/*
Copyright (C) 2001, 2006 by Simon Dixon
This program 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 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 General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program (the file gpl.txt); if not, download it from
http://www.gnu.org/licenses/gpl.txt or write to the
Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
*/
package at.ofai.music.util;
import java.util.LinkedList;
public class Peaks {
public static boolean debug = false;
public static int pre = 3;
public static int post = 1;
/** General peak picking method for finding n local maxima in an array
* @param data input data
* @param peaks list of peak indexes
* @param width minimum distance between peaks
*/
public static int findPeaks(double[] data, int[] peaks, int width) {
int peakCount = 0;
int maxp = 0;
int mid = 0;
int end = data.length;
while (mid < end) {
int i = mid - width;
if (i < 0)
i = 0;
int stop = mid + width + 1;
if (stop > data.length)
stop = data.length;
maxp = i;
for (i++; i < stop; i++)
if (data[i] > data[maxp])
maxp = i;
if (maxp == mid) {
int j;
for (j = peakCount; j > 0; j--) {
if (data[maxp] <= data[peaks[j-1]])
break;
else if (j < peaks.length)
peaks[j] = peaks[j-1];
}
if (j != peaks.length)
peaks[j] = maxp;
if (peakCount != peaks.length)
peakCount++;
}
mid++;
}
return peakCount;
} // findPeaks()
/** General peak picking method for finding local maxima in an array
* @param data input data
* @param width minimum distance between peaks
* @param threshold minimum value of peaks
* @return list of peak indexes
*/
public static LinkedList<Integer> findPeaks(double[] data, int width,
double threshold) {
return findPeaks(data, width, threshold, 0, false);
} // findPeaks()
/** General peak picking method for finding local maxima in an array
* @param data input data
* @param width minimum distance between peaks
* @param threshold minimum value of peaks
* @param decayRate how quickly previous peaks are forgotten
* @param isRelative minimum value of peaks is relative to local average
* @return list of peak indexes
*/
public static LinkedList<Integer> findPeaks(double[] data, int width,
double threshold, double decayRate, boolean isRelative) {
LinkedList<Integer> peaks = new LinkedList<Integer>();
int maxp = 0;
int mid = 0;
int end = data.length;
double av = data[0];
while (mid < end) {
av = decayRate * av + (1 - decayRate) * data[mid];
if (av < data[mid])
av = data[mid];
int i = mid - width;
if (i < 0)
i = 0;
int stop = mid + width + 1;
if (stop > data.length)
stop = data.length;
maxp = i;
for (i++; i < stop; i++)
if (data[i] > data[maxp])
maxp = i;
if (maxp == mid) {
if (overThreshold(data, maxp, width, threshold, isRelative,av)){
if (debug)
System.out.println(" peak");
peaks.add(new Integer(maxp));
} else if (debug)
System.out.println();
}
mid++;
}
return peaks;
} // findPeaks()
public static double expDecayWithHold(double av, double decayRate,
double[] data, int start, int stop) {
while (start < stop) {
av = decayRate * av + (1 - decayRate) * data[start];
if (av < data[start])
av = data[start];
start++;
}
return av;
} // expDecayWithHold()
public static boolean overThreshold(double[] data, int index, int width,
double threshold, boolean isRelative,
double av) {
if (debug)
System.out.printf("%4d : %6.3f Av1: %6.3f ",
index, data[index], av);
if (data[index] < av)
return false;
if (isRelative) {
int iStart = index - pre * width;
if (iStart < 0)
iStart = 0;
int iStop = index + post * width;
if (iStop > data.length)
iStop = data.length;
double sum = 0;
int count = iStop - iStart;
while (iStart < iStop)
sum += data[iStart++];
if (debug)
System.out.printf(" %6.3f %6.3f ", sum / count,
data[index] - sum / count - threshold);
return (data[index] > sum / count + threshold);
} else
return (data[index] > threshold);
} // overThreshold()
public static void normalise(double[] data) {
double sx = 0;
double sxx = 0;
for (int i = 0; i < data.length; i++) {
sx += data[i];
sxx += data[i] * data[i];
}
double mean = sx / data.length;
double sd = Math.sqrt((sxx - sx * mean) / data.length);
if (sd == 0)
sd = 1; // all data[i] == mean -> 0; avoids div by 0
for (int i = 0; i < data.length; i++) {
data[i] = (data[i] - mean) / sd;
}
} // normalise()
/** Uses an n-point linear regression to estimate the slope of data.
* @param data input data
* @param hop spacing of data points
* @param n length of linear regression
* @param slope output data
*/
public static void getSlope(double[] data, double hop, int n,
double[] slope) {
int i = 0, j = 0;
double t;
double sx = 0, sxx = 0, sy = 0, sxy = 0;
for ( ; i < n; i++) {
t = i * hop;
sx += t;
sxx += t * t;
sy += data[i];
sxy += t * data[i];
}
double delta = n * sxx - sx * sx;
for ( ; j < n / 2; j++)
slope[j] = (n * sxy - sx * sy) / delta;
for ( ; j < data.length - (n + 1) / 2; j++, i++) {
slope[j] = (n * sxy - sx * sy) / delta;
sy += data[i] - data[i - n];
sxy += hop * (n * data[i] - sy);
}
for ( ; j < data.length; j++)
slope[j] = (n * sxy - sx * sy) / delta;
} // getSlope()
public static double min(double[] arr) { return arr[imin(arr)]; }
public static double max(double[] arr) { return arr[imax(arr)]; }
public static int imin(double[] arr) {
int i = 0;
for (int j = 1; j < arr.length; j++)
if (arr[j] < arr[i])
i = j;
return i;
} // imin()
public static int imax(double[] arr) {
int i = 0;
for (int j = 1; j < arr.length; j++)
if (arr[j] > arr[i])
i = j;
return i;
} // imax()
} // class Peaks