MATH-1270 SOFM visualization: Topographic error.
Project: http://git-wip-us.apache.org/repos/asf/commons-math/repo Commit: http://git-wip-us.apache.org/repos/asf/commons-math/commit/d7f6c8da Tree: http://git-wip-us.apache.org/repos/asf/commons-math/tree/d7f6c8da Diff: http://git-wip-us.apache.org/repos/asf/commons-math/diff/d7f6c8da Branch: refs/heads/MATH_3_X Commit: d7f6c8da9512af55c04a86984f56ab6f9e2da126 Parents: afac1f0 Author: Gilles <er...@apache.org> Authored: Fri Sep 11 00:54:36 2015 +0200 Committer: Gilles <er...@apache.org> Committed: Fri Sep 11 00:54:36 2015 +0200 ---------------------------------------------------------------------- .../twod/util/TopographicErrorHistogram.java | 90 ++++++++++++++++++++ 1 file changed, 90 insertions(+) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/commons-math/blob/d7f6c8da/src/main/java/org/apache/commons/math3/ml/neuralnet/twod/util/TopographicErrorHistogram.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math3/ml/neuralnet/twod/util/TopographicErrorHistogram.java b/src/main/java/org/apache/commons/math3/ml/neuralnet/twod/util/TopographicErrorHistogram.java new file mode 100644 index 0000000..b337c0a --- /dev/null +++ b/src/main/java/org/apache/commons/math3/ml/neuralnet/twod/util/TopographicErrorHistogram.java @@ -0,0 +1,90 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.commons.math3.ml.neuralnet.twod.util; + +import org.apache.commons.math3.ml.neuralnet.MapUtils; +import org.apache.commons.math3.ml.neuralnet.Neuron; +import org.apache.commons.math3.ml.neuralnet.Network; +import org.apache.commons.math3.ml.neuralnet.twod.NeuronSquareMesh2D; +import org.apache.commons.math3.ml.distance.DistanceMeasure; +import org.apache.commons.math3.util.Pair; + +/** + * Computes the topographic error histogram. + * Each bin will contain the number of data for which the first and + * second best matching units are not adjacent in the map. + */ +public class TopographicErrorHistogram implements MapDataVisualization { + /** Distance. */ + private final DistanceMeasure distance; + /** Whether to compute relative bin counts. */ + private final boolean relativeCount; + + /** + * @param relativeCount Whether to compute relative bin counts. + * If {@code true}, the data count in each bin will be divided by the total + * number of samples mapped to the neuron represented by that bin. + * @param distance Distance. + */ + public TopographicErrorHistogram(boolean relativeCount, + DistanceMeasure distance) { + this.relativeCount = relativeCount; + this.distance = distance; + } + + /** {@inheritDoc} */ + public double[][] computeImage(NeuronSquareMesh2D map, + Iterable<double[]> data) { + final int nR = map.getNumberOfRows(); + final int nC = map.getNumberOfColumns(); + + final Network net = map.getNetwork(); + final LocationFinder finder = new LocationFinder(map); + + // Hit bins. + final int[][] hit = new int[nR][nC]; + // Error bins. + final double[][] error = new double[nR][nC]; + + for (double[] sample : data) { + final Pair<Neuron, Neuron> p = MapUtils.findBestAndSecondBest(sample, map, distance); + final Neuron best = p.getFirst(); + + final LocationFinder.Location loc = finder.getLocation(best); + final int row = loc.getRow(); + final int col = loc.getColumn(); + hit[row][col] += 1; + + if (!net.getNeighbours(best).contains(p.getSecond())) { + // Increment count if first and second best matching units + // are not neighbours. + error[row][col] += 1; + } + } + + if (relativeCount) { + for (int r = 0; r < nR; r++) { + for (int c = 0; c < nC; c++) { + error[r][c] /= hit[r][c]; + } + } + } + + return error; + } +}
