#
#------------------------------------------------------------------------------
# Copyright (c) 2013-2014, Christian Therien
#
# 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.
#------------------------------------------------------------------------------
#
# fns.py - This file is part of the PySptools package.
#
"""
corr, cov functions
"""
from __future__ import division
import numpy as np
[docs]def corr(M):
"""
Compute the sample autocorrelation matrix of a 2D matrix.
Parameters:
M: `numpy array`
2d matrix of HSI data (N x p)
Returns: `numpy array`
Sample autocorrelation matrix.
"""
N = M.shape[0]
return np.dot(M, M.T) / N
[docs]def cov(M):
"""
Compute the sample covariance matrix of a 2D matrix.
Parameters:
M: `numpy array`
2d matrix of HSI data (N x p)
Returns: `numpy array`
sample covariance matrix
"""
N = M.shape[0]
u = M.mean(axis=0)
M = M - np.kron(np.ones((N, 1)), u)
C = np.dot(M.T, M) / (N-1)
return C