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fix the bug in mocap demos

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This commit is contained in:
Zhenwen Dai 2014-05-15 17:56:07 +01:00
parent 3ee2dc920c
commit a796b7bc81
2 changed files with 15 additions and 10 deletions
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8
GPy/examples/dimensionality_reduction.py
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@ -414,9 +414,10 @@ def stick(kernel=None, optimize=True, verbose=True, plot=True):
ax = m.plot_latent() ax = m.plot_latent()
y = m.Y[0, :] y = m.Y[0, :]
data_show = GPy.plotting.matplot_dep.visualize.stick_show(y[None, :], connect=data['connect']) data_show = GPy.plotting.matplot_dep.visualize.stick_show(y[None, :], connect=data['connect'])
vis = GPy.plotting.matplot_dep.visualize.lvm(m.X[:1, :].copy(), m, data_show, latent_axes=ax) lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[:1, :].copy(), m, data_show, latent_axes=ax)
raw_input('Press enter to finish') raw_input('Press enter to finish')
lvm_visualizer.close()
data_show.close()
return m return m
def bcgplvm_linear_stick(kernel=None, optimize=True, verbose=True, plot=True): def bcgplvm_linear_stick(kernel=None, optimize=True, verbose=True, plot=True):
@ -515,9 +516,10 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True, optimize=True, verbose
ax = m.plot_latent() ax = m.plot_latent()
y = m.Y[0, :] y = m.Y[0, :]
data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel']) data_show = GPy.plotting.matplot_dep.visualize.skeleton_show(y[None, :], data['skel'])
lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0, :].copy(), m, data_show, ax) lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm(m.X[0].copy(), m, data_show, latent_axes=ax)
raw_input('Press enter to finish') raw_input('Press enter to finish')
lvm_visualizer.close() lvm_visualizer.close()
data_show.close()
return m return m

17
GPy/plotting/matplot_dep/visualize.py
View file

@ -102,7 +102,8 @@ class lvm(matplotlib_show):
vals = param_to_array(model.X.mean) vals = param_to_array(model.X.mean)
else: else:
vals = param_to_array(model.X) vals = param_to_array(model.X)
if len(vals.shape)==1:
vals = vals[None,:]
matplotlib_show.__init__(self, vals, axes=latent_axes) matplotlib_show.__init__(self, vals, axes=latent_axes)
if isinstance(latent_axes,mpl.axes.Axes): if isinstance(latent_axes,mpl.axes.Axes):
@ -393,14 +394,13 @@ class mocap_data_show_vpython(vpython_show):
def process_values(self): def process_values(self):
raise NotImplementedError, "this needs to be implemented to use the data_show class" raise NotImplementedError, "this needs to be implemented to use the data_show class"
class mocap_data_show(matplotlib_show): class mocap_data_show(matplotlib_show):
"""Base class for visualizing motion capture data.""" """Base class for visualizing motion capture data."""
def __init__(self, vals, axes=None, connect=None): def __init__(self, vals, axes=None, connect=None):
if axes==None: if axes==None:
fig = plt.figure() fig = plt.figure()
axes = fig.add_subplot(111, projection='3d') axes = fig.add_subplot(111, projection='3d',aspect='equal')
matplotlib_show.__init__(self, vals, axes) matplotlib_show.__init__(self, vals, axes)
self.connect = connect self.connect = connect
@ -445,11 +445,12 @@ class mocap_data_show(matplotlib_show):
def process_values(self): def process_values(self):
raise NotImplementedError, "this needs to be implemented to use the data_show class" raise NotImplementedError, "this needs to be implemented to use the data_show class"
def initialize_axes(self): def initialize_axes(self, boundary=0.05):
"""Set up the axes with the right limits and scaling.""" """Set up the axes with the right limits and scaling."""
self.x_lim = np.array([self.vals[:, 0].min(), self.vals[:, 0].max()]) bs = [(self.vals[:, i].max()-self.vals[:, i].min())*boundary for i in xrange(3)]
self.y_lim = np.array([self.vals[:, 1].min(), self.vals[:, 1].max()]) self.x_lim = np.array([self.vals[:, 0].min()-bs[0], self.vals[:, 0].max()+bs[0]])
self.z_lim = np.array([self.vals[:, 2].min(), self.vals[:, 2].max()]) self.y_lim = np.array([self.vals[:, 1].min()-bs[1], self.vals[:, 1].max()+bs[1]])
self.z_lim = np.array([self.vals[:, 2].min()-bs[2], self.vals[:, 2].max()+bs[2]])
def initialize_axes_modify(self): def initialize_axes_modify(self):
self.points_handle.remove() self.points_handle.remove()
@ -472,6 +473,8 @@ class mocap_data_show(matplotlib_show):
class stick_show(mocap_data_show): class stick_show(mocap_data_show):
"""Show a three dimensional point cloud as a figure. Connect elements of the figure together using the matrix connect.""" """Show a three dimensional point cloud as a figure. Connect elements of the figure together using the matrix connect."""
def __init__(self, vals, connect=None, axes=None): def __init__(self, vals, connect=None, axes=None):
if len(vals.shape)==1:
vals = vals[None,:]
mocap_data_show.__init__(self, vals, axes=axes, connect=connect) mocap_data_show.__init__(self, vals, axes=axes, connect=connect)
def process_values(self): def process_values(self):