def transformation_matrix(self, matrix):
R, S = qrp(matrix)
s = numpy.diag(S)
if not numpy.allclose(S, numpy.diag(s)):
raise LinAlgError('Array must be diagonal')
self.rotation_matrix = R
self.scale = s
def alt_transformation_matrix_to_implicit(
matrix: numpy.ndarray, form: str,
) -> Tuple[numpy.ndarray, float, float]:
"""
Return an alternative description of the implicit parameters given a
transformation matrix. This implementation is provided for backwards
compatibility. Do not use for new design.
Parameters
----------
matrix : ndarray
The transformation matrix.
form : {"RSU", "RSL"}
Whether the matrix is of the form `RSU` or `RSL`.
Returns
-------
scale : (sx, sy) as ndarray
x, y scale factors.
rotation : float
Roation angle in counter-clockwise direction as radians.
shear : float
Shear factor.
"""
if form == "RSU":
R, SU = qrp(matrix)
scale = numpy.diag(SU)
rotation = _rotation_matrix_to_angle(R)
shear = SU[0, 1] / SU[0, 0]
elif form == "RSL":
R, SL = qlp(matrix)
scale = numpy.diag(SL)
rotation = _rotation_matrix_to_angle(R)
shear = SL[1, 0] / SL[1, 1]
else:
raise ValueError("`form` must be either 'RSU' or 'RSL'")
return scale, rotation, shear
def transformation_matrix(self, matrix):
R, S = qrp(matrix)
self.rotation_matrix = R
self.scale = numpy.diag(S)
self.shear = S[0, 1] / S[0, 0]