From 1e06c6ce2f242e9581aa2c829cebe788d6f3258d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Masha=20Naslidnyk=20=F0=9F=A6=89?= Date: Thu, 5 Sep 2019 14:39:13 +0100 Subject: [PATCH 001/137] Update self.num_data in GP when X is updated --- GPy/core/gp.py | 6 ++++-- GPy/testing/gp_tests.py | 13 ++++++++++++- 2 files changed, 16 insertions(+), 3 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 1e2e3611..d8f1e758 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -235,6 +235,8 @@ class GP(Model): self.link_parameter(self.X, index=index) else: self.X = ObsAr(X) + + self.num_data, self.input_dim = self.X.shape self.update_model(True) def set_X(self,X): @@ -587,9 +589,9 @@ class GP(Model): :param size: the number of a posteriori samples. :type size: int. :returns: set of simulations - :rtype: np.ndarray (Nnew x D x samples) + :rtype: np.ndarray (Nnew x D x samples) """ - predict_kwargs["full_cov"] = True # Always use the full covariance for posterior samples. + predict_kwargs["full_cov"] = True # Always use the full covariance for posterior samples. m, v = self._raw_predict(X, **predict_kwargs) if self.normalizer is not None: m, v = self.normalizer.inverse_mean(m), self.normalizer.inverse_variance(v) diff --git a/GPy/testing/gp_tests.py b/GPy/testing/gp_tests.py index 97e3718d..1f44304d 100644 --- a/GPy/testing/gp_tests.py +++ b/GPy/testing/gp_tests.py @@ -28,11 +28,14 @@ class Test(unittest.TestCase): Xnew = NormalPosterior(m.X.mean[:10].copy(), m.X.variance[:10].copy()) m.set_XY(Xnew, m.Y[:10].copy()) assert(m.checkgrad()) + + assert(m.num_data == m.X.shape[0]) + assert(m.input_dim == m.X.shape[1]) + 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) @@ -42,6 +45,10 @@ class Test(unittest.TestCase): Xnew = X[:10].copy() m.set_XY(Xnew, m.Y[:10].copy()) assert(m.checkgrad()) + + assert(m.num_data == m.X.shape[0]) + assert(m.input_dim == m.X.shape[1]) + m.set_XY(X, self.Y) mu2, var2 = m.predict(m.X) np.testing.assert_allclose(mu, mu2) @@ -54,6 +61,10 @@ class Test(unittest.TestCase): X = m.X.copy() m.set_XY(m.X[:10], m.Y[:10]) assert(m.checkgrad()) + + assert(m.num_data == m.X.shape[0]) + assert(m.input_dim == m.X.shape[1]) + m.set_XY(X, self.Y) mu2, var2 = m.predict(m.X) np.testing.assert_allclose(mu, mu2) From 5c4c191b6aed819d2a55ea5a701163d341a8693e Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 17 Oct 2019 08:56:36 +0100 Subject: [PATCH 002/137] Update appveyor.yml --- appveyor.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/appveyor.yml b/appveyor.yml index 14a31c95..0bb6e01a 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -3,7 +3,7 @@ environment: secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00= COVERALLS_REPO_TOKEN: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS - gpy_version: 1.9.8 + gpy_version: 1.9.9 matrix: - PYTHON_VERSION: 2.7 MINICONDA: C:\Miniconda-x64 From 5a907bd01396a0b66b9547372273adcc3d5d848d Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 17 Oct 2019 08:57:01 +0100 Subject: [PATCH 003/137] Update setup.cfg --- setup.cfg | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.cfg b/setup.cfg index 081fd450..913a7c55 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.9.8 +current_version = 1.9.9 tag = True commit = True From d1c35ec46759117e9327bc02333431ee20e6a458 Mon Sep 17 00:00:00 2001 From: Hugo van Kemenade Date: Tue, 5 Nov 2019 15:52:49 +0200 Subject: [PATCH 004/137] Stop using legacy bdist_wininst --- appveyor.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/appveyor.yml b/appveyor.yml index 0bb6e01a..d212e3b4 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -51,7 +51,7 @@ test_script: after_test: # This step builds your wheels. - - "python setup.py bdist_wheel bdist_wininst" + - "python setup.py bdist_wheel" - codecov artifacts: From 1a67b0d212b0ad80412b36c626dec2a89b5891d8 Mon Sep 17 00:00:00 2001 From: Mark McLeod Date: Mon, 11 Nov 2019 08:17:14 +0000 Subject: [PATCH 005/137] fix: reorder brackets to avoid an n^2 array --- GPy/inference/latent_function_inference/var_dtc.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/GPy/inference/latent_function_inference/var_dtc.py b/GPy/inference/latent_function_inference/var_dtc.py index 9870015d..b4c9bfdf 100644 --- a/GPy/inference/latent_function_inference/var_dtc.py +++ b/GPy/inference/latent_function_inference/var_dtc.py @@ -142,8 +142,7 @@ class VarDTC(LatentFunctionInference): Cpsi1Vf, _ = dtrtrs(Lm, tmp, lower=1, trans=1) # data fit and derivative of L w.r.t. Kmm - dL_dm = -np.dot((_LBi_Lmi_psi1.T.dot(_LBi_Lmi_psi1)) - - np.eye(Y.shape[0]), VVT_factor) + dL_dm = -_LBi_Lmi_psi1.T.dot(_LBi_Lmi_psi1.dot(VVT_factor)) + VVT_factor delit = tdot(_LBi_Lmi_psi1Vf) data_fit = np.trace(delit) From c0b8de4d9250d0ba306f5f62d9d57bda113873b3 Mon Sep 17 00:00:00 2001 From: Sigrid Passano Hellan Date: Fri, 6 Dec 2019 17:58:32 +0000 Subject: [PATCH 006/137] Minor fix to multioutput regression example, to clarify code + typo. --- GPy/examples/regression.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/GPy/examples/regression.py b/GPy/examples/regression.py index 583f12a9..93e05cbb 100644 --- a/GPy/examples/regression.py +++ b/GPy/examples/regression.py @@ -620,8 +620,10 @@ def multioutput_gp_with_derivative_observations(): # Then create the model, we give everything in lists, the order of the inputs indicates the order of the outputs # Now we have the regular observations first and derivative observations second, meaning that the kernels and - # the likelihoods must follow the same order. Crosscovariances are automatically taken car of - m = GPy.models.MultioutputGP(X_list=[x, xd], Y_list=[y, yd], kernel_list=[se, se_der], likelihood_list = [gauss, gauss]) + # the likelihoods must follow the same order. Crosscovariances are automatically taken care of + m = GPy.models.MultioutputGP(X_list=[x, xd], Y_list=[y, yd], + kernel_list=[se, se_der], + likelihood_list=[gauss, gauss_der]) # Optimize the model m.optimize(messages=0, ipython_notebook=False) From c122c268431407f08902c3b1f947d58c364b7f09 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Wed, 8 Jan 2020 15:24:59 -0800 Subject: [PATCH 007/137] added missing import --- doc/source/tuto_creating_new_kernels.rst | 2 ++ 1 file changed, 2 insertions(+) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index 9db6adc4..20107026 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -53,6 +53,8 @@ your code. The parameters have to be added by calling :py:class:`~GPy.core.parameterization.param.Param` objects as arguments:: + from .core.parameterization import Param + def __init__(self,input_dim,variance=1.,lengthscale=1.,power=1.,active_dims=None): super(RationalQuadratic, self).__init__(input_dim, active_dims, 'rat_quad') assert input_dim == 1, "For this kernel we assume input_dim=1" From 3c753bb1a07ef7038b6916efad52c01846dda616 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Wed, 8 Jan 2020 15:32:46 -0800 Subject: [PATCH 008/137] corrected typo in function name --- doc/source/tuto_creating_new_kernels.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index 20107026..84077f72 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -61,7 +61,7 @@ arguments:: self.variance = Param('variance', variance) self.lengthscale = Param('lengtscale', lengthscale) self.power = Param('power', power) - self.add_parameters(self.variance, self.lengthscale, self.power) + self.link_parameters(self.variance, self.lengthscale, self.power) From now on you can use the parameters ``self.variance, self.lengthscale, self.power`` as normal numpy ``array-like`` s in your From c58104c943be19f57d5bcff2c1520ae3f0cc968a Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Wed, 8 Jan 2020 16:09:59 -0800 Subject: [PATCH 009/137] fixed docstring and added more explanation --- doc/source/tuto_creating_new_kernels.rst | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index 84077f72..426ef95e 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -173,16 +173,23 @@ is set to each ``param``. :: This function is required for GPLVM, BGPLVM, sparse models and uncertain inputs. Computes the derivative of the likelihood with respect to the inputs -``X`` (a :math:`n \times q` np.array). The result is returned by the -function which is a :math:`n \times q` np.array. :: +``X`` (a :math:`n \times q` np.array), that is, it calculates the quantity: + +.. math:: + + \frac{\partial L}{\partial K} \frac{\partial K}{\partial X} + +The partial derivative matrix is, in this case, comes out as an :math:`n \times q` np.array. +Were the number of parameters to be larger than 1 or the number of dimensions likewise any larger +than 1, the calculated partial derivitive would be a 3- or 4-tensor. :: def gradients_X(self,dL_dK,X,X2): - """derivative of the covariance matrix with respect to X.""" + """derivative of the likelihood matrix with respect to X, calculated using dK_dX""" if X2 is None: X2 = X dist2 = np.square((X-X2.T)/self.lengthscale) - dX = -self.variance*self.power * (X-X2.T)/self.lengthscale**2 * (1 + dist2/2./self.lengthscale)**(-self.power-1) - return np.sum(dL_dK*dX,1)[:,None] + dK_dX = -self.variance*self.power * (X-X2.T)/self.lengthscale**2 * (1 + dist2/2./self.lengthscale)**(-self.power-1) + return np.sum(dL_dK*dK_dX,1)[:,None] :py:func:`~GPy.kern.src.kern.Kern.gradients_X_diag` ``(self,dL_dKdiag,X)`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ From 585d9cc92be550d1ff309ffa3e22adb97172c52a Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Wed, 8 Jan 2020 16:10:58 -0800 Subject: [PATCH 010/137] changed ordering of explanation to get to the point fast and provide additional details after --- doc/source/tuto_creating_new_kernels.rst | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index 426ef95e..05e32af0 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -179,9 +179,7 @@ Computes the derivative of the likelihood with respect to the inputs \frac{\partial L}{\partial K} \frac{\partial K}{\partial X} -The partial derivative matrix is, in this case, comes out as an :math:`n \times q` np.array. -Were the number of parameters to be larger than 1 or the number of dimensions likewise any larger -than 1, the calculated partial derivitive would be a 3- or 4-tensor. :: +The partial derivative matrix is, in this case, comes out as an :math:`n \times q` np.array. :: def gradients_X(self,dL_dK,X,X2): """derivative of the likelihood matrix with respect to X, calculated using dK_dX""" @@ -191,6 +189,9 @@ than 1, the calculated partial derivitive would be a 3- or 4-tensor. :: dK_dX = -self.variance*self.power * (X-X2.T)/self.lengthscale**2 * (1 + dist2/2./self.lengthscale)**(-self.power-1) return np.sum(dL_dK*dK_dX,1)[:,None] +Were the number of parameters to be larger than 1 or the number of dimensions likewise any larger +than 1, the calculated partial derivitive would be a 3- or 4-tensor. + :py:func:`~GPy.kern.src.kern.Kern.gradients_X_diag` ``(self,dL_dKdiag,X)`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ From 7871af8dec93070e0e9db542b35cc499e3a3defa Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Masha=20Naslidnyk=20=F0=9F=A6=89?= Date: Fri, 10 Jan 2020 12:42:03 +0000 Subject: [PATCH 011/137] self.num_data and self.input_dim are set dynamically in class GP() after the shape of X. In MRD, the user-specific values are passed around until X is defined. --- GPy/core/gp.py | 11 ++++++++--- GPy/models/mrd.py | 24 ++++++++++-------------- 2 files changed, 18 insertions(+), 17 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index d8f1e758..0f6b2a01 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -43,8 +43,6 @@ class GP(Model): self.X = X.copy() else: self.X = ObsAr(X) - self.num_data, self.input_dim = self.X.shape - assert Y.ndim == 2 logger.info("initializing Y") @@ -199,6 +197,14 @@ class GP(Model): def _predictive_variable(self): return self.X + @property + def num_data(self): + return self.X.shape[0] + + @property + def input_dim(self): + return self.X.shape[1] + def set_XY(self, X=None, Y=None): """ Set the input / output data of the model @@ -236,7 +242,6 @@ class GP(Model): else: self.X = ObsAr(X) - self.num_data, self.input_dim = self.X.shape self.update_model(True) def set_X(self,X): diff --git a/GPy/models/mrd.py b/GPy/models/mrd.py index 4239f7a9..3c8cd4d1 100644 --- a/GPy/models/mrd.py +++ b/GPy/models/mrd.py @@ -63,7 +63,6 @@ class MRD(BayesianGPLVMMiniBatch): Ynames=None, normalizer=False, stochastic=False, batchsize=10): self.logger = logging.getLogger(self.__class__.__name__) - self.input_dim = input_dim self.num_inducing = num_inducing if isinstance(Ylist, dict): @@ -87,11 +86,11 @@ class MRD(BayesianGPLVMMiniBatch): self.inference_method = inference_method if X is None: - X, fracs = self._init_X(initx, Ylist) + X, fracs = self._init_X(input_dim, initx, Ylist) else: fracs = [X.var(0)]*len(Ylist) - Z = self._init_Z(initz, X) + Z = self._init_Z(initz, X, input_dim) self.Z = Param('inducing inputs', Z) self.num_inducing = self.Z.shape[0] # ensure M==N if M>N @@ -128,7 +127,6 @@ class MRD(BayesianGPLVMMiniBatch): self.unlink_parameter(self.likelihood) self.unlink_parameter(self.kern) - self.num_data = Ylist[0].shape[0] if isinstance(batchsize, int): batchsize = itertools.repeat(batchsize) @@ -187,32 +185,32 @@ class MRD(BayesianGPLVMMiniBatch): def log_likelihood(self): return self._log_marginal_likelihood - def _init_X(self, init='PCA', Ylist=None): + def _init_X(self, input_dim, init='PCA', Ylist=None): if Ylist is None: Ylist = self.Ylist if init in "PCA_concat": - X, fracs = initialize_latent('PCA', self.input_dim, np.hstack(Ylist)) + X, fracs = initialize_latent('PCA', input_dim, np.hstack(Ylist)) fracs = [fracs]*len(Ylist) elif init in "PCA_single": - X = np.zeros((Ylist[0].shape[0], self.input_dim)) - fracs = np.empty((len(Ylist), self.input_dim)) - for qs, Y in zip(np.array_split(np.arange(self.input_dim), len(Ylist)), Ylist): + X = np.zeros((Ylist[0].shape[0], input_dim)) + fracs = np.empty((len(Ylist), input_dim)) + for qs, Y in zip(np.array_split(np.arange(input_dim), len(Ylist)), Ylist): x, frcs = initialize_latent('PCA', len(qs), Y) X[:, qs] = x fracs[:, qs] = frcs else: # init == 'random': - X = np.random.randn(Ylist[0].shape[0], self.input_dim) + X = np.random.randn(Ylist[0].shape[0], input_dim) fracs = X.var(0) fracs = [fracs]*len(Ylist) X -= X.mean() X /= X.std() return X, fracs - def _init_Z(self, init, X): + def _init_Z(self, init, X, input_dim): if init in "permute": Z = np.random.permutation(X.copy())[:self.num_inducing] elif init in "random": - Z = np.random.randn(self.num_inducing, self.input_dim) * X.var() + Z = np.random.randn(self.num_inducing, input_dim) * X.var() return Z def predict(self, Xnew, full_cov=False, Y_metadata=None, kern=None, Yindex=0): @@ -350,5 +348,3 @@ class MRD(BayesianGPLVMMiniBatch): print('# Private dimensions model ' + str(i) + ':' + str(privateDims[i])) return sharedDims, privateDims - - From 3c80c6e30f5db8c05547f0ffd186e257074103a9 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Tue, 14 Jan 2020 11:52:03 -0800 Subject: [PATCH 012/137] fixed technical description of gradients_X() --- doc/source/tuto_creating_new_kernels.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index 05e32af0..386c2991 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -182,7 +182,7 @@ Computes the derivative of the likelihood with respect to the inputs The partial derivative matrix is, in this case, comes out as an :math:`n \times q` np.array. :: def gradients_X(self,dL_dK,X,X2): - """derivative of the likelihood matrix with respect to X, calculated using dK_dX""" + """derivative of the likelihood with respect to X, calculated using dL_dK*dK_dX""" if X2 is None: X2 = X dist2 = np.square((X-X2.T)/self.lengthscale) From 1d9bbaf7512695c16f09466a4679a5d4de3ff585 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Tue, 14 Jan 2020 11:57:41 -0800 Subject: [PATCH 013/137] brushed up wording --- doc/source/tuto_creating_new_kernels.rst | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index 386c2991..ec46aedc 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -73,13 +73,13 @@ automatically. The implementation of this function is optional. -This functions deals as a callback for each optimization iteration. If -one optimization step was successfull and the parameters (added by +This functions is called as a callback upon each successful change to the parameters. If +one optimization step was successfull and the parameters (linked by :py:func:`~GPy.core.parameterization.parameterized.Parameterized.link_parameters` -``(*parameters)``) this callback function will be called to be able to -update any precomputations for the kernel. Do not implement the -gradient updates here, as those are being done by the model enclosing -the kernel:: +``(*parameters)``) are changed, this callback function will be called. This callback may be used to +update precomputations for the kernel. Do not implement the +gradient updates here, as gradient updates are performed by the model enclosing +the kernel. In this example, we issue a no-op:: def parameters_changed(self): # nothing todo here @@ -92,8 +92,9 @@ the kernel:: The implementation of this function in mandatory. This function is used to compute the covariance matrix associated with -the inputs X, X2 (np.arrays with arbitrary number of line (say -:math:`n_1`, :math:`n_2`) and ``self.input_dim`` columns). :: +the inputs X, X2 (np.arrays with arbitrary number of lines, +:math:`n_1`, :math:`n_2`, corresponding to the number of samples over which to calculate covariance) +and ``self.input_dim`` columns. :: def K(self,X,X2): if X2 is None: X2 = X From 7550b1e5efa81c241448fc63c10659405e083693 Mon Sep 17 00:00:00 2001 From: Antoine Blanchard Date: Tue, 14 Jan 2020 15:32:25 -0500 Subject: [PATCH 014/137] fix normalizer --- GPy/core/gp.py | 61 ++++++++++++++++++++++++++++++++++++-- GPy/testing/model_tests.py | 43 +++++++++++++++++++++++++-- 2 files changed, 100 insertions(+), 4 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 1e2e3611..9a326c51 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -451,6 +451,15 @@ class GP(Model): alpha = -2.*np.dot(kern.K(Xnew, self._predictive_variable), self.posterior.woodbury_inv) var_jac += kern.gradients_X(alpha, Xnew, self._predictive_variable) + + if self.normalizer is not None: + mean_jac = self.normalizer.inverse_mean(mean_jac) \ + - self.normalizer.inverse_mean(0.) + if self.output_dim > 1: + var_jac = self.normalizer.inverse_covariance(var_jac) + else: + var_jac = self.normalizer.inverse_variance(var_jac) + return mean_jac, var_jac def predict_jacobian(self, Xnew, kern=None, full_cov=False): @@ -711,11 +720,59 @@ class GP(Model): mu_star, var_star = self._raw_predict(x_test) return self.likelihood.log_predictive_density_sampling(y_test, mu_star, var_star, Y_metadata=Y_metadata, num_samples=num_samples) - def posterior_covariance_between_points(self, X1, X2): + + def _raw_posterior_covariance_between_points(self, X1, X2): """ - Computes the posterior covariance between points. + Computes the posterior covariance between points. Does not account for + normalization or likelihood :param X1: some input observations :param X2: other input observations + + :returns: + cov: raw posterior covariance: k(X1,X2) - k(X1,X) G^{-1} K(X,X2) """ return self.posterior.covariance_between_points(self.kern, self.X, X1, X2) + + + def posterior_covariance_between_points(self, X1, X2, Y_metadata=None, + likelihood=None, + include_likelihood=True): + """ + Computes the posterior covariance between points. Includes likelihood + variance as well as normalization so that evaluation at (x,x) is consistent + with model.predict + + :param X1: some input observations + :param X2: other input observations + :param Y_metadata: metadata about the predicting point to pass to the + likelihood + :param include_likelihood: Whether or not to add likelihood noise to + the predicted underlying latent function f. + :type include_likelihood: bool + + :returns: + cov: posterior covariance, a Numpy array, Nnew x Nnew if + self.output_dim == 1, and Nnew x Nnew x self.output_dim otherwise. + """ + + cov = self._raw_posterior_covariance_between_points(X1, X2) + + if include_likelihood: + # Predict latent mean and push through likelihood + mean, _ = self._raw_predict(X1, full_cov=True) + if likelihood is None: + likelihood = self.likelihood + _, cov = likelihood.predictive_values(mean, cov, full_cov=True, + Y_metadata=Y_metadata) + + if self.normalizer is not None: + if self.output_dim > 1: + cov = self.normalizer.inverse_covariance(cov) + else: + cov = self.normalizer.inverse_variance(cov) + + return cov + + + diff --git a/GPy/testing/model_tests.py b/GPy/testing/model_tests.py index ca39932d..9ee16f99 100644 --- a/GPy/testing/model_tests.py +++ b/GPy/testing/model_tests.py @@ -1168,7 +1168,7 @@ class GradientTests(np.testing.TestCase): Y = np.array([[1], [2]]) m = GPy.models.GPRegression(X1, Y, kernel=k) - result = m.posterior_covariance_between_points(X1, X2) + result = m._raw_posterior_covariance_between_points(X1, X2) expected = np.array([[0.4, 2.2], [1.0, 1.0]]) / 3.0 self.assertTrue(np.allclose(result, expected)) @@ -1179,7 +1179,7 @@ class GradientTests(np.testing.TestCase): m = _create_missing_data_model(k, Q) with self.assertRaises(RuntimeError): - m.posterior_covariance_between_points(np.array([[1], [2]]), np.array([[3], [4]])) + m._raw_posterior_covariance_between_points(np.array([[1], [2]]), np.array([[3], [4]])) def test_multioutput_model_with_derivative_observations(self): f = lambda x: np.sin(x)+0.1*(x-2.)**2-0.005*x**3 @@ -1242,6 +1242,45 @@ class GradientTests(np.testing.TestCase): self.assertTrue(m.checkgrad()) + + def test_predictive_gradients_with_normalizer(self): + """ + Check that model.predictive_gradients returns the gradients of + model.predict when normalizer=True + """ + N, M, Q = 10, 15, 3 + X = np.random.rand(M,Q) + Y = np.random.rand(M,1) + x = np.random.rand(N, Q) + model = GPy.models.GPRegression(X=X, Y=Y, normalizer=True) + from GPy.models import GradientChecker + gm = GradientChecker(lambda x: model.predict(x)[0], + lambda x: model.predictive_gradients(x)[0], + x, 'x') + gc = GradientChecker(lambda x: model.predict(x)[1], + lambda x: model.predictive_gradients(x)[1], + x, 'x') + assert(gm.checkgrad()) + assert(gc.checkgrad()) + + + def test_posterior_covariance_between_points_with_normalizer(self): + """ + Check that model.posterior_covariance_between_points returns + the covariance from model.predict when normalizer=True + """ + np.random.seed(3) + N, M, Q = 10, 15, 3 + X = np.random.rand(M,Q) + Y = np.random.rand(M,1) + x = np.random.rand(2, Q) + model = GPy.models.GPRegression(X=X, Y=Y, normalizer=True) + + c1 = model.posterior_covariance_between_points(x,x) + c2 = model.predict(x, full_cov=True)[1] + np.testing.assert_allclose(c1,c2) + + def _create_missing_data_model(kernel, Q): D1, D2, D3, N, num_inducing = 13, 5, 8, 400, 3 _, _, Ylist = GPy.examples.dimensionality_reduction._simulate_matern(D1, D2, D3, N, num_inducing, False) From 522ccc492f174672cd0e08dd094597236f4936d2 Mon Sep 17 00:00:00 2001 From: kae_mihara Date: Mon, 9 Mar 2020 11:56:23 +0800 Subject: [PATCH 015/137] fix ImportError in likelihood.py in function log_predictive_density_sampling --- GPy/likelihoods/likelihood.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index bd84b72c..0f17a883 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -218,7 +218,7 @@ class Likelihood(Parameterized): #fi_samples = np.random.randn(num_samples)*np.sqrt(var_star) + mu_star fi_samples = np.random.normal(mu_star, np.sqrt(var_star), size=(mu_star.shape[0], num_samples)) - from scipy.misc import logsumexp + from scipy.special import logsumexp log_p_ystar = -np.log(num_samples) + logsumexp(self.logpdf(fi_samples, y_test, Y_metadata=Y_metadata), axis=1) log_p_ystar = np.array(log_p_ystar).reshape(*y_test.shape) return log_p_ystar From 31ef0f2844a778b89b5fea1cd0705b1eb0ca5838 Mon Sep 17 00:00:00 2001 From: kae_mihara Date: Mon, 9 Mar 2020 19:23:08 +0800 Subject: [PATCH 016/137] Update setup.py bump min require version of scipy to 1.3.0 --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 523c4433..4d1fa0b5 100644 --- a/setup.py +++ b/setup.py @@ -164,7 +164,7 @@ setup(name = 'GPy', py_modules = ['GPy.__init__'], test_suite = 'GPy.testing', setup_requires = ['numpy>=1.7'], - install_requires = ['numpy>=1.7', 'scipy>=0.16', 'six', 'paramz>=0.9.0'], + install_requires = ['numpy>=1.7', 'scipy>=1.3.0', 'six', 'paramz>=0.9.0'], extras_require = {'docs':['sphinx'], 'optional':['mpi4py', 'ipython>=4.0.0', From 19b572eff6ef0e60a90eb1ae2975acd1ac004563 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Tue, 7 Apr 2020 20:37:05 +0100 Subject: [PATCH 017/137] Add cython into installation requirement --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 4d1fa0b5..abc4b4b4 100644 --- a/setup.py +++ b/setup.py @@ -164,7 +164,7 @@ setup(name = 'GPy', py_modules = ['GPy.__init__'], test_suite = 'GPy.testing', setup_requires = ['numpy>=1.7'], - install_requires = ['numpy>=1.7', 'scipy>=1.3.0', 'six', 'paramz>=0.9.0'], + install_requires = ['numpy>=1.7', 'scipy>=1.3.0', 'six', 'paramz>=0.9.0', 'cython>=0.29'], extras_require = {'docs':['sphinx'], 'optional':['mpi4py', 'ipython>=4.0.0', From 4b742698151fd89d24be5194287fa7a0f466ca57 Mon Sep 17 00:00:00 2001 From: lagph <49130858+lagph@users.noreply.github.com> Date: Wed, 8 Apr 2020 16:00:20 +0100 Subject: [PATCH 018/137] Coregionalized regression bugfix (#824) * route default arg W_rank correctly (Addresses #823) --- GPy/models/gp_coregionalized_regression.py | 2 +- GPy/models/sparse_gp_coregionalized_regression.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/GPy/models/gp_coregionalized_regression.py b/GPy/models/gp_coregionalized_regression.py index 66edb8d7..6604f634 100644 --- a/GPy/models/gp_coregionalized_regression.py +++ b/GPy/models/gp_coregionalized_regression.py @@ -38,7 +38,7 @@ class GPCoregionalizedRegression(GP): if kernel is None: kernel = kern.RBF(X.shape[1]-1) - kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=1,name=kernel_name) + kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=W_rank,name=kernel_name) #Likelihood likelihood = util.multioutput.build_likelihood(Y_list,self.output_index,likelihoods_list) diff --git a/GPy/models/sparse_gp_coregionalized_regression.py b/GPy/models/sparse_gp_coregionalized_regression.py index 88841891..2a19d52c 100644 --- a/GPy/models/sparse_gp_coregionalized_regression.py +++ b/GPy/models/sparse_gp_coregionalized_regression.py @@ -44,7 +44,7 @@ class SparseGPCoregionalizedRegression(SparseGP): if kernel is None: kernel = kern.RBF(X.shape[1]-1) - kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=1,name=kernel_name) + kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=W_rank, name=kernel_name) #Likelihood likelihood = util.multioutput.build_likelihood(Y_list,self.output_index,likelihoods_list) From 8b74bbf6b9e1bc0cfeffe472d6279e07455affdf Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Tue, 5 May 2020 22:15:46 +0200 Subject: [PATCH 019/137] Drop Python 2.7 support (fix #833) --- .travis.yml | 3 --- README.md | 2 +- appveyor.yml | 2 -- setup.py | 2 +- 4 files changed, 2 insertions(+), 7 deletions(-) diff --git a/.travis.yml b/.travis.yml index 038bab01..a1d69b38 100644 --- a/.travis.yml +++ b/.travis.yml @@ -14,9 +14,6 @@ addons: # - "$HOME/install/" env: - - PYTHON_VERSION=2.7 - #- PYTHON_VERSION=3.3 - #- PYTHON_VERSION=3.4 - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 - PYTHON_VERSION=3.7 diff --git a/README.md b/README.md index 0a00823f..386087c2 100644 --- a/README.md +++ b/README.md @@ -76,7 +76,7 @@ If that is the case, it is best to clean the repo and reinstall. [](http://www.apple.com/osx/) [](https://en.wikipedia.org/wiki/List_of_Linux_distributions) -Python 2.7, 3.5 and higher +Python 3.5 and higher ## Citation diff --git a/appveyor.yml b/appveyor.yml index d212e3b4..63fa571c 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -5,8 +5,6 @@ environment: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS gpy_version: 1.9.9 matrix: - - PYTHON_VERSION: 2.7 - MINICONDA: C:\Miniconda-x64 - PYTHON_VERSION: 3.5 MINICONDA: C:\Miniconda35-x64 - PYTHON_VERSION: 3.6 diff --git a/setup.py b/setup.py index abc4b4b4..6e7598e4 100644 --- a/setup.py +++ b/setup.py @@ -182,9 +182,9 @@ setup(name = 'GPy', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Microsoft :: Windows', 'Operating System :: POSIX :: Linux', - 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', 'Framework :: IPython', 'Intended Audience :: Science/Research', 'Intended Audience :: Developers', From 4aa2ea9f5e54c6bca93adc3b9ba2fe3d252475d9 Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Tue, 5 May 2020 22:17:05 +0200 Subject: [PATCH 020/137] travis, appveyor: Add Python 3.8 build --- .travis.yml | 1 + appveyor.yml | 2 ++ setup.py | 1 + 3 files changed, 4 insertions(+) diff --git a/.travis.yml b/.travis.yml index a1d69b38..36c3c74f 100644 --- a/.travis.yml +++ b/.travis.yml @@ -17,6 +17,7 @@ env: - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 - PYTHON_VERSION=3.7 + - PYTHON_VERSION=3.8 before_install: - wget https://github.com/mzwiessele/travis_scripts/raw/master/download_miniconda.sh diff --git a/appveyor.yml b/appveyor.yml index 63fa571c..633184da 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -11,6 +11,8 @@ environment: MINICONDA: C:\Miniconda36-x64 - PYTHON_VERSION: 3.7 MINICONDA: C:\Miniconda36-x64 + - PYTHON_VERSION: 3.8 + MINICONDA: C:\Miniconda36-x64 #configuration: # - Debug diff --git a/setup.py b/setup.py index 6e7598e4..58fe7945 100644 --- a/setup.py +++ b/setup.py @@ -185,6 +185,7 @@ setup(name = 'GPy', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', 'Framework :: IPython', 'Intended Audience :: Science/Research', 'Intended Audience :: Developers', From 2d2bed53fcddd2530b8903830ba76411d8817a4f Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Wed, 17 Jun 2020 15:36:46 +0200 Subject: [PATCH 021/137] README: Fix scipy version number --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 386087c2..171c0369 100644 --- a/README.md +++ b/README.md @@ -93,7 +93,7 @@ We like to pronounce it 'g-pie'. ## Getting started: installing with pip -We are now requiring the newest version (0.16) of +We are requiring a recent version (1.3.0 or later) of [scipy](http://www.scipy.org/) and thus, we strongly recommend using the [anaconda python distribution](http://continuum.io/downloads). With anaconda you can install GPy by the following: @@ -111,7 +111,7 @@ And finally, pip install gpy -We've also had luck with [enthought](http://www.enthought.com). Install scipy 0.16 (or later) +We've also had luck with [enthought](http://www.enthought.com). Install scipy 1.3.0 (or later) and then pip install GPy: pip install gpy From 62c7ebec0d27fa3c0dd4f037b99712317ba8170a Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Wed, 17 Jun 2020 15:51:40 +0200 Subject: [PATCH 022/137] setup.py: Install scipy < 1.5.0 when using Python 3.5 --- setup.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 58fe7945..735078bc 100644 --- a/setup.py +++ b/setup.py @@ -117,6 +117,11 @@ try: except ModuleNotFoundError: ext_mods = [] +install_requirements = ['numpy>=1.7', 'six', 'paramz>=0.9.0', 'cython>=0.29'] +if sys.version_info < (3, 6): + install_requirements += ['scipy>=1.3.0,<1.5.0'] +else: + install_requirements += ['scipy>=1.3.0'] setup(name = 'GPy', version = __version__, @@ -164,7 +169,7 @@ setup(name = 'GPy', py_modules = ['GPy.__init__'], test_suite = 'GPy.testing', setup_requires = ['numpy>=1.7'], - install_requires = ['numpy>=1.7', 'scipy>=1.3.0', 'six', 'paramz>=0.9.0', 'cython>=0.29'], + install_requires = install_requirements, extras_require = {'docs':['sphinx'], 'optional':['mpi4py', 'ipython>=4.0.0', From 599e7a4b24f766a31eacffd3f613f5f4369139b3 Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Thu, 18 Jun 2020 14:07:27 +0200 Subject: [PATCH 023/137] plotting_tests.py: Use os.makedirs instead of matplotlib.cbook.mkdirs (fix #844) --- GPy/testing/plotting_tests.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/testing/plotting_tests.py b/GPy/testing/plotting_tests.py index 20032ca6..23564ff3 100644 --- a/GPy/testing/plotting_tests.py +++ b/GPy/testing/plotting_tests.py @@ -87,7 +87,7 @@ def _image_directories(): result_dir = os.path.join(basedir, 'testresult','.') baseline_dir = os.path.join(basedir, 'baseline','.') if not os.path.exists(result_dir): - cbook.mkdirs(result_dir) + os.makedirs(result_dir) return baseline_dir, result_dir baseline_dir, result_dir = _image_directories() From 5dd81288f246144e55b34703083409d33c7055a1 Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Sun, 3 May 2020 22:07:19 +0200 Subject: [PATCH 024/137] Use super().__init__ consistently, instead of sometimes calling base class __init__ directly --- GPy/core/gp_grid.py | 2 +- GPy/core/sparse_gp.py | 2 +- GPy/mappings/compound.py | 2 +- GPy/mappings/constant.py | 2 +- GPy/mappings/identity.py | 2 +- GPy/mappings/kernel.py | 2 +- GPy/mappings/piecewise_linear.py | 2 +- GPy/models/bcgplvm.py | 2 +- GPy/models/gp_classification.py | 4 ++-- .../gp_kronecker_gaussian_regression.py | 2 +- GPy/models/sparse_gp_classification.py | 10 ++++---- GPy/models/sparse_gp_minibatch.py | 7 +++++- GPy/models/sparse_gp_regression.py | 2 +- GPy/models/sparse_gp_regression_md.py | 2 +- GPy/models/sparse_gplvm.py | 2 +- GPy/plotting/matplot_dep/visualize.py | 24 +++++++++---------- GPy/testing/kernel_tests.py | 12 +++++----- GPy/testing/rv_transformation_tests.py | 2 +- GPy/util/mocap.py | 6 ++--- 19 files changed, 47 insertions(+), 42 deletions(-) diff --git a/GPy/core/gp_grid.py b/GPy/core/gp_grid.py index 3cd7d8cb..cfb96fd4 100644 --- a/GPy/core/gp_grid.py +++ b/GPy/core/gp_grid.py @@ -46,7 +46,7 @@ class GpGrid(GP): inference_method = gaussian_grid_inference.GaussianGridInference() - GP.__init__(self, X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer) + super(GpGrid, self).__init__(X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer) self.posterior = None def parameters_changed(self): diff --git a/GPy/core/sparse_gp.py b/GPy/core/sparse_gp.py index d9439d28..95940282 100644 --- a/GPy/core/sparse_gp.py +++ b/GPy/core/sparse_gp.py @@ -53,7 +53,7 @@ class SparseGP(GP): self.Z = Param('inducing inputs', Z) self.num_inducing = Z.shape[0] - GP.__init__(self, X, Y, kernel, likelihood, mean_function, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer) + super(SparseGP, self).__init__(X, Y, kernel, likelihood, mean_function, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer) logger.info("Adding Z as parameter") self.link_parameter(self.Z, index=0) diff --git a/GPy/mappings/compound.py b/GPy/mappings/compound.py index 5a1e8dd1..9078910f 100644 --- a/GPy/mappings/compound.py +++ b/GPy/mappings/compound.py @@ -21,7 +21,7 @@ class Compound(Mapping): def __init__(self, mapping1, mapping2): assert(mapping1.output_dim==mapping2.input_dim) input_dim, output_dim = mapping1.input_dim, mapping2.output_dim - Mapping.__init__(self, input_dim=input_dim, output_dim=output_dim) + super(Compound, self).__init__(input_dim=input_dim, output_dim=output_dim) self.mapping1 = mapping1 self.mapping2 = mapping2 self.link_parameters(self.mapping1, self.mapping2) diff --git a/GPy/mappings/constant.py b/GPy/mappings/constant.py index 315b47b7..281d72d2 100644 --- a/GPy/mappings/constant.py +++ b/GPy/mappings/constant.py @@ -21,7 +21,7 @@ class Constant(Mapping): """ def __init__(self, input_dim, output_dim, value=0., name='constmap'): - Mapping.__init__(self, input_dim=input_dim, output_dim=output_dim, name=name) + super(Constant, self).__init__(input_dim=input_dim, output_dim=output_dim, name=name) value = np.atleast_1d(value) if not len(value.shape) ==1: raise ValueError("bad constant values: pass a float or flat vectoor") diff --git a/GPy/mappings/identity.py b/GPy/mappings/identity.py index 3567b694..3a5a2ac5 100644 --- a/GPy/mappings/identity.py +++ b/GPy/mappings/identity.py @@ -8,7 +8,7 @@ class Identity(Mapping): A mapping that does nothing! """ def __init__(self, input_dim, output_dim, name='identity'): - Mapping.__init__(self, input_dim, output_dim, name) + super(Identity, self).__init__(input_dim, output_dim, name) def f(self, X): return X diff --git a/GPy/mappings/kernel.py b/GPy/mappings/kernel.py index ea1720db..18b77126 100644 --- a/GPy/mappings/kernel.py +++ b/GPy/mappings/kernel.py @@ -33,7 +33,7 @@ class Kernel(Mapping): """ def __init__(self, input_dim, output_dim, Z, kernel, name='kernmap'): - Mapping.__init__(self, input_dim=input_dim, output_dim=output_dim, name=name) + super(Kernel, self).__init__(input_dim=input_dim, output_dim=output_dim, name=name) self.kern = kernel self.Z = Z self.num_bases, Zdim = Z.shape diff --git a/GPy/mappings/piecewise_linear.py b/GPy/mappings/piecewise_linear.py index 8bdee81e..37ec65fb 100644 --- a/GPy/mappings/piecewise_linear.py +++ b/GPy/mappings/piecewise_linear.py @@ -15,7 +15,7 @@ class PiecewiseLinear(Mapping): assert input_dim==1 assert output_dim==1 - Mapping.__init__(self, input_dim, output_dim, name) + super(PiecewiseLinear, self).__init__(input_dim, output_dim, name) values, breaks = np.array(values).flatten(), np.array(breaks).flatten() assert values.size == breaks.size diff --git a/GPy/models/bcgplvm.py b/GPy/models/bcgplvm.py index 7462fa27..c2baf2b5 100644 --- a/GPy/models/bcgplvm.py +++ b/GPy/models/bcgplvm.py @@ -30,7 +30,7 @@ class BCGPLVM(GPLVM): 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") + super(BCGPLVM, self).__init__(Y, input_dim, X=mapping.f(Y), kernel=kernel, name="bcgplvm") self.unlink_parameter(self.X) self.mapping = mapping self.link_parameter(self.mapping) diff --git a/GPy/models/gp_classification.py b/GPy/models/gp_classification.py index 8a68e74d..8bd01a28 100644 --- a/GPy/models/gp_classification.py +++ b/GPy/models/gp_classification.py @@ -35,8 +35,8 @@ class GPClassification(GP): if inference_method is None: inference_method = EP() - GP.__init__(self, X=X, Y=Y, kernel=kernel, likelihood=likelihood, inference_method=inference_method, - mean_function=mean_function, name='gp_classification', normalizer=normalizer) + super(GPClassification, self).__init__(X=X, Y=Y, kernel=kernel, likelihood=likelihood, inference_method=inference_method, + mean_function=mean_function, name='gp_classification', normalizer=normalizer) @staticmethod def from_gp(gp): diff --git a/GPy/models/gp_kronecker_gaussian_regression.py b/GPy/models/gp_kronecker_gaussian_regression.py index 44177b16..ca9a3f80 100644 --- a/GPy/models/gp_kronecker_gaussian_regression.py +++ b/GPy/models/gp_kronecker_gaussian_regression.py @@ -29,7 +29,7 @@ class GPKroneckerGaussianRegression(Model): """ def __init__(self, X1, X2, Y, kern1, kern2, noise_var=1., name='KGPR'): - Model.__init__(self, name=name) + super(GPKroneckerGaussianRegression, self).__init__(name=name) # accept the construction arguments self.X1 = ObsAr(X1) diff --git a/GPy/models/sparse_gp_classification.py b/GPy/models/sparse_gp_classification.py index 296b70f4..4713b3e9 100644 --- a/GPy/models/sparse_gp_classification.py +++ b/GPy/models/sparse_gp_classification.py @@ -46,8 +46,8 @@ class SparseGPClassification(SparseGP): if inference_method is None: inference_method = EPDTC() - SparseGP.__init__(self, X, Y, Z, kernel, likelihood, mean_function=mean_function, inference_method=inference_method, - normalizer=normalizer, name='SparseGPClassification', Y_metadata=Y_metadata) + super(SparseGPClassification, self).__init__(X, Y, Z, kernel, likelihood, mean_function=mean_function, inference_method=inference_method, + normalizer=normalizer, name='SparseGPClassification', Y_metadata=Y_metadata) @staticmethod def from_sparse_gp(sparse_gp): @@ -136,9 +136,9 @@ class SparseGPClassificationUncertainInput(SparseGP): X = NormalPosterior(X, X_variance) - SparseGP.__init__(self, X, Y, Z, kernel, likelihood, - inference_method=EPDTC(), - name='SparseGPClassification', Y_metadata=Y_metadata, normalizer=normalizer) + super(SparseGPClassificationUncertainInput, self).__init__(X, Y, Z, kernel, likelihood, + inference_method=EPDTC(), name='SparseGPClassification', + Y_metadata=Y_metadata, normalizer=normalizer) def parameters_changed(self): #Compute the psi statistics for N once, but don't sum out N in psi2 diff --git a/GPy/models/sparse_gp_minibatch.py b/GPy/models/sparse_gp_minibatch.py index d1c252f8..68b92618 100644 --- a/GPy/models/sparse_gp_minibatch.py +++ b/GPy/models/sparse_gp_minibatch.py @@ -43,6 +43,10 @@ class SparseGPMiniBatch(SparseGP): missing_data=False, stochastic=False, batchsize=1): self._update_stochastics = False + # FIXME(?): Half of this function seems to be copy-pasted from + # SparseGP.__init, any particular reason why SparseGP.__init + # is not called (instead of calling GP.__init__ directly)? + # pick a sensible inference method if inference_method is None: if isinstance(likelihood, likelihoods.Gaussian): @@ -56,7 +60,8 @@ class SparseGPMiniBatch(SparseGP): self.Z = Param('inducing inputs', Z) self.num_inducing = Z.shape[0] - GP.__init__(self, X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer) + # Skip SparseGP.__init (see remark above) + super(SparseGP, self).__init__(X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer) self.missing_data = missing_data if stochastic and missing_data: diff --git a/GPy/models/sparse_gp_regression.py b/GPy/models/sparse_gp_regression.py index 8b78ac43..4751ed99 100644 --- a/GPy/models/sparse_gp_regression.py +++ b/GPy/models/sparse_gp_regression.py @@ -55,7 +55,7 @@ class SparseGPRegression(SparseGP_MPI): else: infr = VarDTC() - SparseGP_MPI.__init__(self, X, Y, Z, kernel, likelihood, mean_function=mean_function, + super(SparseGPRegression, self).__init__(X, Y, Z, kernel, likelihood, mean_function=mean_function, inference_method=infr, normalizer=normalizer, mpi_comm=mpi_comm, name=name) def parameters_changed(self): diff --git a/GPy/models/sparse_gp_regression_md.py b/GPy/models/sparse_gp_regression_md.py index 4dcfc150..9e601e96 100644 --- a/GPy/models/sparse_gp_regression_md.py +++ b/GPy/models/sparse_gp_regression_md.py @@ -58,7 +58,7 @@ class SparseGPRegressionMD(SparseGP_MPI): infr = VarDTC_MD() - SparseGP_MPI.__init__(self, X, Y, Z, kernel, likelihood, inference_method=infr, normalizer=normalizer, mpi_comm=mpi_comm, name=name) + super(SparseGPRegressionMD, self).__init__(X, Y, Z, kernel, likelihood, inference_method=infr, normalizer=normalizer, mpi_comm=mpi_comm, name=name) self.output_dim = output_dim def parameters_changed(self): diff --git a/GPy/models/sparse_gplvm.py b/GPy/models/sparse_gplvm.py index 53696b45..1ed6d10c 100644 --- a/GPy/models/sparse_gplvm.py +++ b/GPy/models/sparse_gplvm.py @@ -23,7 +23,7 @@ class SparseGPLVM(SparseGPRegression): from ..util.initialization import initialize_latent X, fracs = initialize_latent(init, input_dim, Y) X = Param('latent space', X) - SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing) + super(SparseGPLVM, self).__init__(X, Y, kernel=kernel, num_inducing=num_inducing) self.link_parameter(self.X, 0) def parameters_changed(self): diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index ce95d1ef..d4442dc7 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -36,7 +36,7 @@ class vpython_show(data_show): """ def __init__(self, vals, scene=None): - data_show.__init__(self, vals) + super(vpython_show, self).__init__(vals) # If no axes are defined, create some. if scene==None: @@ -54,7 +54,7 @@ class matplotlib_show(data_show): the matplotlib_show class is a base class for all visualization methods that use matplotlib. It is initialized with an axis. If the axis is set to None it creates a figure window. """ def __init__(self, vals, axes=None): - data_show.__init__(self, vals) + super(matplotlib_show, self).__init__(vals) # If no axes are defined, create some. if axes==None: @@ -72,7 +72,7 @@ class vector_show(matplotlib_show): vector elements alongside their indices. """ def __init__(self, vals, axes=None): - matplotlib_show.__init__(self, vals, axes) + super(vector_show, self).__init__(vals, axes) #assert vals.ndim == 2, "Please give a vector in [n x 1] to plot" #assert vals.shape[1] == 1, "only showing a vector in one dimension" self.size = vals.size @@ -102,7 +102,7 @@ class lvm(matplotlib_show): vals = model.X.values if len(vals.shape)==1: vals = vals[None,:] - matplotlib_show.__init__(self, vals, axes=latent_axes) + super(lvm, self).__init__(vals, axes=latent_axes) if isinstance(latent_axes,mpl.axes.Axes): self.cid = latent_axes.figure.canvas.mpl_connect('button_press_event', self.on_click) @@ -198,10 +198,10 @@ class lvm_subplots(lvm): if i == self.nplots-1: if self.nplots*2!=Model.input_dim: latent_index = [i*2, i*2] - lvm.__init__(self, self.latent_vals, Model, data_visualize, axis, sense_axes, latent_index=latent_index) + super(lvm_subplots, self).__init__(self.latent_vals, Model, data_visualize, axis, sense_axes, latent_index=latent_index) else: latent_index = [i*2, i*2+1] - lvm.__init__(self, self.latent_vals, Model, data_visualize, axis, latent_index=latent_index) + super(lvm_subplots, self).__init__(self.latent_vals, Model, data_visualize, axis, latent_index=latent_index) @@ -223,7 +223,7 @@ class lvm_dimselect(lvm): else: self.sense_axes = sense_axes self.labels = labels - lvm.__init__(self,vals,model,data_visualize,latent_axes,sense_axes,latent_index) + super(lvm_dimselect, self).__init__(vals,model,data_visualize,latent_axes,sense_axes,latent_index) self.show_sensitivities() print(self.latent_values) print("use left and right mouse buttons to select dimensions") @@ -286,7 +286,7 @@ class image_show(matplotlib_show): :type cmap: matplotlib.cm""" def __init__(self, vals, axes=None, dimensions=(16,16), transpose=False, order='C', invert=False, scale=False, palette=[], preset_mean=0., preset_std=1., select_image=0, cmap=None): - matplotlib_show.__init__(self, vals, axes) + super(image_show, self).__init__(vals, axes) self.dimensions = dimensions self.transpose = transpose self.order = order @@ -352,7 +352,7 @@ class mocap_data_show_vpython(vpython_show): """Base class for visualizing motion capture data using visual module.""" def __init__(self, vals, scene=None, connect=None, radius=0.1): - vpython_show.__init__(self, vals, scene) + super(mocap_data_show_vpython, self).__init__(vals, scene) self.radius = radius self.connect = connect self.process_values() @@ -412,7 +412,7 @@ class mocap_data_show(matplotlib_show): if axes==None: fig = plt.figure() axes = fig.add_subplot(111, projection='3d', aspect='equal') - matplotlib_show.__init__(self, vals, axes) + super(mocap_data_show, self).__init__(vals, axes) self.color = color self.connect = connect @@ -496,7 +496,7 @@ class stick_show(mocap_data_show): def __init__(self, vals, connect=None, axes=None): if len(vals.shape)==1: vals = vals[None,:] - mocap_data_show.__init__(self, vals, axes=axes, connect=connect) + super(stick_show, self).__init__(vals, axes=axes, connect=connect) def process_values(self): self.vals = self.vals.reshape((3, self.vals.shape[1]/3)).T @@ -515,7 +515,7 @@ class skeleton_show(mocap_data_show): self.skel = skel self.padding = padding connect = skel.connection_matrix() - mocap_data_show.__init__(self, vals, axes=axes, connect=connect, color=color) + super(skeleton_show, self).__init__(vals, axes=axes, connect=connect, color=color) def process_values(self): """Takes a set of angles and converts them to the x,y,z coordinates in the internal prepresentation of the class, ready for plotting. diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index 9b9cd911..d7140a0b 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -61,7 +61,7 @@ class Kern_check_dK_dtheta(Kern_check_model): respect to parameters. """ def __init__(self, kernel=None, dL_dK=None, X=None, X2=None): - Kern_check_model.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X, X2=X2) + super(Kern_check_dK_dtheta, self).__init__(kernel=kernel,dL_dK=dL_dK, X=X, X2=X2) self.link_parameter(self.kernel) def parameters_changed(self): @@ -74,7 +74,7 @@ class Kern_check_dKdiag_dtheta(Kern_check_model): kernel with respect to the parameters. """ def __init__(self, kernel=None, dL_dK=None, X=None): - Kern_check_model.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X, X2=None) + super(Kern_check_dKdiag_dtheta, self).__init__(kernel=kernel,dL_dK=dL_dK, X=X, X2=None) self.link_parameter(self.kernel) def log_likelihood(self): @@ -86,7 +86,7 @@ class Kern_check_dKdiag_dtheta(Kern_check_model): class Kern_check_dK_dX(Kern_check_model): """This class allows gradient checks for the gradient of a kernel with respect to X. """ def __init__(self, kernel=None, dL_dK=None, X=None, X2=None): - Kern_check_model.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X, X2=X2) + super(Kern_check_dK_dX, self).__init__(kernel=kernel,dL_dK=dL_dK, X=X, X2=X2) self.X = Param('X',X) self.link_parameter(self.X) @@ -96,7 +96,7 @@ class Kern_check_dK_dX(Kern_check_model): class Kern_check_dKdiag_dX(Kern_check_dK_dX): """This class allows gradient checks for the gradient of a kernel diagonal with respect to X. """ def __init__(self, kernel=None, dL_dK=None, X=None, X2=None): - Kern_check_dK_dX.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X, X2=None) + super(Kern_check_dKdiag_dX, self).__init__(kernel=kernel,dL_dK=dL_dK, X=X, X2=None) def log_likelihood(self): return (np.diag(self.dL_dK)*self.kernel.Kdiag(self.X)).sum() @@ -107,7 +107,7 @@ class Kern_check_dKdiag_dX(Kern_check_dK_dX): class Kern_check_d2K_dXdX(Kern_check_model): """This class allows gradient checks for the secondderivative of a kernel with respect to X. """ def __init__(self, kernel=None, dL_dK=None, X=None, X2=None): - Kern_check_model.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X, X2=X2) + super(Kern_check_d2K_dXdX, self).__init__(kernel=kernel,dL_dK=dL_dK, X=X, X2=X2) self.X = Param('X',X.copy()) self.link_parameter(self.X) self.Xc = X.copy() @@ -129,7 +129,7 @@ class Kern_check_d2K_dXdX(Kern_check_model): class Kern_check_d2Kdiag_dXdX(Kern_check_model): """This class allows gradient checks for the second derivative of a kernel with respect to X. """ def __init__(self, kernel=None, dL_dK=None, X=None): - Kern_check_model.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X) + super(Kern_check_d2Kdiag_dXdX, self).__init__(kernel=kernel,dL_dK=dL_dK, X=X) self.X = Param('X',X) self.link_parameter(self.X) self.Xc = X.copy() diff --git a/GPy/testing/rv_transformation_tests.py b/GPy/testing/rv_transformation_tests.py index 9c510aa4..f526d3cf 100644 --- a/GPy/testing/rv_transformation_tests.py +++ b/GPy/testing/rv_transformation_tests.py @@ -15,7 +15,7 @@ class TestModel(GPy.core.Model): A simple GPy model with one parameter. """ def __init__(self, theta=1.): - GPy.core.Model.__init__(self, 'test_model') + super(TestModel, self).__init__('test_model') theta = GPy.core.Param('theta', theta) self.link_parameter(theta) diff --git a/GPy/util/mocap.py b/GPy/util/mocap.py index e405d3a1..8c522083 100644 --- a/GPy/util/mocap.py +++ b/GPy/util/mocap.py @@ -163,7 +163,7 @@ def rotation_matrix(xangle, yangle, zangle, order='zxy', degrees=False): # Motion capture data routines. class skeleton(tree): def __init__(self): - tree.__init__(self) + super(skeleton, self).__init__() def connection_matrix(self): connection = np.zeros((len(self.vertices), len(self.vertices)), dtype=bool) @@ -197,13 +197,13 @@ class skeleton(tree): # class bvh_skeleton(skeleton): # def __init__(self): -# skeleton.__init__(self) +# super(bvh_skeleton, self).__init__() # def to_xyz(self, channels): class acclaim_skeleton(skeleton): def __init__(self, file_name=None): - skeleton.__init__(self) + super(acclaim_skeleton, self).__init__() self.documentation = [] self.angle = 'deg' self.length = 1.0 From 591e76f68984706b1f64244a1249c557bbdab6af Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Tue, 5 May 2020 15:05:06 +0200 Subject: [PATCH 025/137] README.md: Source formatting, one badge per line --- README.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 171c0369..63e46f52 100644 --- a/README.md +++ b/README.md @@ -9,7 +9,12 @@ The Gaussian processes framework in Python. * Travis-CI [unit-tests](https://travis-ci.org/SheffieldML/GPy) * [![licence](https://img.shields.io/badge/licence-BSD-blue.svg)](http://opensource.org/licenses/BSD-3-Clause) -[![deploystat](https://travis-ci.org/SheffieldML/GPy.svg?branch=deploy)](https://travis-ci.org/SheffieldML/GPy) [![appveyor](https://ci.appveyor.com/api/projects/status/662o6tha09m2jix3/branch/deploy?svg=true)](https://ci.appveyor.com/project/mzwiessele/gpy/branch/deploy) [![coverallsdevel](https://coveralls.io/repos/github/SheffieldML/GPy/badge.svg?branch=devel)](https://coveralls.io/github/SheffieldML/GPy?branch=devel) [![covdevel](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel)](http://codecov.io/github/SheffieldML/GPy?branch=devel) [![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy) [![Code Health](https://landscape.io/github/SheffieldML/GPy/devel/landscape.svg?style=flat)](https://landscape.io/github/SheffieldML/GPy/devel) +[![deploystat](https://travis-ci.org/SheffieldML/GPy.svg?branch=deploy)](https://travis-ci.org/SheffieldML/GPy) +[![appveyor](https://ci.appveyor.com/api/projects/status/662o6tha09m2jix3/branch/deploy?svg=true)](https://ci.appveyor.com/project/mzwiessele/gpy/branch/deploy) +[![coverallsdevel](https://coveralls.io/repos/github/SheffieldML/GPy/badge.svg?branch=devel)](https://coveralls.io/github/SheffieldML/GPy?branch=devel) +[![covdevel](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel)](http://codecov.io/github/SheffieldML/GPy?branch=devel) +[![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy) +[![Code Health](https://landscape.io/github/SheffieldML/GPy/devel/landscape.svg?style=flat)](https://landscape.io/github/SheffieldML/GPy/devel) ## What's new: From cb8044b00d4bec5fe6eb2c8892563cf06d47b875 Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Tue, 5 May 2020 15:05:40 +0200 Subject: [PATCH 026/137] README.md: Remove broken landscape badge (fix #831) --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index 63e46f52..2f5c8973 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,6 @@ The Gaussian processes framework in Python. [![coverallsdevel](https://coveralls.io/repos/github/SheffieldML/GPy/badge.svg?branch=devel)](https://coveralls.io/github/SheffieldML/GPy?branch=devel) [![covdevel](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel)](http://codecov.io/github/SheffieldML/GPy?branch=devel) [![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy) -[![Code Health](https://landscape.io/github/SheffieldML/GPy/devel/landscape.svg?style=flat)](https://landscape.io/github/SheffieldML/GPy/devel) ## What's new: From 1486a4d209723761b49b95e54539f56a187c3fe4 Mon Sep 17 00:00:00 2001 From: jbect Date: Tue, 5 May 2020 15:37:33 +0200 Subject: [PATCH 027/137] README.md: Badges for devel and deploy (fix #830) --- README.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 2f5c8973..e1762399 100644 --- a/README.md +++ b/README.md @@ -8,12 +8,14 @@ The Gaussian processes framework in Python. * Developer [documentation](http://gpy.readthedocs.io/) * Travis-CI [unit-tests](https://travis-ci.org/SheffieldML/GPy) * [![licence](https://img.shields.io/badge/licence-BSD-blue.svg)](http://opensource.org/licenses/BSD-3-Clause) + [![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy) -[![deploystat](https://travis-ci.org/SheffieldML/GPy.svg?branch=deploy)](https://travis-ci.org/SheffieldML/GPy) -[![appveyor](https://ci.appveyor.com/api/projects/status/662o6tha09m2jix3/branch/deploy?svg=true)](https://ci.appveyor.com/project/mzwiessele/gpy/branch/deploy) -[![coverallsdevel](https://coveralls.io/repos/github/SheffieldML/GPy/badge.svg?branch=devel)](https://coveralls.io/github/SheffieldML/GPy?branch=devel) -[![covdevel](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel)](http://codecov.io/github/SheffieldML/GPy?branch=devel) -[![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy) +## Status + +| Branch | travis-ci.org | ci.appveyor.com | coveralls.io | codecov.io | +| --- | --- | --- | --- | --- | +| Default branch (`devel`) | [![travis-devel](https://travis-ci.org/SheffieldML/GPy.svg?branch=devel)](https://travis-ci.org/SheffieldML/GPy/branches) | [![appveyor-devel](https://ci.appveyor.com/api/projects/status/662o6tha09m2jix3/branch/devel?svg=true)](https://ci.appveyor.com/project/mzwiessele/gpy/branch/devel) | [![coveralls-devel](https://coveralls.io/repos/github/SheffieldML/GPy/badge.svg?branch=devel)](https://coveralls.io/github/SheffieldML/GPy?branch=devel) | [![codecov-devel](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel)](http://codecov.io/github/SheffieldML/GPy?branch=devel) | +| Deployment branch (`deploy`) | [![travis-deploy](https://travis-ci.org/SheffieldML/GPy.svg?branch=deploy)](https://travis-ci.org/SheffieldML/GPy/branches) | [![appveyor-deploy](https://ci.appveyor.com/api/projects/status/662o6tha09m2jix3/branch/deploy?svg=true)](https://ci.appveyor.com/project/mzwiessele/gpy/branch/deploy) | [![coveralls-deploy](https://coveralls.io/repos/github/SheffieldML/GPy/badge.svg?branch=deploy)](https://coveralls.io/github/SheffieldML/GPy?branch=deploy) | [![codecov-deploy](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=deploy)](http://codecov.io/github/SheffieldML/GPy?branch=deploy) | ## What's new: From bd4d76c27e591402cfe05ceab67d7b3003285369 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Thu, 26 Mar 2020 11:11:37 +0000 Subject: [PATCH 028/137] ignore itermediary sphinx restructured text --- .gitignore | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.gitignore b/.gitignore index 3f15a070..9af82ff5 100644 --- a/.gitignore +++ b/.gitignore @@ -50,3 +50,6 @@ iterate.dat # pycharm IDE stuff .idea/ + +# docs +GPy*.rst \ No newline at end of file From 9463e61e063ff761a6b0d390fca1f5be6fe9d216 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Thu, 26 Mar 2020 11:30:58 +0000 Subject: [PATCH 029/137] ignore vs code project settings file --- .gitignore | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 9af82ff5..950eecdd 100644 --- a/.gitignore +++ b/.gitignore @@ -52,4 +52,7 @@ iterate.dat .idea/ # docs -GPy*.rst \ No newline at end of file +GPy*.rst + +# vscode +settings.json \ No newline at end of file From 36d41a4860ecd2f591e901e78ad5375c0ed486bb Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 27 Mar 2020 10:01:35 +0000 Subject: [PATCH 030/137] add yml config for readthedocs --- .readthedocs.yml | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 .readthedocs.yml diff --git a/.readthedocs.yml b/.readthedocs.yml new file mode 100644 index 00000000..5a7c9cd3 --- /dev/null +++ b/.readthedocs.yml @@ -0,0 +1,23 @@ +# .readthedocs.yml +# Read the Docs configuration file +# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details + +# Required +version: 2 + +# Build documentation in the docs/ directory with Sphinx +sphinx: + configuration: docs/conf.py + +# Build documentation with MkDocs +#mkdocs: +# configuration: mkdocs.yml + +# Optionally build your docs in additional formats such as PDF and ePub +formats: all + +# Optionally set the version of Python and requirements required to build your docs +python: + version: 3.7 + install: + - requirements: doc/source/requirements.txt \ No newline at end of file From a6819de25c5168a51c2dfec6dd7279fe7c6a2aaa Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 27 Mar 2020 10:09:16 +0000 Subject: [PATCH 031/137] correct path --- .readthedocs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.readthedocs.yml b/.readthedocs.yml index 5a7c9cd3..8bdf2f99 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -7,7 +7,7 @@ version: 2 # Build documentation in the docs/ directory with Sphinx sphinx: - configuration: docs/conf.py + configuration: doc/source/conf.py # Build documentation with MkDocs #mkdocs: From f1572467ec7254c2168ec806bb076f1b2825ef00 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 27 Mar 2020 13:31:27 +0000 Subject: [PATCH 032/137] drop epub and pdf builds (as per main GPy) --- .readthedocs.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.readthedocs.yml b/.readthedocs.yml index 8bdf2f99..eda0c9a0 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -14,7 +14,8 @@ sphinx: # configuration: mkdocs.yml # Optionally build your docs in additional formats such as PDF and ePub -formats: all +formats: + -htmlzip # Optionally set the version of Python and requirements required to build your docs python: From dbe28733dc46ea4f7286a6830703217388ee301e Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 27 Mar 2020 13:32:42 +0000 Subject: [PATCH 033/137] typo --- .readthedocs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.readthedocs.yml b/.readthedocs.yml index eda0c9a0..36eef22f 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -15,7 +15,7 @@ sphinx: # Optionally build your docs in additional formats such as PDF and ePub formats: - -htmlzip + - htmlzip # Optionally set the version of Python and requirements required to build your docs python: From 61fb5e2bbe8cf166483c103d0bfa3473d53a542d Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Mon, 30 Mar 2020 11:07:53 +0100 Subject: [PATCH 034/137] headings and structure --- doc/source/index.rst | 21 ++++++++++++--------- 1 file changed, 12 insertions(+), 9 deletions(-) diff --git a/doc/source/index.rst b/doc/source/index.rst index 0994536d..1044d1dc 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -1,10 +1,8 @@ -.. GPy documentation master file, created by - sphinx-quickstart on Fri Sep 18 18:16:28 2015. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. +GPy - A Gaussian Process (GP) framework in Python +================================================= -Welcome to GPy's documentation! -=============================== +Introduction +------------ `GPy `_ is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group. @@ -13,14 +11,19 @@ This documentation is mostly aimed at developers interacting closely with the co The code can be found on our `Github project page `_. It is open source and provided under the BSD license. -For developers: +Installation +------------ + +For developers +-------------- - `Writing new models `_ - `Writing new kernels `_ - `Write a new plotting routine using gpy_plot `_ - `Parameterization handles `_ -Contents: +API Documentation +----------------- .. toctree:: :maxdepth: 1 @@ -40,7 +43,7 @@ Contents: GPy.inference.mcmc Indices and tables -================== +------------------ * :ref:`genindex` * :ref:`modindex` From a70f9a6a95aefc2a3e972f7e018faed0e2193509 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Mon, 30 Mar 2020 11:10:11 +0100 Subject: [PATCH 035/137] update copyright --- doc/source/conf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/conf.py b/doc/source/conf.py index b968fe48..533417bb 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -134,7 +134,7 @@ master_doc = 'index' project = u'GPy' #author = u'`Humans `_' author = 'GPy Authors, see https://github.com/SheffieldML/GPy/graphs/contributors' -copyright = u'2015, '+author +copyright = u'2020, '+author # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the From 8c8fb4cb2b6a5fa26d51e8a528ad6769230f1688 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Mon, 30 Mar 2020 14:58:59 +0100 Subject: [PATCH 036/137] restructuring and smartening --- doc/source/index.rst | 30 ++++++++++++++++++++---------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/doc/source/index.rst b/doc/source/index.rst index 1044d1dc..f99dd356 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -4,29 +4,39 @@ GPy - A Gaussian Process (GP) framework in Python Introduction ------------ -`GPy `_ is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group. +`GPy `_ is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group. It includes support for basic GP regression, multiple output GPs (using coregionalization), various noise models, sparse GPs, non-parametric regression and latent variables. The `GPy homepage `_ contains tutorials for users and further information on the project, including installation instructions. -This documentation is mostly aimed at developers interacting closely with the code-base. + +The documentation hosted here is mostly aimed at developers interacting closely with the code-base. + +Source Code +----------- The code can be found on our `Github project page `_. It is open source and provided under the BSD license. Installation ------------ -For developers --------------- +Installation instructions can currently be found on our `Github project page `_. -- `Writing new models `_ -- `Writing new kernels `_ -- `Write a new plotting routine using gpy_plot `_ -- `Parameterization handles `_ +Tutorials +--------- -API Documentation ------------------ +Several tutorials have been developed in the form of `Jupyter Notebooks `_. .. toctree:: :maxdepth: 1 + :caption: For developers + + tuto_creating_new_models + tuto_creating_new_kernels + tuto_plotting + tuto_parameterized + +.. toctree:: + :maxdepth: 1 + :caption: API Documentation GPy.models GPy.kern From b6dbac6c124ac152acaa8530b6249eb989f906cf Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Mon, 30 Mar 2020 14:59:14 +0100 Subject: [PATCH 037/137] remove dead links --- doc/source/index.rst | 7 ------- 1 file changed, 7 deletions(-) diff --git a/doc/source/index.rst b/doc/source/index.rst index f99dd356..6ae53eb1 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -51,11 +51,4 @@ Several tutorials have been developed in the form of `Jupyter Notebooks Date: Wed, 1 Apr 2020 12:45:08 +0100 Subject: [PATCH 038/137] reorder package docs --- GPy/models/__init__.py | 8 ++++++++ doc/source/conf.py | 2 +- 2 files changed, 9 insertions(+), 1 deletion(-) diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py index 3e788927..4eedf2b1 100644 --- a/GPy/models/__init__.py +++ b/GPy/models/__init__.py @@ -1,6 +1,14 @@ # Copyright (c) 2012, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) +""" +This module does... + +.. automodule:: .src + :members: + :private-members: +""" + from .gp_regression import GPRegression from .gp_classification import GPClassification from .sparse_gp_regression import SparseGPRegression diff --git a/doc/source/conf.py b/doc/source/conf.py index 533417bb..079573b3 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -64,7 +64,7 @@ if on_rtd: print(out) #Lets regenerate our rst files from the source, -P adds private modules (i.e kern._src) - proc = subprocess.Popen("sphinx-apidoc -P -f -o . ../../GPy", stdout=subprocess.PIPE, shell=True) + proc = subprocess.Popen("sphinx-apidoc -M -P -f -o . ../../GPy", stdout=subprocess.PIPE, shell=True) (out, err) = proc.communicate() print("$ Apidoc:") print(out) From 680fd29ba4f42cba5e8878f719b1226b78e1568c Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Thu, 2 Apr 2020 15:51:41 +0100 Subject: [PATCH 039/137] rst "markup" --- .../gp_kronecker_gaussian_regression.py | 13 +++---- GPy/models/gp_multiout_regression.py | 7 ++-- GPy/models/gp_multiout_regression_md.py | 8 +++-- GPy/models/gp_var_gauss.py | 10 ++---- GPy/models/gradient_checker.py | 34 ++++++++++--------- GPy/plotting/gpy_plot/latent_plots.py | 21 ++++++++---- 6 files changed, 51 insertions(+), 42 deletions(-) diff --git a/GPy/models/gp_kronecker_gaussian_regression.py b/GPy/models/gp_kronecker_gaussian_regression.py index 44177b16..a8addf73 100644 --- a/GPy/models/gp_kronecker_gaussian_regression.py +++ b/GPy/models/gp_kronecker_gaussian_regression.py @@ -18,14 +18,11 @@ class GPKroneckerGaussianRegression(Model): The noise must be iid Gaussian. - See Stegle et al. - @inproceedings{stegle2011efficient, - title={Efficient inference in matrix-variate gaussian models with $\\backslash$ iid observation noise}, - author={Stegle, Oliver and Lippert, Christoph and Mooij, Joris M and Lawrence, Neil D and Borgwardt, Karsten M}, - booktitle={Advances in Neural Information Processing Systems}, - pages={630--638}, - year={2011} - } + See [stegle_et_al_2011]_. + + .. rubric:: References + + .. [stegle_et_al_2011] Stegle, O.; Lippert, C.; Mooij, J.M.; Lawrence, N.D.; Borgwardt, K.:Efficient inference in matrix-variate Gaussian models with \iid observation noise. In: Advances in Neural Information Processing Systems, 2011, Pages 630-638 """ def __init__(self, X1, X2, Y, kern1, kern2, noise_var=1., name='KGPR'): diff --git a/GPy/models/gp_multiout_regression.py b/GPy/models/gp_multiout_regression.py index ede6095e..816fc0d7 100644 --- a/GPy/models/gp_multiout_regression.py +++ b/GPy/models/gp_multiout_regression.py @@ -15,9 +15,11 @@ class GPMultioutRegression(SparseGP): """ Gaussian Process model for multi-output regression without missing data - This is an implementation of Latent Variable Multiple Output Gaussian Processes (LVMOGP) in [Dai et al. 2017]. + This is an implementation of Latent Variable Multiple Output Gaussian Processes (LVMOGP) in [Dai_et_al_2017]_. - Zhenwen Dai, Mauricio A. Alvarez and Neil D. Lawrence. Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. In NIPS, 2017. + .. rubric:: References + + .. [Dai_et_al_2017] Dai, Z.; Alvarez, M.A.; Lawrence, N.D: Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. In NIPS, 2017. :param X: input observations. :type X: numpy.ndarray @@ -42,6 +44,7 @@ class GPMultioutRegression(SparseGP): :param int qU_var_c_W_dim: the dimensionality of the covariance of q(U) for the GP regression. If it is smaller than the number of inducing points, it represents a low-rank parameterization of the covariance matrix. :param str init: the choice of initialization: 'GP' or 'rand'. With 'rand', the model is initialized randomly. With 'GP', the model is initialized through a protocol as follows: (1) fits a sparse GP (2) fits a BGPLVM based on the outcome of sparse GP (3) initialize the model based on the outcome of the BGPLVM. :param str name: the name of the model + """ def __init__(self, X, Y, Xr_dim, kernel=None, kernel_row=None, Z=None, Z_row=None, X_row=None, Xvariance_row=None, num_inducing=(10,10), qU_var_r_W_dim=None, qU_var_c_W_dim=None, init='GP', name='GPMR'): diff --git a/GPy/models/gp_multiout_regression_md.py b/GPy/models/gp_multiout_regression_md.py index 36d24c48..3eb91114 100644 --- a/GPy/models/gp_multiout_regression_md.py +++ b/GPy/models/gp_multiout_regression_md.py @@ -16,9 +16,11 @@ class GPMultioutRegressionMD(SparseGP): """ Gaussian Process model for multi-output regression with missing data - This is an implementation of Latent Variable Multiple Output Gaussian Processes (LVMOGP) in [Dai et al. 2017]. This model targets at the use case, in which each output dimension is observed at a different set of inputs. The model takes a different data format: the inputs and outputs observations of all the output dimensions are stacked together correspondingly into two matrices. An extra array is used to indicate the index of output dimension for each data point. The output dimensions are indexed using integers from 0 to D-1 assuming there are D output dimensions. + This is an implementation of Latent Variable Multiple Output Gaussian Processes (LVMOGP) in [Dai_et_al_2017]_. This model targets at the use case, in which each output dimension is observed at a different set of inputs. The model takes a different data format: the inputs and outputs observations of all the output dimensions are stacked together correspondingly into two matrices. An extra array is used to indicate the index of output dimension for each data point. The output dimensions are indexed using integers from 0 to D-1 assuming there are D output dimensions. - Zhenwen Dai, Mauricio A. Alvarez and Neil D. Lawrence. Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. In NIPS, 2017. + .. rubric:: References + + .. [Dai_et_al_2017] Dai, Z.; Alvarez, M.A.; Lawrence, N.D: Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. In NIPS, 2017. :param X: input observations. :type X: numpy.ndarray @@ -46,6 +48,8 @@ class GPMultioutRegressionMD(SparseGP): :param str init: the choice of initialization: 'GP' or 'rand'. With 'rand', the model is initialized randomly. With 'GP', the model is initialized through a protocol as follows: (1) fits a sparse GP (2) fits a BGPLVM based on the outcome of sparse GP (3) initialize the model based on the outcome of the BGPLVM. :param boolean heter_noise: whether assuming heteroscedastic noise in the model, boolean :param str name: the name of the model + + """ def __init__(self, X, Y, indexD, Xr_dim, kernel=None, kernel_row=None, Z=None, Z_row=None, X_row=None, Xvariance_row=None, num_inducing=(10,10), qU_var_r_W_dim=None, qU_var_c_W_dim=None, init='GP', heter_noise=False, name='GPMRMD'): diff --git a/GPy/models/gp_var_gauss.py b/GPy/models/gp_var_gauss.py index 4c8fa7ef..6a61b604 100644 --- a/GPy/models/gp_var_gauss.py +++ b/GPy/models/gp_var_gauss.py @@ -13,13 +13,9 @@ class GPVariationalGaussianApproximation(GP): """ 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}, - } + .. rubric:: References + + .. [opper_archambeau_2009] Opper, M.; Archambeau, C.; The Variational Gaussian Approximation Revisited. Neural Comput. 2009, pages 786-792. """ def __init__(self, X, Y, kernel, likelihood, Y_metadata=None): diff --git a/GPy/models/gradient_checker.py b/GPy/models/gradient_checker.py index f7c17376..904b88c6 100644 --- a/GPy/models/gradient_checker.py +++ b/GPy/models/gradient_checker.py @@ -39,28 +39,30 @@ class GradientChecker(Model): a list of names with the same length is expected. :param args: Arguments passed as f(x, *args, **kwargs) and df(x, *args, **kwargs) - Examples: - --------- + .. rubric:: Examples + + Initialisation:: + from GPy.models import GradientChecker N, M, Q = 10, 5, 3 - Sinusoid: + Sinusoid:: - X = numpy.random.rand(N, Q) - grad = GradientChecker(numpy.sin,numpy.cos,X,'x') - grad.checkgrad(verbose=1) + X = numpy.random.rand(N, Q) + grad = GradientChecker(numpy.sin,numpy.cos,X,'x') + grad.checkgrad(verbose=1) - Using GPy: + Using GPy:: - X, Z = numpy.random.randn(N,Q), numpy.random.randn(M,Q) - kern = GPy.kern.linear(Q, ARD=True) + GPy.kern.rbf(Q, ARD=True) - grad = GradientChecker(kern.K, - lambda x: 2*kern.dK_dX(numpy.ones((1,1)), x), - x0 = X.copy(), - names='X') - grad.checkgrad(verbose=1) - grad.randomize() - grad.checkgrad(verbose=1) + X, Z = numpy.random.randn(N,Q), numpy.random.randn(M,Q) + kern = GPy.kern.linear(Q, ARD=True) + GPy.kern.rbf(Q, ARD=True) + grad = GradientChecker(kern.K, + lambda x: 2*kern.dK_dX(numpy.ones((1,1)), x), + x0 = X.copy(), + names='X') + grad.checkgrad(verbose=1) + grad.randomize() + grad.checkgrad(verbose=1) """ super(GradientChecker, self).__init__(name='GradientChecker') if isinstance(x0, (list, tuple)) and names is None: diff --git a/GPy/plotting/gpy_plot/latent_plots.py b/GPy/plotting/gpy_plot/latent_plots.py index f76fda1c..a749f0c1 100644 --- a/GPy/plotting/gpy_plot/latent_plots.py +++ b/GPy/plotting/gpy_plot/latent_plots.py @@ -89,7 +89,8 @@ def plot_latent_scatter(self, labels=None, Plot a scatter plot of the latent space. :param array-like labels: a label for each data point (row) of the inputs - :param (int, int) which_indices: which input dimensions to plot against each other + :param which_indices: which input dimensions to plot against each other + :type which_indices: (int, int) :param bool legend: whether to plot the legend on the figure :param plot_limits: the plot limits for the plot :type plot_limits: (xmin, xmax, ymin, ymax) or ((xmin, xmax), (ymin, ymax)) @@ -174,7 +175,8 @@ def plot_magnification(self, labels=None, which_indices=None, density of the GP as a gray scale. :param array-like labels: a label for each data point (row) of the inputs - :param (int, int) which_indices: which input dimensions to plot against each other + :param which_indices: which input dimensions to plot against each other + :type which_indices: (int, int) :param int resolution: the resolution at which we predict the magnification factor :param str marker: markers to use - cycle if more labels then markers are given :param bool legend: whether to plot the legend on the figure @@ -183,7 +185,8 @@ def plot_magnification(self, labels=None, which_indices=None, :param bool updates: if possible, make interactive updates using the specific library you are using :param bool mean: use the mean of the Wishart embedding for the magnification factor :param bool covariance: use the covariance of the Wishart embedding for the magnification factor - :param :py:class:`~GPy.kern.Kern` kern: the kernel to use for prediction + :param kern: the kernel to use for prediction + :type kern: :py:class:`~GPy.kern.Kern` :param int num_samples: the number of samples to plot maximally. We do a stratified subsample from the labels, if the number of samples (in X) is higher then num_samples. :param imshow_kwargs: the kwargs for the imshow (magnification factor) :param kwargs: the kwargs for the scatter plots @@ -248,13 +251,15 @@ def plot_latent(self, labels=None, which_indices=None, scatter plot of the input dimemsions selected by which_indices. :param array-like labels: a label for each data point (row) of the inputs - :param (int, int) which_indices: which input dimensions to plot against each other + :param which_indices: which input dimensions to plot against each other + :type which_indices: (int, int) :param int resolution: the resolution at which we predict the magnification factor :param bool legend: whether to plot the legend on the figure :param plot_limits: the plot limits for the plot :type plot_limits: (xmin, xmax, ymin, ymax) or ((xmin, xmax), (ymin, ymax)) :param bool updates: if possible, make interactive updates using the specific library you are using - :param :py:class:`~GPy.kern.Kern` kern: the kernel to use for prediction + :param kern: the kernel to use for prediction + :type kern: :py:class:`~GPy.kern.Kern` :param str marker: markers to use - cycle if more labels then markers are given :param int num_samples: the number of samples to plot maximally. We do a stratified subsample from the labels, if the number of samples (in X) is higher then num_samples. :param imshow_kwargs: the kwargs for the imshow (magnification factor) @@ -316,13 +321,15 @@ def plot_steepest_gradient_map(self, output_labels=None, data_labels=None, which scatter plot of the input dimemsions selected by which_indices. :param array-like labels: a label for each data point (row) of the inputs - :param (int, int) which_indices: which input dimensions to plot against each other + :param which_indices: which input dimensions to plot against each other + :type which_indices: (int, int) :param int resolution: the resolution at which we predict the magnification factor :param bool legend: whether to plot the legend on the figure, if int plot legend columns on legend :param plot_limits: the plot limits for the plot :type plot_limits: (xmin, xmax, ymin, ymax) or ((xmin, xmax), (ymin, ymax)) :param bool updates: if possible, make interactive updates using the specific library you are using - :param :py:class:`~GPy.kern.Kern` kern: the kernel to use for prediction + :param kern: the kernel to use for prediction + :type kern: :py:class:`~GPy.kern.Kern` :param str marker: markers to use - cycle if more labels then markers are given :param int num_samples: the number of samples to plot maximally. We do a stratified subsample from the labels, if the number of samples (in X) is higher then num_samples. :param imshow_kwargs: the kwargs for the imshow (magnification factor) From 3375458dbb516f07f3fcda4d4409ca1cb9d898f7 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 3 Apr 2020 09:26:43 +0100 Subject: [PATCH 040/137] change rst syntax --- GPy/core/gp.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 1a06f088..66d62f62 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -335,7 +335,7 @@ class GP(Model): of the output dimensions. Note: If you want the predictive quantiles (e.g. 95% confidence - interval) use :py:func:"~GPy.core.gp.GP.predict_quantiles". + interval) use :py:func:`~GPy.core.gp.GP.predict_quantiles`. """ # Predict the latent function values @@ -384,7 +384,7 @@ class GP(Model): If full_cov and self.input_dim > 1, the return shape of var is Nnew x Nnew x self.input_dim. If self.input_dim == 1, the return shape is Nnew x Nnew. This is to allow for different normalizations of the output dimensions. - Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:"~GPy.core.gp.GP.predict_quantiles". + Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:`~GPy.core.gp.GP.predict_quantiles`. """ return self.predict(Xnew, full_cov, Y_metadata, kern, None, False) From a312e754bd9d366817f42bfb9f8befd5c4bf522b Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 3 Apr 2020 10:11:44 +0100 Subject: [PATCH 041/137] makes sense for core to go first --- doc/source/index.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/source/index.rst b/doc/source/index.rst index 6ae53eb1..b974acd3 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -38,6 +38,8 @@ Several tutorials have been developed in the form of `Jupyter Notebooks Date: Fri, 3 Apr 2020 10:14:11 +0100 Subject: [PATCH 042/137] add placeholder --- GPy/core/__init__.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/GPy/core/__init__.py b/GPy/core/__init__.py index 49e9c3c7..6f466652 100644 --- a/GPy/core/__init__.py +++ b/GPy/core/__init__.py @@ -1,6 +1,11 @@ # Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) +""" +This module does... + +""" + from GPy.core.model import Model from .parameterization import Param, Parameterized from . import parameterization From 59a7742a9cd7b1bac7c33bc8770a45001bc85f11 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 3 Apr 2020 16:45:24 +0100 Subject: [PATCH 043/137] initial core docs, class diagram --- GPy/core/__init__.py | 16 +++++++++++++++- doc/source/architecture.rst | 4 ++++ doc/source/conf.py | 5 +++++ doc/source/index.rst | 6 ++++++ 4 files changed, 30 insertions(+), 1 deletion(-) create mode 100644 doc/source/architecture.rst diff --git a/GPy/core/__init__.py b/GPy/core/__init__.py index 6f466652..45113474 100644 --- a/GPy/core/__init__.py +++ b/GPy/core/__init__.py @@ -2,7 +2,21 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) """ -This module does... +This module contains the fundamental classes of GPy - classes that are inherited by objects in other parts of GPy in order to provide a consistent interface to major functionality. + +.. inheritance-diagram:: GPy.core.gp.GP + :top-classes: paramz.core.parameter_core.Parameterizable + +:py:class:`GPy.core.model` is inherited by :py:class:`GPy.core.gp.GP`. And :py:class:`GPy.core.model` itself inherits :py:class:`paramz.model.Model` from the `paramz` package. `paramz` essentially provides an inherited set of properties and functions used to manage state (and state changes) of the model. + +:py:class:`GPy.core.gp.GP` represents a GP model. Such an entity is typically passed variables representing known (x) and observed (y) data, along with a kernel and other information needed to create the specific model. It exposes functions which return information derived from the inputs to the model, for example predicting unobserved variables based on new known variables, or the log marginal likelihood of the current state of the model. + +:py:func:`~GPy.core.gp.GP.optimize` is called to optimize hyperparameters of the model. The optimizer argument takes a string which is used to specify non-default optimization schemes. + +Various plotting functions can be called against :py:class:`GPy.core.gp.GP`. + +:py:class:`GPy.core.gp.GP` is inherited by :py:class:`GPy.core.gp_grid`, :py:class:`GPy.core.sparse_gp`, different types of GP model. + """ diff --git a/doc/source/architecture.rst b/doc/source/architecture.rst new file mode 100644 index 00000000..b63166aa --- /dev/null +++ b/doc/source/architecture.rst @@ -0,0 +1,4 @@ +GPy Project Architecture +======================== + + diff --git a/doc/source/conf.py b/doc/source/conf.py index 079573b3..b1cea5eb 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -83,8 +83,13 @@ extensions = [ #'sphinx.ext.coverage', 'sphinx.ext.mathjax', 'sphinx.ext.viewcode', + 'sphinx.ext.graphviz', + 'sphinx.ext.inheritance_diagram', ] +#---sphinx.ext.inheritance_diagram config +inheritance_graph_attrs = dict(rankdir="TB") + #----- Autodoc #import sys #try: diff --git a/doc/source/index.rst b/doc/source/index.rst index b974acd3..61a605d9 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -25,6 +25,12 @@ Tutorials Several tutorials have been developed in the form of `Jupyter Notebooks `_. +.. toctree:: + :maxdepth: 1 + :caption: Architecture + + architecture + .. toctree:: :maxdepth: 1 :caption: For developers From 66015895a72cd2550d3f8ab1a4c60bc48b883dcf Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 17 Apr 2020 11:46:47 +0100 Subject: [PATCH 044/137] lower level detail --- GPy/core/__init__.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/GPy/core/__init__.py b/GPy/core/__init__.py index 45113474..f2dc4904 100644 --- a/GPy/core/__init__.py +++ b/GPy/core/__init__.py @@ -2,6 +2,9 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) """ +Introduction +^^^^^^^^^^^^ + This module contains the fundamental classes of GPy - classes that are inherited by objects in other parts of GPy in order to provide a consistent interface to major functionality. .. inheritance-diagram:: GPy.core.gp.GP @@ -15,8 +18,10 @@ This module contains the fundamental classes of GPy - classes that are inherited Various plotting functions can be called against :py:class:`GPy.core.gp.GP`. -:py:class:`GPy.core.gp.GP` is inherited by :py:class:`GPy.core.gp_grid`, :py:class:`GPy.core.sparse_gp`, different types of GP model. +.. inheritance-diagram:: GPy.core.gp_grid.GpGrid GPy.core.sparse_gp.SparseGP GPy.core.sparse_gp_mpi.SparseGP_MPI GPy.core.svgp.SVGP + :top-classes: GPy.core.gp.GP +:py:class:`GPy.core.gp.GP` is used as the basis for classes supporting more specialized types of Gaussian Process model. These are however generally still not specific enough to be called by the user and are inhereted by members of the :py:class:`GPy.models` package. """ From 14cfd95be88d1344bb50fe94a42eafa2019f67a7 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 17 Apr 2020 08:54:33 +0100 Subject: [PATCH 045/137] higher res diagrams --- doc/source/conf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/conf.py b/doc/source/conf.py index b1cea5eb..38055b64 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -88,7 +88,7 @@ extensions = [ ] #---sphinx.ext.inheritance_diagram config -inheritance_graph_attrs = dict(rankdir="TB") +inheritance_graph_attrs = dict(rankdir="TB", dpi=1200) #----- Autodoc #import sys From 0e8fcfa3195f7208c1a82ae20d347de2dc9b2162 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 17 Apr 2020 08:33:24 +0100 Subject: [PATCH 046/137] layout changes for diagrams resolve conflict --- doc/source/conf.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/doc/source/conf.py b/doc/source/conf.py index 38055b64..28ea3264 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -88,7 +88,7 @@ extensions = [ ] #---sphinx.ext.inheritance_diagram config -inheritance_graph_attrs = dict(rankdir="TB", dpi=1200) +inheritance_graph_attrs = dict(rankdir="LR", dpi=1200) #----- Autodoc #import sys @@ -250,6 +250,9 @@ html_theme = 'sphinx_rtd_theme' # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] +def setup(app): + app.add_stylesheet('wide.css') + # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. From 3b67ecfe307be7db19721f2a1ffeb9172c5d3049 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 17 Apr 2020 08:40:34 +0100 Subject: [PATCH 047/137] better syntax --- doc/source/conf.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/doc/source/conf.py b/doc/source/conf.py index 28ea3264..5fe9be77 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -250,8 +250,9 @@ html_theme = 'sphinx_rtd_theme' # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] -def setup(app): - app.add_stylesheet('wide.css') +html_css_files = [ + 'wide.css', +] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied From b39895644e38d595720a2f063850000a87205657 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 17 Apr 2020 16:34:06 +0100 Subject: [PATCH 048/137] redunant block --- GPy/models/__init__.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py index 4eedf2b1..88091ca9 100644 --- a/GPy/models/__init__.py +++ b/GPy/models/__init__.py @@ -4,9 +4,7 @@ """ This module does... -.. automodule:: .src - :members: - :private-members: + """ from .gp_regression import GPRegression From f2f1c0d7ff8db2b0edce3731661d268300d04939 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 17 Apr 2020 16:43:57 +0100 Subject: [PATCH 049/137] introduction --- GPy/models/__init__.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py index 88091ca9..9797f494 100644 --- a/GPy/models/__init__.py +++ b/GPy/models/__init__.py @@ -2,7 +2,10 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) """ -This module does... +Introduction +^^^^^^^^^^^^ + +This package principally contains classes ultimately inherited from :py:class:`GPy.core.gp.GP` intended as models for end user consuption - much of :py:class:`GPy.core.gp.GP` is not intended to be called directly. Some of these fall into conceptually related groups of models (e.g. :py:class:`GPy.core.sparse_gp`, :py:class:`GPy.core.sparse_gp_mpi`). """ From 1d97744cf6f02de87b5c4499d925517e019c3773 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 21 Apr 2020 16:09:06 +0100 Subject: [PATCH 050/137] inheritance diagrams --- GPy/models/__init__.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py index 9797f494..0badc799 100644 --- a/GPy/models/__init__.py +++ b/GPy/models/__init__.py @@ -5,8 +5,20 @@ Introduction ^^^^^^^^^^^^ -This package principally contains classes ultimately inherited from :py:class:`GPy.core.gp.GP` intended as models for end user consuption - much of :py:class:`GPy.core.gp.GP` is not intended to be called directly. Some of these fall into conceptually related groups of models (e.g. :py:class:`GPy.core.sparse_gp`, :py:class:`GPy.core.sparse_gp_mpi`). +This package principally contains classes ultimately inherited from :py:class:`GPy.core.gp.GP` intended as models for end user consuption - much of :py:class:`GPy.core.gp.GP` is not intended to be called directly. Several models directly inherit :py:class:`GPy.core.gp.GP`: +.. inheritance-diagram:: GPy.models.gp_classification GPy.models.gp_coregionalized_regression GPy.models.gp_heteroscedastic_regression GPy.models.gp_offset_regression GPy.models.gp_regression GPy.models.gp_var_gauss GPy.models.gplvm GPy.models.input_warped_gp GPy.models.multioutput_gp + :top-classes: GPy.core.gp.GP + +Some models fall into conceptually related groups of models (e.g. :py:class:`GPy.core.sparse_gp`, :py:class:`GPy.core.sparse_gp_mpi`): + +.. inheritance-diagram:: GPy.models.bayesian_gplvm GPy.models.bayesian_gplvm_minibatch GPy.models.gp_multiout_regression GPy.models.gp_multiout_regression_md GPy.models.ibp_lfm.IBPLFM GPy.models.sparse_gp_coregionalized_regression GPy.models.sparse_gp_minibatch GPy.models.sparse_gp_regression GPy.models.sparse_gp_regression_md GPy.models.sparse_gplvm + :top-classes: GPy.core.gp.GP + +In some cases one end-user model inherits another e.g. + +.. inheritance-diagram:: GPy.models.bayesian_gplvm_minibatch + :top-classes: GPy.models.sparse_gp_minibatch.SparseGPMiniBatch """ From 2b22d4027aa8faf8ffc288da7c9304951a838b36 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Wed, 22 Apr 2020 10:05:59 +0100 Subject: [PATCH 051/137] more on models --- GPy/models/__init__.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py index 0badc799..6669b357 100644 --- a/GPy/models/__init__.py +++ b/GPy/models/__init__.py @@ -5,7 +5,9 @@ Introduction ^^^^^^^^^^^^ -This package principally contains classes ultimately inherited from :py:class:`GPy.core.gp.GP` intended as models for end user consuption - much of :py:class:`GPy.core.gp.GP` is not intended to be called directly. Several models directly inherit :py:class:`GPy.core.gp.GP`: +This package principally contains classes ultimately inherited from :py:class:`GPy.core.gp.GP` intended as models for end user consuption - much of :py:class:`GPy.core.gp.GP` is not intended to be called directly. The general form of a "model" is a function that takes some data, a kernel (see :py:class:`GPy.kern`) and other parameters, returning an object representation. + +Several models directly inherit :py:class:`GPy.core.gp.GP`: .. inheritance-diagram:: GPy.models.gp_classification GPy.models.gp_coregionalized_regression GPy.models.gp_heteroscedastic_regression GPy.models.gp_offset_regression GPy.models.gp_regression GPy.models.gp_var_gauss GPy.models.gplvm GPy.models.input_warped_gp GPy.models.multioutput_gp :top-classes: GPy.core.gp.GP From 24549e8c7d2d55c9bbaa6fd61b0d6b3a892bde3b Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Wed, 22 Apr 2020 11:14:03 +0100 Subject: [PATCH 052/137] kernel docs to kern.src --- GPy/kern/__init__.py | 6 ------ GPy/kern/src/__init__.py | 9 +++++++++ doc/source/index.rst | 2 +- 3 files changed, 10 insertions(+), 7 deletions(-) diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index 0b769e0a..5ed58e83 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -1,10 +1,4 @@ -""" -Kernel module the kernels to sit in. -.. automodule:: .src - :members: - :private-members: -""" from .src.kern import Kern from .src.add import Add from .src.prod import Prod diff --git a/GPy/kern/src/__init__.py b/GPy/kern/src/__init__.py index 69522e32..4056bf42 100644 --- a/GPy/kern/src/__init__.py +++ b/GPy/kern/src/__init__.py @@ -1 +1,10 @@ +""" + +In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters. + +.. inheritance-diagram:: GPy.kern.src.kern.Kern + :top-classes: GPy.core.parameterization.parameterized.Parameterized + +""" + from . import psi_comp diff --git a/doc/source/index.rst b/doc/source/index.rst index 61a605d9..c0a710e7 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -47,7 +47,7 @@ Several tutorials have been developed in the form of `Jupyter Notebooks Date: Wed, 22 Apr 2020 11:24:36 +0100 Subject: [PATCH 053/137] moved doc back from kern.src to kern --- GPy/kern/__init__.py | 11 +++++++++++ GPy/kern/src/__init__.py | 8 -------- 2 files changed, 11 insertions(+), 8 deletions(-) diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index 5ed58e83..a5fd01ad 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -1,4 +1,15 @@ +""" + +In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters. + +:py:class:`GPy.kern.src.kern.Kern` is a generic kernel object inherited by more specific, end-user kernels used in models. It provides methods that specific kernels should generally have such as :py:class:`GPy.kern.src.kern.Kern.K` to compute the value of the kernel, :py:class:`GPy.kern.src.kern.Kern.add` to combine kernels and numerous functions providing information on kernel gradients. + +.. inheritance-diagram:: GPy.kern.src.kern.Kern + :top-classes: GPy.core.parameterization.parameterized.Parameterized + +""" + from .src.kern import Kern from .src.add import Add from .src.prod import Prod diff --git a/GPy/kern/src/__init__.py b/GPy/kern/src/__init__.py index 4056bf42..2d81d9b6 100644 --- a/GPy/kern/src/__init__.py +++ b/GPy/kern/src/__init__.py @@ -1,10 +1,2 @@ -""" - -In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters. - -.. inheritance-diagram:: GPy.kern.src.kern.Kern - :top-classes: GPy.core.parameterization.parameterized.Parameterized - -""" from . import psi_comp From 4a64e3260ef1894a5ef8ff0dd59e433222f6f5c3 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Wed, 22 Apr 2020 11:26:51 +0100 Subject: [PATCH 054/137] kern not kern.src in index --- doc/source/index.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/index.rst b/doc/source/index.rst index c0a710e7..61a605d9 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -47,7 +47,7 @@ Several tutorials have been developed in the form of `Jupyter Notebooks Date: Thu, 23 Apr 2020 09:04:17 +0100 Subject: [PATCH 055/137] better kernel description --- GPy/kern/__init__.py | 15 +++++++++++++-- 1 file changed, 13 insertions(+), 2 deletions(-) diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index a5fd01ad..33301817 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -1,15 +1,26 @@ """ +Introduction +^^^^^^^^^^^^ -In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters. +In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters. *Note: this may be too simple a definition for the broad range of kernels available in :py:class:`GPy`.* :py:class:`GPy.kern.src.kern.Kern` is a generic kernel object inherited by more specific, end-user kernels used in models. It provides methods that specific kernels should generally have such as :py:class:`GPy.kern.src.kern.Kern.K` to compute the value of the kernel, :py:class:`GPy.kern.src.kern.Kern.add` to combine kernels and numerous functions providing information on kernel gradients. -.. inheritance-diagram:: GPy.kern.src.kern.Kern +There are several inherited types of kernel that provide a basis for specific end user kernels: + +.. inheritance-diagram:: GPy.kern.src.kern.Kern GPy.kern.src.static GPy.kern.src.stationary GPy.kern.src.kern.CombinationKernel GPy.kern.src.brownian GPy.kern.src.linear GPy.kern.src.standard_periodic + :top-classes: GPy.core.parameterization.parameterized.Parameterized + +e.g. the archetype :py:class:`GPy.kern.RBF` does not inherit directly from :py:class:`GPy.kern.src.kern.Kern`, but from :py:class:`GPy.kern.src.stationary`. + +.. inheritance-diagram:: GPy.kern.src.kern.Kern GPy.kern.RBF :top-classes: GPy.core.parameterization.parameterized.Parameterized """ + + from .src.kern import Kern from .src.add import Add from .src.prod import Prod From 4e411c4b26f738dcbd098c5b8c697a9e5e607854 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Fri, 24 Apr 2020 10:19:36 +0100 Subject: [PATCH 056/137] likelihoods --- GPy/likelihoods/__init__.py | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/GPy/likelihoods/__init__.py b/GPy/likelihoods/__init__.py index 7ec8092b..606a5167 100644 --- a/GPy/likelihoods/__init__.py +++ b/GPy/likelihoods/__init__.py @@ -1,3 +1,16 @@ +""" +Introduction +^^^^^^^^^^^^ + +'Likelihood' in this context is a measure of how well a model *f* predicts a dataset *y*. The importance of likelihoods in Gaussian Processes is in determining the 'best' values of kernel and noise hyperparamters to relate known, observed and unobserved data. The purpose of optimizing a model (e.g. :py:class:`GPy.models.GPRegression`) is to determine the 'best' hyperparameters i.e. those that minimize negative log marginal likelihood. + +.. inheritance-diagram:: GPy.likelihoods.likelihood GPy.likelihoods.mixed_noise.MixedNoise + :top-classes: GPy.core.parameterization.parameterized.Parameterized + +Most likelihood classes inherit directly from :py:class:`GPy.likelihoods.likelihood`, although an intermediary class :py:class:`GPy.likelihoods.mixed_noise.MixedNoise` is used by :py:class:`GPy.likelihoods.multioutput_likelihood`. + +""" + from .bernoulli import Bernoulli from .exponential import Exponential from .gaussian import Gaussian, HeteroscedasticGaussian From 3e6cc2888dd693d441bbc27a4548b9d6cb5698fc Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Mon, 27 Apr 2020 09:58:12 +0100 Subject: [PATCH 057/137] placeholder --- GPy/inference/__init__.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/GPy/inference/__init__.py b/GPy/inference/__init__.py index 4d94c619..283cb8dc 100644 --- a/GPy/inference/__init__.py +++ b/GPy/inference/__init__.py @@ -1,3 +1,11 @@ +""" +Introduction +^^^^^^^^^^^^ + + + +""" + from . import optimization from . import latent_function_inference from . import mcmc From b0c18a90a4d755a27e316bfe3858cf7ac8faa1ea Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 28 Apr 2020 09:28:36 +0100 Subject: [PATCH 058/137] add plotting to docs index --- GPy/plotting/__init__.py | 8 ++++++++ doc/source/index.rst | 1 + 2 files changed, 9 insertions(+) diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py index 8c680caf..bbf83fa9 100644 --- a/GPy/plotting/__init__.py +++ b/GPy/plotting/__init__.py @@ -1,3 +1,11 @@ +""" +Introduction +^^^^^^^^^^^^ + + + +""" + # Copyright (c) 2014, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) current_lib = [None] diff --git a/doc/source/index.rst b/doc/source/index.rst index 61a605d9..dea42f81 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -52,6 +52,7 @@ Several tutorials have been developed in the form of `Jupyter Notebooks Date: Tue, 28 Apr 2020 11:04:28 +0100 Subject: [PATCH 059/137] summarise plotting --- GPy/plotting/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py index bbf83fa9..ffed794d 100644 --- a/GPy/plotting/__init__.py +++ b/GPy/plotting/__init__.py @@ -2,7 +2,7 @@ Introduction ^^^^^^^^^^^^ - +:py:class:`GPy.plotting` extends models based on :py:class:`GPy.core.gp.GP` by adding methods to plot useful charts. 'matplotlib', 'plotly' (online) and 'plotly' (offline) are supported. The methods in :py:class:`GPy.plotting` (and child classes :py:class:`GPy.plotting.gpy_plot` and :py:class:`GPy.plotting.matplot_dep`) are not intended to be called directly, but rather are 'injected' into other classes (notably :py:class:`GPy.core.gp.GP`). Documentation describing plots is best found associated with the model being plotted e.g. :py:class:`GPy.core.gp.GP.plot_confidence`. """ From 86a87f3397b0cf980bff38d35543256c62802440 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 28 Apr 2020 11:05:56 +0100 Subject: [PATCH 060/137] clarification --- GPy/plotting/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py index ffed794d..e1c50fe9 100644 --- a/GPy/plotting/__init__.py +++ b/GPy/plotting/__init__.py @@ -2,7 +2,7 @@ Introduction ^^^^^^^^^^^^ -:py:class:`GPy.plotting` extends models based on :py:class:`GPy.core.gp.GP` by adding methods to plot useful charts. 'matplotlib', 'plotly' (online) and 'plotly' (offline) are supported. The methods in :py:class:`GPy.plotting` (and child classes :py:class:`GPy.plotting.gpy_plot` and :py:class:`GPy.plotting.matplot_dep`) are not intended to be called directly, but rather are 'injected' into other classes (notably :py:class:`GPy.core.gp.GP`). Documentation describing plots is best found associated with the model being plotted e.g. :py:class:`GPy.core.gp.GP.plot_confidence`. +:py:class:`GPy.plotting` effectively extends models based on :py:class:`GPy.core.gp.GP` (and other classes) by adding methods to plot useful charts. 'matplotlib', 'plotly' (online) and 'plotly' (offline) are supported. The methods in :py:class:`GPy.plotting` (and child classes :py:class:`GPy.plotting.gpy_plot` and :py:class:`GPy.plotting.matplot_dep`) are not intended to be called directly, but rather are 'injected' into other classes (notably :py:class:`GPy.core.gp.GP`). Documentation describing plots is best found associated with the model being plotted e.g. :py:class:`GPy.core.gp.GP.plot_confidence`. """ From cf11962f05508815e39bafc08ec80e0ff82a4e67 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 28 Apr 2020 11:21:54 +0100 Subject: [PATCH 061/137] neater contents --- doc/source/index.rst | 2 -- 1 file changed, 2 deletions(-) diff --git a/doc/source/index.rst b/doc/source/index.rst index dea42f81..c3f3c54e 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -53,8 +53,6 @@ Several tutorials have been developed in the form of `Jupyter Notebooks Date: Tue, 28 Apr 2020 14:01:26 +0100 Subject: [PATCH 062/137] architecture diagram --- doc/source/architecture.rst | 4 ---- doc/source/index.rst | 39 +++++++++++++++++++++++++++++++++---- 2 files changed, 35 insertions(+), 8 deletions(-) delete mode 100644 doc/source/architecture.rst diff --git a/doc/source/architecture.rst b/doc/source/architecture.rst deleted file mode 100644 index b63166aa..00000000 --- a/doc/source/architecture.rst +++ /dev/null @@ -1,4 +0,0 @@ -GPy Project Architecture -======================== - - diff --git a/doc/source/index.rst b/doc/source/index.rst index c3f3c54e..707afd88 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -25,11 +25,42 @@ Tutorials Several tutorials have been developed in the form of `Jupyter Notebooks `_. -.. toctree:: - :maxdepth: 1 - :caption: Architecture +Architecture +------------ - architecture +GPy is a big, powerful package, with many features. The concept of how to use GPy in general terms is roughly as follows. A model (:py:class:`GPy.models`) is created - this is at the heart of GPy from a user perspective. A kernel (:py:class:`GPy.kern`), data and, usually, a representation of noise are assigned to the model. Specific models require, or can make use of, additional information. The kernel and noise are controlled by hyperparameters - calling the optimize (:py:class:`GPy.core.gp.GP.optimize`) method against the model invokes an iterative process which seeks optimal hyperparameter values. The model object can be used to make plots and predictions (:py:class:`GPy.core.gp.GP.predict`). + +.. graphviz:: + + digraph GPy_Arch { + + rankdir=LR + node[shape="rectangle" style="rounded,filled" fontname="Arial"] + edge [color="#006699" len=2.5] + + Data->Model + Hyperparameters->Kernel + Hyperparameters->Noise + Kernel->Model + Noise->Model + + Model->Optimize + Optimize->Hyperparameters + + Model->Predict + Model->Plot + + Optimize [shape="ellipse"] + Predict [shape="ellipse"] + Plot [shape="ellipse"] + + subgraph cluster_0 { + Data + Kernel + Noise + } + + } .. toctree:: :maxdepth: 1 From dec5bf8cefcc21c1363082fb1d2eb75a32b78af3 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 5 May 2020 12:46:57 +0100 Subject: [PATCH 063/137] using pods --- GPy/examples/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/examples/__init__.py b/GPy/examples/__init__.py index 8c7a5b65..4c5929f1 100644 --- a/GPy/examples/__init__.py +++ b/GPy/examples/__init__.py @@ -4,7 +4,7 @@ Examples for GPy. The examples in this package usually depend on `pods `_ so make sure -you have that installed before running examples. +you have that installed before running examples. The easiest way to do this is to run `pip install pods`. `pods` enables access to 3rd party data required for most of the examples. """ from . import classification from . import regression From f9aeffdba34c164626ff276f33431bfccd3b5944 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 12 May 2020 13:36:49 +0100 Subject: [PATCH 064/137] build with dot --- README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/README.md b/README.md index 171c0369..c8773758 100644 --- a/README.md +++ b/README.md @@ -222,6 +222,13 @@ The documentation can be compiled as follows: sphinx-apidoc -o source/ ../GPy/ make html +alternatively: + +```{shell} +cd doc +sphinx-build -b html -d build/doctrees -D graphviz_dot='' source build/html +``` + The HTML files are then stored in doc/build/html ### Commit new patch to devel From 159ca2eba691e06ccde274b33ea19f736ac1965d Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 12 May 2020 13:44:03 +0100 Subject: [PATCH 065/137] more on examples --- GPy/examples/__init__.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/GPy/examples/__init__.py b/GPy/examples/__init__.py index 4c5929f1..d0636ea8 100644 --- a/GPy/examples/__init__.py +++ b/GPy/examples/__init__.py @@ -1,10 +1,16 @@ # Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) """ -Examples for GPy. +Introduction +^^^^^^^^^^^^ The examples in this package usually depend on `pods `_ so make sure you have that installed before running examples. The easiest way to do this is to run `pip install pods`. `pods` enables access to 3rd party data required for most of the examples. + +The examples are executable and self-contained workflows in that they have their own source data, create their own models, kernels and other objects as needed, execute optimisation as required, and display output. + +Viewing the source code of each model will clarify the steps taken in its execution, and may provide inspiration for developing of user-specific applications of `GPy`. + """ from . import classification from . import regression From 3684e64ac2de501a7e211e87f15bd7047f32fc1c Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Tue, 12 May 2020 13:57:15 +0100 Subject: [PATCH 066/137] introduction for utils package --- GPy/util/__init__.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/GPy/util/__init__.py b/GPy/util/__init__.py index 55b88986..de6df56a 100644 --- a/GPy/util/__init__.py +++ b/GPy/util/__init__.py @@ -1,6 +1,12 @@ # Copyright (c) 2012, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) +""" +Introduction +^^^^^^^^^^^^ +A variety of utility functions including matrix operations and quick access to test datasets. + +""" from . import linalg from . import misc From 9fee83fdb042c561618b962776d653614f473e42 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Wed, 20 May 2020 11:16:19 +0100 Subject: [PATCH 067/137] compromise formatting for sphinx --- GPy/kern/src/coregionalize.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/GPy/kern/src/coregionalize.py b/GPy/kern/src/coregionalize.py index 0c471cb3..d5111c3b 100644 --- a/GPy/kern/src/coregionalize.py +++ b/GPy/kern/src/coregionalize.py @@ -20,12 +20,13 @@ class Coregionalize(Kern): Covariance function for intrinsic/linear coregionalization models This covariance has the form: + .. math:: - \mathbf{B} = \mathbf{W}\mathbf{W}^\top + \text{diag}(kappa) + \mathbf{B} = \mathbf{W}\mathbf{W}^\intercal + \mathrm{diag}(kappa) An intrinsic/linear coregionalization covariance function of the form: - .. math:: + .. math:: k_2(x, y)=\mathbf{B} k(x, y) it is obtained as the tensor product between a covariance function From e0304056f95de8922fce72b2a7ddfcd9bb4916ce Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Wed, 3 Jun 2020 15:52:16 +0100 Subject: [PATCH 068/137] correct likelihod definition --- GPy/likelihoods/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/likelihoods/__init__.py b/GPy/likelihoods/__init__.py index 606a5167..975abc88 100644 --- a/GPy/likelihoods/__init__.py +++ b/GPy/likelihoods/__init__.py @@ -2,7 +2,7 @@ Introduction ^^^^^^^^^^^^ -'Likelihood' in this context is a measure of how well a model *f* predicts a dataset *y*. The importance of likelihoods in Gaussian Processes is in determining the 'best' values of kernel and noise hyperparamters to relate known, observed and unobserved data. The purpose of optimizing a model (e.g. :py:class:`GPy.models.GPRegression`) is to determine the 'best' hyperparameters i.e. those that minimize negative log marginal likelihood. +The likelihood is :math:`p(y|f,X)` which is how well we will predict target values given inputs :math:`X` and our latent function :math:`f` (:math:`y` without noise). Marginal likelihood :math:`p(y|X)`, is the same as likelihood except we marginalize out the model :math:`f`. The importance of likelihoods in Gaussian Processes is in determining the 'best' values of kernel and noise hyperparamters to relate known, observed and unobserved data. The purpose of optimizing a model (e.g. :py:class:`GPy.models.GPRegression`) is to determine the 'best' hyperparameters i.e. those that minimize negative log marginal likelihood. .. inheritance-diagram:: GPy.likelihoods.likelihood GPy.likelihoods.mixed_noise.MixedNoise :top-classes: GPy.core.parameterization.parameterized.Parameterized From ef044197fbcac01e74d14281da1475a14d4702f8 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Thu, 4 Jun 2020 09:51:30 +0100 Subject: [PATCH 069/137] parameterization of priors --- GPy/core/parameterization/__init__.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/GPy/core/parameterization/__init__.py b/GPy/core/parameterization/__init__.py index fb064c9c..28ac755f 100644 --- a/GPy/core/parameterization/__init__.py +++ b/GPy/core/parameterization/__init__.py @@ -1,3 +1,14 @@ +""" +Introduction +^^^^^^^^^^^^ + +Extends the functionality of the `paramz` package (dependency) to support paramterization of priors (:py:class:`GPy.core.parameterization.priors`). + +.. inheritance-diagram:: GPy.core.parameterization.priors + :top-classes: paramz.core.parameter_core.Parameterizable +""" + + # Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) From 923343dcc268f35029bf7e1bd0296d7897e7c84a Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Thu, 18 Jun 2020 09:36:24 +0100 Subject: [PATCH 070/137] latent function inference intro and format --- .../latent_function_inference/__init__.py | 27 ++++++++++++------- 1 file changed, 17 insertions(+), 10 deletions(-) diff --git a/GPy/inference/latent_function_inference/__init__.py b/GPy/inference/latent_function_inference/__init__.py index be4fbde6..5af09442 100644 --- a/GPy/inference/latent_function_inference/__init__.py +++ b/GPy/inference/latent_function_inference/__init__.py @@ -1,23 +1,30 @@ # Copyright (c) 2012-2014, Max Zwiessele, James Hensman # Licensed under the BSD 3-clause license (see LICENSE.txt) -__doc__ = """ +""" +Introduction +^^^^^^^^^^^^ + +Certain :py:class:`GPy.models` can be instanciated with an `inference_method`. This submodule contains objects that can be assigned to `inference_method`. + Inference over Gaussian process latent functions +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -In all our GP models, the consistency propery means that we have a Gaussian -prior over a finite set of points f. This prior is +In all our GP models, the consistency property means that we have a Gaussian +prior over a finite set of points f. This prior is: - math:: N(f | 0, K) +.. math:: + N(f | 0, K) -where K is the kernel matrix. +where :math:`K` is the kernel matrix. -We also have a likelihood (see GPy.likelihoods) which defines how the data are -related to the latent function: p(y | f). If the likelihood is also a Gaussian, -the inference over f is tractable (see exact_gaussian_inference.py). +We also have a likelihood (see :py:class:`GPy.likelihoods`) which defines how the data are +related to the latent function: :math:`p(y | f)`. If the likelihood is also a Gaussian, +the inference over :math:`f` is tractable (see :py:class:`GPy.inference.latent_function_inference.exact_gaussian_inference`). If the likelihood object is something other than Gaussian, then exact inference -is not tractable. We then resort to a Laplace approximation (laplace.py) or -expectation propagation (ep.py). +is not tractable. We then resort to a Laplace approximation (:py:class:`GPy.inference.latent_function_inference.laplace`) or +expectation propagation (:py:class:`GPy.inference.latent_function_inference.expectation_propagation`). The inference methods return a :class:`~GPy.inference.latent_function_inference.posterior.Posterior` From 0a9b1cc10dedca11d9c7b1ac2c86bcbbe77b9eef Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Sat, 20 Jun 2020 08:08:21 +0200 Subject: [PATCH 071/137] maint: Remove tabs (and some trailing spaces) --- GPy/core/parameterization/priors.py | 47 ++++++------- GPy/kern/src/ODE_t.py | 20 +++--- GPy/kern/src/grid_kerns.py | 102 ++++++++++++++-------------- 3 files changed, 85 insertions(+), 84 deletions(-) diff --git a/GPy/core/parameterization/priors.py b/GPy/core/parameterization/priors.py index cbff4ca0..906ad65f 100644 --- a/GPy/core/parameterization/priors.py +++ b/GPy/core/parameterization/priors.py @@ -17,7 +17,7 @@ class Prior(object): if not cls._instance or cls._instance.__class__ is not cls: newfunc = super(Prior, cls).__new__ if newfunc is object.__new__: - cls._instance = newfunc(cls) + cls._instance = newfunc(cls) else: cls._instance = newfunc(cls, *args, **kwargs) return cls._instance @@ -58,9 +58,9 @@ class Gaussian(Prior): return instance() newfunc = super(Prior, cls).__new__ if newfunc is object.__new__: - o = newfunc(cls) + o = newfunc(cls) else: - o = newfunc(cls, mu, sigma) + o = newfunc(cls, mu, sigma) cls._instances.append(weakref.ref(o)) return cls._instances[-1]() @@ -102,9 +102,9 @@ class Uniform(Prior): return instance() newfunc = super(Prior, cls).__new__ if newfunc is object.__new__: - o = newfunc(cls) + o = newfunc(cls) else: - o = newfunc(cls, lower, upper) + o = newfunc(cls, lower, upper) cls._instances.append(weakref.ref(o)) return cls._instances[-1]() @@ -282,7 +282,7 @@ class Gamma(Prior): return instance() newfunc = super(Prior, cls).__new__ if newfunc is object.__new__: - o = newfunc(cls) + o = newfunc(cls) else: o = newfunc(cls, a, b) cls._instances.append(weakref.ref(o)) @@ -542,8 +542,8 @@ class DGPLVM(Prior): """ domain = _REAL - - def __new__(cls, sigma2, lbl, x_shape): + + def __new__(cls, sigma2, lbl, x_shape): return super(Prior, cls).__new__(cls, sigma2, lbl, x_shape) def __init__(self, sigma2, lbl, x_shape): @@ -909,13 +909,13 @@ class DGPLVM_Lamda(Prior, Parameterized): # This function calculates log of our prior def lnpdf(self, x): x = x.reshape(self.x_shape) - - #!!!!!!!!!!!!!!!!!!!!!!!!!!! - #self.lamda.values[:] = self.lamda.values/self.lamda.values.sum() + + #!!!!!!!!!!!!!!!!!!!!!!!!!!! + #self.lamda.values[:] = self.lamda.values/self.lamda.values.sum() xprime = x.dot(np.diagflat(self.lamda)) x = xprime - # print x + # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) M_i = self.compute_Mi(cls) @@ -932,7 +932,7 @@ class DGPLVM_Lamda(Prior, Parameterized): x = x.reshape(self.x_shape) xprime = x.dot(np.diagflat(self.lamda)) x = xprime - # print x + # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) M_i = self.compute_Mi(cls) @@ -964,14 +964,14 @@ class DGPLVM_Lamda(Prior, Parameterized): # Because of the GPy we need to transpose our matrix so that it gets the same shape as out matrix (denominator layout!!!) DPxprim_Dx = DPxprim_Dx.T - + DPxprim_Dlamda = DPx_Dx.dot(x) - # Because of the GPy we need to transpose our matrix so that it gets the same shape as out matrix (denominator layout!!!) + # Because of the GPy we need to transpose our matrix so that it gets the same shape as out matrix (denominator layout!!!) DPxprim_Dlamda = DPxprim_Dlamda.T self.lamda.gradient = np.diag(DPxprim_Dlamda) - # print DPxprim_Dx + # print DPxprim_Dx return DPxprim_Dx @@ -1046,7 +1046,7 @@ class DGPLVM_T(Prior): M_i = np.zeros((self.classnum, self.dim)) for i in cls: # Mean of each class - # class_i = np.multiply(cls[i],vec) + # class_i = np.multiply(cls[i],vec) class_i = cls[i] M_i[i] = np.mean(class_i, axis=0) return M_i @@ -1155,7 +1155,7 @@ class DGPLVM_T(Prior): x = x.reshape(self.x_shape) xprim = x.dot(self.vec) x = xprim - # print x + # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) M_i = self.compute_Mi(cls) @@ -1163,7 +1163,7 @@ class DGPLVM_T(Prior): 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_inv_N = np.linalg.inv(Sb+np.eye(Sb.shape[0])*0.1) - #print 'SB_inv: ', Sb_inv_N + #print 'SB_inv: ', Sb_inv_N #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] return (-1 / self.sigma2) * np.trace(Sb_inv_N.dot(Sw)) @@ -1172,8 +1172,8 @@ class DGPLVM_T(Prior): def lnpdf_grad(self, x): x = x.reshape(self.x_shape) xprim = x.dot(self.vec) - x = xprim - # print x + x = xprim + # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) M_i = self.compute_Mi(cls) @@ -1188,7 +1188,7 @@ class DGPLVM_T(Prior): # Calculating inverse of Sb and its transpose and minus # 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) - #print 'SB_inv: ',Sb_inv_N + #print 'SB_inv: ',Sb_inv_N #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] Sb_inv_N_trans = np.transpose(Sb_inv_N) @@ -1375,4 +1375,5 @@ class StudentT(Prior): def rvs(self, n): from scipy.stats import t ret = t.rvs(self.nu, loc=self.mu, scale=self.sigma, size=n) - return ret + return ret + diff --git a/GPy/kern/src/ODE_t.py b/GPy/kern/src/ODE_t.py index 539330a3..f6530c32 100644 --- a/GPy/kern/src/ODE_t.py +++ b/GPy/kern/src/ODE_t.py @@ -20,7 +20,7 @@ class ODE_t(Kern): self.link_parameters(self.a, self.c, self.variance_Yt, self.lengthscale_Yt,self.ubias) def K(self, X, X2=None): - """Compute the covariance matrix between X and X2.""" + """Compute the covariance matrix between X and X2.""" X,slices = X[:,:-1],index_to_slices(X[:,-1]) if X2 is None: X2,slices2 = X,slices @@ -31,9 +31,9 @@ class ODE_t(Kern): tdist = (X[:,0][:,None] - X2[:,0][None,:])**2 ttdist = (X[:,0][:,None] - X2[:,0][None,:]) - + vyt = self.variance_Yt - + lyt=1/(2*self.lengthscale_Yt) a = -self.a @@ -69,10 +69,10 @@ class ODE_t(Kern): lyt = 1./(2*self.lengthscale_Yt) a = -self.a - c = self.c - + c = self.c + k1 = (2*lyt )*vyt - + Kdiag = np.zeros(X.shape[0]) slices = index_to_slices(X[:,-1]) @@ -106,7 +106,7 @@ class ODE_t(Kern): tdist = (X[:,0][:,None] - X2[:,0][None,:])**2 ttdist = (X[:,0][:,None] - X2[:,0][None,:]) #rdist = [tdist,xdist] - + rd=tdist.shape[0] dka = np.zeros([rd,rd]) @@ -146,7 +146,7 @@ class ODE_t(Kern): elif i==1 and j==1: dkYdvart[ss1,ss2] = (k1(tdist[ss1,ss2]) + 1. )* kyy(tdist[ss1,ss2]) dkYdlent[ss1,ss2] = vyt*dkyydlyt(tdist[ss1,ss2])*( k1(tdist[ss1,ss2]) + 1. ) +\ - vyt*kyy(tdist[ss1,ss2])*dk1dlyt(tdist[ss1,ss2]) + vyt*kyy(tdist[ss1,ss2])*dk1dlyt(tdist[ss1,ss2]) dkdubias[ss1,ss2] = 1 else: dkYdvart[ss1,ss2] = (-k4(ttdist[ss1,ss2])+1)*kyy(tdist[ss1,ss2]) @@ -156,10 +156,10 @@ class ODE_t(Kern): dkdubias[ss1,ss2] = 0 #dkYdlent[ss1,ss2] = vyt*dkyydlyt(tdist[ss1,ss2])* (-2*lyt*(ttdist[ss1,ss2])+1.)+\ #vyt*kyy(tdist[ss1,ss2])*(-2)*(ttdist[ss1,ss2]) - self.variance_Yt.gradient = np.sum(dkYdvart * dL_dK) self.lengthscale_Yt.gradient = np.sum(dkYdlent*(-0.5*self.lengthscale_Yt**(-2)) * dL_dK) - self.ubias.gradient = np.sum(dkdubias * dL_dK) + self.ubias.gradient = np.sum(dkdubias * dL_dK) + diff --git a/GPy/kern/src/grid_kerns.py b/GPy/kern/src/grid_kerns.py index ef18f1a9..9f153c27 100644 --- a/GPy/kern/src/grid_kerns.py +++ b/GPy/kern/src/grid_kerns.py @@ -10,67 +10,67 @@ from paramz.caching import Cache_this class GridKern(Stationary): - def __init__(self, input_dim, variance, lengthscale, ARD, active_dims, name, originalDimensions, useGPU=False): - super(GridKern, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name, useGPU=useGPU) - self.originalDimensions = originalDimensions + def __init__(self, input_dim, variance, lengthscale, ARD, active_dims, name, originalDimensions, useGPU=False): + super(GridKern, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name, useGPU=useGPU) + self.originalDimensions = originalDimensions - @Cache_this(limit=3, ignore_args=()) - def dKd_dVar(self, X, X2=None): - """ - Derivative of Kernel function wrt variance applied on inputs X and X2. - In the stationary case there is an inner function depending on the - distances from X to X2, called r. + @Cache_this(limit=3, ignore_args=()) + def dKd_dVar(self, X, X2=None): + """ + Derivative of Kernel function wrt variance applied on inputs X and X2. + In the stationary case there is an inner function depending on the + distances from X to X2, called r. - dKd_dVar(X, X2) = dKdVar_of_r((X-X2)**2) - """ - r = self._scaled_dist(X, X2) - return self.dKdVar_of_r(r) + dKd_dVar(X, X2) = dKdVar_of_r((X-X2)**2) + """ + r = self._scaled_dist(X, X2) + return self.dKdVar_of_r(r) - @Cache_this(limit=3, ignore_args=()) - def dKd_dLen(self, X, dimension, lengthscale, X2=None): - """ - Derivate of Kernel function wrt lengthscale applied on inputs X and X2. - In the stationary case there is an inner function depending on the - distances from X to X2, called r. + @Cache_this(limit=3, ignore_args=()) + def dKd_dLen(self, X, dimension, lengthscale, X2=None): + """ + Derivate of Kernel function wrt lengthscale applied on inputs X and X2. + In the stationary case there is an inner function depending on the + distances from X to X2, called r. - dKd_dLen(X, X2) = dKdLen_of_r((X-X2)**2) - """ - r = self._scaled_dist(X, X2) - return self.dKdLen_of_r(r, dimension, lengthscale) + dKd_dLen(X, X2) = dKdLen_of_r((X-X2)**2) + """ + r = self._scaled_dist(X, X2) + return self.dKdLen_of_r(r, dimension, lengthscale) class GridRBF(GridKern): - """ - Similar to regular RBF but supplemented with methods required for Gaussian grid regression - Radial Basis Function kernel, aka squared-exponential, exponentiated quadratic or Gaussian kernel: + """ + Similar to regular RBF but supplemented with methods required for Gaussian grid regression + Radial Basis Function kernel, aka squared-exponential, exponentiated quadratic or Gaussian kernel: - .. math:: + .. math:: - k(r) = \sigma^2 \exp \\bigg(- \\frac{1}{2} r^2 \\bigg) + k(r) = \sigma^2 \exp \\bigg(- \\frac{1}{2} r^2 \\bigg) - """ - _support_GPU = True - def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='gridRBF', originalDimensions=1, useGPU=False): - super(GridRBF, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name, originalDimensions, useGPU=useGPU) + """ + _support_GPU = True + def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='gridRBF', originalDimensions=1, useGPU=False): + super(GridRBF, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name, originalDimensions, useGPU=useGPU) - def K_of_r(self, r): - return (self.variance**(float(1)/self.originalDimensions)) * np.exp(-0.5 * r**2) + def K_of_r(self, r): + return (self.variance**(float(1)/self.originalDimensions)) * np.exp(-0.5 * r**2) - def dKdVar_of_r(self, r): - """ - Compute derivative of kernel wrt variance - """ - return np.exp(-0.5 * r**2) + def dKdVar_of_r(self, r): + """ + Compute derivative of kernel wrt variance + """ + return np.exp(-0.5 * r**2) - def dKdLen_of_r(self, r, dimCheck, lengthscale): - """ - Compute derivative of kernel for dimension wrt lengthscale - Computation of derivative changes when lengthscale corresponds to - the dimension of the kernel whose derivate is being computed. - """ - if (dimCheck == True): - return (self.variance**(float(1)/self.originalDimensions)) * np.exp(-0.5 * r**2) * (r**2) / (lengthscale**(float(1)/self.originalDimensions)) - else: - return (self.variance**(float(1)/self.originalDimensions)) * np.exp(-0.5 * r**2) / (lengthscale**(float(1)/self.originalDimensions)) + def dKdLen_of_r(self, r, dimCheck, lengthscale): + """ + Compute derivative of kernel for dimension wrt lengthscale + Computation of derivative changes when lengthscale corresponds to + the dimension of the kernel whose derivate is being computed. + """ + if (dimCheck == True): + return (self.variance**(float(1)/self.originalDimensions)) * np.exp(-0.5 * r**2) * (r**2) / (lengthscale**(float(1)/self.originalDimensions)) + else: + return (self.variance**(float(1)/self.originalDimensions)) * np.exp(-0.5 * r**2) / (lengthscale**(float(1)/self.originalDimensions)) - def dK_dr(self, r): - return -r*self.K_of_r(r) \ No newline at end of file + def dK_dr(self, r): + return -r*self.K_of_r(r) From c23a1a0eb4bf144a79ff603d8e15ff8cecf4871c Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Tue, 23 Jun 2020 22:33:17 +0200 Subject: [PATCH 072/137] dpgplvm.py: Wrap long line + remove tabs --- GPy/models/dpgplvm.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/GPy/models/dpgplvm.py b/GPy/models/dpgplvm.py index b4b1bbef..78a6a73a 100644 --- a/GPy/models/dpgplvm.py +++ b/GPy/models/dpgplvm.py @@ -11,6 +11,11 @@ class DPBayesianGPLVM(BayesianGPLVM): Z=None, kernel=None, inference_method=None, likelihood=None, name='bayesian gplvm', mpi_comm=None, normalizer=None, missing_data=False, stochastic=False, batchsize=1): - super(DPBayesianGPLVM,self).__init__(Y=Y, input_dim=input_dim, X=X, X_variance=X_variance, init=init, num_inducing=num_inducing, Z=Z, kernel=kernel, inference_method=inference_method, likelihood=likelihood, mpi_comm=mpi_comm, normalizer=normalizer, missing_data=missing_data, stochastic=stochastic, batchsize=batchsize, name='dp bayesian gplvm') + super(DPBayesianGPLVM,self).__init__(Y=Y, input_dim=input_dim, X=X, X_variance=X_variance, + init=init, num_inducing=num_inducing, Z=Z, kernel=kernel, + inference_method=inference_method, likelihood=likelihood, + mpi_comm=mpi_comm, normalizer=normalizer, + missing_data=missing_data, stochastic=stochastic, + batchsize=batchsize, name='dp bayesian gplvm') self.X.mean.set_prior(X_prior) self.link_parameter(X_prior) From 1d549ca5c6c65d1760e5091ae22ae67fee1474c7 Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Tue, 23 Jun 2020 22:33:43 +0200 Subject: [PATCH 073/137] dpgplvm.py: Fix typo in the header --- GPy/models/dpgplvm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/models/dpgplvm.py b/GPy/models/dpgplvm.py index 78a6a73a..9c6a36fc 100644 --- a/GPy/models/dpgplvm.py +++ b/GPy/models/dpgplvm.py @@ -1,4 +1,4 @@ -# Copyright (c) 2015 the GPy Austhors (see AUTHORS.txt) +# Copyright (c) 2015 the GPy Authors (see AUTHORS.txt) # Licensed under the BSD 3-clause license (see LICENSE.txt) from .bayesian_gplvm import BayesianGPLVM From d754bc12de8a97919fee358e479ac55b5e678e4e Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Wed, 24 Jun 2020 06:39:40 +0200 Subject: [PATCH 074/137] maint: Wrap very long lines (> 450 chars) --- GPy/kern/src/kern.py | 9 ++++++++- GPy/likelihoods/__init__.py | 21 ++++++++++++++++----- GPy/models/gp_multiout_regression_md.py | 14 +++++++++++--- GPy/models/sparse_gp_regression_md.py | 15 ++++++++++++--- GPy/plotting/__init__.py | 14 +++++++++++--- 5 files changed, 58 insertions(+), 15 deletions(-) diff --git a/GPy/kern/src/kern.py b/GPy/kern/src/kern.py index 362ac418..b8597c73 100644 --- a/GPy/kern/src/kern.py +++ b/GPy/kern/src/kern.py @@ -434,7 +434,14 @@ class CombinationKernel(Kern): [setitem(i_s, (i, k._all_dims_active), k.input_sensitivity(summarize)) for i, k in enumerate(parts)] return i_s else: - raise NotImplementedError("Choose the kernel you want to get the sensitivity for. You need to override the default behaviour for getting the input sensitivity to be able to get the input sensitivity. For sum kernel it is the sum of all sensitivities, TODO: product kernel? Other kernels?, also TODO: shall we return all the sensitivities here in the combination kernel? So we can combine them however we want? This could lead to just plot all the sensitivities here...") + raise NotImplementedError("Choose the kernel you want to get the sensitivity for. " + "You need to override the default behaviour for getting " + "the input sensitivity to be able to get the input sensitivity. " + "For sum kernel it is the sum of all sensitivities, " + "TODO: product kernel? Other kernels?, also " + "TODO: shall we return all the sensitivities here in the combination " + "kernel? So we can combine them however we want? " + "This could lead to just plot all the sensitivities here...") def _check_active_dims(self, X): return diff --git a/GPy/likelihoods/__init__.py b/GPy/likelihoods/__init__.py index 975abc88..49cc5088 100644 --- a/GPy/likelihoods/__init__.py +++ b/GPy/likelihoods/__init__.py @@ -1,13 +1,24 @@ -""" -Introduction +"""Introduction ^^^^^^^^^^^^ -The likelihood is :math:`p(y|f,X)` which is how well we will predict target values given inputs :math:`X` and our latent function :math:`f` (:math:`y` without noise). Marginal likelihood :math:`p(y|X)`, is the same as likelihood except we marginalize out the model :math:`f`. The importance of likelihoods in Gaussian Processes is in determining the 'best' values of kernel and noise hyperparamters to relate known, observed and unobserved data. The purpose of optimizing a model (e.g. :py:class:`GPy.models.GPRegression`) is to determine the 'best' hyperparameters i.e. those that minimize negative log marginal likelihood. +The likelihood is :math:`p(y|f,X)` which is how well we will predict +target values given inputs :math:`X` and our latent function :math:`f` +(:math:`y` without noise). Marginal likelihood :math:`p(y|X)`, is the +same as likelihood except we marginalize out the model :math:`f`. The +importance of likelihoods in Gaussian Processes is in determining the +'best' values of kernel and noise hyperparamters to relate known, +observed and unobserved data. The purpose of optimizing a model +(e.g. :py:class:`GPy.models.GPRegression`) is to determine the 'best' +hyperparameters i.e. those that minimize negative log marginal +likelihood. .. inheritance-diagram:: GPy.likelihoods.likelihood GPy.likelihoods.mixed_noise.MixedNoise :top-classes: GPy.core.parameterization.parameterized.Parameterized -Most likelihood classes inherit directly from :py:class:`GPy.likelihoods.likelihood`, although an intermediary class :py:class:`GPy.likelihoods.mixed_noise.MixedNoise` is used by :py:class:`GPy.likelihoods.multioutput_likelihood`. +Most likelihood classes inherit directly from +:py:class:`GPy.likelihoods.likelihood`, although an intermediary class +:py:class:`GPy.likelihoods.mixed_noise.MixedNoise` is used by +:py:class:`GPy.likelihoods.multioutput_likelihood`. """ @@ -22,4 +33,4 @@ from .mixed_noise import MixedNoise from .binomial import Binomial from .weibull import Weibull from .loglogistic import LogLogistic -from .multioutput_likelihood import MultioutputLikelihood \ No newline at end of file +from .multioutput_likelihood import MultioutputLikelihood diff --git a/GPy/models/gp_multiout_regression_md.py b/GPy/models/gp_multiout_regression_md.py index 3eb91114..292f525d 100644 --- a/GPy/models/gp_multiout_regression_md.py +++ b/GPy/models/gp_multiout_regression_md.py @@ -13,10 +13,18 @@ from ..util.linalg import tdot from .sparse_gp_regression_md import SparseGPRegressionMD class GPMultioutRegressionMD(SparseGP): - """ - Gaussian Process model for multi-output regression with missing data + """Gaussian Process model for multi-output regression with missing data - This is an implementation of Latent Variable Multiple Output Gaussian Processes (LVMOGP) in [Dai_et_al_2017]_. This model targets at the use case, in which each output dimension is observed at a different set of inputs. The model takes a different data format: the inputs and outputs observations of all the output dimensions are stacked together correspondingly into two matrices. An extra array is used to indicate the index of output dimension for each data point. The output dimensions are indexed using integers from 0 to D-1 assuming there are D output dimensions. + This is an implementation of Latent Variable Multiple Output + Gaussian Processes (LVMOGP) in [Dai_et_al_2017]_. This model + targets at the use case, in which each output dimension is + observed at a different set of inputs. The model takes a different + data format: the inputs and outputs observations of all the output + dimensions are stacked together correspondingly into two + matrices. An extra array is used to indicate the index of output + dimension for each data point. The output dimensions are indexed + using integers from 0 to D-1 assuming there are D output + dimensions. .. rubric:: References diff --git a/GPy/models/sparse_gp_regression_md.py b/GPy/models/sparse_gp_regression_md.py index 9e601e96..bf9b784c 100644 --- a/GPy/models/sparse_gp_regression_md.py +++ b/GPy/models/sparse_gp_regression_md.py @@ -10,10 +10,18 @@ from ..inference.latent_function_inference.vardtc_md import VarDTC_MD from GPy.core.parameterization.variational import NormalPosterior class SparseGPRegressionMD(SparseGP_MPI): - """ - Sparse Gaussian Process Regression with Missing Data + """Sparse Gaussian Process Regression with Missing Data - This model targets at the use case, in which there are multiple output dimensions (different dimensions are assumed to be independent following the same GP prior) and each output dimension is observed at a different set of inputs. The model takes a different data format: the inputs and outputs observations of all the output dimensions are stacked together correspondingly into two matrices. An extra array is used to indicate the index of output dimension for each data point. The output dimensions are indexed using integers from 0 to D-1 assuming there are D output dimensions. + This model targets at the use case, in which there are multiple + output dimensions (different dimensions are assumed to be + independent following the same GP prior) and each output dimension + is observed at a different set of inputs. The model takes a + different data format: the inputs and outputs observations of all + the output dimensions are stacked together correspondingly into + two matrices. An extra array is used to indicate the index of + output dimension for each data point. The output dimensions are + indexed using integers from 0 to D-1 assuming there are D output + dimensions. :param X: input observations. :type X: numpy.ndarray @@ -29,6 +37,7 @@ class SparseGPRegressionMD(SparseGP_MPI): :type num_inducing: (int, int) :param boolean individual_Y_noise: whether individual output dimensions have their own noise variance or not, boolean :param str name: the name of the model + """ def __init__(self, X, Y, indexD, kernel=None, Z=None, num_inducing=10, normalizer=None, mpi_comm=None, individual_Y_noise=False, name='sparse_gp'): diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py index e1c50fe9..8c70ef84 100644 --- a/GPy/plotting/__init__.py +++ b/GPy/plotting/__init__.py @@ -1,8 +1,16 @@ -""" -Introduction +"""Introduction ^^^^^^^^^^^^ -:py:class:`GPy.plotting` effectively extends models based on :py:class:`GPy.core.gp.GP` (and other classes) by adding methods to plot useful charts. 'matplotlib', 'plotly' (online) and 'plotly' (offline) are supported. The methods in :py:class:`GPy.plotting` (and child classes :py:class:`GPy.plotting.gpy_plot` and :py:class:`GPy.plotting.matplot_dep`) are not intended to be called directly, but rather are 'injected' into other classes (notably :py:class:`GPy.core.gp.GP`). Documentation describing plots is best found associated with the model being plotted e.g. :py:class:`GPy.core.gp.GP.plot_confidence`. +:py:class:`GPy.plotting` effectively extends models based on +:py:class:`GPy.core.gp.GP` (and other classes) by adding methods to +plot useful charts. 'matplotlib', 'plotly' (online) and 'plotly' +(offline) are supported. The methods in :py:class:`GPy.plotting` (and +child classes :py:class:`GPy.plotting.gpy_plot` and +:py:class:`GPy.plotting.matplot_dep`) are not intended to be called +directly, but rather are 'injected' into other classes (notably +:py:class:`GPy.core.gp.GP`). Documentation describing plots is best +found associated with the model being plotted +e.g. :py:class:`GPy.core.gp.GP.plot_confidence`. """ From 44f4739efb5b19660ab7f606afa1e62df29c18a8 Mon Sep 17 00:00:00 2001 From: Julien Bect Date: Wed, 24 Jun 2020 16:09:02 +0200 Subject: [PATCH 075/137] maint: Wrap very long lines (> 400 chars) --- GPy/core/__init__.py | 27 +++++++++++++---- GPy/kern/__init__.py | 18 ++++++++--- GPy/kern/src/psi_comp/ssrbf_psi_gpucomp.py | 35 +++++++++++++++++----- GPy/util/datasets.py | 10 ++++++- 4 files changed, 73 insertions(+), 17 deletions(-) diff --git a/GPy/core/__init__.py b/GPy/core/__init__.py index f2dc4904..08659add 100644 --- a/GPy/core/__init__.py +++ b/GPy/core/__init__.py @@ -5,23 +5,40 @@ Introduction ^^^^^^^^^^^^ -This module contains the fundamental classes of GPy - classes that are inherited by objects in other parts of GPy in order to provide a consistent interface to major functionality. +This module contains the fundamental classes of GPy - classes that are +inherited by objects in other parts of GPy in order to provide a +consistent interface to major functionality. .. inheritance-diagram:: GPy.core.gp.GP :top-classes: paramz.core.parameter_core.Parameterizable -:py:class:`GPy.core.model` is inherited by :py:class:`GPy.core.gp.GP`. And :py:class:`GPy.core.model` itself inherits :py:class:`paramz.model.Model` from the `paramz` package. `paramz` essentially provides an inherited set of properties and functions used to manage state (and state changes) of the model. +:py:class:`GPy.core.model` is inherited by +:py:class:`GPy.core.gp.GP`. And :py:class:`GPy.core.model` itself +inherits :py:class:`paramz.model.Model` from the `paramz` +package. `paramz` essentially provides an inherited set of properties +and functions used to manage state (and state changes) of the model. -:py:class:`GPy.core.gp.GP` represents a GP model. Such an entity is typically passed variables representing known (x) and observed (y) data, along with a kernel and other information needed to create the specific model. It exposes functions which return information derived from the inputs to the model, for example predicting unobserved variables based on new known variables, or the log marginal likelihood of the current state of the model. +:py:class:`GPy.core.gp.GP` represents a GP model. Such an entity is +typically passed variables representing known (x) and observed (y) +data, along with a kernel and other information needed to create the +specific model. It exposes functions which return information derived +from the inputs to the model, for example predicting unobserved +variables based on new known variables, or the log marginal likelihood +of the current state of the model. -:py:func:`~GPy.core.gp.GP.optimize` is called to optimize hyperparameters of the model. The optimizer argument takes a string which is used to specify non-default optimization schemes. +:py:func:`~GPy.core.gp.GP.optimize` is called to optimize +hyperparameters of the model. The optimizer argument takes a string +which is used to specify non-default optimization schemes. Various plotting functions can be called against :py:class:`GPy.core.gp.GP`. .. inheritance-diagram:: GPy.core.gp_grid.GpGrid GPy.core.sparse_gp.SparseGP GPy.core.sparse_gp_mpi.SparseGP_MPI GPy.core.svgp.SVGP :top-classes: GPy.core.gp.GP -:py:class:`GPy.core.gp.GP` is used as the basis for classes supporting more specialized types of Gaussian Process model. These are however generally still not specific enough to be called by the user and are inhereted by members of the :py:class:`GPy.models` package. +:py:class:`GPy.core.gp.GP` is used as the basis for classes supporting +more specialized types of Gaussian Process model. These are however +generally still not specific enough to be called by the user and are +inhereted by members of the :py:class:`GPy.models` package. """ diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index 33301817..178e4019 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -3,9 +3,20 @@ Introduction ^^^^^^^^^^^^ -In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters. *Note: this may be too simple a definition for the broad range of kernels available in :py:class:`GPy`.* +In terms of Gaussian Processes, a kernel is a function that specifies +the degree of similarity between variables given their relative +positions in parameter space. If known variables *x* and *x'* are +close together then observed variables *y* and *y'* may also be +similar, depending on the kernel function and its parameters. *Note: +this may be too simple a definition for the broad range of kernels +available in :py:class:`GPy`.* -:py:class:`GPy.kern.src.kern.Kern` is a generic kernel object inherited by more specific, end-user kernels used in models. It provides methods that specific kernels should generally have such as :py:class:`GPy.kern.src.kern.Kern.K` to compute the value of the kernel, :py:class:`GPy.kern.src.kern.Kern.add` to combine kernels and numerous functions providing information on kernel gradients. +:py:class:`GPy.kern.src.kern.Kern` is a generic kernel object +inherited by more specific, end-user kernels used in models. It +provides methods that specific kernels should generally have such as +:py:class:`GPy.kern.src.kern.Kern.K` to compute the value of the +kernel, :py:class:`GPy.kern.src.kern.Kern.add` to combine kernels and +numerous functions providing information on kernel gradients. There are several inherited types of kernel that provide a basis for specific end user kernels: @@ -20,7 +31,6 @@ e.g. the archetype :py:class:`GPy.kern.RBF` does not inherit directly from :py:c """ - from .src.kern import Kern from .src.add import Add from .src.prod import Prod @@ -61,4 +71,4 @@ from .src.sde_stationary import sde_RBF,sde_Exponential,sde_RatQuad from .src.sde_brownian import sde_Brownian from .src.multioutput_kern import MultioutputKern from .src.multioutput_derivative_kern import MultioutputDerivativeKern -from .src.diff_kern import DiffKern \ No newline at end of file +from .src.diff_kern import DiffKern diff --git a/GPy/kern/src/psi_comp/ssrbf_psi_gpucomp.py b/GPy/kern/src/psi_comp/ssrbf_psi_gpucomp.py index 488e9e22..f626c2d5 100644 --- a/GPy/kern/src/psi_comp/ssrbf_psi_gpucomp.py +++ b/GPy/kern/src/psi_comp/ssrbf_psi_gpucomp.py @@ -448,12 +448,34 @@ class PSICOMP_SSRBF_GPU(PSICOMP_RBF): dL_dpsi0_sum = dL_dpsi0.sum() self.reset_derivative() - # t=self.g_psi1compDer(dvar_gpu,dl_gpu,dZ_gpu,dmu_gpu,dS_gpu,dL_dpsi1_gpu,psi1_gpu, np.float64(variance),l_gpu,Z_gpu,mu_gpu,S_gpu, np.int32(N), np.int32(M), np.int32(Q), block=(self.threadnum,1,1), grid=(self.blocknum,1),time_kernel=True) + # t=self.g_psi1compDer(dvar_gpu,dl_gpu,dZ_gpu,dmu_gpu,dS_gpu,dL_dpsi1_gpu,psi1_gpu, + # np.float64(variance),l_gpu,Z_gpu,mu_gpu,S_gpu, np.int32(N), + # np.int32(M), np.int32(Q), block=(self.threadnum,1,1), + # grid=(self.blocknum,1),time_kernel=True) # print 'g_psi1compDer '+str(t) - # t=self.g_psi2compDer(dvar_gpu,dl_gpu,dZ_gpu,dmu_gpu,dS_gpu,dL_dpsi2_gpu,psi2n_gpu, np.float64(variance),l_gpu,Z_gpu,mu_gpu,S_gpu, np.int32(N), np.int32(M), np.int32(Q), block=(self.threadnum,1,1), grid=(self.blocknum,1),time_kernel=True) + # t=self.g_psi2compDer(dvar_gpu,dl_gpu,dZ_gpu,dmu_gpu,dS_gpu,dL_dpsi2_gpu,psi2n_gpu, + # np.float64(variance),l_gpu,Z_gpu,mu_gpu,S_gpu, np.int32(N), + # np.int32(M), np.int32(Q), block=(self.threadnum,1,1), + # grid=(self.blocknum,1),time_kernel=True) # print 'g_psi2compDer '+str(t) - self.g_psi1compDer.prepared_call((self.blocknum,1),(self.threadnum,1,1),dvar_gpu.gpudata,dl_gpu.gpudata,dZ_gpu.gpudata,dmu_gpu.gpudata,dS_gpu.gpudata,dgamma_gpu.gpudata,dL_dpsi1_gpu.gpudata,psi1_gpu.gpudata, log_denom1_gpu.gpudata, log_gamma_gpu.gpudata, log_gamma1_gpu.gpudata, np.float64(variance),l_gpu.gpudata,Z_gpu.gpudata,mu_gpu.gpudata,S_gpu.gpudata,gamma_gpu.gpudata,np.int32(N), np.int32(M), np.int32(Q)) - self.g_psi2compDer.prepared_call((self.blocknum,1),(self.threadnum,1,1),dvar_gpu.gpudata,dl_gpu.gpudata,dZ_gpu.gpudata,dmu_gpu.gpudata,dS_gpu.gpudata,dgamma_gpu.gpudata,dL_dpsi2_gpu.gpudata,psi2n_gpu.gpudata, log_denom2_gpu.gpudata, log_gamma_gpu.gpudata, log_gamma1_gpu.gpudata, np.float64(variance),l_gpu.gpudata,Z_gpu.gpudata,mu_gpu.gpudata,S_gpu.gpudata,gamma_gpu.gpudata,np.int32(N), np.int32(M), np.int32(Q)) + self.g_psi1compDer.prepared_call((self.blocknum,1), (self.threadnum,1,1), + dvar_gpu.gpudata, dl_gpu.gpudata, dZ_gpu.gpudata, + dmu_gpu.gpudata, dS_gpu.gpudata, dgamma_gpu.gpudata, + dL_dpsi1_gpu.gpudata, psi1_gpu.gpudata, + log_denom1_gpu.gpudata, log_gamma_gpu.gpudata, + log_gamma1_gpu.gpudata, np.float64(variance), + l_gpu.gpudata, Z_gpu.gpudata, mu_gpu.gpudata, + S_gpu.gpudata, gamma_gpu.gpudata, np.int32(N), + np.int32(M), np.int32(Q)) + self.g_psi2compDer.prepared_call((self.blocknum,1), (self.threadnum,1,1), + dvar_gpu.gpudata, dl_gpu.gpudata, dZ_gpu.gpudata, + dmu_gpu.gpudata, dS_gpu.gpudata, dgamma_gpu.gpudata, + dL_dpsi2_gpu.gpudata, psi2n_gpu.gpudata, + log_denom2_gpu.gpudata, log_gamma_gpu.gpudata, + log_gamma1_gpu.gpudata, np.float64(variance), + l_gpu.gpudata, Z_gpu.gpudata, mu_gpu.gpudata, + S_gpu.gpudata, gamma_gpu.gpudata, np.int32(N), + np.int32(M), np.int32(Q)) dL_dvar = dL_dpsi0_sum + gpuarray.sum(dvar_gpu).get() sum_axis(grad_mu_gpu,dmu_gpu,N*Q,self.blocknum) @@ -468,7 +490,6 @@ class PSICOMP_SSRBF_GPU(PSICOMP_RBF): dL_dlengscale = grad_l_gpu.get() else: dL_dlengscale = gpuarray.sum(dl_gpu).get() - - return dL_dvar, dL_dlengscale, dL_dZ, dL_dmu, dL_dS, dL_dgamma - + + return dL_dvar, dL_dlengscale, dL_dZ, dL_dmu, dL_dS, dL_dgamma diff --git a/GPy/util/datasets.py b/GPy/util/datasets.py index 035f7b75..c406ed7b 100644 --- a/GPy/util/datasets.py +++ b/GPy/util/datasets.py @@ -500,7 +500,15 @@ def drosophila_knirps(data_set='drosophila_protein'): # This will be for downloading google trends data. def google_trends(query_terms=['big data', 'machine learning', 'data science'], data_set='google_trends', refresh_data=False): - """Data downloaded from Google trends for given query terms. Warning, if you use this function multiple times in a row you get blocked due to terms of service violations. The function will cache the result of your query, if you wish to refresh an old query set refresh_data to True. The function is inspired by this notebook: http://nbviewer.ipython.org/github/sahuguet/notebooks/blob/master/GoogleTrends%20meet%20Notebook.ipynb""" + """Data downloaded from Google trends for given query terms. + +Warning, if you use this function multiple times in a row you get +blocked due to terms of service violations. The function will cache +the result of your query, if you wish to refresh an old query set +refresh_data to True. + +The function is inspired by this notebook: +http://nbviewer.ipython.org/github/sahuguet/notebooks/blob/master/GoogleTrends%20meet%20Notebook.ipynb""" query_terms.sort() import pandas From ec20f9ed3a6d98e278a35114e592f1ea098b5531 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Fri, 26 Jun 2020 11:39:28 +0100 Subject: [PATCH 076/137] Add the link to the api doc on the readme page. --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c8f8937e..545a1ae5 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ The Gaussian processes framework in Python. * GPy [homepage](http://sheffieldml.github.io/GPy/) * Tutorial [notebooks](http://nbviewer.ipython.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb) * User [mailing-list](https://lists.shef.ac.uk/sympa/subscribe/gpy-users) -* Developer [documentation](http://gpy.readthedocs.io/) +* Developer [documentation](http://gpy.readthedocs.io/) [documentation (devel branch)](https://gpy.readthedocs.io/en/devel/) * Travis-CI [unit-tests](https://travis-ci.org/SheffieldML/GPy) * [![licence](https://img.shields.io/badge/licence-BSD-blue.svg)](http://opensource.org/licenses/BSD-3-Clause) [![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy) From 04a9d9d994e2a0f5957747e1e2b862da96c75326 Mon Sep 17 00:00:00 2001 From: bobturneruk Date: Thu, 24 Sep 2020 11:14:14 +0100 Subject: [PATCH 077/137] remove deprecated parameter --- GPy/testing/plotting_tests.py | 2 +- travis_tests.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/GPy/testing/plotting_tests.py b/GPy/testing/plotting_tests.py index 23564ff3..90dceab0 100644 --- a/GPy/testing/plotting_tests.py +++ b/GPy/testing/plotting_tests.py @@ -38,7 +38,7 @@ from nose import SkipTest try: import matplotlib - matplotlib.use('agg', warn=False) + matplotlib.use('agg') except ImportError: # matplotlib not installed from nose import SkipTest diff --git a/travis_tests.py b/travis_tests.py index bd3f5680..16713962 100644 --- a/travis_tests.py +++ b/travis_tests.py @@ -31,7 +31,7 @@ #!/usr/bin/env python import matplotlib -matplotlib.use('agg', warn=False) +matplotlib.use('agg') import nose, warnings with warnings.catch_warnings(): From 426ba1dc279f7f3308fceed18c00ac361947cc50 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 16 Nov 2020 10:43:36 +0000 Subject: [PATCH 078/137] Update README.md --- README.md | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/README.md b/README.md index 545a1ae5..25a32658 100644 --- a/README.md +++ b/README.md @@ -51,11 +51,7 @@ For any further questions/suggestions head over to the issues section in GPy. ## Support and questions to the community -We have set up a mailing list for any questions you might have or problems you feel others have encountered: - -gpy-users@lists.shef.ac.uk - -Feel free to join the discussions on the issues section, too. +Ask questions using the issues section. ## Updated Structure From 98fef6d622aba8ef77ccbe1d5bb5689912424fe9 Mon Sep 17 00:00:00 2001 From: gehbiszumeis <16896724+gehbiszumeis@users.noreply.github.com> Date: Mon, 8 Mar 2021 13:52:22 +0100 Subject: [PATCH 079/137] new: Added to_dict() method to Ornstein-Uhlenbeck (OU) kernel --- GPy/kern/src/stationary.py | 18 +++++++++++++++++- GPy/testing/serialization_tests.py | 15 ++++++++------- 2 files changed, 25 insertions(+), 8 deletions(-) diff --git a/GPy/kern/src/stationary.py b/GPy/kern/src/stationary.py index 888320a0..527bb9bb 100644 --- a/GPy/kern/src/stationary.py +++ b/GPy/kern/src/stationary.py @@ -412,7 +412,6 @@ class Exponential(Stationary): # return (F, L, Qc, H, Pinf) - class OU(Stationary): """ OU kernel: @@ -426,6 +425,23 @@ class OU(Stationary): def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='OU'): super(OU, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) + def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + input_dict = super(OU, self)._save_to_input_dict() + input_dict["class"] = "GPy.kern.OU" + return input_dict + + @staticmethod + def _build_from_input_dict(kernel_class, input_dict): + useGPU = input_dict.pop('useGPU', None) + return OU(**input_dict) + def K_of_r(self, r): return self.variance * np.exp(-r) diff --git a/GPy/testing/serialization_tests.py b/GPy/testing/serialization_tests.py index d147d59c..93ec4b2d 100644 --- a/GPy/testing/serialization_tests.py +++ b/GPy/testing/serialization_tests.py @@ -26,14 +26,15 @@ class Test(unittest.TestCase): k7 = GPy.kern.Matern32(2, variance=1.0, lengthscale=[1.0,3.0], ARD=True, active_dims = [1,1]) k8 = GPy.kern.Matern52(2, variance=2.0, lengthscale=[2.0,1.0], ARD=True, active_dims = [1,0]) k9 = GPy.kern.ExpQuad(2, variance=3.0, lengthscale=[1.0,2.0], ARD=True, active_dims = [0,1]) - k10 = k1 + k1.copy() + k2 + k3 + k4 + k5 + k6 - k11 = k1 * k2 * k2.copy() * k3 * k4 * k5 - k12 = (k1 + k2) * (k3 + k4 + k5) - k13 = ((k1 + k2) * k3) + k4 + k5 * k7 - k14 = ((k1 + k2) * k3) + k4 * k5 + k8 - k15 = ((k1 * k2) * k3) + k4 * k5 + k8 + k9 + k10 = GPy.kern.OU(2, variance=2.0, lengthscale=[2.0, 1.0], ARD=True, active_dims=[1, 0]) + k11 = k1 + k1.copy() + k2 + k3 + k4 + k5 + k6 + k12 = k1 * k2 * k2.copy() * k3 * k4 * k5 + k13 = (k1 + k2) * (k3 + k4 + k5) + k14 = ((k1 + k2) * k3) + k4 + k5 * k7 + k15 = ((k1 + k2) * k3) + k4 * k5 + k8 * k10 + k16 = ((k1 * k2) * k3) + k4 * k5 + k8 + k9 - k_list = [k1,k2,k3,k4,k5,k6,k7,k8,k9,k10,k11,k12,k13,k14,k15] + k_list = [k1,k2,k3,k4,k5,k6,k7,k8,k9,k10,k11,k12,k13,k14,k15,k16] for kk in k_list: kk_dict = kk.to_dict() From b9067193253f45a76913c8a1dc2ea605482c974b Mon Sep 17 00:00:00 2001 From: gehbiszumeis <16896724+gehbiszumeis@users.noreply.github.com> Date: Mon, 8 Mar 2021 13:52:23 +0100 Subject: [PATCH 080/137] fix: minor typos in README !minor --- README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 25a32658..1e609cb6 100644 --- a/README.md +++ b/README.md @@ -29,15 +29,16 @@ We welcome any contributions to GPy, after all it is an open source project. We For an in depth description of pull requests, please visit https://help.github.com/articles/using-pull-requests/ . -### Steps to a successfull contribution: +### Steps to a successful contribution: 1. Fork GPy: https://help.github.com/articles/fork-a-repo/ 2. Make your changes to the source in your fork. 3. Make sure the [guidelines](#gl) are met. - 4. Set up tests to test your code. We are using unttests in the testing subfolder of GPy. There is a good chance that there is already a framework set up to test your new model in model_tests.py or kernel in kernel_tests.py. have a look at the source and you might be able to just add your model (or kernel or others) as an additional test in the appropriate file. There is more frameworks for testing the other bits and pieces, just head over to the testing folder and have a look. + 4. Set up tests to test your code. We are using unittests in the testing subfolder of GPy. There is a good chance + that there is already a framework set up to test your new model in model_tests.py or kernel in kernel_tests.py. have a look at the source and you might be able to just add your model (or kernel or others) as an additional test in the appropriate file. There is more frameworks for testing the other bits and pieces, just head over to the testing folder and have a look. 5. Create a pull request to the devel branch in GPy, see above. 6. The tests will be running on your pull request. In the comments section we will be able to discuss the changes and help you with any problems. Let us know if there are any in the comments, so we can help. - 7. The pull request gets accepted and your awsome new feature will be in the next GPy release :) + 7. The pull request gets accepted and your awesome new feature will be in the next GPy release :) For any further questions/suggestions head over to the issues section in GPy. From 9c69b8c6fe972d6dc7e7c86b828d6dadf96db4e3 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Sat, 6 Feb 2021 17:14:31 -0800 Subject: [PATCH 081/137] added python 3.9 build following 4aa2ea9f5e54c6bca93adc3b9ba2fe3d252475d9 to address https://github.com/SheffieldML/GPy/issues/881 --- .travis.yml | 1 + appveyor.yml | 2 ++ setup.py | 1 + 3 files changed, 4 insertions(+) diff --git a/.travis.yml b/.travis.yml index 36c3c74f..84936875 100644 --- a/.travis.yml +++ b/.travis.yml @@ -18,6 +18,7 @@ env: - PYTHON_VERSION=3.6 - PYTHON_VERSION=3.7 - PYTHON_VERSION=3.8 + - PYTHON_VERSION=3.9 before_install: - wget https://github.com/mzwiessele/travis_scripts/raw/master/download_miniconda.sh diff --git a/appveyor.yml b/appveyor.yml index 633184da..f5faee5c 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -13,6 +13,8 @@ environment: MINICONDA: C:\Miniconda36-x64 - PYTHON_VERSION: 3.8 MINICONDA: C:\Miniconda36-x64 + - PYTHON_VERSION: 3.9 + MINICONDA: C:\Miniconda36-x64 #configuration: # - Debug diff --git a/setup.py b/setup.py index 735078bc..73bfc035 100644 --- a/setup.py +++ b/setup.py @@ -191,6 +191,7 @@ setup(name = 'GPy', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', 'Framework :: IPython', 'Intended Audience :: Science/Research', 'Intended Audience :: Developers', From 434e1b0f5e1def4d02c34fa5965cbba1e1db06e8 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Sat, 6 Feb 2021 17:42:58 -0800 Subject: [PATCH 082/137] updated cython-generated c files for python 3.9 via `pyenv virtualenv 3.9.1 gpy391 && pyenv activate gpy391 && python setup.py build --force --- GPy/kern/src/coregionalize_cython.c | 2849 +++---------- GPy/kern/src/stationary_cython.c | 5923 +++++++++++--------------- GPy/models/state_space_cython.c | 3928 +++++++---------- GPy/util/choleskies_cython.c | 6115 +++++++++++---------------- GPy/util/linalg_cython.c | 3189 ++++---------- 5 files changed, 7772 insertions(+), 14232 deletions(-) diff --git a/GPy/kern/src/coregionalize_cython.c b/GPy/kern/src/coregionalize_cython.c index 4b46fadc..484fc6f9 100644 --- a/GPy/kern/src/coregionalize_cython.c +++ b/GPy/kern/src/coregionalize_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.29.2 */ +/* Generated by Cython 0.29.21 */ #define PY_SSIZE_T_CLEAN #include "Python.h" @@ -7,8 +7,8 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) #error Cython requires Python 2.6+ or Python 3.3+. #else -#define CYTHON_ABI "0_29_2" -#define CYTHON_HEX_VERSION 0x001D02F0 +#define CYTHON_ABI "0_29_21" +#define CYTHON_HEX_VERSION 0x001D15F0 #define CYTHON_FUTURE_DIVISION 0 #include #ifndef offsetof @@ -310,8 +310,13 @@ #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else #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) +#endif #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES @@ -346,26 +351,6 @@ #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif -#if CYTHON_USE_DICT_VERSIONS -#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ - (version_var) = __PYX_GET_DICT_VERSION(dict);\ - (cache_var) = (value); -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ - static PY_UINT64_T __pyx_dict_version = 0;\ - static PyObject *__pyx_dict_cached_value = NULL;\ - if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ - (VAR) = __pyx_dict_cached_value;\ - } else {\ - (VAR) = __pyx_dict_cached_value = (LOOKUP);\ - __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ - }\ - } -#else -#define __PYX_GET_DICT_VERSION(dict) (0) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); -#endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) @@ -398,7 +383,7 @@ typedef int Py_tss_t; static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { *key = PyThread_create_key(); - return 0; // PyThread_create_key reports success always + return 0; } static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); @@ -421,7 +406,7 @@ static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { return PyThread_get_key_value(*key); } -#endif // TSS (Thread Specific Storage) API +#endif #if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) #define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) #else @@ -450,7 +435,11 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 @@ -499,8 +488,10 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode #define PyObject_Unicode PyObject_Str #endif +#endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) @@ -511,6 +502,13 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif #if CYTHON_ASSUME_SAFE_MACROS #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) #else @@ -550,7 +548,7 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : (Py_INCREF(func), func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif @@ -591,11 +589,10 @@ static CYTHON_INLINE float __PYX_NAN() { #define __Pyx_truncl truncl #endif - +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } #define __PYX_ERR(f_index, lineno, Ln_error) \ -{ \ - __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ -} + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } #ifndef __PYX_EXTERN_C #ifdef __cplusplus @@ -611,7 +608,13 @@ static CYTHON_INLINE float __PYX_NAN() { #include #include #include "numpy/arrayobject.h" +#include "numpy/ndarrayobject.h" +#include "numpy/ndarraytypes.h" +#include "numpy/arrayscalars.h" #include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + #ifdef _OPENMP #include #endif /* _OPENMP */ @@ -624,7 +627,8 @@ typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* enc const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize @@ -894,7 +898,7 @@ typedef struct { #endif -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":776 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":690 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -903,7 +907,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":691 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -912,7 +916,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -921,7 +925,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":779 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":693 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -930,7 +934,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":697 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -939,7 +943,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":784 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":698 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -948,7 +952,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":785 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -957,7 +961,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":786 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":700 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -966,7 +970,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":704 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -975,7 +979,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":705 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -984,7 +988,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":800 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -993,7 +997,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":715 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1002,7 +1006,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":716 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1011,7 +1015,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":804 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":718 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1020,7 +1024,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":805 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":719 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1029,7 +1033,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":806 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":720 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1038,7 +1042,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":808 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":722 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1047,7 +1051,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":809 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":723 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1056,7 +1060,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":811 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":725 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1065,7 +1069,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":812 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":726 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1074,7 +1078,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":727 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1109,7 +1113,7 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do /*--- Type declarations ---*/ -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":729 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1118,7 +1122,7 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":730 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1127,7 +1131,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":817 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":731 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1136,7 +1140,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":819 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":733 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1258,6 +1262,32 @@ static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + /* GetModuleGlobalName.proto */ #if CYTHON_USE_DICT_VERSIONS #define __Pyx_GetModuleGlobalName(var, name) {\ @@ -1291,7 +1321,7 @@ static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObje #define __Pyx_PyFunction_FastCall(func, args, nargs)\ __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs); +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); #else #define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) #endif @@ -1369,29 +1399,6 @@ static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject #define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) #endif -/* RaiseException.proto */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); - -/* DictGetItem.proto */ -#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); -#define __Pyx_PyObject_Dict_GetItem(obj, name)\ - (likely(PyDict_CheckExact(obj)) ?\ - __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) -#else -#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) -#endif - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - /* GetTopmostException.proto */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); @@ -1424,6 +1431,9 @@ static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); #endif +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + /* TypeImport.proto */ #ifndef __PYX_HAVE_RT_ImportType_proto #define __PYX_HAVE_RT_ImportType_proto @@ -1588,9 +1598,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); #endif #endif -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); - /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); @@ -1648,8 +1655,17 @@ 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_generic = 0; +static PyTypeObject *__pyx_ptype_5numpy_number = 0; +static PyTypeObject *__pyx_ptype_5numpy_integer = 0; +static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; +static PyTypeObject *__pyx_ptype_5numpy_floating = 0; +static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; +static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; +static PyTypeObject *__pyx_ptype_5numpy_character = 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 'GPy.kern.src.coregionalize_cython' */ static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 }; @@ -1661,8 +1677,6 @@ int __pyx_module_is_main_GPy__kern__src__coregionalize_cython = 0; /* Implementation of 'GPy.kern.src.coregionalize_cython' */ static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_ValueError; -static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_ImportError; static const char __pyx_k_B[] = "B"; static const char __pyx_k_D[] = "D"; 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static const char __pyx_k_GPy_kern_src_coregionalize_cytho[] = "GPy/kern/src/coregionalize_cython.pyx"; -static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; -static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; -static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; static const char __pyx_k_GPy_kern_src_coregionalize_cytho_2[] = "GPy.kern.src.coregionalize_cython"; static PyObject *__pyx_n_s_B; static PyObject *__pyx_n_s_D; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_kp_s_GPy_kern_src_coregionalize_cytho; static PyObject *__pyx_n_s_GPy_kern_src_coregionalize_cytho_2; static PyObject *__pyx_n_s_ImportError; @@ -1718,9 +1722,6 @@ static PyObject *__pyx_n_s_K_asymmetric; 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Py_ssize_t __pyx_t_17; Py_ssize_t __pyx_t_18; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("K_symmetric", 0); __pyx_pybuffer_K.pybuffer.buf = NULL; __pyx_pybuffer_K.refcount = 0; @@ -2106,6 +2103,9 @@ static PyObject *__pyx_pw_3GPy_4kern_3src_20coregionalize_cython_3K_asymmetric(P PyArrayObject *__pyx_v_B = 0; PyArrayObject *__pyx_v_X = 0; PyArrayObject *__pyx_v_X2 = 0; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("K_asymmetric (wrapper)", 0); @@ -2213,6 +2213,9 @@ static PyObject *__pyx_pf_3GPy_4kern_3src_20coregionalize_cython_2K_asymmetric(C __pyx_t_5numpy_int64_t __pyx_t_16; Py_ssize_t __pyx_t_17; Py_ssize_t __pyx_t_18; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("K_asymmetric", 0); __pyx_pybuffer_K.pybuffer.buf = NULL; __pyx_pybuffer_K.refcount = 0; 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(void)__Pyx_modinit_function_export_code(); (void)__Pyx_modinit_type_init_code(); - if (unlikely(__Pyx_modinit_type_import_code() != 0)) goto __pyx_L1_error; + if (unlikely(__Pyx_modinit_type_import_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) (void)__Pyx_modinit_variable_import_code(); (void)__Pyx_modinit_function_import_code(); /*--- Execution code ---*/ @@ -5823,12 +4393,12 @@ if (!__Pyx_RefNanny) { if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1046 - * raise ImportError("numpy.core.umath failed to import") + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":1016 * - * cdef inline int import_ufunc() except -1: # <<<<<<<<<<<<<< - * try: - * _import_umath() + * + * cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: # <<<<<<<<<<<<<< + * """ + * returns the unit part of the dtype for a numpy datetime64 object. */ /*--- Wrapped vars code ---*/ @@ -5963,7 +4533,7 @@ static int __Pyx_ParseOptionalKeywords( } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 - if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { + if (likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { @@ -5990,7 +4560,7 @@ static int __Pyx_ParseOptionalKeywords( while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -6006,7 +4576,7 @@ static int __Pyx_ParseOptionalKeywords( while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -6110,7 +4680,7 @@ static int __Pyx_BufFmt_ParseNumber(const char** ts) { return -1; } else { count = *t++ - '0'; - while (*t >= '0' && *t < '9') { + while (*t >= '0' && *t <= '9') { count *= 10; count += *t++ - '0'; } @@ -6131,6 +4701,7 @@ static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { + case '?': return "'bool'"; case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; @@ -6173,7 +4744,7 @@ static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { - case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); @@ -6257,7 +4828,7 @@ static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; - case 'B': case 'H': case 'I': case 'L': case 'Q': + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); @@ -6401,9 +4972,7 @@ static PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; - int i = 0, number; - int ndim = ctx->head->field->type->ndim; -; + int i = 0, number, ndim; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, @@ -6411,6 +4980,7 @@ __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; @@ -6536,12 +5106,12 @@ static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const cha return NULL; } CYTHON_FALLTHROUGH; - case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': - if (ctx->enc_type == *ts && got_Z == ctx->is_complex && - ctx->enc_packmode == ctx->new_packmode) { + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; @@ -6610,7 +5180,7 @@ static int __Pyx__GetBufferAndValidate( __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } - if (unlikely((unsigned)buf->itemsize != dtype->size)) { + if (unlikely((size_t)buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", @@ -6624,6 +5194,32 @@ fail:; return -1; } +/* PyDictVersioning */ + #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + /* GetModuleGlobalName */ #if CYTHON_USE_DICT_VERSIONS static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) @@ -6713,7 +5309,7 @@ static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args return result; } #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) { +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); PyObject *globals = PyFunction_GET_GLOBALS(func); PyObject *argdefs = PyFunction_GET_DEFAULTS(func); @@ -6784,12 +5380,12 @@ static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, } #if PY_MAJOR_VERSION >= 3 result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, kwdefs, closure); #else result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, closure); #endif @@ -6947,6 +5543,161 @@ static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject } #endif +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + /* RaiseException */ #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, @@ -7106,203 +5857,6 @@ bad: } #endif -/* DictGetItem */ - #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()) { - if (unlikely(PyTuple_Check(key))) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) { - PyErr_SetObject(PyExc_KeyError, args); - Py_DECREF(args); - } - } else { - PyErr_SetObject(PyExc_KeyError, key); - } - } - return NULL; - } - Py_INCREF(value); - return value; -} -#endif - -/* RaiseTooManyValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* RaiseNoneIterError */ - static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* GetTopmostException */ - #if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - /* TypeImport */ #ifndef __PYX_HAVE_RT_ImportType #define __PYX_HAVE_RT_ImportType @@ -7394,7 +5948,7 @@ bad: { #if PY_MAJOR_VERSION >= 3 if (level == -1) { - if (strchr(__Pyx_MODULE_NAME, '.')) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); if (!module) { @@ -7431,7 +5985,7 @@ bad: /* CLineInTraceback */ #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { PyObject *use_cline; PyObject *ptype, *pvalue, *ptraceback; #if CYTHON_COMPILING_IN_CPYTHON @@ -7535,7 +6089,7 @@ static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } @@ -7639,7 +6193,6 @@ bad: #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } @@ -7651,7 +6204,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return; } if ((0)) {} - else if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); view->obj = NULL; Py_DECREF(obj); } @@ -7764,13 +6316,13 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { float r = b.imag / b.real; - float s = 1.0 / (b.real + b.imag * r); + float s = (float)(1.0) / (b.real + b.imag * r); return __pyx_t_float_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { float r = b.real / b.imag; - float s = 1.0 / (b.imag + b.real * r); + float s = (float)(1.0) / (b.imag + b.real * r); return __pyx_t_float_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -7828,7 +6380,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { case 1: return a; case 2: - z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(a, a); case 3: z = __Pyx_c_prod_float(a, a); @@ -7850,7 +6401,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { theta = 0; } else { r = -a.real; - theta = atan2f(0, -1); + theta = atan2f(0.0, -1.0); } } else { r = __Pyx_c_abs_float(a); @@ -7919,13 +6470,13 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { double r = b.imag / b.real; - double s = 1.0 / (b.real + b.imag * r); + double s = (double)(1.0) / (b.real + b.imag * r); return __pyx_t_double_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { double r = b.real / b.imag; - double s = 1.0 / (b.imag + b.real * r); + double s = (double)(1.0) / (b.imag + b.real * r); return __pyx_t_double_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -7983,7 +6534,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { case 1: return a; case 2: - z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(a, a); case 3: z = __Pyx_c_prod_double(a, a); @@ -8005,7 +6555,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { theta = 0; } else { r = -a.real; - theta = atan2(0, -1); + theta = atan2(0.0, -1.0); } } else { r = __Pyx_c_abs_double(a); @@ -8021,37 +6571,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif #endif -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { - const enum NPY_TYPES neg_one = (enum NPY_TYPES) ((enum NPY_TYPES) 0 - (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); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(enum NPY_TYPES) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - 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); - } -} - /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) ((int) 0 - (int) 1), const_zero = (int) 0; diff --git a/GPy/kern/src/stationary_cython.c b/GPy/kern/src/stationary_cython.c index 4a1bb32d..9ecdaf9d 100644 --- a/GPy/kern/src/stationary_cython.c +++ b/GPy/kern/src/stationary_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.29.2 */ +/* Generated by Cython 0.29.21 */ #define PY_SSIZE_T_CLEAN #include "Python.h" @@ -7,8 +7,8 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) #error Cython requires Python 2.6+ or Python 3.3+. #else -#define CYTHON_ABI "0_29_2" -#define CYTHON_HEX_VERSION 0x001D02F0 +#define CYTHON_ABI "0_29_21" +#define CYTHON_HEX_VERSION 0x001D15F0 #define CYTHON_FUTURE_DIVISION 0 #include #ifndef offsetof @@ -310,8 +310,13 @@ #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else #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) +#endif #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES @@ -346,26 +351,6 @@ #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif -#if CYTHON_USE_DICT_VERSIONS -#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ - (version_var) = __PYX_GET_DICT_VERSION(dict);\ - (cache_var) = (value); -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ - static PY_UINT64_T __pyx_dict_version = 0;\ - static PyObject *__pyx_dict_cached_value = NULL;\ - if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ - (VAR) = __pyx_dict_cached_value;\ - } else {\ - (VAR) = __pyx_dict_cached_value = (LOOKUP);\ - __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ - }\ - } -#else -#define __PYX_GET_DICT_VERSION(dict) (0) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); -#endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) @@ -398,7 +383,7 @@ typedef int Py_tss_t; static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { *key = PyThread_create_key(); - return 0; // PyThread_create_key reports success always + return 0; } static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); @@ -421,7 +406,7 @@ static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { return PyThread_get_key_value(*key); } -#endif // TSS (Thread Specific Storage) API +#endif #if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) #define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) #else @@ -450,7 +435,11 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 @@ -499,8 +488,10 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode #define PyObject_Unicode PyObject_Str #endif +#endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) @@ -511,6 +502,13 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif #if CYTHON_ASSUME_SAFE_MACROS #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) #else @@ -550,7 +548,7 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : (Py_INCREF(func), func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif @@ -591,11 +589,10 @@ static CYTHON_INLINE float __PYX_NAN() { #define __Pyx_truncl truncl #endif - +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } #define __PYX_ERR(f_index, lineno, Ln_error) \ -{ \ - __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ -} + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } #ifndef __PYX_EXTERN_C #ifdef __cplusplus @@ -611,7 +608,13 @@ static CYTHON_INLINE float __PYX_NAN() { #include #include #include "numpy/arrayobject.h" +#include "numpy/ndarrayobject.h" +#include "numpy/ndarraytypes.h" +#include "numpy/arrayscalars.h" #include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + #include "stationary_utils.h" #include "pythread.h" #include @@ -628,7 +631,8 @@ typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* enc const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize @@ -959,7 +963,7 @@ typedef volatile __pyx_atomic_int_type __pyx_atomic_int; #endif -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":776 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":690 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -968,7 +972,7 @@ typedef volatile __pyx_atomic_int_type __pyx_atomic_int; */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":691 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -977,7 +981,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -986,7 +990,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":779 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":693 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -995,7 +999,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":697 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -1004,7 +1008,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":784 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":698 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -1013,7 +1017,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":785 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -1022,7 +1026,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":786 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":700 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -1031,7 +1035,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":704 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -1040,7 +1044,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":705 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -1049,7 +1053,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":800 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -1058,7 +1062,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":715 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1067,7 +1071,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":716 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1076,7 +1080,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":804 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":718 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1085,7 +1089,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":805 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":719 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1094,7 +1098,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":806 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":720 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1103,7 +1107,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":808 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":722 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1112,7 +1116,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":809 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":723 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1121,7 +1125,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":811 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":725 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1130,7 +1134,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":812 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":726 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1139,7 +1143,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":727 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1187,7 +1191,7 @@ struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":729 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1196,7 +1200,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":730 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1205,7 +1209,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":817 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":731 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1214,7 +1218,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":819 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":733 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1284,7 +1288,7 @@ struct __pyx_memoryview_obj { }; -/* "View.MemoryView":961 +/* "View.MemoryView":965 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -1335,7 +1339,7 @@ struct __pyx_vtabstruct_memoryview { static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; -/* "View.MemoryView":961 +/* "View.MemoryView":965 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -1523,77 +1527,6 @@ 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); -/* PyObjectCall.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); -#else -#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) -#endif - -/* RaiseException.proto */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); - -/* PyCFunctionFastCall.proto */ -#if CYTHON_FAST_PYCCALL -static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); -#else -#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) -#endif - -/* PyFunctionFastCall.proto */ -#if CYTHON_FAST_PYCALL -#define __Pyx_PyFunction_FastCall(func, args, nargs)\ - __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) -#if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs); -#else -#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) -#endif -#define __Pyx_BUILD_ASSERT_EXPR(cond)\ - (sizeof(char [1 - 2*!(cond)]) - 1) -#ifndef Py_MEMBER_SIZE -#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) -#endif - static size_t __pyx_pyframe_localsplus_offset = 0; - #include "frameobject.h" - #define __Pxy_PyFrame_Initialize_Offsets()\ - ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ - (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) - #define __Pyx_PyFrame_GetLocalsplus(frame)\ - (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) -#endif - -/* PyObjectCallMethO.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); -#endif - -/* PyObjectCallOneArg.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); - -/* DictGetItem.proto */ -#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); -#define __Pyx_PyObject_Dict_GetItem(obj, name)\ - (likely(PyDict_CheckExact(obj)) ?\ - __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) -#else -#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) -#endif - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - -/* ExtTypeTest.proto */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); - /* GetTopmostException.proto */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); @@ -1626,9 +1559,57 @@ static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); #endif +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif + /* PyObjectCall2Args.proto */ static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + /* IncludeStringH.proto */ #include @@ -1709,6 +1690,32 @@ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( /* GetAttr3.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + /* GetModuleGlobalName.proto */ #if CYTHON_USE_DICT_VERSIONS #define __Pyx_GetModuleGlobalName(var, name) {\ @@ -1730,6 +1737,18 @@ static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_ve static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); #endif +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + /* SwapException.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) @@ -1763,7 +1782,7 @@ static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { if (likely(L->allocated > len)) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); - Py_SIZE(list) = len+1; + __Pyx_SET_SIZE(list, len + 1); return 0; } return PyList_Append(list, x); @@ -1774,9 +1793,9 @@ static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { /* PyIntBinop.proto */ #if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace); +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); #else -#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\ +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) #endif @@ -1801,7 +1820,7 @@ static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); - Py_SIZE(list) = len+1; + __Pyx_SET_SIZE(list, len + 1); return 0; } return PyList_Append(list, x); @@ -1816,11 +1835,6 @@ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); /* None.proto */ static CYTHON_INLINE long __Pyx_div_long(long, long); -/* WriteUnraisableException.proto */ -static void __Pyx_WriteUnraisable(const char *name, int clineno, - int lineno, const char *filename, - int full_traceback, int nogil); - /* ImportFrom.proto */ static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); @@ -1844,6 +1858,9 @@ static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_nam /* SetVTable.proto */ static int __Pyx_SetVtable(PyObject *dict, void *vtable); +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + /* SetupReduce.proto */ static int __Pyx_setup_reduce(PyObject* type_obj); @@ -2039,9 +2056,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); #endif #endif -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); - /* MemviewSliceCopyTemplate.proto */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, @@ -2104,8 +2118,17 @@ 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_generic = 0; +static PyTypeObject *__pyx_ptype_5numpy_number = 0; +static PyTypeObject *__pyx_ptype_5numpy_integer = 0; +static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; +static PyTypeObject *__pyx_ptype_5numpy_floating = 0; +static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; +static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; +static PyTypeObject *__pyx_ptype_5numpy_character = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; -static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ /* Module declarations from 'cython.view' */ @@ -2165,9 +2188,8 @@ int __pyx_module_is_main_GPy__kern__src__stationary_cython = 0; /* Implementation of 'GPy.kern.src.stationary_cython' */ static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_ValueError; -static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_TypeError; @@ -2246,7 +2268,6 @@ static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; static const char __pyx_k_ImportError[] = "ImportError"; static const char __pyx_k_MemoryError[] = "MemoryError"; static const char __pyx_k_PickleError[] = "PickleError"; -static const char __pyx_k_RuntimeError[] = "RuntimeError"; static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; static const char __pyx_k_stringsource[] = "stringsource"; static const char __pyx_k_grad_X_cython[] = "grad_X_cython"; @@ -2270,31 +2291,25 @@ static const char __pyx_k_contiguous_and_indirect[] = " static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; -static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static const char __pyx_k_GPy_kern_src_stationary_cython[] = "GPy.kern.src.stationary_cython"; static const char __pyx_k_strided_and_direct_or_indirect[] = ""; static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; -static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; -static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static const char __pyx_k_GPy_kern_src_stationary_cython_p[] = "GPy/kern/src/stationary_cython.pyx"; static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; -static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; -static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; -static const 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; @@ -2304,8 +2319,6 @@ static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_n_s_D; static PyObject *__pyx_n_s_Ellipsis; static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_n_s_GPy_kern_src_stationary_cython; static PyObject *__pyx_kp_s_GPy_kern_src_stationary_cython_p; static PyObject *__pyx_n_s_ImportError; @@ -2319,12 +2332,10 @@ static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_N; -static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; static PyObject *__pyx_n_b_O; static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_PickleError; static PyObject *__pyx_n_s_Q; -static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_ValueError; @@ -2373,8 +2384,6 @@ static PyObject *__pyx_n_s_n; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_name_2; static PyObject *__pyx_n_s_nd; -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_ndim; static PyObject *__pyx_n_s_new; static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; @@ -2415,15 +2424,12 @@ static PyObject *__pyx_n_s_tmp; static PyObject *__pyx_n_s_tmp_2; 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_update; static PyObject *__pyx_pf_3GPy_4kern_3src_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_3src_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_3src_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); 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} - /* "View.MemoryView":378 + /* "View.MemoryView":375 + * if self.obj is not None: + * __Pyx_ReleaseBuffer(&self.view) + * elif (<__pyx_buffer *> &self.view).obj == Py_None: # <<<<<<<<<<<<<< + * + * (<__pyx_buffer *> &self.view).obj = NULL + */ + __pyx_t_2 = ((((Py_buffer *)(&__pyx_v_self->view))->obj == Py_None) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":377 + * elif (<__pyx_buffer *> &self.view).obj == Py_None: + * + * (<__pyx_buffer *> &self.view).obj = NULL # <<<<<<<<<<<<<< + * Py_DECREF(Py_None) + * + */ + ((Py_buffer *)(&__pyx_v_self->view))->obj = NULL; + + /* "View.MemoryView":378 + * + * (<__pyx_buffer *> &self.view).obj = NULL + * Py_DECREF(Py_None) # <<<<<<<<<<<<<< + * + * cdef int i + */ + Py_DECREF(Py_None); + + /* "View.MemoryView":375 + * if self.obj is not None: + * __Pyx_ReleaseBuffer(&self.view) + * elif (<__pyx_buffer *> &self.view).obj == Py_None: # <<<<<<<<<<<<<< + * + * (<__pyx_buffer *> &self.view).obj = NULL + */ + } + __pyx_L3:; + + /* "View.MemoryView":382 * cdef int i * global __pyx_memoryview_thread_locks_used * if self.lock != NULL: # <<<<<<<<<<<<<< @@ -8903,7 +7602,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_2 = ((__pyx_v_self->lock != NULL) != 0); if (__pyx_t_2) { - /* "View.MemoryView":379 + /* "View.MemoryView":383 * global __pyx_memoryview_thread_locks_used * if self.lock != NULL: * for i in range(__pyx_memoryview_thread_locks_used): # <<<<<<<<<<<<<< @@ -8915,7 +7614,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":380 + /* "View.MemoryView":384 * if self.lock != NULL: * for i in range(__pyx_memoryview_thread_locks_used): * if __pyx_memoryview_thread_locks[i] is self.lock: # <<<<<<<<<<<<<< @@ -8925,7 +7624,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_2 = (((__pyx_memoryview_thread_locks[__pyx_v_i]) == __pyx_v_self->lock) != 0); if (__pyx_t_2) { - /* "View.MemoryView":381 + /* "View.MemoryView":385 * for i in range(__pyx_memoryview_thread_locks_used): * if __pyx_memoryview_thread_locks[i] is self.lock: * __pyx_memoryview_thread_locks_used -= 1 # <<<<<<<<<<<<<< @@ -8934,7 +7633,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal */ __pyx_memoryview_thread_locks_used = (__pyx_memoryview_thread_locks_used - 1); - /* "View.MemoryView":382 + /* "View.MemoryView":386 * if __pyx_memoryview_thread_locks[i] is self.lock: * __pyx_memoryview_thread_locks_used -= 1 * if i != __pyx_memoryview_thread_locks_used: # <<<<<<<<<<<<<< @@ -8944,7 +7643,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_2 = ((__pyx_v_i != __pyx_memoryview_thread_locks_used) != 0); if (__pyx_t_2) { - /* "View.MemoryView":384 + /* "View.MemoryView":388 * if i != __pyx_memoryview_thread_locks_used: * __pyx_memoryview_thread_locks[i], __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used] = ( * __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used], __pyx_memoryview_thread_locks[i]) # <<<<<<<<<<<<<< @@ -8954,7 +7653,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_6 = (__pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used]); __pyx_t_7 = (__pyx_memoryview_thread_locks[__pyx_v_i]); - /* "View.MemoryView":383 + /* "View.MemoryView":387 * __pyx_memoryview_thread_locks_used -= 1 * if i != __pyx_memoryview_thread_locks_used: * __pyx_memoryview_thread_locks[i], __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used] = ( # <<<<<<<<<<<<<< @@ -8964,7 +7663,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal (__pyx_memoryview_thread_locks[__pyx_v_i]) = __pyx_t_6; (__pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used]) = __pyx_t_7; - /* "View.MemoryView":382 + /* "View.MemoryView":386 * if __pyx_memoryview_thread_locks[i] is self.lock: * __pyx_memoryview_thread_locks_used -= 1 * if i != __pyx_memoryview_thread_locks_used: # <<<<<<<<<<<<<< @@ -8973,7 +7672,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal */ } - /* "View.MemoryView":385 + /* "View.MemoryView":389 * __pyx_memoryview_thread_locks[i], __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used] = ( * __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used], __pyx_memoryview_thread_locks[i]) * break # <<<<<<<<<<<<<< @@ -8982,7 +7681,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal */ goto __pyx_L6_break; - /* "View.MemoryView":380 + /* "View.MemoryView":384 * if self.lock != NULL: * for i in range(__pyx_memoryview_thread_locks_used): * if __pyx_memoryview_thread_locks[i] is self.lock: # <<<<<<<<<<<<<< @@ -8993,7 +7692,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal } /*else*/ { - /* "View.MemoryView":387 + /* "View.MemoryView":391 * break * else: * PyThread_free_lock(self.lock) # <<<<<<<<<<<<<< @@ -9004,7 +7703,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal } __pyx_L6_break:; 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__Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PyList_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 397, __pyx_L1_error) #else - __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 397, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); #endif } else { if (__pyx_t_3 >= PyTuple_GET_SIZE(__pyx_t_2)) break; #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - __pyx_t_5 = PyTuple_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PyTuple_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 397, __pyx_L1_error) #else - __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 397, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); #endif } @@ -9098,7 +7800,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py PyObject* exc_type = PyErr_Occurred(); if (exc_type) { if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) PyErr_Clear(); - else __PYX_ERR(2, 393, __pyx_L1_error) + else __PYX_ERR(2, 397, __pyx_L1_error) } break; } @@ -9109,18 +7811,18 @@ 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":394 + /* "View.MemoryView":398 * * 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_ERR(2, 394, __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 == ((char *)NULL))) __PYX_ERR(2, 394, __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_ERR(2, 398, __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 == ((char *)NULL))) __PYX_ERR(2, 398, __pyx_L1_error) __pyx_v_itemp = __pyx_t_7; - /* "View.MemoryView":393 + /* "View.MemoryView":397 * cdef char *itemp = self.view.buf * * for dim, idx in enumerate(index): # <<<<<<<<<<<<<< @@ -9130,7 +7832,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py } __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "View.MemoryView":396 + /* "View.MemoryView":400 * itemp = pybuffer_index(&self.view, itemp, idx, dim) * * return itemp # <<<<<<<<<<<<<< @@ -9140,7 +7842,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py __pyx_r = __pyx_v_itemp; goto __pyx_L0; - /* "View.MemoryView":389 + /* "View.MemoryView":393 * PyThread_free_lock(self.lock) * * cdef char *get_item_pointer(memoryview self, object index) except NULL: # <<<<<<<<<<<<<< @@ -9160,7 +7862,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py return __pyx_r; } -/* "View.MemoryView":399 +/* "View.MemoryView":403 * * * def __getitem__(memoryview self, object index): # <<<<<<<<<<<<<< @@ -9193,9 +7895,12 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ PyObject *__pyx_t_4 = NULL; PyObject *__pyx_t_5 = NULL; char *__pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__getitem__", 0); - /* "View.MemoryView":400 + /* "View.MemoryView":404 * * def __getitem__(memoryview self, object index): * if index is Ellipsis: # <<<<<<<<<<<<<< @@ -9206,7 +7911,7 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":401 + /* "View.MemoryView":405 * def __getitem__(memoryview self, object index): * if index is Ellipsis: * return self # <<<<<<<<<<<<<< @@ -9218,7 +7923,7 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ __pyx_r = ((PyObject *)__pyx_v_self); goto __pyx_L0; - /* "View.MemoryView":400 + /* "View.MemoryView":404 * * def __getitem__(memoryview self, object index): * if index is Ellipsis: # <<<<<<<<<<<<<< @@ -9227,14 +7932,14 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ */ } - /* "View.MemoryView":403 + /* "View.MemoryView":407 * return self * * have_slices, indices = _unellipsify(index, self.view.ndim) # <<<<<<<<<<<<<< * * cdef char *itemp */ - __pyx_t_3 = _unellipsify(__pyx_v_index, __pyx_v_self->view.ndim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 403, __pyx_L1_error) + __pyx_t_3 = _unellipsify(__pyx_v_index, __pyx_v_self->view.ndim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 407, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); if (likely(__pyx_t_3 != Py_None)) { PyObject* sequence = __pyx_t_3; @@ -9242,7 +7947,7 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ if (unlikely(size != 2)) { if (size > 2) __Pyx_RaiseTooManyValuesError(2); else if (size >= 0) __Pyx_RaiseNeedMoreValuesError(size); - __PYX_ERR(2, 403, __pyx_L1_error) + __PYX_ERR(2, 407, __pyx_L1_error) } #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS __pyx_t_4 = PyTuple_GET_ITEM(sequence, 0); @@ -9250,31 +7955,31 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ __Pyx_INCREF(__pyx_t_4); __Pyx_INCREF(__pyx_t_5); #else - __pyx_t_4 = PySequence_ITEM(sequence, 0); if (unlikely(!__pyx_t_4)) __PYX_ERR(2, 403, __pyx_L1_error) + __pyx_t_4 = PySequence_ITEM(sequence, 0); if (unlikely(!__pyx_t_4)) __PYX_ERR(2, 407, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); - __pyx_t_5 = PySequence_ITEM(sequence, 1); if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 403, __pyx_L1_error) + __pyx_t_5 = PySequence_ITEM(sequence, 1); 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__pyx_v_info->shape = __pyx_t_4; - /* "View.MemoryView":518 + /* "View.MemoryView":522 * raise ValueError("Cannot create writable memory view from read-only memoryview") * * if flags & PyBUF_ND: # <<<<<<<<<<<<<< @@ -10824,7 +9559,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu goto __pyx_L6; } - /* "View.MemoryView":521 + /* "View.MemoryView":525 * info.shape = self.view.shape * else: * info.shape = NULL # <<<<<<<<<<<<<< @@ -10836,7 +9571,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu } __pyx_L6:; - /* "View.MemoryView":523 + /* "View.MemoryView":527 * info.shape = NULL * * if flags & PyBUF_STRIDES: # <<<<<<<<<<<<<< @@ -10846,7 +9581,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_1 = ((__pyx_v_flags & PyBUF_STRIDES) != 0); if (__pyx_t_1) { - /* "View.MemoryView":524 + /* "View.MemoryView":528 * * if flags & PyBUF_STRIDES: * info.strides = self.view.strides # <<<<<<<<<<<<<< @@ -10856,7 +9591,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_4 = __pyx_v_self->view.strides; 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__pyx_t_9 = 0; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(2, 757, __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_ERR(2, 761, __pyx_L1_error) __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L9_bool_binop_done; @@ -13546,20 +12345,20 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_L9_bool_binop_done:; __pyx_v_stop = __pyx_t_10; - /* "View.MemoryView":758 + /* "View.MemoryView":762 * 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_ERR(2, 758, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 762, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_9); - __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) __PYX_ERR(2, 758, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) __PYX_ERR(2, 762, __pyx_L1_error) if (!__pyx_t_1) { __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(2, 758, __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_ERR(2, 762, __pyx_L1_error) __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L11_bool_binop_done; @@ -13568,55 +12367,55 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_L11_bool_binop_done:; __pyx_v_step = __pyx_t_10; - /* "View.MemoryView":760 + /* "View.MemoryView":764 * 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_ERR(2, 760, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 764, __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":761 + /* "View.MemoryView":765 * * 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_ERR(2, 761, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 765, __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":762 + /* "View.MemoryView":766 * 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_ERR(2, 762, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 766, __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":764 + /* "View.MemoryView":768 * 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 == ((int)-1))) __PYX_ERR(2, 764, __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 == ((int)-1))) __PYX_ERR(2, 768, __pyx_L1_error) - /* "View.MemoryView":770 + /* "View.MemoryView":774 * have_start, have_stop, have_step, * True) * new_ndim += 1 # <<<<<<<<<<<<<< @@ -13627,7 +12426,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __pyx_L6:; - /* "View.MemoryView":742 + /* "View.MemoryView":746 * cdef bint have_start, have_stop, have_step * * for dim, index in enumerate(indices): # <<<<<<<<<<<<<< @@ -13637,7 +12436,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":772 + /* "View.MemoryView":776 * new_ndim += 1 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -13648,7 +12447,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":773 + /* "View.MemoryView":777 * * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< @@ -13657,39 +12456,39 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":774 + /* "View.MemoryView":778 * 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_ERR(2, 774, __pyx_L1_error) } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); __PYX_ERR(2, 778, __pyx_L1_error) } - /* "View.MemoryView":775 + /* "View.MemoryView":779 * 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_ERR(2, 775, __pyx_L1_error) } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); __PYX_ERR(2, 779, __pyx_L1_error) } - /* "View.MemoryView":773 + /* "View.MemoryView":777 * * 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_ERR(2, 773, __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_ERR(2, 777, __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_ERR(2, 773, __pyx_L1_error) + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(2, 777, __pyx_L1_error) __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; - /* "View.MemoryView":772 + /* "View.MemoryView":776 * new_ndim += 1 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -13698,7 +12497,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ } - /* "View.MemoryView":778 + /* "View.MemoryView":782 * memview.dtype_is_object) * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< @@ -13708,30 +12507,30 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ /*else*/ { __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":779 + /* "View.MemoryView":783 * 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_ERR(2, 778, __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_ERR(2, 782, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); - /* "View.MemoryView":778 + /* "View.MemoryView":782 * 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_ERR(2, 778, __pyx_L1_error) + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(2, 782, __pyx_L1_error) __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; } - /* "View.MemoryView":706 + /* "View.MemoryView":710 * * @cname('__pyx_memview_slice') * cdef memoryview memview_slice(memoryview memview, object indices): # <<<<<<<<<<<<<< @@ -13753,7 +12552,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ return __pyx_r; } -/* "View.MemoryView":803 +/* "View.MemoryView":807 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -13768,8 +12567,11 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; - /* "View.MemoryView":823 + /* "View.MemoryView":827 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< @@ -13779,7 +12581,7 @@ 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":825 + /* "View.MemoryView":829 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< @@ -13789,7 +12591,7 @@ 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":826 + /* "View.MemoryView":830 * * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -13798,7 +12600,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - /* "View.MemoryView":825 + /* "View.MemoryView":829 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< @@ -13807,7 +12609,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":827 + /* "View.MemoryView":831 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< @@ -13821,16 +12623,16 @@ 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":828 + /* "View.MemoryView":832 * 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, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 828, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 832, __pyx_L1_error) - /* "View.MemoryView":827 + /* "View.MemoryView":831 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< @@ -13839,7 +12641,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":823 + /* "View.MemoryView":827 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< @@ -13849,7 +12651,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L3; } - /* "View.MemoryView":831 + /* "View.MemoryView":835 * else: * * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< @@ -13868,7 +12670,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_L6_bool_binop_done:; __pyx_v_negative_step = __pyx_t_2; - /* "View.MemoryView":833 + /* "View.MemoryView":837 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< @@ -13886,16 +12688,16 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_L9_bool_binop_done:; if (__pyx_t_2) { - /* "View.MemoryView":834 + /* "View.MemoryView":838 * * 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, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 834, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 838, __pyx_L1_error) - /* "View.MemoryView":833 + /* "View.MemoryView":837 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< @@ -13904,7 +12706,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":837 + /* "View.MemoryView":841 * * * if have_start: # <<<<<<<<<<<<<< @@ -13914,7 +12716,7 @@ 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":838 + /* "View.MemoryView":842 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< @@ -13924,7 +12726,7 @@ 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":839 + /* "View.MemoryView":843 * if have_start: * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -13933,7 +12735,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - /* "View.MemoryView":840 + /* "View.MemoryView":844 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< @@ -13943,7 +12745,7 @@ 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":841 + /* "View.MemoryView":845 * start += shape * if start < 0: * start = 0 # <<<<<<<<<<<<<< @@ -13952,7 +12754,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = 0; - /* "View.MemoryView":840 + /* "View.MemoryView":844 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< @@ -13961,7 +12763,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":838 + /* "View.MemoryView":842 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< @@ -13971,7 +12773,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L12; } - /* "View.MemoryView":842 + /* "View.MemoryView":846 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< @@ -13981,7 +12783,7 @@ 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":843 + /* "View.MemoryView":847 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< @@ -13991,7 +12793,7 @@ 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":844 + /* "View.MemoryView":848 * elif start >= shape: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -14000,7 +12802,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_shape - 1); - /* "View.MemoryView":843 + /* "View.MemoryView":847 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< @@ -14010,7 +12812,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L14; } - /* "View.MemoryView":846 + /* "View.MemoryView":850 * start = shape - 1 * else: * start = shape # <<<<<<<<<<<<<< @@ -14022,7 +12824,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L14:; - /* "View.MemoryView":842 + /* "View.MemoryView":846 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< @@ -14032,7 +12834,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L12:; - /* "View.MemoryView":837 + /* "View.MemoryView":841 * * * if have_start: # <<<<<<<<<<<<<< @@ -14042,7 +12844,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L11; } - /* "View.MemoryView":848 + /* "View.MemoryView":852 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -14053,7 +12855,7 @@ 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":849 + /* "View.MemoryView":853 * else: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -14062,7 +12864,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_shape - 1); - /* "View.MemoryView":848 + /* "View.MemoryView":852 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -14072,7 +12874,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L15; } - /* "View.MemoryView":851 + /* "View.MemoryView":855 * start = shape - 1 * else: * start = 0 # <<<<<<<<<<<<<< @@ -14086,7 +12888,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L11:; - /* "View.MemoryView":853 + /* "View.MemoryView":857 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< @@ -14096,7 +12898,7 @@ 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":854 + /* "View.MemoryView":858 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< @@ -14106,7 +12908,7 @@ 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":855 + /* "View.MemoryView":859 * if have_stop: * if stop < 0: * stop += shape # <<<<<<<<<<<<<< @@ -14115,7 +12917,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); - /* "View.MemoryView":856 + /* "View.MemoryView":860 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< @@ -14125,7 +12927,7 @@ 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":857 + /* "View.MemoryView":861 * stop += shape * if stop < 0: * stop = 0 # <<<<<<<<<<<<<< @@ -14134,7 +12936,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = 0; - /* "View.MemoryView":856 + /* "View.MemoryView":860 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< @@ -14143,7 +12945,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":854 + /* "View.MemoryView":858 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< @@ -14153,7 +12955,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L17; } - /* "View.MemoryView":858 + /* "View.MemoryView":862 * if stop < 0: * stop = 0 * elif stop > shape: # <<<<<<<<<<<<<< @@ -14163,7 +12965,7 @@ 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":859 + /* "View.MemoryView":863 * stop = 0 * elif stop > shape: * stop = shape # <<<<<<<<<<<<<< @@ -14172,7 +12974,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = __pyx_v_shape; - /* "View.MemoryView":858 + /* "View.MemoryView":862 * if stop < 0: * stop = 0 * elif stop > shape: # <<<<<<<<<<<<<< @@ -14182,7 +12984,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L17:; - /* "View.MemoryView":853 + /* "View.MemoryView":857 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< @@ -14192,7 +12994,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L16; } - /* "View.MemoryView":861 + /* "View.MemoryView":865 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -14203,7 +13005,7 @@ 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":862 + /* "View.MemoryView":866 * else: * if negative_step: * stop = -1 # <<<<<<<<<<<<<< @@ -14212,7 +13014,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = -1L; - /* "View.MemoryView":861 + /* "View.MemoryView":865 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -14222,7 +13024,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L19; } - /* "View.MemoryView":864 + /* "View.MemoryView":868 * stop = -1 * else: * stop = shape # <<<<<<<<<<<<<< @@ -14236,7 +13038,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L16:; - /* "View.MemoryView":866 + /* "View.MemoryView":870 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< @@ -14246,7 +13048,7 @@ 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":867 + /* "View.MemoryView":871 * * if not have_step: * step = 1 # <<<<<<<<<<<<<< @@ -14255,7 +13057,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_step = 1; - /* "View.MemoryView":866 + /* "View.MemoryView":870 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< @@ -14264,7 +13066,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":871 + /* "View.MemoryView":875 * * with cython.cdivision(True): * new_shape = (stop - start) // step # <<<<<<<<<<<<<< @@ -14273,7 +13075,7 @@ 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":873 + /* "View.MemoryView":877 * new_shape = (stop - start) // step * * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< @@ -14283,7 +13085,7 @@ 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":874 + /* "View.MemoryView":878 * * if (stop - start) - step * new_shape: * new_shape += 1 # <<<<<<<<<<<<<< @@ -14292,7 +13094,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_new_shape = (__pyx_v_new_shape + 1); - /* "View.MemoryView":873 + /* "View.MemoryView":877 * new_shape = (stop - start) // step * * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< @@ -14301,7 +13103,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":876 + /* "View.MemoryView":880 * new_shape += 1 * * if new_shape < 0: # <<<<<<<<<<<<<< @@ -14311,7 +13113,7 @@ 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":877 + /* "View.MemoryView":881 * * if new_shape < 0: * new_shape = 0 # <<<<<<<<<<<<<< @@ -14320,7 +13122,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_new_shape = 0; - /* "View.MemoryView":876 + /* "View.MemoryView":880 * new_shape += 1 * * if new_shape < 0: # <<<<<<<<<<<<<< @@ -14329,7 +13131,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":880 + /* "View.MemoryView":884 * * * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< @@ -14338,7 +13140,7 @@ 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":881 + /* "View.MemoryView":885 * * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< @@ -14347,7 +13149,7 @@ 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":882 + /* "View.MemoryView":886 * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< @@ -14358,7 +13160,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L3:; - /* "View.MemoryView":885 + /* "View.MemoryView":889 * * * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< @@ -14368,7 +13170,7 @@ 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":886 + /* "View.MemoryView":890 * * if suboffset_dim[0] < 0: * dst.data += start * stride # <<<<<<<<<<<<<< @@ -14377,7 +13179,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride)); - /* "View.MemoryView":885 + /* "View.MemoryView":889 * * * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< @@ -14387,7 +13189,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L23; } - /* "View.MemoryView":888 + /* "View.MemoryView":892 * dst.data += start * stride * else: * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< @@ -14400,7 +13202,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L23:; - /* "View.MemoryView":890 + /* "View.MemoryView":894 * dst.suboffsets[suboffset_dim[0]] += start * stride * * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -14410,7 +13212,7 @@ 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":891 + /* "View.MemoryView":895 * * if suboffset >= 0: * if not is_slice: # <<<<<<<<<<<<<< @@ -14420,7 +13222,7 @@ 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":892 + /* "View.MemoryView":896 * if suboffset >= 0: * if not is_slice: * if new_ndim == 0: # <<<<<<<<<<<<<< @@ -14430,7 +13232,7 @@ 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":893 + /* "View.MemoryView":897 * if not is_slice: * if new_ndim == 0: * dst.data = ( dst.data)[0] + suboffset # <<<<<<<<<<<<<< @@ -14439,7 +13241,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset); - /* "View.MemoryView":892 + /* "View.MemoryView":896 * if suboffset >= 0: * if not is_slice: * if new_ndim == 0: # <<<<<<<<<<<<<< @@ -14449,7 +13251,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L26; } - /* "View.MemoryView":895 + /* "View.MemoryView":899 * dst.data = ( dst.data)[0] + suboffset * else: * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<< @@ -14458,18 +13260,18 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ /*else*/ { - /* "View.MemoryView":896 + /* "View.MemoryView":900 * 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, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 895, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 899, __pyx_L1_error) } __pyx_L26:; - /* "View.MemoryView":891 + /* "View.MemoryView":895 * * if suboffset >= 0: * if not is_slice: # <<<<<<<<<<<<<< @@ -14479,7 +13281,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L25; } - /* "View.MemoryView":898 + /* "View.MemoryView":902 * "must be indexed and not sliced", dim) * else: * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< @@ -14491,7 +13293,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L25:; - /* "View.MemoryView":890 + /* "View.MemoryView":894 * dst.suboffsets[suboffset_dim[0]] += start * stride * * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -14500,7 +13302,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":900 + /* "View.MemoryView":904 * suboffset_dim[0] = new_ndim * * return 0 # <<<<<<<<<<<<<< @@ -14510,7 +13312,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":803 + /* "View.MemoryView":807 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -14534,7 +13336,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, return __pyx_r; } -/* "View.MemoryView":906 +/* "View.MemoryView":910 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -14554,9 +13356,12 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P int __pyx_t_2; PyObject *__pyx_t_3 = NULL; PyObject *__pyx_t_4 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("pybuffer_index", 0); - /* "View.MemoryView":908 + /* "View.MemoryView":912 * 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 # <<<<<<<<<<<<<< @@ -14565,7 +13370,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_suboffset = -1L; 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if (unlikely(__pyx_t_2)) { - /* "View.MemoryView":924 + /* "View.MemoryView":928 * 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_ERR(2, 924, __pyx_L1_error) + __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 928, __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_ERR(2, 924, __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_ERR(2, 928, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_builtin_IndexError, __pyx_t_4); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 924, __pyx_L1_error) + __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_builtin_IndexError, __pyx_t_4); 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if (__pyx_t_2) { - /* "View.MemoryView":931 + /* "View.MemoryView":935 * resultp = bufp + index * stride * if suboffset >= 0: * resultp = ( resultp)[0] + suboffset # <<<<<<<<<<<<<< @@ -14802,7 +13607,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_resultp = ((((char **)__pyx_v_resultp)[0]) + __pyx_v_suboffset); - /* "View.MemoryView":930 + /* "View.MemoryView":934 * * resultp = bufp + index * stride * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -14811,7 +13616,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ } - /* "View.MemoryView":933 + /* "View.MemoryView":937 * resultp = ( resultp)[0] + suboffset * * return resultp # <<<<<<<<<<<<<< @@ -14821,7 +13626,7 @@ 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":906 + /* "View.MemoryView":910 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -14840,7 +13645,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P return __pyx_r; 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(__pyx_v_strides[__pyx_v_j]) = __pyx_t_6; - /* "View.MemoryView":950 + /* "View.MemoryView":954 * j = ndim - 1 - i * strides[i], strides[j] = strides[j], strides[i] * shape[i], shape[j] = shape[j], shape[i] # <<<<<<<<<<<<<< @@ -14940,7 +13748,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { (__pyx_v_shape[__pyx_v_i]) = __pyx_t_6; (__pyx_v_shape[__pyx_v_j]) = __pyx_t_5; - /* "View.MemoryView":952 + /* "View.MemoryView":956 * shape[i], shape[j] = shape[j], shape[i] * * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: # <<<<<<<<<<<<<< @@ -14958,16 +13766,16 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { __pyx_L6_bool_binop_done:; if (__pyx_t_7) { - /* "View.MemoryView":953 + /* "View.MemoryView":957 * * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: * _err(ValueError, "Cannot transpose memoryview with indirect dimensions") # <<<<<<<<<<<<<< * * return 1 */ - __pyx_t_9 = __pyx_memoryview_err(__pyx_builtin_ValueError, ((char *)"Cannot transpose memoryview with indirect dimensions")); 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if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 985, __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_ERR(2, 989, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; } __pyx_L3:; - /* "View.MemoryView":981 + /* "View.MemoryView":985 * return memoryview.convert_item_to_object(self, itemp) * * cdef assign_item_from_object(self, char *itemp, object value): # <<<<<<<<<<<<<< @@ -15218,7 +14032,7 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo return __pyx_r; } -/* "View.MemoryView":988 +/* "View.MemoryView":992 * * @property * def base(self): # <<<<<<<<<<<<<< @@ -15244,7 +14058,7 @@ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__ __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__get__", 0); - /* "View.MemoryView":989 + /* "View.MemoryView":993 * @property * def base(self): * return self.from_object # <<<<<<<<<<<<<< @@ -15256,7 +14070,7 @@ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__ __pyx_r = __pyx_v_self->from_object; 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@@ -15378,7 +14198,7 @@ static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUS return __pyx_r; } -/* "View.MemoryView":995 +/* "View.MemoryView":999 * * @cname('__pyx_memoryview_fromslice') * cdef memoryview_fromslice(__Pyx_memviewslice memviewslice, # <<<<<<<<<<<<<< @@ -15401,9 +14221,12 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl Py_ssize_t *__pyx_t_7; Py_ssize_t *__pyx_t_8; Py_ssize_t __pyx_t_9; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_fromslice", 0); - /* "View.MemoryView":1003 + /* "View.MemoryView":1007 * cdef _memoryviewslice result * * if memviewslice.memview == Py_None: # <<<<<<<<<<<<<< @@ -15413,7 +14236,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_1 = ((((PyObject *)__pyx_v_memviewslice.memview) == Py_None) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1004 + /* "View.MemoryView":1008 * * if memviewslice.memview == Py_None: * return None # <<<<<<<<<<<<<< @@ -15424,7 +14247,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_r = Py_None; 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if (__pyx_t_1) { - /* "View.MemoryView":1024 + /* "View.MemoryView":1028 * * if (memviewslice.memview).flags & PyBUF_WRITABLE: * result.flags = PyBUF_RECORDS # <<<<<<<<<<<<<< @@ -15567,7 +14390,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.flags = PyBUF_RECORDS; - /* "View.MemoryView":1023 + /* "View.MemoryView":1027 * Py_INCREF(Py_None) * * if (memviewslice.memview).flags & PyBUF_WRITABLE: # <<<<<<<<<<<<<< @@ -15577,7 +14400,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl goto __pyx_L4; } - /* "View.MemoryView":1026 + /* "View.MemoryView":1030 * result.flags = PyBUF_RECORDS * else: * result.flags = PyBUF_RECORDS_RO # <<<<<<<<<<<<<< @@ -15589,7 +14412,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl } __pyx_L4:; - /* "View.MemoryView":1028 + /* "View.MemoryView":1032 * result.flags = PyBUF_RECORDS_RO * * result.view.shape = result.from_slice.shape # <<<<<<<<<<<<<< @@ -15598,7 +14421,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.shape = ((Py_ssize_t *)__pyx_v_result->from_slice.shape); - /* "View.MemoryView":1029 + /* "View.MemoryView":1033 * * result.view.shape = result.from_slice.shape * result.view.strides = result.from_slice.strides # <<<<<<<<<<<<<< @@ -15607,7 +14430,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.strides = ((Py_ssize_t *)__pyx_v_result->from_slice.strides); - /* "View.MemoryView":1032 + /* "View.MemoryView":1036 * * * result.view.suboffsets = NULL # <<<<<<<<<<<<<< @@ -15616,7 +14439,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.suboffsets = NULL; - /* "View.MemoryView":1033 + /* "View.MemoryView":1037 * * result.view.suboffsets = NULL * for suboffset in result.from_slice.suboffsets[:ndim]: # <<<<<<<<<<<<<< @@ -15628,7 +14451,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_6 = __pyx_t_8; __pyx_v_suboffset = (__pyx_t_6[0]); - /* "View.MemoryView":1034 + /* "View.MemoryView":1038 * result.view.suboffsets = NULL * for suboffset in result.from_slice.suboffsets[:ndim]: * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -15638,7 +14461,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_1 = ((__pyx_v_suboffset >= 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1035 + /* "View.MemoryView":1039 * for suboffset in result.from_slice.suboffsets[:ndim]: * if suboffset >= 0: * result.view.suboffsets = result.from_slice.suboffsets # <<<<<<<<<<<<<< @@ -15647,7 +14470,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.suboffsets = ((Py_ssize_t *)__pyx_v_result->from_slice.suboffsets); - /* "View.MemoryView":1036 + /* "View.MemoryView":1040 * if suboffset >= 0: * result.view.suboffsets = result.from_slice.suboffsets * break # <<<<<<<<<<<<<< @@ -15656,7 +14479,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ goto __pyx_L6_break; - /* "View.MemoryView":1034 + /* "View.MemoryView":1038 * result.view.suboffsets = NULL * for suboffset in result.from_slice.suboffsets[:ndim]: * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -15667,7 +14490,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl } __pyx_L6_break:; - /* "View.MemoryView":1038 + /* "View.MemoryView":1042 * break * * result.view.len = result.view.itemsize # <<<<<<<<<<<<<< @@ -15677,7 +14500,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_9 = __pyx_v_result->__pyx_base.view.itemsize; __pyx_v_result->__pyx_base.view.len = __pyx_t_9; - /* "View.MemoryView":1039 + /* "View.MemoryView":1043 * * result.view.len = result.view.itemsize * for length in result.view.shape[:ndim]: # <<<<<<<<<<<<<< @@ -15687,29 +14510,29 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_7 = (__pyx_v_result->__pyx_base.view.shape + __pyx_v_ndim); for (__pyx_t_8 = __pyx_v_result->__pyx_base.view.shape; __pyx_t_8 < __pyx_t_7; __pyx_t_8++) { __pyx_t_6 = __pyx_t_8; - __pyx_t_2 = PyInt_FromSsize_t((__pyx_t_6[0])); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1039, __pyx_L1_error) + __pyx_t_2 = PyInt_FromSsize_t((__pyx_t_6[0])); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1043, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_XDECREF_SET(__pyx_v_length, __pyx_t_2); __pyx_t_2 = 0; - /* "View.MemoryView":1040 + /* "View.MemoryView":1044 * result.view.len = result.view.itemsize * for length in result.view.shape[:ndim]: * result.view.len *= length # <<<<<<<<<<<<<< * * result.to_object_func = to_object_func */ - __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_result->__pyx_base.view.len); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1040, __pyx_L1_error) + __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_result->__pyx_base.view.len); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1044, __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_ERR(2, 1040, __pyx_L1_error) + __pyx_t_3 = PyNumber_InPlaceMultiply(__pyx_t_2, __pyx_v_length); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 1044, __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_ERR(2, 1040, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyIndex_AsSsize_t(__pyx_t_3); if (unlikely((__pyx_t_9 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(2, 1044, __pyx_L1_error) __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __pyx_v_result->__pyx_base.view.len = __pyx_t_9; } - /* "View.MemoryView":1042 + /* "View.MemoryView":1046 * result.view.len *= length * * result.to_object_func = to_object_func # <<<<<<<<<<<<<< @@ -15718,7 +14541,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_object_func = __pyx_v_to_object_func; - /* "View.MemoryView":1043 + /* "View.MemoryView":1047 * * result.to_object_func = to_object_func * result.to_dtype_func = to_dtype_func # <<<<<<<<<<<<<< @@ -15727,7 +14550,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_dtype_func = __pyx_v_to_dtype_func; - /* "View.MemoryView":1045 + /* "View.MemoryView":1049 * result.to_dtype_func = to_dtype_func * * return result # <<<<<<<<<<<<<< @@ -15739,7 +14562,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_r = ((PyObject *)__pyx_v_result); goto __pyx_L0; - /* "View.MemoryView":995 + /* "View.MemoryView":999 * * @cname('__pyx_memoryview_fromslice') * cdef memoryview_fromslice(__Pyx_memviewslice memviewslice, # <<<<<<<<<<<<<< @@ -15761,11 +14584,11 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl return __pyx_r; } -/* "View.MemoryView":1048 +/* "View.MemoryView":1052 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *mslice): + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj */ @@ -15776,10 +14599,13 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p int __pyx_t_1; int __pyx_t_2; PyObject *__pyx_t_3 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("get_slice_from_memview", 0); - /* "View.MemoryView":1051 - * __Pyx_memviewslice *mslice): + /* "View.MemoryView":1055 + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * obj = memview @@ -15789,20 +14615,20 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1052 + /* "View.MemoryView":1056 * 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_ERR(2, 1052, __pyx_L1_error) + if (!(likely(((((PyObject *)__pyx_v_memview)) == Py_None) || likely(__Pyx_TypeTest(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type))))) __PYX_ERR(2, 1056, __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":1053 + /* "View.MemoryView":1057 * if isinstance(memview, _memoryviewslice): * obj = memview * return &obj.from_slice # <<<<<<<<<<<<<< @@ -15812,8 +14638,8 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p __pyx_r = (&__pyx_v_obj->from_slice); goto __pyx_L0; - /* "View.MemoryView":1051 - * __Pyx_memviewslice *mslice): + /* "View.MemoryView":1055 + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * obj = memview @@ -15821,7 +14647,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p */ } - /* "View.MemoryView":1055 + /* "View.MemoryView":1059 * return &obj.from_slice * else: * slice_copy(memview, mslice) # <<<<<<<<<<<<<< @@ -15831,7 +14657,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p /*else*/ { __pyx_memoryview_slice_copy(__pyx_v_memview, __pyx_v_mslice); - /* "View.MemoryView":1056 + /* "View.MemoryView":1060 * else: * slice_copy(memview, mslice) * return mslice # <<<<<<<<<<<<<< @@ -15842,26 +14668,26 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p goto __pyx_L0; } - /* "View.MemoryView":1048 + /* "View.MemoryView":1052 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *mslice): + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj */ /* 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, 1, 0); - __pyx_r = 0; + __Pyx_AddTraceback("View.MemoryView.get_slice_from_memview", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = NULL; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_obj); __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "View.MemoryView":1059 +/* "View.MemoryView":1063 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -15882,7 +14708,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem Py_ssize_t __pyx_t_5; __Pyx_RefNannySetupContext("slice_copy", 0); - /* "View.MemoryView":1063 + /* "View.MemoryView":1067 * cdef (Py_ssize_t*) shape, strides, suboffsets * * shape = memview.view.shape # <<<<<<<<<<<<<< @@ -15892,7 +14718,7 @@ 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":1064 + /* "View.MemoryView":1068 * * shape = memview.view.shape * strides = memview.view.strides # <<<<<<<<<<<<<< @@ -15902,7 +14728,7 @@ 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":1065 + /* "View.MemoryView":1069 * shape = memview.view.shape * strides = memview.view.strides * suboffsets = memview.view.suboffsets # <<<<<<<<<<<<<< @@ -15912,7 +14738,7 @@ 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":1067 + /* "View.MemoryView":1071 * suboffsets = memview.view.suboffsets * * dst.memview = <__pyx_memoryview *> memview # <<<<<<<<<<<<<< @@ -15921,7 +14747,7 @@ 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":1068 + /* "View.MemoryView":1072 * * dst.memview = <__pyx_memoryview *> memview * dst.data = memview.view.buf # <<<<<<<<<<<<<< @@ -15930,7 +14756,7 @@ 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":1070 + /* "View.MemoryView":1074 * dst.data = memview.view.buf * * for dim in range(memview.view.ndim): # <<<<<<<<<<<<<< @@ -15942,7 +14768,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_dim = __pyx_t_4; - /* "View.MemoryView":1071 + /* "View.MemoryView":1075 * * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] # <<<<<<<<<<<<<< @@ -15951,7 +14777,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ (__pyx_v_dst->shape[__pyx_v_dim]) = (__pyx_v_shape[__pyx_v_dim]); - /* "View.MemoryView":1072 + /* "View.MemoryView":1076 * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] # <<<<<<<<<<<<<< @@ -15960,7 +14786,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ (__pyx_v_dst->strides[__pyx_v_dim]) = (__pyx_v_strides[__pyx_v_dim]); - /* "View.MemoryView":1073 + /* "View.MemoryView":1077 * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 # <<<<<<<<<<<<<< @@ -15975,7 +14801,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem (__pyx_v_dst->suboffsets[__pyx_v_dim]) = __pyx_t_5; } - /* "View.MemoryView":1059 + /* "View.MemoryView":1063 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -15987,7 +14813,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1076 +/* "View.MemoryView":1080 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -16000,9 +14826,12 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy", 0); - /* "View.MemoryView":1079 + /* "View.MemoryView":1083 * "Create a new memoryview object" * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -16011,7 +14840,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx */ __pyx_memoryview_slice_copy(__pyx_v_memview, (&__pyx_v_memviewslice)); - /* "View.MemoryView":1080 + /* "View.MemoryView":1084 * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) * return memoryview_copy_from_slice(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -16019,13 +14848,13 @@ 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_ERR(2, 1080, __pyx_L1_error) + __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 1084, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; - /* "View.MemoryView":1076 + /* "View.MemoryView":1080 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -16044,7 +14873,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx return __pyx_r; } -/* "View.MemoryView":1083 +/* "View.MemoryView":1087 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -16062,9 +14891,12 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview PyObject *(*__pyx_t_3)(char *); int (*__pyx_t_4)(char *, PyObject *); PyObject *__pyx_t_5 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy_from_slice", 0); - /* "View.MemoryView":1090 + /* "View.MemoryView":1094 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -16075,7 +14907,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1091 + /* "View.MemoryView":1095 * * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func # <<<<<<<<<<<<<< @@ -16085,7 +14917,7 @@ 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":1092 + /* "View.MemoryView":1096 * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func # <<<<<<<<<<<<<< @@ -16095,7 +14927,7 @@ 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":1090 + /* "View.MemoryView":1094 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -16105,7 +14937,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview goto __pyx_L3; } - /* "View.MemoryView":1094 + /* "View.MemoryView":1098 * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func * else: * to_object_func = NULL # <<<<<<<<<<<<<< @@ -16115,7 +14947,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview /*else*/ { __pyx_v_to_object_func = NULL; - /* "View.MemoryView":1095 + /* "View.MemoryView":1099 * else: * to_object_func = NULL * to_dtype_func = NULL # <<<<<<<<<<<<<< @@ -16126,7 +14958,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview } __pyx_L3:; - /* "View.MemoryView":1097 + /* "View.MemoryView":1101 * to_dtype_func = NULL * * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< @@ -16135,20 +14967,20 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview */ __Pyx_XDECREF(__pyx_r); - /* "View.MemoryView":1099 + /* "View.MemoryView":1103 * 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_ERR(2, 1097, __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_ERR(2, 1101, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); __pyx_r = __pyx_t_5; __pyx_t_5 = 0; goto __pyx_L0; - /* "View.MemoryView":1083 + /* "View.MemoryView":1087 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -16167,7 +14999,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview return __pyx_r; } -/* "View.MemoryView":1105 +/* "View.MemoryView":1109 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -16179,7 +15011,7 @@ 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":1106 + /* "View.MemoryView":1110 * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: # <<<<<<<<<<<<<< @@ -16189,7 +15021,7 @@ 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":1107 + /* "View.MemoryView":1111 * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: * return -arg # <<<<<<<<<<<<<< @@ -16199,7 +15031,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { __pyx_r = (-__pyx_v_arg); goto __pyx_L0; - /* "View.MemoryView":1106 + /* "View.MemoryView":1110 * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: # <<<<<<<<<<<<<< @@ -16208,7 +15040,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { */ } - /* "View.MemoryView":1109 + /* "View.MemoryView":1113 * return -arg * else: * return arg # <<<<<<<<<<<<<< @@ -16220,7 +15052,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { goto __pyx_L0; } - /* "View.MemoryView":1105 + /* "View.MemoryView":1109 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -16233,7 +15065,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { return __pyx_r; } -/* "View.MemoryView":1112 +/* "View.MemoryView":1116 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -16251,7 +15083,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ int __pyx_t_3; int __pyx_t_4; - /* "View.MemoryView":1117 + /* "View.MemoryView":1121 * """ * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< @@ -16260,7 +15092,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_c_stride = 0; - /* "View.MemoryView":1118 + /* "View.MemoryView":1122 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< @@ -16269,7 +15101,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_f_stride = 0; - /* "View.MemoryView":1120 + /* "View.MemoryView":1124 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -16279,7 +15111,7 @@ 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":1121 + /* "View.MemoryView":1125 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -16289,7 +15121,7 @@ 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":1122 + /* "View.MemoryView":1126 * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -16298,7 +15130,7 @@ 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":1123 + /* "View.MemoryView":1127 * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -16307,7 +15139,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ goto __pyx_L4_break; - /* "View.MemoryView":1121 + /* "View.MemoryView":1125 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -16318,7 +15150,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } __pyx_L4_break:; - /* "View.MemoryView":1125 + /* "View.MemoryView":1129 * break * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -16330,7 +15162,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1126 + /* "View.MemoryView":1130 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -16340,7 +15172,7 @@ 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":1127 + /* "View.MemoryView":1131 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -16349,7 +15181,7 @@ 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":1128 + /* "View.MemoryView":1132 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -16358,7 +15190,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ goto __pyx_L7_break; - /* "View.MemoryView":1126 + /* "View.MemoryView":1130 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -16369,7 +15201,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } __pyx_L7_break:; - /* "View.MemoryView":1130 + /* "View.MemoryView":1134 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< @@ -16379,7 +15211,7 @@ 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":1131 + /* "View.MemoryView":1135 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< @@ -16389,7 +15221,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_r = 'C'; goto __pyx_L0; - /* "View.MemoryView":1130 + /* "View.MemoryView":1134 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< @@ -16398,7 +15230,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ } - /* "View.MemoryView":1133 + /* "View.MemoryView":1137 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< @@ -16410,7 +15242,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ goto __pyx_L0; } - /* "View.MemoryView":1112 + /* "View.MemoryView":1116 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -16423,7 +15255,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ return __pyx_r; } -/* "View.MemoryView":1136 +/* "View.MemoryView":1140 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -16444,7 +15276,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v Py_ssize_t __pyx_t_5; Py_ssize_t __pyx_t_6; - /* "View.MemoryView":1143 + /* "View.MemoryView":1147 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< @@ -16453,7 +15285,7 @@ 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":1144 + /* "View.MemoryView":1148 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< @@ -16462,7 +15294,7 @@ 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":1145 + /* "View.MemoryView":1149 * 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] # <<<<<<<<<<<<<< @@ -16471,7 +15303,7 @@ 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":1146 + /* "View.MemoryView":1150 * 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] # <<<<<<<<<<<<<< @@ -16480,7 +15312,7 @@ 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":1148 + /* "View.MemoryView":1152 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -16490,7 +15322,7 @@ 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":1149 + /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -16510,7 +15342,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v goto __pyx_L5_bool_binop_done; } - /* "View.MemoryView":1150 + /* "View.MemoryView":1154 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< @@ -16525,7 +15357,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; - /* "View.MemoryView":1149 + /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -16534,7 +15366,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ if (__pyx_t_1) { - /* "View.MemoryView":1151 + /* "View.MemoryView":1155 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< @@ -16543,7 +15375,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); - /* "View.MemoryView":1149 + /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -16553,7 +15385,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v goto __pyx_L4; } - /* "View.MemoryView":1153 + /* "View.MemoryView":1157 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< @@ -16566,7 +15398,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1154 + /* "View.MemoryView":1158 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< @@ -16575,7 +15407,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); - /* "View.MemoryView":1155 + /* "View.MemoryView":1159 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -16584,7 +15416,7 @@ 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":1156 + /* "View.MemoryView":1160 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -16596,7 +15428,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } __pyx_L4:; - /* "View.MemoryView":1148 + /* "View.MemoryView":1152 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -16606,7 +15438,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v goto __pyx_L3; } - /* "View.MemoryView":1158 + /* "View.MemoryView":1162 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< @@ -16619,7 +15451,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1159 + /* "View.MemoryView":1163 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< @@ -16628,7 +15460,7 @@ 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":1163 + /* "View.MemoryView":1167 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -16637,7 +15469,7 @@ 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":1164 + /* "View.MemoryView":1168 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -16649,7 +15481,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } __pyx_L3:; - /* "View.MemoryView":1136 + /* "View.MemoryView":1140 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -16660,7 +15492,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v /* function exit code */ } -/* "View.MemoryView":1166 +/* "View.MemoryView":1170 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -16670,7 +15502,7 @@ 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":1169 + /* "View.MemoryView":1173 * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< @@ -16679,7 +15511,7 @@ 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":1166 + /* "View.MemoryView":1170 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -16690,57 +15522,57 @@ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memvi /* function exit code */ } -/* "View.MemoryView":1173 +/* "View.MemoryView":1177 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" - * cdef int i + * cdef Py_ssize_t shape, size = src.memview.view.itemsize */ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { - int __pyx_v_i; + Py_ssize_t __pyx_v_shape; Py_ssize_t __pyx_v_size; Py_ssize_t __pyx_r; Py_ssize_t __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - int __pyx_t_4; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; - /* "View.MemoryView":1176 + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: * "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 # <<<<<<<<<<<<<< + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< * - * for i in range(ndim): + * for shape in src.shape[:ndim]: */ __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_size = __pyx_t_1; - /* "View.MemoryView":1178 - * cdef Py_ssize_t size = src.memview.view.itemsize + /* "View.MemoryView":1181 + * cdef Py_ssize_t shape, size = src.memview.view.itemsize * - * for i in range(ndim): # <<<<<<<<<<<<<< - * size *= src.shape[i] + * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< + * size *= shape * */ - __pyx_t_2 = __pyx_v_ndim; - __pyx_t_3 = __pyx_t_2; - for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_i = __pyx_t_4; + __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); + for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { + __pyx_t_2 = __pyx_t_4; + __pyx_v_shape = (__pyx_t_2[0]); - /* "View.MemoryView":1179 + /* "View.MemoryView":1182 * - * for i in range(ndim): - * size *= src.shape[i] # <<<<<<<<<<<<<< + * for shape in src.shape[:ndim]: + * size *= shape # <<<<<<<<<<<<<< * * return size */ - __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); + __pyx_v_size = (__pyx_v_size * __pyx_v_shape); } - /* "View.MemoryView":1181 - * size *= src.shape[i] + /* "View.MemoryView":1184 + * size *= shape * * return size # <<<<<<<<<<<<<< * @@ -16749,12 +15581,12 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_r = __pyx_v_size; goto __pyx_L0; - /* "View.MemoryView":1173 + /* "View.MemoryView":1177 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" - * cdef int i + * cdef Py_ssize_t shape, size = src.memview.view.itemsize */ /* function exit code */ @@ -16762,7 +15594,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr return __pyx_r; } -/* "View.MemoryView":1184 +/* "View.MemoryView":1187 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -16778,7 +15610,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ int __pyx_t_3; int __pyx_t_4; - /* "View.MemoryView":1193 + /* "View.MemoryView":1196 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< @@ -16788,38 +15620,38 @@ 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":1194 + /* "View.MemoryView":1197 * * if order == 'F': * for idx in range(ndim): # <<<<<<<<<<<<<< * strides[idx] = stride - * stride = stride * shape[idx] + * stride *= shape[idx] */ __pyx_t_2 = __pyx_v_ndim; __pyx_t_3 = __pyx_t_2; for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_idx = __pyx_t_4; - /* "View.MemoryView":1195 + /* "View.MemoryView":1198 * if order == 'F': * for idx in range(ndim): * strides[idx] = stride # <<<<<<<<<<<<<< - * stride = stride * shape[idx] + * stride *= shape[idx] * else: */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1196 + /* "View.MemoryView":1199 * for idx in range(ndim): * strides[idx] = stride - * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * stride *= shape[idx] # <<<<<<<<<<<<<< * else: * for idx in range(ndim - 1, -1, -1): */ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); } - /* "View.MemoryView":1193 + /* "View.MemoryView":1196 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< @@ -16829,30 +15661,30 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ goto __pyx_L3; } - /* "View.MemoryView":1198 - * stride = stride * shape[idx] + /* "View.MemoryView":1201 + * stride *= shape[idx] * else: * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * strides[idx] = stride - * stride = stride * shape[idx] + * 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":1199 + /* "View.MemoryView":1202 * else: * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride # <<<<<<<<<<<<<< - * stride = stride * shape[idx] + * stride *= shape[idx] * */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1200 + /* "View.MemoryView":1203 * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride - * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * stride *= shape[idx] # <<<<<<<<<<<<<< * * return stride */ @@ -16861,8 +15693,8 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ } __pyx_L3:; - /* "View.MemoryView":1202 - * stride = stride * shape[idx] + /* "View.MemoryView":1205 + * stride *= shape[idx] * * return stride # <<<<<<<<<<<<<< * @@ -16871,7 +15703,7 @@ 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":1184 + /* "View.MemoryView":1187 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -16884,7 +15716,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ return __pyx_r; } -/* "View.MemoryView":1205 +/* "View.MemoryView":1208 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -16904,8 +15736,11 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, struct __pyx_memoryview_obj *__pyx_t_4; int __pyx_t_5; int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; - /* "View.MemoryView":1216 + /* "View.MemoryView":1219 * cdef void *result * * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -16915,7 +15750,7 @@ 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":1217 + /* "View.MemoryView":1220 * * cdef size_t itemsize = src.memview.view.itemsize * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< @@ -16924,7 +15759,7 @@ 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":1219 + /* "View.MemoryView":1222 * cdef size_t size = slice_get_size(src, ndim) * * result = malloc(size) # <<<<<<<<<<<<<< @@ -16933,7 +15768,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_result = malloc(__pyx_v_size); - /* "View.MemoryView":1220 + /* "View.MemoryView":1223 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< @@ -16943,16 +15778,16 @@ 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":1221 + /* "View.MemoryView":1224 * result = malloc(size) * if not result: * _err(MemoryError, NULL) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 1221, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 1224, __pyx_L1_error) - /* "View.MemoryView":1220 + /* "View.MemoryView":1223 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< @@ -16961,7 +15796,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ } - /* "View.MemoryView":1224 + /* "View.MemoryView":1227 * * * tmpslice.data = result # <<<<<<<<<<<<<< @@ -16970,7 +15805,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_tmpslice->data = ((char *)__pyx_v_result); - /* "View.MemoryView":1225 + /* "View.MemoryView":1228 * * tmpslice.data = result * tmpslice.memview = src.memview # <<<<<<<<<<<<<< @@ -16980,7 +15815,7 @@ 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":1226 + /* "View.MemoryView":1229 * tmpslice.data = result * tmpslice.memview = src.memview * for i in range(ndim): # <<<<<<<<<<<<<< @@ -16992,7 +15827,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1227 + /* "View.MemoryView":1230 * tmpslice.memview = src.memview * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< @@ -17001,7 +15836,7 @@ 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":1228 + /* "View.MemoryView":1231 * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< @@ -17011,7 +15846,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1L; } - /* "View.MemoryView":1230 + /* "View.MemoryView":1233 * tmpslice.suboffsets[i] = -1 * * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # <<<<<<<<<<<<<< @@ -17020,7 +15855,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (void)(__pyx_fill_contig_strides_array((&(__pyx_v_tmpslice->shape[0])), (&(__pyx_v_tmpslice->strides[0])), __pyx_v_itemsize, __pyx_v_ndim, __pyx_v_order)); - /* "View.MemoryView":1234 + /* "View.MemoryView":1237 * * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -17032,7 +15867,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1235 + /* "View.MemoryView":1238 * * for i in range(ndim): * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< @@ -17042,7 +15877,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_2 = (((__pyx_v_tmpslice->shape[__pyx_v_i]) == 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1236 + /* "View.MemoryView":1239 * for i in range(ndim): * if tmpslice.shape[i] == 1: * tmpslice.strides[i] = 0 # <<<<<<<<<<<<<< @@ -17051,7 +15886,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (__pyx_v_tmpslice->strides[__pyx_v_i]) = 0; - /* "View.MemoryView":1235 + /* "View.MemoryView":1238 * * for i in range(ndim): * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< @@ -17061,7 +15896,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, } } - /* "View.MemoryView":1238 + /* "View.MemoryView":1241 * tmpslice.strides[i] = 0 * * if slice_is_contig(src[0], order, ndim): # <<<<<<<<<<<<<< @@ -17071,7 +15906,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_2 = (__pyx_memviewslice_is_contig((__pyx_v_src[0]), __pyx_v_order, __pyx_v_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1239 + /* "View.MemoryView":1242 * * if slice_is_contig(src[0], order, ndim): * memcpy(result, src.data, size) # <<<<<<<<<<<<<< @@ -17080,7 +15915,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (void)(memcpy(__pyx_v_result, __pyx_v_src->data, __pyx_v_size)); - /* "View.MemoryView":1238 + /* "View.MemoryView":1241 * tmpslice.strides[i] = 0 * * if slice_is_contig(src[0], order, ndim): # <<<<<<<<<<<<<< @@ -17090,7 +15925,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, goto __pyx_L9; } - /* "View.MemoryView":1241 + /* "View.MemoryView":1244 * memcpy(result, src.data, size) * else: * copy_strided_to_strided(src, tmpslice, ndim, itemsize) # <<<<<<<<<<<<<< @@ -17102,7 +15937,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, } __pyx_L9:; - /* "View.MemoryView":1243 + /* "View.MemoryView":1246 * copy_strided_to_strided(src, tmpslice, ndim, itemsize) * * return result # <<<<<<<<<<<<<< @@ -17112,7 +15947,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_r = __pyx_v_result; goto __pyx_L0; - /* "View.MemoryView":1205 + /* "View.MemoryView":1208 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -17136,7 +15971,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, return __pyx_r; } -/* "View.MemoryView":1248 +/* "View.MemoryView":1251 * * @cname('__pyx_memoryview_err_extents') * cdef int _err_extents(int i, Py_ssize_t extent1, # <<<<<<<<<<<<<< @@ -17151,25 +15986,28 @@ static int __pyx_memoryview_err_extents(int __pyx_v_i, Py_ssize_t __pyx_v_extent PyObject *__pyx_t_2 = NULL; PyObject *__pyx_t_3 = NULL; PyObject *__pyx_t_4 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif __Pyx_RefNannySetupContext("_err_extents", 0); - /* "View.MemoryView":1251 + /* "View.MemoryView":1254 * Py_ssize_t extent2) except -1 with gil: * raise ValueError("got differing extents in dimension %d (got %d and %d)" % * (i, extent1, extent2)) # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_err_dim') */ - __pyx_t_1 = __Pyx_PyInt_From_int(__pyx_v_i); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 1251, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyInt_From_int(__pyx_v_i); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 1254, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); 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- /* "View.MemoryView":1286 + /* "View.MemoryView":1289 * broadcast_leading(&dst, dst_ndim, src_ndim) * * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< @@ -17556,7 +16403,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_v_ndim = __pyx_t_5; - /* "View.MemoryView":1288 + /* "View.MemoryView":1291 * cdef int ndim = max(src_ndim, dst_ndim) * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -17568,7 +16415,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1289 + /* "View.MemoryView":1292 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< @@ -17578,7 +16425,7 @@ 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":1290 + /* "View.MemoryView":1293 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< @@ -17588,7 +16435,7 @@ 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":1291 + /* "View.MemoryView":1294 * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: * broadcasting = True # <<<<<<<<<<<<<< @@ -17597,7 +16444,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_broadcasting = 1; - /* "View.MemoryView":1292 + /* "View.MemoryView":1295 * if src.shape[i] == 1: * broadcasting = True * src.strides[i] = 0 # <<<<<<<<<<<<<< @@ -17606,7 +16453,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ (__pyx_v_src.strides[__pyx_v_i]) = 0; - /* "View.MemoryView":1290 + /* "View.MemoryView":1293 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< @@ -17616,7 +16463,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ goto __pyx_L7; } - /* "View.MemoryView":1294 + /* "View.MemoryView":1297 * src.strides[i] = 0 * else: * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< @@ -17624,11 +16471,11 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * if src.suboffsets[i] >= 0: */ /*else*/ { - __pyx_t_6 = __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_6 == ((int)-1))) __PYX_ERR(2, 1294, __pyx_L1_error) + __pyx_t_6 = __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_6 == ((int)-1))) __PYX_ERR(2, 1297, __pyx_L1_error) } __pyx_L7:; - /* "View.MemoryView":1289 + /* "View.MemoryView":1292 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< @@ -17637,7 +16484,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1296 + /* "View.MemoryView":1299 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< @@ -17647,16 +16494,16 @@ 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":1297 + /* "View.MemoryView":1300 * * if src.suboffsets[i] >= 0: * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< * * if slices_overlap(&src, &dst, ndim, itemsize): */ - __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(2, 1297, __pyx_L1_error) + __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(2, 1300, __pyx_L1_error) - /* "View.MemoryView":1296 + /* "View.MemoryView":1299 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< @@ -17666,7 +16513,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } } - /* "View.MemoryView":1299 + /* "View.MemoryView":1302 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< @@ -17676,7 +16523,7 @@ 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":1301 + /* "View.MemoryView":1304 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< @@ -17686,7 +16533,7 @@ 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":1302 + /* "View.MemoryView":1305 * * if not slice_is_contig(src, order, ndim): * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< @@ -17695,7 +16542,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); - /* "View.MemoryView":1301 + /* "View.MemoryView":1304 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< @@ -17704,17 +16551,17 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1304 + /* "View.MemoryView":1307 * order = get_best_order(&dst, ndim) * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< * src = tmp * */ - __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(2, 1304, __pyx_L1_error) + __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(2, 1307, __pyx_L1_error) __pyx_v_tmpdata = __pyx_t_7; - /* "View.MemoryView":1305 + /* "View.MemoryView":1308 * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) * src = tmp # <<<<<<<<<<<<<< @@ -17723,7 +16570,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_src = __pyx_v_tmp; - /* "View.MemoryView":1299 + /* "View.MemoryView":1302 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< @@ -17732,7 +16579,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1307 + /* "View.MemoryView":1310 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< @@ -17742,7 +16589,7 @@ 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":1310 + /* "View.MemoryView":1313 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< @@ -17752,7 +16599,7 @@ 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":1311 + /* "View.MemoryView":1314 * * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< @@ -17761,7 +16608,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); - /* "View.MemoryView":1310 + /* "View.MemoryView":1313 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< @@ -17771,7 +16618,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ goto __pyx_L12; } - /* "View.MemoryView":1312 + /* "View.MemoryView":1315 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< @@ -17781,7 +16628,7 @@ 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":1313 + /* "View.MemoryView":1316 * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< @@ -17790,7 +16637,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); - /* "View.MemoryView":1312 + /* "View.MemoryView":1315 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< @@ -17800,7 +16647,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L12:; - /* "View.MemoryView":1315 + /* "View.MemoryView":1318 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< @@ -17810,7 +16657,7 @@ 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":1317 + /* "View.MemoryView":1320 * if direct_copy: * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -17819,7 +16666,7 @@ 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":1318 + /* "View.MemoryView":1321 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< @@ -17828,7 +16675,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); - /* "View.MemoryView":1319 + /* "View.MemoryView":1322 * 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) # <<<<<<<<<<<<<< @@ -17837,7 +16684,7 @@ 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":1320 + /* "View.MemoryView":1323 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< @@ -17846,7 +16693,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1321 + /* "View.MemoryView":1324 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -17856,7 +16703,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":1315 + /* "View.MemoryView":1318 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< @@ -17865,7 +16712,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1307 + /* "View.MemoryView":1310 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< @@ -17874,7 +16721,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1323 + /* "View.MemoryView":1326 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< @@ -17888,25 +16735,25 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_8 = (__pyx_t_2 != 0); if (__pyx_t_8) { - /* "View.MemoryView":1326 + /* "View.MemoryView":1329 * * * transpose_memslice(&src) # <<<<<<<<<<<<<< * transpose_memslice(&dst) * */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(2, 1326, __pyx_L1_error) + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(2, 1329, __pyx_L1_error) - /* "View.MemoryView":1327 + /* "View.MemoryView":1330 * * 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 == ((int)0))) __PYX_ERR(2, 1327, __pyx_L1_error) + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(2, 1330, __pyx_L1_error) - /* "View.MemoryView":1323 + /* "View.MemoryView":1326 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< @@ -17915,7 +16762,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1329 + /* "View.MemoryView":1332 * transpose_memslice(&dst) * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -17924,7 +16771,7 @@ 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":1330 + /* "View.MemoryView":1333 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< @@ -17933,7 +16780,7 @@ 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":1331 + /* "View.MemoryView":1334 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -17942,7 +16789,7 @@ 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":1333 + /* "View.MemoryView":1336 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< @@ -17951,7 +16798,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1334 + /* "View.MemoryView":1337 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -17961,7 +16808,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":1265 + /* "View.MemoryView":1268 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< @@ -17985,7 +16832,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ return __pyx_r; } -/* "View.MemoryView":1337 +/* "View.MemoryView":1340 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< @@ -18000,7 +16847,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1341 + /* "View.MemoryView":1344 * int ndim_other) nogil: * cdef int i * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< @@ -18009,7 +16856,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); - /* "View.MemoryView":1343 + /* "View.MemoryView":1346 * cdef int offset = ndim_other - ndim * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -18019,7 +16866,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":1344 + /* "View.MemoryView":1347 * * for i in range(ndim - 1, -1, -1): * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< @@ -18028,7 +16875,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); - /* "View.MemoryView":1345 + /* "View.MemoryView":1348 * for i in range(ndim - 1, -1, -1): * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< @@ -18037,7 +16884,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1346 + /* "View.MemoryView":1349 * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< @@ -18047,7 +16894,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); } - /* "View.MemoryView":1348 + /* "View.MemoryView":1351 * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * * for i in range(offset): # <<<<<<<<<<<<<< @@ -18059,7 +16906,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1349 + /* "View.MemoryView":1352 * * for i in range(offset): * mslice.shape[i] = 1 # <<<<<<<<<<<<<< @@ -18068,7 +16915,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->shape[__pyx_v_i]) = 1; - /* "View.MemoryView":1350 + /* "View.MemoryView":1353 * for i in range(offset): * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< @@ -18077,7 +16924,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); - /* "View.MemoryView":1351 + /* "View.MemoryView":1354 * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< @@ -18087,7 +16934,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L; } - /* "View.MemoryView":1337 + /* "View.MemoryView":1340 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< @@ -18098,7 +16945,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic /* function exit code */ } -/* "View.MemoryView":1359 +/* "View.MemoryView":1362 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -18109,7 +16956,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic 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":1363 + /* "View.MemoryView":1366 * * * if dtype_is_object: # <<<<<<<<<<<<<< @@ -18119,7 +16966,7 @@ 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":1364 + /* "View.MemoryView":1367 * * if dtype_is_object: * refcount_objects_in_slice_with_gil(dst.data, dst.shape, # <<<<<<<<<<<<<< @@ -18128,7 +16975,7 @@ 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); - /* "View.MemoryView":1363 + /* "View.MemoryView":1366 * * * if dtype_is_object: # <<<<<<<<<<<<<< @@ -18137,7 +16984,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i */ } - /* "View.MemoryView":1359 + /* "View.MemoryView":1362 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -18148,7 +16995,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i /* function exit code */ } -/* "View.MemoryView":1368 +/* "View.MemoryView":1371 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -18163,7 +17010,7 @@ 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":1371 + /* "View.MemoryView":1374 * Py_ssize_t *strides, int ndim, * bint inc) with gil: * refcount_objects_in_slice(data, shape, strides, ndim, inc) # <<<<<<<<<<<<<< @@ -18172,7 +17019,7 @@ 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":1368 + /* "View.MemoryView":1371 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -18187,7 +17034,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da #endif } -/* "View.MemoryView":1374 +/* "View.MemoryView":1377 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -18204,7 +17051,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss int __pyx_t_4; __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0); - /* "View.MemoryView":1378 + /* "View.MemoryView":1381 * cdef Py_ssize_t i * * for i in range(shape[0]): # <<<<<<<<<<<<<< @@ -18216,7 +17063,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1379 + /* "View.MemoryView":1382 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< @@ -18226,7 +17073,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_4 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_4) { - /* "View.MemoryView":1380 + /* "View.MemoryView":1383 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< @@ -18236,7 +17083,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_4 = (__pyx_v_inc != 0); if (__pyx_t_4) { - /* "View.MemoryView":1381 + /* "View.MemoryView":1384 * if ndim == 1: * if inc: * Py_INCREF(( data)[0]) # <<<<<<<<<<<<<< @@ -18245,7 +17092,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss */ Py_INCREF((((PyObject **)__pyx_v_data)[0])); - /* "View.MemoryView":1380 + /* "View.MemoryView":1383 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< @@ -18255,7 +17102,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss goto __pyx_L6; } - /* "View.MemoryView":1383 + /* "View.MemoryView":1386 * Py_INCREF(( data)[0]) * else: * Py_DECREF(( data)[0]) # <<<<<<<<<<<<<< @@ -18267,7 +17114,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } __pyx_L6:; - /* "View.MemoryView":1379 + /* "View.MemoryView":1382 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< @@ -18277,7 +17124,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss goto __pyx_L5; } - /* "View.MemoryView":1385 + /* "View.MemoryView":1388 * Py_DECREF(( data)[0]) * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -18286,7 +17133,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss */ /*else*/ { - /* "View.MemoryView":1386 + /* "View.MemoryView":1389 * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, * ndim - 1, inc) # <<<<<<<<<<<<<< @@ -18297,7 +17144,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } __pyx_L5:; - /* "View.MemoryView":1388 + /* "View.MemoryView":1391 * ndim - 1, inc) * * data += strides[0] # <<<<<<<<<<<<<< @@ -18307,7 +17154,7 @@ 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":1374 + /* "View.MemoryView":1377 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -18319,7 +17166,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1394 +/* "View.MemoryView":1397 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -18329,7 +17176,7 @@ 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":1397 + /* "View.MemoryView":1400 * size_t itemsize, void *item, * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -18338,7 +17185,7 @@ 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":1398 + /* "View.MemoryView":1401 * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<< @@ -18347,7 +17194,7 @@ 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":1400 + /* "View.MemoryView":1403 * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -18356,7 +17203,7 @@ 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":1394 + /* "View.MemoryView":1397 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -18367,7 +17214,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst /* function exit code */ } -/* "View.MemoryView":1404 +/* "View.MemoryView":1407 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -18384,7 +17231,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t Py_ssize_t __pyx_t_3; Py_ssize_t __pyx_t_4; - /* "View.MemoryView":1408 + /* "View.MemoryView":1411 * size_t itemsize, void *item) nogil: * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< @@ -18393,7 +17240,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_stride = (__pyx_v_strides[0]); - /* "View.MemoryView":1409 + /* "View.MemoryView":1412 * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< @@ -18402,7 +17249,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_extent = (__pyx_v_shape[0]); - /* "View.MemoryView":1411 + /* "View.MemoryView":1414 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -18412,7 +17259,7 @@ 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":1412 + /* "View.MemoryView":1415 * * if ndim == 1: * for i in range(extent): # <<<<<<<<<<<<<< @@ -18424,7 +17271,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1413 + /* "View.MemoryView":1416 * if ndim == 1: * for i in range(extent): * memcpy(data, item, itemsize) # <<<<<<<<<<<<<< @@ -18433,7 +17280,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ (void)(memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize)); - /* "View.MemoryView":1414 + /* "View.MemoryView":1417 * for i in range(extent): * memcpy(data, item, itemsize) * data += stride # <<<<<<<<<<<<<< @@ -18443,7 +17290,7 @@ 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":1411 + /* "View.MemoryView":1414 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -18453,7 +17300,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t goto __pyx_L3; } - /* "View.MemoryView":1416 + /* "View.MemoryView":1419 * data += stride * else: * for i in range(extent): # <<<<<<<<<<<<<< @@ -18466,7 +17313,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1417 + /* "View.MemoryView":1420 * else: * for i in range(extent): * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -18475,7 +17322,7 @@ 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":1419 + /* "View.MemoryView":1422 * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) * data += stride # <<<<<<<<<<<<<< @@ -18487,7 +17334,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t } __pyx_L3:; - /* "View.MemoryView":1404 + /* "View.MemoryView":1407 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -18511,6 +17358,9 @@ static PyObject *__pyx_pw_15View_dot_MemoryView_1__pyx_unpickle_Enum(PyObject *_ PyObject *__pyx_v___pyx_type = 0; long __pyx_v___pyx_checksum; PyObject *__pyx_v___pyx_state = 0; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__pyx_unpickle_Enum (wrapper)", 0); @@ -18588,6 +17438,9 @@ static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSE PyObject *__pyx_t_4 = NULL; PyObject *__pyx_t_5 = NULL; int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__pyx_unpickle_Enum", 0); /* "(tree fragment)":4 @@ -18776,6 +17629,9 @@ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *__ PyObject *__pyx_t_6 = NULL; PyObject *__pyx_t_7 = NULL; PyObject *__pyx_t_8 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__pyx_unpickle_Enum__set_state", 0); /* "(tree fragment)":12 @@ -18917,9 +17773,9 @@ static void __pyx_tp_dealloc_array(PyObject *o) { { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); - ++Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_array___dealloc__(o); - --Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->mode); @@ -19012,7 +17868,12 @@ static PyTypeObject __pyx_type___pyx_array = { sizeof(struct __pyx_array_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -19062,6 +17923,12 @@ static PyTypeObject __pyx_type___pyx_array = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { @@ -19120,7 +17987,12 @@ static PyTypeObject __pyx_type___pyx_MemviewEnum = { sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -19170,6 +18042,12 @@ static PyTypeObject __pyx_type___pyx_MemviewEnum = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; @@ -19206,9 +18084,9 @@ static void __pyx_tp_dealloc_memoryview(PyObject *o) { { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); - ++Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_memoryview___dealloc__(o); - --Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->obj); @@ -19370,7 +18248,12 @@ static PyTypeObject __pyx_type___pyx_memoryview = { sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -19420,6 +18303,12 @@ static PyTypeObject __pyx_type___pyx_memoryview = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; 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int __pyx_t_2; static PyThread_type_lock __pyx_t_3[8]; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannyDeclarations #if CYTHON_PEP489_MULTI_PHASE_INIT if (__pyx_m) { @@ -20460,10 +19336,9 @@ if (!__Pyx_RefNanny) { __pyx_d = PyModule_GetDict(__pyx_m); if (unlikely(!__pyx_d)) __PYX_ERR(0, 1, __pyx_L1_error) Py_INCREF(__pyx_d); __pyx_b = PyImport_AddModule(__Pyx_BUILTIN_MODULE_NAME); if (unlikely(!__pyx_b)) __PYX_ERR(0, 1, __pyx_L1_error) - __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) - #if CYTHON_COMPILING_IN_PYPY Py_INCREF(__pyx_b); - #endif + __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) + Py_INCREF(__pyx_cython_runtime); if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) __PYX_ERR(0, 1, __pyx_L1_error); /*--- Initialize various global constants etc. ---*/ if (__Pyx_InitGlobals() < 0) __PYX_ERR(0, 1, __pyx_L1_error) @@ -20489,8 +19364,8 @@ if (!__Pyx_RefNanny) { (void)__Pyx_modinit_global_init_code(); (void)__Pyx_modinit_variable_export_code(); (void)__Pyx_modinit_function_export_code(); - if (unlikely(__Pyx_modinit_type_init_code() != 0)) goto __pyx_L1_error; - if (unlikely(__Pyx_modinit_type_import_code() != 0)) goto __pyx_L1_error; + if (unlikely(__Pyx_modinit_type_init_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) + if (unlikely(__Pyx_modinit_type_import_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) (void)__Pyx_modinit_variable_import_code(); (void)__Pyx_modinit_function_import_code(); /*--- Execution code ---*/ @@ -20597,7 +19472,7 @@ if (!__Pyx_RefNanny) { * cdef strided = Enum("") # default * cdef indirect = Enum("") */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__34, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 286, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__29, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 286, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(generic); __Pyx_DECREF_SET(generic, __pyx_t_1); @@ -20611,7 +19486,7 @@ if (!__Pyx_RefNanny) { * cdef indirect = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__35, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 287, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 287, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(strided); __Pyx_DECREF_SET(strided, __pyx_t_1); @@ -20625,7 +19500,7 @@ if (!__Pyx_RefNanny) { * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__36, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 288, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__31, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 288, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(indirect); __Pyx_DECREF_SET(indirect, __pyx_t_1); @@ -20639,7 +19514,7 @@ if (!__Pyx_RefNanny) { * cdef indirect_contiguous = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__37, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 291, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__32, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 291, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(contiguous); __Pyx_DECREF_SET(contiguous, __pyx_t_1); @@ -20653,7 +19528,7 @@ if (!__Pyx_RefNanny) { * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__38, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 292, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__33, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 292, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(indirect_contiguous); __Pyx_DECREF_SET(indirect_contiguous, __pyx_t_1); @@ -20686,29 +19561,29 @@ if (!__Pyx_RefNanny) { __pyx_t_3[7] = PyThread_allocate_lock(); memcpy(&(__pyx_memoryview_thread_locks[0]), __pyx_t_3, sizeof(__pyx_memoryview_thread_locks[0]) * (8)); - /* "View.MemoryView":545 + /* "View.MemoryView":549 * info.obj = self * * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 545, __pyx_L1_error) + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 549, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem((PyObject *)__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 545, __pyx_L1_error) + if (PyDict_SetItem((PyObject *)__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 549, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_memoryview_type); - /* "View.MemoryView":991 + /* "View.MemoryView":995 * return self.from_object * * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 991, __pyx_L1_error) + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 995, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem((PyObject *)__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 991, __pyx_L1_error) + if (PyDict_SetItem((PyObject *)__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 995, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_memoryviewslice_type); @@ -20862,7 +19737,7 @@ static int __Pyx_ParseOptionalKeywords( } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 - if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { + if (likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { @@ -20889,7 +19764,7 @@ static int __Pyx_ParseOptionalKeywords( while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -20905,7 +19780,7 @@ static int __Pyx_ParseOptionalKeywords( while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -21009,7 +19884,7 @@ static int __Pyx_BufFmt_ParseNumber(const char** ts) { return -1; } else { count = *t++ - '0'; - while (*t >= '0' && *t < '9') { + while (*t >= '0' && *t <= '9') { count *= 10; count += *t++ - '0'; } @@ -21030,6 +19905,7 @@ static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { + case '?': return "'bool'"; case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; @@ -21072,7 +19948,7 @@ static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { - case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); @@ -21156,7 +20032,7 @@ static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; - case 'B': case 'H': case 'I': case 'L': case 'Q': + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); @@ -21300,9 +20176,7 @@ static PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; - int i = 0, number; - int ndim = ctx->head->field->type->ndim; -; + int i = 0, number, ndim; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, @@ -21310,6 +20184,7 @@ __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; @@ -21435,12 +20310,12 @@ static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const cha return NULL; } CYTHON_FALLTHROUGH; - case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': - if (ctx->enc_type == *ts && got_Z == ctx->is_complex && - ctx->enc_packmode == ctx->new_packmode) { + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; @@ -21509,7 +20384,7 @@ static int __Pyx__GetBufferAndValidate( __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } - if (unlikely((unsigned)buf->itemsize != dtype->size)) { + if (unlikely((size_t)buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", @@ -21558,11 +20433,7 @@ __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int i, retval=-1; Py_buffer *buf = &memview->view; __Pyx_RefNannySetupContext("init_memviewslice", 0); - if (!buf) { - PyErr_SetString(PyExc_ValueError, - "buf is NULL."); - goto fail; - } else if (memviewslice->memview || memviewslice->data) { + if (unlikely(memviewslice->memview || memviewslice->data)) { PyErr_SetString(PyExc_ValueError, "memviewslice is already initialized!"); goto fail; @@ -21641,13 +20512,13 @@ __Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int first_time; struct __pyx_memoryview_obj *memview = memslice->memview; - if (!memview || (PyObject *) memview == Py_None) + if (unlikely(!memview || (PyObject *) memview == Py_None)) return; - if (__pyx_get_slice_count(memview) < 0) + if (unlikely(__pyx_get_slice_count(memview) < 0)) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); first_time = __pyx_add_acquisition_count(memview) == 0; - if (first_time) { + if (unlikely(first_time)) { if (have_gil) { Py_INCREF((PyObject *) memview); } else { @@ -21661,18 +20532,16 @@ static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int last_time; struct __pyx_memoryview_obj *memview = memslice->memview; - if (!memview ) { - return; - } else if ((PyObject *) memview == Py_None) { + if (unlikely(!memview || (PyObject *) memview == Py_None)) { memslice->memview = NULL; return; } - if (__pyx_get_slice_count(memview) <= 0) + if (unlikely(__pyx_get_slice_count(memview) <= 0)) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); last_time = __pyx_sub_acquisition_count(memview) == 1; memslice->data = NULL; - if (last_time) { + if (unlikely(last_time)) { if (have_gil) { Py_CLEAR(memslice->memview); } else { @@ -21685,6 +20554,161 @@ static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, } } +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + /* PyObjectCall */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { @@ -21918,7 +20942,7 @@ static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args return result; } #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) { +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); PyObject *globals = PyFunction_GET_GLOBALS(func); PyObject *argdefs = PyFunction_GET_DEFAULTS(func); @@ -21989,12 +21013,12 @@ static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, } #if PY_MAJOR_VERSION >= 3 result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, kwdefs, closure); #else result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, closure); #endif @@ -22006,6 +21030,35 @@ done: #endif #endif +/* PyObjectCall2Args */ + static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + /* PyObjectCallMethO */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { @@ -22066,245 +21119,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObjec } #endif -/* DictGetItem */ - #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()) { - if (unlikely(PyTuple_Check(key))) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) { - PyErr_SetObject(PyExc_KeyError, args); - Py_DECREF(args); - } - } else { - PyErr_SetObject(PyExc_KeyError, key); - } - } - return NULL; - } - Py_INCREF(value); - return value; -} -#endif - -/* RaiseTooManyValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* RaiseNoneIterError */ - static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* ExtTypeTest */ - static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* GetTopmostException */ - #if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - -/* PyObjectCall2Args */ - static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { - PyObject *args, *result = NULL; - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyFunction_FastCall(function, args, 2); - } - #endif - #if CYTHON_FAST_PYCCALL - if (__Pyx_PyFastCFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyCFunction_FastCall(function, args, 2); - } - #endif - args = PyTuple_New(2); - if (unlikely(!args)) goto done; - Py_INCREF(arg1); - PyTuple_SET_ITEM(args, 0, arg1); - Py_INCREF(arg2); - PyTuple_SET_ITEM(args, 1, arg2); - Py_INCREF(function); - result = __Pyx_PyObject_Call(function, args, NULL); - Py_DECREF(args); - Py_DECREF(function); -done: - return result; -} - /* BytesEquals */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY @@ -22613,9 +21427,9 @@ static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { if (stop < 0) stop += length; } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); length = stop - start; - if (unlikely(length <= 0)) - return PyUnicode_FromUnicode(NULL, 0); cstring += start; if (decode_func) { return decode_func(cstring, length, errors); @@ -22639,6 +21453,32 @@ static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject return (likely(r)) ? r : __Pyx_GetAttr3Default(d); } +/* PyDictVersioning */ + #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + /* GetModuleGlobalName */ #if CYTHON_USE_DICT_VERSIONS static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) @@ -22674,6 +21514,37 @@ static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) return __Pyx_GetBuiltinName(name); } +/* RaiseTooManyValuesToUnpack */ + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ + static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseNoneIterError */ + static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* ExtTypeTest */ + static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + /* SwapException */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { @@ -22739,7 +21610,7 @@ static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, { #if PY_MAJOR_VERSION >= 3 if (level == -1) { - if (strchr(__Pyx_MODULE_NAME, '.')) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); if (!module) { @@ -22876,7 +21747,9 @@ static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObj /* PyIntBinop */ #if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) { +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) { + (void)inplace; + (void)zerodivision_check; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { const long b = intval; @@ -23009,48 +21882,6 @@ static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED return q; } -/* WriteUnraisableException */ - static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, - CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, - int full_traceback, CYTHON_UNUSED int nogil) { - PyObject *old_exc, *old_val, *old_tb; - PyObject *ctx; - __Pyx_PyThreadState_declare -#ifdef WITH_THREAD - PyGILState_STATE state; - if (nogil) - state = PyGILState_Ensure(); -#ifdef _MSC_VER - else state = (PyGILState_STATE)-1; -#endif -#endif - __Pyx_PyThreadState_assign - __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); - } -#ifdef WITH_THREAD - if (nogil) - PyGILState_Release(state); -#endif -} - /* ImportFrom */ static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); @@ -23151,6 +21982,28 @@ bad: return -1; } +/* PyObjectGetAttrStrNoError */ + static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + /* SetupReduce */ static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { int ret; @@ -23178,43 +22031,51 @@ static int __Pyx_setup_reduce(PyObject* type_obj) { PyObject *setstate = NULL; PyObject *setstate_cython = NULL; #if CYTHON_USE_PYTYPE_LOOKUP - if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto GOOD; + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; #else - if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto GOOD; + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; #endif #if CYTHON_USE_PYTYPE_LOOKUP - object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD; + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #else - object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD; + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #endif - reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto BAD; + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; if (reduce_ex == object_reduce_ex) { #if CYTHON_USE_PYTYPE_LOOKUP - object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD; + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #else - object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD; + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #endif - reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto BAD; + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { - reduce_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_cython); if (unlikely(!reduce_cython)) goto BAD; - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto BAD; + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); if (!setstate) PyErr_Clear(); if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { - setstate_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate_cython); if (unlikely(!setstate_cython)) goto BAD; - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto BAD; + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } } PyType_Modified((PyTypeObject*)type_obj); } } - goto GOOD; -BAD: + goto __PYX_GOOD; +__PYX_BAD: if (!PyErr_Occurred()) PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); ret = -1; -GOOD: +__PYX_GOOD: #if !CYTHON_USE_PYTYPE_LOOKUP Py_XDECREF(object_reduce); Py_XDECREF(object_reduce_ex); @@ -23290,7 +22151,7 @@ bad: /* CLineInTraceback */ #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { PyObject *use_cline; PyObject *ptype, *pvalue, *ptraceback; #if CYTHON_COMPILING_IN_CPYTHON @@ -23394,7 +22255,7 @@ static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } @@ -23498,7 +22359,6 @@ bad: #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); @@ -23512,7 +22372,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return; } if ((0)) {} - else if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); view->obj = NULL; Py_DECREF(obj); } @@ -23662,13 +22521,13 @@ __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) if (buf->strides) { if (spec & __Pyx_MEMVIEW_CONTIG) { if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { - if (buf->strides[dim] != sizeof(void *)) { + if (unlikely(buf->strides[dim] != sizeof(void *))) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly contiguous " "in dimension %d.", dim); goto fail; } - } else if (buf->strides[dim] != buf->itemsize) { + } else if (unlikely(buf->strides[dim] != buf->itemsize)) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); @@ -23679,7 +22538,7 @@ __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) Py_ssize_t stride = buf->strides[dim]; if (stride < 0) stride = -stride; - if (stride < buf->itemsize) { + if (unlikely(stride < buf->itemsize)) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); @@ -23687,17 +22546,17 @@ __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) } } } else { - if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { + if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not contiguous in " "dimension %d", dim); goto fail; - } else if (spec & (__Pyx_MEMVIEW_PTR)) { + } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not indirect in " "dimension %d", dim); goto fail; - } else if (buf->suboffsets) { + } else if (unlikely(buf->suboffsets)) { PyErr_SetString(PyExc_ValueError, "Buffer exposes suboffsets but no strides"); goto fail; @@ -23711,7 +22570,7 @@ static int __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) { if (spec & __Pyx_MEMVIEW_DIRECT) { - if (buf->suboffsets && buf->suboffsets[dim] >= 0) { + if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { PyErr_Format(PyExc_ValueError, "Buffer not compatible with direct access " "in dimension %d.", dim); @@ -23719,7 +22578,7 @@ __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec } } if (spec & __Pyx_MEMVIEW_PTR) { - if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { + if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly accessible " "in dimension %d.", dim); @@ -23737,9 +22596,7 @@ __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) if (c_or_f_flag & __Pyx_IS_F_CONTIG) { Py_ssize_t stride = 1; for (i = 0; i < ndim; i++) { - if (stride * buf->itemsize != buf->strides[i] && - buf->shape[i] > 1) - { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { PyErr_SetString(PyExc_ValueError, "Buffer not fortran contiguous."); goto fail; @@ -23749,8 +22606,7 @@ __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { Py_ssize_t stride = 1; for (i = ndim - 1; i >- 1; i--) { - if (stride * buf->itemsize != buf->strides[i] && - buf->shape[i] > 1) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { PyErr_SetString(PyExc_ValueError, "Buffer not C contiguous."); goto fail; @@ -23791,7 +22647,7 @@ static int __Pyx_ValidateAndInit_memviewslice( goto fail; } buf = &memview->view; - if (buf->ndim != ndim) { + if (unlikely(buf->ndim != ndim)) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", ndim, buf->ndim); @@ -23799,9 +22655,9 @@ static int __Pyx_ValidateAndInit_memviewslice( } if (new_memview) { __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; } - if ((unsigned) buf->itemsize != dtype->size) { + if (unlikely((unsigned) buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", @@ -23812,15 +22668,17 @@ static int __Pyx_ValidateAndInit_memviewslice( (dtype->size > 1) ? "s" : ""); goto fail; } - for (i = 0; i < ndim; i++) { - spec = axes_specs[i]; - if (!__pyx_check_strides(buf, i, ndim, spec)) - goto fail; - if (!__pyx_check_suboffsets(buf, i, ndim, spec)) + if (buf->len > 0) { + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) + goto fail; + if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) + goto fail; + } + if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) goto fail; } - if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) - goto fail; if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, new_memview != NULL) == -1)) { goto fail; @@ -23965,13 +22823,13 @@ __pyx_fail: return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { float r = b.imag / b.real; - float s = 1.0 / (b.real + b.imag * r); + float s = (float)(1.0) / (b.real + b.imag * r); return __pyx_t_float_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { float r = b.real / b.imag; - float s = 1.0 / (b.imag + b.real * r); + float s = (float)(1.0) / (b.imag + b.real * r); return __pyx_t_float_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -24029,7 +22887,6 @@ __pyx_fail: case 1: return a; case 2: - z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(a, a); case 3: z = __Pyx_c_prod_float(a, a); @@ -24051,7 +22908,7 @@ __pyx_fail: theta = 0; } else { r = -a.real; - theta = atan2f(0, -1); + theta = atan2f(0.0, -1.0); } } else { r = __Pyx_c_abs_float(a); @@ -24120,13 +22977,13 @@ __pyx_fail: return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { double r = b.imag / b.real; - double s = 1.0 / (b.real + b.imag * r); + double s = (double)(1.0) / (b.real + b.imag * r); return __pyx_t_double_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { double r = b.real / b.imag; - double s = 1.0 / (b.imag + b.real * r); + double s = (double)(1.0) / (b.imag + b.real * r); return __pyx_t_double_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -24184,7 +23041,6 @@ __pyx_fail: case 1: return a; case 2: - z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(a, a); case 3: z = __Pyx_c_prod_double(a, a); @@ -24206,7 +23062,7 @@ __pyx_fail: theta = 0; } else { r = -a.real; - theta = atan2(0, -1); + theta = atan2(0.0, -1.0); } } else { r = __Pyx_c_abs_double(a); @@ -24222,37 +23078,6 @@ __pyx_fail: #endif #endif -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { - const enum NPY_TYPES neg_one = (enum NPY_TYPES) ((enum NPY_TYPES) 0 - (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); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(enum NPY_TYPES) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - 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); - } -} - /* MemviewSliceCopyTemplate */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, @@ -24271,7 +23096,7 @@ __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, struct __pyx_memoryview_obj *memview_obj = NULL; __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); for (i = 0; i < ndim; i++) { - if (from_mvs->suboffsets[i] >= 0) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " "indirect dimensions (axis %d)", i); goto fail; diff --git a/GPy/models/state_space_cython.c b/GPy/models/state_space_cython.c index 2f462748..46d3c02c 100644 --- a/GPy/models/state_space_cython.c +++ b/GPy/models/state_space_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.29.2 */ +/* Generated by Cython 0.29.21 */ #define PY_SSIZE_T_CLEAN #include "Python.h" @@ -7,8 +7,8 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) #error Cython requires Python 2.6+ or Python 3.3+. #else -#define CYTHON_ABI "0_29_2" -#define CYTHON_HEX_VERSION 0x001D02F0 +#define CYTHON_ABI "0_29_21" +#define CYTHON_HEX_VERSION 0x001D15F0 #define CYTHON_FUTURE_DIVISION 0 #include #ifndef offsetof @@ -310,8 +310,13 @@ #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else #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) +#endif #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES @@ -346,26 +351,6 @@ #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif -#if CYTHON_USE_DICT_VERSIONS -#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ - (version_var) = __PYX_GET_DICT_VERSION(dict);\ - (cache_var) = (value); -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ - static PY_UINT64_T __pyx_dict_version = 0;\ - static PyObject *__pyx_dict_cached_value = NULL;\ - if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ - (VAR) = __pyx_dict_cached_value;\ - } else {\ - (VAR) = __pyx_dict_cached_value = (LOOKUP);\ - __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ - }\ - } -#else -#define __PYX_GET_DICT_VERSION(dict) (0) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); -#endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) @@ -398,7 +383,7 @@ typedef int Py_tss_t; static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { *key = PyThread_create_key(); - return 0; // PyThread_create_key reports success always + return 0; } static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); @@ -421,7 +406,7 @@ static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { return PyThread_get_key_value(*key); } -#endif // TSS (Thread Specific Storage) API +#endif #if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) #define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) #else @@ -450,7 +435,11 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 @@ -499,8 +488,10 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode #define PyObject_Unicode PyObject_Str #endif +#endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) @@ -511,6 +502,13 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif #if CYTHON_ASSUME_SAFE_MACROS #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) #else @@ -550,7 +548,7 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : (Py_INCREF(func), func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif @@ -591,11 +589,10 @@ static CYTHON_INLINE float __PYX_NAN() { #define __Pyx_truncl truncl #endif - +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } #define __PYX_ERR(f_index, lineno, Ln_error) \ -{ \ - __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ -} + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } #ifndef __PYX_EXTERN_C #ifdef __cplusplus @@ -611,7 +608,13 @@ static CYTHON_INLINE float __PYX_NAN() { #include #include #include "numpy/arrayobject.h" +#include "numpy/ndarrayobject.h" +#include "numpy/ndarraytypes.h" +#include "numpy/arrayscalars.h" #include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + #include "numpy/npy_math.h" #ifdef _OPENMP #include @@ -625,7 +628,8 @@ typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* enc const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize @@ -884,7 +888,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":776 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":690 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -893,7 +897,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":691 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -902,7 +906,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -911,7 +915,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":779 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":693 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -920,7 +924,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":697 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -929,7 +933,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":784 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":698 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -938,7 +942,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":785 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -947,7 +951,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":786 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":700 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -956,7 +960,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":704 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -965,7 +969,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":705 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -974,7 +978,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":800 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -983,7 +987,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":715 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -992,7 +996,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":716 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1001,7 +1005,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":804 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":718 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1010,7 +1014,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":805 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":719 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1019,7 +1023,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":806 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":720 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1028,7 +1032,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":808 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":722 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1037,7 +1041,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":809 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":723 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1046,7 +1050,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":811 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":725 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1055,7 +1059,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":812 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":726 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1064,7 +1068,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":727 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1124,7 +1128,7 @@ struct __pyx_obj_3GPy_6models_18state_space_cython_Q_handling_Cython; struct __pyx_obj_3GPy_6models_18state_space_cython_Std_Dynamic_Callables_Cython; struct __pyx_obj_3GPy_6models_18state_space_cython_AQcompute_batch_Cython; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":729 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1133,7 +1137,7 @@ struct __pyx_obj_3GPy_6models_18state_space_cython_AQcompute_batch_Cython; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":730 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1142,7 +1146,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":817 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":731 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1151,7 +1155,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":819 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":733 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1542,12 +1546,38 @@ static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + /* PyFunctionFastCall.proto */ #if CYTHON_FAST_PYCALL #define __Pyx_PyFunction_FastCall(func, args, nargs)\ __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs); +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); #else #define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) #endif @@ -1773,9 +1803,9 @@ static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObje /* PyFloatBinop.proto */ #if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double floatval, int inplace); +static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check); #else -#define __Pyx_PyFloat_DivideCObj(op1, op2, floatval, inplace)\ +#define __Pyx_PyFloat_DivideCObj(op1, op2, floatval, inplace, zerodivision_check)\ ((inplace ? __Pyx_PyNumber_InPlaceDivide(op1, op2) : __Pyx_PyNumber_Divide(op1, op2))) #endif @@ -1788,9 +1818,6 @@ static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); /* HasAttr.proto */ static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - /* GetTopmostException.proto */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); @@ -1838,6 +1865,9 @@ static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_nam /* SetVTable.proto */ static int __Pyx_SetVtable(PyObject *dict, void *vtable); +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + /* SetupReduce.proto */ static int __Pyx_setup_reduce(PyObject* type_obj); @@ -2008,9 +2038,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); #endif #endif -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); - /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); @@ -2098,8 +2125,17 @@ 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_generic = 0; +static PyTypeObject *__pyx_ptype_5numpy_number = 0; +static PyTypeObject *__pyx_ptype_5numpy_integer = 0; +static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; +static PyTypeObject *__pyx_ptype_5numpy_floating = 0; +static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; +static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; +static PyTypeObject *__pyx_ptype_5numpy_character = 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' */ @@ -2129,7 +2165,6 @@ static PyObject *__pyx_builtin_NotImplemented; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_super; static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_ImportError; static const char __pyx_k_A[] = "A"; static const char __pyx_k_H[] = "H"; @@ -2268,7 +2303,6 @@ static const char __pyx_k_ImportError[] = "ImportError"; static const char __pyx_k_PickleError[] = "PickleError"; static const char __pyx_k_measurement[] = "measurement"; static const char __pyx_k_overwrite_a[] = "overwrite_a"; -static const char __pyx_k_RuntimeError[] = "RuntimeError"; static const char __pyx_k_check_finite[] = "check_finite"; static const char __pyx_k_k_measurment[] = "k_measurment"; static const char __pyx_k_param_number[] = "param_number"; @@ -2319,7 +2353,6 @@ static const char __pyx_k_d_log_likelihood_update[] = "d_log_likelihood_update"; static const char __pyx_k_p_measurement_callables[] = "p_measurement_callables"; static const char __pyx_k_Dynamic_Callables_Cython[] = "Dynamic_Callables_Cython"; static const char __pyx_k_calc_grad_log_likelihood[] = "calc_grad_log_likelihood"; -static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static const char __pyx_k_Measurement_Callables_Cython[] = "Measurement_Callables_Cython"; static const char __pyx_k_Std_Dynamic_Callables_Cython[] = "Std_Dynamic_Callables_Cython"; static const char __pyx_k_cython_Ak_is_not_implemented[] = "(cython) Ak is not implemented!"; @@ -2345,8 +2378,6 @@ static const char __pyx_k_cython_Q_srk_is_not_implemented[] = "(cython) Q_srk is static const char __pyx_k_cython_reset_is_not_implemented[] = "(cython) reset is not implemented!"; static const char __pyx_k_kalman_prediction_step_SVD_Cyth[] = "_kalman_prediction_step_SVD_Cython"; static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; -static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; -static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static const char __pyx_k_GPy_models_state_space_cython_py[] = "GPy/models/state_space_cython.pyx"; static const char __pyx_k_Incompatible_checksums_s_vs_0x14[] = "Incompatible checksums (%s vs 0x146e1f7 = (As, Q, Q_square_root, Q_svd_dict, Q_time_var_index, Qs, dAs, dQ, dQs, index, last_k, reconstruct_indices, svd_each_time))"; static const char __pyx_k_Incompatible_checksums_s_vs_0x70[] = "Incompatible checksums (%s vs 0x706c35f = (H, H_time_var_index, R, R_square_root, R_time_var_index, dH, dR, index, svd_each_time))"; @@ -2357,11 +2388,8 @@ static const char __pyx_k_Incompatible_checksums_s_vs_0xdf[] = "Incompatible che static const char __pyx_k_Kalman_Filter_Update_SVD_S_is_ne[] = "Kalman Filter Update SVD: S is negative step %i"; static const char __pyx_k_Measurement_dimension_larger_the[] = "Measurement dimension larger then 1 is currently not supported"; static const char __pyx_k_Nan_measurements_are_currently_n[] = "Nan measurements are currently not supported if\n they are intermixed with not NaN measurements"; -static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; static const char __pyx_k_Std_Measurement_Callables_Cython[] = "Std_Measurement_Callables_Cython"; -static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; -static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; static PyObject *__pyx_n_s_A; static PyObject *__pyx_n_s_AQcompute_batch_Cython; static PyObject *__pyx_n_s_A_time_var_index; @@ -2370,8 +2398,6 @@ static PyObject *__pyx_n_s_As; static PyObject *__pyx_n_s_DTYPE; static PyObject *__pyx_n_s_DTYPE_int; static PyObject *__pyx_n_s_Dynamic_Callables_Cython; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_n_s_GPy_models_state_space_cython; static PyObject *__pyx_kp_s_GPy_models_state_space_cython_py; static PyObject *__pyx_n_s_H; @@ -2391,7 +2417,6 @@ static PyObject *__pyx_n_s_Measurement_Callables_Cython; static PyObject *__pyx_kp_s_Measurement_dimension_larger_the; static PyObject *__pyx_kp_s_Nan_measurements_are_currently_n; static PyObject *__pyx_kp_s_Nan_values_in_likelihood_update; -static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; static PyObject *__pyx_n_s_NotImplemented; static PyObject *__pyx_n_s_P; static PyObject *__pyx_n_s_P_init; @@ -2415,7 +2440,6 @@ static PyObject *__pyx_n_s_R_isr; static PyObject *__pyx_n_s_R_isrk; static PyObject *__pyx_n_s_R_time_var_index; static PyObject *__pyx_n_s_Rk; -static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_S; static PyObject *__pyx_n_s_S_new; static PyObject *__pyx_n_s_S_old; @@ -2519,8 +2543,6 @@ static PyObject *__pyx_n_s_measurement; static PyObject *__pyx_n_s_measurement_dim_gt_one; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_nbytes; -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_new; static PyObject *__pyx_n_s_np; static PyObject *__pyx_n_s_numpy; @@ -2587,7 +2609,6 @@ static PyObject *__pyx_n_s_total_size_of_data; static PyObject *__pyx_n_s_unique; static PyObject *__pyx_n_s_unique_Q_number; static PyObject *__pyx_n_s_unique_R_number; -static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; static PyObject *__pyx_n_s_update; static PyObject *__pyx_n_s_v; static PyObject *__pyx_n_s_vstack; @@ -2656,8 +2677,6 @@ static PyObject *__pyx_pf_3GPy_6models_18state_space_cython_12__pyx_unpickle_Std static PyObject *__pyx_pf_3GPy_6models_18state_space_cython_14__pyx_unpickle_Q_handling_Cython(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ static PyObject *__pyx_pf_3GPy_6models_18state_space_cython_16__pyx_unpickle_Std_Dynamic_Callables_Cython(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ static PyObject *__pyx_pf_3GPy_6models_18state_space_cython_18__pyx_unpickle_AQcompute_batch_Cython(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* 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_tp_new_3GPy_6models_18state_space_cython_Dynamic_Callables_Cython(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_3GPy_6models_18state_space_cython_Measurement_Callables_Cython(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_3GPy_6models_18state_space_cython_R_handling_Cython(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ @@ -2699,30 +2718,25 @@ static PyObject *__pyx_tuple__18; static PyObject *__pyx_tuple__19; static PyObject *__pyx_tuple__20; static PyObject *__pyx_tuple__21; -static PyObject *__pyx_tuple__22; static PyObject *__pyx_tuple__23; -static PyObject *__pyx_tuple__24; static PyObject *__pyx_tuple__25; -static PyObject *__pyx_tuple__26; -static PyObject *__pyx_tuple__28; -static PyObject *__pyx_tuple__30; -static PyObject *__pyx_tuple__32; -static PyObject *__pyx_tuple__34; -static PyObject *__pyx_tuple__36; -static PyObject *__pyx_tuple__38; -static PyObject *__pyx_tuple__40; -static PyObject *__pyx_tuple__42; -static PyObject *__pyx_tuple__44; -static PyObject *__pyx_codeobj__27; -static PyObject *__pyx_codeobj__29; -static PyObject *__pyx_codeobj__31; -static PyObject *__pyx_codeobj__33; -static PyObject *__pyx_codeobj__35; -static PyObject *__pyx_codeobj__37; -static PyObject *__pyx_codeobj__39; -static PyObject *__pyx_codeobj__41; -static PyObject *__pyx_codeobj__43; -static PyObject *__pyx_codeobj__45; +static PyObject *__pyx_tuple__27; +static PyObject *__pyx_tuple__29; +static PyObject *__pyx_tuple__31; +static PyObject *__pyx_tuple__33; +static PyObject *__pyx_tuple__35; +static PyObject *__pyx_tuple__37; +static PyObject *__pyx_tuple__39; +static PyObject *__pyx_codeobj__22; +static PyObject *__pyx_codeobj__24; +static PyObject *__pyx_codeobj__26; +static PyObject *__pyx_codeobj__28; +static PyObject *__pyx_codeobj__30; +static PyObject *__pyx_codeobj__32; +static PyObject *__pyx_codeobj__34; +static PyObject *__pyx_codeobj__36; +static PyObject *__pyx_codeobj__38; +static PyObject *__pyx_codeobj__40; /* Late includes */ /* "GPy/models/state_space_cython.pyx":22 @@ -2748,6 +2762,9 @@ static PyObject *__pyx_f_3GPy_6models_18state_space_cython_24Dynamic_Callables_C PyObject *__pyx_t_5 = NULL; int __pyx_t_6; PyObject *__pyx_t_7 = NULL; + int __pyx_lineno = 0; 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+ + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":1006 + * also needed. 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"../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":1020 + * returns the unit part of the dtype for a numpy datetime64 object. + * """ + * return (obj).obmeta.base # <<<<<<<<<<<<<< + */ + __pyx_r = ((NPY_DATETIMEUNIT)((PyDatetimeScalarObject *)__pyx_v_obj)->obmeta.base); + goto __pyx_L0; + + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":1016 + * + * + * cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: # <<<<<<<<<<<<<< + * """ + * returns the unit part of the dtype for a numpy datetime64 object. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} static struct __pyx_vtabstruct_3GPy_6models_18state_space_cython_Dynamic_Callables_Cython __pyx_vtable_3GPy_6models_18state_space_cython_Dynamic_Callables_Cython; static PyObject *__pyx_tp_new_3GPy_6models_18state_space_cython_Dynamic_Callables_Cython(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { @@ -31410,7 +30456,12 @@ 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likely(!__pyx_type_3GPy_6models_18state_space_cython_AQcompute_batch_Cython.tp_dictoffset && __pyx_type_3GPy_6models_18state_space_cython_AQcompute_batch_Cython.tp_getattro == PyObject_GenericGetAttr)) { __pyx_type_3GPy_6models_18state_space_cython_AQcompute_batch_Cython.tp_getattro = __Pyx_PyObject_GenericGetAttr; } @@ -33084,6 +32161,9 @@ static int __Pyx_modinit_type_init_code(void) { static int __Pyx_modinit_type_import_code(void) { __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__Pyx_modinit_type_import_code", 0); /*--- Type import code ---*/ __pyx_t_1 = PyImport_ImportModule(__Pyx_BUILTIN_MODULE_NAME); if (unlikely(!__pyx_t_1)) __PYX_ERR(3, 9, __pyx_L1_error) @@ -33097,18 +32177,38 @@ static int __Pyx_modinit_type_import_code(void) { __Pyx_ImportType_CheckSize_Warn); if (!__pyx_ptype_7cpython_4type_type) __PYX_ERR(3, 9, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); 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__pyx_ptype_5numpy_ufunc = __Pyx_ImportType(__pyx_t_1, "numpy", "ufunc", sizeof(PyUFuncObject), __Pyx_ImportType_CheckSize_Ignore); + if (!__pyx_ptype_5numpy_ufunc) __PYX_ERR(2, 827, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_RefNannyFinishContext(); return 0; @@ -33135,17 +32235,19 @@ static int __Pyx_modinit_function_import_code(void) { } -#if PY_MAJOR_VERSION < 3 -#ifdef CYTHON_NO_PYINIT_EXPORT -#define __Pyx_PyMODINIT_FUNC void -#else +#ifndef CYTHON_NO_PYINIT_EXPORT #define __Pyx_PyMODINIT_FUNC PyMODINIT_FUNC +#elif PY_MAJOR_VERSION < 3 +#ifdef __cplusplus +#define __Pyx_PyMODINIT_FUNC extern "C" void +#else +#define __Pyx_PyMODINIT_FUNC void #endif #else -#ifdef CYTHON_NO_PYINIT_EXPORT -#define __Pyx_PyMODINIT_FUNC PyObject * +#ifdef __cplusplus +#define __Pyx_PyMODINIT_FUNC extern "C" PyObject * #else -#define __Pyx_PyMODINIT_FUNC PyMODINIT_FUNC +#define __Pyx_PyMODINIT_FUNC PyObject * #endif #endif @@ -33228,6 +32330,9 @@ static CYTHON_SMALL_CODE int __pyx_pymod_exec_state_space_cython(PyObject *__pyx { PyObject *__pyx_t_1 = NULL; PyObject *__pyx_t_2 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannyDeclarations #if CYTHON_PEP489_MULTI_PHASE_INIT if (__pyx_m) { @@ -33295,10 +32400,9 @@ if (!__Pyx_RefNanny) { __pyx_d = PyModule_GetDict(__pyx_m); if (unlikely(!__pyx_d)) __PYX_ERR(0, 1, __pyx_L1_error) Py_INCREF(__pyx_d); __pyx_b = PyImport_AddModule(__Pyx_BUILTIN_MODULE_NAME); if (unlikely(!__pyx_b)) __PYX_ERR(0, 1, __pyx_L1_error) - __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) - #if CYTHON_COMPILING_IN_PYPY Py_INCREF(__pyx_b); - #endif + __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) + Py_INCREF(__pyx_cython_runtime); if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) __PYX_ERR(0, 1, __pyx_L1_error); /*--- Initialize various global constants etc. ---*/ if (__Pyx_InitGlobals() < 0) __PYX_ERR(0, 1, __pyx_L1_error) @@ -33324,8 +32428,8 @@ if (!__Pyx_RefNanny) { (void)__Pyx_modinit_global_init_code(); (void)__Pyx_modinit_variable_export_code(); (void)__Pyx_modinit_function_export_code(); - if (unlikely(__Pyx_modinit_type_init_code() != 0)) goto __pyx_L1_error; - if (unlikely(__Pyx_modinit_type_import_code() != 0)) goto __pyx_L1_error; + if (unlikely(__Pyx_modinit_type_init_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) + if (unlikely(__Pyx_modinit_type_import_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) (void)__Pyx_modinit_variable_import_code(); (void)__Pyx_modinit_function_import_code(); /*--- Execution code ---*/ @@ -33509,12 +32613,12 @@ if (!__Pyx_RefNanny) { if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1046 - * raise ImportError("numpy.core.umath failed to import") + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":1016 * - * cdef inline int import_ufunc() except -1: # <<<<<<<<<<<<<< - * try: - * _import_umath() + * + * cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: # <<<<<<<<<<<<<< + * """ + * returns the unit part of the dtype for a numpy datetime64 object. */ /*--- Wrapped vars code ---*/ @@ -33634,7 +32738,7 @@ static int __Pyx_BufFmt_ParseNumber(const char** ts) { return -1; } else { count = *t++ - '0'; - while (*t >= '0' && *t < '9') { + while (*t >= '0' && *t <= '9') { count *= 10; count += *t++ - '0'; } @@ -33655,6 +32759,7 @@ static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { + case '?': return "'bool'"; case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; @@ -33697,7 +32802,7 @@ static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { - case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); @@ -33781,7 +32886,7 @@ static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; - case 'B': case 'H': case 'I': case 'L': case 'Q': + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); @@ -33925,9 +33030,7 @@ static PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; - int i = 0, number; - int ndim = ctx->head->field->type->ndim; -; + int i = 0, number, ndim; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, @@ -33935,6 +33038,7 @@ __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; @@ -34060,12 +33164,12 @@ static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const cha return NULL; } CYTHON_FALLTHROUGH; - case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': - if (ctx->enc_type == *ts && got_Z == ctx->is_complex && - ctx->enc_packmode == ctx->new_packmode) { + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; @@ -34134,7 +33238,7 @@ static int __Pyx__GetBufferAndValidate( __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } - if (unlikely((unsigned)buf->itemsize != dtype->size)) { + if (unlikely((size_t)buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", @@ -34148,6 +33252,32 @@ fail:; return -1; } +/* PyDictVersioning */ + #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + /* PyFunctionFastCall */ #if CYTHON_FAST_PYCALL static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, @@ -34179,7 +33309,7 @@ static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args return result; } #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) { +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); PyObject *globals = PyFunction_GET_GLOBALS(func); PyObject *argdefs = PyFunction_GET_DEFAULTS(func); @@ -34250,12 +33380,12 @@ static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, } #if PY_MAJOR_VERSION >= 3 result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, kwdefs, closure); #else result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, closure); #endif @@ -34555,7 +33685,7 @@ bad: } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 - if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { + if (likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { @@ -34582,7 +33712,7 @@ bad: while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -34598,7 +33728,7 @@ bad: while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -35117,15 +34247,23 @@ static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObje /* PyFloatBinop */ #if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double floatval, CYTHON_UNUSED int inplace) { +#define __Pyx_PyFloat_DivideCObj_ZeroDivisionError(operand) if (unlikely(zerodivision_check && ((operand) == 0))) {\ + PyErr_SetString(PyExc_ZeroDivisionError, "float division by zero");\ + return NULL;\ +} +static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check) { const double a = floatval; double b, result; + (void)inplace; + (void)zerodivision_check; if (likely(PyFloat_CheckExact(op2))) { b = PyFloat_AS_DOUBLE(op2); + __Pyx_PyFloat_DivideCObj_ZeroDivisionError(b) } else #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op2))) { b = (double) PyInt_AS_LONG(op2); + __Pyx_PyFloat_DivideCObj_ZeroDivisionError(b) } else #endif if (likely(PyLong_CheckExact(op2))) { @@ -35133,7 +34271,7 @@ static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double f const digit* digits = ((PyLongObject*)op2)->ob_digit; const Py_ssize_t size = Py_SIZE(op2); switch (size) { - case 0: b = 0.0; break; + case 0: __Pyx_PyFloat_DivideCObj_ZeroDivisionError(0) break; case -1: b = -(double) digits[0]; break; case 1: b = (double) digits[0]; break; case -2: @@ -35175,10 +34313,12 @@ static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double f #endif b = PyLong_AsDouble(op2); if (unlikely(b == -1.0 && PyErr_Occurred())) return NULL; + __Pyx_PyFloat_DivideCObj_ZeroDivisionError(b) } } else { return (inplace ? __Pyx_PyNumber_InPlaceDivide(op1, op2) : __Pyx_PyNumber_Divide(op1, op2)); } + __Pyx_PyFloat_DivideCObj_ZeroDivisionError(b) PyFPE_START_PROTECT("divide", return NULL) result = a / b; PyFPE_END_PROTECT(result) @@ -35216,7 +34356,7 @@ static PyObject* __Pyx_PyFloat_DivideCObj(PyObject *op1, PyObject *op2, double f { #if PY_MAJOR_VERSION >= 3 if (level == -1) { - if (strchr(__Pyx_MODULE_NAME, '.')) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); if (!module) { @@ -35283,11 +34423,6 @@ bad: } } -/* RaiseNoneIterError */ - static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - /* GetTopmostException */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * @@ -35509,6 +34644,28 @@ bad: return -1; } +/* PyObjectGetAttrStrNoError */ + static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + /* SetupReduce */ static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { int ret; @@ -35536,43 +34693,51 @@ static int __Pyx_setup_reduce(PyObject* type_obj) { PyObject *setstate = NULL; PyObject *setstate_cython = NULL; #if CYTHON_USE_PYTYPE_LOOKUP - if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto GOOD; + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; #else - if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto GOOD; + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; #endif #if CYTHON_USE_PYTYPE_LOOKUP - object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD; + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #else - object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD; + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #endif - reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto BAD; + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; if (reduce_ex == object_reduce_ex) { #if CYTHON_USE_PYTYPE_LOOKUP - object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD; + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #else - object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD; + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #endif - reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto BAD; + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { - reduce_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_cython); if (unlikely(!reduce_cython)) goto BAD; - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto BAD; + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); if (!setstate) PyErr_Clear(); if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { - setstate_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate_cython); if (unlikely(!setstate_cython)) goto BAD; - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto BAD; + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } } PyType_Modified((PyTypeObject*)type_obj); } } - goto GOOD; -BAD: + goto __PYX_GOOD; +__PYX_BAD: if (!PyErr_Occurred()) PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); ret = -1; -GOOD: +__PYX_GOOD: #if !CYTHON_USE_PYTYPE_LOOKUP Py_XDECREF(object_reduce); Py_XDECREF(object_reduce_ex); @@ -35648,7 +34813,7 @@ bad: /* CLineInTraceback */ #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { PyObject *use_cline; PyObject *ptype, *pvalue, *ptraceback; #if CYTHON_COMPILING_IN_CPYTHON @@ -35752,7 +34917,7 @@ static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } @@ -35909,7 +35074,6 @@ bad: #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } @@ -35921,7 +35085,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return; } if ((0)) {} - else if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); view->obj = NULL; Py_DECREF(obj); } @@ -36043,13 +35206,13 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { float r = b.imag / b.real; - float s = 1.0 / (b.real + b.imag * r); + float s = (float)(1.0) / (b.real + b.imag * r); return __pyx_t_float_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { float r = b.real / b.imag; - float s = 1.0 / (b.imag + b.real * r); + float s = (float)(1.0) / (b.imag + b.real * r); return __pyx_t_float_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -36107,7 +35270,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { case 1: return a; case 2: - z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(a, a); case 3: z = __Pyx_c_prod_float(a, a); @@ -36129,7 +35291,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { theta = 0; } else { r = -a.real; - theta = atan2f(0, -1); + theta = atan2f(0.0, -1.0); } } else { r = __Pyx_c_abs_float(a); @@ -36198,13 +35360,13 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { double r = b.imag / b.real; - double s = 1.0 / (b.real + b.imag * r); + double s = (double)(1.0) / (b.real + b.imag * r); return __pyx_t_double_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { double r = b.real / b.imag; - double s = 1.0 / (b.imag + b.real * r); + double s = (double)(1.0) / (b.imag + b.real * r); return __pyx_t_double_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -36262,7 +35424,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { case 1: return a; case 2: - z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(a, a); case 3: z = __Pyx_c_prod_double(a, a); @@ -36284,7 +35445,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { theta = 0; } else { r = -a.real; - theta = atan2(0, -1); + theta = atan2(0.0, -1.0); } } else { r = __Pyx_c_abs_double(a); @@ -36300,37 +35461,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif #endif -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { - const enum NPY_TYPES neg_one = (enum NPY_TYPES) ((enum NPY_TYPES) 0 - (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); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(enum NPY_TYPES) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - 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); - } -} - /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) ((int) 0 - (int) 1), const_zero = (int) 0; diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index eb23de8b..92d28165 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.29.2 */ +/* Generated by Cython 0.29.21 */ #define PY_SSIZE_T_CLEAN #include "Python.h" @@ -7,8 +7,8 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) #error Cython requires Python 2.6+ or Python 3.3+. #else -#define CYTHON_ABI "0_29_2" -#define CYTHON_HEX_VERSION 0x001D02F0 +#define CYTHON_ABI "0_29_21" +#define CYTHON_HEX_VERSION 0x001D15F0 #define CYTHON_FUTURE_DIVISION 0 #include #ifndef offsetof @@ -310,8 +310,13 @@ #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else #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) +#endif #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES @@ -346,26 +351,6 @@ #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif -#if CYTHON_USE_DICT_VERSIONS -#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ - (version_var) = __PYX_GET_DICT_VERSION(dict);\ - (cache_var) = (value); -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ - static PY_UINT64_T __pyx_dict_version = 0;\ - static PyObject *__pyx_dict_cached_value = NULL;\ - if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ - (VAR) = __pyx_dict_cached_value;\ - } else {\ - (VAR) = __pyx_dict_cached_value = (LOOKUP);\ - __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ - }\ - } -#else -#define __PYX_GET_DICT_VERSION(dict) (0) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); -#endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) @@ -398,7 +383,7 @@ typedef int Py_tss_t; static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { *key = PyThread_create_key(); - return 0; // PyThread_create_key reports success always + return 0; } static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); @@ -421,7 +406,7 @@ static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { return PyThread_get_key_value(*key); } -#endif // TSS (Thread Specific Storage) API +#endif #if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) #define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) #else @@ -450,7 +435,11 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 @@ -499,8 +488,10 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode #define PyObject_Unicode PyObject_Str #endif +#endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) @@ -511,6 +502,13 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif #if CYTHON_ASSUME_SAFE_MACROS #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) #else @@ -550,7 +548,7 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : (Py_INCREF(func), func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif @@ -591,11 +589,10 @@ static CYTHON_INLINE float __PYX_NAN() { #define __Pyx_truncl truncl #endif - +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } #define __PYX_ERR(f_index, lineno, Ln_error) \ -{ \ - __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ -} + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } #ifndef __PYX_EXTERN_C #ifdef __cplusplus @@ -611,7 +608,13 @@ static CYTHON_INLINE float __PYX_NAN() { #include #include #include "numpy/arrayobject.h" +#include "numpy/ndarrayobject.h" +#include "numpy/ndarraytypes.h" +#include "numpy/arrayscalars.h" #include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + #include "pythread.h" #include #include "pystate.h" @@ -627,7 +630,8 @@ typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* enc const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize @@ -958,7 +962,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":776 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":690 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -967,7 +971,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":691 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -976,7 +980,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -985,7 +989,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":779 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":693 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -994,7 +998,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":697 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -1003,7 +1007,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":784 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":698 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -1012,7 +1016,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":785 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -1021,7 +1025,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":786 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":700 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -1030,7 +1034,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":704 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -1039,7 +1043,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":705 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -1048,7 +1052,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":800 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -1057,7 +1061,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":715 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1066,7 +1070,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":716 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1075,7 +1079,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":804 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":718 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1084,7 +1088,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":805 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":719 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1093,7 +1097,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":806 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":720 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1102,7 +1106,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":808 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":722 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1111,7 +1115,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":809 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":723 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1120,7 +1124,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":811 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":725 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1129,7 +1133,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":812 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":726 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1138,7 +1142,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":727 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1195,7 +1199,7 @@ struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":729 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1204,7 +1208,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":730 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1213,7 +1217,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":817 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":731 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1222,7 +1226,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":819 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":733 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1292,7 +1296,7 @@ struct __pyx_memoryview_obj { }; -/* "View.MemoryView":961 +/* "View.MemoryView":965 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -1343,7 +1347,7 @@ struct __pyx_vtabstruct_memoryview { static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; -/* "View.MemoryView":961 +/* "View.MemoryView":965 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< @@ -1442,6 +1446,32 @@ static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ const char* function_name); +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + /* GetModuleGlobalName.proto */ #if CYTHON_USE_DICT_VERSIONS #define __Pyx_GetModuleGlobalName(var, name) {\ @@ -1475,7 +1505,7 @@ static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObje #define __Pyx_PyFunction_FastCall(func, args, nargs)\ __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs); +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); #else #define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) #endif @@ -1581,32 +1611,6 @@ static void __Pyx_WriteUnraisable(const char *name, int clineno, int lineno, const char *filename, int full_traceback, int nogil); -/* RaiseException.proto */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); - -/* DictGetItem.proto */ -#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); -#define __Pyx_PyObject_Dict_GetItem(obj, name)\ - (likely(PyDict_CheckExact(obj)) ?\ - __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) -#else -#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) -#endif - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - -/* ExtTypeTest.proto */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); - /* GetTopmostException.proto */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); @@ -1639,6 +1643,9 @@ static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); #endif +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + /* ArgTypeTest.proto */ #define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ @@ -1725,6 +1732,18 @@ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( /* GetAttr3.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + /* SwapException.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) @@ -1758,7 +1777,7 @@ static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { if (likely(L->allocated > len)) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); - Py_SIZE(list) = len+1; + __Pyx_SET_SIZE(list, len + 1); return 0; } return PyList_Append(list, x); @@ -1769,9 +1788,9 @@ static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { /* PyIntBinop.proto */ #if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace); +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); #else -#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\ +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) #endif @@ -1796,7 +1815,7 @@ static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); - Py_SIZE(list) = len+1; + __Pyx_SET_SIZE(list, len + 1); return 0; } return PyList_Append(list, x); @@ -1831,6 +1850,9 @@ static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_nam /* SetVTable.proto */ static int __Pyx_SetVtable(PyObject *dict, void *vtable); +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + /* SetupReduce.proto */ static int __Pyx_setup_reduce(PyObject* type_obj); @@ -2042,9 +2064,6 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o #endif #endif -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); - /* MemviewSliceCopyTemplate.proto */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, @@ -2113,8 +2132,17 @@ 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_generic = 0; +static PyTypeObject *__pyx_ptype_5numpy_number = 0; +static PyTypeObject *__pyx_ptype_5numpy_integer = 0; +static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; +static PyTypeObject *__pyx_ptype_5numpy_floating = 0; +static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; +static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; +static PyTypeObject *__pyx_ptype_5numpy_character = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; -static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ /* Module declarations from 'scipy.linalg.cython_blas' */ @@ -2176,9 +2204,8 @@ 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_ImportError; +static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_TypeError; @@ -2258,7 +2285,6 @@ static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; static const char __pyx_k_ImportError[] = "ImportError"; static const char __pyx_k_MemoryError[] = "MemoryError"; static const char __pyx_k_PickleError[] = "PickleError"; -static const char __pyx_k_RuntimeError[] = "RuntimeError"; static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; static const char __pyx_k_stringsource[] = "stringsource"; static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; @@ -2286,30 +2312,24 @@ static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type ' static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; static const char __pyx_k_GPy_util_choleskies_cython[] = "GPy.util.choleskies_cython"; static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; -static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static const char __pyx_k_GPy_util_choleskies_cython_pyx[] = "GPy/util/choleskies_cython.pyx"; static const char __pyx_k_strided_and_direct_or_indirect[] = ""; static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; -static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; -static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; -static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; -static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; -static const 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; @@ -2319,8 +2339,6 @@ static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_n_s_D; static PyObject *__pyx_n_s_Ellipsis; static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_n_s_GPy_util_choleskies_cython; static PyObject *__pyx_kp_s_GPy_util_choleskies_cython_pyx; static PyObject *__pyx_n_s_ImportError; @@ -2336,11 +2354,9 @@ static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_N; -static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; static PyObject *__pyx_n_b_O; static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_PickleError; -static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_ValueError; @@ -2390,8 +2406,6 @@ static PyObject *__pyx_n_s_mm; static PyObject *__pyx_n_s_mode; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_name_2; -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_ndim; static PyObject *__pyx_n_s_new; static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; @@ -2432,7 +2446,6 @@ static PyObject *__pyx_n_s_triang_to_flat; static PyObject *__pyx_n_s_tril; 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_update; static PyObject *__pyx_n_s_xrange; @@ -2442,8 +2455,6 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ 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, __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___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 */ @@ -2503,7 +2514,7 @@ static PyObject *__pyx_tuple__6; static PyObject *__pyx_tuple__7; static PyObject *__pyx_tuple__8; static PyObject *__pyx_tuple__9; -static PyObject *__pyx_slice__22; +static PyObject *__pyx_slice__17; static PyObject *__pyx_tuple__10; static PyObject *__pyx_tuple__11; static PyObject *__pyx_tuple__12; @@ -2511,31 +2522,26 @@ static PyObject *__pyx_tuple__13; static PyObject *__pyx_tuple__14; static PyObject *__pyx_tuple__15; static PyObject *__pyx_tuple__16; -static PyObject *__pyx_tuple__17; static PyObject *__pyx_tuple__18; static PyObject *__pyx_tuple__19; static PyObject *__pyx_tuple__20; static PyObject *__pyx_tuple__21; static PyObject *__pyx_tuple__23; -static PyObject *__pyx_tuple__24; static PyObject *__pyx_tuple__25; -static PyObject *__pyx_tuple__26; -static PyObject *__pyx_tuple__28; -static PyObject *__pyx_tuple__30; +static PyObject *__pyx_tuple__27; +static PyObject *__pyx_tuple__29; +static PyObject *__pyx_tuple__31; static PyObject *__pyx_tuple__32; +static PyObject *__pyx_tuple__33; static PyObject *__pyx_tuple__34; +static PyObject *__pyx_tuple__35; static PyObject *__pyx_tuple__36; -static PyObject *__pyx_tuple__37; -static PyObject *__pyx_tuple__38; -static PyObject *__pyx_tuple__39; -static PyObject *__pyx_tuple__40; -static PyObject *__pyx_tuple__41; -static PyObject *__pyx_codeobj__27; -static PyObject *__pyx_codeobj__29; -static PyObject *__pyx_codeobj__31; -static PyObject *__pyx_codeobj__33; -static PyObject *__pyx_codeobj__35; -static PyObject *__pyx_codeobj__42; +static PyObject *__pyx_codeobj__22; +static PyObject *__pyx_codeobj__24; +static PyObject *__pyx_codeobj__26; +static PyObject *__pyx_codeobj__28; +static PyObject *__pyx_codeobj__30; +static PyObject *__pyx_codeobj__37; /* Late includes */ /* "GPy/util/choleskies_cython.pyx":14 @@ -2548,11 +2554,14 @@ static PyObject *__pyx_codeobj__42; /* Python wrapper */ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -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 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)(void*)(PyCFunctionWithKeywords)__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) { __Pyx_memviewslice __pyx_v_flat = { 0, 0, { 0 }, { 0 }, { 0 } }; int __pyx_v_M; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("flat_to_triang (wrapper)", 0); @@ -2640,6 +2649,9 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U Py_ssize_t __pyx_t_19; Py_ssize_t __pyx_t_20; Py_ssize_t __pyx_t_21; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("flat_to_triang", 0); /* "GPy/util/choleskies_cython.pyx":21 @@ -2885,6 +2897,9 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_3triang_to_flat(PyObjec static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_3triang_to_flat = {"triang_to_flat", (PyCFunction)__pyx_pw_3GPy_4util_17choleskies_cython_3triang_to_flat, METH_O, 0}; static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_3triang_to_flat(PyObject *__pyx_self, PyObject *__pyx_arg_L) { __Pyx_memviewslice __pyx_v_L = { 0, 0, { 0 }, { 0 }, { 0 } }; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("triang_to_flat (wrapper)", 0); @@ -2935,6 +2950,9 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ Py_ssize_t __pyx_t_18; Py_ssize_t __pyx_t_19; Py_ssize_t __pyx_t_20; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("triang_to_flat", 0); /* "GPy/util/choleskies_cython.pyx":36 @@ -2942,7 +2960,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * 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 N = M*(M+1)//2 */ __pyx_v_D = (__pyx_v_L.shape[0]); @@ -2950,7 +2968,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * 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 N = M*(M+1)//2 * cdef int count = 0 */ __pyx_v_M = (__pyx_v_L.shape[1]); @@ -2958,7 +2976,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":38 * cdef int D = L.shape[0] * cdef int M = L.shape[1] - * cdef int N = M*(M+1)/2 # <<<<<<<<<<<<<< + * cdef int N = M*(M+1)//2 # <<<<<<<<<<<<<< * cdef int count = 0 * cdef double[:, ::1] flat = np.empty((N, D)) */ @@ -2966,7 +2984,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":39 * cdef int M = L.shape[1] - * cdef int N = M*(M+1)/2 + * cdef int N = M*(M+1)//2 * cdef int count = 0 # <<<<<<<<<<<<<< * cdef double[:, ::1] flat = np.empty((N, D)) * cdef int d, m, mm @@ -2974,7 +2992,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_v_count = 0; /* "GPy/util/choleskies_cython.pyx":40 - * cdef int N = M*(M+1)/2 + * cdef int N = M*(M+1)//2 * cdef int count = 0 * cdef double[:, ::1] flat = np.empty((N, D)) # <<<<<<<<<<<<<< * cdef int d, m, mm @@ -3184,6 +3202,9 @@ static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_5backprop_gradient static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_5backprop_gradient(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { __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; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("backprop_gradient (wrapper)", 0); @@ -3266,26 +3287,9 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH Py_ssize_t __pyx_t_16; Py_ssize_t __pyx_t_17; 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; - Py_ssize_t __pyx_t_29; - Py_ssize_t __pyx_t_30; - Py_ssize_t __pyx_t_31; - Py_ssize_t __pyx_t_32; - Py_ssize_t __pyx_t_33; - Py_ssize_t __pyx_t_34; - Py_ssize_t __pyx_t_35; - Py_ssize_t __pyx_t_36; - Py_ssize_t __pyx_t_37; - Py_ssize_t __pyx_t_38; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("backprop_gradient", 0); /* "GPy/util/choleskies_cython.pyx":52 @@ -3410,19 +3414,19 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH * for j in range(k + 1, N): * dL_dK[j, k] /= L[k, k] */ - __pyx_t_19 = __pyx_v_i; - __pyx_t_20 = __pyx_v_j; - 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]; - __pyx_t_21 = __pyx_v_i; - __pyx_t_22 = __pyx_v_k; - if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_L.shape[0]; - if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_L.shape[1]; - __pyx_t_23 = __pyx_v_j; - __pyx_t_24 = __pyx_v_k; - if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_23 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_24)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_19 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_20)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_21 * __pyx_v_L.strides[0]) ) + __pyx_t_22 * __pyx_v_L.strides[1]) )))); + __pyx_t_16 = __pyx_v_i; + __pyx_t_15 = __pyx_v_j; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_dL_dK.shape[1]; + __pyx_t_14 = __pyx_v_i; + __pyx_t_13 = __pyx_v_k; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[0]; + if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_v_L.shape[1]; + __pyx_t_18 = __pyx_v_j; + __pyx_t_17 = __pyx_v_k; + if (__pyx_t_18 < 0) __pyx_t_18 += __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_18 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_17)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_16 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_15)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_14 * __pyx_v_L.strides[0]) ) + __pyx_t_13 * __pyx_v_L.strides[1]) )))); } } @@ -3445,15 +3449,15 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] * dL_dK[k, k] /= (2. * L[k, k]) */ - __pyx_t_25 = __pyx_v_k; - __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_j; - __pyx_t_28 = __pyx_v_k; - if (__pyx_t_27 < 0) __pyx_t_27 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_27 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_28)) )) /= (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_25 * __pyx_v_L.strides[0]) ) + __pyx_t_26 * __pyx_v_L.strides[1]) ))); + __pyx_t_13 = __pyx_v_k; + __pyx_t_14 = __pyx_v_k; + if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_v_L.shape[0]; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[1]; + __pyx_t_15 = __pyx_v_j; + __pyx_t_16 = __pyx_v_k; + 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]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_15 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_16)) )) /= (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_13 * __pyx_v_L.strides[0]) ) + __pyx_t_14 * __pyx_v_L.strides[1]) ))); /* "GPy/util/choleskies_cython.pyx":63 * for j in range(k + 1, N): @@ -3462,19 +3466,19 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK */ - __pyx_t_29 = __pyx_v_j; - __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_j; - __pyx_t_32 = __pyx_v_k; - if (__pyx_t_31 < 0) __pyx_t_31 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_v_dL_dK.shape[1]; - __pyx_t_33 = __pyx_v_k; - __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]; - *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_33 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_34)) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_29 * __pyx_v_L.strides[0]) ) + __pyx_t_30 * __pyx_v_L.strides[1]) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_31 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_32)) )))); + __pyx_t_14 = __pyx_v_j; + __pyx_t_13 = __pyx_v_k; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[0]; + if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_v_L.shape[1]; + __pyx_t_16 = __pyx_v_j; + __pyx_t_15 = __pyx_v_k; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_dL_dK.shape[1]; + __pyx_t_17 = __pyx_v_k; + __pyx_t_18 = __pyx_v_k; + if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_17 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_18)) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_14 * __pyx_v_L.strides[0]) ) + __pyx_t_13 * __pyx_v_L.strides[1]) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_16 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_15)) )))); } /* "GPy/util/choleskies_cython.pyx":64 @@ -3484,15 +3488,15 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH * return dL_dK * */ - __pyx_t_35 = __pyx_v_k; - __pyx_t_36 = __pyx_v_k; - if (__pyx_t_35 < 0) __pyx_t_35 += __pyx_v_L.shape[0]; - if (__pyx_t_36 < 0) __pyx_t_36 += __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 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_37 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_38)) )) /= (2. * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_35 * __pyx_v_L.strides[0]) ) + __pyx_t_36 * __pyx_v_L.strides[1]) )))); + __pyx_t_15 = __pyx_v_k; + __pyx_t_16 = __pyx_v_k; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_L.shape[0]; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_L.shape[1]; + __pyx_t_13 = __pyx_v_k; + __pyx_t_14 = __pyx_v_k; + if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_13 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_14)) )) /= (2. * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_15 * __pyx_v_L.strides[0]) ) + __pyx_t_16 * __pyx_v_L.strides[1]) )))); } } @@ -3569,6 +3573,9 @@ static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_7backprop_gradient_ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_7backprop_gradient_par(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { __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; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("backprop_gradient_par (wrapper)", 0); @@ -3654,26 +3661,9 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( Py_ssize_t __pyx_t_19; int __pyx_t_20; int __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; - Py_ssize_t __pyx_t_29; - Py_ssize_t __pyx_t_30; - Py_ssize_t __pyx_t_31; - Py_ssize_t __pyx_t_32; - Py_ssize_t __pyx_t_33; - Py_ssize_t __pyx_t_34; - Py_ssize_t __pyx_t_35; - Py_ssize_t __pyx_t_36; - Py_ssize_t __pyx_t_37; - Py_ssize_t __pyx_t_38; - Py_ssize_t __pyx_t_39; - Py_ssize_t __pyx_t_40; - Py_ssize_t __pyx_t_41; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("backprop_gradient_par", 0); /* "GPy/util/choleskies_cython.pyx":68 @@ -3761,7 +3751,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( #define unlikely(x) (x) #endif #ifdef _OPENMP - #pragma omp parallel private(__pyx_t_10, __pyx_t_11, __pyx_t_12, __pyx_t_13, __pyx_t_14, __pyx_t_15, __pyx_t_16, __pyx_t_17, __pyx_t_18, __pyx_t_19, __pyx_t_20, __pyx_t_21, __pyx_t_22, __pyx_t_23, __pyx_t_24, __pyx_t_25, __pyx_t_26, __pyx_t_27, __pyx_t_7, __pyx_t_8, __pyx_t_9) + #pragma omp parallel private(__pyx_t_10, __pyx_t_11, __pyx_t_12, __pyx_t_13, __pyx_t_14, __pyx_t_15, __pyx_t_16, __pyx_t_17, __pyx_t_18, __pyx_t_19, __pyx_t_20, __pyx_t_21, __pyx_t_7, __pyx_t_8, __pyx_t_9) #endif /* _OPENMP */ { @@ -3774,7 +3764,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( */ __pyx_t_7 = (__pyx_v_k + 1); __pyx_t_8 = __pyx_v_N; - if (1 == 0) abort(); + if ((1 == 0)) abort(); { __pyx_t_10 = (__pyx_t_8 - __pyx_t_7 + 1 - 1/abs(1)) / 1; if (__pyx_t_10 > 0) @@ -3841,19 +3831,19 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( * 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 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_26 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_27)) )) -= ((*((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 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_24 * __pyx_v_L.strides[0]) ) + __pyx_t_25 * __pyx_v_L.strides[1]) )))); + __pyx_t_17 = __pyx_v_j; + __pyx_t_16 = __pyx_v_i; + if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL_dK.shape[1]; + __pyx_t_15 = __pyx_v_j; + __pyx_t_14 = __pyx_v_k; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_L.shape[0]; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[1]; + __pyx_t_19 = __pyx_v_i; + __pyx_t_18 = __pyx_v_k; + if (__pyx_t_19 < 0) __pyx_t_19 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_v_dL_dK.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_19 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_18)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_17 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_16)) ))) * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_15 * __pyx_v_L.strides[0]) ) + __pyx_t_14 * __pyx_v_L.strides[1]) )))); } } } @@ -3887,15 +3877,15 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( * dL_dK[k, k] -= L[j, k] * dL_dK[j, k] * dL_dK[k, k] /= (2. * L[k, k]) */ - __pyx_t_28 = __pyx_v_k; - __pyx_t_29 = __pyx_v_k; - if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_L.shape[0]; - if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_v_L.shape[1]; - __pyx_t_30 = __pyx_v_j; - __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_28 * __pyx_v_L.strides[0]) ) + __pyx_t_29 * __pyx_v_L.strides[1]) ))); + __pyx_t_14 = __pyx_v_k; + __pyx_t_15 = __pyx_v_k; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[0]; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_L.shape[1]; + __pyx_t_16 = __pyx_v_j; + __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 */ (( /* 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":81 * for j in range(k + 1, N): @@ -3904,19 +3894,19 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK */ - __pyx_t_32 = __pyx_v_j; - __pyx_t_33 = __pyx_v_k; - if (__pyx_t_32 < 0) __pyx_t_32 += __pyx_v_L.shape[0]; - if (__pyx_t_33 < 0) __pyx_t_33 += __pyx_v_L.shape[1]; - __pyx_t_34 = __pyx_v_j; - __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]; - __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)) )) -= ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_32 * __pyx_v_L.strides[0]) ) + __pyx_t_33 * __pyx_v_L.strides[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)) )))); + __pyx_t_15 = __pyx_v_j; + __pyx_t_14 = __pyx_v_k; + if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_L.shape[0]; + if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_v_L.shape[1]; + __pyx_t_17 = __pyx_v_j; + __pyx_t_16 = __pyx_v_k; + if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL_dK.shape[1]; + __pyx_t_18 = __pyx_v_k; + __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 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_15 * __pyx_v_L.strides[0]) ) + __pyx_t_14 * __pyx_v_L.strides[1]) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_17 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_16)) )))); } /* "GPy/util/choleskies_cython.pyx":82 @@ -3926,15 +3916,15 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( * return dL_dK * */ - __pyx_t_38 = __pyx_v_k; - __pyx_t_39 = __pyx_v_k; - if (__pyx_t_38 < 0) __pyx_t_38 += __pyx_v_L.shape[0]; - if (__pyx_t_39 < 0) __pyx_t_39 += __pyx_v_L.shape[1]; - __pyx_t_40 = __pyx_v_k; - __pyx_t_41 = __pyx_v_k; - if (__pyx_t_40 < 0) __pyx_t_40 += __pyx_v_dL_dK.shape[0]; - if (__pyx_t_41 < 0) __pyx_t_41 += __pyx_v_dL_dK.shape[1]; - *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_40 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_41)) )) /= (2. * (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_L.data + __pyx_t_38 * __pyx_v_L.strides[0]) ) + __pyx_t_39 * __pyx_v_L.strides[1]) )))); + __pyx_t_16 = __pyx_v_k; + __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_14 = __pyx_v_k; + __pyx_t_15 = __pyx_v_k; + 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]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL_dK.data + __pyx_t_14 * __pyx_v_dL_dK.strides[0]) )) + __pyx_t_15)) )) /= (2. * (*((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]) )))); } } @@ -4020,34 +4010,13 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, int __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; - long __pyx_t_12; - long __pyx_t_13; - int __pyx_t_14; - Py_ssize_t __pyx_t_15; - Py_ssize_t __pyx_t_16; - Py_ssize_t __pyx_t_17; - 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; - double __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; - Py_ssize_t __pyx_t_29; - Py_ssize_t __pyx_t_30; - Py_ssize_t __pyx_t_31; - Py_ssize_t __pyx_t_32; - Py_ssize_t __pyx_t_33; - Py_ssize_t __pyx_t_34; - Py_ssize_t __pyx_t_35; + long __pyx_t_8; + long __pyx_t_9; + int __pyx_t_10; + double __pyx_t_11; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; /* "GPy/util/choleskies_cython.pyx":89 * @@ -4111,14 +4080,14 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * 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]; + __pyx_t_2 = (__pyx_v_k + 1); + __pyx_t_1 = (__pyx_v_k + 1); + if (__pyx_t_2 < 0) __pyx_t_2 += __pyx_v_dL.shape[0]; + if (__pyx_t_1 < 0) __pyx_t_1 += __pyx_v_dL.shape[1]; + __pyx_t_4 = (__pyx_v_k + 1); + __pyx_t_3 = __pyx_v_k; + if (__pyx_t_4 < 0) __pyx_t_4 += __pyx_v_L.shape[0]; + if (__pyx_t_3 < 0) __pyx_t_3 += __pyx_v_L.shape[1]; /* "GPy/util/choleskies_cython.pyx":99 * n = N-k-1 @@ -4127,10 +4096,10 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_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]; + __pyx_t_6 = (__pyx_v_k + 1); + __pyx_t_7 = __pyx_v_k; + 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]; /* "GPy/util/choleskies_cython.pyx":98 * for k in range(N-2, -1, -1): @@ -4139,7 +4108,7 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * beta=&beta, y=&dL[k + 1, k], incy=&N) * */ - __pyx_f_5scipy_6linalg_11cython_blas_dsymv(((char *)"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)); + __pyx_f_5scipy_6linalg_11cython_blas_dsymv(((char *)"u"), (&__pyx_v_n), (&__pyx_v_alpha), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_2 * __pyx_v_dL.strides[0]) )) + __pyx_t_1)) )))), (&__pyx_v_N), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_4 * __pyx_v_L.strides[0]) )) + __pyx_t_3)) )))), (&__pyx_v_incx), (&__pyx_v_beta), (&(*((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)); /* "GPy/util/choleskies_cython.pyx":101 * beta=&beta, y=&dL[k + 1, k], incy=&N) @@ -4148,10 +4117,10 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * 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); - __pyx_t_13 = __pyx_t_12; - for (__pyx_t_14 = 0; __pyx_t_14 < __pyx_t_13; __pyx_t_14+=1) { - __pyx_v_i = __pyx_t_14; + __pyx_t_8 = ((__pyx_v_N - __pyx_v_k) - 1); + __pyx_t_9 = __pyx_t_8; + for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { + __pyx_v_i = __pyx_t_10; /* "GPy/util/choleskies_cython.pyx":102 * @@ -4160,19 +4129,19 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * * scale = 1.0 / L[k, k] */ - __pyx_t_15 = ((__pyx_v_k + __pyx_v_i) + 1); - __pyx_t_16 = ((__pyx_v_k + __pyx_v_i) + 1); - if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_v_dL.shape[0]; - if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_v_dL.shape[1]; - __pyx_t_17 = ((__pyx_v_k + 1) + __pyx_v_i); - __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_k + 1) + __pyx_v_i); - __pyx_t_20 = __pyx_v_k; - if (__pyx_t_19 < 0) __pyx_t_19 += __pyx_v_dL.shape[0]; - if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_dL.shape[1]; - *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_19 * __pyx_v_dL.strides[0]) )) + __pyx_t_20)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_15 * __pyx_v_dL.strides[0]) )) + __pyx_t_16)) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_17 * __pyx_v_L.strides[0]) )) + __pyx_t_18)) )))); + __pyx_t_7 = ((__pyx_v_k + __pyx_v_i) + 1); + __pyx_t_6 = ((__pyx_v_k + __pyx_v_i) + 1); + if (__pyx_t_7 < 0) __pyx_t_7 += __pyx_v_dL.shape[0]; + if (__pyx_t_6 < 0) __pyx_t_6 += __pyx_v_dL.shape[1]; + __pyx_t_3 = ((__pyx_v_k + 1) + __pyx_v_i); + __pyx_t_4 = __pyx_v_k; + if (__pyx_t_3 < 0) __pyx_t_3 += __pyx_v_L.shape[0]; + if (__pyx_t_4 < 0) __pyx_t_4 += __pyx_v_L.shape[1]; + __pyx_t_1 = ((__pyx_v_k + 1) + __pyx_v_i); + __pyx_t_2 = __pyx_v_k; + if (__pyx_t_1 < 0) __pyx_t_1 += __pyx_v_dL.shape[0]; + if (__pyx_t_2 < 0) __pyx_t_2 += __pyx_v_dL.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_1 * __pyx_v_dL.strides[0]) )) + __pyx_t_2)) )) -= ((*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_7 * __pyx_v_dL.strides[0]) )) + __pyx_t_6)) ))) * (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_3 * __pyx_v_L.strides[0]) )) + __pyx_t_4)) )))); } /* "GPy/util/choleskies_cython.pyx":104 @@ -4182,12 +4151,12 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * cblas.dscal(&n, &scale , &dL[k + 1, k], &N) * # */ - __pyx_t_21 = __pyx_v_k; - __pyx_t_22 = __pyx_v_k; - if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_L.shape[0]; - if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_L.shape[1]; - __pyx_t_23 = (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_21 * __pyx_v_L.strides[0]) )) + __pyx_t_22)) ))); - if (unlikely(__pyx_t_23 == 0)) { + __pyx_t_4 = __pyx_v_k; + __pyx_t_3 = __pyx_v_k; + if (__pyx_t_4 < 0) __pyx_t_4 += __pyx_v_L.shape[0]; + if (__pyx_t_3 < 0) __pyx_t_3 += __pyx_v_L.shape[1]; + __pyx_t_11 = (*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_4 * __pyx_v_L.strides[0]) )) + __pyx_t_3)) ))); + if (unlikely(__pyx_t_11 == 0)) { #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif @@ -4197,7 +4166,7 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, #endif __PYX_ERR(0, 104, __pyx_L1_error) } - __pyx_v_scale = (1.0 / __pyx_t_23); + __pyx_v_scale = (1.0 / __pyx_t_11); /* "GPy/util/choleskies_cython.pyx":105 * @@ -4206,11 +4175,11 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * # * dL[k, k] -= cblas.ddot(&n, &dL[k + 1, k], &N, &L[k+1, k], &incx) */ - __pyx_t_24 = (__pyx_v_k + 1); 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+ __pyx_t_3 = __pyx_v_k; + if (__pyx_t_4 < 0) __pyx_t_4 += __pyx_v_dL.shape[0]; + if (__pyx_t_3 < 0) __pyx_t_3 += __pyx_v_dL.shape[1]; + __pyx_t_6 = (__pyx_v_k + 1); + __pyx_t_7 = __pyx_v_k; + if (__pyx_t_6 < 0) __pyx_t_6 += __pyx_v_L.shape[0]; + if (__pyx_t_7 < 0) __pyx_t_7 += __pyx_v_L.shape[1]; + __pyx_t_2 = __pyx_v_k; + __pyx_t_1 = __pyx_v_k; + if (__pyx_t_2 < 0) __pyx_t_2 += __pyx_v_dL.shape[0]; + if (__pyx_t_1 < 0) __pyx_t_1 += __pyx_v_dL.shape[1]; + *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_2 * __pyx_v_dL.strides[0]) )) + __pyx_t_1)) )) -= __pyx_f_5scipy_6linalg_11cython_blas_ddot((&__pyx_v_n), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_dL.data + __pyx_t_4 * __pyx_v_dL.strides[0]) )) + __pyx_t_3)) )))), (&__pyx_v_N), (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_L.data + __pyx_t_6 * __pyx_v_L.strides[0]) )) + __pyx_t_7)) )))), (&__pyx_v_incx)); /* "GPy/util/choleskies_cython.pyx":108 * # @@ -4240,15 +4209,15 @@ static void __pyx_f_3GPy_4util_17choleskies_cython_chol_backprop(int __pyx_v_N, * * def backprop_gradient_par_c(double[:, :] dL, double[:, :] L): */ - __pyx_t_32 = __pyx_v_k; 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goto __pyx_L0; - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1026 + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":935 * PyArray_SetBaseObject(arr, base) * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -6567,12 +4955,12 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py return __pyx_r; } -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1034 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":943 * # Versions of the import_* functions which are more suitable for * # Cython code. * cdef inline int import_array() except -1: # <<<<<<<<<<<<<< * try: - * _import_array() + * __pyx_import_array() */ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { @@ -6586,13 +4974,16 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { PyObject *__pyx_t_6 = NULL; PyObject *__pyx_t_7 = NULL; PyObject *__pyx_t_8 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("import_array", 0); - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1035 + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":944 * # Cython code. * cdef inline int import_array() except -1: * try: # <<<<<<<<<<<<<< - * _import_array() + * __pyx_import_array() * except Exception: */ { @@ -6604,20 +4995,20 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { __Pyx_XGOTREF(__pyx_t_3); /*try:*/ { - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1036 + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":945 * cdef inline int import_array() except -1: * try: - * _import_array() # <<<<<<<<<<<<<< + * __pyx_import_array() # <<<<<<<<<<<<<< * except Exception: * raise ImportError("numpy.core.multiarray failed to import") */ - __pyx_t_4 = _import_array(); 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} -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1040 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":949 * raise ImportError("numpy.core.multiarray failed to import") * * cdef inline int import_umath() except -1: # <<<<<<<<<<<<<< @@ -6715,9 +5106,12 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { PyObject *__pyx_t_6 = NULL; PyObject *__pyx_t_7 = NULL; PyObject *__pyx_t_8 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("import_umath", 0); - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1041 + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":950 * * cdef inline int import_umath() except -1: * try: # <<<<<<<<<<<<<< @@ -6733,16 +5127,16 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { __Pyx_XGOTREF(__pyx_t_3); /*try:*/ { - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1042 + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":951 * cdef inline int import_umath() except -1: * try: * _import_umath() # <<<<<<<<<<<<<< * except Exception: * raise ImportError("numpy.core.umath failed to import") */ - __pyx_t_4 = _import_umath(); 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} - /* "View.MemoryView":378 + /* "View.MemoryView":375 + * if self.obj is not None: + * __Pyx_ReleaseBuffer(&self.view) + * elif (<__pyx_buffer *> &self.view).obj == Py_None: # <<<<<<<<<<<<<< + * + * (<__pyx_buffer *> &self.view).obj = NULL + */ + __pyx_t_2 = ((((Py_buffer *)(&__pyx_v_self->view))->obj == Py_None) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":377 + * elif (<__pyx_buffer *> &self.view).obj == Py_None: + * + * (<__pyx_buffer *> &self.view).obj = NULL # <<<<<<<<<<<<<< + * Py_DECREF(Py_None) + * + */ + ((Py_buffer *)(&__pyx_v_self->view))->obj = NULL; + + /* "View.MemoryView":378 + * + * (<__pyx_buffer *> &self.view).obj = NULL + * Py_DECREF(Py_None) # <<<<<<<<<<<<<< + * + * cdef int i + */ + Py_DECREF(Py_None); + + /* "View.MemoryView":375 + * if self.obj is not None: + * __Pyx_ReleaseBuffer(&self.view) + * elif (<__pyx_buffer *> &self.view).obj == Py_None: # <<<<<<<<<<<<<< + * + * (<__pyx_buffer *> &self.view).obj = NULL + */ + } + __pyx_L3:; + + /* "View.MemoryView":382 * cdef int i * global __pyx_memoryview_thread_locks_used * if self.lock != NULL: # <<<<<<<<<<<<<< @@ -9742,7 +8403,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_2 = ((__pyx_v_self->lock != NULL) != 0); if (__pyx_t_2) { - /* "View.MemoryView":379 + /* "View.MemoryView":383 * global __pyx_memoryview_thread_locks_used * if self.lock != NULL: * for i in range(__pyx_memoryview_thread_locks_used): # <<<<<<<<<<<<<< @@ -9754,7 +8415,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "View.MemoryView":380 + /* "View.MemoryView":384 * if self.lock != NULL: * for i in range(__pyx_memoryview_thread_locks_used): * if __pyx_memoryview_thread_locks[i] is self.lock: # <<<<<<<<<<<<<< @@ -9764,7 +8425,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_2 = (((__pyx_memoryview_thread_locks[__pyx_v_i]) == __pyx_v_self->lock) != 0); if (__pyx_t_2) { - /* "View.MemoryView":381 + /* "View.MemoryView":385 * for i in range(__pyx_memoryview_thread_locks_used): * if __pyx_memoryview_thread_locks[i] is self.lock: * __pyx_memoryview_thread_locks_used -= 1 # <<<<<<<<<<<<<< @@ -9773,7 +8434,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal */ __pyx_memoryview_thread_locks_used = (__pyx_memoryview_thread_locks_used - 1); - /* "View.MemoryView":382 + /* "View.MemoryView":386 * if __pyx_memoryview_thread_locks[i] is self.lock: * __pyx_memoryview_thread_locks_used -= 1 * if i != __pyx_memoryview_thread_locks_used: # <<<<<<<<<<<<<< @@ -9783,7 +8444,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_2 = ((__pyx_v_i != __pyx_memoryview_thread_locks_used) != 0); if (__pyx_t_2) { - /* "View.MemoryView":384 + /* "View.MemoryView":388 * if i != __pyx_memoryview_thread_locks_used: * __pyx_memoryview_thread_locks[i], __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used] = ( * __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used], __pyx_memoryview_thread_locks[i]) # <<<<<<<<<<<<<< @@ -9793,7 +8454,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal __pyx_t_6 = (__pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used]); __pyx_t_7 = (__pyx_memoryview_thread_locks[__pyx_v_i]); - /* "View.MemoryView":383 + /* "View.MemoryView":387 * __pyx_memoryview_thread_locks_used -= 1 * if i != __pyx_memoryview_thread_locks_used: * __pyx_memoryview_thread_locks[i], __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used] = ( # <<<<<<<<<<<<<< @@ -9803,7 +8464,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal (__pyx_memoryview_thread_locks[__pyx_v_i]) = __pyx_t_6; (__pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used]) = __pyx_t_7; - /* "View.MemoryView":382 + /* "View.MemoryView":386 * if __pyx_memoryview_thread_locks[i] is self.lock: * __pyx_memoryview_thread_locks_used -= 1 * if i != __pyx_memoryview_thread_locks_used: # <<<<<<<<<<<<<< @@ -9812,7 +8473,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal */ } - /* "View.MemoryView":385 + /* "View.MemoryView":389 * __pyx_memoryview_thread_locks[i], __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used] = ( * __pyx_memoryview_thread_locks[__pyx_memoryview_thread_locks_used], __pyx_memoryview_thread_locks[i]) * break # <<<<<<<<<<<<<< @@ -9821,7 +8482,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal */ goto __pyx_L6_break; - /* "View.MemoryView":380 + /* "View.MemoryView":384 * if self.lock != NULL: * for i in range(__pyx_memoryview_thread_locks_used): * if __pyx_memoryview_thread_locks[i] is self.lock: # <<<<<<<<<<<<<< @@ -9832,7 +8493,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal } /*else*/ { - /* "View.MemoryView":387 + /* "View.MemoryView":391 * break * else: * PyThread_free_lock(self.lock) # <<<<<<<<<<<<<< @@ -9843,7 +8504,7 @@ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__deal } __pyx_L6_break:; 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__Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PyList_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 397, __pyx_L1_error) #else - __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 397, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); #endif } else { if (__pyx_t_3 >= PyTuple_GET_SIZE(__pyx_t_2)) break; #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - __pyx_t_5 = PyTuple_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PyTuple_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_5); __pyx_t_3++; if (unlikely(0 < 0)) __PYX_ERR(2, 397, __pyx_L1_error) #else - __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 393, __pyx_L1_error) + __pyx_t_5 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 397, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); #endif } @@ -9937,7 +8601,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py PyObject* exc_type = PyErr_Occurred(); if (exc_type) { if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) PyErr_Clear(); - else __PYX_ERR(2, 393, __pyx_L1_error) + else __PYX_ERR(2, 397, __pyx_L1_error) } break; } @@ -9948,18 +8612,18 @@ 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":394 + /* "View.MemoryView":398 * * 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_ERR(2, 394, __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 == ((char *)NULL))) __PYX_ERR(2, 394, __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_ERR(2, 398, __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 == ((char *)NULL))) __PYX_ERR(2, 398, __pyx_L1_error) __pyx_v_itemp = __pyx_t_7; - /* "View.MemoryView":393 + /* "View.MemoryView":397 * cdef char *itemp = self.view.buf * * for dim, idx in enumerate(index): # <<<<<<<<<<<<<< @@ -9969,7 +8633,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py } __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "View.MemoryView":396 + /* "View.MemoryView":400 * itemp = pybuffer_index(&self.view, itemp, idx, dim) * * return itemp # <<<<<<<<<<<<<< @@ -9979,7 +8643,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py __pyx_r = __pyx_v_itemp; goto __pyx_L0; - /* "View.MemoryView":389 + /* "View.MemoryView":393 * PyThread_free_lock(self.lock) * * cdef char *get_item_pointer(memoryview self, object index) except NULL: # <<<<<<<<<<<<<< @@ -9999,7 +8663,7 @@ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__py return __pyx_r; } -/* "View.MemoryView":399 +/* "View.MemoryView":403 * * * def __getitem__(memoryview self, object index): # <<<<<<<<<<<<<< @@ -10032,9 +8696,12 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ PyObject *__pyx_t_4 = NULL; PyObject *__pyx_t_5 = NULL; char *__pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__getitem__", 0); - /* "View.MemoryView":400 + /* "View.MemoryView":404 * * def __getitem__(memoryview self, object index): * if index is Ellipsis: # <<<<<<<<<<<<<< @@ -10045,7 +8712,7 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":401 + /* "View.MemoryView":405 * def __getitem__(memoryview self, object index): * if index is Ellipsis: * return self # <<<<<<<<<<<<<< @@ -10057,7 +8724,7 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ __pyx_r = ((PyObject *)__pyx_v_self); goto __pyx_L0; - /* "View.MemoryView":400 + /* "View.MemoryView":404 * * def __getitem__(memoryview self, object index): * if index is Ellipsis: # <<<<<<<<<<<<<< @@ -10066,14 +8733,14 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ */ } - /* "View.MemoryView":403 + /* "View.MemoryView":407 * return self * * have_slices, indices = _unellipsify(index, self.view.ndim) # <<<<<<<<<<<<<< * * cdef char *itemp */ - __pyx_t_3 = _unellipsify(__pyx_v_index, __pyx_v_self->view.ndim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 403, __pyx_L1_error) + __pyx_t_3 = _unellipsify(__pyx_v_index, __pyx_v_self->view.ndim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 407, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); if (likely(__pyx_t_3 != Py_None)) { PyObject* sequence = __pyx_t_3; @@ -10081,7 +8748,7 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ if (unlikely(size != 2)) { if (size > 2) __Pyx_RaiseTooManyValuesError(2); else if (size >= 0) __Pyx_RaiseNeedMoreValuesError(size); - __PYX_ERR(2, 403, __pyx_L1_error) + __PYX_ERR(2, 407, __pyx_L1_error) } #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS __pyx_t_4 = PyTuple_GET_ITEM(sequence, 0); @@ -10089,31 +8756,31 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ __Pyx_INCREF(__pyx_t_4); __Pyx_INCREF(__pyx_t_5); #else - __pyx_t_4 = PySequence_ITEM(sequence, 0); if (unlikely(!__pyx_t_4)) __PYX_ERR(2, 403, __pyx_L1_error) + __pyx_t_4 = PySequence_ITEM(sequence, 0); if (unlikely(!__pyx_t_4)) __PYX_ERR(2, 407, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); - __pyx_t_5 = PySequence_ITEM(sequence, 1); if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 403, __pyx_L1_error) + __pyx_t_5 = PySequence_ITEM(sequence, 1); if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 407, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); #endif __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; } else { - __Pyx_RaiseNoneNotIterableError(); __PYX_ERR(2, 403, __pyx_L1_error) + __Pyx_RaiseNoneNotIterableError(); __PYX_ERR(2, 407, __pyx_L1_error) } __pyx_v_have_slices = __pyx_t_4; __pyx_t_4 = 0; __pyx_v_indices = __pyx_t_5; __pyx_t_5 = 0; - /* "View.MemoryView":406 + /* "View.MemoryView":410 * * cdef char *itemp * if have_slices: # <<<<<<<<<<<<<< * return memview_slice(self, indices) * else: */ - __pyx_t_2 = __Pyx_PyObject_IsTrue(__pyx_v_have_slices); if (unlikely(__pyx_t_2 < 0)) __PYX_ERR(2, 406, __pyx_L1_error) + __pyx_t_2 = __Pyx_PyObject_IsTrue(__pyx_v_have_slices); if (unlikely(__pyx_t_2 < 0)) __PYX_ERR(2, 410, __pyx_L1_error) if (__pyx_t_2) { - /* "View.MemoryView":407 + /* "View.MemoryView":411 * cdef char *itemp * if have_slices: * return memview_slice(self, indices) # <<<<<<<<<<<<<< @@ -10121,13 +8788,13 @@ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4_ * itemp = self.get_item_pointer(indices) */ __Pyx_XDECREF(__pyx_r); 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if (unlikely(!__pyx_t_7)) __PYX_ERR(2, 431, __pyx_L4_error) + __pyx_t_7 = __Pyx_PyBool_FromLong(__pyx_v_self->dtype_is_object); if (unlikely(!__pyx_t_7)) __PYX_ERR(2, 435, __pyx_L4_error) __Pyx_GOTREF(__pyx_t_7); - /* "View.MemoryView":430 + /* "View.MemoryView":434 * if not isinstance(obj, memoryview): * try: * obj = memoryview(obj, self.flags & ~PyBUF_WRITABLE | PyBUF_ANY_CONTIGUOUS, # <<<<<<<<<<<<<< * self.dtype_is_object) * except TypeError: */ - __pyx_t_8 = PyTuple_New(3); if (unlikely(!__pyx_t_8)) __PYX_ERR(2, 430, __pyx_L4_error) + __pyx_t_8 = PyTuple_New(3); if (unlikely(!__pyx_t_8)) __PYX_ERR(2, 434, __pyx_L4_error) __Pyx_GOTREF(__pyx_t_8); __Pyx_INCREF(__pyx_v_obj); __Pyx_GIVEREF(__pyx_v_obj); @@ -10498,13 +9171,13 @@ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_ 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 *)__pyx_memoryview_type), __pyx_t_8, NULL); if (unlikely(!__pyx_t_7)) __PYX_ERR(2, 430, __pyx_L4_error) + __pyx_t_7 = __Pyx_PyObject_Call(((PyObject *)__pyx_memoryview_type), __pyx_t_8, NULL); 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__pyx_t_3 = 0; - __PYX_ERR(2, 516, __pyx_L1_error) + __PYX_ERR(2, 520, __pyx_L1_error) - /* "View.MemoryView":515 + /* "View.MemoryView":519 * @cname('getbuffer') * def __getbuffer__(self, Py_buffer *info, int flags): * if flags & PyBUF_WRITABLE and self.view.readonly: # <<<<<<<<<<<<<< @@ -11633,7 +10330,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu */ } - /* "View.MemoryView":518 + /* "View.MemoryView":522 * raise ValueError("Cannot create writable memory view from read-only memoryview") * * if flags & PyBUF_ND: # <<<<<<<<<<<<<< @@ -11643,7 +10340,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_1 = ((__pyx_v_flags & PyBUF_ND) != 0); if (__pyx_t_1) { - /* "View.MemoryView":519 + /* "View.MemoryView":523 * * if flags & PyBUF_ND: * info.shape = self.view.shape # <<<<<<<<<<<<<< @@ -11653,7 +10350,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_4 = __pyx_v_self->view.shape; __pyx_v_info->shape = __pyx_t_4; - /* "View.MemoryView":518 + /* "View.MemoryView":522 * raise ValueError("Cannot create writable memory view from read-only memoryview") * * if flags & PyBUF_ND: # <<<<<<<<<<<<<< @@ -11663,7 +10360,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu goto __pyx_L6; } - /* "View.MemoryView":521 + /* "View.MemoryView":525 * info.shape = self.view.shape * else: * info.shape = NULL # <<<<<<<<<<<<<< @@ -11675,7 +10372,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu } __pyx_L6:; - /* "View.MemoryView":523 + /* "View.MemoryView":527 * info.shape = NULL * * if flags & PyBUF_STRIDES: # <<<<<<<<<<<<<< @@ -11685,7 +10382,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_1 = ((__pyx_v_flags & PyBUF_STRIDES) != 0); if (__pyx_t_1) { - /* "View.MemoryView":524 + /* "View.MemoryView":528 * * if flags & PyBUF_STRIDES: * info.strides = self.view.strides # <<<<<<<<<<<<<< @@ -11695,7 +10392,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_4 = __pyx_v_self->view.strides; __pyx_v_info->strides = __pyx_t_4; - /* "View.MemoryView":523 + /* "View.MemoryView":527 * info.shape = NULL * * if flags & PyBUF_STRIDES: # <<<<<<<<<<<<<< @@ -11705,7 +10402,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu goto __pyx_L7; } - /* "View.MemoryView":526 + /* "View.MemoryView":530 * info.strides = self.view.strides * else: * info.strides = NULL # <<<<<<<<<<<<<< @@ -11717,7 +10414,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu } __pyx_L7:; - /* "View.MemoryView":528 + /* "View.MemoryView":532 * info.strides = NULL * * if flags & PyBUF_INDIRECT: # <<<<<<<<<<<<<< @@ -11727,7 +10424,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_1 = ((__pyx_v_flags & PyBUF_INDIRECT) != 0); if (__pyx_t_1) { - /* "View.MemoryView":529 + /* "View.MemoryView":533 * * if flags & PyBUF_INDIRECT: * info.suboffsets = self.view.suboffsets # <<<<<<<<<<<<<< @@ -11737,7 +10434,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_4 = __pyx_v_self->view.suboffsets; __pyx_v_info->suboffsets = __pyx_t_4; - /* "View.MemoryView":528 + /* "View.MemoryView":532 * info.strides = NULL * * if flags & PyBUF_INDIRECT: # <<<<<<<<<<<<<< @@ -11747,7 +10444,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu goto __pyx_L8; } - /* "View.MemoryView":531 + /* "View.MemoryView":535 * info.suboffsets = self.view.suboffsets * else: * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -11759,7 +10456,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu } __pyx_L8:; - /* "View.MemoryView":533 + /* "View.MemoryView":537 * info.suboffsets = NULL * * if flags & PyBUF_FORMAT: # <<<<<<<<<<<<<< @@ -11769,7 +10466,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_1 = ((__pyx_v_flags & PyBUF_FORMAT) != 0); if (__pyx_t_1) { - /* "View.MemoryView":534 + /* "View.MemoryView":538 * * if flags & PyBUF_FORMAT: * info.format = self.view.format # <<<<<<<<<<<<<< @@ -11779,7 +10476,7 @@ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbu __pyx_t_5 = __pyx_v_self->view.format; 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#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - __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_ERR(2, 742, __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_ERR(2, 746, __pyx_L1_error) #else - __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 742, __pyx_L1_error) + __pyx_t_9 = PySequence_ITEM(__pyx_t_3, __pyx_t_7); __pyx_t_7++; if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 746, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_9); #endif } @@ -14234,7 +12995,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ PyObject* exc_type = PyErr_Occurred(); if (exc_type) { if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) PyErr_Clear(); - else __PYX_ERR(2, 742, __pyx_L1_error) + else __PYX_ERR(2, 746, __pyx_L1_error) } break; } @@ -14245,7 +13006,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_v_dim = __pyx_t_6; 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if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(2, 744, __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 == ((int)-1))) __PYX_ERR(2, 748, __pyx_L1_error) - /* "View.MemoryView":743 + /* "View.MemoryView":747 * * for dim, index in enumerate(indices): * if PyIndex_Check(index): # <<<<<<<<<<<<<< @@ -14283,7 +13044,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ goto __pyx_L6; } - /* "View.MemoryView":750 + /* "View.MemoryView":754 * 0, 0, 0, # have_{start,stop,step} * False) * elif index is None: # <<<<<<<<<<<<<< @@ -14294,7 +13055,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_1 = (__pyx_t_2 != 0); if (__pyx_t_1) { - /* "View.MemoryView":751 + /* "View.MemoryView":755 * False) * elif index is None: * p_dst.shape[new_ndim] = 1 # <<<<<<<<<<<<<< @@ -14303,7 +13064,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ (__pyx_v_p_dst->shape[__pyx_v_new_ndim]) = 1; 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- __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) __PYX_ERR(2, 758, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely(__pyx_t_1 < 0)) __PYX_ERR(2, 762, __pyx_L1_error) if (!__pyx_t_1) { __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; } else { - __pyx_t_12 = __Pyx_PyIndex_AsSsize_t(__pyx_t_9); if (unlikely((__pyx_t_12 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(2, 758, __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_ERR(2, 762, __pyx_L1_error) __pyx_t_10 = __pyx_t_12; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; goto __pyx_L11_bool_binop_done; @@ -14407,55 +13168,55 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_L11_bool_binop_done:; __pyx_v_step = __pyx_t_10; - /* "View.MemoryView":760 + /* "View.MemoryView":764 * 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_ERR(2, 760, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_start); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 764, __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":761 + /* "View.MemoryView":765 * * 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_ERR(2, 761, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_stop); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 765, __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":762 + /* "View.MemoryView":766 * 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_ERR(2, 762, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) __PYX_ERR(2, 766, __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":764 + /* "View.MemoryView":768 * 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 == ((int)-1))) __PYX_ERR(2, 764, __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 == ((int)-1))) __PYX_ERR(2, 768, __pyx_L1_error) - /* "View.MemoryView":770 + /* "View.MemoryView":774 * have_start, have_stop, have_step, * True) * new_ndim += 1 # <<<<<<<<<<<<<< @@ -14466,7 +13227,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __pyx_L6:; - /* "View.MemoryView":742 + /* "View.MemoryView":746 * cdef bint have_start, have_stop, have_step * * for dim, index in enumerate(indices): # <<<<<<<<<<<<<< @@ -14476,7 +13237,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - /* "View.MemoryView":772 + /* "View.MemoryView":776 * new_ndim += 1 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -14487,7 +13248,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":773 + /* "View.MemoryView":777 * * if isinstance(memview, _memoryviewslice): * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< @@ -14496,39 +13257,39 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":774 + /* "View.MemoryView":778 * 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_ERR(2, 774, __pyx_L1_error) } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); __PYX_ERR(2, 778, __pyx_L1_error) } - /* "View.MemoryView":775 + /* "View.MemoryView":779 * 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_ERR(2, 775, __pyx_L1_error) } + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); __PYX_ERR(2, 779, __pyx_L1_error) } - /* "View.MemoryView":773 + /* "View.MemoryView":777 * * 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_ERR(2, 773, __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_ERR(2, 777, __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_ERR(2, 773, __pyx_L1_error) + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(2, 777, __pyx_L1_error) __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; - /* "View.MemoryView":772 + /* "View.MemoryView":776 * new_ndim += 1 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -14537,7 +13298,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ */ } - /* "View.MemoryView":778 + /* "View.MemoryView":782 * memview.dtype_is_object) * else: * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< @@ -14547,30 +13308,30 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ /*else*/ { __Pyx_XDECREF(((PyObject *)__pyx_r)); - /* "View.MemoryView":779 + /* "View.MemoryView":783 * 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_ERR(2, 778, __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_ERR(2, 782, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); - /* "View.MemoryView":778 + /* "View.MemoryView":782 * 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_ERR(2, 778, __pyx_L1_error) + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(2, 782, __pyx_L1_error) __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); __pyx_t_3 = 0; goto __pyx_L0; } - /* "View.MemoryView":706 + /* "View.MemoryView":710 * * @cname('__pyx_memview_slice') * cdef memoryview memview_slice(memoryview memview, object indices): # <<<<<<<<<<<<<< @@ -14592,7 +13353,7 @@ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_ return __pyx_r; } -/* "View.MemoryView":803 +/* "View.MemoryView":807 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -14607,8 +13368,11 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; - /* "View.MemoryView":823 + /* "View.MemoryView":827 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< @@ -14618,7 +13382,7 @@ 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":825 + /* "View.MemoryView":829 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< @@ -14628,7 +13392,7 @@ 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":826 + /* "View.MemoryView":830 * * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -14637,7 +13401,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - /* "View.MemoryView":825 + /* "View.MemoryView":829 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< @@ -14646,7 +13410,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":827 + /* "View.MemoryView":831 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< @@ -14660,16 +13424,16 @@ 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":828 + /* "View.MemoryView":832 * 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, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 828, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 832, __pyx_L1_error) - /* "View.MemoryView":827 + /* "View.MemoryView":831 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< @@ -14678,7 +13442,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":823 + /* "View.MemoryView":827 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< @@ -14688,7 +13452,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L3; } - /* "View.MemoryView":831 + /* "View.MemoryView":835 * else: * * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< @@ -14707,7 +13471,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_L6_bool_binop_done:; __pyx_v_negative_step = __pyx_t_2; - /* "View.MemoryView":833 + /* "View.MemoryView":837 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< @@ -14725,16 +13489,16 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_L9_bool_binop_done:; if (__pyx_t_2) { - /* "View.MemoryView":834 + /* "View.MemoryView":838 * * 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, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 834, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 838, __pyx_L1_error) - /* "View.MemoryView":833 + /* "View.MemoryView":837 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< @@ -14743,7 +13507,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":837 + /* "View.MemoryView":841 * * * if have_start: # <<<<<<<<<<<<<< @@ -14753,7 +13517,7 @@ 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":838 + /* "View.MemoryView":842 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< @@ -14763,7 +13527,7 @@ 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":839 + /* "View.MemoryView":843 * if have_start: * if start < 0: * start += shape # <<<<<<<<<<<<<< @@ -14772,7 +13536,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - /* "View.MemoryView":840 + /* "View.MemoryView":844 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< @@ -14782,7 +13546,7 @@ 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":841 + /* "View.MemoryView":845 * start += shape * if start < 0: * start = 0 # <<<<<<<<<<<<<< @@ -14791,7 +13555,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = 0; - /* "View.MemoryView":840 + /* "View.MemoryView":844 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< @@ -14800,7 +13564,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":838 + /* "View.MemoryView":842 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< @@ -14810,7 +13574,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L12; } - /* "View.MemoryView":842 + /* "View.MemoryView":846 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< @@ -14820,7 +13584,7 @@ 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":843 + /* "View.MemoryView":847 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< @@ -14830,7 +13594,7 @@ 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":844 + /* "View.MemoryView":848 * elif start >= shape: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -14839,7 +13603,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_shape - 1); - /* "View.MemoryView":843 + /* "View.MemoryView":847 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< @@ -14849,7 +13613,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L14; } - /* "View.MemoryView":846 + /* "View.MemoryView":850 * start = shape - 1 * else: * start = shape # <<<<<<<<<<<<<< @@ -14861,7 +13625,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L14:; - /* "View.MemoryView":842 + /* "View.MemoryView":846 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< @@ -14871,7 +13635,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L12:; - /* "View.MemoryView":837 + /* "View.MemoryView":841 * * * if have_start: # <<<<<<<<<<<<<< @@ -14881,7 +13645,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L11; } - /* "View.MemoryView":848 + /* "View.MemoryView":852 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -14892,7 +13656,7 @@ 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":849 + /* "View.MemoryView":853 * else: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< @@ -14901,7 +13665,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_start = (__pyx_v_shape - 1); - /* "View.MemoryView":848 + /* "View.MemoryView":852 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -14911,7 +13675,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L15; } - /* "View.MemoryView":851 + /* "View.MemoryView":855 * start = shape - 1 * else: * start = 0 # <<<<<<<<<<<<<< @@ -14925,7 +13689,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L11:; - /* "View.MemoryView":853 + /* "View.MemoryView":857 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< @@ -14935,7 +13699,7 @@ 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":854 + /* "View.MemoryView":858 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< @@ -14945,7 +13709,7 @@ 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":855 + /* "View.MemoryView":859 * if have_stop: * if stop < 0: * stop += shape # <<<<<<<<<<<<<< @@ -14954,7 +13718,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); - /* "View.MemoryView":856 + /* "View.MemoryView":860 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< @@ -14964,7 +13728,7 @@ 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":857 + /* "View.MemoryView":861 * stop += shape * if stop < 0: * stop = 0 # <<<<<<<<<<<<<< @@ -14973,7 +13737,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = 0; - /* "View.MemoryView":856 + /* "View.MemoryView":860 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< @@ -14982,7 +13746,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":854 + /* "View.MemoryView":858 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< @@ -14992,7 +13756,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L17; } - /* "View.MemoryView":858 + /* "View.MemoryView":862 * if stop < 0: * stop = 0 * elif stop > shape: # <<<<<<<<<<<<<< @@ -15002,7 +13766,7 @@ 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":859 + /* "View.MemoryView":863 * stop = 0 * elif stop > shape: * stop = shape # <<<<<<<<<<<<<< @@ -15011,7 +13775,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = __pyx_v_shape; - /* "View.MemoryView":858 + /* "View.MemoryView":862 * if stop < 0: * stop = 0 * elif stop > shape: # <<<<<<<<<<<<<< @@ -15021,7 +13785,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L17:; - /* "View.MemoryView":853 + /* "View.MemoryView":857 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< @@ -15031,7 +13795,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L16; } - /* "View.MemoryView":861 + /* "View.MemoryView":865 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -15042,7 +13806,7 @@ 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":862 + /* "View.MemoryView":866 * else: * if negative_step: * stop = -1 # <<<<<<<<<<<<<< @@ -15051,7 +13815,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_stop = -1L; - /* "View.MemoryView":861 + /* "View.MemoryView":865 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< @@ -15061,7 +13825,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L19; } - /* "View.MemoryView":864 + /* "View.MemoryView":868 * stop = -1 * else: * stop = shape # <<<<<<<<<<<<<< @@ -15075,7 +13839,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L16:; - /* "View.MemoryView":866 + /* "View.MemoryView":870 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< @@ -15085,7 +13849,7 @@ 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":867 + /* "View.MemoryView":871 * * if not have_step: * step = 1 # <<<<<<<<<<<<<< @@ -15094,7 +13858,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_step = 1; - /* "View.MemoryView":866 + /* "View.MemoryView":870 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< @@ -15103,7 +13867,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":871 + /* "View.MemoryView":875 * * with cython.cdivision(True): * new_shape = (stop - start) // step # <<<<<<<<<<<<<< @@ -15112,7 +13876,7 @@ 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":873 + /* "View.MemoryView":877 * new_shape = (stop - start) // step * * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< @@ -15122,7 +13886,7 @@ 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":874 + /* "View.MemoryView":878 * * if (stop - start) - step * new_shape: * new_shape += 1 # <<<<<<<<<<<<<< @@ -15131,7 +13895,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_new_shape = (__pyx_v_new_shape + 1); - /* "View.MemoryView":873 + /* "View.MemoryView":877 * new_shape = (stop - start) // step * * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< @@ -15140,7 +13904,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":876 + /* "View.MemoryView":880 * new_shape += 1 * * if new_shape < 0: # <<<<<<<<<<<<<< @@ -15150,7 +13914,7 @@ 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":877 + /* "View.MemoryView":881 * * if new_shape < 0: * new_shape = 0 # <<<<<<<<<<<<<< @@ -15159,7 +13923,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_new_shape = 0; - /* "View.MemoryView":876 + /* "View.MemoryView":880 * new_shape += 1 * * if new_shape < 0: # <<<<<<<<<<<<<< @@ -15168,7 +13932,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":880 + /* "View.MemoryView":884 * * * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< @@ -15177,7 +13941,7 @@ 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":881 + /* "View.MemoryView":885 * * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< @@ -15186,7 +13950,7 @@ 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":882 + /* "View.MemoryView":886 * dst.strides[new_ndim] = stride * step * dst.shape[new_ndim] = new_shape * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< @@ -15197,7 +13961,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L3:; - /* "View.MemoryView":885 + /* "View.MemoryView":889 * * * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< @@ -15207,7 +13971,7 @@ 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":886 + /* "View.MemoryView":890 * * if suboffset_dim[0] < 0: * dst.data += start * stride # <<<<<<<<<<<<<< @@ -15216,7 +13980,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride)); - /* "View.MemoryView":885 + /* "View.MemoryView":889 * * * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< @@ -15226,7 +13990,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L23; } - /* "View.MemoryView":888 + /* "View.MemoryView":892 * dst.data += start * stride * else: * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< @@ -15239,7 +14003,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L23:; - /* "View.MemoryView":890 + /* "View.MemoryView":894 * dst.suboffsets[suboffset_dim[0]] += start * stride * * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -15249,7 +14013,7 @@ 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":891 + /* "View.MemoryView":895 * * if suboffset >= 0: * if not is_slice: # <<<<<<<<<<<<<< @@ -15259,7 +14023,7 @@ 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":892 + /* "View.MemoryView":896 * if suboffset >= 0: * if not is_slice: * if new_ndim == 0: # <<<<<<<<<<<<<< @@ -15269,7 +14033,7 @@ 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":893 + /* "View.MemoryView":897 * if not is_slice: * if new_ndim == 0: * dst.data = ( dst.data)[0] + suboffset # <<<<<<<<<<<<<< @@ -15278,7 +14042,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset); - /* "View.MemoryView":892 + /* "View.MemoryView":896 * if suboffset >= 0: * if not is_slice: * if new_ndim == 0: # <<<<<<<<<<<<<< @@ -15288,7 +14052,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L26; } - /* "View.MemoryView":895 + /* "View.MemoryView":899 * dst.data = ( dst.data)[0] + suboffset * else: * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<< @@ -15297,18 +14061,18 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ /*else*/ { - /* "View.MemoryView":896 + /* "View.MemoryView":900 * 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, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 895, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 899, __pyx_L1_error) } __pyx_L26:; - /* "View.MemoryView":891 + /* "View.MemoryView":895 * * if suboffset >= 0: * if not is_slice: # <<<<<<<<<<<<<< @@ -15318,7 +14082,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, goto __pyx_L25; } - /* "View.MemoryView":898 + /* "View.MemoryView":902 * "must be indexed and not sliced", dim) * else: * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< @@ -15330,7 +14094,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, } __pyx_L25:; - /* "View.MemoryView":890 + /* "View.MemoryView":894 * dst.suboffsets[suboffset_dim[0]] += start * stride * * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -15339,7 +14103,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, */ } - /* "View.MemoryView":900 + /* "View.MemoryView":904 * suboffset_dim[0] = new_ndim * * return 0 # <<<<<<<<<<<<<< @@ -15349,7 +14113,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":803 + /* "View.MemoryView":807 * * @cname('__pyx_memoryview_slice_memviewslice') * cdef int slice_memviewslice( # <<<<<<<<<<<<<< @@ -15373,7 +14137,7 @@ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, return __pyx_r; } -/* "View.MemoryView":906 +/* "View.MemoryView":910 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -15393,9 +14157,12 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P int __pyx_t_2; PyObject *__pyx_t_3 = NULL; PyObject *__pyx_t_4 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("pybuffer_index", 0); - /* "View.MemoryView":908 + /* "View.MemoryView":912 * 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 # <<<<<<<<<<<<<< @@ -15404,7 +14171,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_suboffset = -1L; - /* "View.MemoryView":909 + /* "View.MemoryView":913 * Py_ssize_t dim) except NULL: * cdef Py_ssize_t shape, stride, suboffset = -1 * cdef Py_ssize_t itemsize = view.itemsize # <<<<<<<<<<<<<< @@ -15414,7 +14181,7 @@ 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":912 + /* "View.MemoryView":916 * cdef char *resultp * * if view.ndim == 0: # <<<<<<<<<<<<<< @@ -15424,7 +14191,7 @@ 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":913 + /* "View.MemoryView":917 * * if view.ndim == 0: * shape = view.len / itemsize # <<<<<<<<<<<<<< @@ -15433,15 +14200,15 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ if (unlikely(__pyx_v_itemsize == 0)) { PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero"); 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if (unlikely(__pyx_t_2)) { - /* "View.MemoryView":924 + /* "View.MemoryView":928 * 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_ERR(2, 924, __pyx_L1_error) + __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 928, __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_ERR(2, 924, __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_ERR(2, 928, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_builtin_IndexError, __pyx_t_4); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 924, __pyx_L1_error) + __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_builtin_IndexError, __pyx_t_4); 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if (unlikely(__pyx_t_2)) { - /* "View.MemoryView":927 + /* "View.MemoryView":931 * * if index >= shape: * raise IndexError("Out of bounds on buffer access (axis %d)" % dim) # <<<<<<<<<<<<<< * * resultp = bufp + index * stride */ - __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 927, __pyx_L1_error) + __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_dim); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 931, __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_ERR(2, 927, __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_ERR(2, 931, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_builtin_IndexError, __pyx_t_4); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 927, __pyx_L1_error) + __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_builtin_IndexError, __pyx_t_4); 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if (__pyx_t_2) { - /* "View.MemoryView":931 + /* "View.MemoryView":935 * resultp = bufp + index * stride * if suboffset >= 0: * resultp = ( resultp)[0] + suboffset # <<<<<<<<<<<<<< @@ -15641,7 +14408,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ __pyx_v_resultp = ((((char **)__pyx_v_resultp)[0]) + __pyx_v_suboffset); - /* "View.MemoryView":930 + /* "View.MemoryView":934 * * resultp = bufp + index * stride * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -15650,7 +14417,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P */ } - /* "View.MemoryView":933 + /* "View.MemoryView":937 * resultp = ( resultp)[0] + suboffset * * return resultp # <<<<<<<<<<<<<< @@ -15660,7 +14427,7 @@ 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":906 + /* "View.MemoryView":910 * * @cname('__pyx_pybuffer_index') * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< @@ -15679,7 +14446,7 @@ static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, P return __pyx_r; 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(__pyx_v_strides[__pyx_v_j]) = __pyx_t_6; - /* "View.MemoryView":950 + /* "View.MemoryView":954 * j = ndim - 1 - i * strides[i], strides[j] = strides[j], strides[i] * shape[i], shape[j] = shape[j], shape[i] # <<<<<<<<<<<<<< @@ -15779,7 +14549,7 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { (__pyx_v_shape[__pyx_v_i]) = __pyx_t_6; (__pyx_v_shape[__pyx_v_j]) = __pyx_t_5; - /* "View.MemoryView":952 + /* "View.MemoryView":956 * shape[i], shape[j] = shape[j], shape[i] * * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: # <<<<<<<<<<<<<< @@ -15797,16 +14567,16 @@ static int __pyx_memslice_transpose(__Pyx_memviewslice *__pyx_v_memslice) { __pyx_L6_bool_binop_done:; if (__pyx_t_7) { - /* "View.MemoryView":953 + /* "View.MemoryView":957 * * if memslice.suboffsets[i] >= 0 or memslice.suboffsets[j] >= 0: * _err(ValueError, "Cannot transpose memoryview with indirect dimensions") # <<<<<<<<<<<<<< * * return 1 */ - __pyx_t_9 = __pyx_memoryview_err(__pyx_builtin_ValueError, ((char *)"Cannot transpose memoryview with indirect dimensions")); 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if (__pyx_t_1) { - /* "View.MemoryView":983 + /* "View.MemoryView":987 * cdef assign_item_from_object(self, char *itemp, object value): * if self.to_dtype_func != NULL: * self.to_dtype_func(itemp, value) # <<<<<<<<<<<<<< * else: * memoryview.assign_item_from_object(self, itemp, value) */ - __pyx_t_2 = __pyx_v_self->to_dtype_func(__pyx_v_itemp, __pyx_v_value); if (unlikely(__pyx_t_2 == ((int)0))) __PYX_ERR(2, 983, __pyx_L1_error) + __pyx_t_2 = __pyx_v_self->to_dtype_func(__pyx_v_itemp, __pyx_v_value); if (unlikely(__pyx_t_2 == ((int)0))) __PYX_ERR(2, 987, __pyx_L1_error) - /* "View.MemoryView":982 + /* "View.MemoryView":986 * * cdef assign_item_from_object(self, char *itemp, object value): * if self.to_dtype_func != NULL: # <<<<<<<<<<<<<< @@ -16022,7 +14798,7 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo goto __pyx_L3; } - /* "View.MemoryView":985 + /* "View.MemoryView":989 * self.to_dtype_func(itemp, value) * else: * memoryview.assign_item_from_object(self, itemp, value) # <<<<<<<<<<<<<< @@ -16030,13 +14806,13 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo * @property */ /*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_ERR(2, 985, __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_ERR(2, 989, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; } __pyx_L3:; - /* "View.MemoryView":981 + /* "View.MemoryView":985 * return memoryview.convert_item_to_object(self, itemp) * * cdef assign_item_from_object(self, char *itemp, object value): # <<<<<<<<<<<<<< @@ -16057,7 +14833,7 @@ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memo return __pyx_r; } -/* "View.MemoryView":988 +/* "View.MemoryView":992 * * @property * def base(self): # <<<<<<<<<<<<<< @@ -16083,7 +14859,7 @@ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__ __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__get__", 0); - /* "View.MemoryView":989 + /* "View.MemoryView":993 * @property * def base(self): * return self.from_object # <<<<<<<<<<<<<< @@ -16095,7 +14871,7 @@ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__ __pyx_r = __pyx_v_self->from_object; goto __pyx_L0; - /* "View.MemoryView":988 + /* "View.MemoryView":992 * * @property * def base(self): # <<<<<<<<<<<<<< @@ -16133,6 +14909,9 @@ static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__reduce_cython__", 0); /* "(tree fragment)":2 @@ -16141,7 +14920,7 @@ static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED * def __setstate_cython__(self, __pyx_state): * raise TypeError("no default __reduce__ due to non-trivial __cinit__") */ - __pyx_t_1 = __Pyx_PyObject_Call(__pyx_builtin_TypeError, __pyx_tuple__24, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 2, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(__pyx_builtin_TypeError, __pyx_tuple__19, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 2, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_Raise(__pyx_t_1, 0, 0, 0); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -16187,6 +14966,9 @@ static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUS PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__setstate_cython__", 0); /* "(tree fragment)":4 @@ -16194,7 +14976,7 @@ static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUS * def __setstate_cython__(self, __pyx_state): * raise TypeError("no default __reduce__ due to non-trivial __cinit__") # <<<<<<<<<<<<<< */ - __pyx_t_1 = __Pyx_PyObject_Call(__pyx_builtin_TypeError, __pyx_tuple__25, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 4, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(__pyx_builtin_TypeError, __pyx_tuple__20, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 4, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_Raise(__pyx_t_1, 0, 0, 0); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -16217,7 +14999,7 @@ static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUS return __pyx_r; } -/* "View.MemoryView":995 +/* "View.MemoryView":999 * * @cname('__pyx_memoryview_fromslice') * cdef memoryview_fromslice(__Pyx_memviewslice memviewslice, # <<<<<<<<<<<<<< @@ -16240,9 +15022,12 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl Py_ssize_t *__pyx_t_7; Py_ssize_t *__pyx_t_8; Py_ssize_t __pyx_t_9; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_fromslice", 0); - /* "View.MemoryView":1003 + /* "View.MemoryView":1007 * cdef _memoryviewslice result * * if memviewslice.memview == Py_None: # <<<<<<<<<<<<<< @@ -16252,7 +15037,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_1 = ((((PyObject *)__pyx_v_memviewslice.memview) == Py_None) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1004 + /* "View.MemoryView":1008 * * if memviewslice.memview == Py_None: * return None # <<<<<<<<<<<<<< @@ -16263,7 +15048,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_r = Py_None; __Pyx_INCREF(Py_None); goto __pyx_L0; - /* "View.MemoryView":1003 + /* "View.MemoryView":1007 * cdef _memoryviewslice result * * if memviewslice.memview == Py_None: # <<<<<<<<<<<<<< @@ -16272,16 +15057,16 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ } - /* "View.MemoryView":1009 + /* "View.MemoryView":1013 * * * result = _memoryviewslice(None, 0, dtype_is_object) # <<<<<<<<<<<<<< * * result.from_slice = memviewslice */ - __pyx_t_2 = __Pyx_PyBool_FromLong(__pyx_v_dtype_is_object); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1009, __pyx_L1_error) + __pyx_t_2 = __Pyx_PyBool_FromLong(__pyx_v_dtype_is_object); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1013, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 1009, __pyx_L1_error) + __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 1013, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); __Pyx_INCREF(Py_None); __Pyx_GIVEREF(Py_None); @@ -16292,13 +15077,13 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __Pyx_GIVEREF(__pyx_t_2); PyTuple_SET_ITEM(__pyx_t_3, 2, __pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = __Pyx_PyObject_Call(((PyObject *)__pyx_memoryviewslice_type), __pyx_t_3, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1009, __pyx_L1_error) + __pyx_t_2 = __Pyx_PyObject_Call(((PyObject *)__pyx_memoryviewslice_type), __pyx_t_3, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1013, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __pyx_v_result = ((struct __pyx_memoryviewslice_obj *)__pyx_t_2); __pyx_t_2 = 0; - /* "View.MemoryView":1011 + /* "View.MemoryView":1015 * result = _memoryviewslice(None, 0, dtype_is_object) * * result.from_slice = memviewslice # <<<<<<<<<<<<<< @@ -16307,7 +15092,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->from_slice = __pyx_v_memviewslice; - /* "View.MemoryView":1012 + /* "View.MemoryView":1016 * * result.from_slice = memviewslice * __PYX_INC_MEMVIEW(&memviewslice, 1) # <<<<<<<<<<<<<< @@ -16316,14 +15101,14 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __PYX_INC_MEMVIEW((&__pyx_v_memviewslice), 1); - /* "View.MemoryView":1014 + /* "View.MemoryView":1018 * __PYX_INC_MEMVIEW(&memviewslice, 1) * * result.from_object = ( memviewslice.memview).base # <<<<<<<<<<<<<< * result.typeinfo = memviewslice.memview.typeinfo * */ - __pyx_t_2 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_memviewslice.memview), __pyx_n_s_base); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1014, __pyx_L1_error) + __pyx_t_2 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_memviewslice.memview), __pyx_n_s_base); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1018, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); __Pyx_GOTREF(__pyx_v_result->from_object); @@ -16331,7 +15116,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_v_result->from_object = __pyx_t_2; __pyx_t_2 = 0; - /* "View.MemoryView":1015 + /* "View.MemoryView":1019 * * result.from_object = ( memviewslice.memview).base * result.typeinfo = memviewslice.memview.typeinfo # <<<<<<<<<<<<<< @@ -16341,7 +15126,7 @@ 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":1017 + /* "View.MemoryView":1021 * result.typeinfo = memviewslice.memview.typeinfo * * result.view = memviewslice.memview.view # <<<<<<<<<<<<<< @@ -16351,7 +15136,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_5 = __pyx_v_memviewslice.memview->view; __pyx_v_result->__pyx_base.view = __pyx_t_5; - /* "View.MemoryView":1018 + /* "View.MemoryView":1022 * * result.view = memviewslice.memview.view * result.view.buf = memviewslice.data # <<<<<<<<<<<<<< @@ -16360,7 +15145,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.buf = ((void *)__pyx_v_memviewslice.data); - /* "View.MemoryView":1019 + /* "View.MemoryView":1023 * result.view = memviewslice.memview.view * result.view.buf = memviewslice.data * result.view.ndim = ndim # <<<<<<<<<<<<<< @@ -16369,7 +15154,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.ndim = __pyx_v_ndim; - /* "View.MemoryView":1020 + /* "View.MemoryView":1024 * result.view.buf = memviewslice.data * result.view.ndim = ndim * (<__pyx_buffer *> &result.view).obj = Py_None # <<<<<<<<<<<<<< @@ -16378,7 +15163,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ ((Py_buffer *)(&__pyx_v_result->__pyx_base.view))->obj = Py_None; - /* "View.MemoryView":1021 + /* "View.MemoryView":1025 * result.view.ndim = ndim * (<__pyx_buffer *> &result.view).obj = Py_None * Py_INCREF(Py_None) # <<<<<<<<<<<<<< @@ -16387,7 +15172,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ Py_INCREF(Py_None); - /* "View.MemoryView":1023 + /* "View.MemoryView":1027 * Py_INCREF(Py_None) * * if (memviewslice.memview).flags & PyBUF_WRITABLE: # <<<<<<<<<<<<<< @@ -16397,7 +15182,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_1 = ((((struct __pyx_memoryview_obj *)__pyx_v_memviewslice.memview)->flags & PyBUF_WRITABLE) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1024 + /* "View.MemoryView":1028 * * if (memviewslice.memview).flags & PyBUF_WRITABLE: * result.flags = PyBUF_RECORDS # <<<<<<<<<<<<<< @@ -16406,7 +15191,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.flags = PyBUF_RECORDS; - /* "View.MemoryView":1023 + /* "View.MemoryView":1027 * Py_INCREF(Py_None) * * if (memviewslice.memview).flags & PyBUF_WRITABLE: # <<<<<<<<<<<<<< @@ -16416,7 +15201,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl goto __pyx_L4; } - /* "View.MemoryView":1026 + /* "View.MemoryView":1030 * result.flags = PyBUF_RECORDS * else: * result.flags = PyBUF_RECORDS_RO # <<<<<<<<<<<<<< @@ -16428,7 +15213,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl } __pyx_L4:; - /* "View.MemoryView":1028 + /* "View.MemoryView":1032 * result.flags = PyBUF_RECORDS_RO * * result.view.shape = result.from_slice.shape # <<<<<<<<<<<<<< @@ -16437,7 +15222,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.shape = ((Py_ssize_t *)__pyx_v_result->from_slice.shape); - /* "View.MemoryView":1029 + /* "View.MemoryView":1033 * * result.view.shape = result.from_slice.shape * result.view.strides = result.from_slice.strides # <<<<<<<<<<<<<< @@ -16446,7 +15231,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.strides = ((Py_ssize_t *)__pyx_v_result->from_slice.strides); - /* "View.MemoryView":1032 + /* "View.MemoryView":1036 * * * result.view.suboffsets = NULL # <<<<<<<<<<<<<< @@ -16455,7 +15240,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.suboffsets = NULL; - /* "View.MemoryView":1033 + /* "View.MemoryView":1037 * * result.view.suboffsets = NULL * for suboffset in result.from_slice.suboffsets[:ndim]: # <<<<<<<<<<<<<< @@ -16467,7 +15252,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_6 = __pyx_t_8; __pyx_v_suboffset = (__pyx_t_6[0]); - /* "View.MemoryView":1034 + /* "View.MemoryView":1038 * result.view.suboffsets = NULL * for suboffset in result.from_slice.suboffsets[:ndim]: * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -16477,7 +15262,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_1 = ((__pyx_v_suboffset >= 0) != 0); if (__pyx_t_1) { - /* "View.MemoryView":1035 + /* "View.MemoryView":1039 * for suboffset in result.from_slice.suboffsets[:ndim]: * if suboffset >= 0: * result.view.suboffsets = result.from_slice.suboffsets # <<<<<<<<<<<<<< @@ -16486,7 +15271,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->__pyx_base.view.suboffsets = ((Py_ssize_t *)__pyx_v_result->from_slice.suboffsets); - /* "View.MemoryView":1036 + /* "View.MemoryView":1040 * if suboffset >= 0: * result.view.suboffsets = result.from_slice.suboffsets * break # <<<<<<<<<<<<<< @@ -16495,7 +15280,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ goto __pyx_L6_break; - /* "View.MemoryView":1034 + /* "View.MemoryView":1038 * result.view.suboffsets = NULL * for suboffset in result.from_slice.suboffsets[:ndim]: * if suboffset >= 0: # <<<<<<<<<<<<<< @@ -16506,7 +15291,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl } __pyx_L6_break:; - /* "View.MemoryView":1038 + /* "View.MemoryView":1042 * break * * result.view.len = result.view.itemsize # <<<<<<<<<<<<<< @@ -16516,7 +15301,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_9 = __pyx_v_result->__pyx_base.view.itemsize; __pyx_v_result->__pyx_base.view.len = __pyx_t_9; - /* "View.MemoryView":1039 + /* "View.MemoryView":1043 * * result.view.len = result.view.itemsize * for length in result.view.shape[:ndim]: # <<<<<<<<<<<<<< @@ -16526,29 +15311,29 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_t_7 = (__pyx_v_result->__pyx_base.view.shape + __pyx_v_ndim); for (__pyx_t_8 = __pyx_v_result->__pyx_base.view.shape; __pyx_t_8 < __pyx_t_7; __pyx_t_8++) { __pyx_t_6 = __pyx_t_8; - __pyx_t_2 = PyInt_FromSsize_t((__pyx_t_6[0])); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1039, __pyx_L1_error) + __pyx_t_2 = PyInt_FromSsize_t((__pyx_t_6[0])); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1043, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_XDECREF_SET(__pyx_v_length, __pyx_t_2); __pyx_t_2 = 0; - /* "View.MemoryView":1040 + /* "View.MemoryView":1044 * result.view.len = result.view.itemsize * for length in result.view.shape[:ndim]: * result.view.len *= length # <<<<<<<<<<<<<< * * result.to_object_func = to_object_func */ - __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_result->__pyx_base.view.len); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1040, __pyx_L1_error) + __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_result->__pyx_base.view.len); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1044, __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_ERR(2, 1040, __pyx_L1_error) + __pyx_t_3 = PyNumber_InPlaceMultiply(__pyx_t_2, __pyx_v_length); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 1044, __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_ERR(2, 1040, __pyx_L1_error) + __pyx_t_9 = __Pyx_PyIndex_AsSsize_t(__pyx_t_3); if (unlikely((__pyx_t_9 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(2, 1044, __pyx_L1_error) __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __pyx_v_result->__pyx_base.view.len = __pyx_t_9; } - /* "View.MemoryView":1042 + /* "View.MemoryView":1046 * result.view.len *= length * * result.to_object_func = to_object_func # <<<<<<<<<<<<<< @@ -16557,7 +15342,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_object_func = __pyx_v_to_object_func; - /* "View.MemoryView":1043 + /* "View.MemoryView":1047 * * result.to_object_func = to_object_func * result.to_dtype_func = to_dtype_func # <<<<<<<<<<<<<< @@ -16566,7 +15351,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl */ __pyx_v_result->to_dtype_func = __pyx_v_to_dtype_func; - /* "View.MemoryView":1045 + /* "View.MemoryView":1049 * result.to_dtype_func = to_dtype_func * * return result # <<<<<<<<<<<<<< @@ -16578,7 +15363,7 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl __pyx_r = ((PyObject *)__pyx_v_result); goto __pyx_L0; - /* "View.MemoryView":995 + /* "View.MemoryView":999 * * @cname('__pyx_memoryview_fromslice') * cdef memoryview_fromslice(__Pyx_memviewslice memviewslice, # <<<<<<<<<<<<<< @@ -16600,11 +15385,11 @@ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice __pyx_v_memviewsl return __pyx_r; } -/* "View.MemoryView":1048 +/* "View.MemoryView":1052 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *mslice): + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj */ @@ -16615,10 +15400,13 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p int __pyx_t_1; int __pyx_t_2; PyObject *__pyx_t_3 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("get_slice_from_memview", 0); - /* "View.MemoryView":1051 - * __Pyx_memviewslice *mslice): + /* "View.MemoryView":1055 + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * obj = memview @@ -16628,20 +15416,20 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1052 + /* "View.MemoryView":1056 * 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_ERR(2, 1052, __pyx_L1_error) + if (!(likely(((((PyObject *)__pyx_v_memview)) == Py_None) || likely(__Pyx_TypeTest(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type))))) __PYX_ERR(2, 1056, __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":1053 + /* "View.MemoryView":1057 * if isinstance(memview, _memoryviewslice): * obj = memview * return &obj.from_slice # <<<<<<<<<<<<<< @@ -16651,8 +15439,8 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p __pyx_r = (&__pyx_v_obj->from_slice); goto __pyx_L0; - /* "View.MemoryView":1051 - * __Pyx_memviewslice *mslice): + /* "View.MemoryView":1055 + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * obj = memview @@ -16660,7 +15448,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p */ } - /* "View.MemoryView":1055 + /* "View.MemoryView":1059 * return &obj.from_slice * else: * slice_copy(memview, mslice) # <<<<<<<<<<<<<< @@ -16670,7 +15458,7 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p /*else*/ { __pyx_memoryview_slice_copy(__pyx_v_memview, __pyx_v_mslice); - /* "View.MemoryView":1056 + /* "View.MemoryView":1060 * else: * slice_copy(memview, mslice) * return mslice # <<<<<<<<<<<<<< @@ -16681,26 +15469,26 @@ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __p goto __pyx_L0; } - /* "View.MemoryView":1048 + /* "View.MemoryView":1052 * * @cname('__pyx_memoryview_get_slice_from_memoryview') * cdef __Pyx_memviewslice *get_slice_from_memview(memoryview memview, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *mslice): + * __Pyx_memviewslice *mslice) except NULL: * cdef _memoryviewslice obj */ /* 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, 1, 0); - __pyx_r = 0; + __Pyx_AddTraceback("View.MemoryView.get_slice_from_memview", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = NULL; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_obj); __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "View.MemoryView":1059 +/* "View.MemoryView":1063 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -16721,7 +15509,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem Py_ssize_t __pyx_t_5; __Pyx_RefNannySetupContext("slice_copy", 0); - /* "View.MemoryView":1063 + /* "View.MemoryView":1067 * cdef (Py_ssize_t*) shape, strides, suboffsets * * shape = memview.view.shape # <<<<<<<<<<<<<< @@ -16731,7 +15519,7 @@ 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":1064 + /* "View.MemoryView":1068 * * shape = memview.view.shape * strides = memview.view.strides # <<<<<<<<<<<<<< @@ -16741,7 +15529,7 @@ 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":1065 + /* "View.MemoryView":1069 * shape = memview.view.shape * strides = memview.view.strides * suboffsets = memview.view.suboffsets # <<<<<<<<<<<<<< @@ -16751,7 +15539,7 @@ 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":1067 + /* "View.MemoryView":1071 * suboffsets = memview.view.suboffsets * * dst.memview = <__pyx_memoryview *> memview # <<<<<<<<<<<<<< @@ -16760,7 +15548,7 @@ 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":1068 + /* "View.MemoryView":1072 * * dst.memview = <__pyx_memoryview *> memview * dst.data = memview.view.buf # <<<<<<<<<<<<<< @@ -16769,7 +15557,7 @@ 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":1070 + /* "View.MemoryView":1074 * dst.data = memview.view.buf * * for dim in range(memview.view.ndim): # <<<<<<<<<<<<<< @@ -16781,7 +15569,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_dim = __pyx_t_4; - /* "View.MemoryView":1071 + /* "View.MemoryView":1075 * * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] # <<<<<<<<<<<<<< @@ -16790,7 +15578,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ (__pyx_v_dst->shape[__pyx_v_dim]) = (__pyx_v_shape[__pyx_v_dim]); - /* "View.MemoryView":1072 + /* "View.MemoryView":1076 * for dim in range(memview.view.ndim): * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] # <<<<<<<<<<<<<< @@ -16799,7 +15587,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem */ (__pyx_v_dst->strides[__pyx_v_dim]) = (__pyx_v_strides[__pyx_v_dim]); - /* "View.MemoryView":1073 + /* "View.MemoryView":1077 * dst.shape[dim] = shape[dim] * dst.strides[dim] = strides[dim] * dst.suboffsets[dim] = suboffsets[dim] if suboffsets else -1 # <<<<<<<<<<<<<< @@ -16814,7 +15602,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem (__pyx_v_dst->suboffsets[__pyx_v_dim]) = __pyx_t_5; } - /* "View.MemoryView":1059 + /* "View.MemoryView":1063 * * @cname('__pyx_memoryview_slice_copy') * cdef void slice_copy(memoryview memview, __Pyx_memviewslice *dst): # <<<<<<<<<<<<<< @@ -16826,7 +15614,7 @@ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *__pyx_v_mem __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1076 +/* "View.MemoryView":1080 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -16839,9 +15627,12 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy", 0); - /* "View.MemoryView":1079 + /* "View.MemoryView":1083 * "Create a new memoryview object" * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -16850,7 +15641,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx */ __pyx_memoryview_slice_copy(__pyx_v_memview, (&__pyx_v_memviewslice)); - /* "View.MemoryView":1080 + /* "View.MemoryView":1084 * cdef __Pyx_memviewslice memviewslice * slice_copy(memview, &memviewslice) * return memoryview_copy_from_slice(memview, &memviewslice) # <<<<<<<<<<<<<< @@ -16858,13 +15649,13 @@ 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_ERR(2, 1080, __pyx_L1_error) + __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 1084, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; - /* "View.MemoryView":1076 + /* "View.MemoryView":1080 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< @@ -16883,7 +15674,7 @@ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *__pyx return __pyx_r; } -/* "View.MemoryView":1083 +/* "View.MemoryView":1087 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -16901,9 +15692,12 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview PyObject *(*__pyx_t_3)(char *); int (*__pyx_t_4)(char *, PyObject *); PyObject *__pyx_t_5 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("memoryview_copy_from_slice", 0); - /* "View.MemoryView":1090 + /* "View.MemoryView":1094 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -16914,7 +15708,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "View.MemoryView":1091 + /* "View.MemoryView":1095 * * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func # <<<<<<<<<<<<<< @@ -16924,7 +15718,7 @@ 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":1092 + /* "View.MemoryView":1096 * if isinstance(memview, _memoryviewslice): * to_object_func = (<_memoryviewslice> memview).to_object_func * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func # <<<<<<<<<<<<<< @@ -16934,7 +15728,7 @@ 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":1090 + /* "View.MemoryView":1094 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< @@ -16944,7 +15738,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview goto __pyx_L3; } - /* "View.MemoryView":1094 + /* "View.MemoryView":1098 * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func * else: * to_object_func = NULL # <<<<<<<<<<<<<< @@ -16954,7 +15748,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview /*else*/ { __pyx_v_to_object_func = NULL; - /* "View.MemoryView":1095 + /* "View.MemoryView":1099 * else: * to_object_func = NULL * to_dtype_func = NULL # <<<<<<<<<<<<<< @@ -16965,7 +15759,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview } __pyx_L3:; - /* "View.MemoryView":1097 + /* "View.MemoryView":1101 * to_dtype_func = NULL * * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< @@ -16974,20 +15768,20 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview */ __Pyx_XDECREF(__pyx_r); - /* "View.MemoryView":1099 + /* "View.MemoryView":1103 * 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_ERR(2, 1097, __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_ERR(2, 1101, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); __pyx_r = __pyx_t_5; __pyx_t_5 = 0; goto __pyx_L0; - /* "View.MemoryView":1083 + /* "View.MemoryView":1087 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< @@ -17006,7 +15800,7 @@ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview return __pyx_r; } -/* "View.MemoryView":1105 +/* "View.MemoryView":1109 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -17018,7 +15812,7 @@ 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":1106 + /* "View.MemoryView":1110 * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: # <<<<<<<<<<<<<< @@ -17028,7 +15822,7 @@ 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":1107 + /* "View.MemoryView":1111 * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: * return -arg # <<<<<<<<<<<<<< @@ -17038,7 +15832,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { __pyx_r = (-__pyx_v_arg); goto __pyx_L0; - /* "View.MemoryView":1106 + /* "View.MemoryView":1110 * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: * if arg < 0: # <<<<<<<<<<<<<< @@ -17047,7 +15841,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { */ } - /* "View.MemoryView":1109 + /* "View.MemoryView":1113 * return -arg * else: * return arg # <<<<<<<<<<<<<< @@ -17059,7 +15853,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { goto __pyx_L0; } - /* "View.MemoryView":1105 + /* "View.MemoryView":1109 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< @@ -17072,7 +15866,7 @@ static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { return __pyx_r; } -/* "View.MemoryView":1112 +/* "View.MemoryView":1116 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -17090,7 +15884,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ int __pyx_t_3; int __pyx_t_4; - /* "View.MemoryView":1117 + /* "View.MemoryView":1121 * """ * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< @@ -17099,7 +15893,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_c_stride = 0; - /* "View.MemoryView":1118 + /* "View.MemoryView":1122 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< @@ -17108,7 +15902,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ __pyx_v_f_stride = 0; - /* "View.MemoryView":1120 + /* "View.MemoryView":1124 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -17118,7 +15912,7 @@ 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":1121 + /* "View.MemoryView":1125 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -17128,7 +15922,7 @@ 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":1122 + /* "View.MemoryView":1126 * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -17137,7 +15931,7 @@ 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":1123 + /* "View.MemoryView":1127 * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -17146,7 +15940,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ goto __pyx_L4_break; - /* "View.MemoryView":1121 + /* "View.MemoryView":1125 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -17157,7 +15951,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } __pyx_L4_break:; - /* "View.MemoryView":1125 + /* "View.MemoryView":1129 * break * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -17169,7 +15963,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1126 + /* "View.MemoryView":1130 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -17179,7 +15973,7 @@ 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":1127 + /* "View.MemoryView":1131 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< @@ -17188,7 +15982,7 @@ 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":1128 + /* "View.MemoryView":1132 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< @@ -17197,7 +15991,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ goto __pyx_L7_break; - /* "View.MemoryView":1126 + /* "View.MemoryView":1130 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< @@ -17208,7 +16002,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ } __pyx_L7_break:; - /* "View.MemoryView":1130 + /* "View.MemoryView":1134 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< @@ -17218,7 +16012,7 @@ 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":1131 + /* "View.MemoryView":1135 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< @@ -17228,7 +16022,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ __pyx_r = 'C'; goto __pyx_L0; - /* "View.MemoryView":1130 + /* "View.MemoryView":1134 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< @@ -17237,7 +16031,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ */ } - /* "View.MemoryView":1133 + /* "View.MemoryView":1137 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< @@ -17249,7 +16043,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ goto __pyx_L0; } - /* "View.MemoryView":1112 + /* "View.MemoryView":1116 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< @@ -17262,7 +16056,7 @@ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int _ return __pyx_r; } -/* "View.MemoryView":1136 +/* "View.MemoryView":1140 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -17283,7 +16077,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v Py_ssize_t __pyx_t_5; Py_ssize_t __pyx_t_6; - /* "View.MemoryView":1143 + /* "View.MemoryView":1147 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< @@ -17292,7 +16086,7 @@ 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":1144 + /* "View.MemoryView":1148 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< @@ -17301,7 +16095,7 @@ 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":1145 + /* "View.MemoryView":1149 * 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] # <<<<<<<<<<<<<< @@ -17310,7 +16104,7 @@ 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":1146 + /* "View.MemoryView":1150 * 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] # <<<<<<<<<<<<<< @@ -17319,7 +16113,7 @@ 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":1148 + /* "View.MemoryView":1152 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -17329,7 +16123,7 @@ 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":1149 + /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -17349,7 +16143,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v goto __pyx_L5_bool_binop_done; } - /* "View.MemoryView":1150 + /* "View.MemoryView":1154 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< @@ -17364,7 +16158,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; - /* "View.MemoryView":1149 + /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -17373,7 +16167,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ if (__pyx_t_1) { - /* "View.MemoryView":1151 + /* "View.MemoryView":1155 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< @@ -17382,7 +16176,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); - /* "View.MemoryView":1149 + /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< @@ -17392,7 +16186,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v goto __pyx_L4; } - /* "View.MemoryView":1153 + /* "View.MemoryView":1157 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< @@ -17405,7 +16199,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1154 + /* "View.MemoryView":1158 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< @@ -17414,7 +16208,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v */ (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); - /* "View.MemoryView":1155 + /* "View.MemoryView":1159 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -17423,7 +16217,7 @@ 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":1156 + /* "View.MemoryView":1160 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -17435,7 +16229,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } __pyx_L4:; - /* "View.MemoryView":1148 + /* "View.MemoryView":1152 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -17445,7 +16239,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v goto __pyx_L3; } - /* "View.MemoryView":1158 + /* "View.MemoryView":1162 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< @@ -17458,7 +16252,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1159 + /* "View.MemoryView":1163 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< @@ -17467,7 +16261,7 @@ 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":1163 + /* "View.MemoryView":1167 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< @@ -17476,7 +16270,7 @@ 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":1164 + /* "View.MemoryView":1168 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< @@ -17488,7 +16282,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v } __pyx_L3:; - /* "View.MemoryView":1136 + /* "View.MemoryView":1140 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< @@ -17499,7 +16293,7 @@ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v /* function exit code */ } -/* "View.MemoryView":1166 +/* "View.MemoryView":1170 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -17509,7 +16303,7 @@ 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":1169 + /* "View.MemoryView":1173 * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< @@ -17518,7 +16312,7 @@ 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":1166 + /* "View.MemoryView":1170 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -17529,57 +16323,57 @@ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memvi /* function exit code */ } -/* "View.MemoryView":1173 +/* "View.MemoryView":1177 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" - * cdef int i + * cdef Py_ssize_t shape, size = src.memview.view.itemsize */ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { - int __pyx_v_i; + Py_ssize_t __pyx_v_shape; Py_ssize_t __pyx_v_size; Py_ssize_t __pyx_r; Py_ssize_t __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - int __pyx_t_4; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; - /* "View.MemoryView":1176 + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: * "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 # <<<<<<<<<<<<<< + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< * - * for i in range(ndim): + * for shape in src.shape[:ndim]: */ __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_size = __pyx_t_1; - /* "View.MemoryView":1178 - * cdef Py_ssize_t size = src.memview.view.itemsize + /* "View.MemoryView":1181 + * cdef Py_ssize_t shape, size = src.memview.view.itemsize * - * for i in range(ndim): # <<<<<<<<<<<<<< - * size *= src.shape[i] + * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< + * size *= shape * */ - __pyx_t_2 = __pyx_v_ndim; - __pyx_t_3 = __pyx_t_2; - for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_i = __pyx_t_4; + __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); + for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { + __pyx_t_2 = __pyx_t_4; + __pyx_v_shape = (__pyx_t_2[0]); - /* "View.MemoryView":1179 + /* "View.MemoryView":1182 * - * for i in range(ndim): - * size *= src.shape[i] # <<<<<<<<<<<<<< + * for shape in src.shape[:ndim]: + * size *= shape # <<<<<<<<<<<<<< * * return size */ - __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); + __pyx_v_size = (__pyx_v_size * __pyx_v_shape); } - /* "View.MemoryView":1181 - * size *= src.shape[i] + /* "View.MemoryView":1184 + * size *= shape * * return size # <<<<<<<<<<<<<< * @@ -17588,12 +16382,12 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr __pyx_r = __pyx_v_size; goto __pyx_L0; - /* "View.MemoryView":1173 + /* "View.MemoryView":1177 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" - * cdef int i + * cdef Py_ssize_t shape, size = src.memview.view.itemsize */ /* function exit code */ @@ -17601,7 +16395,7 @@ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_sr return __pyx_r; } -/* "View.MemoryView":1184 +/* "View.MemoryView":1187 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -17617,7 +16411,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ int __pyx_t_3; int __pyx_t_4; - /* "View.MemoryView":1193 + /* "View.MemoryView":1196 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< @@ -17627,38 +16421,38 @@ 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":1194 + /* "View.MemoryView":1197 * * if order == 'F': * for idx in range(ndim): # <<<<<<<<<<<<<< * strides[idx] = stride - * stride = stride * shape[idx] + * stride *= shape[idx] */ __pyx_t_2 = __pyx_v_ndim; __pyx_t_3 = __pyx_t_2; for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_idx = __pyx_t_4; - /* "View.MemoryView":1195 + /* "View.MemoryView":1198 * if order == 'F': * for idx in range(ndim): * strides[idx] = stride # <<<<<<<<<<<<<< - * stride = stride * shape[idx] + * stride *= shape[idx] * else: */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1196 + /* "View.MemoryView":1199 * for idx in range(ndim): * strides[idx] = stride - * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * stride *= shape[idx] # <<<<<<<<<<<<<< * else: * for idx in range(ndim - 1, -1, -1): */ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); } - /* "View.MemoryView":1193 + /* "View.MemoryView":1196 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< @@ -17668,30 +16462,30 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ goto __pyx_L3; } - /* "View.MemoryView":1198 - * stride = stride * shape[idx] + /* "View.MemoryView":1201 + * stride *= shape[idx] * else: * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * strides[idx] = stride - * stride = stride * shape[idx] + * 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":1199 + /* "View.MemoryView":1202 * else: * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride # <<<<<<<<<<<<<< - * stride = stride * shape[idx] + * stride *= shape[idx] * */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - /* "View.MemoryView":1200 + /* "View.MemoryView":1203 * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride - * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * stride *= shape[idx] # <<<<<<<<<<<<<< * * return stride */ @@ -17700,8 +16494,8 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ } __pyx_L3:; - /* "View.MemoryView":1202 - * stride = stride * shape[idx] + /* "View.MemoryView":1205 + * stride *= shape[idx] * * return stride # <<<<<<<<<<<<<< * @@ -17710,7 +16504,7 @@ 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":1184 + /* "View.MemoryView":1187 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< @@ -17723,7 +16517,7 @@ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ return __pyx_r; } -/* "View.MemoryView":1205 +/* "View.MemoryView":1208 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -17743,8 +16537,11 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, struct __pyx_memoryview_obj *__pyx_t_4; int __pyx_t_5; int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; - /* "View.MemoryView":1216 + /* "View.MemoryView":1219 * cdef void *result * * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< @@ -17754,7 +16551,7 @@ 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":1217 + /* "View.MemoryView":1220 * * cdef size_t itemsize = src.memview.view.itemsize * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< @@ -17763,7 +16560,7 @@ 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":1219 + /* "View.MemoryView":1222 * cdef size_t size = slice_get_size(src, ndim) * * result = malloc(size) # <<<<<<<<<<<<<< @@ -17772,7 +16569,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_result = malloc(__pyx_v_size); - /* "View.MemoryView":1220 + /* "View.MemoryView":1223 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< @@ -17782,16 +16579,16 @@ 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":1221 + /* "View.MemoryView":1224 * result = malloc(size) * if not result: * _err(MemoryError, NULL) # <<<<<<<<<<<<<< * * */ - __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 1221, __pyx_L1_error) + __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(2, 1224, __pyx_L1_error) - /* "View.MemoryView":1220 + /* "View.MemoryView":1223 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< @@ -17800,7 +16597,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ } - /* "View.MemoryView":1224 + /* "View.MemoryView":1227 * * * tmpslice.data = result # <<<<<<<<<<<<<< @@ -17809,7 +16606,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ __pyx_v_tmpslice->data = ((char *)__pyx_v_result); - /* "View.MemoryView":1225 + /* "View.MemoryView":1228 * * tmpslice.data = result * tmpslice.memview = src.memview # <<<<<<<<<<<<<< @@ -17819,7 +16616,7 @@ 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":1226 + /* "View.MemoryView":1229 * tmpslice.data = result * tmpslice.memview = src.memview * for i in range(ndim): # <<<<<<<<<<<<<< @@ -17831,7 +16628,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1227 + /* "View.MemoryView":1230 * tmpslice.memview = src.memview * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< @@ -17840,7 +16637,7 @@ 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":1228 + /* "View.MemoryView":1231 * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< @@ -17850,7 +16647,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1L; } - /* "View.MemoryView":1230 + /* "View.MemoryView":1233 * tmpslice.suboffsets[i] = -1 * * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # <<<<<<<<<<<<<< @@ -17859,7 +16656,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (void)(__pyx_fill_contig_strides_array((&(__pyx_v_tmpslice->shape[0])), (&(__pyx_v_tmpslice->strides[0])), __pyx_v_itemsize, __pyx_v_ndim, __pyx_v_order)); - /* "View.MemoryView":1234 + /* "View.MemoryView":1237 * * * for i in range(ndim): # <<<<<<<<<<<<<< @@ -17871,7 +16668,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; - /* "View.MemoryView":1235 + /* "View.MemoryView":1238 * * for i in range(ndim): * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< @@ -17881,7 +16678,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_2 = (((__pyx_v_tmpslice->shape[__pyx_v_i]) == 1) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1236 + /* "View.MemoryView":1239 * for i in range(ndim): * if tmpslice.shape[i] == 1: * tmpslice.strides[i] = 0 # <<<<<<<<<<<<<< @@ -17890,7 +16687,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (__pyx_v_tmpslice->strides[__pyx_v_i]) = 0; - /* "View.MemoryView":1235 + /* "View.MemoryView":1238 * * for i in range(ndim): * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< @@ -17900,7 +16697,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, } } - /* "View.MemoryView":1238 + /* "View.MemoryView":1241 * tmpslice.strides[i] = 0 * * if slice_is_contig(src[0], order, ndim): # <<<<<<<<<<<<<< @@ -17910,7 +16707,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_t_2 = (__pyx_memviewslice_is_contig((__pyx_v_src[0]), __pyx_v_order, __pyx_v_ndim) != 0); if (__pyx_t_2) { - /* "View.MemoryView":1239 + /* "View.MemoryView":1242 * * if slice_is_contig(src[0], order, ndim): * memcpy(result, src.data, size) # <<<<<<<<<<<<<< @@ -17919,7 +16716,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, */ (void)(memcpy(__pyx_v_result, __pyx_v_src->data, __pyx_v_size)); - /* "View.MemoryView":1238 + /* "View.MemoryView":1241 * tmpslice.strides[i] = 0 * * if slice_is_contig(src[0], order, ndim): # <<<<<<<<<<<<<< @@ -17929,7 +16726,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, goto __pyx_L9; } - /* "View.MemoryView":1241 + /* "View.MemoryView":1244 * memcpy(result, src.data, size) * else: * copy_strided_to_strided(src, tmpslice, ndim, itemsize) # <<<<<<<<<<<<<< @@ -17941,7 +16738,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, } __pyx_L9:; - /* "View.MemoryView":1243 + /* "View.MemoryView":1246 * copy_strided_to_strided(src, tmpslice, ndim, itemsize) * * return result # <<<<<<<<<<<<<< @@ -17951,7 +16748,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __pyx_r = __pyx_v_result; goto __pyx_L0; - /* "View.MemoryView":1205 + /* "View.MemoryView":1208 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< @@ -17975,7 +16772,7 @@ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, return __pyx_r; } -/* "View.MemoryView":1248 +/* "View.MemoryView":1251 * * @cname('__pyx_memoryview_err_extents') * cdef int _err_extents(int i, Py_ssize_t extent1, # <<<<<<<<<<<<<< @@ -17990,25 +16787,28 @@ static int __pyx_memoryview_err_extents(int __pyx_v_i, Py_ssize_t __pyx_v_extent PyObject *__pyx_t_2 = NULL; PyObject *__pyx_t_3 = NULL; PyObject *__pyx_t_4 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif __Pyx_RefNannySetupContext("_err_extents", 0); - /* "View.MemoryView":1251 + /* "View.MemoryView":1254 * Py_ssize_t extent2) except -1 with gil: * raise ValueError("got differing extents in dimension %d (got %d and %d)" % * (i, extent1, extent2)) # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_err_dim') */ - __pyx_t_1 = __Pyx_PyInt_From_int(__pyx_v_i); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 1251, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyInt_From_int(__pyx_v_i); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 1254, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_extent1); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1251, __pyx_L1_error) + __pyx_t_2 = PyInt_FromSsize_t(__pyx_v_extent1); if (unlikely(!__pyx_t_2)) __PYX_ERR(2, 1254, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_extent2); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 1251, __pyx_L1_error) + __pyx_t_3 = PyInt_FromSsize_t(__pyx_v_extent2); if (unlikely(!__pyx_t_3)) __PYX_ERR(2, 1254, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); - __pyx_t_4 = PyTuple_New(3); if (unlikely(!__pyx_t_4)) __PYX_ERR(2, 1251, __pyx_L1_error) + __pyx_t_4 = PyTuple_New(3); if (unlikely(!__pyx_t_4)) __PYX_ERR(2, 1254, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_GIVEREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_1); @@ -18020,24 +16820,24 @@ static int __pyx_memoryview_err_extents(int __pyx_v_i, Py_ssize_t __pyx_v_extent __pyx_t_2 = 0; __pyx_t_3 = 0; - /* "View.MemoryView":1250 + /* "View.MemoryView":1253 * cdef int _err_extents(int i, Py_ssize_t extent1, * Py_ssize_t extent2) except -1 with gil: * raise ValueError("got differing extents in dimension %d (got %d and %d)" % # <<<<<<<<<<<<<< * (i, extent1, extent2)) * */ - __pyx_t_3 = __Pyx_PyString_Format(__pyx_kp_s_got_differing_extents_in_dimensi, __pyx_t_4); 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if (__pyx_t_2) { - /* "View.MemoryView":1291 + /* "View.MemoryView":1294 * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: * broadcasting = True # <<<<<<<<<<<<<< @@ -18436,7 +17245,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_broadcasting = 1; - /* "View.MemoryView":1292 + /* "View.MemoryView":1295 * if src.shape[i] == 1: * broadcasting = True * src.strides[i] = 0 # <<<<<<<<<<<<<< @@ -18445,7 +17254,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ (__pyx_v_src.strides[__pyx_v_i]) = 0; - /* "View.MemoryView":1290 + /* "View.MemoryView":1293 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< @@ -18455,7 +17264,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ goto __pyx_L7; } - /* "View.MemoryView":1294 + /* "View.MemoryView":1297 * src.strides[i] = 0 * else: * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< @@ -18463,11 +17272,11 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ * if src.suboffsets[i] >= 0: */ /*else*/ { - __pyx_t_6 = __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_6 == ((int)-1))) __PYX_ERR(2, 1294, __pyx_L1_error) + __pyx_t_6 = __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_6 == ((int)-1))) __PYX_ERR(2, 1297, __pyx_L1_error) } __pyx_L7:; - /* "View.MemoryView":1289 + /* "View.MemoryView":1292 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< @@ -18476,7 +17285,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1296 + /* "View.MemoryView":1299 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< @@ -18486,16 +17295,16 @@ 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":1297 + /* "View.MemoryView":1300 * * if src.suboffsets[i] >= 0: * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< * * if slices_overlap(&src, &dst, ndim, itemsize): */ - __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(2, 1297, __pyx_L1_error) + __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(2, 1300, __pyx_L1_error) - /* "View.MemoryView":1296 + /* "View.MemoryView":1299 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< @@ -18505,7 +17314,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } } - /* "View.MemoryView":1299 + /* "View.MemoryView":1302 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< @@ -18515,7 +17324,7 @@ 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":1301 + /* "View.MemoryView":1304 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< @@ -18525,7 +17334,7 @@ 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":1302 + /* "View.MemoryView":1305 * * if not slice_is_contig(src, order, ndim): * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< @@ -18534,7 +17343,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); - /* "View.MemoryView":1301 + /* "View.MemoryView":1304 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< @@ -18543,17 +17352,17 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1304 + /* "View.MemoryView":1307 * order = get_best_order(&dst, ndim) * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< * src = tmp * */ - __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(2, 1304, __pyx_L1_error) + __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(2, 1307, __pyx_L1_error) __pyx_v_tmpdata = __pyx_t_7; - /* "View.MemoryView":1305 + /* "View.MemoryView":1308 * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) * src = tmp # <<<<<<<<<<<<<< @@ -18562,7 +17371,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_src = __pyx_v_tmp; - /* "View.MemoryView":1299 + /* "View.MemoryView":1302 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< @@ -18571,7 +17380,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1307 + /* "View.MemoryView":1310 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< @@ -18581,7 +17390,7 @@ 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":1310 + /* "View.MemoryView":1313 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< @@ -18591,7 +17400,7 @@ 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":1311 + /* "View.MemoryView":1314 * * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< @@ -18600,7 +17409,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); - /* "View.MemoryView":1310 + /* "View.MemoryView":1313 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< @@ -18610,7 +17419,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ goto __pyx_L12; } - /* "View.MemoryView":1312 + /* "View.MemoryView":1315 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< @@ -18620,7 +17429,7 @@ 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":1313 + /* "View.MemoryView":1316 * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< @@ -18629,7 +17438,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); - /* "View.MemoryView":1312 + /* "View.MemoryView":1315 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< @@ -18639,7 +17448,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ } __pyx_L12:; - /* "View.MemoryView":1315 + /* "View.MemoryView":1318 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< @@ -18649,7 +17458,7 @@ 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":1317 + /* "View.MemoryView":1320 * if direct_copy: * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -18658,7 +17467,7 @@ 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":1318 + /* "View.MemoryView":1321 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< @@ -18667,7 +17476,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); - /* "View.MemoryView":1319 + /* "View.MemoryView":1322 * 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) # <<<<<<<<<<<<<< @@ -18676,7 +17485,7 @@ 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":1320 + /* "View.MemoryView":1323 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< @@ -18685,7 +17494,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1321 + /* "View.MemoryView":1324 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -18695,7 +17504,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":1315 + /* "View.MemoryView":1318 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< @@ -18704,7 +17513,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1307 + /* "View.MemoryView":1310 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< @@ -18713,7 +17522,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1323 + /* "View.MemoryView":1326 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< @@ -18727,25 +17536,25 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_t_8 = (__pyx_t_2 != 0); if (__pyx_t_8) { - /* "View.MemoryView":1326 + /* "View.MemoryView":1329 * * * transpose_memslice(&src) # <<<<<<<<<<<<<< * transpose_memslice(&dst) * */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(2, 1326, __pyx_L1_error) + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(2, 1329, __pyx_L1_error) - /* "View.MemoryView":1327 + /* "View.MemoryView":1330 * * 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 == ((int)0))) __PYX_ERR(2, 1327, __pyx_L1_error) + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(2, 1330, __pyx_L1_error) - /* "View.MemoryView":1323 + /* "View.MemoryView":1326 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< @@ -18754,7 +17563,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ } - /* "View.MemoryView":1329 + /* "View.MemoryView":1332 * transpose_memslice(&dst) * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -18763,7 +17572,7 @@ 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":1330 + /* "View.MemoryView":1333 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< @@ -18772,7 +17581,7 @@ 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":1331 + /* "View.MemoryView":1334 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -18781,7 +17590,7 @@ 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":1333 + /* "View.MemoryView":1336 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< @@ -18790,7 +17599,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ */ free(__pyx_v_tmpdata); - /* "View.MemoryView":1334 + /* "View.MemoryView":1337 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< @@ -18800,7 +17609,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ __pyx_r = 0; goto __pyx_L0; - /* "View.MemoryView":1265 + /* "View.MemoryView":1268 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< @@ -18824,7 +17633,7 @@ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_ return __pyx_r; } -/* "View.MemoryView":1337 +/* "View.MemoryView":1340 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< @@ -18839,7 +17648,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic int __pyx_t_2; int __pyx_t_3; - /* "View.MemoryView":1341 + /* "View.MemoryView":1344 * int ndim_other) nogil: * cdef int i * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< @@ -18848,7 +17657,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); - /* "View.MemoryView":1343 + /* "View.MemoryView":1346 * cdef int offset = ndim_other - ndim * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< @@ -18858,7 +17667,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; - /* "View.MemoryView":1344 + /* "View.MemoryView":1347 * * for i in range(ndim - 1, -1, -1): * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< @@ -18867,7 +17676,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); - /* "View.MemoryView":1345 + /* "View.MemoryView":1348 * for i in range(ndim - 1, -1, -1): * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< @@ -18876,7 +17685,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); - /* "View.MemoryView":1346 + /* "View.MemoryView":1349 * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< @@ -18886,7 +17695,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); } - /* "View.MemoryView":1348 + /* "View.MemoryView":1351 * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * * for i in range(offset): # <<<<<<<<<<<<<< @@ -18898,7 +17707,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1349 + /* "View.MemoryView":1352 * * for i in range(offset): * mslice.shape[i] = 1 # <<<<<<<<<<<<<< @@ -18907,7 +17716,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->shape[__pyx_v_i]) = 1; - /* "View.MemoryView":1350 + /* "View.MemoryView":1353 * for i in range(offset): * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< @@ -18916,7 +17725,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic */ (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); - /* "View.MemoryView":1351 + /* "View.MemoryView":1354 * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< @@ -18926,7 +17735,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L; } - /* "View.MemoryView":1337 + /* "View.MemoryView":1340 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< @@ -18937,7 +17746,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic /* function exit code */ } -/* "View.MemoryView":1359 +/* "View.MemoryView":1362 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -18948,7 +17757,7 @@ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslic 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":1363 + /* "View.MemoryView":1366 * * * if dtype_is_object: # <<<<<<<<<<<<<< @@ -18958,7 +17767,7 @@ 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":1364 + /* "View.MemoryView":1367 * * if dtype_is_object: * refcount_objects_in_slice_with_gil(dst.data, dst.shape, # <<<<<<<<<<<<<< @@ -18967,7 +17776,7 @@ 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); - /* "View.MemoryView":1363 + /* "View.MemoryView":1366 * * * if dtype_is_object: # <<<<<<<<<<<<<< @@ -18976,7 +17785,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i */ } - /* "View.MemoryView":1359 + /* "View.MemoryView":1362 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< @@ -18987,7 +17796,7 @@ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, i /* function exit code */ } -/* "View.MemoryView":1368 +/* "View.MemoryView":1371 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -19002,7 +17811,7 @@ 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":1371 + /* "View.MemoryView":1374 * Py_ssize_t *strides, int ndim, * bint inc) with gil: * refcount_objects_in_slice(data, shape, strides, ndim, inc) # <<<<<<<<<<<<<< @@ -19011,7 +17820,7 @@ 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":1368 + /* "View.MemoryView":1371 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -19026,7 +17835,7 @@ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_da #endif } -/* "View.MemoryView":1374 +/* "View.MemoryView":1377 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -19043,7 +17852,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss int __pyx_t_4; __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0); - /* "View.MemoryView":1378 + /* "View.MemoryView":1381 * cdef Py_ssize_t i * * for i in range(shape[0]): # <<<<<<<<<<<<<< @@ -19055,7 +17864,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "View.MemoryView":1379 + /* "View.MemoryView":1382 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< @@ -19065,7 +17874,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_4 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_4) { - /* "View.MemoryView":1380 + /* "View.MemoryView":1383 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< @@ -19075,7 +17884,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __pyx_t_4 = (__pyx_v_inc != 0); if (__pyx_t_4) { - /* "View.MemoryView":1381 + /* "View.MemoryView":1384 * if ndim == 1: * if inc: * Py_INCREF(( data)[0]) # <<<<<<<<<<<<<< @@ -19084,7 +17893,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss */ Py_INCREF((((PyObject **)__pyx_v_data)[0])); - /* "View.MemoryView":1380 + /* "View.MemoryView":1383 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< @@ -19094,7 +17903,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss goto __pyx_L6; } - /* "View.MemoryView":1383 + /* "View.MemoryView":1386 * Py_INCREF(( data)[0]) * else: * Py_DECREF(( data)[0]) # <<<<<<<<<<<<<< @@ -19106,7 +17915,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } __pyx_L6:; - /* "View.MemoryView":1379 + /* "View.MemoryView":1382 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< @@ -19116,7 +17925,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss goto __pyx_L5; } - /* "View.MemoryView":1385 + /* "View.MemoryView":1388 * Py_DECREF(( data)[0]) * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -19125,7 +17934,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss */ /*else*/ { - /* "View.MemoryView":1386 + /* "View.MemoryView":1389 * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, * ndim - 1, inc) # <<<<<<<<<<<<<< @@ -19136,7 +17945,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss } __pyx_L5:; - /* "View.MemoryView":1388 + /* "View.MemoryView":1391 * ndim - 1, inc) * * data += strides[0] # <<<<<<<<<<<<<< @@ -19146,7 +17955,7 @@ 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":1374 + /* "View.MemoryView":1377 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -19158,7 +17967,7 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ss __Pyx_RefNannyFinishContext(); } -/* "View.MemoryView":1394 +/* "View.MemoryView":1397 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -19168,7 +17977,7 @@ 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":1397 + /* "View.MemoryView":1400 * size_t itemsize, void *item, * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< @@ -19177,7 +17986,7 @@ 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":1398 + /* "View.MemoryView":1401 * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<< @@ -19186,7 +17995,7 @@ 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":1400 + /* "View.MemoryView":1403 * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< @@ -19195,7 +18004,7 @@ 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":1394 + /* "View.MemoryView":1397 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< @@ -19206,7 +18015,7 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst /* function exit code */ } -/* "View.MemoryView":1404 +/* "View.MemoryView":1407 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -19223,7 +18032,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t Py_ssize_t __pyx_t_3; Py_ssize_t __pyx_t_4; - /* "View.MemoryView":1408 + /* "View.MemoryView":1411 * size_t itemsize, void *item) nogil: * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< @@ -19232,7 +18041,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_stride = (__pyx_v_strides[0]); - /* "View.MemoryView":1409 + /* "View.MemoryView":1412 * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< @@ -19241,7 +18050,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ __pyx_v_extent = (__pyx_v_shape[0]); - /* "View.MemoryView":1411 + /* "View.MemoryView":1414 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -19251,7 +18060,7 @@ 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":1412 + /* "View.MemoryView":1415 * * if ndim == 1: * for i in range(extent): # <<<<<<<<<<<<<< @@ -19263,7 +18072,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1413 + /* "View.MemoryView":1416 * if ndim == 1: * for i in range(extent): * memcpy(data, item, itemsize) # <<<<<<<<<<<<<< @@ -19272,7 +18081,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t */ (void)(memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize)); - /* "View.MemoryView":1414 + /* "View.MemoryView":1417 * for i in range(extent): * memcpy(data, item, itemsize) * data += stride # <<<<<<<<<<<<<< @@ -19282,7 +18091,7 @@ 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":1411 + /* "View.MemoryView":1414 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< @@ -19292,7 +18101,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t goto __pyx_L3; } - /* "View.MemoryView":1416 + /* "View.MemoryView":1419 * data += stride * else: * for i in range(extent): # <<<<<<<<<<<<<< @@ -19305,7 +18114,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; - /* "View.MemoryView":1417 + /* "View.MemoryView":1420 * else: * for i in range(extent): * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< @@ -19314,7 +18123,7 @@ 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":1419 + /* "View.MemoryView":1422 * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) * data += stride # <<<<<<<<<<<<<< @@ -19326,7 +18135,7 @@ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t } __pyx_L3:; - /* "View.MemoryView":1404 + /* "View.MemoryView":1407 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< @@ -19350,6 +18159,9 @@ static PyObject *__pyx_pw_15View_dot_MemoryView_1__pyx_unpickle_Enum(PyObject *_ PyObject *__pyx_v___pyx_type = 0; long __pyx_v___pyx_checksum; PyObject *__pyx_v___pyx_state = 0; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__pyx_unpickle_Enum (wrapper)", 0); @@ -19427,6 +18239,9 @@ static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSE PyObject *__pyx_t_4 = NULL; PyObject *__pyx_t_5 = NULL; int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__pyx_unpickle_Enum", 0); /* "(tree fragment)":4 @@ -19615,6 +18430,9 @@ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *__ PyObject *__pyx_t_6 = NULL; PyObject *__pyx_t_7 = NULL; PyObject *__pyx_t_8 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__pyx_unpickle_Enum__set_state", 0); /* "(tree fragment)":12 @@ -19756,9 +18574,9 @@ static void __pyx_tp_dealloc_array(PyObject *o) { { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); - ++Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_array___dealloc__(o); - --Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->mode); @@ -19851,7 +18669,12 @@ static PyTypeObject __pyx_type___pyx_array = { sizeof(struct __pyx_array_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -19901,6 +18724,12 @@ static PyTypeObject __pyx_type___pyx_array = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { @@ -19959,7 +18788,12 @@ static PyTypeObject __pyx_type___pyx_MemviewEnum = { sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -20009,6 +18843,12 @@ static PyTypeObject __pyx_type___pyx_MemviewEnum = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; @@ -20045,9 +18885,9 @@ static void __pyx_tp_dealloc_memoryview(PyObject *o) { { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); - ++Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_memoryview___dealloc__(o); - --Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->obj); @@ -20209,7 +19049,12 @@ static PyTypeObject __pyx_type___pyx_memoryview = { sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -20259,6 +19104,12 @@ static PyTypeObject __pyx_type___pyx_memoryview = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; @@ -20284,9 +19135,9 @@ static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); - ++Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_memoryviewslice___dealloc__(o); - --Py_REFCNT(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->from_object); @@ -20336,7 +19187,12 @@ static PyTypeObject __pyx_type___pyx_memoryviewslice = { sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 @@ -20394,6 +19250,12 @@ static PyTypeObject __pyx_type___pyx_memoryviewslice = { #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif }; static PyMethodDef __pyx_methods[] = { @@ -20451,8 +19313,6 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_n_s_D, __pyx_k_D, sizeof(__pyx_k_D), 0, 0, 1, 1}, {&__pyx_n_s_Ellipsis, __pyx_k_Ellipsis, sizeof(__pyx_k_Ellipsis), 0, 0, 1, 1}, {&__pyx_kp_s_Empty_shape_tuple_for_cython_arr, __pyx_k_Empty_shape_tuple_for_cython_arr, sizeof(__pyx_k_Empty_shape_tuple_for_cython_arr), 0, 0, 1, 0}, - {&__pyx_kp_u_Format_string_allocated_too_shor, __pyx_k_Format_string_allocated_too_shor, sizeof(__pyx_k_Format_string_allocated_too_shor), 0, 1, 0, 0}, - {&__pyx_kp_u_Format_string_allocated_too_shor_2, __pyx_k_Format_string_allocated_too_shor_2, sizeof(__pyx_k_Format_string_allocated_too_shor_2), 0, 1, 0, 0}, {&__pyx_n_s_GPy_util_choleskies_cython, __pyx_k_GPy_util_choleskies_cython, sizeof(__pyx_k_GPy_util_choleskies_cython), 0, 0, 1, 1}, {&__pyx_kp_s_GPy_util_choleskies_cython_pyx, __pyx_k_GPy_util_choleskies_cython_pyx, sizeof(__pyx_k_GPy_util_choleskies_cython_pyx), 0, 0, 1, 0}, {&__pyx_n_s_ImportError, __pyx_k_ImportError, sizeof(__pyx_k_ImportError), 0, 0, 1, 1}, @@ -20468,11 +19328,9 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_kp_s_MemoryView_of_r_at_0x_x, __pyx_k_MemoryView_of_r_at_0x_x, sizeof(__pyx_k_MemoryView_of_r_at_0x_x), 0, 0, 1, 0}, {&__pyx_kp_s_MemoryView_of_r_object, __pyx_k_MemoryView_of_r_object, sizeof(__pyx_k_MemoryView_of_r_object), 0, 0, 1, 0}, {&__pyx_n_s_N, __pyx_k_N, sizeof(__pyx_k_N), 0, 0, 1, 1}, - {&__pyx_kp_u_Non_native_byte_order_not_suppor, __pyx_k_Non_native_byte_order_not_suppor, sizeof(__pyx_k_Non_native_byte_order_not_suppor), 0, 1, 0, 0}, {&__pyx_n_b_O, __pyx_k_O, sizeof(__pyx_k_O), 0, 0, 0, 1}, {&__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_k_Out_of_bounds_on_buffer_access_a, sizeof(__pyx_k_Out_of_bounds_on_buffer_access_a), 0, 0, 1, 0}, {&__pyx_n_s_PickleError, __pyx_k_PickleError, sizeof(__pyx_k_PickleError), 0, 0, 1, 1}, - {&__pyx_n_s_RuntimeError, __pyx_k_RuntimeError, sizeof(__pyx_k_RuntimeError), 0, 0, 1, 1}, {&__pyx_n_s_TypeError, __pyx_k_TypeError, sizeof(__pyx_k_TypeError), 0, 0, 1, 1}, {&__pyx_kp_s_Unable_to_convert_item_to_object, __pyx_k_Unable_to_convert_item_to_object, sizeof(__pyx_k_Unable_to_convert_item_to_object), 0, 0, 1, 0}, {&__pyx_n_s_ValueError, __pyx_k_ValueError, sizeof(__pyx_k_ValueError), 0, 0, 1, 1}, @@ -20522,8 +19380,6 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_n_s_mode, __pyx_k_mode, sizeof(__pyx_k_mode), 0, 0, 1, 1}, {&__pyx_n_s_name, __pyx_k_name, sizeof(__pyx_k_name), 0, 0, 1, 1}, {&__pyx_n_s_name_2, __pyx_k_name_2, sizeof(__pyx_k_name_2), 0, 0, 1, 1}, - {&__pyx_kp_u_ndarray_is_not_C_contiguous, __pyx_k_ndarray_is_not_C_contiguous, sizeof(__pyx_k_ndarray_is_not_C_contiguous), 0, 1, 0, 0}, - {&__pyx_kp_u_ndarray_is_not_Fortran_contiguou, __pyx_k_ndarray_is_not_Fortran_contiguou, sizeof(__pyx_k_ndarray_is_not_Fortran_contiguou), 0, 1, 0, 0}, {&__pyx_n_s_ndim, __pyx_k_ndim, sizeof(__pyx_k_ndim), 0, 0, 1, 1}, {&__pyx_n_s_new, __pyx_k_new, sizeof(__pyx_k_new), 0, 0, 1, 1}, {&__pyx_kp_s_no_default___reduce___due_to_non, __pyx_k_no_default___reduce___due_to_non, sizeof(__pyx_k_no_default___reduce___due_to_non), 0, 0, 1, 0}, @@ -20564,7 +19420,6 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = { {&__pyx_n_s_tril, __pyx_k_tril, sizeof(__pyx_k_tril), 0, 0, 1, 1}, {&__pyx_kp_s_unable_to_allocate_array_data, __pyx_k_unable_to_allocate_array_data, sizeof(__pyx_k_unable_to_allocate_array_data), 0, 0, 1, 0}, {&__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_update, __pyx_k_update, sizeof(__pyx_k_update), 0, 0, 1, 1}, {&__pyx_n_s_xrange, __pyx_k_xrange, sizeof(__pyx_k_xrange), 0, 0, 1, 1}, @@ -20578,15 +19433,14 @@ static CYTHON_SMALL_CODE int __Pyx_InitCachedBuiltins(void) { #else __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); 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__pyx_t_1 = 0; __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -21169,17 +20006,19 @@ static int __Pyx_modinit_function_import_code(void) { } -#if PY_MAJOR_VERSION < 3 -#ifdef CYTHON_NO_PYINIT_EXPORT -#define __Pyx_PyMODINIT_FUNC void -#else +#ifndef CYTHON_NO_PYINIT_EXPORT #define __Pyx_PyMODINIT_FUNC PyMODINIT_FUNC +#elif PY_MAJOR_VERSION < 3 +#ifdef __cplusplus +#define __Pyx_PyMODINIT_FUNC extern "C" void +#else +#define __Pyx_PyMODINIT_FUNC void #endif #else -#ifdef CYTHON_NO_PYINIT_EXPORT -#define __Pyx_PyMODINIT_FUNC PyObject * +#ifdef __cplusplus +#define __Pyx_PyMODINIT_FUNC extern "C" PyObject * #else -#define __Pyx_PyMODINIT_FUNC PyMODINIT_FUNC +#define __Pyx_PyMODINIT_FUNC PyObject * #endif #endif @@ -21263,6 +20102,9 @@ static CYTHON_SMALL_CODE int __pyx_pymod_exec_choleskies_cython(PyObject *__pyx_ PyObject *__pyx_t_1 = NULL; int __pyx_t_2; static PyThread_type_lock __pyx_t_3[8]; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannyDeclarations #if CYTHON_PEP489_MULTI_PHASE_INIT if (__pyx_m) { @@ -21330,10 +20172,9 @@ if (!__Pyx_RefNanny) { __pyx_d = PyModule_GetDict(__pyx_m); if (unlikely(!__pyx_d)) __PYX_ERR(0, 1, __pyx_L1_error) Py_INCREF(__pyx_d); __pyx_b = PyImport_AddModule(__Pyx_BUILTIN_MODULE_NAME); if (unlikely(!__pyx_b)) __PYX_ERR(0, 1, __pyx_L1_error) - __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) - #if CYTHON_COMPILING_IN_PYPY Py_INCREF(__pyx_b); - #endif + __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) + Py_INCREF(__pyx_cython_runtime); if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) __PYX_ERR(0, 1, __pyx_L1_error); /*--- Initialize various global constants etc. ---*/ if (__Pyx_InitGlobals() < 0) __PYX_ERR(0, 1, __pyx_L1_error) @@ -21359,10 +20200,10 @@ if (!__Pyx_RefNanny) { (void)__Pyx_modinit_global_init_code(); (void)__Pyx_modinit_variable_export_code(); (void)__Pyx_modinit_function_export_code(); - if (unlikely(__Pyx_modinit_type_init_code() != 0)) goto __pyx_L1_error; - if (unlikely(__Pyx_modinit_type_import_code() != 0)) goto __pyx_L1_error; + if (unlikely(__Pyx_modinit_type_init_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) + if (unlikely(__Pyx_modinit_type_import_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) (void)__Pyx_modinit_variable_import_code(); - if (unlikely(__Pyx_modinit_function_import_code() != 0)) goto __pyx_L1_error; + if (unlikely(__Pyx_modinit_function_import_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) /*--- Execution code ---*/ #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) if (__Pyx_patch_abc() < 0) __PYX_ERR(0, 1, __pyx_L1_error) @@ -21479,7 +20320,7 @@ if (!__Pyx_RefNanny) { * cdef strided = Enum("") # default * cdef indirect = Enum("") */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__36, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 286, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__31, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 286, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(generic); __Pyx_DECREF_SET(generic, __pyx_t_1); @@ -21493,7 +20334,7 @@ if (!__Pyx_RefNanny) { * cdef indirect = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__37, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 287, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__32, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 287, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(strided); __Pyx_DECREF_SET(strided, __pyx_t_1); @@ -21507,7 +20348,7 @@ if (!__Pyx_RefNanny) { * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__38, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 288, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__33, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 288, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); 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@@ -21568,29 +20409,29 @@ if (!__Pyx_RefNanny) { __pyx_t_3[7] = PyThread_allocate_lock(); memcpy(&(__pyx_memoryview_thread_locks[0]), __pyx_t_3, sizeof(__pyx_memoryview_thread_locks[0]) * (8)); - /* "View.MemoryView":545 + /* "View.MemoryView":549 * info.obj = self * * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 545, __pyx_L1_error) + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 549, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem((PyObject *)__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 545, __pyx_L1_error) + if (PyDict_SetItem((PyObject *)__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 549, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_memoryview_type); - /* "View.MemoryView":991 + /* "View.MemoryView":995 * return self.from_object * * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< * * */ - __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 991, __pyx_L1_error) + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(2, 995, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem((PyObject *)__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 991, __pyx_L1_error) + if (PyDict_SetItem((PyObject *)__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(2, 995, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; PyType_Modified(__pyx_memoryviewslice_type); @@ -21744,7 +20585,7 @@ static int __Pyx_ParseOptionalKeywords( } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 - if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { + if (likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { @@ -21771,7 +20612,7 @@ static int __Pyx_ParseOptionalKeywords( while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -21787,7 +20628,7 @@ static int __Pyx_ParseOptionalKeywords( while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -21824,6 +20665,32 @@ bad: return -1; } +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + /* GetModuleGlobalName */ #if CYTHON_USE_DICT_VERSIONS static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) @@ -21913,7 +20780,7 @@ static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args return result; } #if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) { +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); PyObject *globals = PyFunction_GET_GLOBALS(func); PyObject *argdefs = PyFunction_GET_DEFAULTS(func); @@ -21984,12 +20851,12 @@ static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, } #if PY_MAJOR_VERSION >= 3 result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, kwdefs, closure); #else result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, nargs, + args, (int)nargs, k, (int)nk, d, (int)nd, closure); #endif @@ -22121,11 +20988,7 @@ __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int i, retval=-1; Py_buffer *buf = &memview->view; __Pyx_RefNannySetupContext("init_memviewslice", 0); - if (!buf) { - PyErr_SetString(PyExc_ValueError, - "buf is NULL."); - goto fail; - } else if (memviewslice->memview || memviewslice->data) { + if (unlikely(memviewslice->memview || memviewslice->data)) { PyErr_SetString(PyExc_ValueError, "memviewslice is already initialized!"); goto fail; @@ -22204,13 +21067,13 @@ __Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int first_time; struct __pyx_memoryview_obj *memview = memslice->memview; - if (!memview || (PyObject *) memview == Py_None) + if (unlikely(!memview || (PyObject *) memview == Py_None)) return; - if (__pyx_get_slice_count(memview) < 0) + if (unlikely(__pyx_get_slice_count(memview) < 0)) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); first_time = __pyx_add_acquisition_count(memview) == 0; - if (first_time) { + if (unlikely(first_time)) { if (have_gil) { Py_INCREF((PyObject *) memview); } else { @@ -22224,18 +21087,16 @@ static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int last_time; struct __pyx_memoryview_obj *memview = memslice->memview; - if (!memview ) { - return; - } else if ((PyObject *) memview == Py_None) { + if (unlikely(!memview || (PyObject *) memview == Py_None)) { memslice->memview = NULL; return; } - if (__pyx_get_slice_count(memview) <= 0) + if (unlikely(__pyx_get_slice_count(memview) <= 0)) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); last_time = __pyx_sub_acquisition_count(memview) == 1; memslice->data = NULL; - if (last_time) { + if (unlikely(last_time)) { if (have_gil) { Py_CLEAR(memslice->memview); } else { @@ -22322,6 +21183,161 @@ static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, #endif } +/* GetTopmostException */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + /* RaiseException */ #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, @@ -22481,216 +21497,6 @@ bad: } #endif -/* DictGetItem */ -#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()) { - if (unlikely(PyTuple_Check(key))) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) { - PyErr_SetObject(PyExc_KeyError, args); - Py_DECREF(args); - } - } else { - PyErr_SetObject(PyExc_KeyError, key); - } - } - return NULL; - } - Py_INCREF(value); - return value; -} -#endif - -/* RaiseTooManyValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* RaiseNoneIterError */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* ExtTypeTest */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* GetTopmostException */ -#if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ -#if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ -#if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - /* ArgTypeTest */ static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) { @@ -23020,9 +21826,9 @@ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( if (stop < 0) stop += length; } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); length = stop - start; - if (unlikely(length <= 0)) - return PyUnicode_FromUnicode(NULL, 0); cstring += start; if (decode_func) { return decode_func(cstring, length, errors); @@ -23046,6 +21852,37 @@ static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject return (likely(r)) ? r : __Pyx_GetAttr3Default(d); } +/* RaiseTooManyValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseNoneIterError */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* ExtTypeTest */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + /* SwapException */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { @@ -23111,7 +21948,7 @@ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { { #if PY_MAJOR_VERSION >= 3 if (level == -1) { - if (strchr(__Pyx_MODULE_NAME, '.')) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); if (!module) { @@ -23248,7 +22085,9 @@ static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObj /* PyIntBinop */ #if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) { +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) { + (void)inplace; + (void)zerodivision_check; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { const long b = intval; @@ -23473,6 +22312,28 @@ bad: return -1; } +/* PyObjectGetAttrStrNoError */ +static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + /* SetupReduce */ static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { int ret; @@ -23500,43 +22361,51 @@ static int __Pyx_setup_reduce(PyObject* type_obj) { PyObject *setstate = NULL; PyObject *setstate_cython = NULL; #if CYTHON_USE_PYTYPE_LOOKUP - if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto GOOD; + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; #else - if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto GOOD; + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; #endif #if CYTHON_USE_PYTYPE_LOOKUP - object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD; + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #else - object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD; + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #endif - reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto BAD; + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; if (reduce_ex == object_reduce_ex) { #if CYTHON_USE_PYTYPE_LOOKUP - object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD; + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #else - object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD; + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #endif - reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto BAD; + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { - reduce_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_cython); if (unlikely(!reduce_cython)) goto BAD; - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto BAD; + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); if (!setstate) PyErr_Clear(); if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { - setstate_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate_cython); if (unlikely(!setstate_cython)) goto BAD; - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto BAD; + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } } PyType_Modified((PyTypeObject*)type_obj); } } - goto GOOD; -BAD: + goto __PYX_GOOD; +__PYX_BAD: if (!PyErr_Occurred()) PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); ret = -1; -GOOD: +__PYX_GOOD: #if !CYTHON_USE_PYTYPE_LOOKUP Py_XDECREF(object_reduce); Py_XDECREF(object_reduce_ex); @@ -23612,7 +22481,7 @@ bad: /* CLineInTraceback */ #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { PyObject *use_cline; PyObject *ptype, *pvalue, *ptraceback; #if CYTHON_COMPILING_IN_CPYTHON @@ -23716,7 +22585,7 @@ static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } @@ -23820,7 +22689,6 @@ bad: #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); @@ -23834,7 +22702,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return; } if ((0)) {} - else if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); view->obj = NULL; Py_DECREF(obj); } @@ -23958,7 +22825,7 @@ static int __Pyx_BufFmt_ParseNumber(const char** ts) { return -1; } else { count = *t++ - '0'; - while (*t >= '0' && *t < '9') { + while (*t >= '0' && *t <= '9') { count *= 10; count += *t++ - '0'; } @@ -23979,6 +22846,7 @@ static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { + case '?': return "'bool'"; case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; @@ -24021,7 +22889,7 @@ static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { - case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); @@ -24105,7 +22973,7 @@ static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; - case 'B': case 'H': case 'I': case 'L': case 'Q': + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); @@ -24249,9 +23117,7 @@ static PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; - int i = 0, number; - int ndim = ctx->head->field->type->ndim; -; + int i = 0, number, ndim; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, @@ -24259,6 +23125,7 @@ __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; @@ -24384,12 +23251,12 @@ static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const cha return NULL; } CYTHON_FALLTHROUGH; - case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': - if (ctx->enc_type == *ts && got_Z == ctx->is_complex && - ctx->enc_packmode == ctx->new_packmode) { + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; @@ -24475,13 +23342,13 @@ __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) if (buf->strides) { if (spec & __Pyx_MEMVIEW_CONTIG) { if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { - if (buf->strides[dim] != sizeof(void *)) { + if (unlikely(buf->strides[dim] != sizeof(void *))) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly contiguous " "in dimension %d.", dim); goto fail; } - } else if (buf->strides[dim] != buf->itemsize) { + } else if (unlikely(buf->strides[dim] != buf->itemsize)) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); @@ -24492,7 +23359,7 @@ __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) Py_ssize_t stride = buf->strides[dim]; if (stride < 0) stride = -stride; - if (stride < buf->itemsize) { + if (unlikely(stride < buf->itemsize)) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); @@ -24500,17 +23367,17 @@ __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) } } } else { - if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { + if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not contiguous in " "dimension %d", dim); goto fail; - } else if (spec & (__Pyx_MEMVIEW_PTR)) { + } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not indirect in " "dimension %d", dim); goto fail; - } else if (buf->suboffsets) { + } else if (unlikely(buf->suboffsets)) { PyErr_SetString(PyExc_ValueError, "Buffer exposes suboffsets but no strides"); goto fail; @@ -24524,7 +23391,7 @@ static int __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) { if (spec & __Pyx_MEMVIEW_DIRECT) { - if (buf->suboffsets && buf->suboffsets[dim] >= 0) { + if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { PyErr_Format(PyExc_ValueError, "Buffer not compatible with direct access " "in dimension %d.", dim); @@ -24532,7 +23399,7 @@ __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec } } if (spec & __Pyx_MEMVIEW_PTR) { - if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { + if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly accessible " "in dimension %d.", dim); @@ -24550,9 +23417,7 @@ __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) if (c_or_f_flag & __Pyx_IS_F_CONTIG) { Py_ssize_t stride = 1; for (i = 0; i < ndim; i++) { - if (stride * buf->itemsize != buf->strides[i] && - buf->shape[i] > 1) - { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { PyErr_SetString(PyExc_ValueError, "Buffer not fortran contiguous."); goto fail; @@ -24562,8 +23427,7 @@ __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { Py_ssize_t stride = 1; for (i = ndim - 1; i >- 1; i--) { - if (stride * buf->itemsize != buf->strides[i] && - buf->shape[i] > 1) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { PyErr_SetString(PyExc_ValueError, "Buffer not C contiguous."); goto fail; @@ -24604,7 +23468,7 @@ static int __Pyx_ValidateAndInit_memviewslice( goto fail; } buf = &memview->view; - if (buf->ndim != ndim) { + if (unlikely(buf->ndim != ndim)) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", ndim, buf->ndim); @@ -24612,9 +23476,9 @@ static int __Pyx_ValidateAndInit_memviewslice( } if (new_memview) { __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; } - if ((unsigned) buf->itemsize != dtype->size) { + if (unlikely((unsigned) buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", @@ -24625,15 +23489,17 @@ static int __Pyx_ValidateAndInit_memviewslice( (dtype->size > 1) ? "s" : ""); goto fail; } - for (i = 0; i < ndim; i++) { - spec = axes_specs[i]; - if (!__pyx_check_strides(buf, i, ndim, spec)) - goto fail; - if (!__pyx_check_suboffsets(buf, i, ndim, spec)) + if (buf->len > 0) { + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) + goto fail; + if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) + goto fail; + } + if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) goto fail; } - if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) - goto fail; if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, new_memview != NULL) == -1)) { goto fail; @@ -24843,13 +23709,13 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { float r = b.imag / b.real; - float s = 1.0 / (b.real + b.imag * r); + float s = (float)(1.0) / (b.real + b.imag * r); return __pyx_t_float_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { float r = b.real / b.imag; - float s = 1.0 / (b.imag + b.real * r); + float s = (float)(1.0) / (b.imag + b.real * r); return __pyx_t_float_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -24907,7 +23773,6 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o case 1: return a; case 2: - z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(a, a); case 3: z = __Pyx_c_prod_float(a, a); @@ -24929,7 +23794,7 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o theta = 0; } else { r = -a.real; - theta = atan2f(0, -1); + theta = atan2f(0.0, -1.0); } } else { r = __Pyx_c_abs_float(a); @@ -24998,13 +23863,13 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { double r = b.imag / b.real; - double s = 1.0 / (b.real + b.imag * r); + double s = (double)(1.0) / (b.real + b.imag * r); return __pyx_t_double_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { double r = b.real / b.imag; - double s = 1.0 / (b.imag + b.real * r); + double s = (double)(1.0) / (b.imag + b.real * r); return __pyx_t_double_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -25062,7 +23927,6 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o case 1: return a; case 2: - z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(a, a); case 3: z = __Pyx_c_prod_double(a, a); @@ -25084,7 +23948,7 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o theta = 0; } else { r = -a.real; - theta = atan2(0, -1); + theta = atan2(0.0, -1.0); } } else { r = __Pyx_c_abs_double(a); @@ -25100,37 +23964,6 @@ static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *o #endif #endif -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { - const enum NPY_TYPES neg_one = (enum NPY_TYPES) ((enum NPY_TYPES) 0 - (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); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(enum NPY_TYPES) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - 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); - } -} - /* MemviewSliceCopyTemplate */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, @@ -25149,7 +23982,7 @@ __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, struct __pyx_memoryview_obj *memview_obj = NULL; __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); for (i = 0; i < ndim; i++) { - if (from_mvs->suboffsets[i] >= 0) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " "indirect dimensions (axis %d)", i); goto fail; diff --git a/GPy/util/linalg_cython.c b/GPy/util/linalg_cython.c index d48e943a..e576b9ed 100644 --- a/GPy/util/linalg_cython.c +++ b/GPy/util/linalg_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.29.2 */ +/* Generated by Cython 0.29.21 */ #define PY_SSIZE_T_CLEAN #include "Python.h" @@ -7,8 +7,8 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) #error Cython requires Python 2.6+ or Python 3.3+. #else -#define CYTHON_ABI "0_29_2" -#define CYTHON_HEX_VERSION 0x001D02F0 +#define CYTHON_ABI "0_29_21" +#define CYTHON_HEX_VERSION 0x001D15F0 #define CYTHON_FUTURE_DIVISION 0 #include #ifndef offsetof @@ -310,8 +310,13 @@ #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else #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) +#endif #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES @@ -346,26 +351,6 @@ #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif -#if CYTHON_USE_DICT_VERSIONS -#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ - (version_var) = __PYX_GET_DICT_VERSION(dict);\ - (cache_var) = (value); -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ - static PY_UINT64_T __pyx_dict_version = 0;\ - static PyObject *__pyx_dict_cached_value = NULL;\ - if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ - (VAR) = __pyx_dict_cached_value;\ - } else {\ - (VAR) = __pyx_dict_cached_value = (LOOKUP);\ - __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ - }\ - } -#else -#define __PYX_GET_DICT_VERSION(dict) (0) -#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) -#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); -#endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) @@ -398,7 +383,7 @@ typedef int Py_tss_t; static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { *key = PyThread_create_key(); - return 0; // PyThread_create_key reports success always + return 0; } static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); @@ -421,7 +406,7 @@ static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { return PyThread_get_key_value(*key); } -#endif // TSS (Thread Specific Storage) API +#endif #if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) #define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) #else @@ -450,7 +435,11 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 @@ -499,8 +488,10 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode #define PyObject_Unicode PyObject_Str #endif +#endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) @@ -511,6 +502,13 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif #if CYTHON_ASSUME_SAFE_MACROS #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) #else @@ -550,7 +548,7 @@ static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : (Py_INCREF(func), func)) + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif @@ -591,11 +589,10 @@ static CYTHON_INLINE float __PYX_NAN() { #define __Pyx_truncl truncl #endif - +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } #define __PYX_ERR(f_index, lineno, Ln_error) \ -{ \ - __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ -} + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } #ifndef __PYX_EXTERN_C #ifdef __cplusplus @@ -612,7 +609,13 @@ static CYTHON_INLINE float __PYX_NAN() { #include #include #include "numpy/arrayobject.h" +#include "numpy/ndarrayobject.h" +#include "numpy/ndarraytypes.h" +#include "numpy/arrayscalars.h" #include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + #include "pythread.h" #ifdef _OPENMP #include @@ -626,7 +629,8 @@ typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* enc const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) #define __PYX_DEFAULT_STRING_ENCODING "" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize @@ -898,7 +902,7 @@ typedef struct { #endif -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":776 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":690 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -907,7 +911,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":691 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -916,7 +920,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -925,7 +929,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":779 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":693 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -934,7 +938,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":697 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -943,7 +947,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":784 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":698 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -952,7 +956,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":785 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -961,7 +965,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":786 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":700 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -970,7 +974,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":790 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":704 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -979,7 +983,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":791 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":705 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -988,7 +992,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":800 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -997,7 +1001,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":801 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":715 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1006,7 +1010,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":802 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":716 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1015,7 +1019,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":804 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":718 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1024,7 +1028,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":805 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":719 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1033,7 +1037,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":806 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":720 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1042,7 +1046,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":808 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":722 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1051,7 +1055,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":809 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":723 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1060,7 +1064,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":811 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":725 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1069,7 +1073,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":812 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":726 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1078,7 +1082,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":727 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1113,7 +1117,7 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do /*--- Type declarations ---*/ -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":729 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1122,7 +1126,7 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":730 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1131,7 +1135,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":817 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":731 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1140,7 +1144,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":819 +/* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":733 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1300,77 +1304,6 @@ static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject #endif #define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) -/* PyObjectCall.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); -#else -#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) -#endif - -/* RaiseException.proto */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); - -/* PyCFunctionFastCall.proto */ -#if CYTHON_FAST_PYCCALL -static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); -#else -#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) -#endif - -/* PyFunctionFastCall.proto */ -#if CYTHON_FAST_PYCALL -#define __Pyx_PyFunction_FastCall(func, args, nargs)\ - __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) -#if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs); -#else -#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) -#endif -#define __Pyx_BUILD_ASSERT_EXPR(cond)\ - (sizeof(char [1 - 2*!(cond)]) - 1) -#ifndef Py_MEMBER_SIZE -#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) -#endif - static size_t __pyx_pyframe_localsplus_offset = 0; - #include "frameobject.h" - #define __Pxy_PyFrame_Initialize_Offsets()\ - ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ - (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) - #define __Pyx_PyFrame_GetLocalsplus(frame)\ - (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) -#endif - -/* PyObjectCallMethO.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); -#endif - -/* PyObjectCallOneArg.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); - -/* DictGetItem.proto */ -#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); -#define __Pyx_PyObject_Dict_GetItem(obj, name)\ - (likely(PyDict_CheckExact(obj)) ?\ - __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) -#else -#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) -#endif - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - -/* ExtTypeTest.proto */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); - /* GetTopmostException.proto */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); @@ -1403,6 +1336,16 @@ static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); #endif +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + /* TypeImport.proto */ #ifndef __PYX_HAVE_RT_ImportType_proto #define __PYX_HAVE_RT_ImportType_proto @@ -1414,6 +1357,32 @@ enum __Pyx_ImportType_CheckSize { static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); #endif +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + /* CLineInTraceback.proto */ #ifdef CYTHON_CLINE_IN_TRACEBACK #define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) @@ -1564,9 +1533,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); #endif #endif -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); - /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); @@ -1688,8 +1654,17 @@ 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_generic = 0; +static PyTypeObject *__pyx_ptype_5numpy_number = 0; +static PyTypeObject *__pyx_ptype_5numpy_integer = 0; +static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; +static PyTypeObject *__pyx_ptype_5numpy_floating = 0; +static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; +static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; +static PyTypeObject *__pyx_ptype_5numpy_character = 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' */ @@ -1701,9 +1676,6 @@ int __pyx_module_is_main_GPy__util__linalg_cython = 0; /* Implementation of 'GPy.util.linalg_cython' */ static PyObject *__pyx_builtin_xrange; -static PyObject *__pyx_builtin_ValueError; -static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_ImportError; static const char __pyx_k_A[] = "A"; static const char __pyx_k_L[] = "L"; @@ -1720,33 +1692,20 @@ static const char __pyx_k_test[] = "__test__"; static const char __pyx_k_range[] = "range"; static const char __pyx_k_upper[] = "upper"; static const char __pyx_k_xrange[] = "xrange"; -static const char __pyx_k_ValueError[] = "ValueError"; static const char __pyx_k_cholupdate[] = "cholupdate"; static const char __pyx_k_symmetrify[] = "symmetrify"; static const char __pyx_k_ImportError[] = "ImportError"; -static const char __pyx_k_RuntimeError[] = "RuntimeError"; static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; static const char __pyx_k_GPy_util_linalg_cython[] = "GPy.util.linalg_cython"; static const char __pyx_k_GPy_util_linalg_cython_pyx[] = "GPy/util/linalg_cython.pyx"; -static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; -static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; -static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; -static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; -static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; -static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; static PyObject *__pyx_n_s_A; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; -static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_n_s_GPy_util_linalg_cython; static PyObject *__pyx_kp_s_GPy_util_linalg_cython_pyx; static PyObject *__pyx_n_s_ImportError; static PyObject *__pyx_n_s_L; static PyObject *__pyx_n_s_N; -static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; -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_n_s_cline_in_traceback; @@ -1754,8 +1713,6 @@ static PyObject *__pyx_n_s_i; static PyObject *__pyx_n_s_j; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_name; -static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; -static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; static PyObject *__pyx_n_s_r; @@ -1763,25 +1720,17 @@ static PyObject *__pyx_n_s_range; static PyObject *__pyx_n_s_s; static PyObject *__pyx_n_s_symmetrify; static PyObject *__pyx_n_s_test; -static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; 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} } } @@ -2050,6 +2001,9 @@ static PyObject *__pyx_pw_3GPy_4util_13linalg_cython_3cholupdate(PyObject *__pyx PyArrayObject *__pyx_v_x = 0; PyArrayObject *__pyx_v_L = 0; int __pyx_v_N; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("cholupdate (wrapper)", 0); @@ -2143,27 +2097,12 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P 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; - Py_ssize_t __pyx_t_16; - int __pyx_t_17; - int __pyx_t_18; - int __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; - Py_ssize_t __pyx_t_29; - Py_ssize_t __pyx_t_30; + int __pyx_t_10; + int __pyx_t_11; + int __pyx_t_12; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannySetupContext("cholupdate", 0); __pyx_pybuffer_x.pybuffer.buf = NULL; __pyx_pybuffer_x.refcount = 0; @@ -2233,9 +2172,9 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P * s = x[j] / L[j, j] * L[j, j] = r */ - __pyx_t_10 = __pyx_v_j; - __pyx_t_11 = __pyx_v_j; - __pyx_v_c = (__pyx_v_r / (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_10, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_11, __pyx_pybuffernd_L.diminfo[1].strides))); + __pyx_t_9 = __pyx_v_j; + __pyx_t_8 = __pyx_v_j; + __pyx_v_c = (__pyx_v_r / (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_9, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_8, __pyx_pybuffernd_L.diminfo[1].strides))); /* "GPy/util/linalg_cython.pyx":32 * r = sqrt(L[j, j] * L[j, j] + x[j] * x[j]) @@ -2244,10 +2183,10 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P * L[j, j] = r * for i in xrange(j): */ - __pyx_t_12 = __pyx_v_j; - __pyx_t_13 = __pyx_v_j; - __pyx_t_14 = __pyx_v_j; - __pyx_v_s = ((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_x.rcbuffer->pybuffer.buf, __pyx_t_12, __pyx_pybuffernd_x.diminfo[0].strides)) / (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_14, __pyx_pybuffernd_L.diminfo[1].strides))); + __pyx_t_8 = __pyx_v_j; + __pyx_t_9 = __pyx_v_j; + __pyx_t_7 = __pyx_v_j; + __pyx_v_s = ((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_x.rcbuffer->pybuffer.buf, __pyx_t_8, __pyx_pybuffernd_x.diminfo[0].strides)) / (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_9, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_7, __pyx_pybuffernd_L.diminfo[1].strides))); /* "GPy/util/linalg_cython.pyx":33 * c = r / L[j, j] @@ -2256,9 +2195,9 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P * for i in xrange(j): * L[i, j] = (L[i, j] + s * x[i]) / c */ - __pyx_t_15 = __pyx_v_j; 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/* "GPy/util/linalg_cython.pyx":36 * for i in xrange(j): @@ -2292,11 +2231,11 @@ static PyObject *__pyx_pf_3GPy_4util_13linalg_cython_2cholupdate(CYTHON_UNUSED P * x[i] = c * x[i] - s * L[i, j] # <<<<<<<<<<<<<< * r = sqrt(L[j, j]) */ - __pyx_t_25 = __pyx_v_i; - __pyx_t_26 = __pyx_v_i; - __pyx_t_27 = __pyx_v_j; - __pyx_t_28 = __pyx_v_i; - *__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_x.rcbuffer->pybuffer.buf, __pyx_t_28, __pyx_pybuffernd_x.diminfo[0].strides) = ((__pyx_v_c * (*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_x.rcbuffer->pybuffer.buf, __pyx_t_25, __pyx_pybuffernd_x.diminfo[0].strides))) - (__pyx_v_s * (*__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_t_8 = __pyx_v_i; + __pyx_t_7 = __pyx_v_i; + __pyx_t_9 = __pyx_v_j; + __pyx_t_5 = __pyx_v_i; + *__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_x.rcbuffer->pybuffer.buf, __pyx_t_5, __pyx_pybuffernd_x.diminfo[0].strides) = ((__pyx_v_c * (*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_x.rcbuffer->pybuffer.buf, __pyx_t_8, __pyx_pybuffernd_x.diminfo[0].strides))) - (__pyx_v_s * (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_7, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_9, __pyx_pybuffernd_L.diminfo[1].strides)))); 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+ int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; __Pyx_RefNannyDeclarations #if CYTHON_PEP489_MULTI_PHASE_INIT if (__pyx_m) { @@ -5253,10 +3753,9 @@ if (!__Pyx_RefNanny) { __pyx_d = PyModule_GetDict(__pyx_m); if (unlikely(!__pyx_d)) __PYX_ERR(0, 1, __pyx_L1_error) Py_INCREF(__pyx_d); __pyx_b = PyImport_AddModule(__Pyx_BUILTIN_MODULE_NAME); if (unlikely(!__pyx_b)) __PYX_ERR(0, 1, __pyx_L1_error) - __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) - #if CYTHON_COMPILING_IN_PYPY Py_INCREF(__pyx_b); - #endif + __pyx_cython_runtime = PyImport_AddModule((char *) "cython_runtime"); if (unlikely(!__pyx_cython_runtime)) __PYX_ERR(0, 1, __pyx_L1_error) + Py_INCREF(__pyx_cython_runtime); if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) __PYX_ERR(0, 1, __pyx_L1_error); /*--- Initialize various global constants etc. ---*/ if (__Pyx_InitGlobals() < 0) __PYX_ERR(0, 1, __pyx_L1_error) @@ -5283,7 +3782,7 @@ if (!__Pyx_RefNanny) { (void)__Pyx_modinit_variable_export_code(); (void)__Pyx_modinit_function_export_code(); (void)__Pyx_modinit_type_init_code(); - if (unlikely(__Pyx_modinit_type_import_code() != 0)) goto __pyx_L1_error; + if (unlikely(__Pyx_modinit_type_import_code() < 0)) __PYX_ERR(0, 1, __pyx_L1_error) (void)__Pyx_modinit_variable_import_code(); (void)__Pyx_modinit_function_import_code(); /*--- Execution code ---*/ @@ -5325,12 +3824,12 @@ if (!__Pyx_RefNanny) { if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../.conda/envs/bays-dev-py2/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":1046 - * raise ImportError("numpy.core.umath failed to import") + /* "../../.pyenv/versions/gpy391/lib/python3.9/site-packages/numpy/__init__.pxd":1016 * - * cdef inline int import_ufunc() except -1: # <<<<<<<<<<<<<< - * try: - * _import_umath() + * + * cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: # <<<<<<<<<<<<<< + * """ + * returns the unit part of the dtype for a numpy datetime64 object. */ /*--- Wrapped vars code ---*/ @@ -5465,7 +3964,7 @@ static int __Pyx_ParseOptionalKeywords( } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 - if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { + if (likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { @@ -5492,7 +3991,7 @@ static int __Pyx_ParseOptionalKeywords( while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -5508,7 +4007,7 @@ static int __Pyx_ParseOptionalKeywords( while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; @@ -5612,7 +4111,7 @@ static int __Pyx_BufFmt_ParseNumber(const char** ts) { return -1; } else { count = *t++ - '0'; - while (*t >= '0' && *t < '9') { + while (*t >= '0' && *t <= '9') { count *= 10; count += *t++ - '0'; } @@ -5633,6 +4132,7 @@ static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { + case '?': return "'bool'"; case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; @@ -5675,7 +4175,7 @@ static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { - case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); @@ -5759,7 +4259,7 @@ static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; - case 'B': case 'H': case 'I': case 'L': case 'Q': + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); @@ -5903,9 +4403,7 @@ static PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; - int i = 0, number; - int ndim = ctx->head->field->type->ndim; -; + int i = 0, number, ndim; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, @@ -5913,6 +4411,7 @@ __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; @@ -6038,12 +4537,12 @@ static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const cha return NULL; } CYTHON_FALLTHROUGH; - case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': - if (ctx->enc_type == *ts && got_Z == ctx->is_complex && - ctx->enc_packmode == ctx->new_packmode) { + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; @@ -6112,7 +4611,7 @@ static int __Pyx__GetBufferAndValidate( __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } - if (unlikely((unsigned)buf->itemsize != dtype->size)) { + if (unlikely((size_t)buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", @@ -6150,6 +4649,161 @@ static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject } #endif +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + /* PyObjectCall */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { @@ -6329,418 +4983,6 @@ bad: } #endif -/* PyCFunctionFastCall */ - #if CYTHON_FAST_PYCCALL -static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { - PyCFunctionObject *func = (PyCFunctionObject*)func_obj; - PyCFunction meth = PyCFunction_GET_FUNCTION(func); - PyObject *self = PyCFunction_GET_SELF(func); - int flags = PyCFunction_GET_FLAGS(func); - assert(PyCFunction_Check(func)); - assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); - assert(nargs >= 0); - assert(nargs == 0 || args != NULL); - /* _PyCFunction_FastCallDict() must not be called with an exception set, - because it may clear it (directly or indirectly) and so the - caller loses its exception */ - assert(!PyErr_Occurred()); - if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { - return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); - } else { - return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); - } -} -#endif - -/* PyFunctionFastCall */ - #if CYTHON_FAST_PYCALL -static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, - PyObject *globals) { - PyFrameObject *f; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject **fastlocals; - Py_ssize_t i; - PyObject *result; - assert(globals != NULL); - /* XXX Perhaps we should create a specialized - PyFrame_New() that doesn't take locals, but does - take builtins without sanity checking them. - */ - assert(tstate != NULL); - f = PyFrame_New(tstate, co, globals, NULL); - if (f == NULL) { - return NULL; - } - fastlocals = __Pyx_PyFrame_GetLocalsplus(f); - for (i = 0; i < na; i++) { - Py_INCREF(*args); - fastlocals[i] = *args++; - } - result = PyEval_EvalFrameEx(f,0); - ++tstate->recursion_depth; - Py_DECREF(f); - --tstate->recursion_depth; - return result; -} -#if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) { - PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); - PyObject *globals = PyFunction_GET_GLOBALS(func); - PyObject *argdefs = PyFunction_GET_DEFAULTS(func); - PyObject *closure; -#if PY_MAJOR_VERSION >= 3 - PyObject *kwdefs; -#endif - PyObject *kwtuple, **k; - PyObject **d; - Py_ssize_t nd; - Py_ssize_t nk; - PyObject *result; - assert(kwargs == NULL || PyDict_Check(kwargs)); - nk = kwargs ? PyDict_Size(kwargs) : 0; - if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { - return NULL; - } - if ( -#if PY_MAJOR_VERSION >= 3 - co->co_kwonlyargcount == 0 && -#endif - likely(kwargs == NULL || nk == 0) && - co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { - if (argdefs == NULL && co->co_argcount == nargs) { - result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); - goto done; - } - else if (nargs == 0 && argdefs != NULL - && co->co_argcount == Py_SIZE(argdefs)) { - /* function called with no arguments, but all parameters have - a default value: use default values as arguments .*/ - args = &PyTuple_GET_ITEM(argdefs, 0); - result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); - goto done; - } - } - if (kwargs != NULL) { - Py_ssize_t pos, i; - kwtuple = PyTuple_New(2 * nk); - if (kwtuple == NULL) { - result = NULL; - goto done; - } - k = &PyTuple_GET_ITEM(kwtuple, 0); - pos = i = 0; - while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { - Py_INCREF(k[i]); - Py_INCREF(k[i+1]); - i += 2; - } - nk = i / 2; - } - else { - kwtuple = NULL; - k = NULL; - } - closure = PyFunction_GET_CLOSURE(func); -#if PY_MAJOR_VERSION >= 3 - kwdefs = PyFunction_GET_KW_DEFAULTS(func); -#endif - if (argdefs != NULL) { - d = &PyTuple_GET_ITEM(argdefs, 0); - nd = Py_SIZE(argdefs); - } - else { - d = NULL; - nd = 0; - } -#if PY_MAJOR_VERSION >= 3 - result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, nargs, - k, (int)nk, - d, (int)nd, kwdefs, closure); -#else - result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, nargs, - k, (int)nk, - d, (int)nd, closure); -#endif - Py_XDECREF(kwtuple); -done: - Py_LeaveRecursiveCall(); - return result; -} -#endif -#endif - -/* PyObjectCallMethO */ - #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 - -/* PyObjectCallOneArg */ - #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) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, &arg, 1); - } -#endif - if (likely(PyCFunction_Check(func))) { - if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { - return __Pyx_PyObject_CallMethO(func, arg); -#if CYTHON_FAST_PYCCALL - } else if (PyCFunction_GET_FLAGS(func) & METH_FASTCALL) { - return __Pyx_PyCFunction_FastCall(func, &arg, 1); -#endif - } - } - return __Pyx__PyObject_CallOneArg(func, arg); -} -#else -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_Pack(1, arg); - if (unlikely(!args)) return NULL; - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -#endif - -/* DictGetItem */ - #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()) { - if (unlikely(PyTuple_Check(key))) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) { - PyErr_SetObject(PyExc_KeyError, args); - Py_DECREF(args); - } - } else { - PyErr_SetObject(PyExc_KeyError, key); - } - } - return NULL; - } - Py_INCREF(value); - return value; -} -#endif - -/* RaiseTooManyValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* RaiseNoneIterError */ - static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* ExtTypeTest */ - static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* GetTopmostException */ - #if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - /* TypeImport */ #ifndef __PYX_HAVE_RT_ImportType #define __PYX_HAVE_RT_ImportType @@ -6802,9 +5044,35 @@ bad: } #endif +/* PyDictVersioning */ + #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + /* CLineInTraceback */ #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { PyObject *use_cline; PyObject *ptype, *pvalue, *ptraceback; #if CYTHON_COMPILING_IN_CPYTHON @@ -6908,7 +5176,7 @@ static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } @@ -7012,7 +5280,6 @@ bad: #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } @@ -7024,7 +5291,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return; } if ((0)) {} - else if (__Pyx_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); view->obj = NULL; Py_DECREF(obj); } @@ -7137,13 +5403,13 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { float r = b.imag / b.real; - float s = 1.0 / (b.real + b.imag * r); + float s = (float)(1.0) / (b.real + b.imag * r); return __pyx_t_float_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { float r = b.real / b.imag; - float s = 1.0 / (b.imag + b.real * r); + float s = (float)(1.0) / (b.imag + b.real * r); return __pyx_t_float_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -7201,7 +5467,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { case 1: return a; case 2: - z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(a, a); case 3: z = __Pyx_c_prod_float(a, a); @@ -7223,7 +5488,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { theta = 0; } else { r = -a.real; - theta = atan2f(0, -1); + theta = atan2f(0.0, -1.0); } } else { r = __Pyx_c_abs_float(a); @@ -7292,13 +5557,13 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { double r = b.imag / b.real; - double s = 1.0 / (b.real + b.imag * r); + double s = (double)(1.0) / (b.real + b.imag * r); return __pyx_t_double_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { double r = b.real / b.imag; - double s = 1.0 / (b.imag + b.real * r); + double s = (double)(1.0) / (b.imag + b.real * r); return __pyx_t_double_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } @@ -7356,7 +5621,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { case 1: return a; case 2: - z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(a, a); case 3: z = __Pyx_c_prod_double(a, a); @@ -7378,7 +5642,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { theta = 0; } else { r = -a.real; - theta = atan2(0, -1); + theta = atan2(0.0, -1.0); } } else { r = __Pyx_c_abs_double(a); @@ -7394,37 +5658,6 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif #endif -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { - const enum NPY_TYPES neg_one = (enum NPY_TYPES) ((enum NPY_TYPES) 0 - (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); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(enum NPY_TYPES) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - 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); - } -} - /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) ((int) 0 - (int) 1), const_zero = (int) 0; From 55c2d66c99466f43202ccdfd7f9255be9c92d2d4 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Tue, 11 May 2021 09:37:07 -0700 Subject: [PATCH 083/137] updated osx to macOS 10.15.7, JDK to 14.0.2, and XCode to Xcode 12.2 (#904) The CI was broken. This commit fixes the CI. The root cause is reported in more detail in issue #905. In short, the default macOS version (10.13, see the TravisCI docs) used in TravisCI isn't supported by brew which caused the brew install pandoc in the download_miniconda.sh pre-install script to hang and time out the build. It failed even on inert PRs (adding a line to README, e.g.). Now, with the updated macOS version (from 10.13 to 10.15), brew is supported and the brew install pandoc command succeeds and allows the remainder of the CI build and test sequence to succeed. --- .travis.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.travis.yml b/.travis.yml index 84936875..f2fc73f0 100644 --- a/.travis.yml +++ b/.travis.yml @@ -1,5 +1,7 @@ sudo: false +osx_image: xcode12.2 + os: - osx - linux From e272c666c1e13a8c799ce3949d2174a9038b85a7 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Tue, 11 May 2021 14:32:05 -0700 Subject: [PATCH 084/137] incremented version --- GPy/__version__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/__version__.py b/GPy/__version__.py index 5986f100..fcfdf383 100644 --- a/GPy/__version__.py +++ b/GPy/__version__.py @@ -1 +1 @@ -__version__ = "1.9.9" +__version__ = "1.10.0" From 46ce7c1680ecadd6e5f25262edefecd7abaa4e86 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Thu, 13 May 2021 18:50:32 +0100 Subject: [PATCH 085/137] Fix description of exponentiated quadratic covariance function and add kernels. (#872) * Fix description of ExpQuad covariance. * Add sinc kernel. * Add ExpQuadCosine covariance --- GPy/kern/__init__.py | 2 +- GPy/kern/src/stationary.py | 69 +++++++++++++++++++++++++-- GPy/testing/kernel_tests.py | 16 +++++++ GPy/testing/state_space_main_tests.py | 6 +-- 4 files changed, 86 insertions(+), 7 deletions(-) diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index 178e4019..80467290 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -38,7 +38,7 @@ from .src.rbf import RBF from .src.linear import Linear, LinearFull from .src.static import Bias, White, Fixed, WhiteHeteroscedastic, Precomputed from .src.brownian import Brownian -from .src.stationary import Exponential, OU, Matern32, Matern52, ExpQuad, RatQuad, Cosine +from .src.stationary import Exponential, OU, Matern32, Matern52, ExpQuad, RatQuad, Cosine, Sinc, ExpQuadCosine from .src.mlp import MLP from .src.periodic import PeriodicExponential, PeriodicMatern32, PeriodicMatern52 from .src.standard_periodic import StdPeriodic diff --git a/GPy/kern/src/stationary.py b/GPy/kern/src/stationary.py index 527bb9bb..53bb98c2 100644 --- a/GPy/kern/src/stationary.py +++ b/GPy/kern/src/stationary.py @@ -621,10 +621,10 @@ class ExpQuad(Stationary): .. math:: - k(r) = \sigma^2 (1 + \sqrt{5} r + \\frac53 r^2) \exp(- \sqrt{5} r) + k(r) = \sigma^2 \exp(- 0.5 r^2) notes:: - - Yes, this is exactly the same as the RBF covariance function, but the + - This is exactly the same as the RBF covariance function, but the RBF implementation also has some features for doing variational kernels (the psi-statistics). @@ -657,6 +657,14 @@ class ExpQuad(Stationary): return -r*self.K_of_r(r) class Cosine(Stationary): + """ + Cosine Covariance function + + .. math:: + + k(r) = \sigma^2 \cos(r) + + """ def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='Cosine'): super(Cosine, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) @@ -666,6 +674,62 @@ class Cosine(Stationary): def dK_dr(self, r): return -self.variance * np.sin(r) +class ExpQuadCosine(Stationary): + """ + Exponentiated quadratic multiplied by cosine covariance function (spectral mixture kernel). + + .. math:: + + k(r) = \sigma^2 \exp(-2\pi^2r^2)\cos(2\pi r/T) + + """ + + def __init__(self, input_dim, variance=1., lengthscale=None, period=1., ARD=False, active_dims=None, name='ExpQuadCosine'): + super(ExpQuadCosine, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) + self.period = Param('period', period, Logexp()) + self.link_parameters(self.period) + + def K_of_r(self, r): + return self.variance * np.exp(-2*np.pi**2*r**2)*np.cos(2*np.pi*r/self.period) + + def dK_dr(self, r): + return -4*np.pi**2*r*self.K_of_r(r) - self.variance * 2*np.pi/self.period*np.exp(-2*np.pi**2*r**2)*np.sin(2*np.pi*r/self.period) + + def update_gradients_full(self, dL_dK, X, X2=None): + super(ExpQuadCosine, self).update_gradients_full(dL_dK, X, X2) + r = self._scaled_dist(X, X2) + r2 = np.square(r) + dK_dperiod = self.variance * 2*np.pi*r/self.period**2*np.exp(-2*np.pi**2*r**2)*np.sin(2*np.pi*r/self.period) + grad = np.sum(dL_dK*dK_dperiod) + self.period.gradient = grad + + def update_gradients_diag(self, dL_dKdiag, X): + super(ExpQuadCosine, self).update_gradients_diag(dL_dKdiag, X) + self.period.gradient = 0. + + + +class Sinc(Stationary): + """ + Sinc Covariance function + + .. math:: + + k(r) = \sigma^2 \sinc(\pi r) + + """ + + def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='Sinc'): + super(Sinc, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) + + def K_of_r(self, r): + return self.variance * np.sinc(2*r) + + def dK_dr(self, r): + # small angle approximation to avoid divide by zero errors. + return np.where(r<1e-5, -self.variance*4/3*np.pi*np.pi*r, self.variance/r * (np.cos(2*np.pi*r)-np.sinc(2*r))) + + class RatQuad(Stationary): """ @@ -677,7 +741,6 @@ class RatQuad(Stationary): """ - def __init__(self, input_dim, variance=1., lengthscale=None, power=2., ARD=False, active_dims=None, name='RatQuad'): super(RatQuad, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) self.power = Param('power', power, Logexp()) diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index d7140a0b..6490f809 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -426,6 +426,22 @@ class KernelGradientTestsContinuous(unittest.TestCase): k.randomize() self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + def test_Cosine(self): + # Don't test Cosine directly as it fails positive definite test. + k = GPy.kern.RBF(self.D-1, ARD=False)*GPy.kern.Cosine(self.D-1, ARD=True) + k.randomize() + self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + + def test_ExpQuadCosine(self): + k = GPy.kern.ExpQuadCosine(self.D-1, ARD=True) + k.randomize() + self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + + def test_Sinc(self): + k = GPy.kern.Sinc(self.D-1, ARD=True) + k.randomize() + self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) + def test_RatQuad(self): k = GPy.kern.RatQuad(self.D-1, ARD=True) k.randomize() diff --git a/GPy/testing/state_space_main_tests.py b/GPy/testing/state_space_main_tests.py index 5a1e6cd0..5a3e353f 100644 --- a/GPy/testing/state_space_main_tests.py +++ b/GPy/testing/state_space_main_tests.py @@ -722,9 +722,9 @@ class StateSpaceKernelsTests(np.testing.TestCase): # plotting <- # 2D measurement, 3 ts_no <- - def test_continuos_ss(self,plot=False): + def test_continuous_ss(self,plot=False): """ - This function tests the continuos state-space model. + This function tests the continuous state-space model. """ # 1D measurements, 1 ts_no -> @@ -974,4 +974,4 @@ if __name__ == '__main__': #res = tt.test_discrete_ss_2D(plot=False) #res = tt.test_continuos_ss(plot=True) - \ No newline at end of file + From ff82f12c3d321bfc3ce6615447fad25aea9de6bd Mon Sep 17 00:00:00 2001 From: monabf <26089777+monabf@users.noreply.github.com> Date: Sat, 15 May 2021 00:21:47 +0200 Subject: [PATCH 086/137] Corrected Multivariate Gaussian prior (#775) * Corrected MultivariateGaussian prior Some corrections including adapting to current version of pdinv, correcting the expressions of constant, pdf and its gradient, and adding the printing function. After some tests, seems to run as expected, similarly to the Gaussian prior which was already working. * Added test of MultivariateGaussian prior Simple unit test for creating a kernel with Multivariate Gaussian prior over the lengthscales, then performing GP regression. * Took care of case where x of shape (n, 1) for multivariate Gaussian prior * Got rid of unnecessary asserts in Multivariate Gaussian prior since loss of time Co-authored-by: and --- GPy/core/parameterization/priors.py | 42 +++++++++++++++++++---------- GPy/testing/model_tests.py | 28 +++++++++++++++++++ 2 files changed, 56 insertions(+), 14 deletions(-) diff --git a/GPy/core/parameterization/priors.py b/GPy/core/parameterization/priors.py index 906ad65f..6269436b 100644 --- a/GPy/core/parameterization/priors.py +++ b/GPy/core/parameterization/priors.py @@ -200,37 +200,50 @@ class MultivariateGaussian(Prior): def __new__(cls, mu=0, var=1): # Singleton: if cls._instances: - cls._instances[:] = [instance for instance in cls._instances if instance()] + cls._instances[:] = [instance for instance in cls._instances if + instance()] for instance in cls._instances: - if np.all(instance().mu == mu) and np.all(instance().var == var): + if np.all(instance().mu == mu) and np.all( + instance().var == var): return instance() - o = super(Prior, cls).__new__(cls, mu, var) + newfunc = super(Prior, cls).__new__ + if newfunc is object.__new__: + o = newfunc(cls) + else: + o = newfunc(cls, mu, var) cls._instances.append(weakref.ref(o)) return cls._instances[-1]() def __init__(self, mu, var): self.mu = np.array(mu).flatten() self.var = np.array(var) - assert len(self.var.shape) == 2 - assert self.var.shape[0] == self.var.shape[1] + assert len(self.var.shape) == 2, 'Covariance must be a matrix' + assert self.var.shape[0] == self.var.shape[1], \ + 'Covariance must be a square matrix' assert self.var.shape[0] == self.mu.size self.input_dim = self.mu.size - self.inv, self.hld = pdinv(self.var) - self.constant = -0.5 * self.input_dim * np.log(2 * np.pi) - self.hld + self.inv, _, self.hld, _ = pdinv(self.var) + self.constant = -0.5 * (self.input_dim * np.log(2 * np.pi) + self.hld) + + def __str__(self): + return 'MultiN(' + str(self.mu) + ', ' + str(np.diag(self.var)) + ')' def summary(self): raise NotImplementedError def pdf(self, x): + x = np.array(x).flatten() return np.exp(self.lnpdf(x)) def lnpdf(self, x): + x = np.array(x).flatten() d = x - self.mu - return self.constant - 0.5 * np.sum(d * np.dot(d, self.inv), 1) + return self.constant - 0.5 * np.dot(d.T, np.dot(self.inv, d)) def lnpdf_grad(self, x): + x = np.array(x).flatten() d = x - self.mu - return -np.dot(self.inv, d) + return - np.dot(self.inv, d) def rvs(self, n): return np.random.multivariate_normal(self.mu, self.var, n) @@ -247,14 +260,15 @@ class MultivariateGaussian(Prior): return self.mu, self.var def __setstate__(self, state): - self.mu = state[0] + self.mu = np.array(state[0]).flatten() self.var = state[1] - assert len(self.var.shape) == 2 - assert self.var.shape[0] == self.var.shape[1] + assert len(self.var.shape) == 2, 'Covariance must be a matrix' + assert self.var.shape[0] == self.var.shape[1], \ + 'Covariance must be a square matrix' assert self.var.shape[0] == self.mu.size self.input_dim = self.mu.size - self.inv, self.hld = pdinv(self.var) - self.constant = -0.5 * self.input_dim * np.log(2 * np.pi) - self.hld + self.inv, _, self.hld, _ = pdinv(self.var) + self.constant = -0.5 * (self.input_dim * np.log(2 * np.pi) + self.hld) def gamma_from_EV(E, V): warnings.warn("use Gamma.from_EV to create Gamma Prior", FutureWarning) diff --git a/GPy/testing/model_tests.py b/GPy/testing/model_tests.py index 9ee16f99..a241fc9c 100644 --- a/GPy/testing/model_tests.py +++ b/GPy/testing/model_tests.py @@ -936,6 +936,34 @@ class GradientTests(np.testing.TestCase): #import ipdb;ipdb.set_trace() #m.constrain_fixed('.*rbf_var', 1.) self.assertTrue(m.checkgrad()) + + def test_simple_MultivariateGaussian_prior(self): + X = np.random.multivariate_normal( + [1, 5], np.diag([0.5, 0.3]), (100, 1)).reshape(100, 2) + Y = X + np.random.randn(100, 2) * 0.05 + kernel = GPy.kern.RBF(input_dim=2, variance=1,lengthscale=1, ARD=True) + kernel.unconstrain() + kernel.variance.set_prior(GPy.priors.Gaussian(150, 5)) + kernel.lengthscale.set_prior(GPy.priors.MultivariateGaussian( + np.array([20, 20]), np.diag([5, 5]))) + m = GPy.models.GPRegression(X, Y, kernel=kernel) + m.optimize() + print(m.kern.variance) + print(m.kern.lengthscale) + + def test_simple_MultivariateGaussian_prior_matrixmean(self): + X = np.random.multivariate_normal( + [1, 5], np.diag([0.5, 0.3]), (100, 1)).reshape(100, 2) + Y = X + np.random.randn(100, 2) * 0.05 + kernel = GPy.kern.RBF(input_dim=2, variance=1,lengthscale=1, ARD=True) + kernel.unconstrain() + kernel.variance.set_prior(GPy.priors.Gaussian(150, 5)) + kernel.lengthscale.set_prior(GPy.priors.MultivariateGaussian( + np.array([[20, 20]]), np.diag([5, 5]))) + m = GPy.models.GPRegression(X, Y, kernel=kernel) + m.optimize() + print(m.kern.variance) + print(m.kern.lengthscale) def test_multioutput_sparse_regression_1D(self): X1 = np.random.rand(500, 1) * 8 From fee16c7b1886a9911cdf947f4d3c7eca5bc00d72 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 17:38:21 +0100 Subject: [PATCH 087/137] Update visualize.py Due to this issue: https://github.com/matplotlib/matplotlib/issues/17172 setting aspect equal doesn't work on 3D axes. Removing for the moment. --- GPy/plotting/matplot_dep/visualize.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index d4442dc7..0c20933b 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -411,7 +411,7 @@ class mocap_data_show(matplotlib_show): def __init__(self, vals, axes=None, connect=None, color='b'): if axes==None: fig = plt.figure() - axes = fig.add_subplot(111, projection='3d', aspect='equal') + axes = fig.add_subplot(111, projection='3d') #, aspect='equal') aspect equal not implemented in 3D plots currently see this issue: https://github.com/matplotlib/matplotlib/issues/17172 super(mocap_data_show, self).__init__(vals, axes) self.color = color From 89a7988bddb0ab9e1ffaa1089aa5f18b8bba1bca Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 17:43:52 +0100 Subject: [PATCH 088/137] Remove == None and replace with is --- GPy/plotting/matplot_dep/visualize.py | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 0c20933b..26f62777 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -39,7 +39,7 @@ class vpython_show(data_show): super(vpython_show, self).__init__(vals) # If no axes are defined, create some. - if scene==None: + if scene is None: self.scene = visual.display(title='Data Visualization') else: self.scene = scene @@ -57,7 +57,7 @@ class matplotlib_show(data_show): super(matplotlib_show, self).__init__(vals) # If no axes are defined, create some. - if axes==None: + if axes is None: fig = plt.figure() self.axes = fig.add_subplot(111) else: @@ -190,7 +190,7 @@ class lvm_subplots(lvm): def __init__(self, vals, Model, data_visualize, latent_axes=None, sense_axes=None): self.nplots = int(np.ceil(Model.input_dim/2.))+1 assert len(latent_axes)==self.nplots - if vals==None: + if vals is None: vals = Model.X[0, :] self.latent_values = vals @@ -215,9 +215,9 @@ class lvm_dimselect(lvm): """ def __init__(self, vals, model, data_visualize, latent_axes=None, sense_axes=None, latent_index=[0, 1], labels=None): - if latent_axes==None and sense_axes==None: + if latent_axes is None and sense_axes is None: self.fig,(latent_axes,self.sense_axes) = plt.subplots(1,2) - elif sense_axes==None: + elif sense_axes is None: fig=plt.figure() self.sense_axes = fig.add_subplot(111) else: @@ -300,7 +300,7 @@ class image_show(matplotlib_show): self.set_image(self.vals) if not self.palette == []: # Can just show the image (self.set_image() took care of setting the palette) self.handle = self.axes.imshow(self.vals, interpolation='nearest') - elif cmap==None: # Use a jet map. + elif cmap is None: # Use a jet map. self.handle = self.axes.imshow(self.vals, cmap=plt.cm.jet, interpolation='nearest') # @UndefinedVariable else: # Use the selected map. self.handle = self.axes.imshow(self.vals, cmap=cmap, interpolation='nearest') # @UndefinedVariable @@ -368,7 +368,7 @@ class mocap_data_show_vpython(vpython_show): def draw_edges(self): self.rods = [] self.line_handle = [] - if not self.connect==None: + if self.connect is not None: self.I, self.J = np.nonzero(self.connect) for i, j in zip(self.I, self.J): pos, axis = self.pos_axis(i, j) @@ -380,7 +380,7 @@ class mocap_data_show_vpython(vpython_show): def modify_edges(self): self.line_handle = [] - if not self.connect==None: + if self.connect is not None: self.I, self.J = np.nonzero(self.connect) for rod, i, j in zip(self.rods, self.I, self.J): rod.pos, rod.axis = self.pos_axis(i, j) @@ -409,7 +409,7 @@ class mocap_data_show(matplotlib_show): """Base class for visualizing motion capture data.""" def __init__(self, vals, axes=None, connect=None, color='b'): - if axes==None: + if axes is None: fig = plt.figure() axes = fig.add_subplot(111, projection='3d') #, aspect='equal') aspect equal not implemented in 3D plots currently see this issue: https://github.com/matplotlib/matplotlib/issues/17172 super(mocap_data_show, self).__init__(vals, axes) @@ -428,7 +428,7 @@ class mocap_data_show(matplotlib_show): def draw_edges(self): self.line_handle = [] - if not self.connect==None: + if self.connect is not None: x = [] y = [] z = [] From 0291c282e714f58b316478299be5d11dc5e24fa4 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 17:51:00 +0100 Subject: [PATCH 089/137] Give latent axes proper key. --- GPy/plotting/matplot_dep/visualize.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 26f62777..9895131b 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -111,11 +111,11 @@ class lvm(matplotlib_show): self.cid = latent_axes.figure.canvas.mpl_connect('axes_leave_event', self.on_leave) self.cid = latent_axes.figure.canvas.mpl_connect('axes_enter_event', self.on_enter) else: - self.cid = latent_axes[0].figure.canvas.mpl_connect('button_press_event', self.on_click) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('button_press_event', self.on_click) if not disable_drag: - self.cid = latent_axes[0].figure.canvas.mpl_connect('motion_notify_event', self.on_move) - self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) - self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('motion_notify_event', self.on_move) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) self.data_visualize = data_visualize self.model = model From 6751515c1998a03c25fcb78fc9ef68b9e28c8496 Mon Sep 17 00:00:00 2001 From: Aditya Saini <49980787+adityasaini70@users.noreply.github.com> Date: Tue, 18 May 2021 22:44:58 +0530 Subject: [PATCH 090/137] Fix docstring for gp.py::GP.__init__() (#915) Removed indication in docstring that was incorrect: `kernel` is a required arg, but docstring stated it was optional. Now, docstring does not say it's optional. --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 66d62f62..0704c6a6 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -21,7 +21,7 @@ class GP(Model): :param X: input observations :param Y: output observations - :param kernel: a GPy kernel, defaults to rbf+white + :param kernel: a GPy kernel :param likelihood: a GPy likelihood :param inference_method: The :class:`~GPy.inference.latent_function_inference.LatentFunctionInference` inference method to use for this GP :rtype: model object From 4ab77fbc3692a1833ee2aa19f6a8b2594b51d8b7 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:15:17 +0100 Subject: [PATCH 091/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index fe84df72..ec5dbf01 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -78,7 +78,8 @@ def gplvm_oil_100(optimize=True, verbose=1, plot=True): m = GPy.models.GPLVM(Y, 6, kernel=kernel) m.data_labels = data['Y'].argmax(axis=1) if optimize: m.optimize('scg', messages=verbose) - if plot: m.plot_latent(labels=m.data_labels) + if plot: + m.plot_latent(labels=m.data_labels) return m def sparse_gplvm_oil(optimize=True, verbose=0, plot=True, N=100, Q=6, num_inducing=15, max_iters=50): @@ -689,7 +690,9 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose if optimize: m.optimize(messages=verbose, max_f_eval=10000) if plot: - ax = m.plot_latent() + fig, (latent_axes, sense_axes) = plt.subplots(1, 2) + m.plot_latent(ax=latent_axes) + ax = gca y = m.Y[0, :] data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax) From 44c22372a1805d69ce8f945006314dfe86178218 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:18:23 +0100 Subject: [PATCH 092/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 1 + 1 file changed, 1 insertion(+) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index ec5dbf01..f0639ca3 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -676,6 +676,7 @@ def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True): def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose=True, plot=True): + import matplotlib.pyplot as plt import GPy import pods From b8f515ca0515ad4bc1e0b142acc601d749b22bf4 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:22:22 +0100 Subject: [PATCH 093/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 1 - 1 file changed, 1 deletion(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index f0639ca3..c66f2f92 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -693,7 +693,6 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose if plot: fig, (latent_axes, sense_axes) = plt.subplots(1, 2) m.plot_latent(ax=latent_axes) - ax = gca y = m.Y[0, :] data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax) From 530531f4ff7e9344bab81f32d66797b724c0c8b9 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:24:18 +0100 Subject: [PATCH 094/137] Fix cmu_mocap demo. --- GPy/plotting/matplot_dep/visualize.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 9895131b..26f62777 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -111,11 +111,11 @@ class lvm(matplotlib_show): self.cid = latent_axes.figure.canvas.mpl_connect('axes_leave_event', self.on_leave) self.cid = latent_axes.figure.canvas.mpl_connect('axes_enter_event', self.on_enter) else: - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('button_press_event', self.on_click) + self.cid = latent_axes[0].figure.canvas.mpl_connect('button_press_event', self.on_click) if not disable_drag: - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('motion_notify_event', self.on_move) - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) + self.cid = latent_axes[0].figure.canvas.mpl_connect('motion_notify_event', self.on_move) + self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) + self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) self.data_visualize = data_visualize self.model = model From 8e6dbfdc614eb45567f5e92735f4716f30579b65 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:27:16 +0100 Subject: [PATCH 095/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index c66f2f92..634f9790 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -695,7 +695,7 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose m.plot_latent(ax=latent_axes) y = m.Y[0, :] data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax) + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes) input('Press enter to finish') lvm_visualizer.close() data_show.close() From 9ac6bb3545db951782bcfd10234052043dcbc60e Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:45:21 +0100 Subject: [PATCH 096/137] Update GPLVM class to use metadata and output normalizers. --- GPy/models/gplvm.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/GPy/models/gplvm.py b/GPy/models/gplvm.py index cdc0ab47..3d0b0d5c 100644 --- a/GPy/models/gplvm.py +++ b/GPy/models/gplvm.py @@ -14,7 +14,7 @@ class GPLVM(GP): """ - def __init__(self, Y, input_dim, init='PCA', X=None, kernel=None, name="gplvm"): + def __init__(self, Y, input_dim, init='PCA', X=None, kernel=None, name="gplvm", Y_metadata=None, normalizer=False): """ :param Y: observed data @@ -23,6 +23,11 @@ class GPLVM(GP): :type input_dim: int :param init: initialisation method for the latent space :type init: 'PCA'|'random' + :param normalizer: + normalize the outputs Y. + If normalizer is True, we will normalize using Standardize. + If normalizer is False (the default), no normalization will be done. + :type normalizer: bool """ if X is None: from ..util.initialization import initialize_latent @@ -34,7 +39,7 @@ class GPLVM(GP): likelihood = Gaussian() - super(GPLVM, self).__init__(X, Y, kernel, likelihood, name='GPLVM') + super(GPLVM, self).__init__(X, Y, kernel, likelihood, name='GPLVM', Y_metadata=Y_metadata, normalizer=normalizer) self.X = Param('latent_mean', X) self.link_parameter(self.X, index=0) From 2d82aa185ccc471007c7d86b2b5c0f63275fb7e0 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:50:51 +0100 Subject: [PATCH 097/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 2e6d991a..4fe9815c 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -90,6 +90,9 @@ class Standardize(_Norm): Y = np.ma.masked_invalid(Y, copy=False) self.mean = Y.mean(0).view(np.ndarray) self.std = Y.std(0).view(np.ndarray) + if np.any(self.std) == 0: + self.std[np.where(Y_std==0)]=1. + warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") def normalize(self, Y): super(Standardize, self).normalize(Y) From 7f1d62757cb6f5b67f53f115d57ad14df62eded6 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:55:13 +0100 Subject: [PATCH 098/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 4fe9815c..07716bc9 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -90,7 +90,7 @@ class Standardize(_Norm): Y = np.ma.masked_invalid(Y, copy=False) self.mean = Y.mean(0).view(np.ndarray) self.std = Y.std(0).view(np.ndarray) - if np.any(self.std) == 0: + if np.any(self.std == 0): self.std[np.where(Y_std==0)]=1. warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") From ede1174d8f73a95cc61d3a2a16354790bf32be54 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:58:16 +0100 Subject: [PATCH 099/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 07716bc9..83c79b32 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -91,8 +91,8 @@ class Standardize(_Norm): self.mean = Y.mean(0).view(np.ndarray) self.std = Y.std(0).view(np.ndarray) if np.any(self.std == 0): - self.std[np.where(Y_std==0)]=1. warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") + self.std[np.where(self.std==0)]=1. def normalize(self, Y): super(Standardize, self).normalize(Y) From c0cd01423f09f7011cfc30659e2158265b774c2c Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 10:00:41 +0100 Subject: [PATCH 100/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 83c79b32..243f81c7 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -4,7 +4,7 @@ Created on Aug 27, 2014 @author: Max Zwiessele ''' import numpy as np - +import warnings class _Norm(object): def __init__(self): From dc7bf22400b38ae0efacacca695b973c16bcfba7 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 10:06:40 +0100 Subject: [PATCH 101/137] Fix dimensionality reduction example to work with notebook. --- GPy/examples/dimensionality_reduction.py | 18 ++++++++++++------ 1 file changed, 12 insertions(+), 6 deletions(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index 634f9790..9218a0e8 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -685,17 +685,23 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose # Make figure move in place. data['Y'][:, 0:3] = 0.0 Y = data['Y'] - Y_mean = Y.mean(0) - Y_std = Y.std(0) - m = GPy.models.GPLVM((Y - Y_mean) / Y_std, 2) + m = GPy.models.GPLVM(Y, 2, normalizer=True) if optimize: m.optimize(messages=verbose, max_f_eval=10000) if plot: - fig, (latent_axes, sense_axes) = plt.subplots(1, 2) + fig, _ = plt.subplots(figsize=(8, 5)) + latent_axes = fig.add_subplot(131) + sense_axes = fig.add_subplot(132) + viz_axes = fig.add_subplot(133, projection='3d') + + m.plot_latent(ax=latent_axes) + latent_axes.set_aspect('equal') + y = m.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes) + data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel'], viz_axes) + + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes) input('Press enter to finish') lvm_visualizer.close() data_show.close() From d645fc34bc8f87b8f03315392f00c20678e2f5cb Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 18:31:52 +0100 Subject: [PATCH 102/137] Update GPy/util/normalizer.py --- GPy/util/normalizer.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 243f81c7..d04e7324 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -92,7 +92,8 @@ class Standardize(_Norm): self.std = Y.std(0).view(np.ndarray) if np.any(self.std == 0): warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") - self.std[np.where(self.std==0)]=1. + # Choice of setting to 1.0 is somewhat arbitrary. It avoids a divide by zero error, but setting to EPS would also do this. Don't have strong reasons for choosing 1.0, it was just first instinct + self.std[np.where(self.std==0)]=1. def normalize(self, Y): super(Standardize, self).normalize(Y) From cc00de7d41f97ab352c5cc06324759c0b3fa21b0 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 17:38:21 +0100 Subject: [PATCH 103/137] Update visualize.py Due to this issue: https://github.com/matplotlib/matplotlib/issues/17172 setting aspect equal doesn't work on 3D axes. Removing for the moment. --- GPy/plotting/matplot_dep/visualize.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index d4442dc7..0c20933b 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -411,7 +411,7 @@ class mocap_data_show(matplotlib_show): def __init__(self, vals, axes=None, connect=None, color='b'): if axes==None: fig = plt.figure() - axes = fig.add_subplot(111, projection='3d', aspect='equal') + axes = fig.add_subplot(111, projection='3d') #, aspect='equal') aspect equal not implemented in 3D plots currently see this issue: https://github.com/matplotlib/matplotlib/issues/17172 super(mocap_data_show, self).__init__(vals, axes) self.color = color From f822caaf2c2cc8ef00f613756929b979f9a8df12 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 17:43:52 +0100 Subject: [PATCH 104/137] Remove == None and replace with is --- GPy/plotting/matplot_dep/visualize.py | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 0c20933b..26f62777 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -39,7 +39,7 @@ class vpython_show(data_show): super(vpython_show, self).__init__(vals) # If no axes are defined, create some. - if scene==None: + if scene is None: self.scene = visual.display(title='Data Visualization') else: self.scene = scene @@ -57,7 +57,7 @@ class matplotlib_show(data_show): super(matplotlib_show, self).__init__(vals) # If no axes are defined, create some. - if axes==None: + if axes is None: fig = plt.figure() self.axes = fig.add_subplot(111) else: @@ -190,7 +190,7 @@ class lvm_subplots(lvm): def __init__(self, vals, Model, data_visualize, latent_axes=None, sense_axes=None): self.nplots = int(np.ceil(Model.input_dim/2.))+1 assert len(latent_axes)==self.nplots - if vals==None: + if vals is None: vals = Model.X[0, :] self.latent_values = vals @@ -215,9 +215,9 @@ class lvm_dimselect(lvm): """ def __init__(self, vals, model, data_visualize, latent_axes=None, sense_axes=None, latent_index=[0, 1], labels=None): - if latent_axes==None and sense_axes==None: + if latent_axes is None and sense_axes is None: self.fig,(latent_axes,self.sense_axes) = plt.subplots(1,2) - elif sense_axes==None: + elif sense_axes is None: fig=plt.figure() self.sense_axes = fig.add_subplot(111) else: @@ -300,7 +300,7 @@ class image_show(matplotlib_show): self.set_image(self.vals) if not self.palette == []: # Can just show the image (self.set_image() took care of setting the palette) self.handle = self.axes.imshow(self.vals, interpolation='nearest') - elif cmap==None: # Use a jet map. + elif cmap is None: # Use a jet map. self.handle = self.axes.imshow(self.vals, cmap=plt.cm.jet, interpolation='nearest') # @UndefinedVariable else: # Use the selected map. self.handle = self.axes.imshow(self.vals, cmap=cmap, interpolation='nearest') # @UndefinedVariable @@ -368,7 +368,7 @@ class mocap_data_show_vpython(vpython_show): def draw_edges(self): self.rods = [] self.line_handle = [] - if not self.connect==None: + if self.connect is not None: self.I, self.J = np.nonzero(self.connect) for i, j in zip(self.I, self.J): pos, axis = self.pos_axis(i, j) @@ -380,7 +380,7 @@ class mocap_data_show_vpython(vpython_show): def modify_edges(self): self.line_handle = [] - if not self.connect==None: + if self.connect is not None: self.I, self.J = np.nonzero(self.connect) for rod, i, j in zip(self.rods, self.I, self.J): rod.pos, rod.axis = self.pos_axis(i, j) @@ -409,7 +409,7 @@ class mocap_data_show(matplotlib_show): """Base class for visualizing motion capture data.""" def __init__(self, vals, axes=None, connect=None, color='b'): - if axes==None: + if axes is None: fig = plt.figure() axes = fig.add_subplot(111, projection='3d') #, aspect='equal') aspect equal not implemented in 3D plots currently see this issue: https://github.com/matplotlib/matplotlib/issues/17172 super(mocap_data_show, self).__init__(vals, axes) @@ -428,7 +428,7 @@ class mocap_data_show(matplotlib_show): def draw_edges(self): self.line_handle = [] - if not self.connect==None: + if self.connect is not None: x = [] y = [] z = [] From 4dfc22277f27e4b0236721655e7dd82ebd1d96c2 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 17:51:00 +0100 Subject: [PATCH 105/137] Give latent axes proper key. --- GPy/plotting/matplot_dep/visualize.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 26f62777..9895131b 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -111,11 +111,11 @@ class lvm(matplotlib_show): self.cid = latent_axes.figure.canvas.mpl_connect('axes_leave_event', self.on_leave) self.cid = latent_axes.figure.canvas.mpl_connect('axes_enter_event', self.on_enter) else: - self.cid = latent_axes[0].figure.canvas.mpl_connect('button_press_event', self.on_click) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('button_press_event', self.on_click) if not disable_drag: - self.cid = latent_axes[0].figure.canvas.mpl_connect('motion_notify_event', self.on_move) - self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) - self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('motion_notify_event', self.on_move) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) + self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) self.data_visualize = data_visualize self.model = model From 20750d7a5ee6bdf8276ecee63717831d03cb6264 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:15:17 +0100 Subject: [PATCH 106/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index fe84df72..ec5dbf01 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -78,7 +78,8 @@ def gplvm_oil_100(optimize=True, verbose=1, plot=True): m = GPy.models.GPLVM(Y, 6, kernel=kernel) m.data_labels = data['Y'].argmax(axis=1) if optimize: m.optimize('scg', messages=verbose) - if plot: m.plot_latent(labels=m.data_labels) + if plot: + m.plot_latent(labels=m.data_labels) return m def sparse_gplvm_oil(optimize=True, verbose=0, plot=True, N=100, Q=6, num_inducing=15, max_iters=50): @@ -689,7 +690,9 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose if optimize: m.optimize(messages=verbose, max_f_eval=10000) if plot: - ax = m.plot_latent() + fig, (latent_axes, sense_axes) = plt.subplots(1, 2) + m.plot_latent(ax=latent_axes) + ax = gca y = m.Y[0, :] data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax) From 9686a58b35181236495863f9026936a4a8b8084b Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:18:23 +0100 Subject: [PATCH 107/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 1 + 1 file changed, 1 insertion(+) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index ec5dbf01..f0639ca3 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -676,6 +676,7 @@ def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True): def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose=True, plot=True): + import matplotlib.pyplot as plt import GPy import pods From 67834da1950819c23a68b06dfaea1e493f2a781e Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:22:22 +0100 Subject: [PATCH 108/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 1 - 1 file changed, 1 deletion(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index f0639ca3..c66f2f92 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -693,7 +693,6 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose if plot: fig, (latent_axes, sense_axes) = plt.subplots(1, 2) m.plot_latent(ax=latent_axes) - ax = gca y = m.Y[0, :] data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax) From fbe0a09506b1eb7df6f9905dafa2c1e1c89aff90 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:24:18 +0100 Subject: [PATCH 109/137] Fix cmu_mocap demo. --- GPy/plotting/matplot_dep/visualize.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 9895131b..26f62777 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -111,11 +111,11 @@ class lvm(matplotlib_show): self.cid = latent_axes.figure.canvas.mpl_connect('axes_leave_event', self.on_leave) self.cid = latent_axes.figure.canvas.mpl_connect('axes_enter_event', self.on_enter) else: - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('button_press_event', self.on_click) + self.cid = latent_axes[0].figure.canvas.mpl_connect('button_press_event', self.on_click) if not disable_drag: - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('motion_notify_event', self.on_move) - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) - self.cid = latent_axes['scatter'].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) + self.cid = latent_axes[0].figure.canvas.mpl_connect('motion_notify_event', self.on_move) + self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_leave_event', self.on_leave) + self.cid = latent_axes[0].figure.canvas.mpl_connect('axes_enter_event', self.on_enter) self.data_visualize = data_visualize self.model = model From 8b098ec59bafb7e8db0c0f0925d6bb567e59f9f7 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Tue, 18 May 2021 20:27:16 +0100 Subject: [PATCH 110/137] Fix cmu_mocap demo. --- GPy/examples/dimensionality_reduction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index c66f2f92..634f9790 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -695,7 +695,7 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose m.plot_latent(ax=latent_axes) y = m.Y[0, :] data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax) + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes) input('Press enter to finish') lvm_visualizer.close() data_show.close() From 5c71aa45c7be64c134eb544428feca3425bf6414 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:45:21 +0100 Subject: [PATCH 111/137] Update GPLVM class to use metadata and output normalizers. --- GPy/models/gplvm.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/GPy/models/gplvm.py b/GPy/models/gplvm.py index cdc0ab47..3d0b0d5c 100644 --- a/GPy/models/gplvm.py +++ b/GPy/models/gplvm.py @@ -14,7 +14,7 @@ class GPLVM(GP): """ - def __init__(self, Y, input_dim, init='PCA', X=None, kernel=None, name="gplvm"): + def __init__(self, Y, input_dim, init='PCA', X=None, kernel=None, name="gplvm", Y_metadata=None, normalizer=False): """ :param Y: observed data @@ -23,6 +23,11 @@ class GPLVM(GP): :type input_dim: int :param init: initialisation method for the latent space :type init: 'PCA'|'random' + :param normalizer: + normalize the outputs Y. + If normalizer is True, we will normalize using Standardize. + If normalizer is False (the default), no normalization will be done. + :type normalizer: bool """ if X is None: from ..util.initialization import initialize_latent @@ -34,7 +39,7 @@ class GPLVM(GP): likelihood = Gaussian() - super(GPLVM, self).__init__(X, Y, kernel, likelihood, name='GPLVM') + super(GPLVM, self).__init__(X, Y, kernel, likelihood, name='GPLVM', Y_metadata=Y_metadata, normalizer=normalizer) self.X = Param('latent_mean', X) self.link_parameter(self.X, index=0) From 11f806df3f2cc35d84d4a0022ca011304699e136 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:50:51 +0100 Subject: [PATCH 112/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 2e6d991a..4fe9815c 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -90,6 +90,9 @@ class Standardize(_Norm): Y = np.ma.masked_invalid(Y, copy=False) self.mean = Y.mean(0).view(np.ndarray) self.std = Y.std(0).view(np.ndarray) + if np.any(self.std) == 0: + self.std[np.where(Y_std==0)]=1. + warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") def normalize(self, Y): super(Standardize, self).normalize(Y) From 943be980d4b4625d8d663dbd829049cef581202f Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:55:13 +0100 Subject: [PATCH 113/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 4fe9815c..07716bc9 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -90,7 +90,7 @@ class Standardize(_Norm): Y = np.ma.masked_invalid(Y, copy=False) self.mean = Y.mean(0).view(np.ndarray) self.std = Y.std(0).view(np.ndarray) - if np.any(self.std) == 0: + if np.any(self.std == 0): self.std[np.where(Y_std==0)]=1. warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") From 95426aed34a41b54c52cd60937d0875707d91454 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 09:58:16 +0100 Subject: [PATCH 114/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 07716bc9..83c79b32 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -91,8 +91,8 @@ class Standardize(_Norm): self.mean = Y.mean(0).view(np.ndarray) self.std = Y.std(0).view(np.ndarray) if np.any(self.std == 0): - self.std[np.where(Y_std==0)]=1. warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") + self.std[np.where(self.std==0)]=1. def normalize(self, Y): super(Standardize, self).normalize(Y) From 5f68d8a7c34a52b57be4d4cef44e646a81c2c931 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 10:00:41 +0100 Subject: [PATCH 115/137] Fix normalizer to catch when output scale is zero. --- GPy/util/normalizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 83c79b32..243f81c7 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -4,7 +4,7 @@ Created on Aug 27, 2014 @author: Max Zwiessele ''' import numpy as np - +import warnings class _Norm(object): def __init__(self): From ef90137c4c4251cccffc27811fc2f341a0116e40 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 10:06:40 +0100 Subject: [PATCH 116/137] Fix dimensionality reduction example to work with notebook. --- GPy/examples/dimensionality_reduction.py | 18 ++++++++++++------ 1 file changed, 12 insertions(+), 6 deletions(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index 634f9790..9218a0e8 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -685,17 +685,23 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose # Make figure move in place. data['Y'][:, 0:3] = 0.0 Y = data['Y'] - Y_mean = Y.mean(0) - Y_std = Y.std(0) - m = GPy.models.GPLVM((Y - Y_mean) / Y_std, 2) + m = GPy.models.GPLVM(Y, 2, normalizer=True) if optimize: m.optimize(messages=verbose, max_f_eval=10000) if plot: - fig, (latent_axes, sense_axes) = plt.subplots(1, 2) + fig, _ = plt.subplots(figsize=(8, 5)) + latent_axes = fig.add_subplot(131) + sense_axes = fig.add_subplot(132) + viz_axes = fig.add_subplot(133, projection='3d') + + m.plot_latent(ax=latent_axes) + latent_axes.set_aspect('equal') + y = m.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes) + data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel'], viz_axes) + + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes) input('Press enter to finish') lvm_visualizer.close() data_show.close() From 714ad858aa5df0851b72e40b5af2e53ccc347f47 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Wed, 19 May 2021 18:31:52 +0100 Subject: [PATCH 117/137] Update GPy/util/normalizer.py --- GPy/util/normalizer.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 243f81c7..d04e7324 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -92,7 +92,8 @@ class Standardize(_Norm): self.std = Y.std(0).view(np.ndarray) if np.any(self.std == 0): warnings.warn("Some values of Y have standard deviation of zero. Resetting to 1.0 to avoid divide by zero errors.") - self.std[np.where(self.std==0)]=1. + # Choice of setting to 1.0 is somewhat arbitrary. It avoids a divide by zero error, but setting to EPS would also do this. Don't have strong reasons for choosing 1.0, it was just first instinct + self.std[np.where(self.std==0)]=1. def normalize(self, Y): super(Standardize, self).normalize(Y) From c36cd195722efdce0d85711aa2056637fdc656e2 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Fri, 21 May 2021 07:29:01 +0100 Subject: [PATCH 118/137] Force integer division (missed Python2-Python 3 change) --- GPy/plotting/matplot_dep/visualize.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 26f62777..7c62f60e 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -499,7 +499,7 @@ class stick_show(mocap_data_show): super(stick_show, self).__init__(vals, axes=axes, connect=connect) def process_values(self): - self.vals = self.vals.reshape((3, self.vals.shape[1]/3)).T + self.vals = self.vals.reshape((3, self.vals.shape[1]//3)).T class skeleton_show(mocap_data_show): """data_show class for visualizing motion capture data encoded as a skeleton with angles.""" From 74fab170d1d986ff34762ce18fcea94e37fba60f Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Fri, 21 May 2021 08:01:39 +0100 Subject: [PATCH 119/137] Update visualize stick_show for Python 3 and with clear error message for failure. --- GPy/plotting/matplot_dep/visualize.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 7c62f60e..16f9fc5f 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -499,7 +499,13 @@ class stick_show(mocap_data_show): super(stick_show, self).__init__(vals, axes=axes, connect=connect) def process_values(self): - self.vals = self.vals.reshape((3, self.vals.shape[1]//3)).T + """Convert vector of values into a matrix for use as a 3-D point cloud.""" + try: + self.vals = self.vals.reshape((3, self.vals.shape[1]//3)).T + except ValueError as e: + print('Passed values to data_show need to have a dimension which is divisible by 3 for display as they should be a point cloud of 3-D points.') + raise(e) + class skeleton_show(mocap_data_show): """data_show class for visualizing motion capture data encoded as a skeleton with angles.""" From a12298d60e2f714b4ae6212f3dfe96833c9d3dd0 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Fri, 21 May 2021 08:03:50 +0100 Subject: [PATCH 120/137] Update error message a little. --- GPy/plotting/matplot_dep/visualize.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 16f9fc5f..2a1b636d 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -503,7 +503,9 @@ class stick_show(mocap_data_show): try: self.vals = self.vals.reshape((3, self.vals.shape[1]//3)).T except ValueError as e: - print('Passed values to data_show need to have a dimension which is divisible by 3 for display as they should be a point cloud of 3-D points.') + print('Passed values to stick_show need to have a + dimension which is divisible by 3 for display as they + should be a point cloud of 3-D points.') raise(e) From 0219847ce955b448ab455ae71527bf41aad9505b Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Fri, 21 May 2021 08:21:48 +0100 Subject: [PATCH 121/137] Update osu-run1 example. --- GPy/plotting/matplot_dep/visualize.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 2a1b636d..b942d763 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -503,9 +503,7 @@ class stick_show(mocap_data_show): try: self.vals = self.vals.reshape((3, self.vals.shape[1]//3)).T except ValueError as e: - print('Passed values to stick_show need to have a - dimension which is divisible by 3 for display as they - should be a point cloud of 3-D points.') + print("Passed values to stick_show need to have a dimension which is divisible by 3 for display as they should be a point cloud of 3-D points.") raise(e) From 599f57cad5b6b38d6bc555636d62751fe89b775d Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 24 May 2021 08:38:46 +0100 Subject: [PATCH 122/137] Run black on examples. --- GPy/examples/classification.py | 177 +++++--- GPy/examples/dimensionality_reduction.py | 499 +++++++++++++++-------- GPy/examples/non_gaussian.py | 281 +++++++------ GPy/examples/regression.py | 449 ++++++++++++-------- GPy/examples/state_space.py | 14 +- 5 files changed, 911 insertions(+), 509 deletions(-) diff --git a/GPy/examples/classification.py b/GPy/examples/classification.py index af1c8c7a..ce3bd6d8 100644 --- a/GPy/examples/classification.py +++ b/GPy/examples/classification.py @@ -7,39 +7,47 @@ import GPy default_seed = 10000 + def oil(num_inducing=50, max_iters=100, kernel=None, optimize=True, plot=True): """ Run a Gaussian process classification on the three phase oil data. The demonstration calls the basic GP classification model and uses EP to approximate the likelihood. """ - try:import pods - except ImportError:raise ImportWarning('Need pods for example datasets. See https://github.com/sods/ods, or pip install pods.') + try: + import pods + except ImportError: + raise ImportWarning( + "Need pods for example datasets. See https://github.com/sods/ods, or pip install pods." + ) data = pods.datasets.oil() - X = data['X'] - Xtest = data['Xtest'] - Y = data['Y'][:, 0:1] - Ytest = data['Ytest'][:, 0:1] - Y[Y.flatten()==-1] = 0 - Ytest[Ytest.flatten()==-1] = 0 + X = data["X"] + Xtest = data["Xtest"] + Y = data["Y"][:, 0:1] + Ytest = data["Ytest"][:, 0:1] + Y[Y.flatten() == -1] = 0 + Ytest[Ytest.flatten() == -1] = 0 # Create GP model - m = GPy.models.SparseGPClassification(X, Y, kernel=kernel, num_inducing=num_inducing) + m = GPy.models.SparseGPClassification( + X, Y, kernel=kernel, num_inducing=num_inducing + ) m.Ytest = Ytest # Contrain all parameters to be positive - #m.tie_params('.*len') - m['.*len'] = 10. + # m.tie_params('.*len') + m[".*len"] = 10.0 # Optimize if optimize: m.optimize(messages=1) print(m) - #Test + # Test probs = m.predict(Xtest)[0] GPy.util.classification.conf_matrix(probs, Ytest) return m + def toy_linear_1d_classification(seed=default_seed, optimize=True, plot=True): """ Simple 1D classification example using EP approximation @@ -48,26 +56,31 @@ def toy_linear_1d_classification(seed=default_seed, optimize=True, plot=True): :type seed: int """ - try:import pods - except ImportError:raise ImportWarning('Need pods for example datasets. See https://github.com/sods/ods, or pip install pods.') + try: + import pods + except ImportError: + raise ImportWarning( + "Need pods for example datasets. See https://github.com/sods/ods, or pip install pods." + ) data = pods.datasets.toy_linear_1d_classification(seed=seed) - Y = data['Y'][:, 0:1] + Y = data["Y"][:, 0:1] Y[Y.flatten() == -1] = 0 # Model definition - m = GPy.models.GPClassification(data['X'], Y) + m = GPy.models.GPClassification(data["X"], Y) # Optimize if optimize: - #m.update_likelihood_approximation() + # m.update_likelihood_approximation() # Parameters optimization: m.optimize() - #m.update_likelihood_approximation() - #m.pseudo_EM() + # m.update_likelihood_approximation() + # m.pseudo_EM() # Plot if plot: from matplotlib import pyplot as plt + fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -75,6 +88,7 @@ def toy_linear_1d_classification(seed=default_seed, optimize=True, plot=True): print(m) return m + def toy_linear_1d_classification_laplace(seed=default_seed, optimize=True, plot=True): """ Simple 1D classification example using Laplace approximation @@ -84,10 +98,12 @@ def toy_linear_1d_classification_laplace(seed=default_seed, optimize=True, plot= """ - try:import pods - except ImportError:print('pods unavailable, see https://github.com/sods/ods for example datasets') + try: + import pods + except ImportError: + print("pods unavailable, see https://github.com/sods/ods for example datasets") data = pods.datasets.toy_linear_1d_classification(seed=seed) - Y = data['Y'][:, 0:1] + Y = data["Y"][:, 0:1] Y[Y.flatten() == -1] = 0 likelihood = GPy.likelihoods.Bernoulli() @@ -95,18 +111,21 @@ def toy_linear_1d_classification_laplace(seed=default_seed, optimize=True, plot= kernel = GPy.kern.RBF(1) # Model definition - m = GPy.core.GP(data['X'], Y, kernel=kernel, likelihood=likelihood, inference_method=laplace_inf) + m = GPy.core.GP( + data["X"], Y, kernel=kernel, likelihood=likelihood, inference_method=laplace_inf + ) # Optimize if optimize: try: - m.optimize('scg', messages=1) + m.optimize("scg", messages=1) except Exception as e: return m # Plot if plot: from matplotlib import pyplot as plt + fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -114,7 +133,10 @@ def toy_linear_1d_classification_laplace(seed=default_seed, optimize=True, plot= print(m) return m -def sparse_toy_linear_1d_classification(num_inducing=10, seed=default_seed, optimize=True, plot=True): + +def sparse_toy_linear_1d_classification( + num_inducing=10, seed=default_seed, optimize=True, plot=True +): """ Sparse 1D classification example @@ -123,15 +145,17 @@ def sparse_toy_linear_1d_classification(num_inducing=10, seed=default_seed, opti """ - try:import pods - except ImportError:print('pods unavailable, see https://github.com/sods/ods for example datasets') + try: + import pods + except ImportError: + print("pods unavailable, see https://github.com/sods/ods for example datasets") data = pods.datasets.toy_linear_1d_classification(seed=seed) - Y = data['Y'][:, 0:1] + Y = data["Y"][:, 0:1] Y[Y.flatten() == -1] = 0 # Model definition - m = GPy.models.SparseGPClassification(data['X'], Y, num_inducing=num_inducing) - m['.*len'] = 4. + m = GPy.models.SparseGPClassification(data["X"], Y, num_inducing=num_inducing) + m[".*len"] = 4.0 # Optimize if optimize: @@ -140,6 +164,7 @@ def sparse_toy_linear_1d_classification(num_inducing=10, seed=default_seed, opti # Plot if plot: from matplotlib import pyplot as plt + fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -147,7 +172,10 @@ def sparse_toy_linear_1d_classification(num_inducing=10, seed=default_seed, opti print(m) return m -def sparse_toy_linear_1d_classification_uncertain_input(num_inducing=10, seed=default_seed, optimize=True, plot=True): + +def sparse_toy_linear_1d_classification_uncertain_input( + num_inducing=10, seed=default_seed, optimize=True, plot=True +): """ Sparse 1D classification example @@ -156,18 +184,23 @@ def sparse_toy_linear_1d_classification_uncertain_input(num_inducing=10, seed=de """ - try:import pods - except ImportError:print('pods unavailable, see https://github.com/sods/ods for example datasets') + try: + import pods + except ImportError: + print("pods unavailable, see https://github.com/sods/ods for example datasets") import numpy as np + data = pods.datasets.toy_linear_1d_classification(seed=seed) - Y = data['Y'][:, 0:1] + Y = data["Y"][:, 0:1] Y[Y.flatten() == -1] = 0 - X = data['X'] - X_var = np.random.uniform(0.3,0.5,X.shape) + X = data["X"] + X_var = np.random.uniform(0.3, 0.5, X.shape) # Model definition - m = GPy.models.SparseGPClassificationUncertainInput(X, X_var, Y, num_inducing=num_inducing) - m['.*len'] = 4. + m = GPy.models.SparseGPClassificationUncertainInput( + X, X_var, Y, num_inducing=num_inducing + ) + m[".*len"] = 4.0 # Optimize if optimize: @@ -176,6 +209,7 @@ def sparse_toy_linear_1d_classification_uncertain_input(num_inducing=10, seed=de # Plot if plot: from matplotlib import pyplot as plt + fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -183,6 +217,7 @@ def sparse_toy_linear_1d_classification_uncertain_input(num_inducing=10, seed=de print(m) return m + def toy_heaviside(seed=default_seed, max_iters=100, optimize=True, plot=True): """ Simple 1D classification example using a heavy side gp transformation @@ -192,29 +227,41 @@ def toy_heaviside(seed=default_seed, max_iters=100, optimize=True, plot=True): """ - try:import pods - except ImportError:print('pods unavailable, see https://github.com/sods/ods for example datasets') + try: + import pods + except ImportError: + print("pods unavailable, see https://github.com/sods/ods for example datasets") data = pods.datasets.toy_linear_1d_classification(seed=seed) - Y = data['Y'][:, 0:1] + Y = data["Y"][:, 0:1] Y[Y.flatten() == -1] = 0 # Model definition kernel = GPy.kern.RBF(1) - likelihood = GPy.likelihoods.Bernoulli(gp_link=GPy.likelihoods.link_functions.Heaviside()) + likelihood = GPy.likelihoods.Bernoulli( + gp_link=GPy.likelihoods.link_functions.Heaviside() + ) ep = GPy.inference.latent_function_inference.expectation_propagation.EP() - m = GPy.core.GP(X=data['X'], Y=Y, kernel=kernel, likelihood=likelihood, inference_method=ep, name='gp_classification_heaviside') - #m = GPy.models.GPClassification(data['X'], likelihood=likelihood) + m = GPy.core.GP( + X=data["X"], + Y=Y, + kernel=kernel, + likelihood=likelihood, + inference_method=ep, + name="gp_classification_heaviside", + ) + # m = GPy.models.GPClassification(data['X'], likelihood=likelihood) # Optimize if optimize: # Parameters optimization: for _ in range(5): - m.optimize(max_iters=int(max_iters/5)) + m.optimize(max_iters=int(max_iters / 5)) print(m) # Plot if plot: from matplotlib import pyplot as plt + fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -222,7 +269,15 @@ def toy_heaviside(seed=default_seed, max_iters=100, optimize=True, plot=True): print(m) return m -def crescent_data(model_type='Full', num_inducing=10, seed=default_seed, kernel=None, optimize=True, plot=True): + +def crescent_data( + model_type="Full", + num_inducing=10, + seed=default_seed, + kernel=None, + optimize=True, + plot=True, +): """ Run a Gaussian process classification on the crescent data. The demonstration calls the basic GP classification model and uses EP to approximate the likelihood. @@ -234,22 +289,28 @@ def crescent_data(model_type='Full', num_inducing=10, seed=default_seed, kernel= :param kernel: kernel to use in the model :type kernel: a GPy kernel """ - try:import pods - except ImportError:print('pods unavailable, see https://github.com/sods/ods for example datasets') + try: + import pods + except ImportError: + print("pods unavailable, see https://github.com/sods/ods for example datasets") data = pods.datasets.crescent_data(seed=seed) - Y = data['Y'] - Y[Y.flatten()==-1] = 0 + Y = data["Y"] + Y[Y.flatten() == -1] = 0 - if model_type == 'Full': - m = GPy.models.GPClassification(data['X'], Y, kernel=kernel) + if model_type == "Full": + m = GPy.models.GPClassification(data["X"], Y, kernel=kernel) - elif model_type == 'DTC': - m = GPy.models.SparseGPClassification(data['X'], Y, kernel=kernel, num_inducing=num_inducing) - m['.*len'] = 10. + elif model_type == "DTC": + m = GPy.models.SparseGPClassification( + data["X"], Y, kernel=kernel, num_inducing=num_inducing + ) + m[".*len"] = 10.0 - elif model_type == 'FITC': - m = GPy.models.FITCClassification(data['X'], Y, kernel=kernel, num_inducing=num_inducing) - m['.*len'] = 3. + elif model_type == "FITC": + m = GPy.models.FITCClassification( + data["X"], Y, kernel=kernel, num_inducing=num_inducing + ) + m[".*len"] = 3.0 if optimize: m.optimize(messages=1) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index 9218a0e8..74df5235 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -1,10 +1,12 @@ # Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as _np + default_seed = 123344 # default_seed = _np.random.seed(123344) + def bgplvm_test_model(optimize=False, verbose=1, plot=False, output_dim=200, nan=False): """ model for testing purposes. Samples from a GP with rbf kernel and learns @@ -24,7 +26,7 @@ def bgplvm_test_model(optimize=False, verbose=1, plot=False, output_dim=200, nan # generate GPLVM-like data X = _np.random.rand(num_inputs, input_dim) lengthscales = _np.random.rand(input_dim) - k = GPy.kern.RBF(input_dim, .5, lengthscales, ARD=True) + k = GPy.kern.RBF(input_dim, 0.5, lengthscales, ARD=True) K = k.K(X) Y = _np.random.multivariate_normal(_np.zeros(num_inputs), K, (output_dim,)).T @@ -35,88 +37,102 @@ def bgplvm_test_model(optimize=False, verbose=1, plot=False, output_dim=200, nan # k = GPy.kern.RBF(input_dim, .5, 2., ARD=0) + GPy.kern.RBF(input_dim, .3, .2, ARD=0) # k = GPy.kern.RBF(input_dim, .5, _np.ones(input_dim) * 2., ARD=True) + GPy.kern.linear(input_dim, _np.ones(input_dim) * .2, ARD=True) - p = .3 + p = 0.3 m = GPy.models.BayesianGPLVM(Y, input_dim, kernel=k, num_inducing=num_inducing) if nan: - m.inference_method = GPy.inference.latent_function_inference.var_dtc.VarDTCMissingData() + m.inference_method = ( + GPy.inference.latent_function_inference.var_dtc.VarDTCMissingData() + ) m.Y[_np.random.binomial(1, p, size=(Y.shape)).astype(bool)] = _np.nan m.parameters_changed() - #=========================================================================== + # =========================================================================== # randomly obstruct data with percentage p - #=========================================================================== + # =========================================================================== # m2 = GPy.models.BayesianGPLVMWithMissingData(Y_obstruct, input_dim, kernel=k, num_inducing=num_inducing) # m.lengthscales = lengthscales if plot: import matplotlib.pyplot as pb + m.plot() - pb.title('PCA initialisation') + pb.title("PCA initialisation") # m2.plot() # pb.title('PCA initialisation') if optimize: - m.optimize('scg', messages=verbose) + m.optimize("scg", messages=verbose) # m2.optimize('scg', messages=verbose) if plot: m.plot() - pb.title('After optimisation') + pb.title("After optimisation") # m2.plot() # pb.title('After optimisation') return m + def gplvm_oil_100(optimize=True, verbose=1, plot=True): import GPy import pods + data = pods.datasets.oil_100() - Y = data['X'] + Y = data["X"] # create simple GP model kernel = GPy.kern.RBF(6, ARD=True) + GPy.kern.Bias(6) m = GPy.models.GPLVM(Y, 6, kernel=kernel) - m.data_labels = data['Y'].argmax(axis=1) - if optimize: m.optimize('scg', messages=verbose) + m.data_labels = data["Y"].argmax(axis=1) + if optimize: + m.optimize("scg", messages=verbose) if plot: m.plot_latent(labels=m.data_labels) return m -def sparse_gplvm_oil(optimize=True, verbose=0, plot=True, N=100, Q=6, num_inducing=15, max_iters=50): + +def sparse_gplvm_oil( + optimize=True, verbose=0, plot=True, N=100, Q=6, num_inducing=15, max_iters=50 +): import GPy import pods _np.random.seed(0) data = pods.datasets.oil() - Y = data['X'][:N] + Y = data["X"][:N] Y = Y - Y.mean(0) Y /= Y.std(0) # Create the model kernel = GPy.kern.RBF(Q, ARD=True) + GPy.kern.Bias(Q) m = GPy.models.SparseGPLVM(Y, Q, kernel=kernel, num_inducing=num_inducing) - m.data_labels = data['Y'][:N].argmax(axis=1) + m.data_labels = data["Y"][:N].argmax(axis=1) - if optimize: m.optimize('scg', messages=verbose, max_iters=max_iters) + if optimize: + m.optimize("scg", messages=verbose, max_iters=max_iters) if plot: m.plot_latent(labels=m.data_labels) m.kern.plot_ARD() return m -def swiss_roll(optimize=True, verbose=1, plot=True, N=1000, num_inducing=25, Q=4, sigma=.2): + +def swiss_roll( + optimize=True, verbose=1, plot=True, N=1000, num_inducing=25, Q=4, sigma=0.2 +): import GPy from pods.datasets import swiss_roll_generated from GPy.models import BayesianGPLVM data = swiss_roll_generated(num_samples=N, sigma=sigma) - Y = data['Y'] + Y = data["Y"] Y -= Y.mean() Y /= Y.std() - t = data['t'] - c = data['colors'] + t = data["t"] + c = data["colors"] try: from sklearn.manifold.isomap import Isomap + iso = Isomap().fit(Y) X = iso.embedding_ if Q > 2: @@ -127,8 +143,9 @@ def swiss_roll(optimize=True, verbose=1, plot=True, N=1000, num_inducing=25, Q=4 if plot: import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D # @UnusedImport + fig = plt.figure("Swiss Roll Data") - ax = fig.add_subplot(121, projection='3d') + ax = fig.add_subplot(121, projection="3d") ax.scatter(*Y.T, c=c) ax.set_title("Swiss Roll") @@ -136,60 +153,96 @@ def swiss_roll(optimize=True, verbose=1, plot=True, N=1000, num_inducing=25, Q=4 ax.scatter(*X.T[:2], c=c) ax.set_title("BGPLVM init") - var = .5 - S = (var * _np.ones_like(X) + _np.clip(_np.random.randn(N, Q) * var ** 2, - - (1 - var), - (1 - var))) + .001 + var = 0.5 + S = ( + var * _np.ones_like(X) + + _np.clip(_np.random.randn(N, Q) * var ** 2, -(1 - var), (1 - var)) + ) + 0.001 Z = _np.random.permutation(X)[:num_inducing] - kernel = GPy.kern.RBF(Q, ARD=True) + GPy.kern.Bias(Q, _np.exp(-2)) + GPy.kern.White(Q, _np.exp(-2)) + kernel = ( + GPy.kern.RBF(Q, ARD=True) + + GPy.kern.Bias(Q, _np.exp(-2)) + + GPy.kern.White(Q, _np.exp(-2)) + ) - m = BayesianGPLVM(Y, Q, X=X, X_variance=S, num_inducing=num_inducing, Z=Z, kernel=kernel) + m = BayesianGPLVM( + Y, Q, X=X, X_variance=S, num_inducing=num_inducing, Z=Z, kernel=kernel + ) m.data_colors = c m.data_t = t if optimize: - m.optimize('bfgs', messages=verbose, max_iters=2e3) + m.optimize("bfgs", messages=verbose, max_iters=2e3) if plot: - fig = plt.figure('fitted') + fig = plt.figure("fitted") ax = fig.add_subplot(111) s = m.input_sensitivity().argsort()[::-1][:2] ax.scatter(*m.X.mean.T[s], c=c) return m -def bgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40, max_iters=1000, **k): + +def bgplvm_oil( + optimize=True, + verbose=1, + plot=True, + N=200, + Q=7, + num_inducing=40, + max_iters=1000, + **k +): import GPy from matplotlib import pyplot as plt import numpy as np + _np.random.seed(0) try: import pods + data = pods.datasets.oil() except ImportError: data = GPy.util.datasets.oil() - - kernel = GPy.kern.RBF(Q, 1., 1. / _np.random.uniform(0, 1, (Q,)), ARD=True) # + GPy.kern.Bias(Q, _np.exp(-2)) - Y = data['X'][:N] + kernel = GPy.kern.RBF( + Q, 1.0, 1.0 / _np.random.uniform(0, 1, (Q,)), ARD=True + ) # + GPy.kern.Bias(Q, _np.exp(-2)) + Y = data["X"][:N] m = GPy.models.BayesianGPLVM(Y, Q, kernel=kernel, num_inducing=num_inducing, **k) - m.data_labels = data['Y'][:N].argmax(axis=1) + m.data_labels = data["Y"][:N].argmax(axis=1) if optimize: - m.optimize('bfgs', messages=verbose, max_iters=max_iters, gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: fig, (latent_axes, sense_axes) = plt.subplots(1, 2) m.plot_latent(ax=latent_axes, labels=m.data_labels) data_show = GPy.plotting.matplot_dep.visualize.vector_show((m.Y[0, :])) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm_dimselect(m.X.mean.values[0:1, :], # @UnusedVariable - m, data_show, latent_axes=latent_axes, sense_axes=sense_axes, labels=m.data_labels) - input('Press enter to finish') + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm_dimselect( + m.X.mean.values[0:1, :], # @UnusedVariable + m, + data_show, + latent_axes=latent_axes, + sense_axes=sense_axes, + labels=m.data_labels, + ) + input("Press enter to finish") plt.close(fig) return m -def ssgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40, max_iters=1000, **k): + +def ssgplvm_oil( + optimize=True, + verbose=1, + plot=True, + N=200, + Q=7, + num_inducing=40, + max_iters=1000, + **k +): import GPy from matplotlib import pyplot as plt import pods @@ -197,39 +250,57 @@ def ssgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40 _np.random.seed(0) data = pods.datasets.oil() - kernel = GPy.kern.RBF(Q, 1., 1. / _np.random.uniform(0, 1, (Q,)), ARD=True) # + GPy.kern.Bias(Q, _np.exp(-2)) - Y = data['X'][:N] + kernel = GPy.kern.RBF( + Q, 1.0, 1.0 / _np.random.uniform(0, 1, (Q,)), ARD=True + ) # + GPy.kern.Bias(Q, _np.exp(-2)) + Y = data["X"][:N] m = GPy.models.SSGPLVM(Y, Q, kernel=kernel, num_inducing=num_inducing, **k) - m.data_labels = data['Y'][:N].argmax(axis=1) + m.data_labels = data["Y"][:N].argmax(axis=1) if optimize: - m.optimize('bfgs', messages=verbose, max_iters=max_iters, gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: fig, (latent_axes, sense_axes) = plt.subplots(1, 2) m.plot_latent(ax=latent_axes, labels=m.data_labels) data_show = GPy.plotting.matplot_dep.visualize.vector_show((m.Y[0, :])) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm_dimselect(m.X.mean.values[0:1, :], # @UnusedVariable - m, data_show, latent_axes=latent_axes, sense_axes=sense_axes, labels=m.data_labels) - input('Press enter to finish') + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm_dimselect( + m.X.mean.values[0:1, :], # @UnusedVariable + m, + data_show, + latent_axes=latent_axes, + sense_axes=sense_axes, + labels=m.data_labels, + ) + input("Press enter to finish") plt.close(fig) return m + def _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim=False): """Simulate some data drawn from a matern covariance and a periodic exponential for use in MRD demos.""" Q_signal = 4 import GPy import numpy as np + np.random.seed(3000) - k = GPy.kern.Matern32(Q_signal, 1., lengthscale=(np.random.uniform(1, 6, Q_signal)), ARD=1) + k = GPy.kern.Matern32( + Q_signal, 1.0, lengthscale=(np.random.uniform(1, 6, Q_signal)), ARD=1 + ) for i in range(Q_signal): - k += GPy.kern.PeriodicExponential(1, variance=1., active_dims=[i], period=3., lower=-2, upper=6) + k += GPy.kern.PeriodicExponential( + 1, variance=1.0, active_dims=[i], period=3.0, lower=-2, upper=6 + ) t = np.c_[[np.linspace(-1, 5, N) for _ in range(Q_signal)]].T K = k.K(t) - s2, s1, s3, sS = np.random.multivariate_normal(np.zeros(K.shape[0]), K, size=(4))[:, :, None] + s2, s1, s3, sS = np.random.multivariate_normal(np.zeros(K.shape[0]), K, size=(4))[ + :, :, None + ] - Y1, Y2, Y3, S1, S2, S3 = _generate_high_dimensional_output(D1, D2, D3, s1, s2, s3, sS) + Y1, Y2, Y3, S1, S2, S3 = _generate_high_dimensional_output( + D1, D2, D3, s1, s2, s3, sS + ) slist = [sS, s1, s2, s3] slist_names = ["sS", "s1", "s2", "s3"] @@ -239,6 +310,7 @@ def _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim=False): from matplotlib import pyplot as plt import matplotlib.cm as cm import itertools + fig = plt.figure("MRD Simulation Data", figsize=(8, 6)) fig.clf() ax = fig.add_subplot(2, 1, 1) @@ -248,13 +320,14 @@ def _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim=False): ax.legend() for i, Y in enumerate(Ylist): ax = fig.add_subplot(2, len(Ylist), len(Ylist) + 1 + i) - ax.imshow(Y, aspect='auto', cmap=cm.gray) # @UndefinedVariable + ax.imshow(Y, aspect="auto", cmap=cm.gray) # @UndefinedVariable ax.set_title("Y{}".format(i + 1)) plt.draw() plt.tight_layout() return slist, [S1, S2, S3], Ylist + def _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim=False): """Simulate some data drawn from sine and cosine for use in demos of MRD""" _np.random.seed(1234) @@ -262,7 +335,7 @@ def _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim=False): x = _np.linspace(0, 4 * _np.pi, N)[:, None] s1 = _np.vectorize(lambda x: _np.sin(x)) s2 = _np.vectorize(lambda x: _np.cos(x)) - s3 = _np.vectorize(lambda x:-_np.exp(-_np.cos(2 * x))) + s3 = _np.vectorize(lambda x: -_np.exp(-_np.cos(2 * x))) sS = _np.vectorize(lambda x: _np.cos(x)) s1 = s1(x) @@ -270,12 +343,18 @@ def _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim=False): s3 = s3(x) sS = sS(x) - s1 -= s1.mean(); s1 /= s1.std(0) - s2 -= s2.mean(); s2 /= s2.std(0) - s3 -= s3.mean(); s3 /= s3.std(0) - sS -= sS.mean(); sS /= sS.std(0) + s1 -= s1.mean() + s1 /= s1.std(0) + s2 -= s2.mean() + s2 /= s2.std(0) + s3 -= s3.mean() + s3 /= s3.std(0) + sS -= sS.mean() + sS /= sS.std(0) - Y1, Y2, Y3, S1, S2, S3 = _generate_high_dimensional_output(D1, D2, D3, s1, s2, s3, sS) + Y1, Y2, Y3, S1, S2, S3 = _generate_high_dimensional_output( + D1, D2, D3, s1, s2, s3, sS + ) slist = [sS, s1, s2, s3] slist_names = ["sS", "s1", "s2", "s3"] @@ -285,6 +364,7 @@ def _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim=False): from matplotlib import pyplot as plt import matplotlib.cm as cm import itertools + fig = plt.figure("MRD Simulation Data", figsize=(8, 6)) fig.clf() ax = fig.add_subplot(2, 1, 1) @@ -294,13 +374,14 @@ def _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim=False): ax.legend() for i, Y in enumerate(Ylist): ax = fig.add_subplot(2, len(Ylist), len(Ylist) + 1 + i) - ax.imshow(Y, aspect='auto', cmap=cm.gray) # @UndefinedVariable + ax.imshow(Y, aspect="auto", cmap=cm.gray) # @UndefinedVariable ax.set_title("Y{}".format(i + 1)) plt.draw() plt.tight_layout() return slist, [S1, S2, S3], Ylist + def _generate_high_dimensional_output(D1, D2, D3, s1, s2, s3, sS): S1 = _np.hstack([s1, sS]) S2 = _np.hstack([sS]) @@ -308,9 +389,9 @@ def _generate_high_dimensional_output(D1, D2, D3, s1, s2, s3, sS): Y1 = S1.dot(_np.random.randn(S1.shape[1], D1)) Y2 = S2.dot(_np.random.randn(S2.shape[1], D2)) Y3 = S3.dot(_np.random.randn(S3.shape[1], D3)) - Y1 += .3 * _np.random.randn(*Y1.shape) - Y2 += .2 * _np.random.randn(*Y2.shape) - Y3 += .25 * _np.random.randn(*Y3.shape) + Y1 += 0.3 * _np.random.randn(*Y1.shape) + Y2 += 0.2 * _np.random.randn(*Y2.shape) + Y3 += 0.25 * _np.random.randn(*Y3.shape) Y1 -= Y1.mean(0) Y2 -= Y2.mean(0) Y3 -= Y3.mean(0) @@ -319,10 +400,10 @@ def _generate_high_dimensional_output(D1, D2, D3, s1, s2, s3, sS): Y3 /= Y3.std(0) return Y1, Y2, Y3, S1, S2, S3 -def bgplvm_simulation(optimize=True, verbose=1, - plot=True, plot_sim=False, - max_iters=2e4, - ): + +def bgplvm_simulation( + optimize=True, verbose=1, plot=True, plot_sim=False, max_iters=2e4, +): from GPy import kern from GPy.models import BayesianGPLVM @@ -332,22 +413,21 @@ def bgplvm_simulation(optimize=True, verbose=1, k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q) # k = kern.RBF(Q, ARD=True, lengthscale=10.) m = BayesianGPLVM(Y, Q, init="PCA", num_inducing=num_inducing, kernel=k) - m.X.variance[:] = _np.random.uniform(0, .01, m.X.shape) - m.likelihood.variance = .1 + m.X.variance[:] = _np.random.uniform(0, 0.01, m.X.shape) + m.likelihood.variance = 0.1 if optimize: print("Optimizing model:") - m.optimize('bfgs', messages=verbose, max_iters=max_iters, - gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: m.X.plot("BGPLVM Latent Space 1D") m.kern.plot_ARD() return m -def gplvm_simulation(optimize=True, verbose=1, - plot=True, plot_sim=False, - max_iters=2e4, - ): + +def gplvm_simulation( + optimize=True, verbose=1, plot=True, plot_sim=False, max_iters=2e4, +): from GPy import kern from GPy.models import GPLVM @@ -357,20 +437,20 @@ def gplvm_simulation(optimize=True, verbose=1, k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q) # k = kern.RBF(Q, ARD=True, lengthscale=10.) m = GPLVM(Y, Q, init="PCA", kernel=k) - m.likelihood.variance = .1 + m.likelihood.variance = 0.1 if optimize: print("Optimizing model:") - m.optimize('bfgs', messages=verbose, max_iters=max_iters, - gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: m.X.plot("BGPLVM Latent Space 1D") m.kern.plot_ARD() return m -def ssgplvm_simulation(optimize=True, verbose=1, - plot=True, plot_sim=False, - max_iters=2e4, useGPU=False - ): + + +def ssgplvm_simulation( + optimize=True, verbose=1, plot=True, plot_sim=False, max_iters=2e4, useGPU=False +): from GPy import kern from GPy.models import SSGPLVM @@ -379,23 +459,30 @@ def ssgplvm_simulation(optimize=True, verbose=1, Y = Ylist[0] k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q) # k = kern.RBF(Q, ARD=True, lengthscale=10.) - m = SSGPLVM(Y, Q, init="rand", num_inducing=num_inducing, kernel=k, group_spike=True) - m.X.variance[:] = _np.random.uniform(0, .01, m.X.shape) - m.likelihood.variance = .01 + m = SSGPLVM( + Y, Q, init="rand", num_inducing=num_inducing, kernel=k, group_spike=True + ) + m.X.variance[:] = _np.random.uniform(0, 0.01, m.X.shape) + m.likelihood.variance = 0.01 if optimize: print("Optimizing model:") - m.optimize('bfgs', messages=verbose, max_iters=max_iters, - gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: m.X.plot("SSGPLVM Latent Space 1D") m.kern.plot_ARD() return m -def bgplvm_simulation_missing_data(optimize=True, verbose=1, - plot=True, plot_sim=False, - max_iters=2e4, percent_missing=.1, d=13, - ): + +def bgplvm_simulation_missing_data( + optimize=True, + verbose=1, + plot=True, + plot_sim=False, + max_iters=2e4, + percent_missing=0.1, + d=13, +): from GPy import kern from GPy.models.bayesian_gplvm_minibatch import BayesianGPLVMMiniBatch @@ -404,28 +491,42 @@ def bgplvm_simulation_missing_data(optimize=True, verbose=1, Y = Ylist[0] k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q) - inan = _np.random.binomial(1, percent_missing, size=Y.shape).astype(bool) # 80% missing data + inan = _np.random.binomial(1, percent_missing, size=Y.shape).astype( + bool + ) # 80% missing data Ymissing = Y.copy() Ymissing[inan] = _np.nan - m = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing, - kernel=k, missing_data=True) + m = BayesianGPLVMMiniBatch( + Ymissing, + Q, + init="random", + num_inducing=num_inducing, + kernel=k, + missing_data=True, + ) m.Yreal = Y if optimize: print("Optimizing model:") - m.optimize('bfgs', messages=verbose, max_iters=max_iters, - gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: m.X.plot("BGPLVM Latent Space 1D") m.kern.plot_ARD() return m -def bgplvm_simulation_missing_data_stochastics(optimize=True, verbose=1, - plot=True, plot_sim=False, - max_iters=2e4, percent_missing=.1, d=13, batchsize=2, - ): + +def bgplvm_simulation_missing_data_stochastics( + optimize=True, + verbose=1, + plot=True, + plot_sim=False, + max_iters=2e4, + percent_missing=0.1, + d=13, + batchsize=2, +): from GPy import kern from GPy.models.bayesian_gplvm_minibatch import BayesianGPLVMMiniBatch @@ -434,19 +535,28 @@ def bgplvm_simulation_missing_data_stochastics(optimize=True, verbose=1, Y = Ylist[0] k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q) - inan = _np.random.binomial(1, percent_missing, size=Y.shape).astype(bool) # 80% missing data + inan = _np.random.binomial(1, percent_missing, size=Y.shape).astype( + bool + ) # 80% missing data Ymissing = Y.copy() Ymissing[inan] = _np.nan - m = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing, - kernel=k, missing_data=True, stochastic=True, batchsize=batchsize) + m = BayesianGPLVMMiniBatch( + Ymissing, + Q, + init="random", + num_inducing=num_inducing, + kernel=k, + missing_data=True, + stochastic=True, + batchsize=batchsize, + ) m.Yreal = Y if optimize: print("Optimizing model:") - m.optimize('bfgs', messages=verbose, max_iters=max_iters, - gtol=.05) + m.optimize("bfgs", messages=verbose, max_iters=max_iters, gtol=0.05) if plot: m.X.plot("BGPLVM Latent Space 1D") m.kern.plot_ARD() @@ -461,9 +571,17 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw): _, _, Ylist = _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim) k = kern.Linear(Q, ARD=True) + kern.White(Q, variance=1e-4) - m = MRD(Ylist, input_dim=Q, num_inducing=num_inducing, kernel=k, initx="PCA_concat", initz='permute', **kw) + m = MRD( + Ylist, + input_dim=Q, + num_inducing=num_inducing, + kernel=k, + initx="PCA_concat", + initz="permute", + **kw + ) - m['.*noise'] = [Y.var() / 40. for Y in Ylist] + m[".*noise"] = [Y.var() / 40.0 for Y in Ylist] if optimize: print("Optimizing Model:") @@ -473,7 +591,10 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw): m.plot_scales() return m -def mrd_simulation_missing_data(optimize=True, verbose=True, plot=True, plot_sim=True, **kw): + +def mrd_simulation_missing_data( + optimize=True, verbose=True, plot=True, plot_sim=True, **kw +): from GPy import kern from GPy.models import MRD @@ -484,29 +605,37 @@ def mrd_simulation_missing_data(optimize=True, verbose=True, plot=True, plot_sim inanlist = [] for Y in Ylist: - inan = _np.random.binomial(1, .6, size=Y.shape).astype(bool) + inan = _np.random.binomial(1, 0.6, size=Y.shape).astype(bool) inanlist.append(inan) Y[inan] = _np.nan - m = MRD(Ylist, input_dim=Q, num_inducing=num_inducing, - kernel=k, inference_method=None, - initx="random", initz='permute', **kw) + m = MRD( + Ylist, + input_dim=Q, + num_inducing=num_inducing, + kernel=k, + inference_method=None, + initx="random", + initz="permute", + **kw + ) if optimize: print("Optimizing Model:") - m.optimize('bfgs', messages=verbose, max_iters=8e3, gtol=.1) + m.optimize("bfgs", messages=verbose, max_iters=8e3, gtol=0.1) if plot: m.X.plot("MRD Latent Space 1D") m.plot_scales() return m + def brendan_faces(optimize=True, verbose=True, plot=True): import GPy import pods data = pods.datasets.brendan_faces() Q = 2 - Y = data['Y'] + Y = data["Y"] Yn = Y - Y.mean() Yn /= Yn.std() @@ -514,39 +643,56 @@ def brendan_faces(optimize=True, verbose=True, plot=True): # optimize - if optimize: m.optimize('bfgs', messages=verbose, max_iters=1000) + if optimize: + m.optimize("bfgs", messages=verbose, max_iters=1000) if plot: ax = m.plot_latent(which_indices=(0, 1)) y = m.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.image_show(y[None, :], dimensions=(20, 28), transpose=True, order='F', invert=False, scale=False) - lvm = GPy.plotting.matplot_dep.visualize.lvm(m.X.mean[0, :].copy(), m, data_show, ax) - input('Press enter to finish') + data_show = GPy.plotting.matplot_dep.visualize.image_show( + y[None, :], + dimensions=(20, 28), + transpose=True, + order="F", + invert=False, + scale=False, + ) + lvm = GPy.plotting.matplot_dep.visualize.lvm( + m.X.mean[0, :].copy(), m, data_show, ax + ) + input("Press enter to finish") return m + def olivetti_faces(optimize=True, verbose=True, plot=True): import GPy import pods data = pods.datasets.olivetti_faces() Q = 2 - Y = data['Y'] + Y = data["Y"] Yn = Y - Y.mean() Yn /= Yn.std() m = GPy.models.BayesianGPLVM(Yn, Q, num_inducing=20) - if optimize: m.optimize('bfgs', messages=verbose, max_iters=1000) + if optimize: + m.optimize("bfgs", messages=verbose, max_iters=1000) if plot: ax = m.plot_latent(which_indices=(0, 1)) y = m.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.image_show(y[None, :], dimensions=(112, 92), transpose=False, invert=False, scale=False) - lvm = GPy.plotting.matplot_dep.visualize.lvm(m.X.mean[0, :].copy(), m, data_show, ax) - input('Press enter to finish') + data_show = GPy.plotting.matplot_dep.visualize.image_show( + y[None, :], dimensions=(112, 92), transpose=False, invert=False, scale=False + ) + lvm = GPy.plotting.matplot_dep.visualize.lvm( + m.X.mean[0, :].copy(), m, data_show, ax + ) + input("Press enter to finish") return m + def stick_play(range=None, frame_rate=15, optimize=False, verbose=True, plot=True): import GPy import pods @@ -554,15 +700,18 @@ def stick_play(range=None, frame_rate=15, optimize=False, verbose=True, plot=Tru data = pods.datasets.osu_run1() # optimize if range == None: - Y = data['Y'].copy() + Y = data["Y"].copy() else: - Y = data['Y'][range[0]:range[1], :].copy() + Y = data["Y"][range[0] : range[1], :].copy() if plot: y = Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.stick_show(y[None, :], connect=data['connect']) + data_show = GPy.plotting.matplot_dep.visualize.stick_show( + y[None, :], connect=data["connect"] + ) GPy.plotting.matplot_dep.visualize.data_play(Y, data_show, frame_rate) return Y + def stick(kernel=None, optimize=True, verbose=True, plot=True): from matplotlib import pyplot as plt import GPy @@ -570,19 +719,25 @@ def stick(kernel=None, optimize=True, verbose=True, plot=True): data = pods.datasets.osu_run1() # optimize - m = GPy.models.GPLVM(data['Y'], 2, kernel=kernel) - if optimize: m.optimize('bfgs', messages=verbose, max_f_eval=10000) + m = GPy.models.GPLVM(data["Y"], 2, kernel=kernel) + if optimize: + m.optimize("bfgs", messages=verbose, max_f_eval=10000) if plot: plt.clf ax = m.plot_latent() y = m.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.stick_show(y[None, :], connect=data['connect']) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[:1, :].copy(), m, data_show, latent_axes=ax) - input('Press enter to finish') + data_show = GPy.plotting.matplot_dep.visualize.stick_show( + y[None, :], connect=data["connect"] + ) + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm( + m.X[:1, :].copy(), m, data_show, latent_axes=ax + ) + input("Press enter to finish") lvm_visualizer.close() data_show.close() return m + def bcgplvm_linear_stick(kernel=None, optimize=True, verbose=True, plot=True): from matplotlib import pyplot as plt import GPy @@ -590,19 +745,23 @@ def bcgplvm_linear_stick(kernel=None, optimize=True, verbose=True, plot=True): data = pods.datasets.osu_run1() # optimize - mapping = GPy.mappings.Linear(data['Y'].shape[1], 2) - m = GPy.models.BCGPLVM(data['Y'], 2, kernel=kernel, mapping=mapping) - if optimize: m.optimize(messages=verbose, max_f_eval=10000) + mapping = GPy.mappings.Linear(data["Y"].shape[1], 2) + m = GPy.models.BCGPLVM(data["Y"], 2, kernel=kernel, mapping=mapping) + if optimize: + m.optimize(messages=verbose, max_f_eval=10000) if plot and GPy.plotting.matplot_dep.visualize.visual_available: plt.clf ax = m.plot_latent() y = m.likelihood.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.stick_show(y[None, :], connect=data['connect']) + data_show = GPy.plotting.matplot_dep.visualize.stick_show( + y[None, :], connect=data["connect"] + ) GPy.plotting.matplot_dep.visualize.lvm(m.X[0, :].copy(), m, data_show, ax) - input('Press enter to finish') + input("Press enter to finish") return m + def bcgplvm_stick(kernel=None, optimize=True, verbose=True, plot=True): from matplotlib import pyplot as plt import GPy @@ -610,20 +769,24 @@ def bcgplvm_stick(kernel=None, optimize=True, verbose=True, plot=True): data = pods.datasets.osu_run1() # optimize - back_kernel = GPy.kern.RBF(data['Y'].shape[1], lengthscale=5.) - mapping = GPy.mappings.Kernel(X=data['Y'], output_dim=2, kernel=back_kernel) - m = GPy.models.BCGPLVM(data['Y'], 2, kernel=kernel, mapping=mapping) - if optimize: m.optimize(messages=verbose, max_f_eval=10000) + back_kernel = GPy.kern.RBF(data["Y"].shape[1], lengthscale=5.0) + mapping = GPy.mappings.Kernel(X=data["Y"], output_dim=2, kernel=back_kernel) + m = GPy.models.BCGPLVM(data["Y"], 2, kernel=kernel, mapping=mapping) + if optimize: + m.optimize(messages=verbose, max_f_eval=10000) if plot and GPy.plotting.matplot_dep.visualize.visual_available: plt.clf ax = m.plot_latent() y = m.likelihood.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.stick_show(y[None, :], connect=data['connect']) + data_show = GPy.plotting.matplot_dep.visualize.stick_show( + y[None, :], connect=data["connect"] + ) GPy.plotting.matplot_dep.visualize.lvm(m.X[0, :].copy(), m, data_show, ax) # input('Press enter to finish') return m + def robot_wireless(optimize=True, verbose=True, plot=True): from matplotlib import pyplot as plt import GPy @@ -631,13 +794,15 @@ def robot_wireless(optimize=True, verbose=True, plot=True): data = pods.datasets.robot_wireless() # optimize - m = GPy.models.BayesianGPLVM(data['Y'], 4, num_inducing=25) - if optimize: m.optimize(messages=verbose, max_f_eval=10000) + m = GPy.models.BayesianGPLVM(data["Y"], 4, num_inducing=25) + if optimize: + m.optimize(messages=verbose, max_f_eval=10000) if plot: m.plot_latent() return m + def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True): """Interactive visualisation of the Stick Man data from Ohio State University with the Bayesian GPLVM.""" from GPy.models import BayesianGPLVM @@ -648,15 +813,16 @@ def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True): data = pods.datasets.osu_run1() Q = 6 - kernel = GPy.kern.RBF(Q, lengthscale=np.repeat(.5, Q), ARD=True) - m = BayesianGPLVM(data['Y'], Q, init="PCA", num_inducing=20, kernel=kernel) + kernel = GPy.kern.RBF(Q, lengthscale=np.repeat(0.5, Q), ARD=True) + m = BayesianGPLVM(data["Y"], Q, init="PCA", num_inducing=20, kernel=kernel) m.data = data m.likelihood.variance = 0.001 # optimize try: - if optimize: m.optimize('bfgs', messages=verbose, max_iters=5e3, bfgs_factor=10) + if optimize: + m.optimize("bfgs", messages=verbose, max_iters=5e3, bfgs_factor=10) except KeyboardInterrupt: print("Keyboard interrupt, continuing to plot and return") @@ -665,17 +831,27 @@ def stick_bgplvm(model=None, optimize=True, verbose=True, plot=True): plt.sca(latent_axes) m.plot_latent(ax=latent_axes) y = m.Y[:1, :].copy() - data_show = GPy.plotting.matplot_dep.visualize.stick_show(y, connect=data['connect']) - dim_select = GPy.plotting.matplot_dep.visualize.lvm_dimselect(m.X.mean[:1, :].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes) + data_show = GPy.plotting.matplot_dep.visualize.stick_show( + y, connect=data["connect"] + ) + dim_select = GPy.plotting.matplot_dep.visualize.lvm_dimselect( + m.X.mean[:1, :].copy(), + m, + data_show, + latent_axes=latent_axes, + sense_axes=sense_axes, + ) fig.canvas.draw() # Canvas.show doesn't work on OSX. - #fig.canvas.show() - input('Press enter to finish') + # fig.canvas.show() + input("Press enter to finish") return m -def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose=True, plot=True): +def cmu_mocap( + subject="35", motion=["01"], in_place=True, optimize=True, verbose=True, plot=True +): import matplotlib.pyplot as plt import GPy import pods @@ -683,34 +859,40 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose data = pods.datasets.cmu_mocap(subject, motion) if in_place: # Make figure move in place. - data['Y'][:, 0:3] = 0.0 - Y = data['Y'] + data["Y"][:, 0:3] = 0.0 + Y = data["Y"] m = GPy.models.GPLVM(Y, 2, normalizer=True) - if optimize: m.optimize(messages=verbose, max_f_eval=10000) + if optimize: + m.optimize(messages=verbose, max_f_eval=10000) if plot: fig, _ = plt.subplots(figsize=(8, 5)) latent_axes = fig.add_subplot(131) sense_axes = fig.add_subplot(132) - viz_axes = fig.add_subplot(133, projection='3d') - + viz_axes = fig.add_subplot(133, projection="3d") m.plot_latent(ax=latent_axes) - latent_axes.set_aspect('equal') + latent_axes.set_aspect("equal") y = m.Y[0, :] - data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel'], viz_axes) + data_show = GPy.plotting.matplot_dep.visualize.skeleton_show( + y[None, :], data["skel"], viz_axes + ) - lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes) - input('Press enter to finish') + lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm( + m.X[0].copy(), m, data_show, latent_axes=latent_axes, sense_axes=sense_axes + ) + input("Press enter to finish") lvm_visualizer.close() data_show.close() return m + def ssgplvm_simulation_linear(): import numpy as np import GPy + N, D, Q = 1000, 20, 5 pi = 0.2 @@ -721,7 +903,7 @@ def ssgplvm_simulation_linear(): if dies[q] < pi: x[q] = np.random.randn() else: - x[q] = 0. + x[q] = 0.0 return x Y = np.empty((N, D)) @@ -731,4 +913,3 @@ def ssgplvm_simulation_linear(): X[n] = sample_X(Q, pi) w = np.random.randn(D, Q) Y[n] = np.dot(w, X[n]) - diff --git a/GPy/examples/non_gaussian.py b/GPy/examples/non_gaussian.py index 5d5fc7f6..1f030f2c 100644 --- a/GPy/examples/non_gaussian.py +++ b/GPy/examples/non_gaussian.py @@ -4,38 +4,40 @@ import GPy import numpy as np from GPy.util import datasets + try: import matplotlib.pyplot as plt except: pass + def student_t_approx(optimize=True, plot=True): """ Example of regressing with a student t likelihood using Laplace """ real_std = 0.1 - #Start a function, any function - X = np.linspace(0.0, np.pi*2, 100)[:, None] - Y = np.sin(X) + np.random.randn(*X.shape)*real_std - Y = Y/Y.max() + # Start a function, any function + X = np.linspace(0.0, np.pi * 2, 100)[:, None] + Y = np.sin(X) + np.random.randn(*X.shape) * real_std + Y = Y / Y.max() Yc = Y.copy() - X_full = np.linspace(0.0, np.pi*2, 500)[:, None] + X_full = np.linspace(0.0, np.pi * 2, 500)[:, None] Y_full = np.sin(X_full) - Y_full = Y_full/Y_full.max() + Y_full = Y_full / Y_full.max() - #Slightly noisy data + # Slightly noisy data Yc[75:80] += 1 - #Very noisy data - #Yc[10] += 100 - #Yc[25] += 10 - #Yc[23] += 10 - #Yc[26] += 1000 - #Yc[24] += 10 - #Yc = Yc/Yc.max() + # Very noisy data + # Yc[10] += 100 + # Yc[25] += 10 + # Yc[23] += 10 + # Yc[26] += 1000 + # Yc[24] += 10 + # Yc = Yc/Yc.max() - #Add student t random noise to datapoints + # Add student t random noise to datapoints deg_free = 1 print("Real noise: ", real_std) initial_var_guess = 0.5 @@ -47,45 +49,50 @@ def student_t_approx(optimize=True, plot=True): kernel3 = GPy.kern.RBF(X.shape[1]) + GPy.kern.White(X.shape[1]) kernel4 = GPy.kern.RBF(X.shape[1]) + GPy.kern.White(X.shape[1]) - #Gaussian GP model on clean data + # Gaussian GP model on clean data m1 = GPy.models.GPRegression(X, Y.copy(), kernel=kernel1) # optimize - m1['.*white'].constrain_fixed(1e-5) + m1[".*white"].constrain_fixed(1e-5) m1.randomize() - #Gaussian GP model on corrupt data + # Gaussian GP model on corrupt data m2 = GPy.models.GPRegression(X, Yc.copy(), kernel=kernel2) - m2['.*white'].constrain_fixed(1e-5) + m2[".*white"].constrain_fixed(1e-5) m2.randomize() - #Student t GP model on clean data + # Student t GP model on clean data t_distribution = GPy.likelihoods.StudentT(deg_free=deg_free, sigma2=edited_real_sd) laplace_inf = GPy.inference.latent_function_inference.Laplace() - m3 = GPy.core.GP(X, Y.copy(), kernel3, likelihood=t_distribution, inference_method=laplace_inf) - m3['.*t_scale2'].constrain_bounded(1e-6, 10.) - m3['.*white'].constrain_fixed(1e-5) + m3 = GPy.core.GP( + X, Y.copy(), kernel3, likelihood=t_distribution, inference_method=laplace_inf + ) + m3[".*t_scale2"].constrain_bounded(1e-6, 10.0) + m3[".*white"].constrain_fixed(1e-5) m3.randomize() - #Student t GP model on corrupt data + # Student t GP model on corrupt data t_distribution = GPy.likelihoods.StudentT(deg_free=deg_free, sigma2=edited_real_sd) laplace_inf = GPy.inference.latent_function_inference.Laplace() - m4 = GPy.core.GP(X, Yc.copy(), kernel4, likelihood=t_distribution, inference_method=laplace_inf) - m4['.*t_scale2'].constrain_bounded(1e-6, 10.) - m4['.*white'].constrain_fixed(1e-5) + m4 = GPy.core.GP( + X, Yc.copy(), kernel4, likelihood=t_distribution, inference_method=laplace_inf + ) + m4[".*t_scale2"].constrain_bounded(1e-6, 10.0) + m4[".*white"].constrain_fixed(1e-5) m4.randomize() print(m4) - debug=True + debug = True if debug: m4.optimize(messages=1) from matplotlib import pyplot as pb + pb.plot(m4.X, m4.inference_method.f_hat) - pb.plot(m4.X, m4.Y, 'rx') + pb.plot(m4.X, m4.Y, "rx") m4.plot() print(m4) return m4 if optimize: - optimizer='scg' + optimizer = "scg" print("Clean Gaussian") m1.optimize(optimizer, messages=1) print("Corrupt Gaussian") @@ -97,77 +104,91 @@ def student_t_approx(optimize=True, plot=True): if plot: plt.figure(1) - plt.suptitle('Gaussian likelihood') + plt.suptitle("Gaussian likelihood") ax = plt.subplot(211) m1.plot(ax=ax) plt.plot(X_full, Y_full) plt.ylim(-1.5, 1.5) - plt.title('Gaussian clean') + plt.title("Gaussian clean") ax = plt.subplot(212) m2.plot(ax=ax) plt.plot(X_full, Y_full) plt.ylim(-1.5, 1.5) - plt.title('Gaussian corrupt') + plt.title("Gaussian corrupt") plt.figure(2) - plt.suptitle('Student-t likelihood') + plt.suptitle("Student-t likelihood") ax = plt.subplot(211) m3.plot(ax=ax) plt.plot(X_full, Y_full) plt.ylim(-1.5, 1.5) - plt.title('Student-t rasm clean') + plt.title("Student-t rasm clean") ax = plt.subplot(212) m4.plot(ax=ax) plt.plot(X_full, Y_full) plt.ylim(-1.5, 1.5) - plt.title('Student-t rasm corrupt') + plt.title("Student-t rasm corrupt") return m1, m2, m3, m4 + def boston_example(optimize=True, plot=True): raise NotImplementedError("Needs updating") import sklearn from sklearn.cross_validation import KFold - optimizer='bfgs' - messages=0 + + optimizer = "bfgs" + messages = 0 data = datasets.boston_housing() degrees_freedoms = [3, 5, 8, 10] - X = data['X'].copy() - Y = data['Y'].copy() - X = X-X.mean(axis=0) - X = X/X.std(axis=0) - Y = Y-Y.mean() - Y = Y/Y.std() + X = data["X"].copy() + Y = data["Y"].copy() + X = X - X.mean(axis=0) + X = X / X.std(axis=0) + Y = Y - Y.mean() + Y = Y / Y.std() num_folds = 10 kf = KFold(len(Y), n_folds=num_folds, indices=True) - num_models = len(degrees_freedoms) + 3 #3 for baseline, gaussian, gaussian laplace approx + num_models = ( + len(degrees_freedoms) + 3 + ) # 3 for baseline, gaussian, gaussian laplace approx score_folds = np.zeros((num_models, num_folds)) pred_density = score_folds.copy() def rmse(Y, Ystar): - return np.sqrt(np.mean((Y-Ystar)**2)) + return np.sqrt(np.mean((Y - Ystar) ** 2)) for n, (train, test) in enumerate(kf): X_train, X_test, Y_train, Y_test = X[train], X[test], Y[train], Y[test] print("Fold {}".format(n)) - noise = 1e-1 #np.exp(-2) + noise = 1e-1 # np.exp(-2) rbf_len = 0.5 data_axis_plot = 4 - kernelstu = GPy.kern.RBF(X.shape[1]) + GPy.kern.white(X.shape[1]) + GPy.kern.bias(X.shape[1]) - kernelgp = GPy.kern.RBF(X.shape[1]) + GPy.kern.white(X.shape[1]) + GPy.kern.bias(X.shape[1]) + kernelstu = ( + GPy.kern.RBF(X.shape[1]) + + GPy.kern.white(X.shape[1]) + + GPy.kern.bias(X.shape[1]) + ) + kernelgp = ( + GPy.kern.RBF(X.shape[1]) + + GPy.kern.white(X.shape[1]) + + GPy.kern.bias(X.shape[1]) + ) - #Baseline + # Baseline score_folds[0, n] = rmse(Y_test, np.mean(Y_train)) - #Gaussian GP + # Gaussian GP print("Gauss GP") - mgp = GPy.models.GPRegression(X_train.copy(), Y_train.copy(), kernel=kernelgp.copy()) - mgp.constrain_fixed('.*white', 1e-5) - mgp['.*len'] = rbf_len - mgp['.*noise'] = noise + mgp = GPy.models.GPRegression( + X_train.copy(), Y_train.copy(), kernel=kernelgp.copy() + ) + mgp.constrain_fixed(".*white", 1e-5) + mgp[".*len"] = rbf_len + mgp[".*noise"] = noise print(mgp) if optimize: mgp.optimize(optimizer=optimizer, messages=messages) @@ -179,13 +200,20 @@ def boston_example(optimize=True, plot=True): print("Gaussian Laplace GP") N, D = Y_train.shape - g_distribution = GPy.likelihoods.noise_model_constructors.gaussian(variance=noise, N=N, D=D) + g_distribution = GPy.likelihoods.noise_model_constructors.gaussian( + variance=noise, N=N, D=D + ) g_likelihood = GPy.likelihoods.Laplace(Y_train.copy(), g_distribution) - mg = GPy.models.GPRegression(X_train.copy(), Y_train.copy(), kernel=kernelstu.copy(), likelihood=g_likelihood) - mg.constrain_positive('noise_variance') - mg.constrain_fixed('.*white', 1e-5) - mg['rbf_len'] = rbf_len - mg['noise'] = noise + mg = GPy.models.GPRegression( + X_train.copy(), + Y_train.copy(), + kernel=kernelstu.copy(), + likelihood=g_likelihood, + ) + mg.constrain_positive("noise_variance") + mg.constrain_fixed(".*white", 1e-5) + mg["rbf_len"] = rbf_len + mg["noise"] = noise print(mg) if optimize: mg.optimize(optimizer=optimizer, messages=messages) @@ -196,101 +224,108 @@ def boston_example(optimize=True, plot=True): print(mg) for stu_num, df in enumerate(degrees_freedoms): - #Student T + # Student T print("Student-T GP {}df".format(df)) - t_distribution = GPy.likelihoods.noise_model_constructors.student_t(deg_free=df, sigma2=noise) + t_distribution = GPy.likelihoods.noise_model_constructors.student_t( + deg_free=df, sigma2=noise + ) stu_t_likelihood = GPy.likelihoods.Laplace(Y_train.copy(), t_distribution) - mstu_t = GPy.models.GPRegression(X_train.copy(), Y_train.copy(), kernel=kernelstu.copy(), likelihood=stu_t_likelihood) - mstu_t.constrain_fixed('.*white', 1e-5) - mstu_t.constrain_bounded('.*t_scale2', 0.0001, 1000) - mstu_t['rbf_len'] = rbf_len - mstu_t['.*t_scale2'] = noise + mstu_t = GPy.models.GPRegression( + X_train.copy(), + Y_train.copy(), + kernel=kernelstu.copy(), + likelihood=stu_t_likelihood, + ) + mstu_t.constrain_fixed(".*white", 1e-5) + mstu_t.constrain_bounded(".*t_scale2", 0.0001, 1000) + mstu_t["rbf_len"] = rbf_len + mstu_t[".*t_scale2"] = noise print(mstu_t) if optimize: mstu_t.optimize(optimizer=optimizer, messages=messages) Y_test_pred = mstu_t.predict(X_test) - score_folds[3+stu_num, n] = rmse(Y_test, Y_test_pred[0]) - pred_density[3+stu_num, n] = np.mean(mstu_t.log_predictive_density(X_test, Y_test)) + score_folds[3 + stu_num, n] = rmse(Y_test, Y_test_pred[0]) + pred_density[3 + stu_num, n] = np.mean( + mstu_t.log_predictive_density(X_test, Y_test) + ) print(pred_density) print(mstu_t) if plot: plt.figure() plt.scatter(X_test[:, data_axis_plot], Y_test_pred[0]) - plt.scatter(X_test[:, data_axis_plot], Y_test, c='r', marker='x') - plt.title('GP gauss') + plt.scatter(X_test[:, data_axis_plot], Y_test, c="r", marker="x") + plt.title("GP gauss") plt.figure() plt.scatter(X_test[:, data_axis_plot], Y_test_pred[0]) - plt.scatter(X_test[:, data_axis_plot], Y_test, c='r', marker='x') - plt.title('Lap gauss') + plt.scatter(X_test[:, data_axis_plot], Y_test, c="r", marker="x") + plt.title("Lap gauss") plt.figure() plt.scatter(X_test[:, data_axis_plot], Y_test_pred[0]) - plt.scatter(X_test[:, data_axis_plot], Y_test, c='r', marker='x') - plt.title('Stu t {}df'.format(df)) + plt.scatter(X_test[:, data_axis_plot], Y_test, c="r", marker="x") + plt.title("Stu t {}df".format(df)) print("Average scores: {}".format(np.mean(score_folds, 1))) print("Average pred density: {}".format(np.mean(pred_density, 1))) if plot: - #Plotting - stu_t_legends = ['Student T, df={}'.format(df) for df in degrees_freedoms] - legends = ['Baseline', 'Gaussian', 'Laplace Approx Gaussian'] + stu_t_legends + # Plotting + stu_t_legends = ["Student T, df={}".format(df) for df in degrees_freedoms] + legends = ["Baseline", "Gaussian", "Laplace Approx Gaussian"] + stu_t_legends - #Plot boxplots for RMSE density + # Plot boxplots for RMSE density fig = plt.figure() - ax=fig.add_subplot(111) - plt.title('RMSE') - bp = ax.boxplot(score_folds.T, notch=0, sym='+', vert=1, whis=1.5) - plt.setp(bp['boxes'], color='black') - plt.setp(bp['whiskers'], color='black') - plt.setp(bp['fliers'], color='red', marker='+') + ax = fig.add_subplot(111) + plt.title("RMSE") + bp = ax.boxplot(score_folds.T, notch=0, sym="+", vert=1, whis=1.5) + plt.setp(bp["boxes"], color="black") + plt.setp(bp["whiskers"], color="black") + plt.setp(bp["fliers"], color="red", marker="+") xtickNames = plt.setp(ax, xticklabels=legends) plt.setp(xtickNames, rotation=45, fontsize=8) - ax.set_ylabel('RMSE') - ax.set_xlabel('Distribution') - #Make grid and put it below boxes - ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', - alpha=0.5) + ax.set_ylabel("RMSE") + ax.set_xlabel("Distribution") + # Make grid and put it below boxes + ax.yaxis.grid(True, linestyle="-", which="major", color="lightgrey", alpha=0.5) ax.set_axisbelow(True) - #Plot boxplots for predictive density + # Plot boxplots for predictive density fig = plt.figure() - ax=fig.add_subplot(111) - plt.title('Predictive density') - bp = ax.boxplot(pred_density[1:,:].T, notch=0, sym='+', vert=1, whis=1.5) - plt.setp(bp['boxes'], color='black') - plt.setp(bp['whiskers'], color='black') - plt.setp(bp['fliers'], color='red', marker='+') + ax = fig.add_subplot(111) + plt.title("Predictive density") + bp = ax.boxplot(pred_density[1:, :].T, notch=0, sym="+", vert=1, whis=1.5) + plt.setp(bp["boxes"], color="black") + plt.setp(bp["whiskers"], color="black") + plt.setp(bp["fliers"], color="red", marker="+") xtickNames = plt.setp(ax, xticklabels=legends[1:]) plt.setp(xtickNames, rotation=45, fontsize=8) - ax.set_ylabel('Mean Log probability P(Y*|Y)') - ax.set_xlabel('Distribution') - #Make grid and put it below boxes - ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', - alpha=0.5) + ax.set_ylabel("Mean Log probability P(Y*|Y)") + ax.set_xlabel("Distribution") + # Make grid and put it below boxes + ax.yaxis.grid(True, linestyle="-", which="major", color="lightgrey", alpha=0.5) ax.set_axisbelow(True) return mstu_t -#def precipitation_example(): - #import sklearn - #from sklearn.cross_validation import KFold - #data = datasets.boston_housing() - #X = data['X'].copy() - #Y = data['Y'].copy() - #X = X-X.mean(axis=0) - #X = X/X.std(axis=0) - #Y = Y-Y.mean() - #Y = Y/Y.std() - #import ipdb; ipdb.set_trace() # XXX BREAKPOINT - #num_folds = 10 - #kf = KFold(len(Y), n_folds=num_folds, indices=True) - #score_folds = np.zeros((4, num_folds)) - #def rmse(Y, Ystar): - #return np.sqrt(np.mean((Y-Ystar)**2)) - ##for train, test in kf: - #for n, (train, test) in enumerate(kf): - #X_train, X_test, Y_train, Y_test = X[train], X[test], Y[train], Y[test] - #print "Fold {}".format(n) +# def precipitation_example(): +# import sklearn +# from sklearn.cross_validation import KFold +# data = datasets.boston_housing() +# X = data['X'].copy() +# Y = data['Y'].copy() +# X = X-X.mean(axis=0) +# X = X/X.std(axis=0) +# Y = Y-Y.mean() +# Y = Y/Y.std() +# import ipdb; ipdb.set_trace() # XXX BREAKPOINT +# num_folds = 10 +# kf = KFold(len(Y), n_folds=num_folds, indices=True) +# score_folds = np.zeros((4, num_folds)) +# def rmse(Y, Ystar): +# return np.sqrt(np.mean((Y-Ystar)**2)) +##for train, test in kf: +# for n, (train, test) in enumerate(kf): +# X_train, X_test, Y_train, Y_test = X[train], X[test], Y[train], Y[test] +# print "Fold {}".format(n) diff --git a/GPy/examples/regression.py b/GPy/examples/regression.py index 93e05cbb..9ade6552 100644 --- a/GPy/examples/regression.py +++ b/GPy/examples/regression.py @@ -11,88 +11,112 @@ except: import numpy as np import GPy + def olympic_marathon_men(optimize=True, plot=True): """Run a standard Gaussian process regression on the Olympic marathon data.""" - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.olympic_marathon_men() # create simple GP Model - m = GPy.models.GPRegression(data['X'], data['Y']) + m = GPy.models.GPRegression(data["X"], data["Y"]) # set the lengthscale to be something sensible (defaults to 1) - m.kern.lengthscale = 10. + m.kern.lengthscale = 10.0 if optimize: - m.optimize('bfgs', max_iters=200) + m.optimize("bfgs", max_iters=200) if plot: m.plot(plot_limits=(1850, 2050)) return m + def coregionalization_toy(optimize=True, plot=True): """ A simple demonstration of coregionalization on two sinusoidal functions. """ - #build a design matrix with a column of integers indicating the output + # build a design matrix with a column of integers indicating the output X1 = np.random.rand(50, 1) * 8 X2 = np.random.rand(30, 1) * 5 - #build a suitable set of observed variables + # build a suitable set of observed variables Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05 - Y2 = np.sin(X2) + np.random.randn(*X2.shape) * 0.05 + 2. + Y2 = np.sin(X2) + np.random.randn(*X2.shape) * 0.05 + 2.0 - m = GPy.models.GPCoregionalizedRegression(X_list=[X1,X2], Y_list=[Y1,Y2]) + m = GPy.models.GPCoregionalizedRegression(X_list=[X1, X2], Y_list=[Y1, Y2]) if optimize: - m.optimize('bfgs', max_iters=100) + m.optimize("bfgs", max_iters=100) if plot: - slices = GPy.util.multioutput.get_slices([X1,X2]) - m.plot(fixed_inputs=[(1,0)],which_data_rows=slices[0],Y_metadata={'output_index':0}) - m.plot(fixed_inputs=[(1,1)],which_data_rows=slices[1],Y_metadata={'output_index':1},ax=pb.gca()) + slices = GPy.util.multioutput.get_slices([X1, X2]) + m.plot( + fixed_inputs=[(1, 0)], + which_data_rows=slices[0], + Y_metadata={"output_index": 0}, + ) + m.plot( + fixed_inputs=[(1, 1)], + which_data_rows=slices[1], + Y_metadata={"output_index": 1}, + ax=pb.gca(), + ) return m + def coregionalization_sparse(optimize=True, plot=True): """ A simple demonstration of coregionalization on two sinusoidal functions using sparse approximations. """ - #build a design matrix with a column of integers indicating the output + # build a design matrix with a column of integers indicating the output X1 = np.random.rand(50, 1) * 8 X2 = np.random.rand(30, 1) * 5 - #build a suitable set of observed variables + # build a suitable set of observed variables Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05 - Y2 = np.sin(X2) + np.random.randn(*X2.shape) * 0.05 + 2. + Y2 = np.sin(X2) + np.random.randn(*X2.shape) * 0.05 + 2.0 - m = GPy.models.SparseGPCoregionalizedRegression(X_list=[X1,X2], Y_list=[Y1,Y2]) + m = GPy.models.SparseGPCoregionalizedRegression(X_list=[X1, X2], Y_list=[Y1, Y2]) if optimize: - m.optimize('bfgs', max_iters=100) + m.optimize("bfgs", max_iters=100) if plot: - slices = GPy.util.multioutput.get_slices([X1,X2]) - m.plot(fixed_inputs=[(1,0)],which_data_rows=slices[0],Y_metadata={'output_index':0}) - m.plot(fixed_inputs=[(1,1)],which_data_rows=slices[1],Y_metadata={'output_index':1},ax=pb.gca()) + slices = GPy.util.multioutput.get_slices([X1, X2]) + m.plot( + fixed_inputs=[(1, 0)], + which_data_rows=slices[0], + Y_metadata={"output_index": 0}, + ) + m.plot( + fixed_inputs=[(1, 1)], + which_data_rows=slices[1], + Y_metadata={"output_index": 1}, + ax=pb.gca(), + ) pb.ylim(-3,) return m + def epomeo_gpx(max_iters=200, optimize=True, plot=True): """ Perform Gaussian process regression on the latitude and longitude data from the Mount Epomeo runs. Requires gpxpy to be installed on your system to load in the data. """ - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.epomeo_gpx() num_data_list = [] - for Xpart in data['X']: + for Xpart in data["X"]: num_data_list.append(Xpart.shape[0]) num_data_array = np.array(num_data_list) @@ -100,29 +124,43 @@ def epomeo_gpx(max_iters=200, optimize=True, plot=True): Y = np.zeros((num_data, 2)) t = np.zeros((num_data, 2)) start = 0 - for Xpart, index in zip(data['X'], range(len(data['X']))): - end = start+Xpart.shape[0] - t[start:end, :] = np.hstack((Xpart[:, 0:1], - index*np.ones((Xpart.shape[0], 1)))) + for Xpart, index in zip(data["X"], range(len(data["X"]))): + end = start + Xpart.shape[0] + t[start:end, :] = np.hstack( + (Xpart[:, 0:1], index * np.ones((Xpart.shape[0], 1))) + ) Y[start:end, :] = Xpart[:, 1:3] num_inducing = 200 - Z = np.hstack((np.linspace(t[:,0].min(), t[:, 0].max(), num_inducing)[:, None], - np.random.randint(0, 4, num_inducing)[:, None])) + Z = np.hstack( + ( + np.linspace(t[:, 0].min(), t[:, 0].max(), num_inducing)[:, None], + np.random.randint(0, 4, num_inducing)[:, None], + ) + ) k1 = GPy.kern.RBF(1) k2 = GPy.kern.Coregionalize(output_dim=5, rank=5) - k = k1**k2 + k = k1 ** k2 m = GPy.models.SparseGPRegression(t, Y, kernel=k, Z=Z, normalize_Y=True) - m.constrain_fixed('.*variance', 1.) + m.constrain_fixed(".*variance", 1.0) m.inducing_inputs.constrain_fixed() m.Gaussian_noise.variance.constrain_bounded(1e-3, 1e-1) - m.optimize(max_iters=max_iters,messages=True) + m.optimize(max_iters=max_iters, messages=True) return m -def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=10000, max_iters=300, optimize=True, plot=True): + +def multiple_optima( + gene_number=937, + resolution=80, + model_restarts=10, + seed=10000, + max_iters=300, + optimize=True, + plot=True, +): """ Show an example of a multimodal error surface for Gaussian process regression. Gene 939 has bimodal behaviour where the noisy mode is @@ -130,25 +168,30 @@ def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=1000 """ # Contour over a range of length scales and signal/noise ratios. - length_scales = np.linspace(0.1, 60., resolution) - log_SNRs = np.linspace(-3., 4., resolution) + length_scales = np.linspace(0.1, 60.0, resolution) + log_SNRs = np.linspace(-3.0, 4.0, resolution) - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return - data = pods.datasets.della_gatta_TRP63_gene_expression(data_set='della_gatta',gene_number=gene_number) + data = pods.datasets.della_gatta_TRP63_gene_expression( + data_set="della_gatta", gene_number=gene_number + ) # data['Y'] = data['Y'][0::2, :] # data['X'] = data['X'][0::2, :] - data['Y'] = data['Y'] - np.mean(data['Y']) + data["Y"] = data["Y"] - np.mean(data["Y"]) - lls = GPy.examples.regression._contour_data(data, length_scales, log_SNRs, GPy.kern.RBF) + lls = GPy.examples.regression._contour_data( + data, length_scales, log_SNRs, GPy.kern.RBF + ) if plot: pb.contour(length_scales, log_SNRs, np.exp(lls), 20, cmap=pb.cm.jet) ax = pb.gca() - pb.xlabel('length scale') - pb.ylabel('log_10 SNR') + pb.xlabel("length scale") + pb.ylabel("log_10 SNR") xlim = ax.get_xlim() ylim = ax.get_ylim() @@ -160,28 +203,41 @@ def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=1000 np.random.seed(seed=seed) for i in range(0, model_restarts): # kern = GPy.kern.RBF(1, variance=np.random.exponential(1.), lengthscale=np.random.exponential(50.)) - kern = GPy.kern.RBF(1, variance=np.random.uniform(1e-3, 1), lengthscale=np.random.uniform(5, 50)) + kern = GPy.kern.RBF( + 1, variance=np.random.uniform(1e-3, 1), lengthscale=np.random.uniform(5, 50) + ) - m = GPy.models.GPRegression(data['X'], data['Y'], kernel=kern) + m = GPy.models.GPRegression(data["X"], data["Y"], kernel=kern) m.likelihood.variance = np.random.uniform(1e-3, 1) optim_point_x[0] = m.rbf.lengthscale - optim_point_y[0] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance); + optim_point_y[0] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance) # optimize if optimize: - m.optimize('scg', xtol=1e-6, ftol=1e-6, max_iters=max_iters) + m.optimize("scg", xtol=1e-6, ftol=1e-6, max_iters=max_iters) optim_point_x[1] = m.rbf.lengthscale - optim_point_y[1] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance); + optim_point_y[1] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance) if plot: - pb.arrow(optim_point_x[0], optim_point_y[0], optim_point_x[1] - optim_point_x[0], optim_point_y[1] - optim_point_y[0], label=str(i), head_length=1, head_width=0.5, fc='k', ec='k') + pb.arrow( + optim_point_x[0], + optim_point_y[0], + optim_point_x[1] - optim_point_x[0], + optim_point_y[1] - optim_point_y[0], + label=str(i), + head_length=1, + head_width=0.5, + fc="k", + ec="k", + ) models.append(m) if plot: ax.set_xlim(xlim) ax.set_ylim(ylim) - return m # (models, lls) + return m # (models, lls) + def _contour_data(data, length_scales, log_SNRs, kernel_call=GPy.kern.RBF): """ @@ -195,19 +251,19 @@ def _contour_data(data, length_scales, log_SNRs, kernel_call=GPy.kern.RBF): """ lls = [] - total_var = np.var(data['Y']) - kernel = kernel_call(1, variance=1., lengthscale=1.) - model = GPy.models.GPRegression(data['X'], data['Y'], kernel=kernel) + total_var = np.var(data["Y"]) + kernel = kernel_call(1, variance=1.0, lengthscale=1.0) + model = GPy.models.GPRegression(data["X"], data["Y"], kernel=kernel) for log_SNR in log_SNRs: - SNR = 10.**log_SNR - noise_var = total_var / (1. + SNR) + SNR = 10.0 ** log_SNR + noise_var = total_var / (1.0 + SNR) signal_var = total_var - noise_var - model.kern['.*variance'] = signal_var + model.kern[".*variance"] = signal_var model.likelihood.variance = noise_var length_scale_lls = [] for length_scale in length_scales: - model['.*lengthscale'] = length_scale + model[".*lengthscale"] = length_scale length_scale_lls.append(model.log_likelihood()) lls.append(length_scale_lls) @@ -217,86 +273,97 @@ def _contour_data(data, length_scales, log_SNRs, kernel_call=GPy.kern.RBF): def olympic_100m_men(optimize=True, plot=True): """Run a standard Gaussian process regression on the Rogers and Girolami olympics data.""" - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.olympic_100m_men() # create simple GP Model - m = GPy.models.GPRegression(data['X'], data['Y']) + m = GPy.models.GPRegression(data["X"], data["Y"]) # set the lengthscale to be something sensible (defaults to 1) m.rbf.lengthscale = 10 if optimize: - m.optimize('bfgs', max_iters=200) + m.optimize("bfgs", max_iters=200) if plot: m.plot(plot_limits=(1850, 2050)) return m + def toy_rbf_1d(optimize=True, plot=True): """Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance.""" - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.toy_rbf_1d() # create simple GP Model - m = GPy.models.GPRegression(data['X'], data['Y']) + m = GPy.models.GPRegression(data["X"], data["Y"]) if optimize: - m.optimize('bfgs') + m.optimize("bfgs") if plot: m.plot() return m + def toy_rbf_1d_50(optimize=True, plot=True): """Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance.""" - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.toy_rbf_1d_50() # create simple GP Model - m = GPy.models.GPRegression(data['X'], data['Y']) + m = GPy.models.GPRegression(data["X"], data["Y"]) if optimize: - m.optimize('bfgs') + m.optimize("bfgs") if plot: m.plot() return m + def toy_poisson_rbf_1d_laplace(optimize=True, plot=True): """Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance.""" - optimizer='scg' + optimizer = "scg" x_len = 100 X = np.linspace(0, 10, x_len)[:, None] f_true = np.random.multivariate_normal(np.zeros(x_len), GPy.kern.RBF(1).K(X)) - Y = np.array([np.random.poisson(np.exp(f)) for f in f_true])[:,None] + Y = np.array([np.random.poisson(np.exp(f)) for f in f_true])[:, None] kern = GPy.kern.RBF(1) poisson_lik = GPy.likelihoods.Poisson() laplace_inf = GPy.inference.latent_function_inference.Laplace() # create simple GP Model - m = GPy.core.GP(X, Y, kernel=kern, likelihood=poisson_lik, inference_method=laplace_inf) + m = GPy.core.GP( + X, Y, kernel=kern, likelihood=poisson_lik, inference_method=laplace_inf + ) if optimize: m.optimize(optimizer) if plot: m.plot() # plot the real underlying rate function - pb.plot(X, np.exp(f_true), '--k', linewidth=2) + pb.plot(X, np.exp(f_true), "--k", linewidth=2) return m -def toy_ARD(max_iters=1000, kernel_type='linear', num_samples=300, D=4, optimize=True, plot=True): + +def toy_ARD( + max_iters=1000, kernel_type="linear", num_samples=300, D=4, optimize=True, plot=True +): # Create an artificial dataset where the values in the targets (Y) # only depend in dimensions 1 and 3 of the inputs (X). Run ARD to # see if this dependency can be recovered @@ -310,14 +377,14 @@ def toy_ARD(max_iters=1000, kernel_type='linear', num_samples=300, D=4, optimize Y2 = np.asarray(4 * (X[:, 2] - 1.5 * X[:, 0])).reshape(-1, 1) Y = np.hstack((Y1, Y2)) - Y = np.dot(Y, np.random.rand(2, D)); + Y = np.dot(Y, np.random.rand(2, D)) Y = Y + 0.2 * np.random.randn(Y.shape[0], Y.shape[1]) Y -= Y.mean() Y /= Y.std() - if kernel_type == 'linear': + if kernel_type == "linear": kernel = GPy.kern.Linear(X.shape[1], ARD=1) - elif kernel_type == 'rbf_inv': + elif kernel_type == "rbf_inv": kernel = GPy.kern.RBF_inv(X.shape[1], ARD=1) else: kernel = GPy.kern.RBF(X.shape[1], ARD=1) @@ -327,14 +394,17 @@ def toy_ARD(max_iters=1000, kernel_type='linear', num_samples=300, D=4, optimize # m.set_prior('.*lengthscale',len_prior) if optimize: - m.optimize(optimizer='scg', max_iters=max_iters) + m.optimize(optimizer="scg", max_iters=max_iters) if plot: m.kern.plot_ARD() return m -def toy_ARD_sparse(max_iters=1000, kernel_type='linear', num_samples=300, D=4, optimize=True, plot=True): + +def toy_ARD_sparse( + max_iters=1000, kernel_type="linear", num_samples=300, D=4, optimize=True, plot=True +): # Create an artificial dataset where the values in the targets (Y) # only depend in dimensions 1 and 3 of the inputs (X). Run ARD to # see if this dependency can be recovered @@ -348,69 +418,73 @@ def toy_ARD_sparse(max_iters=1000, kernel_type='linear', num_samples=300, D=4, o Y2 = np.asarray(4 * (X[:, 2] - 1.5 * X[:, 0]))[:, None] Y = np.hstack((Y1, Y2)) - Y = np.dot(Y, np.random.rand(2, D)); + Y = np.dot(Y, np.random.rand(2, D)) Y = Y + 0.2 * np.random.randn(Y.shape[0], Y.shape[1]) Y -= Y.mean() Y /= Y.std() - if kernel_type == 'linear': + if kernel_type == "linear": kernel = GPy.kern.Linear(X.shape[1], ARD=1) - elif kernel_type == 'rbf_inv': + elif kernel_type == "rbf_inv": kernel = GPy.kern.RBF_inv(X.shape[1], ARD=1) else: kernel = GPy.kern.RBF(X.shape[1], ARD=1) - #kernel += GPy.kern.Bias(X.shape[1]) + # kernel += GPy.kern.Bias(X.shape[1]) X_variance = np.ones(X.shape) * 0.5 m = GPy.models.SparseGPRegression(X, Y, kernel, X_variance=X_variance) # len_prior = GPy.priors.inverse_gamma(1,18) # 1, 25 # m.set_prior('.*lengthscale',len_prior) if optimize: - m.optimize(optimizer='scg', max_iters=max_iters) + m.optimize(optimizer="scg", max_iters=max_iters) if plot: m.kern.plot_ARD() return m + def robot_wireless(max_iters=100, kernel=None, optimize=True, plot=True): """Predict the location of a robot given wirelss signal strength readings.""" - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.robot_wireless() # create simple GP Model - m = GPy.models.GPRegression(data['Y'], data['X'], kernel=kernel) + m = GPy.models.GPRegression(data["Y"], data["X"], kernel=kernel) # optimize if optimize: m.optimize(max_iters=max_iters) - Xpredict = m.predict(data['Ytest'])[0] + Xpredict = m.predict(data["Ytest"])[0] if plot: - pb.plot(data['Xtest'][:, 0], data['Xtest'][:, 1], 'r-') - pb.plot(Xpredict[:, 0], Xpredict[:, 1], 'b-') - pb.axis('equal') - pb.title('WiFi Localization with Gaussian Processes') - pb.legend(('True Location', 'Predicted Location')) + pb.plot(data["Xtest"][:, 0], data["Xtest"][:, 1], "r-") + pb.plot(Xpredict[:, 0], Xpredict[:, 1], "b-") + pb.axis("equal") + pb.title("WiFi Localization with Gaussian Processes") + pb.legend(("True Location", "Predicted Location")) - sse = ((data['Xtest'] - Xpredict)**2).sum() + sse = ((data["Xtest"] - Xpredict) ** 2).sum() - print(('Sum of squares error on test data: ' + str(sse))) + print(("Sum of squares error on test data: " + str(sse))) return m + def silhouette(max_iters=100, optimize=True, plot=True): """Predict the pose of a figure given a silhouette. This is a task from Agarwal and Triggs 2004 ICML paper.""" - try:import pods + try: + import pods except ImportError: - print('pods unavailable, see https://github.com/sods/ods for example datasets') + print("pods unavailable, see https://github.com/sods/ods for example datasets") return data = pods.datasets.silhouette() # create simple GP Model - m = GPy.models.GPRegression(data['X'], data['Y']) + m = GPy.models.GPRegression(data["X"], data["Y"]) # optimize if optimize: @@ -419,10 +493,18 @@ def silhouette(max_iters=100, optimize=True, plot=True): print(m) return m -def sparse_GP_regression_1D(num_samples=400, num_inducing=5, max_iters=100, optimize=True, plot=True, checkgrad=False): + +def sparse_GP_regression_1D( + num_samples=400, + num_inducing=5, + max_iters=100, + optimize=True, + plot=True, + checkgrad=False, +): """Run a 1D example of a sparse GP regression.""" # sample inputs and outputs - X = np.random.uniform(-3., 3., (num_samples, 1)) + X = np.random.uniform(-3.0, 3.0, (num_samples, 1)) Y = np.sin(X) + np.random.randn(num_samples, 1) * 0.05 # construct kernel rbf = GPy.kern.RBF(1) @@ -433,20 +515,23 @@ def sparse_GP_regression_1D(num_samples=400, num_inducing=5, max_iters=100, opti m.checkgrad() if optimize: - m.optimize('tnc', max_iters=max_iters) + m.optimize("tnc", max_iters=max_iters) if plot: m.plot() return m -def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100, optimize=True, plot=True, nan=False): + +def sparse_GP_regression_2D( + num_samples=400, num_inducing=50, max_iters=100, optimize=True, plot=True, nan=False +): """Run a 2D example of a sparse GP regression.""" np.random.seed(1234) - X = np.random.uniform(-3., 3., (num_samples, 2)) + X = np.random.uniform(-3.0, 3.0, (num_samples, 2)) Y = np.sin(X[:, 0:1]) * np.sin(X[:, 1:2]) + np.random.randn(num_samples, 1) * 0.05 if nan: - inan = np.random.binomial(1,.2,size=Y.shape) + inan = np.random.binomial(1, 0.2, size=Y.shape) Y[inan] = np.nan # construct kernel @@ -456,13 +541,13 @@ def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100, opt m = GPy.models.SparseGPRegression(X, Y, kernel=rbf, num_inducing=num_inducing) # contrain all parameters to be positive (but not inducing inputs) - m['.*len'] = 2. + m[".*len"] = 2.0 m.checkgrad() # optimize if optimize: - m.optimize('tnc', messages=1, max_iters=max_iters) + m.optimize("tnc", messages=1, max_iters=max_iters) # plot if plot: @@ -471,76 +556,79 @@ def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100, opt print(m) return m + def uncertain_inputs_sparse_regression(max_iters=200, optimize=True, plot=True): """Run a 1D example of a sparse GP regression with uncertain inputs.""" fig, axes = pb.subplots(1, 2, figsize=(12, 5), sharex=True, sharey=True) # sample inputs and outputs S = np.ones((20, 1)) - X = np.random.uniform(-3., 3., (20, 1)) + X = np.random.uniform(-3.0, 3.0, (20, 1)) Y = np.sin(X) + np.random.randn(20, 1) * 0.05 # likelihood = GPy.likelihoods.Gaussian(Y) - Z = np.random.uniform(-3., 3., (7, 1)) + Z = np.random.uniform(-3.0, 3.0, (7, 1)) k = GPy.kern.RBF(1) # create simple GP Model - no input uncertainty on this one m = GPy.models.SparseGPRegression(X, Y, kernel=k, Z=Z) if optimize: - m.optimize('scg', messages=1, max_iters=max_iters) + m.optimize("scg", messages=1, max_iters=max_iters) if plot: m.plot(ax=axes[0]) - axes[0].set_title('no input uncertainty') + axes[0].set_title("no input uncertainty") print(m) # the same Model with uncertainty m = GPy.models.SparseGPRegression(X, Y, kernel=GPy.kern.RBF(1), Z=Z, X_variance=S) if optimize: - m.optimize('scg', messages=1, max_iters=max_iters) + m.optimize("scg", messages=1, max_iters=max_iters) if plot: m.plot(ax=axes[1]) - axes[1].set_title('with input uncertainty') + axes[1].set_title("with input uncertainty") fig.canvas.draw() print(m) return m + def simple_mean_function(max_iters=100, optimize=True, plot=True): """ The simplest possible mean function. No parameters, just a simple Sinusoid. """ - #create simple mean function - mf = GPy.core.Mapping(1,1) + # create simple mean function + mf = GPy.core.Mapping(1, 1) mf.f = np.sin - mf.update_gradients = lambda a,b: None + mf.update_gradients = lambda a, b: None - X = np.linspace(0,10,50).reshape(-1,1) - Y = np.sin(X) + 0.5*np.cos(3*X) + 0.1*np.random.randn(*X.shape) + X = np.linspace(0, 10, 50).reshape(-1, 1) + Y = np.sin(X) + 0.5 * np.cos(3 * X) + 0.1 * np.random.randn(*X.shape) - k =GPy.kern.RBF(1) + k = GPy.kern.RBF(1) lik = GPy.likelihoods.Gaussian() m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf) if optimize: m.optimize(max_iters=max_iters) if plot: - m.plot(plot_limits=(-10,15)) + m.plot(plot_limits=(-10, 15)) return m + def parametric_mean_function(max_iters=100, optimize=True, plot=True): """ A linear mean function with parameters that we'll learn alongside the kernel """ - #create simple mean function - mf = GPy.core.Mapping(1,1) + # create simple mean function + mf = GPy.core.Mapping(1, 1) mf.f = np.sin - X = np.linspace(0,10,50).reshape(-1,1) - Y = np.sin(X) + 0.5*np.cos(3*X) + 0.1*np.random.randn(*X.shape) + 3*X + X = np.linspace(0, 10, 50).reshape(-1, 1) + Y = np.sin(X) + 0.5 * np.cos(3 * X) + 0.1 * np.random.randn(*X.shape) + 3 * X - mf = GPy.mappings.Linear(1,1) + mf = GPy.mappings.Linear(1, 1) - k =GPy.kern.RBF(1) + k = GPy.kern.RBF(1) lik = GPy.likelihoods.Gaussian() m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf) if optimize: @@ -556,23 +644,27 @@ def warped_gp_cubic_sine(max_iters=100): Snelson's paper. """ X = (2 * np.pi) * np.random.random(151) - np.pi - Y = np.sin(X) + np.random.normal(0,0.2,151) - Y = np.array([np.power(abs(y),float(1)/3) * (1,-1)[y<0] for y in Y]) + Y = np.sin(X) + np.random.normal(0, 0.2, 151) + Y = np.array([np.power(abs(y), float(1) / 3) * (1, -1)[y < 0] for y in Y]) X = X[:, None] Y = Y[:, None] warp_k = GPy.kern.RBF(1) warp_f = GPy.util.warping_functions.TanhFunction(n_terms=2) warp_m = GPy.models.WarpedGP(X, Y, kernel=warp_k, warping_function=warp_f) - warp_m['.*\.d'].constrain_fixed(1.0) + warp_m[".*\.d"].constrain_fixed(1.0) m = GPy.models.GPRegression(X, Y) - m.optimize_restarts(parallel=False, robust=True, num_restarts=5, max_iters=max_iters) - warp_m.optimize_restarts(parallel=False, robust=True, num_restarts=5, max_iters=max_iters) - #m.optimize(max_iters=max_iters) - #warp_m.optimize(max_iters=max_iters) + m.optimize_restarts( + parallel=False, robust=True, num_restarts=5, max_iters=max_iters + ) + warp_m.optimize_restarts( + parallel=False, robust=True, num_restarts=5, max_iters=max_iters + ) + # m.optimize(max_iters=max_iters) + # warp_m.optimize(max_iters=max_iters) print(warp_m) - print(warp_m['.*warp.*']) + print(warp_m[".*warp.*"]) warp_m.predict_in_warped_space = False warp_m.plot(title="Warped GP - Latent space") @@ -584,55 +676,88 @@ def warped_gp_cubic_sine(max_iters=100): return warp_m - def multioutput_gp_with_derivative_observations(): - def plot_gp_vs_real(m, x, yreal, size_inputs, title, fixed_input=1, xlim=[0,11], ylim=[-1.5,3]): + def plot_gp_vs_real( + m, x, yreal, size_inputs, title, fixed_input=1, xlim=[0, 11], ylim=[-1.5, 3] + ): fig, ax = pb.subplots() ax.set_title(title) - pb.plot(x, yreal, "r", label='Real function') - rows = slice(0, size_inputs[0]) if fixed_input == 0 else slice(size_inputs[0], size_inputs[0]+size_inputs[1]) - m.plot(fixed_inputs=[(1, fixed_input)], which_data_rows=rows, xlim=xlim, ylim=ylim, ax=ax) - f = lambda x: np.sin(x)+0.1*(x-2.)**2-0.005*x**3 - fd = lambda x: np.cos(x)+0.2*(x-2.)-0.015*x**2 - N=10 # Number of observations - M=10 # Number of derivative observations - Npred=100 # Number of prediction points - sigma = 0.05 # Noise of observations - sigma_der = 0.05 # Noise of derivative observations - x = np.array([np.linspace(1,10,N)]).T - y = f(x) + np.array(sigma*np.random.normal(0,1,(N,1))) + pb.plot(x, yreal, "r", label="Real function") + rows = ( + slice(0, size_inputs[0]) + if fixed_input == 0 + else slice(size_inputs[0], size_inputs[0] + size_inputs[1]) + ) + m.plot( + fixed_inputs=[(1, fixed_input)], + which_data_rows=rows, + xlim=xlim, + ylim=ylim, + ax=ax, + ) - xd = np.array([np.linspace(2,8,M)]).T - yd = fd(xd) + np.array(sigma_der*np.random.normal(0,1,(M,1))) + f = lambda x: np.sin(x) + 0.1 * (x - 2.0) ** 2 - 0.005 * x ** 3 + fd = lambda x: np.cos(x) + 0.2 * (x - 2.0) - 0.015 * x ** 2 + N = 10 # Number of observations + M = 10 # Number of derivative observations + Npred = 100 # Number of prediction points + sigma = 0.05 # Noise of observations + sigma_der = 0.05 # Noise of derivative observations + x = np.array([np.linspace(1, 10, N)]).T + y = f(x) + np.array(sigma * np.random.normal(0, 1, (N, 1))) - xpred = np.array([np.linspace(0,11,Npred)]).T + xd = np.array([np.linspace(2, 8, M)]).T + yd = fd(xd) + np.array(sigma_der * np.random.normal(0, 1, (M, 1))) + + xpred = np.array([np.linspace(0, 11, Npred)]).T ypred_true = f(xpred) ydpred_true = fd(xpred) # squared exponential kernel: - se = GPy.kern.RBF(input_dim = 1, lengthscale=1.5, variance=0.2) + se = GPy.kern.RBF(input_dim=1, lengthscale=1.5, variance=0.2) # We need to generate separate kernel for the derivative observations and give the created kernel as an input: se_der = GPy.kern.DiffKern(se, 0) - #Then - gauss = GPy.likelihoods.Gaussian(variance=sigma**2) - gauss_der = GPy.likelihoods.Gaussian(variance=sigma_der**2) + # Then + gauss = GPy.likelihoods.Gaussian(variance=sigma ** 2) + gauss_der = GPy.likelihoods.Gaussian(variance=sigma_der ** 2) # Then create the model, we give everything in lists, the order of the inputs indicates the order of the outputs # Now we have the regular observations first and derivative observations second, meaning that the kernels and # the likelihoods must follow the same order. Crosscovariances are automatically taken care of - m = GPy.models.MultioutputGP(X_list=[x, xd], Y_list=[y, yd], - kernel_list=[se, se_der], - likelihood_list=[gauss, gauss_der]) + m = GPy.models.MultioutputGP( + X_list=[x, xd], + Y_list=[y, yd], + kernel_list=[se, se_der], + likelihood_list=[gauss, gauss_der], + ) # Optimize the model m.optimize(messages=0, ipython_notebook=False) - #Plot the model, the syntax is same as for multioutput models: - plot_gp_vs_real(m, xpred, ydpred_true, [x.shape[0], xd.shape[0]], title='Latent function derivatives', fixed_input=1, xlim=[0,11], ylim=[-1.5,3]) - plot_gp_vs_real(m, xpred, ypred_true, [x.shape[0], xd.shape[0]], title='Latent function', fixed_input=0, xlim=[0,11], ylim=[-1.5,3]) + # Plot the model, the syntax is same as for multioutput models: + plot_gp_vs_real( + m, + xpred, + ydpred_true, + [x.shape[0], xd.shape[0]], + title="Latent function derivatives", + fixed_input=1, + xlim=[0, 11], + ylim=[-1.5, 3], + ) + plot_gp_vs_real( + m, + xpred, + ypred_true, + [x.shape[0], xd.shape[0]], + title="Latent function", + fixed_input=0, + xlim=[0, 11], + ylim=[-1.5, 3], + ) - #making predictions for the values: - mu, var = m.predict_noiseless(Xnew=[xpred, np.empty((0,1))]) + # making predictions for the values: + mu, var = m.predict_noiseless(Xnew=[xpred, np.empty((0, 1))]) return m diff --git a/GPy/examples/state_space.py b/GPy/examples/state_space.py index 898d1676..33faf89d 100644 --- a/GPy/examples/state_space.py +++ b/GPy/examples/state_space.py @@ -4,26 +4,26 @@ import matplotlib.pyplot as plt import GPy.models.state_space_model as SS_model + def state_space_example(): X = np.linspace(0, 10, 2000)[:, None] - Y = np.sin(X) + np.random.randn(*X.shape)*0.1 + Y = np.sin(X) + np.random.randn(*X.shape) * 0.1 kernel1 = GPy.kern.Matern32(X.shape[1]) - m1 = GPy.models.GPRegression(X,Y, kernel1) + m1 = GPy.models.GPRegression(X, Y, kernel1) print(m1) - m1.optimize(optimizer='bfgs',messages=True) + m1.optimize(optimizer="bfgs", messages=True) print(m1) kernel2 = GPy.kern.sde_Matern32(X.shape[1]) - #m2 = SS_model.StateSpace(X,Y, kernel2) - m2 = GPy.models.StateSpace(X,Y, kernel2) + # m2 = SS_model.StateSpace(X,Y, kernel2) + m2 = GPy.models.StateSpace(X, Y, kernel2) print(m2) - m2.optimize(optimizer='bfgs',messages=True) + m2.optimize(optimizer="bfgs", messages=True) print(m2) return m1, m2 - From ed2d90fb220c571cb8ec6a82441e3016c1e343ed Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 24 May 2021 08:45:29 +0100 Subject: [PATCH 123/137] Fix badly formatted comment region. : --- GPy/examples/non_gaussian.py | 43 ++++++++++++++++++++---------------- 1 file changed, 24 insertions(+), 19 deletions(-) diff --git a/GPy/examples/non_gaussian.py b/GPy/examples/non_gaussian.py index 1f030f2c..cb86c83c 100644 --- a/GPy/examples/non_gaussian.py +++ b/GPy/examples/non_gaussian.py @@ -310,22 +310,27 @@ def boston_example(optimize=True, plot=True): # def precipitation_example(): -# import sklearn -# from sklearn.cross_validation import KFold -# data = datasets.boston_housing() -# X = data['X'].copy() -# Y = data['Y'].copy() -# X = X-X.mean(axis=0) -# X = X/X.std(axis=0) -# Y = Y-Y.mean() -# Y = Y/Y.std() -# import ipdb; ipdb.set_trace() # XXX BREAKPOINT -# num_folds = 10 -# kf = KFold(len(Y), n_folds=num_folds, indices=True) -# score_folds = np.zeros((4, num_folds)) -# def rmse(Y, Ystar): -# return np.sqrt(np.mean((Y-Ystar)**2)) -##for train, test in kf: -# for n, (train, test) in enumerate(kf): -# X_train, X_test, Y_train, Y_test = X[train], X[test], Y[train], Y[test] -# print "Fold {}".format(n) +# import sklearn +# from sklearn.cross_validation import KFold + +# data = datasets.boston_housing() +# X = data["X"].copy() +# Y = data["Y"].copy() +# X = X - X.mean(axis=0) +# X = X / X.std(axis=0) +# Y = Y - Y.mean() +# Y = Y / Y.std() +# import ipdb + +# ipdb.set_trace() # XXX BREAKPOINT +# num_folds = 10 +# kf = KFold(len(Y), n_folds=num_folds, indices=True) +# score_folds = np.zeros((4, num_folds)) + +# def rmse(Y, Ystar): +# return np.sqrt(np.mean((Y - Ystar) ** 2)) + +# for train, test in kf: +# for n, (train, test) in enumerate(kf): +# X_train, X_test, Y_train, Y_test = X[train], X[test], Y[train], Y[test] +# print("Fold {}".format(n)) From 5686950b5177f65ced91f81278e3c7aa123a491d Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 24 May 2021 08:51:24 +0100 Subject: [PATCH 124/137] Add Eric's suggesiton to 'raise from' --- GPy/plotting/matplot_dep/visualize.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index b942d763..a6c2f233 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -503,8 +503,7 @@ class stick_show(mocap_data_show): try: self.vals = self.vals.reshape((3, self.vals.shape[1]//3)).T except ValueError as e: - print("Passed values to stick_show need to have a dimension which is divisible by 3 for display as they should be a point cloud of 3-D points.") - raise(e) + raise ValueError("Passed values to stick_show need to have a dimension which is divisible by 3 for display as they should be a point cloud of 3-D points.") from e class skeleton_show(mocap_data_show): From 5fb4aeb688ad265dc464d993c71b8f9d60b098ee Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 24 May 2021 09:15:00 +0100 Subject: [PATCH 125/137] Start integration of flake8 errors into examples --- GPy/examples/classification.py | 34 +++--- GPy/examples/non_gaussian.py | 10 +- GPy/examples/regression.py | 190 +++++++++++++++++---------------- 3 files changed, 118 insertions(+), 116 deletions(-) diff --git a/GPy/examples/classification.py b/GPy/examples/classification.py index ce3bd6d8..3f3eb447 100644 --- a/GPy/examples/classification.py +++ b/GPy/examples/classification.py @@ -3,6 +3,11 @@ """ Gaussian Processes classification examples """ +try: + import matplotlib.pyplot as plt +except ImportError: + MPL_AVAILABLE = False + import GPy default_seed = 10000 @@ -78,9 +83,7 @@ def toy_linear_1d_classification(seed=default_seed, optimize=True, plot=True): # m.pseudo_EM() # Plot - if plot: - from matplotlib import pyplot as plt - + if MPL_AVAILABLE and plot: fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -117,15 +120,12 @@ def toy_linear_1d_classification_laplace(seed=default_seed, optimize=True, plot= # Optimize if optimize: - try: - m.optimize("scg", messages=1) - except Exception as e: - return m + m.optimize("scg", messages=True) + + return m # Plot - if plot: - from matplotlib import pyplot as plt - + if MPL_AVAILABLE and plot: fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -162,9 +162,7 @@ def sparse_toy_linear_1d_classification( m.optimize() # Plot - if plot: - from matplotlib import pyplot as plt - + if MPL_AVAILABLE and plot: fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -207,9 +205,7 @@ def sparse_toy_linear_1d_classification_uncertain_input( m.optimize() # Plot - if plot: - from matplotlib import pyplot as plt - + if MPL_AVAILABLE and plot: fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -259,9 +255,7 @@ def toy_heaviside(seed=default_seed, max_iters=100, optimize=True, plot=True): print(m) # Plot - if plot: - from matplotlib import pyplot as plt - + if MPL_AVAILABLE and plot: fig, axes = plt.subplots(2, 1) m.plot_f(ax=axes[0]) m.plot(ax=axes[1]) @@ -314,7 +308,7 @@ def crescent_data( if optimize: m.optimize(messages=1) - if plot: + if MPL_AVAILABLE and plot: m.plot() print(m) diff --git a/GPy/examples/non_gaussian.py b/GPy/examples/non_gaussian.py index cb86c83c..c685c4db 100644 --- a/GPy/examples/non_gaussian.py +++ b/GPy/examples/non_gaussian.py @@ -7,8 +7,8 @@ from GPy.util import datasets try: import matplotlib.pyplot as plt -except: - pass +except ImportError: + MPL_AVAILABLE = False def student_t_approx(optimize=True, plot=True): @@ -102,7 +102,7 @@ def student_t_approx(optimize=True, plot=True): print("Corrupt student t") m4.optimize(optimizer, messages=1) - if plot: + if MPL_AVAILABLE and plot: plt.figure(1) plt.suptitle("Gaussian likelihood") ax = plt.subplot(211) @@ -251,7 +251,7 @@ def boston_example(optimize=True, plot=True): print(pred_density) print(mstu_t) - if plot: + if MPL_AVAILABLE and plot: plt.figure() plt.scatter(X_test[:, data_axis_plot], Y_test_pred[0]) plt.scatter(X_test[:, data_axis_plot], Y_test, c="r", marker="x") @@ -270,7 +270,7 @@ def boston_example(optimize=True, plot=True): print("Average scores: {}".format(np.mean(score_folds, 1))) print("Average pred density: {}".format(np.mean(pred_density, 1))) - if plot: + if MPL_AVAILABLE and plot: # Plotting stu_t_legends = ["Student T, df={}".format(df) for df in degrees_freedoms] legends = ["Baseline", "Gaussian", "Laplace Approx Gaussian"] + stu_t_legends diff --git a/GPy/examples/regression.py b/GPy/examples/regression.py index 9ade6552..fb1c9323 100644 --- a/GPy/examples/regression.py +++ b/GPy/examples/regression.py @@ -5,9 +5,10 @@ Gaussian Processes regression examples """ try: - from matplotlib import pyplot as pb -except: - pass + import matplotlib.pyplot as plt +except ImportError: + MPL_AVAILABLE = False + import numpy as np import GPy @@ -29,7 +30,7 @@ def olympic_marathon_men(optimize=True, plot=True): if optimize: m.optimize("bfgs", max_iters=200) - if plot: + if MPL_AVAILABLE and plot: m.plot(plot_limits=(1850, 2050)) return m @@ -52,7 +53,7 @@ def coregionalization_toy(optimize=True, plot=True): if optimize: m.optimize("bfgs", max_iters=100) - if plot: + if MPL_AVAILABLE and plot: slices = GPy.util.multioutput.get_slices([X1, X2]) m.plot( fixed_inputs=[(1, 0)], @@ -63,15 +64,14 @@ def coregionalization_toy(optimize=True, plot=True): fixed_inputs=[(1, 1)], which_data_rows=slices[1], Y_metadata={"output_index": 1}, - ax=pb.gca(), + ax=plt.gca(), ) return m def coregionalization_sparse(optimize=True, plot=True): - """ - A simple demonstration of coregionalization on two sinusoidal functions using sparse approximations. - """ + """A simple demonstration of coregionalization on two sinusoidal + functions using sparse approximations. """ # build a design matrix with a column of integers indicating the output X1 = np.random.rand(50, 1) * 8 X2 = np.random.rand(30, 1) * 5 @@ -85,7 +85,7 @@ def coregionalization_sparse(optimize=True, plot=True): if optimize: m.optimize("bfgs", max_iters=100) - if plot: + if MPL_AVAILABLE and plot: slices = GPy.util.multioutput.get_slices([X1, X2]) m.plot( fixed_inputs=[(1, 0)], @@ -96,9 +96,9 @@ def coregionalization_sparse(optimize=True, plot=True): fixed_inputs=[(1, 1)], which_data_rows=slices[1], Y_metadata={"output_index": 1}, - ax=pb.gca(), + ax=plt.gca(), ) - pb.ylim(-3,) + plt.ylim(-3,) return m @@ -187,11 +187,11 @@ def multiple_optima( lls = GPy.examples.regression._contour_data( data, length_scales, log_SNRs, GPy.kern.RBF ) - if plot: - pb.contour(length_scales, log_SNRs, np.exp(lls), 20, cmap=pb.cm.jet) - ax = pb.gca() - pb.xlabel("length scale") - pb.ylabel("log_10 SNR") + if MPL_AVAILABLE and plot: + plt.contour(length_scales, log_SNRs, np.exp(lls), 20, cmap=plt.cm.jet) + ax = plt.gca() + plt.xlabel("length scale") + plt.ylabel("log_10 SNR") xlim = ax.get_xlim() ylim = ax.get_ylim() @@ -202,7 +202,9 @@ def multiple_optima( optim_point_y = np.empty(2) np.random.seed(seed=seed) for i in range(0, model_restarts): - # kern = GPy.kern.RBF(1, variance=np.random.exponential(1.), lengthscale=np.random.exponential(50.)) + # kern = GPy.kern.RBF( + # 1, variance=np.random.exponential(1.), lengthscale=np.random.exponential(50.) + # ) kern = GPy.kern.RBF( 1, variance=np.random.uniform(1e-3, 1), lengthscale=np.random.uniform(5, 50) ) @@ -219,8 +221,8 @@ def multiple_optima( optim_point_x[1] = m.rbf.lengthscale optim_point_y[1] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance) - if plot: - pb.arrow( + if MPL_AVAILABLE and plot: + plt.arrow( optim_point_x[0], optim_point_y[0], optim_point_x[1] - optim_point_x[0], @@ -233,7 +235,7 @@ def multiple_optima( ) models.append(m) - if plot: + if MPL_AVAILABLE and plot: ax.set_xlim(xlim) ax.set_ylim(ylim) return m # (models, lls) @@ -289,7 +291,7 @@ def olympic_100m_men(optimize=True, plot=True): if optimize: m.optimize("bfgs", max_iters=200) - if plot: + if MPL_AVAILABLE and plot: m.plot(plot_limits=(1850, 2050)) return m @@ -308,14 +310,16 @@ def toy_rbf_1d(optimize=True, plot=True): if optimize: m.optimize("bfgs") - if plot: + if MPL_AVAILABLE and plot: m.plot() return m def toy_rbf_1d_50(optimize=True, plot=True): - """Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance.""" + """Run a simple demonstration of a standard Gaussian process fitting +it to data sampled from an RBF covariance.""" + try: import pods except ImportError: @@ -328,7 +332,7 @@ def toy_rbf_1d_50(optimize=True, plot=True): if optimize: m.optimize("bfgs") - if plot: + if MPL_AVAILABLE and plot: m.plot() return m @@ -353,10 +357,10 @@ def toy_poisson_rbf_1d_laplace(optimize=True, plot=True): if optimize: m.optimize(optimizer) - if plot: + if MPL_AVAILABLE and plot: m.plot() # plot the real underlying rate function - pb.plot(X, np.exp(f_true), "--k", linewidth=2) + plt.plot(X, np.exp(f_true), "--k", linewidth=2) return m @@ -396,7 +400,7 @@ def toy_ARD( if optimize: m.optimize(optimizer="scg", max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.kern.plot_ARD() return m @@ -438,7 +442,7 @@ def toy_ARD_sparse( if optimize: m.optimize(optimizer="scg", max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.kern.plot_ARD() return m @@ -461,12 +465,12 @@ def robot_wireless(max_iters=100, kernel=None, optimize=True, plot=True): m.optimize(max_iters=max_iters) Xpredict = m.predict(data["Ytest"])[0] - if plot: - pb.plot(data["Xtest"][:, 0], data["Xtest"][:, 1], "r-") - pb.plot(Xpredict[:, 0], Xpredict[:, 1], "b-") - pb.axis("equal") - pb.title("WiFi Localization with Gaussian Processes") - pb.legend(("True Location", "Predicted Location")) + if MPL_AVAILABLE and plot: + plt.plot(data["Xtest"][:, 0], data["Xtest"][:, 1], "r-") + plt.plot(Xpredict[:, 0], Xpredict[:, 1], "b-") + plt.axis("equal") + plt.title("WiFi Localization with Gaussian Processes") + plt.legend(("True Location", "Predicted Location")) sse = ((data["Xtest"] - Xpredict) ** 2).sum() @@ -517,7 +521,7 @@ def sparse_GP_regression_1D( if optimize: m.optimize("tnc", max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.plot() return m @@ -550,7 +554,7 @@ def sparse_GP_regression_2D( m.optimize("tnc", messages=1, max_iters=max_iters) # plot - if plot: + if MPL_AVAILABLE and plot: m.plot() print(m) @@ -559,7 +563,8 @@ def sparse_GP_regression_2D( def uncertain_inputs_sparse_regression(max_iters=200, optimize=True, plot=True): """Run a 1D example of a sparse GP regression with uncertain inputs.""" - fig, axes = pb.subplots(1, 2, figsize=(12, 5), sharex=True, sharey=True) + if MPL_AVAILABLE and plot: + fig, axes = plt.subplots(1, 2, figsize=(12, 5), sharex=True, sharey=True) # sample inputs and outputs S = np.ones((20, 1)) @@ -575,7 +580,7 @@ def uncertain_inputs_sparse_regression(max_iters=200, optimize=True, plot=True): if optimize: m.optimize("scg", messages=1, max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.plot(ax=axes[0]) axes[0].set_title("no input uncertainty") print(m) @@ -584,7 +589,7 @@ def uncertain_inputs_sparse_regression(max_iters=200, optimize=True, plot=True): m = GPy.models.SparseGPRegression(X, Y, kernel=GPy.kern.RBF(1), Z=Z, X_variance=S) if optimize: m.optimize("scg", messages=1, max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.plot(ax=axes[1]) axes[1].set_title("with input uncertainty") fig.canvas.draw() @@ -610,7 +615,7 @@ def simple_mean_function(max_iters=100, optimize=True, plot=True): m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf) if optimize: m.optimize(max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.plot(plot_limits=(-10, 15)) return m @@ -633,12 +638,12 @@ def parametric_mean_function(max_iters=100, optimize=True, plot=True): m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf) if optimize: m.optimize(max_iters=max_iters) - if plot: + if MPL_AVAILABLE and plot: m.plot() return m -def warped_gp_cubic_sine(max_iters=100): +def warped_gp_cubic_sine(max_iters=100, plot=True): """ A test replicating the cubic sine regression problem from Snelson's paper. @@ -652,7 +657,7 @@ def warped_gp_cubic_sine(max_iters=100): warp_k = GPy.kern.RBF(1) warp_f = GPy.util.warping_functions.TanhFunction(n_terms=2) warp_m = GPy.models.WarpedGP(X, Y, kernel=warp_k, warping_function=warp_f) - warp_m[".*\.d"].constrain_fixed(1.0) + warp_m[".*\\.d"].constrain_fixed(1.0) m = GPy.models.GPRegression(X, Y) m.optimize_restarts( parallel=False, robust=True, num_restarts=5, max_iters=max_iters @@ -666,35 +671,18 @@ def warped_gp_cubic_sine(max_iters=100): print(warp_m) print(warp_m[".*warp.*"]) - warp_m.predict_in_warped_space = False - warp_m.plot(title="Warped GP - Latent space") - warp_m.predict_in_warped_space = True - warp_m.plot(title="Warped GP - Warped space") - m.plot(title="Standard GP") - warp_m.plot_warping() - pb.show() + if MPL_AVAILABLE and plot: + warp_m.predict_in_warped_space = False + warp_m.plot(title="Warped GP - Latent space") + warp_m.predict_in_warped_space = True + warp_m.plot(title="Warped GP - Warped space") + m.plot(title="Standard GP") + warp_m.plot_warping() + plt.show() return warp_m -def multioutput_gp_with_derivative_observations(): - def plot_gp_vs_real( - m, x, yreal, size_inputs, title, fixed_input=1, xlim=[0, 11], ylim=[-1.5, 3] - ): - fig, ax = pb.subplots() - ax.set_title(title) - pb.plot(x, yreal, "r", label="Real function") - rows = ( - slice(0, size_inputs[0]) - if fixed_input == 0 - else slice(size_inputs[0], size_inputs[0] + size_inputs[1]) - ) - m.plot( - fixed_inputs=[(1, fixed_input)], - which_data_rows=rows, - xlim=xlim, - ylim=ylim, - ax=ax, - ) +def multioutput_gp_with_derivative_observations(plot=True): f = lambda x: np.sin(x) + 0.1 * (x - 2.0) ** 2 - 0.005 * x ** 3 fd = lambda x: np.cos(x) + 0.2 * (x - 2.0) - 0.015 * x ** 2 @@ -735,27 +723,47 @@ def multioutput_gp_with_derivative_observations(): # Optimize the model m.optimize(messages=0, ipython_notebook=False) - # Plot the model, the syntax is same as for multioutput models: - plot_gp_vs_real( - m, - xpred, - ydpred_true, - [x.shape[0], xd.shape[0]], - title="Latent function derivatives", - fixed_input=1, - xlim=[0, 11], - ylim=[-1.5, 3], - ) - plot_gp_vs_real( - m, - xpred, - ypred_true, - [x.shape[0], xd.shape[0]], - title="Latent function", - fixed_input=0, - xlim=[0, 11], - ylim=[-1.5, 3], - ) + if MPL_AVAILABLE and plot: + def plot_gp_vs_real( + m, x, yreal, size_inputs, title, fixed_input=1, xlim=[0, 11], ylim=[-1.5, 3] + ): + fig, ax = plt.subplots() + ax.set_title(title) + plt.plot(x, yreal, "r", label="Real function") + rows = ( + slice(0, size_inputs[0]) + if fixed_input == 0 + else slice(size_inputs[0], size_inputs[0] + size_inputs[1]) + ) + m.plot( + fixed_inputs=[(1, fixed_input)], + which_data_rows=rows, + xlim=xlim, + ylim=ylim, + ax=ax, + ) + + # Plot the model, the syntax is same as for multioutput models: + plot_gp_vs_real( + m, + xpred, + ydpred_true, + [x.shape[0], xd.shape[0]], + title="Latent function derivatives", + fixed_input=1, + xlim=[0, 11], + ylim=[-1.5, 3], + ) + plot_gp_vs_real( + m, + xpred, + ypred_true, + [x.shape[0], xd.shape[0]], + title="Latent function", + fixed_input=0, + xlim=[0, 11], + ylim=[-1.5, 3], + ) # making predictions for the values: mu, var = m.predict_noiseless(Xnew=[xpred, np.empty((0, 1))]) From b174b58b79403185615f74586569f661841df316 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 24 May 2021 09:19:45 +0100 Subject: [PATCH 126/137] Fix MPL_AVAILABLE error. --- GPy/examples/classification.py | 1 + GPy/examples/non_gaussian.py | 9 +++++++-- GPy/examples/regression.py | 1 + 3 files changed, 9 insertions(+), 2 deletions(-) diff --git a/GPy/examples/classification.py b/GPy/examples/classification.py index 3f3eb447..1c5318e5 100644 --- a/GPy/examples/classification.py +++ b/GPy/examples/classification.py @@ -3,6 +3,7 @@ """ Gaussian Processes classification examples """ +MPL_AVAILABLE = True try: import matplotlib.pyplot as plt except ImportError: diff --git a/GPy/examples/non_gaussian.py b/GPy/examples/non_gaussian.py index c685c4db..a9ee34d9 100644 --- a/GPy/examples/non_gaussian.py +++ b/GPy/examples/non_gaussian.py @@ -3,8 +3,8 @@ import GPy import numpy as np -from GPy.util import datasets +MPL_AVAILABLE = True try: import matplotlib.pyplot as plt except ImportError: @@ -141,7 +141,12 @@ def boston_example(optimize=True, plot=True): optimizer = "bfgs" messages = 0 - data = datasets.boston_housing() + try: + import pods + except ImportError: + print("pods unavailable, see https://github.com/sods/ods for example datasets") + return + data = pods.datasets.boston_housing() degrees_freedoms = [3, 5, 8, 10] X = data["X"].copy() Y = data["Y"].copy() diff --git a/GPy/examples/regression.py b/GPy/examples/regression.py index fb1c9323..9c6b68ab 100644 --- a/GPy/examples/regression.py +++ b/GPy/examples/regression.py @@ -4,6 +4,7 @@ """ Gaussian Processes regression examples """ +MPL_AVAILABLE = True try: import matplotlib.pyplot as plt except ImportError: From 62d735e6a659f356c381fb45dce53e26e7b84338 Mon Sep 17 00:00:00 2001 From: Eric Kalosa-Kenyon Date: Wed, 26 May 2021 17:37:55 -0700 Subject: [PATCH 127/137] Fix GPy.priors.InverseGamma (#903) * fixed InverseGamma prior: beforehand, it was a child class of Gamma but it defined a broken __new__ method of its own. Now, it just inherits Gamma's __new__; also added a test that ensures the InverseGamma can be instantiated and integrated into a GPy model * overwrote misleading inherited methods in InverseGamma, deleted unnecessary repeated code --- GPy/core/parameterization/priors.py | 22 +++++++--------------- GPy/testing/prior_tests.py | 15 +++++++++++++++ 2 files changed, 22 insertions(+), 15 deletions(-) diff --git a/GPy/core/parameterization/priors.py b/GPy/core/parameterization/priors.py index 6269436b..c4dfbc2a 100644 --- a/GPy/core/parameterization/priors.py +++ b/GPy/core/parameterization/priors.py @@ -371,24 +371,17 @@ class InverseGamma(Gamma): """ domain = _POSITIVE _instances = [] - def __new__(cls, a=1, b=.5): # 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().b == b: - return instance() - o = super(Prior, cls).__new__(cls, a, b) - cls._instances.append(weakref.ref(o)) - return cls._instances[-1]() - - def __init__(self, a, b): - self._a = float(a) - self._b = float(b) - self.constant = -gammaln(self.a) + a * np.log(b) def __str__(self): return "iGa({:.2g}, {:.2g})".format(self.a, self.b) + def summary(self): + return {} + + @staticmethod + def from_EV(E, V): + raise NotImplementedError + def lnpdf(self, x): return self.constant - (self.a + 1) * np.log(x) - self.b / x @@ -398,7 +391,6 @@ 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 diff --git a/GPy/testing/prior_tests.py b/GPy/testing/prior_tests.py index 377ae504..83dfd0d6 100644 --- a/GPy/testing/prior_tests.py +++ b/GPy/testing/prior_tests.py @@ -55,6 +55,21 @@ class PriorTests(unittest.TestCase): m.randomize() self.assertTrue(m.checkgrad()) + def test_InverseGamma(self): + # Test that this prior object can be instantiated and performs its basic functions + # in integration. + xmin, xmax = 1, 2.5*np.pi + b, C, SNR = 1, 0, 0.1 + X = np.linspace(xmin, xmax, 500) + y = b*X + C + 1*np.sin(X) + y += 0.05*np.random.randn(len(X)) + X, y = X[:, None], y[:, None] + m = GPy.models.GPRegression(X, y) + InverseGamma = GPy.priors.InverseGamma(1, 1) + m.rbf.set_prior(InverseGamma) + m.randomize() + self.assertTrue(m.checkgrad()) + def test_incompatibility(self): xmin, xmax = 1, 2.5*np.pi b, C, SNR = 1, 0, 0.1 From 4089a662a9e64d3a1fc268a941b690f29a46ef1d Mon Sep 17 00:00:00 2001 From: Tim Gates Date: Fri, 28 May 2021 12:47:48 +1000 Subject: [PATCH 128/137] docs: fix simple typo, symetric -> symmetric (#883) There is a small typo in doc/source/tuto_creating_new_kernels.rst. Should read `symmetric` rather than `symetric`. --- doc/source/tuto_creating_new_kernels.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/tuto_creating_new_kernels.rst b/doc/source/tuto_creating_new_kernels.rst index ec46aedc..9d909c3b 100644 --- a/doc/source/tuto_creating_new_kernels.rst +++ b/doc/source/tuto_creating_new_kernels.rst @@ -7,7 +7,7 @@ We will see in this tutorial how to create new kernels in GPy. We will also give Structure of a kernel in GPy ============================ -In GPy a kernel object is made of a list of kernpart objects, which correspond to symetric positive definite functions. More precisely, the kernel should be understood as the sum of the kernparts. In order to implement a new covariance, the following steps must be followed +In GPy a kernel object is made of a list of kernpart objects, which correspond to symmetric positive definite functions. More precisely, the kernel should be understood as the sum of the kernparts. In order to implement a new covariance, the following steps must be followed 1. implement the new covariance as a :py:class:`GPy.kern.src.kern.Kern` object 2. update the :py:mod:`GPy.kern.src` file From 3e19a85575687e37fd6f61174115d7c94d2c96e6 Mon Sep 17 00:00:00 2001 From: Tao Cui Date: Tue, 8 Jun 2021 12:28:37 +1000 Subject: [PATCH 129/137] Update priors_plots.py (#929) Change pb.hist(rvs, 100, normed=True) to pb.hist(rvs, 100, density=True) in file priors_plots.py. --- GPy/plotting/matplot_dep/priors_plots.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/plotting/matplot_dep/priors_plots.py b/GPy/plotting/matplot_dep/priors_plots.py index 51d84f86..c537f5e5 100644 --- a/GPy/plotting/matplot_dep/priors_plots.py +++ b/GPy/plotting/matplot_dep/priors_plots.py @@ -11,7 +11,7 @@ except: def univariate_plot(prior): rvs = prior.rvs(1000) - pb.hist(rvs, 100, normed=True) + pb.hist(rvs, 100, density=True) xmin, xmax = pb.xlim() xx = np.linspace(xmin, xmax, 1000) pb.plot(xx, prior.pdf(xx), 'r', linewidth=2) From bb1bc5088671f9316bc92a46d356734e34c2d5c0 Mon Sep 17 00:00:00 2001 From: gehbiszumeis <16896724+gehbiszumeis@users.noreply.github.com> Date: Thu, 9 Dec 2021 20:14:27 +0100 Subject: [PATCH 130/137] to_dict() and from_dict() functionality for Coregionalize Kernel and MixedNoise Likelihood class, appveyor CI resurrected (#951) This PR adds two main things to GPy: - to- and from-dict functions for the kernels listed belop - a fix for the appveyor CI Please see the squashed commit messages listed below. Authors: @gehbiszumeis @ppk42 respectively Reviewer: @ekalosak --- * new: added to_dict() method to Coregionalize kernel class * new: added to_dict() method to MixedNoise likelihood class * fix: made Y_metadata dict content serializable * fix: typo * added additional needed parameters to to_dict() method for Coregionalize kernel + added _build_from_input dict method * new: added possibility to build MixedNoise likelihood from input_dict * Y_metadata conversion from serializable to np.array when loading from dict * fix: rework Y_metadata part for compatibility with unittests !minor * conda cleanup in appveyors pipeline * conda clean up after conda update * conda clean before conda update * try pinning packages for conda * revert all conda changes * conda clean all (not only packages) * use conda update anaconda * pin conda package * pin conda package * try installing charset-normalizer beforehand * try to get from conda-forge * revert all conda changes * Try to fix the conda update challange. See: https://community.intel.com/t5/Intel-Distribution-for-Python/Conda-update-Conda-fails/td-p/1126174 It is just a try for a different context/(conda version). * Still fixing build error on appveyor I also use a newer miniconda version for greater python versions. * Update appveyor.yml Thinking it over it decided to use miniconda38 for all python versions unless python 3.5. * revert miniconda versioning changes * adjust GPy version in appveyor.yml * 1st attempt bring the appveyor build to life again * #955 fixing ci build on appveyor After bringing the miniconda env to work again, the wrong matplotlib version was used. This commit should fix that. * #955 Fix CI build Freezing numpy and scipy was a bad idea. I freeze matplotlib dependend on the python version only. * add: built_from_dict method for White Kernel Co-authored-by: Peter Paul Kiefer Co-authored-by: Peter Paul Kiefer --- GPy/core/gp.py | 12 ++++++---- GPy/core/parameterization/variational.py | 2 +- GPy/kern/src/coregionalize.py | 25 ++++++++++++++++++++ GPy/kern/src/static.py | 5 ++++ GPy/likelihoods/mixed_noise.py | 29 ++++++++++++++++++++++++ appveyor.yml | 18 ++++++++++----- setup.py | 5 +++- 7 files changed, 84 insertions(+), 12 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 0704c6a6..3cfa38ec 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -134,9 +134,10 @@ class GP(Model): if self.mean_function is not None: input_dict["mean_function"] = self.mean_function.to_dict() input_dict["inference_method"] = self.inference_method.to_dict() - #FIXME: Assumes the Y_metadata is serializable. We should create a Metadata class + # TODO: We should create a Metadata class if self.Y_metadata is not None: - input_dict["Y_metadata"] = self.Y_metadata + # make Y_metadata serializable + input_dict["Y_metadata"] = {k: self.Y_metadata[k].tolist() for k in self.Y_metadata.keys()} if self.normalizer is not None: input_dict["normalizer"] = self.normalizer.to_dict() return input_dict @@ -162,9 +163,12 @@ class GP(Model): input_dict["mean_function"] = mean_function input_dict["inference_method"] = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(input_dict["inference_method"]) - #FIXME: Assumes the Y_metadata is serializable. We should create a Metadata class + # converts Y_metadata from serializable to array. We should create a Metadata class Y_metadata = input_dict.get("Y_metadata") - input_dict["Y_metadata"] = Y_metadata + if isinstance(Y_metadata, dict): + input_dict["Y_metadata"] = {k: np.array(Y_metadata[k]) for k in Y_metadata.keys()} + else: + input_dict["Y_metadata"] = Y_metadata normalizer = input_dict.get("normalizer") if normalizer is not None: diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index 1dbd205b..911c5b3e 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -106,7 +106,7 @@ class VariationalPosterior(Parameterized): self.link_parameters(self.mean, self.variance) self.num_data, self.input_dim = self.mean.shape if self.has_uncertain_inputs(): - assert self.variance.shape == self.mean.shape, "need one variance per sample and dimenion" + assert self.variance.shape == self.mean.shape, "need one variance per sample and dimension" def set_gradients(self, grad): self.mean.gradient, self.variance.gradient = grad diff --git a/GPy/kern/src/coregionalize.py b/GPy/kern/src/coregionalize.py index d5111c3b..d05f5c6a 100644 --- a/GPy/kern/src/coregionalize.py +++ b/GPy/kern/src/coregionalize.py @@ -134,3 +134,28 @@ class Coregionalize(Kern): def gradients_X_diag(self, dL_dKdiag, X): return np.zeros(X.shape) + + def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Coregionalize, self)._save_to_input_dict() + input_dict["class"] = "GPy.kern.Coregionalize" + # W and kappa must be serializable + input_dict["W"] = self.W.values.tolist() + input_dict["kappa"] = self.kappa.values.tolist() + input_dict["output_dim"] = self.output_dim + return input_dict + + @staticmethod + def _build_from_input_dict(kernel_class, input_dict): + useGPU = input_dict.pop('useGPU', None) + # W and kappa must be converted back to numpy arrays + input_dict['W'] = np.array(input_dict['W']) + input_dict['kappa'] = np.array(input_dict['kappa']) + return Coregionalize(**input_dict) diff --git a/GPy/kern/src/static.py b/GPy/kern/src/static.py index e0251337..a854fe41 100644 --- a/GPy/kern/src/static.py +++ b/GPy/kern/src/static.py @@ -68,6 +68,11 @@ class White(Static): input_dict = super(White, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.White" return input_dict + + @staticmethod + def _build_from_input_dict(kernel_class, input_dict): + useGPU = input_dict.pop('useGPU', None) + return White(**input_dict) def K(self, X, X2=None): if X2 is None: diff --git a/GPy/likelihoods/mixed_noise.py b/GPy/likelihoods/mixed_noise.py index db230b13..50289e44 100644 --- a/GPy/likelihoods/mixed_noise.py +++ b/GPy/likelihoods/mixed_noise.py @@ -80,3 +80,32 @@ class MixedNoise(Likelihood): _ysim = np.array([np.random.normal(lik.gp_link.transf(gpj), scale=np.sqrt(lik.variance), size=1) for gpj in gp_filtered.flatten()]) Ysim[flt,:] = _ysim.reshape(n1,N2) return Ysim + + def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + # input_dict = super(MixedNoise, self)._save_to_input_dict() + input_dict = {"name": self.name, + "class": "GPy.likelihoods.MixedNoise", + "likelihoods_list": []} + for ii in range(len(self.likelihoods_list)): + input_dict["likelihoods_list"].append(self.likelihoods_list[ii].to_dict()) + + return input_dict + + @staticmethod + def _build_from_input_dict(likelihood_class, input_dict): + import copy + input_dict = copy.deepcopy(input_dict) + # gp_link_dict = input_dict.pop('gp_link_dict') + # import GPy + # gp_link = GPy.likelihoods.link_functions.GPTransformation.from_dict(gp_link_dict) + # input_dict["gp_link"] = gp_link + input_dict['likelihoods_list'] = [Likelihood.from_dict(l) for l in input_dict['likelihoods_list']] + return likelihood_class(**input_dict) diff --git a/appveyor.yml b/appveyor.yml index f5faee5c..9cfad489 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -3,18 +3,23 @@ environment: secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00= COVERALLS_REPO_TOKEN: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS - gpy_version: 1.9.9 + gpy_version: 1.10.0 matrix: - PYTHON_VERSION: 3.5 MINICONDA: C:\Miniconda35-x64 + MPL_VERSION: 3.0.0 - PYTHON_VERSION: 3.6 - MINICONDA: C:\Miniconda36-x64 + MINICONDA: C:\Miniconda3-x64 + MPL_VERSION: 3.3.4 - PYTHON_VERSION: 3.7 - MINICONDA: C:\Miniconda36-x64 + MINICONDA: C:\Miniconda3-x64 + MPL_VERSION: 3.3.4 - PYTHON_VERSION: 3.8 - MINICONDA: C:\Miniconda36-x64 + MINICONDA: C:\Miniconda3-x64 + MPL_VERSION: 3.3.4 - PYTHON_VERSION: 3.9 - MINICONDA: C:\Miniconda36-x64 + MINICONDA: C:\Miniconda3-x64 + MPL_VERSION: 3.3.4 #configuration: # - Debug @@ -25,7 +30,8 @@ install: - conda config --set always_yes yes --set changeps1 no - conda update -q conda - conda info -a - - "conda create -q -n build-environment python=%PYTHON_VERSION% numpy scipy matplotlib" +# github issue #955: freeze build version of matplotlib + - "conda create -q -n build-environment python=%PYTHON_VERSION% numpy scipy matplotlib=%MPL_VERSION%" - activate build-environment # We need wheel installed to build wheels - python -m pip install wheel diff --git a/setup.py b/setup.py index 73bfc035..b79a0d12 100644 --- a/setup.py +++ b/setup.py @@ -118,8 +118,10 @@ except ModuleNotFoundError: ext_mods = [] install_requirements = ['numpy>=1.7', 'six', 'paramz>=0.9.0', 'cython>=0.29'] +matplotlib_version = 'matplotlib==3.3.4' if sys.version_info < (3, 6): install_requirements += ['scipy>=1.3.0,<1.5.0'] + matplotlib_version = 'matplotlib==3.0.0' else: install_requirements += ['scipy>=1.3.0'] @@ -174,7 +176,8 @@ setup(name = 'GPy', 'optional':['mpi4py', 'ipython>=4.0.0', ], - 'plotting':['matplotlib >= 3.0', + #matplotlib Version see github issue #955 + 'plotting':[matplotlib_version, 'plotly >= 1.8.6'], 'notebook':['jupyter_client >= 4.0.6', 'ipywidgets >= 4.0.3', From 0a9893e839f3c2a06831162fc9f0ee0793bb296d Mon Sep 17 00:00:00 2001 From: Yixin Lin <1heart@users.noreply.github.com> Date: Sun, 17 Apr 2022 12:25:17 -0400 Subject: [PATCH 131/137] Fix rank>0 thread exiting during SparseGP multiprocessing (#731) If you run mpiexec -n 2 on any code to try to use MPI multiprocessing for SparseGPRegression, it crashes (see #618) because the rank>1 processes do not have ret defined. --- GPy/core/sparse_gp_mpi.py | 1 + 1 file changed, 1 insertion(+) diff --git a/GPy/core/sparse_gp_mpi.py b/GPy/core/sparse_gp_mpi.py index d9c29a2f..d747ac83 100644 --- a/GPy/core/sparse_gp_mpi.py +++ b/GPy/core/sparse_gp_mpi.py @@ -108,6 +108,7 @@ class SparseGP_MPI(SparseGP): raise self._fail_count += 1 elif flag==-1: + ret = None break else: self._IN_OPTIMIZATION_ = False From f63ed48b0d4bf043868a0a1729d28003c13fe263 Mon Sep 17 00:00:00 2001 From: Noam Finkelstein <2919482+nsfinkelstein@users.noreply.github.com> Date: Sun, 17 Apr 2022 12:28:05 -0400 Subject: [PATCH 132/137] Add error message for excess inducing points (#746) The number of inducing points in the latent space defaults to 10, which creates an error if there are fewer than 10 conditions (i.e. output dimension is less than 10). Currently this error shows up somewhat opaquely. This fix makes the error explicit, which may save time for future developers. The current error shown is: ``` ~/code/anaconda/lib/python3.6/site-packages/GPy/inference/latent_function_inference/vardtc_svi_multiout_miss.py in inference_d(self, d, beta, Y, indexD, grad_dict, mid_res, uncertain_inputs_r, uncertain_inputs_c, Mr, Mc) 82 LcInvPsi1_cT = dtrtrs(Lc, psi1_c.T)[0] 83 LrInvPsi1_rT = dtrtrs(Lr, psi1_r.T)[0] ---> 84 85 tr_LrInvPsi2_rLrInvT_LrInvSrLrInvT = (LrInvPsi2_rLrInvT*LrInvSrLrInvT).sum() 86 tr_LcInvPsi2_cLcInvT_LcInvScLcInvT = (LcInvPsi2_cLcInvT*LcInvScLcInvT).sum() ValueError: operands could not be broadcast together with shapes (5,5) (6,6) ``` --- GPy/models/gp_multiout_regression_md.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/GPy/models/gp_multiout_regression_md.py b/GPy/models/gp_multiout_regression_md.py index 292f525d..917fa4b7 100644 --- a/GPy/models/gp_multiout_regression_md.py +++ b/GPy/models/gp_multiout_regression_md.py @@ -72,6 +72,10 @@ class GPMultioutRegressionMD(SparseGP): kernel = kern.RBF(X.shape[1]) if kernel_row is None: kernel_row = kern.RBF(Xr_dim,name='kern_row') + + if num_inducing[1] > self.output_dim: + msg = 'Number of inducing points ({}) in latent space must be <= output dim ({})' + raise ValueError(msg.format(num_inducing[1], self.output_dim)) if init=='GP': from . import SparseGPRegression, BayesianGPLVM From 3c3ec60dea0941d898c34f86c767e8ced6a000ca Mon Sep 17 00:00:00 2001 From: Martin Bubel <37817171+MartinBubel@users.noreply.github.com> Date: Fri, 21 Apr 2023 18:32:33 +0200 Subject: [PATCH 133/137] Fix issues encountered in modern python versions (#1011) * Update setup.py remove special handling of scipy dependencies for old python versions * Update __init__.py replace numpy type by native type * replace np.bool by bool --- GPy/core/__init__.py | 2 +- GPy/inference/mcmc/samplers.py | 2 +- GPy/plotting/matplot_dep/base_plots.py | 4 ++-- GPy/plotting/matplot_dep/plot_definitions.py | 4 ++-- setup.py | 6 +----- 5 files changed, 7 insertions(+), 11 deletions(-) diff --git a/GPy/core/__init__.py b/GPy/core/__init__.py index 08659add..5219de24 100644 --- a/GPy/core/__init__.py +++ b/GPy/core/__init__.py @@ -77,7 +77,7 @@ def randomize(self, rand_gen=None, *args, **kwargs): # now draw from prior where possible x = self.param_array.copy() [np.put(x, ind, p.rvs(ind.size)) for p, ind in self.priors.items() if not p is None] - unfixlist = np.ones((self.size,),dtype=np.bool) + unfixlist = np.ones((self.size,),dtype=bool) from paramz.transformations import __fixed__ unfixlist[self.constraints[__fixed__]] = False self.param_array.flat[unfixlist] = x.view(np.ndarray).ravel()[unfixlist] diff --git a/GPy/inference/mcmc/samplers.py b/GPy/inference/mcmc/samplers.py index d2f11a49..684afe37 100644 --- a/GPy/inference/mcmc/samplers.py +++ b/GPy/inference/mcmc/samplers.py @@ -38,7 +38,7 @@ class Metropolis_Hastings(object): 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() - accepted = np.zeros(Ntotal,dtype=np.bool) + accepted = np.zeros(Ntotal,dtype=bool) for it in range(Ntotal): print("sample %d of %d\r"%(it+1,Ntotal),end="") sys.stdout.flush() diff --git a/GPy/plotting/matplot_dep/base_plots.py b/GPy/plotting/matplot_dep/base_plots.py index 567f869b..e43f8efa 100644 --- a/GPy/plotting/matplot_dep/base_plots.py +++ b/GPy/plotting/matplot_dep/base_plots.py @@ -82,9 +82,9 @@ def gradient_fill(x, percentiles, ax=None, fignum=None, **kwargs): y2 = np.ones_like(x) * y2 if where is None: - where = np.ones(len(x), np.bool) + where = np.ones(len(x), bool) else: - where = np.asarray(where, np.bool) + where = np.asarray(where, bool) if not (x.shape == y1.shape == y2.shape == where.shape): raise ValueError("Argument dimensions are incompatible") diff --git a/GPy/plotting/matplot_dep/plot_definitions.py b/GPy/plotting/matplot_dep/plot_definitions.py index 34f32ac5..7fadbf67 100644 --- a/GPy/plotting/matplot_dep/plot_definitions.py +++ b/GPy/plotting/matplot_dep/plot_definitions.py @@ -255,9 +255,9 @@ class MatplotlibPlots(AbstractPlottingLibrary): y2 = np.ones_like(x) * y2 if where is None: - where = np.ones(len(x), np.bool) + where = np.ones(len(x), bool) else: - where = np.asarray(where, np.bool) + where = np.asarray(where, bool) if not (x.shape == y1.shape == y2.shape == where.shape): raise ValueError("Argument dimensions are incompatible") diff --git a/setup.py b/setup.py index b79a0d12..4d3ea00a 100644 --- a/setup.py +++ b/setup.py @@ -119,11 +119,7 @@ except ModuleNotFoundError: install_requirements = ['numpy>=1.7', 'six', 'paramz>=0.9.0', 'cython>=0.29'] matplotlib_version = 'matplotlib==3.3.4' -if sys.version_info < (3, 6): - install_requirements += ['scipy>=1.3.0,<1.5.0'] - matplotlib_version = 'matplotlib==3.0.0' -else: - install_requirements += ['scipy>=1.3.0'] +install_requirements += ['scipy>=1.3.0'] setup(name = 'GPy', version = __version__, From 8ddd14c75fbf14edccd41aa29933af107efc2957 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Fri, 21 Apr 2023 17:39:13 +0100 Subject: [PATCH 134/137] Bump the version --- GPy/__version__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/__version__.py b/GPy/__version__.py index fcfdf383..b518f6ee 100644 --- a/GPy/__version__.py +++ b/GPy/__version__.py @@ -1 +1 @@ -__version__ = "1.10.0" +__version__ = "1.12.0" From 159695944ae067851722b3a2608982dcbf0a9bd2 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Fri, 21 Apr 2023 17:46:25 +0100 Subject: [PATCH 135/137] bump the version --- setup.cfg | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.cfg b/setup.cfg index 913a7c55..d66b5eea 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.9.9 +current_version = 1.12.0 tag = True commit = True From 54d87b3b5e34f69a1442d4043bdf26bbb704f393 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Fri, 28 Apr 2023 09:41:43 +0100 Subject: [PATCH 136/137] Drop the Python 3.5 from the test env --- appveyor.yml | 3 --- 1 file changed, 3 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index 667ab99d..7db6a95a 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -5,9 +5,6 @@ environment: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS gpy_version: 1.12.0 matrix: - - PYTHON_VERSION: 3.5 - MINICONDA: C:\Miniconda35-x64 - MPL_VERSION: 3.0.0 - PYTHON_VERSION: 3.6 MINICONDA: C:\Miniconda3-x64 MPL_VERSION: 3.3.4 From 9ec3e50e3b96a10db58175a206ed998ec5a8e3e3 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Fri, 28 Apr 2023 09:42:20 +0100 Subject: [PATCH 137/137] Drop the Python 3.5 from the test env --- .travis.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index f2fc73f0..7fa2e442 100644 --- a/.travis.yml +++ b/.travis.yml @@ -16,7 +16,6 @@ addons: # - "$HOME/install/" env: - - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 - PYTHON_VERSION=3.7 - PYTHON_VERSION=3.8