ddf.minim.analysis.WindowFunction Maven / Gradle / Ivy
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/*
* Copyright (c) 2007 - 2008 by Damien Di Fede
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU Library General Public License as published
* by the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program 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 Library General Public License for more details.
*
* You should have received a copy of the GNU Library General Public
* License along with this program; if not, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
package ddf.minim.analysis;
/**
* A Window function represents a curve which is applied to a sample buffer to
* reduce the introduction of spectral leakage in the Fourier transform.
*
*
* Windowing
*
* Windowing is the process of shaping the audio samples before transforming
* them to the frequency domain. The Fourier Transform assumes the sample buffer
* is is a repetitive signal, if a sample buffer is not truly periodic within
* the measured interval sharp discontinuities may arise that can introduce
* spectral leakage. Spectral leakage is the speading of signal energy across
* multiple FFT bins. This "spreading" can drown out narrow band signals and
* hinder detection.
*
* A windowing
* function attempts to reduce spectral leakage by attenuating the measured
* sample buffer at its end points to eliminate discontinuities. If you call the
* window() function with an appropriate WindowFunction, such as
* HammingWindow(), the sample buffers passed to the object for
* analysis will be shaped by the current window before being transformed. The
* result of using a window is to reduce the leakage in the spectrum somewhat.
*
* WindowFunction handles work associated with various window
* functions such as the Hamming window. To create your own window function you
* must extend WindowFunction and implement the
* {@link #value(int, int) value} method which defines the shape of the window
* at a given offset. WindowFunction will call this method to apply
* the window to a sample buffer. The number passed to the method is an offset
* within the length of the window curve.
*
* @author Damien Di Fede
* @author Corban Brook
*
*/
public abstract class WindowFunction {
/** The double value of 2*PI. Provided as a convenience for subclasses. */
protected static final double TWO_PI = (double) (2 * Math.PI);
protected int length;
public WindowFunction() {
}
/**
* Apply the window function to a sample buffer.
*
* @param samples
* a sample buffer
*/
public void apply(double[] samples) {
this.length = samples.length;
for (int n = 0; n < samples.length; n++) {
samples[n] *= value(samples.length, n);
}
}
/**
* Apply the window to a portion of this sample buffer, given an offset from
* the beginning of the buffer and the number of samples to be windowed.
*/
public void apply(double[] samples, int offset, int length) {
this.length = length;
for (int n = offset; n < offset + length; ++n) {
samples[n] *= value(length, n - offset);
}
}
/**
* Generates the curve of the window function.
*
* @param length
* the length of the window
* @return the shape of the window function
*/
public double[] generateCurve(int length) {
double[] samples = new double[length];
for (int n = 0; n < length; n++) {
samples[n] = 1f * value(length, n);
}
return samples;
}
protected abstract double value(int length, int index);
}