Source code for thewalrus._permanent
# Copyright 2019 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Permanent Python interface
"""
import numpy as np
from ._hafnian import hafnian_repeated
from .libwalrus import perm_complex, perm_real
[docs]def perm(A, quad=True, fsum=False):
"""Returns the permanent of a matrix via the
`Ryser formula <https://en.wikipedia.org/wiki/Computing_the_permanent#Ryser_formula>`_.
For more direct control, you may wish to call :func:`perm_real`
or :func:`perm_complex` directly.
Args:
A (array): a square array.
quad (bool): If ``True``, the input matrix is cast to a ``long double``
matrix internally for a quadruple precision hafnian computation.
fsum (bool): Whether to use the ``fsum`` method for higher accuracy summation.
Note that if ``fsum`` is true, double precision will be used, and the
``quad`` keyword argument will be ignored.
Returns:
np.float64 or np.complex128: the permanent of matrix A.
"""
if not isinstance(A, np.ndarray):
raise TypeError("Input matrix must be a NumPy array.")
matshape = A.shape
if matshape[0] != matshape[1]:
raise ValueError("Input matrix must be square.")
if np.isnan(A).any():
raise ValueError("Input matrix must not contain NaNs.")
if matshape[0] == 2:
return A[0, 0] * A[1, 1] + A[0, 1] * A[1, 0]
if matshape[0] == 3:
return (
A[0, 2] * A[1, 1] * A[2, 0]
+ A[0, 1] * A[1, 2] * A[2, 0]
+ A[0, 2] * A[1, 0] * A[2, 1]
+ A[0, 0] * A[1, 2] * A[2, 1]
+ A[0, 1] * A[1, 0] * A[2, 2]
+ A[0, 0] * A[1, 1] * A[2, 2]
)
if A.dtype == np.complex:
if np.any(np.iscomplex(A)):
return perm_complex(A, quad=quad)
return perm_real(np.float64(A.real), quad=quad, fsum=fsum)
return perm_real(A, quad=quad, fsum=fsum)
[docs]def permanent_repeated(A, rpt):
r"""Calculates the permanent of matrix :math:`A`, where the ith row/column
of :math:`A` is repeated :math:`rpt_i` times.
This function constructs the matrix
.. math:: B = \begin{bmatrix} 0 & A\\ A^T & 0 \end{bmatrix},
and then calculates :math:`perm(A)=haf(B)`, by calling
>>> hafnian_repeated(B, rpt*2, loop=False)
Args:
A (array): matrix of size [N, N]
rpt (Sequence): sequence of N positive integers indicating the corresponding rows/columns
of A to be repeated.
Returns:
np.int64 or np.float64 or np.complex128: the permanent of matrix A.
"""
n = A.shape[0]
O = np.zeros([n, n])
B = np.vstack([np.hstack([O, A]), np.hstack([A.T, O])])
return hafnian_repeated(B, rpt * 2, loop=False)
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