JMSL Chart Guide: Dendrogram Chart

JMSL Chart Programmer's Guide

Charting 2D Types >> Dendrogram Chart

Dendrogram Chart

A dendrogram chart is a graphical way to display results from hierarchical cluster analysis. This section describes the construction of a dendrogram chart.

Example

The data for this example is grouped into clusters using the Dissimilarities and ClusterHierarchical classes. A Dendrogram node is then created as a child of an axis node. The Dendrogram constructor requires input values from the ClusterHierarchical object.

The setLables and setLineColor methods are used to customize the look of the chart. Labels are provided in a String array in the order of the input data and sorted by the Dendrogram object to match the output order. Clusters are grouped by color based on the number of elements in the array passed to the setLineColor method.

(Download Code)

import com.imsl.stat.*;
import com.imsl.chart.*;

public class SampleDendrogram extends javax.swing.JApplet {
    private JPanelChart panel;

    public void init() {
        Chart chart = new Chart(this);
        panel = new JPanelChart(chart);
        getContentPane().add(panel, java.awt.BorderLayout.CENTER);
        setup(chart);
    }

    static private void setup(Chart chart) {

        /*
        1998 test data from 17 school districts in Los Angeles County.

        The variables were:
        lep - Proportion of LEP students to total tested
        read - The Reading Scaled Score for 5th Grade
        math - The Math Scaled Score for 5th Grade
        lang - The Language Scaled Score for 5th Grade

        The districts were:
        lau - Los Angeles
        ccu - Culver City
        bhu - Beverly Hills
        ing - Inglewood
        com - Compton
        smm - Santa Monica Malibu
        bur - Burbank
        gln - Glendale
        pvu - Palos Verdes
        sgu - San Gabriel
        abc - Artesia, Bloomfield, and Carmenita
        pas - Pasadena
        lan - Lancaster
        plm - Palmdale
        tor - Torrance
        dow - Downey
        lbu - Long Beach

        input lep read math lang str3 district
        .38 626.5 601.3 605.3 lau
        .18 654.0 647.1 641.8 ccu
        .07 677.2 676.5 670.5 bhu
        .09 639.9 640.3 636.0 ing
        .19 614.7 617.3 606.2 com
        .12 670.2 666.0 659.3 smm
        .20 651.1 645.2 643.4 bur
        .41 645.4 645.8 644.8 gln
        .07 683.5 682.9 674.3 pvu
        .39 648.6 647.8 643.1 sgu
        .21 650.4 650.8 643.9 abc
        .24 637.0 636.9 626.5 pas
        .09 641.1 628.8 629.4 lan
        .12 638.0 627.7 628.6 plm
        .11 661.4 659.0 651.8 tor
        .22 646.4 646.2 647.0 dow
        .33 634.1 632.0 627.8 lbu
        */

        double[][] data = {
            {.38, 626.5, 601.3, 605.3},
            {.18, 654.0, 647.1, 641.8},
            {.07, 677.2, 676.5, 670.5},
            {.09, 639.9, 640.3, 636.0},
            {.19, 614.7, 617.3, 606.2},
            {.12, 670.2, 666.0, 659.3},
            {.20, 651.1, 645.2, 643.4},
            {.41, 645.4, 645.8, 644.8},
            {.07, 683.5, 682.9, 674.3},
            {.39, 648.6, 647.8, 643.1},
            {.21, 650.4, 650.8, 643.9},
            {.24, 637.0, 636.9, 626.5},
            {.09, 641.1, 628.8, 629.4},
            {.12, 638.0, 627.7, 628.6},
            {.11, 661.4, 659.0, 651.8},
            {.22, 646.4, 646.2, 647.0},
            {.33, 634.1, 632.0, 627.8}};

        String[] lab = {"lau", "ccu", "bhu", "ing", "com", "smm",
                        "bur", "gln", "pvu", "sgu", "abc", "pas",
                        "lan", "plm", "tor", "dor", "lbu"};


        // 3rd arg in Dissimilarities gives different results for 0,1,2
        try {
            Dissimilarities dist = new Dissimilarities(data, 0, 1, 1);
            double[][] distanceMatrix = dist.getDistanceMatrix();
            ClusterHierarchical clink =
                    new ClusterHierarchical(dist.getDistanceMatrix(), 4, 0);

            int nClusters = 4;
            int[] iclus = clink.getClusterMembership(nClusters);
            int[] nclus = clink.getObsPerCluster(nClusters);

            AxisXY axis = new AxisXY(chart);

            // use either method below to create the chart
            Dendrogram dc =
                    new Dendrogram(axis, clink, Data.DENDROGRAM_TYPE_HORIZONTAL);
            /*
            Dendrogram dc = 
                    new Dendrogram(axis, clink.getClusterLevel(), 
                        clink.getClusterLeftSons(), clink.getClusterRightSons(),
                        Data.DENDROGRAM_TYPE_HORIZONTAL);
             */
            dc.setLabels(lab);
            dc.setLineColor(new String[] {"Blue","Green", "Red", "Orange"});
        } catch (com.imsl.IMSLException e) {
            System.out.println(e.getStackTrace());
        }
    }

    public static void main(String argv[]) {
        JFrameChart frame = new JFrameChart();
        SampleDendrogram.setup(frame.getChart());
        frame.setVisible(true);
    }
}