Example usage for org.jfree.chart.axis NumberAxis getUpperMargin

Introduction

In this page you can find the example usage for org.jfree.chart.axis NumberAxis getUpperMargin.

Prototype

public double getUpperMargin() 

Source Link

Document

Returns the upper margin for the axis, expressed as a percentage of the axis range.

Usage

From source file:hudson.graph.jfreechart.Utils.java

/**
 * Adjusts the Y-axis so that abnormally large value won't spoil the whole chart
 * by making everything look virtually 0.
 *
 * <p>/*  w ww  .j av a2  s . c o  m*/
 * The algorithm is based on <a href="http://en.wikipedia.org/wiki/Chebyshev%27s_inequality">Chebyshev's inequality</a>,
 * which states that given any number sequence, nore more than 1/(N^2) values are more than N x stddev away
 * from the average.
 *
 * <p>
 * So the algorithm is to set Y-axis range so that we can see all data points that are within N x stddev
 * of the average. Most of the time, Cebyshev's inequality is very conservative, so it shouldn't do
 * much harm.
 *
 * <p>
 * When the algorithm does kick in, however, we can kick out at most 1 in N^2 data points.
 * (So for example if N=3 then we can "fix" the graph as long as we only have less than 1/(3*3)=11.111...% bad data.
 *
 * <p>
 * Also see issue #1246.
 */
public static void adjustChebyshev(CategoryDataset dataset, NumberAxis yAxis) {
    // first compute E(X) and Var(X)
    double sum = 0, sum2 = 0;

    final int nColumns = dataset.getColumnCount();
    final int nRows = dataset.getRowCount();
    for (int i = 0; i < nRows; i++) {
        Comparable rowKey = dataset.getRowKey(i);
        for (int j = 0; j < nColumns; j++) {
            Comparable columnKey = dataset.getColumnKey(j);

            double n = dataset.getValue(rowKey, columnKey).doubleValue();
            sum += n;
            sum2 += n * n;
        }
    }

    double average = sum / (nColumns * nRows);
    double stddev = Math.sqrt(sum2 / (nColumns * nRows) - average * average);

    double rangeMin = average - stddev * CHEBYSHEV_N;
    double rangeMax = average + stddev * CHEBYSHEV_N;

    // now see if there are any data points that fall outside (rangeMin,rangeMax)
    boolean found = false;
    double min = 0, max = 0;
    for (int i = 0; i < nRows; i++) {
        Comparable rowKey = dataset.getRowKey(i);
        for (int j = 0; j < nColumns; j++) {
            Comparable columnKey = dataset.getColumnKey(j);

            double n = dataset.getValue(rowKey, columnKey).doubleValue();
            if (n < rangeMin || rangeMax < n) {
                found = true;
                continue; // ignore this value
            }

            min = Math.min(min, n);
            max = Math.max(max, n);
        }
    }

    if (!found)
        return; // no adjustment was necessary

    // some values fell outside the range, so adjust the Y-axis

    // if we are ever to extend this method to handle negative value ranges correctly,
    // the code after this needs modifications

    min = Math.min(0, min); // always include 0 in the graph
    max += yAxis.getUpperMargin() * (max - min);

    yAxis.setRange(min, max);
}

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