def plotDynamicalSystemComparison(data1, data2, name1, name2, axs, axs_diff):
lines1 = plotDynamicalSystem(data1, axs)
lines2 = plotDynamicalSystem(data2, axs)
plt.setp(lines1,
linestyle='-',
linewidth=4,
color=(0.8, 0.8, 0.8),
label=name1)
plt.setp(lines2,
linestyle='--',
linewidth=2,
color=(0.0, 0.0, 0.5),
label=name2)
plt.legend()
data_diff = data1 - data2
data_diff[:, -1] = data1[:, -1] # Don't subtract time...
lines_diff = plotDynamicalSystem(data_diff, axs_diff)
plt.setp(lines_diff,
linestyle='-',
linewidth=2,
color=(0.50, 0.00, 0.00),
label='diff')
plt.legend()
def plotDynamicalSystemComparison(data1,data2,name1,name2,axs,axs_diff):
lines1 = plotDynamicalSystem(data1,axs)
lines2 = plotDynamicalSystem(data2,axs)
plt.setp(lines1,linestyle='-', linewidth=4, color=(0.8,0.8,0.8), label=name1)
plt.setp(lines2,linestyle='--', linewidth=2, color=(0.0,0.0,0.5), label=name2)
plt.legend()
data_diff = data1-data2;
data_diff[:,-1] = data1[:,-1] # Don't subtract time...
lines_diff = plotDynamicalSystem(data_diff,axs_diff)
plt.setp(lines_diff,linestyle= '-', linewidth=2, color=(0.50,0.00,0.00), label='diff')
plt.legend()
def plotDmp(data, fig, forcing_terms_data=0, fa_output_data=0):
# Number of columns in the data
n_cols = data.shape[1]
# Dimensionality of dynamical system. -1 because of time, /2 because both x and xd are stored.
n_state_length = (n_cols - 1) / 2
# Dimensionality of the DMP. -2 because of phase and gating (which are 1D) and /3 because of spring system (which has dimensionality 2*n_dims_dmp) and goal system (which has dimensionality n_dims_dmp)
n_dims_dmp = (n_state_length - 2) / 3
D = n_dims_dmp
# Abbreviation for convencience
# We will loop over each of the subsystems of the DMP: prepare some variables here
# Names of each of the subsystems
system_names = ['phase', 'gating', 'goal', 'spring']
system_varname = ['x', 'v', '\mathbf{y}^{g_d}', '\mathbf{y}']
# The indices they have in the data
system_indices = [
range(3 * D, 3 * D + 1),
range(3 * D + 1, 3 * D + 2),
range(2 * D, 3 * D),
range(0 * D, 2 * D)
]
system_order = [1, 1, 1, 2]
# The subplot in which they are plotted (x is plotted here, xd in the subplot+1)
subplot_offsets = [1, 6, 3, 8]
# Loop over each of the subsystems of the DMP
n_systems = len(system_names)
for i_system in range(n_systems):
# Plot 'x' for this subsystem (analytical solution and step-by-step integration)
#fig.suptitle(filename)
axs = []
axs.append(fig.add_subplot(3, 5, subplot_offsets[i_system]))
axs.append(fig.add_subplot(3, 5, subplot_offsets[i_system] + 1))
if (system_order[i_system] == 2):
axs.append(fig.add_subplot(3, 5, subplot_offsets[i_system] + 2))
indices = system_indices[i_system]
indices_xd = [i + n_state_length for i in indices
] # +n_state_length because xd is in second half
indices.extend(indices_xd) # For derivative
indices.append(-1) # For time
lines = plotDynamicalSystem(data[:, indices], axs)
if (system_names[i_system] == 'gating'):
plt.setp(lines, color='m')
axs[0].set_ylim([0, 1.1])
if (system_names[i_system] == 'phase'):
axs[0].set_ylim([0, 1.1])
plt.setp(lines, color='c')
for ii in range(len(axs)):
x = numpy.mean(axs[ii].get_xlim())
y = numpy.mean(axs[ii].get_ylim())
axs[ii].text(x,
y,
system_names[i_system],
horizontalalignment='center')
if (ii == 0):
axs[ii].set_ylabel(r'$' + system_varname[i_system] + '$')
if (ii == 1):
axs[ii].set_ylabel(r'$\dot{' + system_varname[i_system] + '}$')
if (ii == 2):
axs[ii].set_ylabel(r'$\ddot{' + system_varname[i_system] +
'}$')
ts = data[:, -1]
# nnn Fix this
if (len(fa_output_data) > 1):
ax = fig.add_subplot(3, 5, 11)
ax.plot(ts, fa_output_data)
x = numpy.mean(ax.get_xlim())
y = numpy.mean(ax.get_ylim())
ax.text(x, y, 'func. approx.', horizontalalignment='center')
ax.set_xlabel(r'time ($s$)')
ax.set_ylabel(r'$f_\mathbf{\theta}(' + system_varname[0] + ')$')
if (len(forcing_terms_data) > 1):
ax = fig.add_subplot(3, 5, 12)
ax.plot(ts, forcing_terms_data)
x = numpy.mean(ax.get_xlim())
y = numpy.mean(ax.get_ylim())
ax.text(x, y, 'forcing term', horizontalalignment='center')
ax.set_xlabel(r'time ($s$)')
ax.set_ylabel(r'$v\cdot f_{\mathbf{\theta}}(' + system_varname[0] +
')$')
executable = "../../../bin/demoExponentialSystem"
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/demoExponentialSystem"
subprocess.call([executable, directory])
fig = plt.figure(1)
data_ana = numpy.loadtxt(directory+"/analytical.txt")
plotDynamicalSystem(data_ana,[fig.add_subplot(1,2,1), fig.add_subplot(1,2,2)])
plt.title('analytical')
fig = plt.figure(2)
data_num = numpy.loadtxt(directory+"/numerical.txt")
plotDynamicalSystem(data_num,[fig.add_subplot(1,2,1), fig.add_subplot(1,2,2)])
plt.title('numerical')
fig = plt.figure(3)
axs = [fig.add_subplot(2,2,1), fig.add_subplot(2,2,2)]
axs_diff = [fig.add_subplot(2,2,3), fig.add_subplot(2,2,4)]
plotDynamicalSystemComparison(data_ana,data_num,'analytical','numerical',axs,axs_diff)
plt.show()
def plotDmp(data,fig,forcing_terms_data=0,fa_output_data=0):
# Number of columns in the data
n_cols = data.shape[1]
# Dimensionality of dynamical system. -1 because of time, /2 because both x and xd are stored.
n_state_length = (n_cols-1)/2
# Dimensionality of the DMP. -2 because of phase and gating (which are 1D) and /3 because of spring system (which has dimensionality 2*n_dims_dmp) and goal system (which has dimensionality n_dims_dmp)
n_dims_dmp = (n_state_length-2)/3
D = n_dims_dmp; # Abbreviation for convencience
# We will loop over each of the subsystems of the DMP: prepare some variables here
# Names of each of the subsystems
system_names = ['phase','gating','goal','spring'];
system_varname = [ 'x', 'v', '\mathbf{y}^{g_d}', '\mathbf{y}' ];
# The indices they have in the data
system_indices = [ range(3*D,3*D+1), range(3*D+1,3*D+2), range(2*D,3*D), range(0*D,2*D) ];
system_order = [ 1, 1, 1, 2 ];
# The subplot in which they are plotted (x is plotted here, xd in the subplot+1)
subplot_offsets = [ 1, 6, 3, 8 ];
# Loop over each of the subsystems of the DMP
n_systems = len(system_names)
for i_system in range(n_systems):
# Plot 'x' for this subsystem (analytical solution and step-by-step integration)
#fig.suptitle(filename)
axs = [];
axs.append(fig.add_subplot(3,5,subplot_offsets[i_system]))
axs.append(fig.add_subplot(3,5,subplot_offsets[i_system]+1))
if (system_order[i_system]==2):
axs.append(fig.add_subplot(3,5,subplot_offsets[i_system]+2))
indices = system_indices[i_system];
indices_xd =[i+n_state_length for i in indices] # +n_state_length because xd is in second half
indices.extend(indices_xd) # For derivative
indices.append(-1) # For time
lines = plotDynamicalSystem(data[:,indices],axs);
if (system_names[i_system]=='gating'):
plt.setp(lines,color='m')
axs[0].set_ylim([0, 1.1])
if (system_names[i_system]=='phase'):
axs[0].set_ylim([0, 1.1])
plt.setp(lines,color='c')
for ii in range(len(axs)):
x = numpy.mean(axs[ii].get_xlim())
y = numpy.mean(axs[ii].get_ylim())
axs[ii].text(x,y,system_names[i_system], horizontalalignment='center');
if (ii==0):
axs[ii].set_ylabel(r'$'+system_varname[i_system]+'$')
if (ii==1):
axs[ii].set_ylabel(r'$\dot{'+system_varname[i_system]+'}$')
if (ii==2):
axs[ii].set_ylabel(r'$\ddot{'+system_varname[i_system]+'}$')
ts = data[:,-1];
# todo Fix this
if (len(fa_output_data)>1):
ax = fig.add_subplot(3,5,11)
ax.plot(ts,fa_output_data)
x = numpy.mean(ax.get_xlim())
y = numpy.mean(ax.get_ylim())
ax.text(x,y,'func. approx.', horizontalalignment='center');
ax.set_xlabel(r'time ($s$)');
ax.set_ylabel(r'$f_\mathbf{\theta}('+system_varname[0]+')$');
if (len(forcing_terms_data)>1):
ax = fig.add_subplot(3,5,12)
ax.plot(ts,forcing_terms_data)
x = numpy.mean(ax.get_xlim())
y = numpy.mean(ax.get_ylim())
ax.text(x,y,'forcing term', horizontalalignment='center');
ax.set_xlabel(r'time ($s$)');
ax.set_ylabel(r'$v\cdot f_{\mathbf{\theta}}('+system_varname[0]+')$');
