polymerist.maths.linearalg.decomposition

Tools for matrix decomposition

Functions

`diagonalize`(→ tuple[numpy.ndarray])	Diagonalize a matrix into it's eigenbasis. Return rotation and diagonal matrices P, D, and P^-1
`inv_left`(...)	Return the left-inverse of an arbitrary (not necessarily square) matrix
`inv_right`(...)	Return the right-inverse of an arbitrary (not necessarily square) matrix

polymerist.maths.linearalg.decomposition.diagonalize(matrix: numpy.ndarray) → tuple[numpy.ndarray][source]: Diagonalize a matrix into it’s eigenbasis. Return rotation and diagonal matrices P, D, and P^-1

polymerist.maths.linearalg.decomposition.inv_left(matrix: numpy.ndarray[polymerist.genutils.typetools.numpytypes.Shape[polymerist.genutils.typetools.numpytypes.M, polymerist.genutils.typetools.numpytypes.N], polymerist.genutils.typetools.numpytypes.DType]) → numpy.ndarray[polymerist.genutils.typetools.numpytypes.Shape[polymerist.genutils.typetools.numpytypes.N, polymerist.genutils.typetools.numpytypes.M], polymerist.genutils.typetools.numpytypes.DType][source]: Return the left-inverse of an arbitrary (not necessarily square) matrix

polymerist.maths.linearalg.decomposition.inv_right(matrix: numpy.ndarray[polymerist.genutils.typetools.numpytypes.Shape[polymerist.genutils.typetools.numpytypes.M, polymerist.genutils.typetools.numpytypes.N], polymerist.genutils.typetools.numpytypes.DType]) → numpy.ndarray[polymerist.genutils.typetools.numpytypes.Shape[polymerist.genutils.typetools.numpytypes.N, polymerist.genutils.typetools.numpytypes.M], polymerist.genutils.typetools.numpytypes.DType][source]: Return the right-inverse of an arbitrary (not necessarily square) matrix