def reconstruct_skel_matrix(A, k, idx):
"""
Reconstruct skeleton matrix from ID.
The skeleton matrix can be reconstructed from the original matrix `A` and its
ID rank and indices `k` and `idx`, respectively, as::
B = A[:,idx[:k]]
The original matrix can then be reconstructed via::
numpy.hstack([B, numpy.dot(B, proj)])[:,numpy.argsort(idx)]
See also :func:`reconstruct_matrix_from_id` and
:func:`reconstruct_interp_matrix`.
.. This function automatically detects the matrix data type and calls the
appropriate backend. For details, see :func:`backend.idd_copycols` and
:func:`backend.idz_copycols`.
Parameters
----------
A : :class:`numpy.ndarray`
Original matrix.
k : int
Rank of ID.
idx : :class:`numpy.ndarray`
Column index array.
Returns
-------
:class:`numpy.ndarray`
Skeleton matrix.
"""
if _is_real(A):
return backend.idd_copycols(A, k, idx + 1)
else:
return backend.idz_copycols(A, k, idx + 1)
def reconstruct_skel_matrix(A, k, idx):
"""
Reconstruct skeleton matrix from ID.
The skeleton matrix can be reconstructed from the original matrix `A` and its
ID rank and indices `k` and `idx`, respectively, as::
B = A[:,idx[:k]]
The original matrix can then be reconstructed via::
numpy.hstack([B, numpy.dot(B, proj)])[:,numpy.argsort(idx)]
See also :func:`reconstruct_matrix_from_id` and
:func:`reconstruct_interp_matrix`.
.. This function automatically detects the matrix data type and calls the
appropriate backend. For details, see :func:`backend.idd_copycols` and
:func:`backend.idz_copycols`.
Parameters
----------
A : :class:`numpy.ndarray`
Original matrix.
k : int
Rank of ID.
idx : :class:`numpy.ndarray`
Column index array.
Returns
-------
:class:`numpy.ndarray`
Skeleton matrix.
"""
if _is_real(A):
return backend.idd_copycols(A, k, idx + 1)
else:
return backend.idz_copycols(A, k, idx + 1)