added spectrogram plot
git-svn-id: https://svn.d4science.research-infrastructures.eu/gcube/trunk/data-analysis/EcologicalEngine@92654 82a268e6-3cf1-43bd-a215-b396298e98cf
This commit is contained in:
parent
ef44fa2376
commit
a9579a12af
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@ -0,0 +1,110 @@
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package org.gcube.contentmanagement.graphtools.plotting.graphs;
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/*
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* Copyright 1999-2004 Carnegie Mellon University.
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* Portions Copyright 2002-2004 Sun Microsystems, Inc.
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* Portions Copyright 2002-2004 Mitsubishi Electric Research Laboratories.
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* All Rights Reserved. Use is subject to license terms.
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*
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* See the file "README" for information on usage and
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* redistribution of this file, and for a DISCLAIMER OF ALL
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* WARRANTIES.
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*
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*/
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import java.util.Arrays;
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import java.awt.Color;
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public class ColorMap
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{
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public int size;
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public byte r[];
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public byte g[];
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public byte b[];
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public Color table[];
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public static ColorMap getJet()
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{
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return getJet(64);
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}
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public static ColorMap getJet(int n)
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{
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byte r[] = new byte[n];
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byte g[] = new byte[n];
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byte b[] = new byte[n];
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int maxval = 255;
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//Arrays.fill(g, 0, 8, (byte)0);
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Arrays.fill(g, 0, n/8, (byte)0);
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//for(int x = 0; x < 16; x++)
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// g[x+8] = (byte)(maxval*x/16);
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for(int x = 0; x < n/4; x++)
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g[x+n/8] = (byte)(maxval*x*4/n);
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//Arrays.fill(g, 24, 40, (byte)maxval);
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Arrays.fill(g, n*3/8, n*5/8, (byte)maxval);
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//for(int x = 0; x < 16; x++)
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// g[x+40] = (byte)(maxval-(maxval*x/16));
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for(int x = 0; x < n/4; x++)
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g[x+n*5/8] = (byte)(maxval-(maxval*x*4/n));
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//Arrays.fill(g, 56, 64, (byte)0);
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Arrays.fill(g, n*7/8, n, (byte)0);
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//for(int x = 0; x < g.length; x++)
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// b[x] = g[(x+16) % g.length];
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for(int x = 0; x < g.length; x++)
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b[x] = g[(x+n/4) % g.length];
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//Arrays.fill(b, 56, 64, (byte)0);
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Arrays.fill(b, n*7/8, n, (byte)0);
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//Arrays.fill(g, 0, 8, (byte)0);
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Arrays.fill(g, 0, n/8, (byte)0);
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//for(int x = 8; x < g.length; x++)
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// r[x] = g[(x+48) % g.length];
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for(int x = n/8; x < g.length; x++)
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r[x] = g[(x+n*6/8) % g.length];
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ColorMap cm = new ColorMap();
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cm.size = n;
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cm.r = r;
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cm.g = g;
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cm.b = b;
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cm.table = new Color[n];
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for(int x = 0; x < n; x++)
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//cm.table[x] = new Color((int)r[x]+maxval/2+1,
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//(int)g[x]+maxval/2+1, (int)b[x]+maxval/2+1);
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cm.table[x] = new Color(cm.getColor(x));
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return cm;
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}
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public int getColor(int idx)
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{
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int pixel = ((r[idx] << 16) & 0xff0000)
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| ((g[idx] << 8) & 0xff00)
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| (b[idx] & 0xff);
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return pixel;
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}
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public String toString()
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{
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StringBuffer s = new StringBuffer(500);
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for(int x = 0; x < size; x++)
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{
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s.append(x+": {"+r[x]+",\t"+g[x]+",\t"+b[x]+"}\t");
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if(x%3 == 2)
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s.append("\n");
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}
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return s.toString();
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}
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public static void main(String[] args)
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{
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ColorMap jet = getJet();
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ColorMap jet128 = getJet(128);
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System.out.println("Jet:\n"+jet+"\n\nJet128:\n"+jet128);
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}
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}
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@ -0,0 +1,191 @@
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package org.gcube.contentmanagement.graphtools.plotting.graphs;
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import java.awt.Color;
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import java.awt.Dimension;
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import java.awt.Graphics;
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import java.awt.Image;
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import java.awt.image.BufferedImage;
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import java.awt.image.FilteredImageSource;
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import java.awt.image.ImageFilter;
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import java.awt.image.ImageObserver;
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import java.awt.image.ReplicateScaleFilter;
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import javax.swing.JPanel;
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public class SpectrumPlot2 extends JPanel {
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private BufferedImage spectrogram = null;
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private Image scaledSpectrogram = null;
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private float zoom = 1.0f;
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private float vzoom = 1.0f;
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private double offsetFactor;
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private double[][] data;
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public int width;
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public int height;
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private ColorMap cmap = ColorMap.getJet(64);
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// private static float minZoom = .1f;
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private double minVal;
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private double maxVal;
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public SpectrumPlot2(double[][] dat) {
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data = dat;
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width = dat.length;
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height = dat[0].length;
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// audio.addChangeListener(new ChangeListener() {
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// public void stateChanged(ChangeEvent event) {
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// computeSpectrogram();
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// }
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// });
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computeSpectrogram();
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}
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private void computeSpectrogram() {
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try {
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// prepare the data:
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maxVal = 0;
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minVal = Integer.MAX_VALUE;
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for (int x = 0; x < width; x++) {
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for (int y = 0; y < height; y++) {
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if (data[x][y] > maxVal)
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maxVal = data[x][y];
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if (data[x][y] < minVal)
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minVal = data[x][y];
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}
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}
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double minIntensity = Math.abs(minVal);
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double maxIntensity = maxVal + minIntensity;
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int maxYIndex = height - 1;
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Dimension d = new Dimension(width, height);
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setMinimumSize(d);
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setMaximumSize(d);
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setPreferredSize(d);
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/*
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* Create the image for displaying the data.
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*/
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spectrogram = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
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/*
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* Set scaleFactor so that the maximum value, after removing the
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* offset, will be 0xff.
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*/
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double scaleFactor = ((0x3f + offsetFactor) / maxIntensity);
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for (int i = 0; i < width; i++) {
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for (int j = maxYIndex; j >= 0; j--) {
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/*
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* Adjust the grey value to make a value of 0 to mean white
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* and a value of 0xff to mean black.
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*/
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int grey = (int) ((data[i][j] + minIntensity) * scaleFactor - offsetFactor);
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// System.out.println(grey);
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// use grey as an index into the colormap;
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spectrogram.setRGB(i, maxYIndex - j, cmap.getColor(grey));
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}
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}
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ImageFilter scaleFilter = new ReplicateScaleFilter((int) (zoom * width), (int) (vzoom * height));
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scaledSpectrogram = createImage(new FilteredImageSource(spectrogram.getSource(), scaleFilter));
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Dimension sz = getSize();
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repaint(0, 0, 0, sz.width - 1, sz.height - 1);
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// ImageIO.write(ImageTools.toBufferedImage(scaledSpectrogram), "png", new File("saved.png"));
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} catch (Exception e) {
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e.printStackTrace();
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}
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}
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public void setOffsetFactor(double offsetFactor) {
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this.offsetFactor = offsetFactor;
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computeSpectrogram();
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}
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public void vzoomSet(float vzoom) {
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this.vzoom = vzoom;
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zoom();
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}
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public void hzoomSet(float zoom) {
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zoomSet(zoom);
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}
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protected void zoomSet(float zoom) {
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this.zoom = zoom;
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zoom();
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}
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public void zoom() {
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if (spectrogram != null) {
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int width = spectrogram.getWidth();
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int height = spectrogram.getHeight();
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// do the zooming
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width = (int) (zoom * width);
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height = (int) (vzoom * height);
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ImageFilter scaleFilter = new ReplicateScaleFilter(width, height);
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scaledSpectrogram = createImage(new FilteredImageSource(spectrogram.getSource(), scaleFilter));
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// so ScrollPane gets notified of the new size:
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setPreferredSize(new Dimension(width, height));
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revalidate();
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repaint();
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}
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}
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public float getVZoom() {
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return vzoom;
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}
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public float getHZoom() {
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return zoom;
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}
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public SpectrumPlot2 getColorBar() {
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int barWidth = 20;
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double[][] cb = new double[barWidth][cmap.size];
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for (int x = 0; x < cb.length; x++)
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for (int y = 0; y < cb[x].length; y++)
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cb[x][y] = y;
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return new SpectrumPlot2(cb);
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}
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public double getData(int x, int y) {
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return data[x][y];
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}
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public int getDataWidth() {
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return width;
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}
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public int getDataHeight() {
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return height;
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}
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public void paint(Graphics g) {
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Dimension sz = getSize();
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g.setColor(Color.WHITE);
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g.fillRect(0, 0, sz.width - 1, sz.height - 1);
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if (spectrogram != null) {
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g.drawImage(scaledSpectrogram, 0, 0, (ImageObserver) null);
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}
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}
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}
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@ -24,6 +24,11 @@ public class PeriodicityDetector {
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static float defaultSNratio = 0;
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static float defaultFreqError = 1f;
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public int currentSamplingRate;
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public int currentWindowShiftSamples;
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public int currentWindowAnalysisSamples;
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public double[][] currentspectrum;
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public double meanF=0;
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public double lowermeanF=0;
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public double uppermeanF=0;
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@ -38,6 +43,8 @@ public class PeriodicityDetector {
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public double endPeriodSampleIndex=0;
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public double periodicityStrength=0;
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public double minFrequency;
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public double maxFrequency;
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public String getPeriodicityStregthInterpretation(){
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if (periodicityStrength>0.6)
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@ -91,6 +98,7 @@ public class PeriodicityDetector {
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return detectFrequency(signal, false);
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}
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public double detectFrequency(double[] signal, int samplingRate, float minPossibleFreq, float maxPossibleFreq, float wantedFreqError, boolean display) throws Exception {
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// estimate the best samples based on the error we want
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@ -119,12 +127,18 @@ public class PeriodicityDetector {
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if (minPossibleFreq==0)
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minPossibleFreq = 0.1f;
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minFrequency=minPossibleFreq;
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maxFrequency=maxPossibleFreq;
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// display the signal
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if (display)
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SignalProcessing.displaySignalWithGenericTime(signal, 0, 1, "signal");
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this.currentSamplingRate = samplingRate;
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this.currentWindowShiftSamples = windowShiftSamples;
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this.currentWindowAnalysisSamples = windowAnalysisSamples;
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// trace spectrum
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double[][] spectrum = SignalConverter.spectrogram("spectogram", signal, samplingRate, windowShiftSamples, windowAnalysisSamples, false);
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double[][] spectrum = SignalConverter.spectrogram("spectrogram", signal, samplingRate, windowShiftSamples, windowAnalysisSamples, false);
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if (display)
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SignalConverter.displaySpectrogram(spectrum, signal, "complete spectrogram", samplingRate, windowShiftSamples, windowAnalysisSamples);
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// apply the bandpass filter
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@ -136,7 +150,7 @@ public class PeriodicityDetector {
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SignalConverter signalMaximumAnalyzer = new SignalConverter();
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double[] maxfrequencies = signalMaximumAnalyzer.takeMaxFrequenciesInSpectrogram(spectrum, samplingRate, windowAnalysisSamples, minPossibleFreq);
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double[] powers = signalMaximumAnalyzer.averagepower;
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currentspectrum=spectrum;
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// display the maximum freqs
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AnalysisLogger.getLogger().debug("Number of frequency peaks " + maxfrequencies.length);
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// take the longest stable sequence of frequencies
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@ -83,10 +83,10 @@ public class SignalConverter {
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return cepc;
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}
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public static BufferedImage createImage(JPanel panel) {
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public static BufferedImage createImage(JPanel panel, int w, int h) {
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int w = panel.getWidth();
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int h = panel.getHeight();
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// int w = panel.getWidth();
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// int h = panel.getHeight();
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BufferedImage bi = new BufferedImage(w, h, BufferedImage.TYPE_INT_RGB);
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Graphics2D g = bi.createGraphics();
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panel.paint(g);
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@ -277,6 +277,7 @@ public class SignalConverter {
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* File(name+".png"));
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*/
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// Thread.sleep(2000);
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// createImage(spec);
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}
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return spectrum;
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}
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@ -1,5 +1,7 @@
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package org.gcube.dataanalysis.ecoengine.signals;
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import java.awt.Image;
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import java.awt.image.BufferedImage;
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import java.io.BufferedReader;
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import java.io.File;
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import java.io.FileReader;
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@ -8,12 +10,18 @@ import java.util.Arrays;
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import java.util.Date;
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import java.util.List;
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import marytts.signalproc.display.SpectrogramCustom;
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import marytts.signalproc.window.Window;
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import org.gcube.contentmanagement.graphtools.data.BigSamplesTable;
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import org.gcube.contentmanagement.graphtools.data.conversions.ImageTools;
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import org.gcube.contentmanagement.graphtools.plotting.graphs.NumericSeriesGraph;
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import org.gcube.contentmanagement.graphtools.plotting.graphs.SpectrumPlot2;
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import org.gcube.contentmanagement.graphtools.plotting.graphs.TimeSeriesGraph;
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import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
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import org.gcube.contentmanagement.lexicalmatcher.utils.MathFunctions;
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import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
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import org.jfree.chart.JFreeChart;
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import org.jfree.data.time.FixedMillisecond;
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import org.jfree.data.time.TimeSeriesCollection;
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import org.jfree.data.xy.XYSeriesCollection;
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@ -110,6 +118,58 @@ public class SignalProcessing {
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nsg.render(collection);
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}
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public static Image renderSignalWithGenericTime(double[] signal, float t0, float timeshift, String name) {
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org.jfree.data.xy.XYSeries xyseries = new org.jfree.data.xy.XYSeries(name);
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float time = t0;
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for (int i = 0; i < signal.length; i++) {
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xyseries.add(time, signal[i]);
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time = time + timeshift;
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}
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XYSeriesCollection collection = new XYSeriesCollection(xyseries);
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JFreeChart chart = NumericSeriesGraph.createStaticChart(collection);
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Image image = ImageTools.toImage(chart.createBufferedImage(680, 420));
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return image;
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}
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public static Image renderSignalWithGenericTime(double[] signal, double [] timeline, String name) {
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org.jfree.data.xy.XYSeries xyseries = new org.jfree.data.xy.XYSeries(name);
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for (int i = 0; i < signal.length; i++) {
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xyseries.add(timeline[i], signal[i]);
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}
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XYSeriesCollection collection = new XYSeriesCollection(xyseries);
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JFreeChart chart = NumericSeriesGraph.createStaticChart(collection);
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Image image = ImageTools.toImage(chart.createBufferedImage(680, 420));
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return image;
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}
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public static Image renderSignalSpectrogram(double[] signal, double [] timeline, int samplingRate, int frameslength, int windowshift) {
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SpectrogramCustom spec = new SpectrogramCustom(signal, samplingRate, Window.get(Window.HAMMING, frameslength), windowshift, frameslength, 640, 480);
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double[][] spectrum = spec.spectra.toArray(new double[spec.spectra.size()][]);
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spec.setZoomX(640d/(double)spectrum.length);
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BufferedImage image = SignalConverter.createImage(spec,640,480);
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return ImageTools.toImage(image);
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}
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public static Image renderSignalSpectrogram2(double[][] spectrogram) {
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SpectrumPlot2 spectrumPlot = new SpectrumPlot2(spectrogram);
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AnalysisLogger.getLogger().debug("Spectrum W:"+spectrumPlot.width);
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AnalysisLogger.getLogger().debug("Spectrum H:"+spectrumPlot.height);
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// spectrumPlot.hzoomSet(2f);
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spectrumPlot.hzoomSet(640f/(float)spectrumPlot.width);
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spectrumPlot.vzoomSet(480f/(float)spectrumPlot.height);
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/*
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ApplicationFrame app = new ApplicationFrame("Spectrogram ");
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app.setContentPane(spectrumPlot);
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app.pack();
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app.setVisible(true);
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*/
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BufferedImage image = SignalConverter.createImage(spectrumPlot,640,480);
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return ImageTools.toImage(image);
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}
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public static void displaySignalWithTime(double[] signal, Date[] dates, String name, String format) {
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org.jfree.data.time.TimeSeries series = new org.jfree.data.time.TimeSeries(name);
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for (int i = 0; i < signal.length; i++)
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Reference in New Issue