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ImageJ is an open source Java image processing program inspired by NIH Image for the Macintosh.

There is a newer version: 1.54m

package ij.plugin;
import ij.*;
import ij.gui.*;
import ij.process.*;
import ij.plugin.PlugIn;
import ij.measure.*;
import ij.util.Tools;
import java.util.*;
import java.awt.*;
import java.awt.event.*;
import java.util.Vector;

/**
This plugin implements the Analyze/Distribution command.
It reads the data from the ResultsTable and plots a frequency histogram.
@author G. Landini at bham. ac. uk
*/
public class Distribution implements PlugIn, TextListener {
	static String parameter = "Area";
	static boolean autoBinning = true;
	static int nBins = 10;
	static String range = "0-0";
	Checkbox checkbox;
	TextField nBinsField, rangeField;
	String defaultNBins, defaultRange;

	public void run(String arg) {
		ResultsTable rt=ResultsTable.getResultsTable();
		int count = rt.size();
		if (count==0) {
			IJ.error("Distribution", "The \"Results\" table is empty");
			return;
		}
		String head= rt.getColumnHeadings();
		//IJ.log(head);

		StringTokenizer t = new StringTokenizer(head, "\t");
		int tokens = t.countTokens()-1;
		String[] strings = new String[tokens];
		strings[0] = t.nextToken(); // first token is empty?
	   	for(int i=0; i=0)
			data = rt.getColumn(index);
		if (data==null) {
			IJ.error("Distribution", "No available results: \""+parameter+"\"");
			return;
		}

		float [] pars = new float [11];
		stats(count, data, pars);
		if (autoBinning) {
			//sd = 7, min = 3, max = 4
			// use Scott's method (1979 Biometrika, 66:605-610) for optimal binning: 3.49*sd*N^-1/3
			float binWidth = (float)(3.49 * pars[7]*(float)Math.pow((float)count, -1.0/3.0));
			nBins= (int)Math.floor(((pars[4]-pars[3])/binWidth)+.5);
			if (nBins<2) nBins = 2;
		}

		ImageProcessor ip = new FloatProcessor(count, 1, data, null);
		ImagePlus imp = new ImagePlus("", ip);
		ImageStatistics stats = new StackStatistics(imp, nBins, nMin, nMax);
		int maxCount = 0;
		for (int i=0; imaxCount)
				maxCount = stats.histogram[i];
		}
		stats.histYMax = maxCount;
		new HistogramWindow(parameter+" Distribution", imp, stats);
	}
	
	int getIndex(String[] strings) {
		for (int i=0; imax) max = data[i];
		}

		ave = totl/nc;

		for(i=0;i 0){
			skew = (float)skew / (nc * (float) Math.pow(sdev,3));
			kurt = (float)kurt / (nc * (float) Math.pow(var, 2)) - 3;
		}
		pars[1]=(float) nc;
		pars[2]=totl;
		pars[3]=min;
		pars[4]=max;
		pars[5]=ave;
		pars[6]=adev;
		pars[7]=sdev;
		pars[8]=var;
		pars[9]=skew;
		pars[10]=kurt;

	}

}