def from_matrices(labels, commute, inverse, same):
logger.info('Creating PlanReducer from matrices:\n' +
formatm('same', same, 'oppo', inverse, 'swap', commute))
pr = PlanReducer()
for i, j in iterate_indices(commute.shape):
li = labels[i]
lj = labels[j]
if commute[i, j]:
assert commute[j, i]
pr.set_commute(li, lj)
if same[i, j]:
assert same[j, i]
pr.set_same(li, lj)
if inverse[i, j]:
assert inverse[j, i]
pr.set_inverse(li, lj)
return pr
def show_compositions(self, report):
# f_ba = report.figure()
n = len(self.dds.actions)
f_ab_norm = report.figure(cols=n, caption='Norm of AB')
f_ab_phase = report.figure(cols=n, caption='Phase of AB')
f_ab_info = report.figure(cols=n, caption='Certainty of AB')
for a, b in iterate_indices((n, n)):
A = self.dds.actions[a]
B = self.dds.actions[b]
AB = DiffeoAction.compose(A, B)
norm_rgb = diffeo_to_rgb_norm(AB.diffeo.d)
phase_rgb = diffeo_to_rgb_angle(AB.diffeo.d)
info_rgb = scalaruncertainty2rgb(AB.diffeo.variance)
label = '%s-%s' % (A.label, B.label)
caption = '%s, %s' % (A.label, B.label)
f_ab_norm.data_rgb('%s_norm' % label, norm_rgb, caption=caption)
f_ab_phase.data_rgb('%s_phase' % label, phase_rgb, caption=caption)
f_ab_info.data_rgb('%s_info' % label, info_rgb, caption=caption)
def show_compositions(self, report):
# f_ba = report.figure()
n = len(self.dds.actions)
f_ab_norm = report.figure(cols=n, caption='Norm of AB')
f_ab_phase = report.figure(cols=n, caption='Phase of AB')
f_ab_info = report.figure(cols=n, caption='Certainty of AB')
for a, b in iterate_indices((n, n)):
A = self.dds.actions[a]
B = self.dds.actions[b]
AB = DiffeoAction.compose(A, B)
norm_rgb = diffeo_to_rgb_norm(AB.diffeo.d)
phase_rgb = diffeo_to_rgb_angle(AB.diffeo.d)
info_rgb = scalaruncertainty2rgb(AB.diffeo.variance)
label = '%s-%s' % (A.label, B.label)
caption = '%s, %s' % (A.label, B.label)
f_ab_norm.data_rgb('%s_norm' % label, norm_rgb, caption=caption)
f_ab_phase.data_rgb('%s_phase' % label, phase_rgb, caption=caption)
f_ab_info.data_rgb('%s_info' % label, info_rgb, caption=caption)
def from_matrices(labels, commute, inverse, same):
logger.info('Creating PlanReducer from matrices:\n' +
formatm('same', same, 'oppo', inverse, 'swap', commute))
pr = PlanReducer()
for i, j in iterate_indices(commute.shape):
li = labels[i]
lj = labels[j]
if commute[i, j]:
assert commute[j, i]
pr.set_commute(li, lj)
if same[i, j]:
assert same[j, i]
pr.set_same(li, lj)
if inverse[i, j]:
assert inverse[j, i]
pr.set_inverse(li, lj)
return pr
