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[plotting] got the old way in again

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Max Zwiessele 2015-10-16 14:55:04 +01:00
parent 327ed46c6e
commit b236896fbd
4 changed files with 10 additions and 5 deletions
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2
GPy/plotting/__init__.py
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@ -13,6 +13,7 @@ def change_plotting_library(lib):
if lib == 'matplotlib': if lib == 'matplotlib':
import matplotlib import matplotlib
from .matplot_dep.plot_definitions import MatplotlibPlots from .matplot_dep.plot_definitions import MatplotlibPlots
from .matplot_dep import visualize, mapping_plots, priors_plots, ssgplvm, svig_plots, variational_plots, img_plots
current_lib[0] = MatplotlibPlots() current_lib[0] = MatplotlibPlots()
if lib == 'plotly': if lib == 'plotly':
import plotly import plotly
@ -22,6 +23,7 @@ def change_plotting_library(lib):
current_lib[0] = None current_lib[0] = None
#=========================================================================== #===========================================================================
except (ImportError, NameError): except (ImportError, NameError):
raise
config.set('plotting', 'library', 'none') config.set('plotting', 'library', 'none')
import warnings import warnings
warnings.warn(ImportWarning("{} not available, install newest version of {} for plotting".format(lib, lib))) warnings.warn(ImportWarning("{} not available, install newest version of {} for plotting".format(lib, lib)))

5
GPy/plotting/gpy_plot/plot_util.py
View file

@ -285,7 +285,10 @@ def get_x_y_var(model):
else: else:
X = model.X.values X = model.X.values
X_variance = None X_variance = None
Y = model.Y.values try:
Y = model.Y.values
except AttributeError:
Y = model.Y
if sparse.issparse(Y): Y = Y.todense().view(np.ndarray) if sparse.issparse(Y): Y = Y.todense().view(np.ndarray)
return X, X_variance, Y return X, X_variance, Y

2
GPy/plotting/matplot_dep/mapping_plots.py
View file

@ -7,7 +7,6 @@ try:
from matplotlib import pyplot as pb from matplotlib import pyplot as pb
except: except:
pass pass
from .base_plots import x_frame1D, x_frame2D
def plot_mapping(self, plot_limits=None, which_data='all', which_parts='all', resolution=None, levels=20, samples=0, fignum=None, ax=None, fixed_inputs=[], linecol=Tango.colorsHex['darkBlue']): def plot_mapping(self, plot_limits=None, which_data='all', which_parts='all', resolution=None, levels=20, samples=0, fignum=None, ax=None, fixed_inputs=[], linecol=Tango.colorsHex['darkBlue']):
@ -52,6 +51,7 @@ def plot_mapping(self, plot_limits=None, which_data='all', which_parts='all', re
ax = fig.add_subplot(111) ax = fig.add_subplot(111)
plotdims = self.input_dim - len(fixed_inputs) plotdims = self.input_dim - len(fixed_inputs)
from ..gpy_plot.plot_util import x_frame1D, x_frame2D
if plotdims == 1: if plotdims == 1:

2
GPy/plotting/matplot_dep/variational_plots.py
View file

@ -94,7 +94,7 @@ def plot_SpikeSlab(parameterized, fignum=None, ax=None, colors=None, side_by_sid
a.set_xticklabels('') a.set_xticklabels('')
# binary prob plot # binary prob plot
a = fig.add_subplot(*sub2) a = fig.add_subplot(*sub2)
a.bar(x,gamma[:,i],bottom=0.,linewidth=0,width=1.0,align='center') a.bar(x,gamma[:,i],bottom=0.,linewidth=1.,width=1.0,align='center')
a.set_xlim(x.min(), x.max()) a.set_xlim(x.min(), x.max())
a.set_ylim([0.,1.]) a.set_ylim([0.,1.])
pb.draw() pb.draw()