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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 boolean showStats = false;
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.getCounter();
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<tokens; i++)
strings[i] = t.nextToken();
defaultNBins = ""+nBins;
defaultRange = range;
GenericDialog gd = new GenericDialog("Distribution");
gd.addChoice("Parameter: ", strings, strings[getIndex(strings)]);
gd.addMessage("Data points: "+ count);
gd.addCheckbox("Automatic binning", autoBinning);
gd.addNumericField ("or specify bins:", nBins, 0);
gd.addStringField ("and range:", range);
//gd.addCheckbox("Log Statistics", showStats);
Vector v = gd.getNumericFields();
nBinsField = (TextField)v.elementAt(0);
nBinsField.addTextListener(this);
v = gd.getStringFields();
rangeField = (TextField)v.elementAt(0);
rangeField.addTextListener(this);
checkbox = (Checkbox)(gd.getCheckboxes().elementAt(0));
gd.showDialog();
if (gd.wasCanceled())
return;
parameter = gd.getNextChoice ();
autoBinning = gd.getNextBoolean();
double nMin=0.0, nMax=0.0;
if (!autoBinning) {
nBins = (int)gd.getNextNumber();
range = gd.getNextString();
String[] minAndMax = Tools.split(range, " -");
nMin = Tools.parseDouble(minAndMax[0]);
nMax = minAndMax.length==2?Tools.parseDouble(minAndMax[1]):Double.NaN;
if (Double.isNaN(nMin) || Double.isNaN(nMax))
{nMin=0.0; nMax=0.0; range="0-0";}
}
//boolean showStats = gd.getNextBoolean();
//int nBins =5;
float[] data = rt.getColumn(rt.getColumnIndex(parameter));
float [] pars = new float [11];
stats(count, data, pars);
if (showStats) {
IJ.log("Param: "+parameter);
IJ.log("Data: "+ pars[1]);
IJ.log("Sum: "+pars[2]);
IJ.log("Min: "+pars[3]);
IJ.log("Max: "+pars[4]);
IJ.log("Mean: "+pars[5]);
IJ.log("AvDev: "+pars[6]);
IJ.log("StDev: "+pars[7]);
IJ.log("Var: "+pars[8]);
IJ.log("Skew: "+pars[9]);
IJ.log("Kurt: "+pars[10]);
IJ.log(" ");
}
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; i<stats.histogram.length; i++) {
if (stats.histogram[i]>maxCount)
maxCount = stats.histogram[i];
}
stats.histYMax = maxCount;
new HistogramWindow(parameter+" Distribution", imp, stats);
}
int getIndex(String[] strings) {
for (int i=0; i<strings.length; i++) {
if (strings[i].equals(parameter))
return i;
}
return 0;
}
public void textValueChanged(TextEvent e) {
if (!defaultNBins.equals(nBinsField.getText()))
checkbox.setState(false);
if (!defaultRange.equals(rangeField.getText()))
checkbox.setState(false);
}
void stats(int nc, float [] data, float [] pars){
// ("\tPoints\tEdges_n\tGraph_Length\tMin\tMax\tMean\tAvDev\tSDev\tVar\tSkew\tKurt");
int i;
float s = 0, min = Float.MAX_VALUE, max = -Float.MAX_VALUE, totl=0, ave=0, adev=0, sdev=0, var=0, skew=0, kurt=0, p;
for(i=0;i<nc;i++){
totl+= data[i];
//tot& = tot& + 1
if(data[i]<min) min = data[i];
if(data[i]>max) max = data[i];
}
ave = totl/nc;
for(i=0;i<nc;i++){
s = data[i] - ave;
adev+=Math.abs(s);
p = s * s;
var+= p;
p*=s;
skew+= p;
p*= s;
kurt+= p;
}
adev/= nc;
var/=nc-1;
sdev = (float) Math.sqrt(var);
if(var> 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;
}
}
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