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[latent plots] legend was always plotted

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This commit is contained in:
Max Zwiessele 2016-02-26 09:54:41 +00:00
parent 218616154c
commit 6d34cf3ad1
1 changed files with 12 additions and 10 deletions
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22
GPy/plotting/gpy_plot/latent_plots.py
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@ -188,11 +188,12 @@ def plot_magnification(self, labels=None, which_indices=None,
_, _, Xgrid, _, _, xmin, xmax, resolution = helper_for_plot_data(self, X, plot_limits, which_indices, None, resolution)
canvas, imshow_kwargs = pl().new_canvas(xlim=(xmin[0], xmax[0]), ylim=(xmin[1], xmax[1]),
xlabel='latent dimension %i' % input_1, ylabel='latent dimension %i' % input_2, **imshow_kwargs)
if (labels is not None) and legend:
legend = find_best_layout_for_subplots(len(np.unique(labels)))[1]
else:
labels = np.ones(self.num_data)
legend = False
if legend:
if (labels is not None):
legend = find_best_layout_for_subplots(len(np.unique(labels)))[1]
else:
labels = np.ones(self.num_data)
legend = False
scatters = _plot_latent_scatter(canvas, X, which_indices, labels, marker, num_samples, projection='2d', **scatter_kwargs or {})
view = _plot_magnification(self, canvas, which_indices, Xgrid, xmin, xmax, resolution, updates, mean, covariance, kern, **imshow_kwargs)
retval = pl().add_to_canvas(canvas, dict(scatter=scatters, imshow=view),
@ -254,11 +255,12 @@ def plot_latent(self, labels=None, which_indices=None,
_, _, Xgrid, _, _, xmin, xmax, resolution = helper_for_plot_data(self, X, plot_limits, which_indices, None, resolution)
canvas, imshow_kwargs = pl().new_canvas(xlim=(xmin[0], xmax[0]), ylim=(xmin[1], xmax[1]),
xlabel='latent dimension %i' % input_1, ylabel='latent dimension %i' % input_2, **imshow_kwargs)
if (labels is not None) and legend:
legend = find_best_layout_for_subplots(len(np.unique(labels)))[1]
elif legend:
labels = np.ones(self.num_data)
legend = False
if legend:
if (labels is not None):
legend = find_best_layout_for_subplots(len(np.unique(labels)))[1]
else:
labels = np.ones(self.num_data)
legend = False
scatters = _plot_latent_scatter(canvas, X, which_indices, labels, marker, num_samples, projection='2d', **scatter_kwargs or {})
view = _plot_latent(self, canvas, which_indices, Xgrid, xmin, xmax, resolution, updates, kern, **imshow_kwargs)
retval = pl().add_to_canvas(canvas, dict(scatter=scatters, imshow=view), legend=legend)