def test_scaling_transform_inverse_known_values(self):
"""
ScalingTransform.inverse should return known result with known input
for scaling transformations.
"""
src = SCALING_KNOWN_VALUES[0][-1]
for rotation, scale, _, translation, dst in SCALING_KNOWN_VALUES:
tform = ScalingTransform(rotation=rotation, scale=scale,
translation=translation).inverse()
numpy.testing.assert_array_almost_equal(src, tform.apply(dst))
def test_scaling_transform_matrix_known_values(self):
for rotation, scale, shear, _, _ in SCALING_KNOWN_VALUES:
tform = ScalingTransform(rotation=rotation, scale=scale)
R = _rotation_matrix_from_angle(rotation)
S = scale * numpy.eye(2)
matrix = numpy.dot(R, S)
numpy.testing.assert_array_almost_equal(matrix, tform.transformation_matrix)
def test_scaling_transform_from_pointset_non_negative_scaling(self):
"""
ScalingTransform.from_pointset should not return a negative value for
the scaling when there is a reflection in the point set for scaling
transformations.
"""
src = numpy.array([(0., 0.), (1., 0.), (0., 2.)])
dst = numpy.array([(0., 0.), (-1., 0.), (0., 2.)])
tform = ScalingTransform.from_pointset(src, dst)
self.assertTrue(numpy.all(tform.scale > 0.))
def test_scaling_transform_from_pointset_known_values(self):
"""
ScalingTransform.from_pointset should return known result with known
input for scaling transformations.
"""
src = SCALING_KNOWN_VALUES[0][-1]
for rotation, scale, _, translation, dst in SCALING_KNOWN_VALUES:
tform = ScalingTransform.from_pointset(src, dst)
self.assertAlmostEqual(0., _angle_diff(rotation, tform.rotation))
numpy.testing.assert_array_almost_equal(scale, tform.scale)
numpy.testing.assert_array_almost_equal(translation, tform.translation)