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Minor tidy up of names in visualize (replace histogram with bar chart in lvm_dimselect).

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Neil Lawrence 2013-04-30 07:17:44 +01:00
parent 71114eef8c
commit e941c949e5
1 changed files with 20 additions and 31 deletions
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51
GPy/util/visualize.py
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@ -96,18 +96,8 @@ class lvm(data_show):
pass
def on_click(self, event):
#print 'click', event.xdata, event.ydata
if event.inaxes!=self.latent_axes: return
self.move_on = not self.move_on
# if self.called:
# self.xs.append(event.xdata)
# self.ys.append(event.ydata)
# self.line.set_data(self.xs, self.ys)
# self.line.figure.canvas.draw()
# else:
# self.xs = [event.xdata]
# self.ys = [event.ydata]
# self.line, = self.latent_axes.plot(event.xdata, event.ydata)
self.called = True
def on_move(self, event):
if event.inaxes!=self.latent_axes: return
@ -120,7 +110,7 @@ class lvm(data_show):
class lvm_subplots(lvm):
"""
latent_axes is a np array of dimension np.ceil(Q/2) + 1,
one for each pair of the axes, and the last one for the sensitiity histogram
one for each pair of the axes, and the last one for the sensitiity bar chart
"""
def __init__(self, vals, model, data_visualize, latent_axes=None, latent_index=[0,1]):
lvm.__init__(self, vals, model,data_visualize,latent_axes,[0,1])
@ -132,39 +122,39 @@ class lvm_subplots(lvm):
class lvm_dimselect(lvm):
"""
A visualizer for latent variable models which allows selection of the latent dimensions to use by clicking on a histogram of their length scales.
A visualizer for latent variable models which allows selection of the latent dimensions to use by clicking on a bar chart of their length scales.
"""
def __init__(self, vals, model, data_visualize, latent_axes=None, hist_axes=None, latent_index=[0, 1]):
if latent_axes==None and hist_axes==None:
self.fig,(latent_axes,self.hist_axes) = plt.subplots(1,2)
elif hist_axes==None:
def __init__(self, vals, model, data_visualize, latent_axes=None, sense_axes=None, latent_index=[0, 1]):
if latent_axes==None and sense_axes==None:
self.fig,(latent_axes,self.sense_axes) = plt.subplots(1,2)
elif sense_axes==None:
fig=plt.figure()
self.hist_axes = fig.add_subplot(111)
self.sense_axes = fig.add_subplot(111)
else:
self.hist_axes = hist_axes
self.sense_axes = sense_axes
lvm.__init__(self,vals,model,data_visualize,latent_axes,latent_index)
self.draw_histogram()
self.show_sensitivities()
print "use left and right mouse butons to select dimensions"
def draw_histogram(self):
# A click in the histogram axis for selection a dimension.
self.hist_axes.cla()
self.hist_axes.bar(np.arange(self.model.Q),1./self.model.input_sensitivity(),color='b')
def show_sensitivities(self):
# A click in the bar chart axis for selection a dimension.
self.sense_axes.cla()
self.sense_axes.bar(np.arange(self.model.Q),1./self.model.input_sensitivity(),color='b')
if self.latent_index[1] == self.latent_index[0]:
self.hist_axes.bar(np.array(self.latent_index[0]),1./self.model.input_sensitivity()[self.latent_index[0]],color='y')
self.hist_axes.bar(np.array(self.latent_index[1]),1./self.model.input_sensitivity()[self.latent_index[1]],color='y')
self.sense_axes.bar(np.array(self.latent_index[0]),1./self.model.input_sensitivity()[self.latent_index[0]],color='y')
self.sense_axes.bar(np.array(self.latent_index[1]),1./self.model.input_sensitivity()[self.latent_index[1]],color='y')
else:
self.hist_axes.bar(np.array(self.latent_index[0]),1./self.model.input_sensitivity()[self.latent_index[0]],color='g')
self.hist_axes.bar(np.array(self.latent_index[1]),1./self.model.input_sensitivity()[self.latent_index[1]],color='r')
self.sense_axes.bar(np.array(self.latent_index[0]),1./self.model.input_sensitivity()[self.latent_index[0]],color='g')
self.sense_axes.bar(np.array(self.latent_index[1]),1./self.model.input_sensitivity()[self.latent_index[1]],color='r')
self.hist_axes.figure.canvas.draw()
self.sense_axes.figure.canvas.draw()
def on_click(self, event):
if event.inaxes==self.hist_axes:
if event.inaxes==self.sense_axes:
new_index = max(0,min(int(np.round(event.xdata-0.5)),self.model.Q-1))
if event.button == 1:
# Make it red if and y-axis (red=port=left) if it is a left button click
@ -173,7 +163,7 @@ class lvm_dimselect(lvm):
# Make it green and x-axis (green=starboard=right) if it is a right button click
self.latent_index[0] = new_index
self.draw_histogram()
self.show_sensitivities()
self.latent_axes.cla()
self.model.plot_latent(which_indices=self.latent_index,
@ -188,7 +178,6 @@ class lvm_dimselect(lvm):
def on_move(self, event):
#print "move"
if event.inaxes!=self.latent_axes: return
if self.called and self.move_on:
self.latent_values[self.latent_index[0]]=event.xdata