def gen_path(self, trajectory):
"""Generate the DMPs necessary to follow the
specified trajectory.
trajectory np.array: the time series of points to follow
[DOFs, time], with a column of None
wherever the pen should be lifted
"""
if trajectory.ndim == 1:
trajectory = trajectory.reshape(1,len(trajectory))
num_DOF = trajectory.shape[0]
# break up the trajectory into its different words
# NaN or None signals a new word / break in drawing
breaks = np.array(np.where(trajectory[0] != trajectory[0]))[0]
self.num_seqs = len(breaks) - 1
self.dmp_sets = []
for ii in range(self.num_seqs):
# get the ii'th sequence
seq = trajectory[:, breaks[ii]+1:breaks[ii+1]]
if self.pattern == 'discrete':
dmps = DMP_discrete.DMPs_discrete(dmps=num_DOF, bfs=self.bfs)
elif self.pattern == 'rhythmic':
dmps = DMP_rhythmic.DMPs_rhythmic(dmps=num_DOF, bfs=self.bfs)
else:
raise Exception('Invalid pattern type specified. Valid choices \
are discrete or rhythmic.')
dmps.imitate_path(y_des=seq)
self.dmp_sets.append(dmps)
self.dmps = self.dmp_sets[0]
def gen_path(self, trajectory):
"""Generates the trajectories for the
position, velocity, and acceleration to follow
during run time to reproduce the given trajectory.
trajectory np.array: a list of points to follow
"""
if trajectory.ndim == 1:
trajectory = trajectory.reshape(1, len(trajectory))
dt = 1.0 / trajectory.shape[1]
# break up the trajectory into its different words
# NaN or None signals a new word / break in drawing
breaks = np.where(trajectory != trajectory)
# some vector manipulation to get what we want
breaks = breaks[1][:len(breaks[1]) / 2]
self.num_seqs = len(breaks) - 1
import scipy.interpolate
self.seqs_x = []
self.seqs_y = []
for ii in range(self.num_seqs):
# get the ii'th sequence
seq_x = trajectory[0, breaks[ii] + 1:breaks[ii + 1]]
seq_y = trajectory[1, breaks[ii] + 1:breaks[ii + 1]]
# generate function to interpolate the desired trajectory
vals = np.linspace(0, 1, len(seq_x))
self.seqs_x.append(scipy.interpolate.interp1d(vals, seq_x))
self.seqs_y.append(scipy.interpolate.interp1d(vals, seq_y))
self.trajectory = [self.seqs_x[0], self.seqs_y[0]]
def gen_path(self, trajectory):
"""Generates the trajectories for the
position, velocity, and acceleration to follow
during run time to reproduce the given trajectory.
trajectory np.array: a list of points to follow
"""
if trajectory.ndim == 1:
trajectory = trajectory.reshape(1,len(trajectory))
dt = 1.0 / trajectory.shape[1]
# break up the trajectory into its different words
# NaN or None signals a new word / break in drawing
breaks = np.where(trajectory != trajectory)
# some vector manipulation to get what we want
breaks = breaks[1][:len(breaks[1])/2]
self.num_seqs = len(breaks) - 1
import scipy.interpolate
self.seqs_x = []
self.seqs_y = []
for ii in range(self.num_seqs):
# get the ii'th sequence
seq_x = trajectory[0, breaks[ii]+1:breaks[ii+1]]
seq_y = trajectory[1, breaks[ii]+1:breaks[ii+1]]
# generate function to interpolate the desired trajectory
vals = np.linspace(0, 1, len(seq_x))
self.seqs_x.append(scipy.interpolate.interp1d(vals, seq_x))
self.seqs_y.append(scipy.interpolate.interp1d(vals, seq_y))
self.trajectory = [self.seqs_x[0], self.seqs_y[0]]
def gen_path(self, trajectory):
"""Generate the DMPs necessary to follow the
specified trajectory.
trajectory np.array: the time series of points to follow
[DOFs, time], with a column of None
wherever the pen should be lifted
"""
if trajectory.ndim == 1:
trajectory = trajectory.reshape(1, len(trajectory))
num_DOF = trajectory.shape[0]
# break up the trajectory into its different words
# NaN or None signals a new word / break in drawing
breaks = np.array(np.where(trajectory[0] != trajectory[0]))[0]
self.num_seqs = len(breaks) - 1
self.dmp_sets = []
for ii in range(self.num_seqs):
# get the ii'th sequence
seq = trajectory[:, breaks[ii] + 1:breaks[ii + 1]]
if self.pattern == 'discrete':
dmps = DMP_discrete.DMPs_discrete(dmps=num_DOF, bfs=self.bfs)
elif self.pattern == 'rhythmic':
dmps = DMP_rhythmic.DMPs_rhythmic(dmps=num_DOF, bfs=self.bfs)
else:
raise Exception(
'Invalid pattern type specified. Valid choices \
are discrete or rhythmic.')
dmps.imitate_path(y_des=seq)
self.dmp_sets.append(dmps)
self.dmps = self.dmp_sets[0]
