def oneUpdate(directory,plot_results=False):
inputs = np.linspace(-1.5,1.5,21);
a = 2.0
c = -1.0
n_params = 2
regularization = 0.01
task = DemoTaskApproximateQuadraticFunction(a,c,inputs,regularization)
mean_init = np.full(n_params,0.5)
covar_init = 0.25*np.eye(n_params)
initial_distribution = DistributionGaussian(mean_init, covar_init)
eliteness = 10
weighting_method = 'PI-BB'
covar_decay_factor = 0.8
updater = UpdaterCovarDecay(eliteness,weighting_method,covar_decay_factor)
n_samples_per_update = 10
i_update = runOptimizationTaskOneUpdate(directory, task, initial_distribution, updater, n_samples_per_update)
i_update -= 1
if plot_results and i_update>1:
# Plot the optimization results (from the files saved to disk)
fig = plt.figure(1,figsize=(15, 5))
plotOptimizationRollouts(directory,fig,task.plotRollout)
plt.show()
"""Simple script to plot y of DMP trajectory"""
n_dofs = (cost_vars.shape[1] - 1) // 4
y = cost_vars[:, 0:n_dofs]
if n_dofs == 1:
line_handles = ax.plot(y, linewidth=0.5)
else:
line_handles = ax.plot(y[:, 0], y[:, 1], linewidth=0.5)
return line_handles
if __name__ == '__main__':
executable = "../../../bin/demoOptimizationDmp"
if (not os.path.isfile(executable)):
print("")
print("ERROR: Executable '" + executable + "' does not exist.")
print("Please call 'make install' in the build directory first.")
print("")
sys.exit(-1)
# Call the executable with the directory to which results should be written
directory = "/tmp/demoOptimizationDmp"
command = executable + " " + directory
print(command)
subprocess.call(command, shell=True)
fig = plt.figure(1, figsize=(12, 4))
plotOptimizationRollouts(directory, fig, plotRollout)
plt.show()
#line_handles = ax.plot(t,cost_vars[:,1:1+n_dofs],linewidth=0.5)
line_handles = ax.plot(x_endeff,y_endeff,linewidth=0.5)
ax.plot(0.5, 0.5, 'or')
ax.axis('equal')
return line_handles
if __name__=='__main__':
for n_dofs in [3]:
# Initialize a viapoint task and save it to file
viapoint = 0.5*np.ones(2) # Always 2D!
task = TaskViapoint(viapoint)
directory = "/tmp/demoOptimizationDmpArm2D/"+str(n_dofs)+"D/"
task.saveToFile(directory,"viapoint_task.txt")
# Call the executable with the directory to which results should be written
print("Call executable to run optimization with "+str(n_dofs)+"D viapoint.")
executable = "../../bin/demoOptimizationDmpArm2D"
print(executeBinary(executable, str(n_dofs)+" "+directory))
print(" Plotting")
fig = plt.figure(n_dofs,figsize=(12, 4))
plotOptimizationRollouts(directory,fig,plotRollout)
#plotOptimizationRolloutsTask(directory,fig,task)
print("Showing")
plt.show()
