def get_data(prefix, part_rangestart, finalize, debug_run): # pylint: disable=too-many-branches
"""Get the data."""
rangestart = part_rangestart
rangeend = 10 if part_rangestart == 0 else part_rangestart + 3
train_f = h5py.File(
path.join(DIRECT3D_DATA_FP, '91', '500', prefix, 'train.hdf5'))
train_dset = train_f['2dto3d']
if debug_run:
train_dta = np.array(train_dset[:10000])
else:
train_dta = np.array(train_dset)
preprocess(train_dta)
#add_noise(train_dta)
val_f = h5py.File(
path.join(DIRECT3D_DATA_FP, '91', '500', prefix, 'val.hdf5'))
val_dset = val_f['2dto3d']
if debug_run:
val_dta = np.array(val_dset[:10])
else:
val_dta = np.array(val_dset)
preprocess(val_dta)
if finalize:
train_dta = np.vstack((train_dta, val_dta))
val_f = h5py.File(
path.join(DIRECT3D_DATA_FP, '91', '500', prefix, 'test.hdf5'))
val_dset = val_f['2dto3d']
if debug_run:
val_dta = np.array(val_dset[:10])
else:
val_dta = np.array(val_dset)
preprocess(val_dta)
train_annot = train_dta[:, 182 + rangestart:182 + rangeend]
val_annot = val_dta[:, 182 + rangestart:182 + rangeend]
rel_ids = create_featseltuple(lmset_to_use[(rangestart, rangeend)])
train_dta = train_dta[:, rel_ids]
val_dta = val_dta[:, rel_ids]
if rangestart > 0 and rangestart < 82:
train_annot = axis_angle_to_matrix(train_annot)
val_annot = axis_angle_to_matrix(val_annot)
return train_dta, train_annot, val_dta, val_annot
def test_matrix_cycle(self):
"""Test cycling from axis angle through matrix through versor back."""
np.random.seed(1)
angles = self._create_test_axis_angle_matrix()
mat = conversions.axis_angle_to_matrix(angles)
vers = conversions.matrix_to_versor(mat)
angles_res = conversions.versor_to_axis_angle_ipr(vers)
'''
for idx in range(1000):
if not np.allclose(angles[idx], angles_res[idx]):
print(idx)
'''
self.assertTrue(np.allclose(angles, angles_res))
def test_multitarget(self):
"""Test multiple prediction target functionality."""
#np.seterr(all='raise')
angles = self._create_test_axis_angle_matrix(n_angles=2)
mat = conversions.axis_angle_to_matrix(angles)
dta = np.random.uniform(size=(1000, 5))
from rotation_forest import RotationForest
rf = RotationForest(n_jobs=2) # pylint: disable=invalid-name
rf.fit(dta, mat)
res = rf.predict(dta)
import cPickle as pickle
pstr = pickle.dumps(rf)
nf = pickle.loads(pstr) # pylint: disable=invalid-name
self.assertTrue(np.all(nf.predict(dta) == res))
def test_matrix_projection(self):
"""Test the manifold projection."""
np.random.seed(1)
angles = self._create_test_axis_angle_matrix()
mat = conversions.axis_angle_to_matrix(angles)
n_failed = 0
for matrix_id, matrix in enumerate(mat): # pylint: disable=unused-variable
self.assertTrue(
np.allclose(np.linalg.det(matrix.reshape((3, 3))), 1.))
"""
if not np.allclose(np.dot(matrix.reshape((3, 3)),
matrix.reshape((3, 3)).T),
np.eye(3), atol=1e-6):
print np.dot(matrix.reshape((3, 3)), matrix.reshape((3, 3)).T), matrix_id
"""
self.assertTrue(
np.allclose(np.dot(matrix.reshape((3, 3)),
matrix.reshape((3, 3)).T),
np.eye(3),
atol=1e-6))
# Perturb.
offs = np.random.normal()
idx = np.random.randint(low=0, high=9)
matrix[idx] += offs
# Recover.
try:
rec, dist = conversions.project_to_rot(matrix) # pylint: disable=unused-variable
self.assertTrue(
np.allclose(np.linalg.det(rec.reshape((3, 3))),
1.,
atol=1e-5))
"""
if not np.allclose(np.dot(rec.reshape((3, 3)),
rec.reshape((3, 3)).T),
np.eye(3), atol=1e-6):
print np.dot(rec.reshape((3, 3)),
rec.reshape((3, 3)).T), matrix_id
"""
self.assertTrue(
np.allclose(np.dot(rec.reshape((3, 3)),
rec.reshape((3, 3)).T),
np.eye(3),
atol=1e-6))
except: # pylint: disable=bare-except
n_failed += 1
self.assertEqual(n_failed, 56)
def test_opencv_rodrigues(self):
"""Test the manifold projection."""
import cv2
np.random.seed(1)
angles = self._create_test_axis_angle_matrix()
mat = conversions.axis_angle_to_matrix(angles)
n_failed = 0
for matrix_id, matrix in enumerate(mat): # pylint: disable=unused-variable
self.assertTrue(
np.allclose(np.linalg.det(matrix.reshape((3, 3))), 1.))
"""
if not np.allclose(np.dot(matrix.reshape((3, 3)),
matrix.reshape((3, 3)).T),
np.eye(3), atol=1e-6):
print np.dot(matrix.reshape((3, 3)), matrix.reshape((3, 3)).T), matrix_id
"""
self.assertTrue(
np.allclose(np.dot(matrix.reshape((3, 3)),
matrix.reshape((3, 3)).T),
np.eye(3),
atol=1e-6))
# Perturb.
offs = np.random.normal()
idx = np.random.randint(low=0, high=9)
matrix[idx] += offs
# Recover.
rec = cv2.Rodrigues(cv2.Rodrigues(matrix.reshape((3, 3)))[0])[0] # pylint: disable=unused-variable
self.assertTrue(
np.allclose(np.linalg.det(rec.reshape((3, 3))), 1., atol=1e-5))
"""
if not np.allclose(np.dot(rec.reshape((3, 3)),
rec.reshape((3, 3)).T),
np.eye(3), atol=1e-6):
print np.dot(rec.reshape((3, 3)),
rec.reshape((3, 3)).T), matrix_id
"""
self.assertTrue(
np.allclose(np.dot(rec.reshape((3, 3)),
rec.reshape((3, 3)).T),
np.eye(3),
atol=1e-6))