Mercurial > dive4elements > river
view flys-artifacts/src/main/java/de/intevation/flys/artifacts/math/Outlier.java @ 2716:150dcdefeb7d
Only offer soundings that fit to the current km range in MINFO bed height workflow.
flys-artifacts/trunk@4444 c6561f87-3c4e-4783-a992-168aeb5c3f6f
author | Ingo Weinzierl <ingo.weinzierl@intevation.de> |
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date | Fri, 18 May 2012 12:44:20 +0000 |
parents | c11da3540b70 |
children | ab81ffd1343e |
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package de.intevation.flys.artifacts.math; import org.apache.commons.math.MathException; import org.apache.commons.math.stat.descriptive.moment.Mean; import org.apache.commons.math.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math.distribution.TDistributionImpl; import java.util.List; import java.util.ArrayList; import org.apache.log4j.Logger; public class Outlier { private static Logger log = Logger.getLogger(Outlier.class); public static class IndexedValue { protected int index; protected double value; public IndexedValue() { } public IndexedValue(int index, double value) { this.index = index; this.value = value; } public int getIndex() { return index; } public void setIndex(int index) { this.index = index; } public double getValue() { return value; } public void setValue(double value) { this.value = value; } } // class IndexedValue public Outlier() { } public static List<IndexedValue> findOutliers( List<IndexedValue> inputValues, double alpha ) { ArrayList<IndexedValue> outliers = new ArrayList<IndexedValue>(); ArrayList<IndexedValue> values = new ArrayList<IndexedValue>(inputValues); for (;;) { int N = values.size(); if (N < 4) { break; } Mean mean = new Mean(); StandardDeviation std = new StandardDeviation(); for (IndexedValue value: values) { mean.increment(value.getValue()); std.increment(value.getValue()); } double m = mean.getResult(); double s = std.getResult(); double maxZ = -Double.MAX_VALUE; int iv = -1; for (int i = N-1; i >= 0; --i) { IndexedValue v = values.get(i); double z = Math.abs(m - v.getValue())/s; if (z > maxZ) { maxZ = z; iv = i; } } double t = Math.sqrt((N*(N-2)*maxZ*maxZ) /((N-1)*(N-1) - N*maxZ*maxZ)); TDistributionImpl tdist = new TDistributionImpl(N-2); try { double p = tdist.cumulativeProbability(t); if (p < alpha) { outliers.add(values.get(iv)); values.remove(iv); } } catch (MathException me) { log.error(me); } } return outliers; } } // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 :