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plot_latent: added param_to_array to model.X and model.Z for matplotlib plotting

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Max Zwiessele 2014-01-24 16:49:19 +00:00
parent a9e5513c3f
commit 8e73c41a81
1 changed files with 9 additions and 7 deletions
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16
GPy/util/plot_latent.py
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@ -38,9 +38,10 @@ def plot_latent(model, labels=None, which_indices=None,
labels = np.ones(model.num_data)
input_1, input_2 = most_significant_input_dimensions(model, which_indices)
X = param_to_array(model.X)
# first, plot the output variance as a function of the latent space
Xtest, xx, yy, xmin, xmax = util.plot.x_frame2D(model.X[:, [input_1, input_2]], resolution=resolution)
Xtest, xx, yy, xmin, xmax = util.plot.x_frame2D(X[:, [input_1, input_2]], resolution=resolution)
Xtest_full = np.zeros((Xtest.shape[0], model.X.shape[1]))
def plot_function(x):
@ -49,7 +50,7 @@ def plot_latent(model, labels=None, which_indices=None,
var = var[:, :1]
return np.log(var)
view = ImshowController(ax, plot_function,
tuple(model.X[:, [input_1, input_2]].min(0)) + tuple(model.X[:, [input_1, input_2]].max(0)),
tuple(X[:, [input_1, input_2]].min(0)) + tuple(X[:, [input_1, input_2]].max(0)),
resolution, aspect=aspect, interpolation='bilinear',
cmap=pb.cm.binary)
@ -75,11 +76,11 @@ def plot_latent(model, labels=None, which_indices=None,
index = np.nonzero(labels == ul)[0]
if model.input_dim == 1:
x = param_to_array(model.X)[index, input_1]
x = X[index, input_1]
y = np.zeros(index.size)
else:
x = model.X[index, input_1]
y = model.X[index, input_2]
x = X[index, input_1]
y = X[index, input_2]
ax.scatter(x, y, marker=m, s=s, color=util.plot.Tango.nextMedium(), label=this_label)
ax.set_xlabel('latent dimension %i' % input_1)
@ -94,7 +95,8 @@ def plot_latent(model, labels=None, which_indices=None,
ax.set_aspect('auto') # set a nice aspect ratio
if plot_inducing:
ax.plot(model.Z[:, input_1], model.Z[:, input_2], '^w')
Z = param_to_array(model.Z)
ax.plot(Z[:, input_1], Z[:, input_2], '^w')
if updates:
ax.figure.canvas.show()