[plotting] tests

GPy/plotting/gpy_plot/data_plots.py

@@ -175,7 +175,7 @@ def _plot_inducing(self, canvas, visible_dims, projection, label, **plot_kwargs)
         visible_dims = [i for i in sig_dims if i is not None]
     free_dims = get_free_dims(self, visible_dims, None)
 
-    Z = self.Z[:, free_dims]
+    Z = self.Z.values
     plots = {}
 
     #one dimensional plotting

GPy/plotting/gpy_plot/latent_plots.py

@@ -113,19 +113,18 @@ def plot_latent_inducing(self,
                         legend=False,
                         plot_limits=None,
                         marker=None,
-                        num_samples=1000,
                         projection='2d',
                         **kwargs):
     """
     Plot a scatter plot of the inducing inputs.
 
-    :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 [int] which_indices: which input dimensions to plot against each other
     :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 str marker: marker to use [default is custom arrow like]
     :param kwargs: the kwargs for the scatter plots
+    :param str projection: for now 2d or 3d projection (other projections can be implemented, see developer documentation)
     """
     canvas, projection, kwargs, sig_dims = _new_canvas(self, projection, kwargs, which_indices)
 
@@ -135,7 +134,7 @@ def plot_latent_inducing(self,
         kwargs['marker'] = marker
     update_not_existing_kwargs(kwargs, pl().defaults.inducing_2d)  # @UndefinedVariable
     from .data_plots import _plot_inducing
-    scatters = _plot_inducing(self, canvas, sig_dims[:2], projection, label, num_samples=num_samples, **kwargs)
+    scatters = _plot_inducing(self, canvas, sig_dims[:2], projection, label, **kwargs)
     return pl().add_to_canvas(canvas, dict(scatter=scatters), legend=legend)
 
 

GPy/testing/plotting_tests.py

@@ -252,7 +252,7 @@ def test_kernel():
         k2.plot_ARD(['rbf', 'linear', 'bias'], legend=True)
         k2.plot_covariance(visible_dims=[0, 3], plot_limits=(-1,3))
         k2.plot_covariance(visible_dims=[2], plot_limits=(-1, 3))
-        k2.plot_covariance(visible_dims=[2, 4], plot_limits=((-1, 0), (5, 3)), projection='3d')
+        k2.plot_covariance(visible_dims=[2, 4], plot_limits=((-1, 0), (5, 3)), projection='3d', rstride=10, cstride=10)
         k2.plot_covariance(visible_dims=[1, 4])
         for do_test in _image_comparison(
                 baseline_images=['kern_{}'.format(sub) for sub in ["ARD", 'cov_2d', 'cov_1d', 'cov_3d', 'cov_no_lim']],
@@ -325,7 +325,7 @@ def test_threed():
     m.plot_samples(projection='3d', plot_raw=False, samples=1)
     plt.close('all')
     m.plot_data(projection='3d')
-    m.plot_mean(projection='3d')
+    m.plot_mean(projection='3d', rstride=10, cstride=10)
     m.plot_inducing(projection='3d')
     #m.plot_errorbars_trainset(projection='3d')
     for do_test in _image_comparison(baseline_images=['gp_3d_{}'.format(sub) for sub in ["data", "mean", 'inducing',