def test_checks(self):
R = np.zeros((10, 10))
fail("rotation_matrix", R)
R = random_rotation()
R[0, 2] += R[0, 1]
fail("rotation_matrix", R)
R = random_rotation()
R *= 2
fail("rotation_matrix", R)
def test_checks(self):
R = np.zeros((10, 10))
fail('rotation_matrix', R)
R = random_rotation()
R[0, 2] += R[0, 1]
fail('rotation_matrix', R)
R = random_rotation()
R *= 2
fail('rotation_matrix', R)
def test_checks(self):
if not self.is_contracts_active():
return
R = np.zeros((10, 10))
fail('rotation_matrix', R)
R = random_rotation()
R[0, 2] += R[0, 1]
fail('rotation_matrix', R)
R = random_rotation()
R *= 2
fail('rotation_matrix', R)
def test_checks(self):
if not self.is_contracts_active():
return
R = np.zeros((10, 10))
fail('rotation_matrix', R)
R = random_rotation()
R[0, 2] += R[0, 1]
fail('rotation_matrix', R)
R = random_rotation()
R *= 2
fail('rotation_matrix', R)
def compute_performer_start(self) -> Dict[str, Dict[str, float]]:
"""Compute the starting location (position & rotation) for the performer. Must return the same thing on
multiple calls. This default implementation chooses a random location."""
if self._performer_start is None:
self._performer_start = {
'position': {
'x': geometry.random_position(),
'y': 0,
'z': geometry.random_position()
},
'rotation': {
'y': geometry.random_rotation()
}
}
return self._performer_start
def best_similarity_transform_test():
N = 20
for K in [3]: # TODO: multiple dimensions
X = np.random.randn(K, N)
R = random_rotation()
# R = np.eye(K)
t = np.random.randn(K, 1)
# print 'R: %s' % R
# print 't: %s' % t
Y = np.dot(R, X) + t
R2, t2 = best_similarity_transform(X, Y)
# print 'R2: %s' % R2
# print 't2: %s' % t2
Y2 = np.dot(R2, X) + t2
assert_allclose(R, R2, atol=1e-10)
assert_allclose(t, t2)
assert_allclose(Y, Y2)
def best_similarity_transform_test():
N = 20
for K in [3]: # TODO: multiple dimensions
X = np.random.randn(K, N)
R = random_rotation()
# R = np.eye(K)
t = np.random.randn(K, 1)
# print 'R: %s' % R
# print 't: %s' % t
Y = np.dot(R, X) + t
R2, t2 = best_similarity_transform(X, Y)
# print 'R2: %s' % R2
# print 't2: %s' % t2
Y2 = np.dot(R2, X) + t2
assert_allclose(R, R2, atol=1e-10)
assert_allclose(t, t2)
assert_allclose(Y, Y2)
def test_random_rotations(self):
for i in range(N): #@UnusedVariable
random_rotation()
def rotations_sequence():
yield np.eye(3)
# TODO: add special values
for i in range(N): # @UnusedVariable
yield random_rotation()
def test_random_rotations(self):
for i in range(N): # @UnusedVariable
random_rotation()
def best_orthogonal_transform_test1():
X = random_directions(20)
R = random_rotation()
Y = np.dot(R, X)
R2 = best_orthogonal_transform(X, Y)
assert_allclose(R, R2)
def closest_orthogonal_matrix_test1():
R = random_rotation()
R2 = closest_orthogonal_matrix(R)
assert_allclose(R, R2)
def best_orthogonal_transform_test1():
X = random_directions(20)
R = random_rotation()
Y = np.dot(R, X)
R2 = best_orthogonal_transform(X, Y)
assert_allclose(R, R2)
def closest_orthogonal_matrix_test1():
R = random_rotation()
R2 = closest_orthogonal_matrix(R)
assert_allclose(R, R2)
def rotations_sequence():
yield np.eye(3)
# TODO: add special values
for i in range(N): # @UnusedVariable
yield random_rotation()
