.14 13.80 - 6.39312 0.00 18.100 0 0.5840 6.1620 97.40 2.2060 24 666.0 20.20 302.76 24.10 13.30 - 4.87141 0.00 18.100 0 0.6140 6.4840 93.60 2.3053 24 666.0 20.20 396.21 18.68 16.70 -15.02340 0.00 18.100 0 0.6140 5.3040 97.30 2.1007 24 666.0 20.20 349.48 24.91 12.00 -10.23300 0.00 18.100 0 0.6140 6.1850 96.70 2.1705 24 666.0 20.20 379.70 18.03 14.60 -14.33370 0.00 18.100 0 0.6140 6.2290 88.00 1.9512 24 666.0 20.20 383.32 13.11 21.40 - 5.82401 0.00 18.100 0 0.5320 6.2420 64.70 3.4242 24 666.0 20.20 396.90 10.74 23.00 - 5.70818 0.00 18.100 0 0.5320 6.7500 74.90 3.3317 24 666.0 20.20 393.07 7.74 23.70 - 5.73116 0.00 18.100 0 0.5320 7.0610 77.00 3.4106 24 666.0 20.20 395.28 7.01 25.00 - 2.81838 0.00 18.100 0 0.5320 5.7620 40.30 4.0983 24 666.0 20.20 392.92 10.42 21.80 - 2.37857 0.00 18.100 0 0.5830 5.8710 41.90 3.7240 24 666.0 20.20 370.73 13.34 20.60 - 3.67367 0.00 18.100 0 0.5830 6.3120 51.90 3.9917 24 666.0 20.20 388.62 10.58 21.20 - 5.69175 0.00 18.100 0 0.5830 6.1140 79.80 3.5459 24 666.0 20.20 392.68 14.98 19.10 - 4.83567 0.00 18.100 0 0.5830 5.9050 53.20 3.1523 24 666.0 20.20 388.22 11.45 20.60 - 0.15086 0.00 27.740 0 0.6090 5.4540 92.70 1.8209 4 711.0 20.10 395.09 18.06 15.20 - 0.18337 0.00 27.740 0 0.6090 5.4140 98.30 1.7554 4 711.0 20.10 344.05 23.97 7.00 - 0.20746 0.00 27.740 0 0.6090 5.0930 98.00 1.8226 4 711.0 20.10 318.43 29.68 8.10 - 0.10574 0.00 27.740 0 0.6090 5.9830 98.80 1.8681 4 711.0 20.10 390.11 18.07 13.60 - 0.11132 0.00 27.740 0 0.6090 5.9830 83.50 2.1099 4 711.0 20.10 396.90 13.35 20.10 - 0.17331 0.00 9.690 0 0.5850 5.7070 54.00 2.3817 6 391.0 19.20 396.90 12.01 21.80 - 0.27957 0.00 9.690 0 0.5850 5.9260 42.60 2.3817 6 391.0 19.20 396.90 13.59 24.50 - 0.17899 0.00 9.690 0 0.5850 5.6700 28.80 2.7986 6 391.0 19.20 393.29 17.60 23.10 - 0.28960 0.00 9.690 0 0.5850 5.3900 72.90 2.7986 6 391.0 19.20 396.90 21.14 19.70 - 0.26838 0.00 9.690 0 0.5850 5.7940 70.60 2.8927 6 391.0 19.20 396.90 14.10 18.30 - 0.23912 0.00 9.690 0 0.5850 6.0190 65.30 2.4091 6 391.0 19.20 396.90 12.92 21.20 - 0.17783 0.00 9.690 0 0.5850 5.5690 73.50 2.3999 6 391.0 19.20 395.77 15.10 17.50 - 0.22438 0.00 9.690 0 0.5850 6.0270 79.70 2.4982 6 391.0 19.20 396.90 14.33 16.80 - 0.06263 0.00 11.930 0 0.5730 6.5930 69.10 2.4786 1 273.0 21.00 391.99 9.67 22.40 - 0.04527 0.00 11.930 0 0.5730 6.1200 76.70 2.2875 1 273.0 21.00 396.90 9.08 20.60 - 0.06076 0.00 11.930 0 0.5730 6.9760 91.00 2.1675 1 273.0 21.00 396.90 5.64 23.90 - 0.10959 0.00 11.930 0 0.5730 6.7940 89.30 2.3889 1 273.0 21.00 393.45 6.48 22.00 - 0.04741 0.00 11.930 0 0.5730 6.0300 80.80 2.5050 1 273.0 21.00 396.90 7.88 11.90 diff --git a/benchmarks/regression/evaluation.py b/benchmarks/regression/evaluation.py new file mode 100644 index 00000000..fbbfe6d7 --- /dev/null +++ b/benchmarks/regression/evaluation.py @@ -0,0 +1,21 @@ +# Copyright (c) 2015, Zhenwen Dai +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +import abc +import numpy as np + +class Evaluation(object): + __metaclass__ = abc.ABCMeta + + @abc.abstractmethod + def evaluate(self, gt, pred): + """Compute a scalar for access the performance""" + return None + +class RMSE(Evaluation): + "Rooted Mean Square Error" + name = 'RMSE' + + def evaluate(self, gt, pred): + return np.sqrt(np.square(gt-pred).astype(np.float).mean()) + \ No newline at end of file diff --git a/benchmarks/regression/methods.py b/benchmarks/regression/methods.py new file mode 100644 index 00000000..9325396d --- /dev/null +++ b/benchmarks/regression/methods.py @@ -0,0 +1,109 @@ +# Copyright (c) 2015, Zhenwen Dai +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +import abc +import numpy as np +import GPy + +class RegressionMethod(object): + __metaclass__ = abc.ABCMeta + + def __init__(self): + self.preprocess = True + + def _preprocess(self, data, train): + """Zero-mean, unit-variance normalization by default""" + if train: + inputs, labels = data + self.data_mean = inputs.mean(axis=0) + self.data_std = inputs.std(axis=0) + self.labels_mean = labels.mean(axis=0) + self.labels_std = labels.std(axis=0) + return ((inputs-self.data_mean)/self.data_std, (labels-self.labels_mean)/self.labels_std) + else: + return (data-self.data_mean)/self.data_std + + def _reverse_trans_labels(self, labels): + return labels*self.labels_std+self.labels_mean + + def fit(self, train_data): + if self.preprocess: + train_data = self._preprocess(train_data, True) + return self._fit(train_data) + + def predict(self, test_data): + if self.preprocess: + test_data = self._preprocess(test_data, False) + labels = self._predict(test_data) + if self.preprocess: + labels = self._reverse_trans_labels(labels) + return labels + + @abc.abstractmethod + def _fit(self, train_data): + """Fit the model. Return True if successful""" + return True + + @abc.abstractmethod + def _predict(self, test_data): + """Predict on test data""" + return None + +class GP_RBF(RegressionMethod): + name = 'GP_RBF' + + def _fit(self, train_data): + inputs, labels = train_data + self.model = GPy.models.GPRegression(inputs, labels,kernel=GPy.kern.RBF(inputs.shape[-1],ARD=True) +GPy.kern.Linear(inputs.shape[1], ARD=True) ) + self.model.likelihood.variance[:] = labels.var()*0.01 + self.model.optimize() + return True + + def _predict(self, test_data): + return self.model.predict(test_data)[0] + +class SparseGP_RBF(RegressionMethod): + name = 'SparseGP_RBF' + + def _fit(self, train_data): + inputs, labels = train_data + self.model = GPy.models.SparseGPRegression(inputs, labels,kernel=GPy.kern.RBF(inputs.shape[-1],ARD=True) +GPy.kern.Linear(inputs.shape[1], ARD=True) ,num_inducing=100) + self.model.likelihood.variance[:] = labels.var()*0.01 + self.model.optimize() + return True + + def _predict(self, test_data): + return self.model.predict(test_data)[0] + +# class MRD_RBF(RegressionMethod): +# name = 'MRD_RBF' +# +# def _fit(self, train_data): +# inputs, labels = train_data +# Q = 5 +# self.model = GPy.models.MRD([inputs, labels],Q,kernel=GPy.kern.RBF(Q,ARD=True),num_inducing=50) +# self.model.Y0.likelihood.variance[:] = inputs.var()*0.01 +# self.model.Y1.likelihood.variance[:] = labels.var()*0.01 +# self.model.optimize() +# return True +# +# def _predict(self, test_data): +# return self.model.predict(self.model.Y0.infer_newX(test_data)[0])[0] + +class SVIGP_RBF(RegressionMethod): + name = 'SVIGP_RBF' + + def _fit(self, train_data): + X, Y = train_data + + Z = X[np.random.permutation(X.shape[0])[:100]] + k = GPy.kern.RBF(X.shape[1], ARD=True) + GPy.kern.Linear(X.shape[1], ARD=True) + GPy.kern.White(X.shape[1],0.01) + + lik = GPy.likelihoods.StudentT(deg_free=3.) + self.model = GPy.core.SVGP(X, Y, Z=Z, kernel=k, likelihood=lik) + [self.model.optimize('scg', max_iters=40, gtol=0, messages=0, xtol=0, ftol=0) for i in range(10)] + self.model.optimize('bfgs', max_iters=1000, gtol=0, messages=0) + return True + + def _predict(self, test_data): + return self.model.predict(test_data)[0] diff --git a/benchmarks/regression/outputs.py b/benchmarks/regression/outputs.py new file mode 100644 index 00000000..2294bbe0 --- /dev/null +++ b/benchmarks/regression/outputs.py @@ -0,0 +1,64 @@ +# Copyright (c) 2015, Zhenwen Dai +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +from __future__ import print_function +import abc +import os +import numpy as np + +class Output(object): + __metaclass__ = abc.ABCMeta + + @abc.abstractmethod + def output(self, config, results): + """Return the test data: training data and labels""" + return None + +class ScreenOutput(Output): + + def output(self, config, results): + print('='*10+'Report'+'='*10) + print('\t'.join([' ']+[m.name+'('+e+')' for m in config['methods'] for e in [a.name for a in config['evaluations']]+['time']])) + for task_i in range(len(config['tasks'])): + print(config['tasks'][task_i].name+'\t', end='') + + outputs = [] + for method_i in range(len(config['methods'])): + for ei in range(len(config['evaluations'])+1): + m,s = results[task_i, method_i, ei].mean(), results[task_i, method_i, ei].std() + outputs.append('%e(%e)'%(m,s)) + print('\t'.join(outputs)) + +class CSVOutput(Output): + + def __init__(self, outpath, prjname): + self.fname = os.path.join(outpath, prjname+'.csv') + + def output(self, config, results): + with open(self.fname,'w') as f: + f.write(','.join([' ']+[m.name+'('+e+')' for m in config['methods'] for e in [a.name for a in config['evaluations']]+['time']])+'\n') + for task_i in range(len(config['tasks'])): + f.write(config['tasks'][task_i].name+',') + + outputs = [] + for method_i in range(len(config['methods'])): + for ei in range(len(config['evaluations'])+1): + m,s = results[task_i, method_i, ei].mean(), results[task_i, method_i, ei].std() + outputs.append('%e (%e)'%(m,s)) + f.write(','.join(outputs)+'\n') + f.close() + +class H5Output(Output): + + def __init__(self, outpath, prjname): + self.fname = os.path.join(outpath, prjname+'.h5') + + def output(self, config, results): + try: + import h5py + f = h5py.File(self.fname,'w') + d = f.create_dataset('results',results.shape, dtype=results.dtype) + d[:] = results + f.close() + except: + raise 'Fails to write the parameters into a HDF5 file!' diff --git a/benchmarks/regression/run.py b/benchmarks/regression/run.py new file mode 100644 index 00000000..452d4ff5 --- /dev/null +++ b/benchmarks/regression/run.py @@ -0,0 +1,53 @@ +# Copyright (c) 2015, Zhenwen Dai +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +from __future__ import print_function +from evaluation import RMSE +from methods import GP_RBF, SVIGP_RBF, SparseGP_RBF +from tasks import Housing, WineQuality +from outputs import ScreenOutput, CSVOutput, H5Output +import numpy as np +import time + +outpath = '.' +prjname = 'regression' +config = { + 'evaluations':[RMSE], + 'methods':[GP_RBF, SVIGP_RBF, SparseGP_RBF], + 'tasks':[WineQuality,Housing], + 'repeats':2, + 'outputs': [ScreenOutput(), CSVOutput(outpath, prjname), H5Output(outpath, prjname)] + } + +if __name__=='__main__': + results = np.zeros((len(config['tasks']), len(config['methods']), len(config['evaluations'])+1, config['repeats'])) + + for task_i in range(len(config['tasks'])): + dataset = config['tasks'][task_i]() + print('Benchmarking on '+dataset.name) + res = dataset.load_data() + if not res: print('Fail to load '+config['tasks'][task_i].name); continue + train = dataset.get_training_data() + test = dataset.get_test_data() + + for method_i in range(len(config['methods'])): + method = config['methods'][method_i] + print('With the method '+method.name, end='') + for ri in range(config['repeats']): + m = method() + t_st = time.time() + m.fit(train) + pred = m.predict(test[0]) + t_pd = time.time() - t_st + for ei in range(len(config['evaluations'])): + evalu = config['evaluations'][ei]() + results[task_i, method_i, ei, ri] = evalu.evaluate(test[1], pred) + results[task_i, method_i, -1, ri] = t_pd + print('.',end='') + print() + + [out.output(config, results) for out in config['outputs']] + + + + diff --git a/benchmarks/regression/tasks.py b/benchmarks/regression/tasks.py new file mode 100644 index 00000000..9cecbdd8 --- /dev/null +++ b/benchmarks/regression/tasks.py @@ -0,0 +1,86 @@ +# Copyright (c) 2015, Zhenwen Dai +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +import abc +import os +import numpy as np + +class RegressionTask(object): + __metaclass__ = abc.ABCMeta + + def __init__(self, datapath='./'): + self.datapath = datapath + + @abc.abstractmethod + def load_data(self): + """Download the dataset if not exist. Return True if successful""" + return True + + @abc.abstractmethod + def get_training_data(self): + """Return the training data: training data and labels""" + return None + + @abc.abstractmethod + def get_test_data(self): + """Return the test data: training data and labels""" + return None + +class Housing(RegressionTask): + + name='Housing' + url = "https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data" + filename = 'housing.data' + + def load_data(self): + from GPy.util.datasets import download_url, data_path + if not os.path.exists(os.path.join(data_path,self.datapath, self.filename)): + download_url(Housing.url, self.datapath, messages=True) + if not os.path.exists(os.path.join(data_path, self.datapath, self.filename)): + return False + + data = np.loadtxt(os.path.join(data_path, self.datapath, self.filename)) + self.data = data + data_train = data[:250,:-1] + label_train = data[:250, -1:] + self.train = (data_train, label_train) + data_test = data[250:,:-1] + label_test = data[250:,-1:] + self.test = (data_test, label_test) + return True + + def get_training_data(self): + return self.train + + def get_test_data(self): + return self.test + +class WineQuality(RegressionTask): + + name='WineQuality' + url = "https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv" + filename = 'winequality-red.csv' + + def load_data(self): + from GPy.util.datasets import download_url, data_path + if not os.path.exists(os.path.join(data_path,self.datapath, self.filename)): + download_url(self.url, self.datapath, messages=True) + if not os.path.exists(os.path.join(data_path, self.datapath, self.filename)): + return False + + data = np.loadtxt(os.path.join(data_path, self.datapath, self.filename),skiprows=1,delimiter=';') + self.data = data + data_train = data[:1000,:-1] + label_train = data[:1000, -1:] + self.train = (data_train, label_train) + data_test = data[1000:,:-1] + label_test = data[1000:,-1:] + self.test = (data_test, label_test) + return True + + def get_training_data(self): + return self.train + + def get_test_data(self): + return self.test + diff --git a/doc/conf.py b/doc/conf.py index 91a6c75b..f63f2a13 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -92,13 +92,17 @@ print "Importing extensions" extensions = ['sphinx.ext.autodoc', #'sphinx.ext.doctest' 'sphinx.ext.viewcode', - 'sphinx.ext.pngmath', + #'sphinx.ext.pngmath', + 'sphinx.ext.mathjax', 'ipython_directive', 'ipython_console_highlighting' #'matplotlib.sphinxext.plot_directive' ] plot_formats = [('png', 80), ('pdf', 50)] +#pngmath_latex_preamble=r'\usepackage[active]{preview}\usepackage{MnSymbol}' # + other custom stuff for inline math, such as non-default math fonts etc. +#pngmath_use_preview=True + print "finished importing" ############################################################################## @@ -218,7 +222,7 @@ exclude_patterns = ['_build'] #show_authors = False # The name of the Pygments (syntax highlighting) style to use. -pygments_style = 'sphinx' +pygments_style = 'default' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] @@ -228,10 +232,10 @@ pygments_style = 'sphinx' # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. -html_theme = 'default' +html_theme = 'alabaster' # This is to revert to the default theme on readthedocs -html_style = '/default.css' +html_style = '/alabaster.css' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the @@ -317,7 +321,7 @@ latex_elements = { #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. - 'preamble': '\\usepackage{MnSymbol}', + 'preamble': '\\usepackage{MnSymbol,amsmath}', } # Grouping the document tree into LaTeX files. List of tuples diff --git a/doc/index.rst b/doc/index.rst index fec4aef1..b8e572a2 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -25,7 +25,7 @@ The code can be found on our `Github project page - from sympy.utilities.lambdify import lambdastr, _imp_namespace, _get_namespace -ImportError: No module named lambdify -/home/alans/Work/GPy/GPy/core/parameterization/parameter_core.py:docstring of GPy.core.parameterization.parameter_core.Indexable.unset_priors:1: WARNING: Inline emphasis start-string without end-string. -/home/alans/Work/GPy/GPy/core/parameterization/parameter_core.py:docstring of GPy.core.parameterization.parameter_core.Nameable.hierarchy_name:4: WARNING: Field list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/core/parameterization/parameter_core.py:docstring of GPy.core.parameterization.parameter_core.Observable.notify_observers:5: SEVERE: Unexpected section title or transition. - -^^^^^^^^^^^^^^^^ -/home/alans/Work/GPy/GPy/core/parameterization/parameter_core.py:docstring of GPy.core.parameterization.parameter_core.Observable.notify_observers:6: WARNING: Definition list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/core/parameterization/parameter_core.py:docstring of GPy.core.parameterization.parameter_core.Parameterizable.traverse:1: WARNING: Inline emphasis start-string without end-string. -/home/alans/Work/GPy/GPy/core/parameterization/parameter_core.py:docstring of GPy.core.parameterization.parameter_core.Parameterizable.traverse:1: WARNING: Inline strong start-string without end-string. -/home/alans/Work/GPy/GPy/core/parameterization/parameterized.py:docstring of GPy.core.parameterization.parameterized.Parameterized:18: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/core/parameterization/parameterized.py:docstring of GPy.core.parameterization.parameterized.Parameterized:20: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/core/parameterization/ties_and_remappings.py:docstring of GPy.core.parameterization.ties_and_remappings.Tie:18: SEVERE: Unexpected section title or transition. - -================================ -/home/alans/Work/GPy/GPy/kern/_src/coregionalize.py:docstring of GPy.kern._src.coregionalize.Coregionalize:5: ERROR: Unexpected indentation. -/home/alans/Work/GPy/doc/GPy.kern._src.rst:73: WARNING: autodoc: failed to import module u'GPy.kern._src.hierarchical'; the following exception was raised: -Traceback (most recent call last): - File "/home/alans/anaconda/envs/GPy/lib/python2.7/site-packages/sphinx/ext/autodoc.py", line 335, in import_object - __import__(self.modname) - File "/home/alans/Work/GPy/GPy/kern/_src/hierarchical.py", line 4, in - from kernpart import Kernpart -ImportError: No module named kernpart -/home/alans/Work/GPy/GPy/kern/_src/independent_outputs.py:docstring of GPy.kern._src.independent_outputs.IndependentOutputs:9: WARNING: Field list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/kern/_src/stationary.py:docstring of GPy.kern._src.stationary.Stationary:12: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/kern/_src/stationary.py:docstring of GPy.kern._src.stationary.Stationary:22: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/kern/_src/stationary.py:docstring of GPy.kern._src.stationary.Stationary:23: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/doc/GPy.kern._src.rst:177: WARNING: autodoc: failed to import module u'GPy.kern._src.symbolic'; the following exception was raised: -Traceback (most recent call last): - File "/home/alans/anaconda/envs/GPy/lib/python2.7/site-packages/sphinx/ext/autodoc.py", line 335, in import_object - __import__(self.modname) - File "/home/alans/Work/GPy/GPy/kern/_src/symbolic.py", line 5, in - from ...core.symbolic import Symbolic_core - File "/home/alans/Work/GPy/GPy/core/symbolic.py", line 10, in - from sympy.utilities.lambdify import lambdastr, _imp_namespace, _get_namespace -ImportError: No module named lambdify -/home/alans/Work/GPy/GPy/models/gp_kronecker_gaussian_regression.py:docstring of GPy.models.gp_kronecker_gaussian_regression.GPKroneckerGaussianRegression:13: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/models/gp_kronecker_gaussian_regression.py:docstring of GPy.models.gp_kronecker_gaussian_regression.GPKroneckerGaussianRegression:18: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/models/gp_var_gauss.py:docstring of GPy.models.gp_var_gauss.GPVariationalGaussianApproximation:9: WARNING: Definition list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/models/mrd.py:docstring of GPy.models.mrd.MRD:32: WARNING: Field list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/models/mrd.py:docstring of GPy.models.mrd.MRD:32: WARNING: Inline interpreted text or phrase reference start-string without end-string. -/home/alans/Work/GPy/GPy/models/mrd.py:docstring of GPy.models.mrd.MRD:34: WARNING: Definition list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/models/sparse_gp_minibatch.py:docstring of GPy.models.sparse_gp_minibatch.SparseGPMiniBatch:2: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/plotting/matplot_dep/netpbmfile.py:docstring of GPy.plotting.matplot_dep.netpbmfile.imread:6: SEVERE: Unexpected section title. - -Examples --------- -/home/alans/Work/GPy/GPy/plotting/matplot_dep/netpbmfile.py:docstring of GPy.plotting.matplot_dep.netpbmfile.imsave:4: SEVERE: Unexpected section title. - -Examples --------- -/home/alans/Work/GPy/GPy/testing/likelihood_tests.py:docstring of GPy.testing.likelihood_tests.dparam_checkgrad:6: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/testing/likelihood_tests.py:docstring of GPy.testing.likelihood_tests.dparam_checkgrad:7: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/testing/likelihood_tests.py:docstring of GPy.testing.likelihood_tests.dparam_partial:7: WARNING: Definition list ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/GPy/testing/likelihood_tests.py:docstring of GPy.testing.likelihood_tests.dparam_partial:9: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/util/datasets.py:docstring of GPy.util.datasets.hapmap3:7: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/doc/GPy.util.rst:2: SEVERE: Duplicate ID: "module-GPy.util.diag". -/home/alans/Work/GPy/GPy/util/netpbmfile.py:docstring of GPy.util.netpbmfile.imread:6: SEVERE: Unexpected section title. - -Examples --------- -/home/alans/Work/GPy/GPy/util/netpbmfile.py:docstring of GPy.util.netpbmfile.imsave:4: SEVERE: Unexpected section title. - -Examples --------- -/home/alans/Work/GPy/doc/GPy.util.rst:2: SEVERE: Duplicate ID: "module-GPy.util.subarray_and_sorting". -/home/alans/Work/GPy/GPy/util/subarray_and_sorting.py:docstring of GPy.util.subarray_and_sorting.common_subarrays:8: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/util/subarray_and_sorting.py:docstring of GPy.util.subarray_and_sorting.common_subarrays:11: SEVERE: Unexpected section title. - -Examples: -========= -/home/alans/Work/GPy/GPy/util/subarray_and_sorting.py:docstring of GPy.util.subarray_and_sorting.common_subarrays:19: ERROR: Unexpected indentation. -/home/alans/Work/GPy/GPy/util/subarray_and_sorting.py:docstring of GPy.util.subarray_and_sorting.common_subarrays:21: WARNING: Block quote ends without a blank line; unexpected unindent. -/home/alans/Work/GPy/doc/installation.rst:22: ERROR: Unexpected indentation. -/home/alans/Work/GPy/doc/installation.rst:27: ERROR: Unexpected indentation. -/home/alans/Work/GPy/doc/tuto_creating_new_kernels.rst:58: WARNING: Inline literal start-string without end-string. -/home/alans/Work/GPy/doc/tuto_creating_new_models.rst:24: ERROR: Unknown target name: "parameterized". -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:83: WARNING: Title underline too short. - -Interacting with Parameters: -======================= -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:83: WARNING: Title underline too short. - -Interacting with Parameters: -======================= -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:109: WARNING: Title underline too short. - -Regular expressions ----------------- -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:164: WARNING: Title underline too short. - -Setting and fetching parameters `parameter_array` ------------------------------------------- -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:164: WARNING: Title underline too short. - -Setting and fetching parameters `parameter_array` ------------------------------------------- -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:220: WARNING: Title underline too short. - -Getting the model parameter's gradients -============================ -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:220: WARNING: Title underline too short. - -Getting the model parameter's gradients -============================ -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:236: WARNING: Title underline too short. - -Adjusting the model's constraints -================================ -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:236: WARNING: Title underline too short. - -Adjusting the model's constraints -================================ -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:287: WARNING: Title underline too short. - -Available Constraints -============== -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:287: WARNING: Title underline too short. - -Available Constraints -============== -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:299: WARNING: Title underline too short. - -Tying Parameters -============ -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:299: WARNING: Title underline too short. - -Tying Parameters -============ -/home/alans/Work/GPy/doc/tuto_parameterized.rst:3: WARNING: Title overline too short. - -******************* -Parameterization handling -******************* -/home/alans/Work/GPy/doc/tuto_parameterized.rst:10: WARNING: Title underline too short. - -Parameter handles -============== -/home/alans/Work/GPy/doc/tuto_parameterized.rst:16: WARNING: Title underline too short. - -:py:class:`~GPy.core.parameterization.parameterized.Parameterized` -========== -/home/alans/Work/GPy/doc/tuto_parameterized.rst:16: WARNING: Title underline too short. - -:py:class:`~GPy.core.parameterization.parameterized.Parameterized` -========== -/home/alans/Work/GPy/doc/tuto_parameterized.rst:21: WARNING: Title underline too short. - -:py:class:`~GPy.core.parameterization.param.Param` -=========== -/home/alans/Work/GPy/doc/tuto_parameterized.rst:21: WARNING: Title underline too short. - -:py:class:`~GPy.core.parameterization.param.Param` -=========== -/home/alans/Work/GPy/doc/installation.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/kernel_implementation.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/modules.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/tuto_GP_regression.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/tuto_creating_new_kernels.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/tuto_creating_new_models.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/tuto_kernel_overview.rst:: WARNING: document isn't included in any toctree -/home/alans/Work/GPy/doc/tuto_parameterized.rst:: WARNING: document isn't included in any toctree -WARNING: dvipng command 'dvipng' cannot be run (needed for math display), check the pngmath_dvipng setting -/home/alans/Work/GPy/doc/tuto_interacting_with_models.rst:336: WARNING: undefined label: creating_new_kernels (if the link has no caption the label must precede a section header) -WARNING: html_static_path entry u'/home/alans/Work/GPy/doc/_static' does not exist diff --git a/doc/tuto_kernel_overview.rst b/doc/tuto_kernel_overview.rst index e9e8f290..fc93491a 100644 --- a/doc/tuto_kernel_overview.rst +++ b/doc/tuto_kernel_overview.rst @@ -13,9 +13,9 @@ First we import the libraries we will need :: For most kernels, the dimension is the only mandatory parameter to define a kernel object. However, it is also possible to specify the values of the parameters. For example, the three following commands are valid for defining a squared exponential kernel (ie rbf or Gaussian) :: - ker1 = GPy.kern.rbf(1) # Equivalent to ker1 = GPy.kern.rbf(input_dim=1, variance=1., lengthscale=1.) - ker2 = GPy.kern.rbf(input_dim=1, variance = .75, lengthscale=2.) - ker3 = GPy.kern.rbf(1, .5, .5) + ker1 = GPy.kern.RBF(1) # Equivalent to ker1 = GPy.kern.RBF(input_dim=1, variance=1., lengthscale=1.) + ker2 = GPy.kern.RBF(input_dim=1, variance = .75, lengthscale=2.) + ker3 = GPy.kern.RBF(1, .5, .5) A ``print`` and a ``plot`` functions are implemented to represent kernel objects. The commands :: @@ -52,21 +52,18 @@ Operations to combine kernels In ``GPy``, kernel objects can be added or multiplied. In both cases, two kinds of operations are possible since one can assume that the kernels to add/multiply are defined on the same space or on different subspaces. In other words, it is possible to use two kernels :math:`k_1,\ k_2` over :math:`\mathbb{R} \times \mathbb{R}` to create - * a kernel over :math:`\mathbb{R} \times \mathbb{R}`: :math:`k(x,y) = k_1(x,y) \times k_2(x,y)` - * a kernel over :math:`\mathbb{R}^2 \times \mathbb{R}^2`: :math:`k(\mathbf{x},\mathbf{y}) = k_1(x_1,y_1) \times k_2(x_2,y_2)` + * a kernel over :math:`\mathbb{R} \times \mathbb{R}`: :math:`k(x,y) = k_1(x,y) \times k_2(x,y)`. -These two options are available in GPy using the flag ``tensor`` in the ``add`` and ``prod`` functions. Here is a quick example :: +This is available in GPy via the ``add`` and ``prod`` functions. Here is a quick example :: - k1 = GPy.kern.rbf(1,1.,2.) + k1 = GPy.kern.RBF(1,1.,2.) k2 = GPy.kern.Matern32(1, 0.5, 0.2) # Product of kernels - k_prod = k1.prod(k2) # By default, tensor=False - k_prodtens = k1.prod(k2,tensor=True) + k_prod = k1.prod(k2) # Sum of kernels - k_add = k1.add(k2) # By default, tensor=False - k_addtens = k1.add(k2,tensor=True) + k_add = k1.add(k2) .. # plots pb.figure(figsize=(8,8)) @@ -75,23 +72,23 @@ These two options are available in GPy using the flag ``tensor`` in the ``add`` pb.title('prod') pb.subplot(2,2,2) k_prodtens.plot() - pb.title('tensor prod') + pb.title('prod') pb.subplot(2,2,3) k_add.plot() pb.title('sum') pb.subplot(2,2,4) k_addtens.plot() - pb.title('tensor sum') + pb.title('sum') pb.subplots_adjust(wspace=0.3, hspace=0.3) .. figure:: Figures/tuto_kern_overview_multadd.png :align: center :height: 500px -A shortcut for ``add`` and ``prod`` (with default flag ``tensor=False``) is provided by the usual ``+`` and ``*`` operators. Here is another example where we create a periodic kernel with some decay :: +A shortcut for ``add`` and ``prod`` is provided by the usual ``+`` and ``*`` operators. Here is another example where we create a periodic kernel with some decay :: - k1 = GPy.kern.rbf(1,1.,2) - k2 = GPy.kern.periodic_Matern52(1,variance=1e3, lengthscale=1, period = 1.5, lower=-5., upper = 5) + k1 = GPy.kern.RBF(1,1.,2) + k2 = GPy.kern.PeriodicMatern52(1,variance=1e3, lengthscale=1, period = 1.5, lower=-5., upper = 5) k = k1 * k2 # equivalent to k = k1.prod(k2) print k @@ -116,14 +113,14 @@ A shortcut for ``add`` and ``prod`` (with default flag ``tensor=False``) is prov In general, ``kern`` objects can be seen as a sum of ``kernparts`` objects, where the later are covariance functions defined on the same space. For example, the following code :: k = (k1+k2)*(k1+k2) - print k.parts[0].name, '\n', k.parts[1].name, '\n', k.parts[2].name, '\n', k.parts[3].name + print k.parts[0].name, '\n', k.parts[1].name, '\n', k.parts[1].parts[0].name, '\n', k.parts[1].parts[1].name, '\n' returns :: + add_1 + add_2 + rbf + periodic_Matern52 - rbfrbf - rbfperiodic_Mat52 - periodic_Mat52rbf - periodic_Mat52periodic_Mat52 Constraining the parameters =========================== @@ -137,9 +134,9 @@ Various constrains can be applied to the parameters of a kernel When calling one of these functions, the parameters to constrain can either by specified by a regular expression that matches its name or by a number that corresponds to the rank of the parameter. Here is an example :: - k1 = GPy.kern.rbf(1) + k1 = GPy.kern.RBF(1) k2 = GPy.kern.Matern32(1) - k3 = GPy.kern.white(1) + k3 = GPy.kern.White(1) k = k1 + k2 + k3 print k @@ -182,9 +179,9 @@ In two dimensions ANOVA kernels have the following form: Let us assume that we want to define an ANOVA kernel with a Matern 3/2 kernel for :math:`k_i`. As seen previously, we can define this kernel as follows :: - k_cst = GPy.kern.bias(1,variance=1.) - k_mat = GPy.kern.Matern52(1,variance=1., lengthscale=3) - Kanova = (k_cst + k_mat).prod(k_cst + k_mat,tensor=True) + k_cst = GPy.kern.Bias(1,variance=1.) + k_mat = GPy.kern.Matern52(1,variance=1.,lengthscale=3) + Kanova = (k_cst + k_mat).prod(k_cst + k_mat) print Kanova Printing the resulting kernel outputs the following :: @@ -257,17 +254,17 @@ The submodels can be represented with the option ``which_function`` of ``plot``: import GPy pb.ion() - ker1 = GPy.kern.rbf(D=1) # Equivalent to ker1 = GPy.kern.rbf(D=1, variance=1., lengthscale=1.) - ker2 = GPy.kern.rbf(D=1, variance = .75, lengthscale=3.) - ker3 = GPy.kern.rbf(1, .5, .25) + ker1 = GPy.kern.RBF(D=1) # Equivalent to ker1 = GPy.kern.RBF(D=1, variance=1., lengthscale=1.) + ker2 = GPy.kern.RBF(D=1, variance = .75, lengthscale=3.) + ker3 = GPy.kern.RBF(1, .5, .25) ker1.plot() ker2.plot() ker3.plot() #pb.savefig("Figures/tuto_kern_overview_basicdef.png") - kernels = [GPy.kern.rbf(1), GPy.kern.exponential(1), GPy.kern.Matern32(1), GPy.kern.Matern52(1), GPy.kern.Brownian(1), GPy.kern.bias(1), GPy.kern.linear(1), GPy.kern.spline(1), GPy.kern.periodic_exponential(1), GPy.kern.periodic_Matern32(1), GPy.kern.periodic_Matern52(1), GPy.kern.white(1)] - kernel_names = ["GPy.kern.rbf", "GPy.kern.exponential", "GPy.kern.Matern32", "GPy.kern.Matern52", "GPy.kern.Brownian", "GPy.kern.bias", "GPy.kern.linear", "GPy.kern.spline", "GPy.kern.periodic_exponential", "GPy.kern.periodic_Matern32", "GPy.kern.periodic_Matern52", "GPy.kern.white"] + kernels = [GPy.kern.RBF(1), GPy.kern.Exponential(1), GPy.kern.Matern32(1), GPy.kern.Matern52(1), GPy.kern.Brownian(1), GPy.kern.Bias(1), GPy.kern.Linear(1), GPy.kern.PeriodicExponential(1), GPy.kern.PeriodicMatern32(1), GPy.kern.PeriodicMatern52(1), GPy.kern.White(1)] + kernel_names = ["GPy.kern.RBF", "GPy.kern.Exponential", "GPy.kern.Matern32", "GPy.kern.Matern52", "GPy.kern.Brownian", "GPy.kern.Bias", "GPy.kern.Linear", "GPy.kern.PeriodicExponential", "GPy.kern.PeriodicMatern32", "GPy.kern.PeriodicMatern52", "GPy.kern.White"] pb.figure(figsize=(16,12)) pb.subplots_adjust(wspace=.5, hspace=.5) diff --git a/setup.cfg b/setup.cfg new file mode 100644 index 00000000..7fc74878 --- /dev/null +++ b/setup.cfg @@ -0,0 +1,10 @@ +[bumpversion] +current_version = 0.8.8 +tag = True +commit = True + +[bumpversion:file:GPy/__version__.py] + +[bdist_wheel] +universal = 1 + diff --git a/setup.py b/setup.py index 8025cd5d..0432cbad 100644 --- a/setup.py +++ b/setup.py @@ -1,29 +1,51 @@ #!/usr/bin/env python # -*- coding: utf-8 -*- - +from __future__ import print_function import os +import sys from setuptools import setup, Extension import numpy as np -# Version number -version = '0.6.1' def read(fname): return open(os.path.join(os.path.dirname(__file__), fname)).read() -#compile_flags = ["-march=native", '-fopenmp', '-O3', ] -compile_flags = [ '-fopenmp', '-O3', ] +def read_to_rst(fname): + try: + import pypandoc + #print 'Warning in installation: For rst formatting in pypi, consider installing pypandoc for conversion' + with open('README.rst', 'w') as f: + f.write(pypandoc.convert('README.md', 'rst')) + except: + return read(fname) + +version_dummy = {} +exec(read('GPy/__version__.py'), version_dummy) +__version__ = version_dummy['__version__'] +del version_dummy + +#Mac OS X Clang doesn't support OpenMP at the current time. +#This detects if we are building on a Mac +def ismac(): + return sys.platform[:6] == 'darwin' + +if ismac(): + compile_flags = [ '-O3', ] + link_args = [] +else: + compile_flags = [ '-fopenmp', '-O3', ] + link_args = ['-lgomp'] ext_mods = [Extension(name='GPy.kern._src.stationary_cython', sources=['GPy/kern/_src/stationary_cython.c','GPy/kern/_src/stationary_utils.c'], include_dirs=[np.get_include()], extra_compile_args=compile_flags, - extra_link_args = ['-lgomp']), + extra_link_args = link_args), Extension(name='GPy.util.choleskies_cython', - sources=['GPy/util/choleskies_cython.c', 'GPy/util/cholesky_backprop.c'], + sources=['GPy/util/choleskies_cython.c'], include_dirs=[np.get_include()], - extra_link_args = ['-lgomp', '-lblas'], - extra_compile_args=compile_flags+['-std=c99']), + extra_link_args = link_args, + extra_compile_args=compile_flags), Extension(name='GPy.util.linalg_cython', sources=['GPy/util/linalg_cython.c'], include_dirs=[np.get_include()], @@ -34,9 +56,9 @@ ext_mods = [Extension(name='GPy.kern._src.stationary_cython', extra_compile_args=compile_flags)] setup(name = 'GPy', - version = version, + version = __version__, author = read('AUTHORS.txt'), - author_email = "james.hensman@gmail.com", + author_email = "gpy.authors@gmail.com", description = ("The Gaussian Process Toolbox"), license = "BSD 3-clause", keywords = "machine-learning gaussian-processes kernels", @@ -58,12 +80,13 @@ setup(name = 'GPy', package_dir={'GPy': 'GPy'}, package_data = {'GPy': ['defaults.cfg', 'installation.cfg', 'util/data_resources.json', - 'util/football_teams.json']}, + 'util/football_teams.json', + ]}, include_package_data = True, py_modules = ['GPy.__init__'], test_suite = 'GPy.testing', - long_description=read('README.md'), - install_requires=['numpy>=1.7', 'scipy>=0.12'], + long_description=read_to_rst('README.md'), + install_requires=['numpy>=1.7', 'scipy>=0.16', 'six'], extras_require = {'docs':['matplotlib >=1.3','Sphinx','IPython']}, classifiers=['License :: OSI Approved :: BSD License', 'Natural Language :: English',