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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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17
GPy/plotting/matplot_dep/visualize.py
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@ -102,7 +102,8 @@ class lvm(matplotlib_show):
vals = param_to_array(model.X.mean)
else:
vals = param_to_array(model.X)
if len(vals.shape)==1:
vals = vals[None,:]
matplotlib_show.__init__(self, vals, axes=latent_axes)
if isinstance(latent_axes,mpl.axes.Axes):
@ -393,14 +394,13 @@ class mocap_data_show_vpython(vpython_show):
def process_values(self):
raise NotImplementedError, "this needs to be implemented to use the data_show class"
class mocap_data_show(matplotlib_show):
"""Base class for visualizing motion capture data."""
def __init__(self, vals, axes=None, connect=None):
if axes==None:
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)
self.connect = connect
@ -445,11 +445,12 @@ class mocap_data_show(matplotlib_show):
def process_values(self):
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."""
self.x_lim = np.array([self.vals[:, 0].min(), self.vals[:, 0].max()])
self.y_lim = np.array([self.vals[:, 1].min(), self.vals[:, 1].max()])
self.z_lim = np.array([self.vals[:, 2].min(), self.vals[:, 2].max()])
bs = [(self.vals[:, i].max()-self.vals[:, i].min())*boundary for i in xrange(3)]
self.x_lim = np.array([self.vals[:, 0].min()-bs[0], self.vals[:, 0].max()+bs[0]])
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):
self.points_handle.remove()
@ -472,6 +473,8 @@ class mocap_data_show(matplotlib_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."""
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)
def process_values(self):