def sample(self, size=1):
""" Sample random variables from the model.
Parameters
----------
size : int
number of sample to take
Returns
-------
:obj:`list` of :obj:`ParallelJawPtGrasp3D`
sampled grasps in various poses
"""
samples = []
for i in range(size):
# sample random pose
xi = self.r_xi_rv_.rvs(size=1)
S_xi = skew(xi)
axis_sigma = self.R_sample_sigma_.T.dot(self.grasp_.axis)
v = self.R_sample_sigma_.dot(scipy.linalg.expm(S_xi).dot(axis_sigma))
t = self.R_sample_sigma_.dot(self.t_rv_.rvs(size=1).T).T
open_width = max(self.open_width_rv_.rvs(size=1), 0)
close_width = max(self.close_width_rv_.rvs(size=1), 0)
approach = self.approach_rv_.rvs(size=1)
# transform grasp by pose
grasp_sample = ParallelJawPtGrasp3D(ParallelJawPtGrasp3D.configuration_from_params(t, v, open_width, approach, self.grasp_.jaw_width, close_width))
samples.append(grasp_sample)
if size == 1:
return samples[0]
return samples
def sample(self, size=1):
""" Sample rigid transform random variables.
Parameters
----------
size : int
number of sample to take
Returns
-------
:obj:`list` of :obj:`RigidTransform`
sampled rigid transformations
"""
samples = []
for i in range(size):
# sample random pose
xi = self._r_xi_rv.rvs(size=1)
S_xi = skew(xi)
R_sample = scipy.linalg.expm(S_xi)
t_sample = self._t_rv.rvs(size=1)
samples.append(
RigidTransform(rotation=R_sample,
translation=t_sample,
from_frame=self._from_frame,
to_frame=self._to_frame))
# not a list if only 1 sample
if size == 1 and len(samples) > 0:
return samples[0]
return samples
def sample(self, size=1):
""" Sample random variables from the model.
Parameters
----------
size : int
number of sample to take
Returns
-------
:obj:`list` of :obj:`GraspableObject3D`
sampled graspable objects from the pose random variable
"""
samples = []
for i in range(size):
num_consecutive_failures = 0
prev_len = len(samples)
while len(samples) == prev_len:
try:
# sample random pose
obj_copy = copy.deepcopy(self.obj_)
xi = self.r_xi_rv_.rvs(size=1)
S_xi = skew(xi)
R = self.R_sample_sigma_.dot(
scipy.linalg.expm(S_xi).dot(
self.R_sample_sigma_.T.dot(
self.mean_T_obj_world_.rotation)))
s = max(self.s_rv_.rvs(size=1)[0], 0)
t = self.R_sample_sigma_.dot(self.t_rv_.rvs(size=1).T).T
z = self.R_sample_sigma_.dot(self.com_rv_.rvs(size=1))
sample_tf = SimilarityTransform(rotation=R.T,
translation=t,
scale=s)
z_tf = sample_tf * Point(z, frame=sample_tf.from_frame)
z_tf = z_tf.data
# transform object by pose
obj_sample = obj_copy.transform(sample_tf)
obj_sample.mesh.center_of_mass = z_tf
samples.append(obj_sample)
except Exception as e:
num_consecutive_failures += 1
if num_consecutive_failures > 3:
raise
# not a list if only 1 sample
if size == 1 and len(samples) > 0:
return samples[0]
return samples
