def _plot_valfun(self, VMat):
"""
:returns: handle to the figure
.. warning::
The calling function MUST call pl.draw() or the figures
will not be updated.
"""
if self.valueFunction_fig is None or self.valueFunction_img is None:
maxV = VMat.max()
minV = VMat.min()
self.valueFunction_fig = pl.figure("Value Function")
ax = self.valueFunction_fig.add_subplot(111)
self.valueFunction_img = ax.imshow(
VMat,
cmap='ValueFunction',
interpolation='nearest',
origin='lower',
vmin=minV,
vmax=maxV)
pl.xticks(self.xTicks, self.xTicksLabels, fontsize=12)
# Don't need the y labels since we share axes on subplot
pl.xlabel(r"$\theta$ (degree)")
pl.title('Value Function')
norm = colors.Normalize(vmin=VMat.min(), vmax=VMat.max())
self.valueFunction_img.set_data(VMat)
self.valueFunction_img.set_norm(norm)
self.valueFunction_fig.canvas.draw()
def _plot_policy(self, piMat):
"""
:returns: handle to the figure
.. warning::
The calling function MUST call pl.draw() or the figures
will not be updated.
"""
if self.policy_fig is None or self.policy_img is None:
self.policy_fig = pl.figure("Policy")
ax = self.policy_fig.add_subplot(111)
self.policy_img = ax.imshow(
piMat,
cmap='InvertedPendulumActions',
interpolation='nearest',
origin='lower',
vmin=0,
vmax=self.actions_num)
pl.xticks(self.xTicks, self.xTicksLabels, fontsize=12)
pl.yticks(self.yTicks, self.yTicksLabels, fontsize=12)
pl.xlabel(r"$\theta$ (degree)")
pl.ylabel(r"$\dot{\theta}$ (degree/sec)")
pl.title('Policy')
self.policy_img.set_data(piMat)
self.policy_fig.canvas.draw()
