apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-27 14:25:16 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

[plotting] was failing on some 3 dimensional plots (latent)

Browse source
This commit is contained in:
Max Zwiessele 2016-01-11 16:13:13 +00:00
parent 82f888f89c
commit d8b5a72ea8
3 changed files with 51 additions and 53 deletions
Download patch file Download diff file Expand all files Collapse all files

32
GPy/plotting/gpy_plot/latent_plots.py
View file

@ -50,6 +50,19 @@ def _wait_for_updates(view, updates):
# No updateable view:
pass
def _new_canvas(self, projection, kwargs, which_indices):
input_1, input_2, input_3 = sig_dims = self.get_most_significant_input_dimensions(which_indices)
if input_3 is None:
zlabel = None
else:
zlabel = 'latent dimension %i' % input_3
if 'color' not in kwargs:
kwargs['color'] = 'white'
canvas, kwargs = pl().new_canvas(projection=projection, xlabel='latent dimension %i' % input_1,
ylabel='latent dimension %i' % input_2,
zlabel=zlabel, **kwargs)
return canvas, projection, kwargs, sig_dims
def _plot_latent_scatter(canvas, X, visible_dims, labels, marker, num_samples, projection='2d', **kwargs):
from .. import Tango
@ -85,12 +98,8 @@ def plot_latent_scatter(self, labels=None,
:param str marker: markers to use - cycle if more labels then markers are given
:param kwargs: the kwargs for the scatter plots
"""
input_1, input_2, input_3 = sig_dims = self.get_most_significant_input_dimensions(which_indices)
canvas, projection, kwargs, sig_dims = _new_canvas(self, projection, kwargs, which_indices)
canvas, kwargs = pl().new_canvas(projection=projection,
xlabel='latent dimension %i' % input_1,
ylabel='latent dimension %i' % input_2,
zlabel='latent dimension %i' % input_3, **kwargs)
X, _, _ = get_x_y_var(self)
if labels is None:
labels = np.ones(self.num_data)
@ -101,8 +110,6 @@ def plot_latent_scatter(self, labels=None,
return pl().add_to_canvas(canvas, dict(scatter=scatters), legend=legend)
def plot_latent_inducing(self,
which_indices=None,
legend=False,
@ -122,17 +129,8 @@ def plot_latent_inducing(self,
:param str marker: markers to use - cycle if more labels then markers are given
:param kwargs: the kwargs for the scatter plots
"""
input_1, input_2, input_3 = sig_dims = self.get_most_significant_input_dimensions(which_indices)
if input_3 is None: zlabel=None
else: zlabel = 'latent dimension %i' % input_3
canvas, projection, kwargs, sig_dims = _new_canvas(self, projection, kwargs, which_indices)
if 'color' not in kwargs:
kwargs['color'] = 'white'
canvas, kwargs = pl().new_canvas(projection=projection,
xlabel='latent dimension %i' % input_1,
ylabel='latent dimension %i' % input_2,
zlabel=zlabel, **kwargs)
Z = self.Z.values
labels = np.array(['inducing'] * Z.shape[0])
scatters = _plot_latent_scatter(canvas, Z, sig_dims, labels, marker, num_samples, projection=projection, **kwargs)