def set_cld(self, cld):
"""
sets the cloud for this appropriately
won't allocate any new memory
"""
scaled_cld, scale_params = unit_boxify(cld)
proj_mats, offset_mats, K = self.get_sol_params(scaled_cld)
K_gpu = gpu_pad(K, (MAX_CLD_SIZE, MAX_CLD_SIZE))
cld_gpu = gpu_pad(scaled_cld, (MAX_CLD_SIZE, DATA_DIM))
self.pts = [cld_gpu for _ in range(self.N)]
self.scale_params = scale_params
self.kernels = [K_gpu for _ in range(self.N)]
proj_mats_gpu = dict(
[(b, gpu_pad(p.get(), (MAX_CLD_SIZE + DATA_DIM + 1, MAX_CLD_SIZE))) for b, p in proj_mats.iteritems()]
)
self.proj_mats = dict([(b, [p for _ in range(self.N)]) for b, p in proj_mats_gpu.iteritems()])
offset_mats_gpu = dict(
[(b, gpu_pad(p.get(), (MAX_CLD_SIZE + DATA_DIM + 1, DATA_DIM))) for b, p in offset_mats.iteritems()]
)
self.offset_mats = dict([(b, [p for _ in range(self.N)]) for b, p in offset_mats_gpu.iteritems()])
self.dims = [scaled_cld.shape[0]]
self.pt_ptrs.fill(int(self.pts[0].gpudata))
self.kernel_ptrs.fill(int(self.kernels[0].gpudata))
self.dims_gpu.fill(self.dims[0])
for b in self.bend_coefs:
self.proj_mat_ptrs[b].fill(int(self.proj_mats[b][0].gpudata))
self.offset_mat_ptrs[b].fill(int(self.offset_mats[b][0].gpudata))
def main():
scikits.cuda.linalg.init()
args = parse_arguments()
f = h5py.File(args.datafile, 'r+')
bend_coefs = np.around(
loglinspace(args.bend_coef_init, args.bend_coef_final, args.n_iter),
BEND_COEF_DIGITS)
for seg_name, seg_info in f.iteritems():
if 'inv' in seg_info:
if args.replace:
del seg_info['inv']
inv_group = seg_info.create_group('inv')
else:
inv_group = seg_info['inv']
else:
inv_group = seg_info.create_group('inv')
ds_key = 'DS_SIZE_{}'.format(DS_SIZE)
if ds_key in inv_group:
scaled_x_na = inv_group[ds_key]['scaled_cloud_xyz'][:]
K_nn = inv_group[ds_key]['scaled_K_nn'][:]
else:
ds_g = inv_group.create_group(ds_key)
x_na = downsample_cloud(seg_info[args.cloud_name][:, :3])
scaled_x_na, scale_params = unit_boxify(x_na)
K_nn = tps_kernel_matrix(scaled_x_na)
if args.fill_traj:
r_traj = seg_info['r_gripper_tool_frame']['hmat'][:, :3, 3]
l_traj = seg_info['l_gripper_tool_frame']['hmat'][:, :3, 3]
scaled_r_traj = r_traj * scale_params[0] + scale_params[1]
scaled_l_traj = l_traj * scale_params[0] + scale_params[1]
scaled_r_traj_K = tps_kernel_matrix2(scaled_r_traj,
scaled_x_na)
scaled_l_traj_K = tps_kernel_matrix2(scaled_l_traj,
scaled_x_na)
ds_g['scaled_r_traj'] = scaled_r_traj
ds_g['scaled_l_traj'] = scaled_l_traj
ds_g['scaled_r_traj_K'] = scaled_r_traj_K
ds_g['scaled_l_traj_K'] = scaled_l_traj_K
# Precompute l,r closing indices
lr2finger_traj = {}
for lr in 'lr':
arm_name = {"l": "leftarm", "r": "rightarm"}[lr]
lr2finger_traj[
lr] = gripper_joint2gripper_l_finger_joint_values(
np.asarray(seg_info['%s_gripper_joint' %
lr]))[:, None]
opening_inds, closing_inds = get_opening_closing_inds(
lr2finger_traj[lr])
if '%s_closing_inds' % lr in seg_info:
del seg_info['%s_closing_inds' % lr]
if not closing_inds:
closing_inds = False
seg_info['%s_closing_inds' % lr] = closing_inds
#
ds_g['cloud_xyz'] = x_na
ds_g['scaled_cloud_xyz'] = scaled_x_na
ds_g['scaling'] = scale_params[0]
ds_g['scaled_translation'] = scale_params[1]
ds_g['scaled_K_nn'] = K_nn
for bend_coef in bend_coefs:
if str(bend_coef) in inv_group:
continue
bend_coef_g = inv_group.create_group(str(bend_coef))
_, res = get_sol_params(scaled_x_na, K_nn, bend_coef)
for k, v in res.iteritems():
bend_coef_g[k] = v
if args.verbose:
sys.stdout.write(
'\rprecomputed tps solver for segment {}'.format(seg_name))
sys.stdout.flush()
print ""
if args.test:
atol = 1e-7
print 'Running batch get sol params test with atol = ', atol
test_batch_get_sol_params(f, [bend_coef], atol=atol)
print 'batch sol params test succeeded'
print ""
bend_coefs = np.around(
loglinspace(args.exact_bend_coef_init, args.exact_bend_coef_final,
args.exact_n_iter), BEND_COEF_DIGITS)
for seg_name, seg_info in f.iteritems():
if 'solver' in seg_info:
if args.replace:
del seg_info['solver']
solver_g = seg_info.create_group('solver')
else:
solver_g = seg_info['solver']
else:
solver_g = seg_info.create_group('solver')
x_nd = seg_info['inv'][ds_key]['scaled_cloud_xyz'][:]
K_nn = seg_info['inv'][ds_key]['scaled_K_nn'][:]
N, QN, NON, NR = get_exact_solver(x_nd, K_nn, bend_coefs)
solver_g['N'] = N
solver_g['QN'] = QN
solver_g['NR'] = NR
solver_g['x_nd'] = x_nd
solver_g['K_nn'] = K_nn
NON_g = solver_g.create_group('NON')
for b in bend_coefs:
NON_g[str(b)] = NON[b]
if args.verbose:
sys.stdout.write(
'\rprecomputed exact tps solver for segment {}'.format(
seg_name))
sys.stdout.flush()
print ""
f.close()
def main():
scikits.cuda.linalg.init()
args = parse_arguments()
f = h5py.File(args.datafile, 'r+')
bend_coefs = np.around(loglinspace(args.bend_coef_init, args.bend_coef_final, args.n_iter),
BEND_COEF_DIGITS)
for seg_name, seg_info in f.iteritems():
if 'inv' in seg_info:
if args.replace:
del seg_info['inv']
inv_group = seg_info.create_group('inv')
else:
inv_group = seg_info['inv']
else:
inv_group = seg_info.create_group('inv')
ds_key = 'DS_SIZE_{}'.format(DS_SIZE)
if ds_key in inv_group:
scaled_x_na = inv_group[ds_key]['scaled_cloud_xyz'][:]
K_nn = inv_group[ds_key]['scaled_K_nn'][:]
else:
ds_g = inv_group.create_group(ds_key)
x_na = downsample_cloud(seg_info[args.cloud_name][:, :3])
scaled_x_na, scale_params = unit_boxify(x_na)
K_nn = tps_kernel_matrix(scaled_x_na)
if args.fill_traj:
r_traj = seg_info['r_gripper_tool_frame']['hmat'][:, :3, 3]
l_traj = seg_info['l_gripper_tool_frame']['hmat'][:, :3, 3]
scaled_r_traj = r_traj * scale_params[0] + scale_params[1]
scaled_l_traj = l_traj * scale_params[0] + scale_params[1]
scaled_r_traj_K = tps_kernel_matrix2(scaled_r_traj, scaled_x_na)
scaled_l_traj_K = tps_kernel_matrix2(scaled_l_traj, scaled_x_na)
ds_g['scaled_r_traj'] = scaled_r_traj
ds_g['scaled_l_traj'] = scaled_l_traj
ds_g['scaled_r_traj_K'] = scaled_r_traj_K
ds_g['scaled_l_traj_K'] = scaled_l_traj_K
# Precompute l,r closing indices
lr2finger_traj = {}
for lr in 'lr':
arm_name = {"l":"leftarm", "r":"rightarm"}[lr]
lr2finger_traj[lr] = gripper_joint2gripper_l_finger_joint_values(np.asarray(seg_info['%s_gripper_joint'%lr]))[:,None]
opening_inds, closing_inds = get_opening_closing_inds(lr2finger_traj[lr])
if '%s_closing_inds'%lr in seg_info:
del seg_info['%s_closing_inds'%lr]
if not closing_inds:
closing_inds = False
seg_info['%s_closing_inds'%lr] = closing_inds
#
ds_g['cloud_xyz'] = x_na
ds_g['scaled_cloud_xyz'] = scaled_x_na
ds_g['scaling'] = scale_params[0]
ds_g['scaled_translation'] = scale_params[1]
ds_g['scaled_K_nn'] = K_nn
for bend_coef in bend_coefs:
if str(bend_coef) in inv_group:
continue
bend_coef_g = inv_group.create_group(str(bend_coef))
_, res = get_sol_params(scaled_x_na, K_nn, bend_coef)
for k, v in res.iteritems():
bend_coef_g[k] = v
if args.verbose:
sys.stdout.write('\rprecomputed tps solver for segment {}'.format(seg_name))
sys.stdout.flush()
print ""
if args.test:
atol = 1e-7
print 'Running batch get sol params test with atol = ', atol
test_batch_get_sol_params(f, [bend_coef], atol=atol)
print 'batch sol params test succeeded'
print ""
bend_coefs = np.around(loglinspace(args.exact_bend_coef_init, args.exact_bend_coef_final,
args.exact_n_iter),
BEND_COEF_DIGITS)
for seg_name, seg_info in f.iteritems():
if 'solver' in seg_info:
if args.replace:
del seg_info['solver']
solver_g = seg_info.create_group('solver')
else:
solver_g = seg_info['solver']
else:
solver_g = seg_info.create_group('solver')
x_nd = seg_info['inv'][ds_key]['scaled_cloud_xyz'][:]
K_nn = seg_info['inv'][ds_key]['scaled_K_nn'][:]
N, QN, NON, NR = get_exact_solver(x_nd, K_nn, bend_coefs)
solver_g['N'] = N
solver_g['QN'] = QN
solver_g['NR'] = NR
solver_g['x_nd'] = x_nd
solver_g['K_nn'] = K_nn
NON_g = solver_g.create_group('NON')
for b in bend_coefs:
NON_g[str(b)] = NON[b]
if args.verbose:
sys.stdout.write('\rprecomputed exact tps solver for segment {}'.format(seg_name))
sys.stdout.flush()
print ""
f.close()
