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Java example source code file (BarnesHutTsneTest.java)

This example Java source code file (BarnesHutTsneTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

barneshuttsne, barneshuttsnetest, classpathresource, delta, exception, file, indarray, list, string, test, util

The BarnesHutTsneTest.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed 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.deeplearning4j.plot;

import org.apache.commons.io.IOUtils;
import org.junit.Test;
import static org.junit.Assert.*;
import org.nd4j.linalg.api.buffer.DataBuffer;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.indexing.NDArrayIndex;
import org.nd4j.linalg.io.ClassPathResource;


import java.io.File;
import java.util.List;

/**
 * Created by agibsonccc on 10/1/14.
 */
public class BarnesHutTsneTest {

    @Test
    public void testTsne() throws Exception {
        Nd4j.ENFORCE_NUMERICAL_STABILITY = true;
        Nd4j.factory().setDType(DataBuffer.Type.DOUBLE);
        Nd4j.getRandom().setSeed(123);
        BarnesHutTsne b = new BarnesHutTsne.Builder().stopLyingIteration(10).setMaxIter(10)
                .theta(0.5).learningRate(500).useAdaGrad(false)
                .build();

        ClassPathResource resource = new ClassPathResource("/mnist2500_X.txt");
        File f = resource.getFile();
        INDArray data = Nd4j.readNumpy(f.getAbsolutePath(),"   ").get(NDArrayIndex.interval(0,100),NDArrayIndex.interval(0,784));



        ClassPathResource labels = new ClassPathResource("mnist2500_labels.txt");
        List<String> labelsList = IOUtils.readLines(labels.getInputStream()).subList(0,100);
        b.fit(data);
    }

    @Test
    public void testBuilderFields() throws Exception {
        final double theta = 0;
        final boolean invert = false;
        final String similarityFunctions = "euclidean";
        final int maxIter = 1;
        final double realMin = 1.0;
        final double initialMomentum = 2.0;
        final double finalMomentum = 3.0;
        final double momentum = 4.0;
        final int switchMomentumIteration = 1;
        final boolean normalize = false;
        final boolean usePca = true;
        final int stopLyingIteration = 100;
        final double tolerance = 1e-1;
        final double learningRate = 100;
        final boolean useAdaGrad = false;
        final double perplexity = 1.0;
        final double minGain = 1.0;

        BarnesHutTsne b = new BarnesHutTsne.Builder().theta(theta).invertDistanceMetric(invert).similarityFunction(similarityFunctions)
                .setMaxIter(maxIter).setRealMin(realMin).setInitialMomentum(initialMomentum).setFinalMomentum(finalMomentum)
                .setMomentum(momentum).setSwitchMomentumIteration(switchMomentumIteration).normalize(normalize)
                .usePca(usePca).stopLyingIteration(stopLyingIteration).tolerance(tolerance).learningRate(learningRate)
                .perplexity(perplexity).minGain(minGain).build();

        final double DELTA = 1e-15;

        assertEquals(theta,b.getTheta(),DELTA);
        assertEquals("invert", invert, b.isInvert());
        assertEquals("similarityFunctions",similarityFunctions,b.getSimiarlityFunction());
        assertEquals("maxIter", maxIter, b.maxIter);
        assertEquals(realMin,b.realMin,DELTA);
        assertEquals(initialMomentum,b.initialMomentum,DELTA);
        assertEquals(finalMomentum, b.finalMomentum,DELTA);
        assertEquals(momentum,b.momentum,DELTA);
        assertEquals("switchMomentumnIteration", switchMomentumIteration, b.switchMomentumIteration);
        assertEquals("normalize", normalize,b.normalize);
        assertEquals("usePca", usePca,b.usePca);
        assertEquals("stopLyingIteration", stopLyingIteration,b.stopLyingIteration);
        assertEquals(tolerance,b.tolerance,DELTA);
        assertEquals(learningRate,b.learningRate,DELTA);
        assertEquals("useAdaGrad", useAdaGrad, b.useAdaGrad);
        assertEquals(perplexity,b.getPerplexity(),DELTA);
        assertEquals(minGain,b.minGain,DELTA);
    }
}

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