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Copy pathutils.py
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102 lines (74 loc) · 2.09 KB
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# Copyright 2016 Intel Corporation
#
# 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.
import numpy as np
import logging
"""
Some utility functions that can be used by different algorithms
"""
def from_tri_2_sym(tri, dim):
"""convert a upper triangular matrix in 1D format
to 2D symmetric matrix
Parameters
----------
tri: 1D array
Contains elements of upper triangular matrix
dim : int
The dimension of target matrix.
Returns
-------
symm : 2D array
Symmetric matrix in shape=[dim, dim]
"""
symm = np.zeros((dim, dim))
symm[np.triu_indices(dim)] = tri
return symm
def from_sym_2_tri(symm):
"""convert a 2D symmetric matrix to an upper
triangular matrix in 1D format
Parameters
----------
symm : 2D array
Symmetric matrix
Returns
-------
tri: 1D array
Contains elements of upper triangular matrix
"""
inds = np.triu_indices_from(symm)
tri = symm[inds]
return tri
def fast_inv(a):
"""to invert a 2D matrix
Parameters
----------
a : 2D array
Returns
-------
inva: 2D array
inverse of input matrix a
Raises
-------
LinAlgError
If a is singular or not square
"""
if a.ndim != 2:
raise TypeError("Input matrix should be 2D array")
identity = np.identity(a.shape[1], dtype=a.dtype)
inva = None
try:
inva = np.linalg.solve(a, identity)
return inva
except np.linalg.linalg.LinAlgError:
logging.exception('Error from np.linalg.solve')
raise