def idzr_rsvd(m, n, matveca, matvec, k):
"""
Compute SVD of a complex matrix to a specified rank using random
matrix-vector multiplication.
:param m:
Matrix row dimension.
:type m: int
:param n:
Matrix column dimension.
:type n: int
:param matveca:
Function to apply the matrix adjoint to a vector, with call signature
`y = matveca(x)`, where `x` and `y` are the input and output vectors,
respectively.
:type matveca: function
:param matvec:
Function to apply the matrix to a vector, with call signature
`y = matvec(x)`, where `x` and `y` are the input and output vectors,
respectively.
:type matvec: function
:param k:
Rank of SVD.
:type k: int
:return:
Left singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Right singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Singular values.
:rtype: :class:`numpy.ndarray`
"""
U, V, S, ier = _id.idzr_rsvd(m, n, matveca, matvec, k)
if ier:
raise _RETCODE_ERROR
return U, V, S
def idzr_rsvd(m, n, matveca, matvec, k):
"""
Compute SVD of a complex matrix to a specified rank using random
matrix-vector multiplication.
:param m:
Matrix row dimension.
:type m: int
:param n:
Matrix column dimension.
:type n: int
:param matveca:
Function to apply the matrix adjoint to a vector, with call signature
`y = matveca(x)`, where `x` and `y` are the input and output vectors,
respectively.
:type matveca: function
:param matvec:
Function to apply the matrix to a vector, with call signature
`y = matvec(x)`, where `x` and `y` are the input and output vectors,
respectively.
:type matvec: function
:param k:
Rank of SVD.
:type k: int
:return:
Left singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Right singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Singular values.
:rtype: :class:`numpy.ndarray`
"""
U, V, S, ier = _id.idzr_rsvd(m, n, matveca, matvec, k)
if ier:
raise _RETCODE_ERROR
return U, V, S