view flys-artifacts/src/main/java/de/intevation/flys/artifacts/math/GrubbsOutlier.java @ 5622:b28a6d05e969

Add a new mechanism in mapfish print call to add arbitary data maps Data properties are identified by starting with mapfish-data and they are then split in info value pairs where info can be the description of the information and value the value of the information to be transported in the data map.
author Andre Heinecke <aheinecke@intevation.de>
date Tue, 09 Apr 2013 19:04:32 +0200
parents a7d080347ac3
children
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package de.intevation.flys.artifacts.math;

import java.util.List;

import org.apache.commons.math.MathException;

import org.apache.commons.math.distribution.TDistributionImpl;

import org.apache.commons.math.stat.descriptive.moment.Mean;
import org.apache.commons.math.stat.descriptive.moment.StandardDeviation;

import org.apache.log4j.Logger;

public class GrubbsOutlier
{
    public static final double EPSILON = 1e-5;

    public static final double DEFAULT_ALPHA = 0.05;

    private static Logger log = Logger.getLogger(GrubbsOutlier.class);

    protected GrubbsOutlier() {
    }

    public static Integer findOutlier(List<Double> values) {
        return findOutlier(values, DEFAULT_ALPHA, null);
    }

    public static Integer findOutlier(
        List<Double> values,
        double alpha,
        double[] stdDevResult
    ) {
        boolean debug = log.isDebugEnabled();

        if (debug) {
            log.debug("outliers significance: " + alpha);
        }

        alpha = 1d - alpha;

        int N = values.size();

        if (debug) {
            log.debug("Values to check: " + N);
        }

        if (N < 3) {
            return null;
        }

        Mean mean = new Mean();
        StandardDeviation std = new StandardDeviation();

        for (Double value: values) {
            double v = value.doubleValue();
            mean.increment(v);
            std .increment(v);
        }

        double m = mean.getResult();
        double s = std.getResult();

        if (debug) {
            log.debug("mean: " + m);
            log.debug("std dev: " + s);
        }

        double maxZ = -Double.MAX_VALUE;
        int iv = -1;
        for (int i = N-1; i >= 0; --i) {
            double v = values.get(i).doubleValue();
            double z = Math.abs(v - m);
            if (z > maxZ) {
                maxZ = z;
                iv = i;
            }
        }

        if (Math.abs(s) < EPSILON) {
            return null;
        }

        maxZ /= s;

        TDistributionImpl tdist = new TDistributionImpl(N-2);

        double t;

        try {
            t = tdist.inverseCumulativeProbability(alpha/(N+N));
        }
        catch (MathException me) {
            log.error(me);
            return null;
        }

        t *= t;

        double za = ((N-1)/Math.sqrt(N))*Math.sqrt(t/(N-2d+t));

        if (debug) {
            log.debug("max: " + maxZ + " crit: " + za);
        }
        if (stdDevResult != null) {
            stdDevResult[0] = std.getResult();
        }
        return maxZ > za
            ? Integer.valueOf(iv)
            : null;
    }
}
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