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windowfunctions.cpp
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/*************************************************************************
Copyright 2011-2015 Ibrahim Sha'ath
This file is part of LibKeyFinder.
LibKeyFinder is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
LibKeyFinder is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with LibKeyFinder. If not, see <http://www.gnu.org/licenses/>.
*************************************************************************/
#include "windowfunctions.h"
namespace KeyFinder {
double WindowFunction::window(temporal_window_t windowType, int n, int N) const {
switch (windowType) {
case WINDOW_BLACKMAN:
return 0.42 - (0.5 * cos((2 * PI * n)/(N-1))) + (0.08 * cos((4 * PI * n)/(N-1)));
default:
// This should be unreachable code, but just in case fall back to hamming window.
// fall through
case WINDOW_HAMMING:
return 0.54 - (0.46 * cos((2 * PI * n)/(N-1)));
}
}
double WindowFunction::gaussianWindow(int n, int N, double sigma) const {
return exp(-1 * (pow(n - (N / 2), 2) / (2 * sigma * sigma)));
}
std::vector<double> WindowFunction::convolve(const std::vector<double>& input, const std::vector<double>& window) const {
unsigned int inputSize = input.size();
unsigned int padding = window.size() / 2;
std::vector<double> convolved(inputSize, 0.0);
// TODO: this implements zero padding for boundary effects, write something mean-based later.
for (unsigned int sample = 0; sample < inputSize; sample++) {
double convolution = 0.0;
for (unsigned int k = 0; k < window.size(); k++) {
int frm = (signed)sample - (signed)padding + (signed)k;
if (frm >= 0 && frm < (signed)inputSize) {
// don't run off either end
convolution += input[frm] * window[k] / window.size();
}
}
convolved[sample] = convolution;
}
return convolved;
}
}