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Set up module for example applications. 

Moved "Chinese Rings" example into the new module.
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Gilles Sadowski 2021-05-19 15:28:59 +02:00
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===============================================================================
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Apache Commons Math
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Apache License 2.0:
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code developed by Mike Giles, Oxford-Man Institute of Quantitative Finance,
and published in GPU Computing Gems, volume 2, 2010 (grant received on
March 23th 2013)
- The LinearConstraint, LinearObjectiveFunction, LinearOptimizer,
RelationShip, SimplexSolver and SimplexTableau classes in package
org.apache.commons.math3.optimization.linear include software developed by
Benjamin McCann (http://www.benmccann.com) and distributed with
the following copyright: Copyright 2009 Google Inc. (grant received on
March 16th 2009)
- The class "org.apache.commons.math3.exception.util.LocalizedFormatsTest" which
is an adapted version of "OrekitMessagesTest" test class for the Orekit library
- The "org.apache.commons.math3.analysis.interpolation.HermiteInterpolator"
has been imported from the Orekit space flight dynamics library.
===============================================================================
APACHE COMMONS MATH DERIVATIVE WORKS:
The Apache commons-math library includes a number of subcomponents
whose implementation is derived from original sources written
in C or Fortran. License terms of the original sources
are reproduced below.
===============================================================================
For the lmder, lmpar and qrsolv Fortran routine from minpack and translated in
the LevenbergMarquardtOptimizer class in package
org.apache.commons.math3.optimization.general
Original source copyright and license statement:
Minpack Copyright Notice (1999) University of Chicago. All rights reserved
Redistribution and use in source and binary forms, with or
without modification, are permitted provided that the
following conditions are met:
1. Redistributions of source code must retain the above
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disclaimer.
2. Redistributions in binary form must reproduce the above
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provided with the distribution.
3. The end-user documentation included with the
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Alternately, this acknowledgment may appear in the software
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4. WARRANTY DISCLAIMER. THE SOFTWARE IS SUPPLIED "AS IS"
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(INCLUDING NEGLIGENCE OR STRICT LIABILITY), OR OTHERWISE,
EVEN IF ANY OF SAID PARTIES HAS BEEN WARNED OF THE
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===============================================================================
Copyright and license statement for the odex Fortran routine developed by
E. Hairer and G. Wanner and translated in GraggBulirschStoerIntegrator class
in package org.apache.commons.math3.ode.nonstiff:
Copyright (c) 2004, Ernst Hairer
Redistribution and use in source and binary forms, with or without
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===============================================================================
Copyright and license statement for the original Mersenne twister C
routines translated in MersenneTwister class in package
org.apache.commons.math3.random:
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The names of its contributors may not be used to endorse or promote
products derived from this software without specific prior written
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===============================================================================
The initial code for shuffling an array (originally in class
"org.apache.commons.math3.random.RandomDataGenerator", now replaced by
a method in class "org.apache.commons.math3.util.MathArrays") was
inspired from the algorithm description provided in
"Algorithms", by Ian Craw and John Pulham (University of Aberdeen 1999).
The textbook (containing a proof that the shuffle is uniformly random) is
available here:
http://citeseerx.ist.psu.edu/viewdoc/download;?doi=10.1.1.173.1898&rep=rep1&type=pdf
===============================================================================
License statement for the direction numbers in the resource files for Sobol sequences.
-----------------------------------------------------------------------------
Licence pertaining to sobol.cc and the accompanying sets of direction numbers
-----------------------------------------------------------------------------
Copyright (c) 2008, Frances Y. Kuo and Stephen Joe
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the names of the copyright holders nor the names of the
University of New South Wales and the University of Waikato
and its contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===============================================================================
The initial commit of package "org.apache.commons.math3.ml.neuralnet" is
an adapted version of code developed in the context of the Data Processing
and Analysis Consortium (DPAC) of the "Gaia" project of the European Space
Agency (ESA).
===============================================================================
The initial commit of the class "org.apache.commons.math3.special.BesselJ" is
an adapted version of code translated from the netlib Fortran program, rjbesl
http://www.netlib.org/specfun/rjbesl by R.J. Cody at Argonne National
Laboratory (USA). There is no license or copyright statement included with the
original Fortran sources.
===============================================================================
The BracketFinder (package org.apache.commons.math3.optimization.univariate)
and PowellOptimizer (package org.apache.commons.math3.optimization.general)
classes are based on the Python code in module "optimize.py" (version 0.5)
developed by Travis E. Oliphant for the SciPy library (http://www.scipy.org/)
Copyright © 2003-2009 SciPy Developers.
SciPy license
Copyright © 2001, 2002 Enthought, Inc.
All rights reserved.
Copyright © 2003-2013 SciPy Developers.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of Enthought nor the names of the SciPy Developers may
be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===============================================================================

9
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Apache Commons Math
Copyright 2001-2020 The Apache Software Foundation
This product includes software developed at
The Apache Software Foundation (http://www.apache.org/).
This product includes software developed for Orekit by
CS Systèmes d'Information (http://www.c-s.fr/)
Copyright 2010-2012 CS Systèmes d'Information

457
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===============================================================================
APACHE COMMONS MATH DERIVATIVE WORKS:
The Apache commons-math library includes a number of subcomponents
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===============================================================================
For the lmder, lmpar and qrsolv Fortran routine from minpack and translated in
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org.apache.commons.math3.optimization.general
Original source copyright and license statement:
Minpack Copyright Notice (1999) University of Chicago. All rights reserved
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===============================================================================
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in package org.apache.commons.math3.ode.nonstiff:
Copyright (c) 2004, Ernst Hairer
Redistribution and use in source and binary forms, with or without
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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===============================================================================
Copyright and license statement for the original Mersenne twister C
routines translated in MersenneTwister class in package
org.apache.commons.math3.random:
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.
Redistribution and use in source and binary forms, with or without
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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===============================================================================
The initial code for shuffling an array (originally in class
"org.apache.commons.math3.random.RandomDataGenerator", now replaced by
a method in class "org.apache.commons.math3.util.MathArrays") was
inspired from the algorithm description provided in
"Algorithms", by Ian Craw and John Pulham (University of Aberdeen 1999).
The textbook (containing a proof that the shuffle is uniformly random) is
available here:
http://citeseerx.ist.psu.edu/viewdoc/download;?doi=10.1.1.173.1898&rep=rep1&type=pdf
===============================================================================
License statement for the direction numbers in the resource files for Sobol sequences.
-----------------------------------------------------------------------------
Licence pertaining to sobol.cc and the accompanying sets of direction numbers
-----------------------------------------------------------------------------
Copyright (c) 2008, Frances Y. Kuo and Stephen Joe
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===============================================================================
The initial commit of package "org.apache.commons.math3.ml.neuralnet" is
an adapted version of code developed in the context of the Data Processing
and Analysis Consortium (DPAC) of the "Gaia" project of the European Space
Agency (ESA).
===============================================================================
The initial commit of the class "org.apache.commons.math3.special.BesselJ" is
an adapted version of code translated from the netlib Fortran program, rjbesl
http://www.netlib.org/specfun/rjbesl by R.J. Cody at Argonne National
Laboratory (USA). There is no license or copyright statement included with the
original Fortran sources.
===============================================================================
The BracketFinder (package org.apache.commons.math3.optimization.univariate)
and PowellOptimizer (package org.apache.commons.math3.optimization.general)
classes are based on the Python code in module "optimize.py" (version 0.5)
developed by Travis E. Oliphant for the SciPy library (http://www.scipy.org/)
Copyright © 2003-2009 SciPy Developers.
SciPy license
Copyright © 2001, 2002 Enthought, Inc.
All rights reserved.
Copyright © 2003-2013 SciPy Developers.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of Enthought nor the names of the SciPy Developers may
be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===============================================================================

9
commons-math-examples/examples-sofm/chinese-rings/NOTICE Normal file
View File

@ -0,0 +1,9 @@
Apache Commons Math
Copyright 2001-2020 The Apache Software Foundation
This product includes software developed at
The Apache Software Foundation (http://www.apache.org/).
This product includes software developed for Orekit by
CS Systèmes d'Information (http://www.c-s.fr/)
Copyright 2010-2012 CS Systèmes d'Information

96
commons-math-examples/examples-sofm/chinese-rings/pom.xml Normal file
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@ -0,0 +1,96 @@
<?xml version="1.0"?>
<!--
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.
-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.commons</groupId>
<artifactId>examples-sofm</artifactId>
<version>4.0-SNAPSHOT</version>
</parent>
<artifactId>examples-sofm-chinese-rings</artifactId>
<version>4.0-SNAPSHOT</version>
<!-- This name is used in the shaded jar to provide the application title for the version information. -->
<name>Chinese Rings</name>
<description>SOFM used for classification.</description>
<properties>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<!-- OSGi -->
<commons.osgi.symbolicName>org.apache.commons.math4.examples.sofm.chineserings</commons.osgi.symbolicName>
<commons.osgi.export>org.apache.commons.math4.examples.sofm.chineserings</commons.osgi.export>
<!-- Java 9+ -->
<commons.automatic.module.name>org.apache.commons.math4.examples.sofm.chineserings</commons.automatic.module.name>
<!-- Workaround to avoid duplicating config files. -->
<math.parent.dir>${basedir}/../../..</math.parent.dir>
<uberjar.name>examples-sofm-chineserings</uberjar.name>
<project.mainClass>org.apache.commons.math4.examples.sofm.chineserings.StandAlone</project.mainClass>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-geometry-euclidean</artifactId>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<finalName>${uberjar.name}</finalName>
<minimizeJar>true</minimizeJar>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
<mainClass>${project.mainClass}</mainClass>
</transformer>
</transformers>
<filters>
<filter>
<!-- Shading signed JARs will fail without this. http://stackoverflow.com/questions/999489/invalid-signature-file-when-attempting-to-run-a-jar -->
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>

41
src/userguide/java/org/apache/commons/math4/userguide/sofm/ChineseRings.java → commons-math-examples/examples-sofm/chinese-rings/src/main/java/org/apache/commons/math4/examples/sofm/chineserings/ChineseRings.java
View File

@ -15,7 +15,9 @@
* limitations under the License.
*/
package org.apache.commons.math4.userguide.sofm;
package org.apache.commons.math4.examples.sofm.chineserings;
import java.util.Iterator;
import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.simple.RandomSource;
@ -27,10 +29,10 @@ import org.apache.commons.statistics.distribution.ContinuousDistribution;
import org.apache.commons.statistics.distribution.UniformContinuousDistribution;
/**
* Class that creates two intertwined rings.
* Class that creates two intertwined rings in 3D-space.
* Each ring is composed of a cloud of points.
*/
public class ChineseRings {
class ChineseRings {
/** Points in the two rings. */
private final Vector3D[] points;
@ -110,4 +112,37 @@ public class ChineseRings {
public Vector3D[] getPoints() {
return points.clone();
}
/**
* Creates an iterable that will present the points coordinates.
*
* @return the iterable.
*/
public Iterable<double[]> createIterable() {
return new Iterable<double[]>() {
public Iterator<double[]> iterator() {
return new Iterator<double[]>() {
/** Data. */
final Vector3D[] points = getPoints();
/** Number of samples. */
private int n = 0;
/** {@inheritDoc} */
public boolean hasNext() {
return n < points.length;
}
/** {@inheritDoc} */
public double[] next() {
return points[n++].toArray();
}
/** {@inheritDoc} */
public void remove() {
throw new UnsupportedOperationException();
}
};
}
};
}
}

190
commons-math-examples/examples-sofm/chinese-rings/src/main/java/org/apache/commons/math4/examples/sofm/chineserings/ChineseRingsClassifier.java Normal file
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@ -0,0 +1,190 @@
/*
* 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.math4.examples.sofm.chineserings;
import java.util.Iterator;
import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.simple.RandomSource;
import org.apache.commons.geometry.euclidean.threed.Vector3D;
import org.apache.commons.math4.legacy.ml.neuralnet.SquareNeighbourhood;
import org.apache.commons.math4.legacy.ml.neuralnet.FeatureInitializer;
import org.apache.commons.math4.legacy.ml.neuralnet.FeatureInitializerFactory;
import org.apache.commons.math4.legacy.ml.neuralnet.MapUtils;
import org.apache.commons.math4.legacy.ml.neuralnet.twod.NeuronSquareMesh2D;
import org.apache.commons.math4.legacy.ml.neuralnet.sofm.LearningFactorFunction;
import org.apache.commons.math4.legacy.ml.neuralnet.sofm.LearningFactorFunctionFactory;
import org.apache.commons.math4.legacy.ml.neuralnet.sofm.NeighbourhoodSizeFunction;
import org.apache.commons.math4.legacy.ml.neuralnet.sofm.NeighbourhoodSizeFunctionFactory;
import org.apache.commons.math4.legacy.ml.neuralnet.sofm.KohonenUpdateAction;
import org.apache.commons.math4.legacy.ml.neuralnet.sofm.KohonenTrainingTask;
import org.apache.commons.math4.legacy.ml.distance.DistanceMeasure;
import org.apache.commons.math4.legacy.ml.distance.EuclideanDistance;
import org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics;
/**
* SOFM for categorizing points that belong to each of two intertwined rings.
*/
class ChineseRingsClassifier {
/** SOFM. */
private final NeuronSquareMesh2D sofm;
/** Rings. */
private final ChineseRings rings;
/** Distance function. */
private final DistanceMeasure distance = new EuclideanDistance();
/**
* @param rings Training data.
* @param dim1 Number of rows of the SOFM.
* @param dim2 Number of columns of the SOFM.
*/
public ChineseRingsClassifier(ChineseRings rings,
int dim1,
int dim2) {
this.rings = rings;
sofm = new NeuronSquareMesh2D(dim1, false,
dim2, false,
SquareNeighbourhood.MOORE,
makeInitializers());
}
/**
* Creates training tasks.
*
* @param numTasks Number of tasks to create.
* @param numSamplesPerTask Number of training samples per task.
* @return the created tasks.
*/
public Runnable[] createParallelTasks(int numTasks,
long numSamplesPerTask) {
final Runnable[] tasks = new Runnable[numTasks];
final LearningFactorFunction learning
= LearningFactorFunctionFactory.exponentialDecay(1e-1,
5e-2,
numSamplesPerTask / 2);
final double numNeurons = Math.sqrt(sofm.getNumberOfRows() * sofm.getNumberOfColumns());
final NeighbourhoodSizeFunction neighbourhood
= NeighbourhoodSizeFunctionFactory.exponentialDecay(0.5 * numNeurons,
0.2 * numNeurons,
numSamplesPerTask / 2);
for (int i = 0; i < numTasks; i++) {
final KohonenUpdateAction action = new KohonenUpdateAction(distance,
learning,
neighbourhood);
tasks[i] = new KohonenTrainingTask(sofm.getNetwork(),
createRandomIterator(numSamplesPerTask),
action);
}
return tasks;
}
/**
* Creates a training task.
*
* @param numSamples Number of training samples.
* @return the created task.
*/
public Runnable createSequentialTask(long numSamples) {
return createParallelTasks(1, numSamples)[0];
}
/**
* Computes various quality measures.
*
* @return the indicators.
*/
public NeuronSquareMesh2D.DataVisualization computeQualityIndicators() {
return sofm.computeQualityIndicators(rings.createIterable());
}
/**
* Creates the features' initializers.
* They are sampled from a uniform distribution around the barycentre of
* the rings.
*
* @return an array containing the initializers for the x, y and
* z coordinates of the features array of the neurons.
*/
private FeatureInitializer[] makeInitializers() {
final SummaryStatistics[] centre = new SummaryStatistics[] {
new SummaryStatistics(),
new SummaryStatistics(),
new SummaryStatistics()
};
for (Vector3D p : rings.getPoints()) {
centre[0].addValue(p.getX());
centre[1].addValue(p.getY());
centre[2].addValue(p.getZ());
}
final double[] mean = new double[] {
centre[0].getMean(),
centre[1].getMean(),
centre[2].getMean()
};
final double s = 0.1;
final double[] dev = new double[] {
s * centre[0].getStandardDeviation(),
s * centre[1].getStandardDeviation(),
s * centre[2].getStandardDeviation()
};
return new FeatureInitializer[] {
FeatureInitializerFactory.uniform(mean[0] - dev[0], mean[0] + dev[0]),
FeatureInitializerFactory.uniform(mean[1] - dev[1], mean[1] + dev[1]),
FeatureInitializerFactory.uniform(mean[2] - dev[2], mean[2] + dev[2])
};
}
/**
* Creates an iterator that will present a series of points coordinates in
* a random order.
*
* @param numSamples Number of samples.
* @return the iterator.
*/
private Iterator<double[]> createRandomIterator(final long numSamples) {
return new Iterator<double[]>() {
/** Data. */
final Vector3D[] points = rings.getPoints();
/** RNG. */
final UniformRandomProvider rng = RandomSource.create(RandomSource.KISS);
/** Number of samples. */
private long n = 0;
/** {@inheritDoc} */
public boolean hasNext() {
return n < numSamples;
}
/** {@inheritDoc} */
public double[] next() {
++n;
return points[rng.nextInt(points.length)].toArray();
}
/** {@inheritDoc} */
public void remove() {
throw new UnsupportedOperationException();
}
};
}
}

118
commons-math-examples/examples-sofm/chinese-rings/src/main/java/org/apache/commons/math4/examples/sofm/chineserings/StandAlone.java Normal file
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@ -0,0 +1,118 @@
/*
* 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.math4.examples.sofm.chineserings;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.concurrent.Callable;
import picocli.CommandLine;
import picocli.CommandLine.Option;
import picocli.CommandLine.Command;
import org.apache.commons.geometry.euclidean.threed.Vector3D;
import org.apache.commons.math4.legacy.ml.neuralnet.twod.NeuronSquareMesh2D;
/**
* Application class.
*/
@Command(description = "Run the application",
mixinStandardHelpOptions = true)
public class StandAlone implements Callable<Void> {
@Option(names = { "-r" }, paramLabel = "numRows",
description = "Number of rows of the 2D SOFM (default: ${DEFAULT-VALUE}).")
private int _numRows = 15;
@Option(names = { "-c" }, paramLabel = "numCols",
description = "Number of columns of the 2D SOFM (default: ${DEFAULT-VALUE}).")
private int _numCols = 15;
@Option(names = { "-s" }, paramLabel = "numSamples",
description = "Number of samples for the training (default: ${DEFAULT-VALUE}).")
private long _numSamples = 100000;
@Option(names = { "-o" }, paramLabel = "outputFile", required = true,
description = "Output file name.")
private String _outputFile = null;
/**
* Program entry point. All solver parameters must be provided
* through a {@link java.util.Properties Properties} file.
*
* @param args Command line arguments and options.
*/
public static void main(String[] args) {
CommandLine.call(new StandAlone(), args);
}
@Override
public Void call() throws Exception {
final ChineseRings rings = new ChineseRings(Vector3D.of(1, 2, 3),
25, 2,
20, 1,
2000, 1500);
final ChineseRingsClassifier classifier = new ChineseRingsClassifier(rings, _numRows, _numCols);
classifier.createSequentialTask(_numSamples).run();
printResult(_outputFile, classifier);
return null;
}
/**
* Prints various quality measures of the map to files.
*
* @param fileName File name.
* @param sofm Classifier.
*/
private static void printResult(String fileName,
ChineseRingsClassifier sofm) {
final NeuronSquareMesh2D.DataVisualization result = sofm.computeQualityIndicators();
try (final PrintWriter out = new PrintWriter(fileName)) {
out.println("# Number of samples: " + result.getNumberOfSamples());
out.println("# Quantization error: " + result.getMeanQuantizationError());
out.println("# Topographic error: " + result.getMeanTopographicError());
out.println();
printImage("Quantization error", result.getQuantizationError(), out);
printImage("Topographic error", result.getTopographicError(), out);
printImage("Normalized hits", result.getNormalizedHits(), out);
printImage("U-matrix", result.getUMatrix(), out);
} catch (IOException e) {
// Do nothing.
}
}
/**
* @param desc Data description.
* @param image Data.
* @param out Output stream.
*/
private static void printImage(String desc,
double[][] image,
PrintWriter out) {
out.println("# " + desc);
final int nR = image.length;
final int nC = image[0].length;
for (int i = 0; i < nR; i++) {
for (int j = 0; j < nC; j++) {
out.print(image[i][j] + " ");
}
out.println();
}
out.println();
}
}

57
commons-math-examples/examples-sofm/pom.xml Normal file
View File

@ -0,0 +1,57 @@
<?xml version="1.0"?>
<!--
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.
-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math-examples</artifactId>
<version>4.0-SNAPSHOT</version>
</parent>
<artifactId>examples-sofm</artifactId>
<version>4.0-SNAPSHOT</version>
<packaging>pom</packaging>
<name>SOFM</name>
<description>Self-organized feature map (ANN) sample codes.</description>
<properties>
<!-- Workaround to avoid duplicating config files. -->
<math.parent.dir>${basedir}/../..</math.parent.dir>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math4-legacy</artifactId>
</dependency>
<dependency>
<groupId>info.picocli</groupId>
<artifactId>picocli</artifactId>
</dependency>
</dependencies>
<modules>
<module>chinese-rings</module>
</modules>
</project>

41
commons-math-examples/examples-sofm/src/main/java/org/apache/commons/math4/examples/neuralnet/sofm/tsp/StandAlone.java Normal file
View File

@ -0,0 +1,41 @@
/*
* 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.examples.neuralnet.sofm.tsp;
import org.apache.commons.rng.simple.RandomSource;
/**
*/
public class StandAlone {
/**
* Program entry point.
*
* @param args Arguments.
* The order is as follows:
* <ol>
* <li>
* </li>
* <li>
* </li>
* </ol>
*/
public static void main(String[] args) {
if (args.length != EXPECTED_ARGUMENTS) {
throw new IllegalStateException("Missing arguments");
}
}
}

119
commons-math-examples/pom.xml Normal file
View File

@ -0,0 +1,119 @@
<?xml version="1.0"?>
<!--
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.
-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math-parent</artifactId>
<version>4.0-SNAPSHOT</version>
</parent>
<artifactId>commons-math-examples</artifactId>
<version>4.0-SNAPSHOT</version>
<packaging>pom</packaging>
<name>Apache Commons Math Examples</name>
<description>Examples of use of the "Commons Math" library.
Codes in this module and its sub-modules are not part of the public API.
</description>
<properties>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<!-- OSGi -->
<commons.osgi.symbolicName>org.apache.commons.math4.examples</commons.osgi.symbolicName>
<commons.osgi.export>org.apache.commons.math4.examples</commons.osgi.export>
<!-- Java 9+ -->
<commons.automatic.module.name>org.apache.commons.math4.examples</commons.automatic.module.name>
<!-- Workaround to avoid duplicating config files. -->
<math.parent.dir>${basedir}/..</math.parent.dir>
<math.version>4.0-SNAPSHOT</math.version>
<math.picocli.version>3.9.5</math.picocli.version>
<math.rng.version>1.3</math.rng.version>
<math.geometry.version>1.0-beta1</math.geometry.version>
<!-- Disable JApiCmp failures (but keep the report). The examples API is allowed to change. -->
<commons.japicmp.breakBuildOnBinaryIncompatibleModifications>false</commons.japicmp.breakBuildOnBinaryIncompatibleModifications>
<commons.japicmp.breakBuildOnSourceIncompatibleModifications>false</commons.japicmp.breakBuildOnSourceIncompatibleModifications>
<math.jira.component>examples</math.jira.component>
</properties>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math4-neuralnet</artifactId>
<version>${math.version}</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math4-legacy</artifactId>
<version>${math.version}</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-rng-client-api</artifactId>
<version>${math.rng.version}</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-rng-simple</artifactId>
<version>${math.rng.version}</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-geometry-euclidean</artifactId>
<version>${math.geometry.version}</version>
</dependency>
<dependency>
<groupId>info.picocli</groupId>
<artifactId>picocli</artifactId>
<version>${math.picocli.version}</version>
</dependency>
</dependencies>
</dependencyManagement>
<build>
<pluginManagement>
<plugins>
<plugin>
<groupId>org.codehaus.mojo</groupId>
<artifactId>exec-maven-plugin</artifactId>
<version>1.6.0</version>
</plugin>
</plugins>
</pluginManagement>
</build>
<modules>
<module>examples-sofm</module>
</modules>
</project>

13
pom.xml
View File

@ -106,9 +106,7 @@
<modules>
<module>commons-math-legacy</module>
<!-- <module>commons-math-core</module> -->
<!-- <module>commons-math-ml-nn</module> -->
<!-- <module>commons-math-ml-ga</module> -->
<module>commons-math-examples</module>
</modules>
<scm>
@ -721,15 +719,6 @@
</plugins>
</build>
</profile>
<!--
Profiles for modules with special requirements.
-->
<profile>
<id>commons-numbers-examples</id>
<modules>
<module>commons-numbers-examples</module>
</modules>
</profile>
</profiles>
<developers>

337
src/userguide/java/org/apache/commons/math4/userguide/sofm/ChineseRingsClassifier.java
View File

@ -1,337 +0,0 @@
/*
* 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.math4.userguide.sofm;
import java.util.Iterator;
import java.io.PrintWriter;
import java.io.IOException;
import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.simple.RandomSource;
import org.apache.commons.geometry.euclidean.threed.Vector3D;
import org.apache.commons.math4.ml.neuralnet.SquareNeighbourhood;
import org.apache.commons.math4.ml.neuralnet.FeatureInitializer;
import org.apache.commons.math4.ml.neuralnet.FeatureInitializerFactory;
import org.apache.commons.math4.ml.neuralnet.MapUtils;
import org.apache.commons.math4.ml.neuralnet.twod.NeuronSquareMesh2D;
import org.apache.commons.math4.ml.neuralnet.sofm.LearningFactorFunction;
import org.apache.commons.math4.ml.neuralnet.sofm.LearningFactorFunctionFactory;
import org.apache.commons.math4.ml.neuralnet.sofm.NeighbourhoodSizeFunction;
import org.apache.commons.math4.ml.neuralnet.sofm.NeighbourhoodSizeFunctionFactory;
import org.apache.commons.math4.ml.neuralnet.sofm.KohonenUpdateAction;
import org.apache.commons.math4.ml.neuralnet.sofm.KohonenTrainingTask;
import org.apache.commons.math4.ml.distance.DistanceMeasure;
import org.apache.commons.math4.ml.distance.EuclideanDistance;
import org.apache.commons.math4.stat.descriptive.SummaryStatistics;
import org.apache.commons.math4.util.FastMath;
import org.apache.commons.math4.exception.MathUnsupportedOperationException;
/**
* SOFM for categorizing points that belong to each of two intertwined rings.
*
* The output currently consists in 3 text files:
* <ul>
* <li>"before.chinese.U.seq.dat": U-matrix of the SOFM before training</li>
* <li>"after.chinese.U.seq.dat": U-matrix of the SOFM after training</li>
* <li>"after.chinese.hit.seq.dat": Hit histogram after training</li>
* </ul>
*/
public class ChineseRingsClassifier {
/** SOFM. */
private final NeuronSquareMesh2D sofm;
/** Rings. */
private final ChineseRings rings;
/** Distance function. */
private final DistanceMeasure distance = new EuclideanDistance();
public static void main(String[] args) {
final ChineseRings rings = new ChineseRings(Vector3D.of(1, 2, 3),
25, 2,
20, 1,
2000, 1500);
final ChineseRingsClassifier classifier = new ChineseRingsClassifier(rings, 15, 15);
printU("before.chinese.U.seq.dat", classifier);
classifier.createSequentialTask(100000).run();
printU("after.chinese.U.seq.dat", classifier);
printHit("after.chinese.hit.seq.dat", classifier);
}
/**
* @param rings Training data.
* @param dim1 Number of rows of the SOFM.
* @param dim2 Number of columns of the SOFM.
*/
public ChineseRingsClassifier(ChineseRings rings,
int dim1,
int dim2) {
this.rings = rings;
sofm = new NeuronSquareMesh2D(dim1, false,
dim2, false,
SquareNeighbourhood.MOORE,
makeInitializers());
}
/**
* Creates training tasks.
*
* @param numTasks Number of tasks to create.
* @param numSamplesPerTask Number of training samples per task.
* @return the created tasks.
*/
public Runnable[] createParallelTasks(int numTasks,
long numSamplesPerTask) {
final Runnable[] tasks = new Runnable[numTasks];
final LearningFactorFunction learning
= LearningFactorFunctionFactory.exponentialDecay(1e-1,
5e-2,
numSamplesPerTask / 2);
final double numNeurons = FastMath.sqrt(sofm.getNumberOfRows() * sofm.getNumberOfColumns());
final NeighbourhoodSizeFunction neighbourhood
= NeighbourhoodSizeFunctionFactory.exponentialDecay(0.5 * numNeurons,
0.2 * numNeurons,
numSamplesPerTask / 2);
for (int i = 0; i < numTasks; i++) {
final KohonenUpdateAction action = new KohonenUpdateAction(distance,
learning,
neighbourhood);
tasks[i] = new KohonenTrainingTask(sofm.getNetwork(),
createRandomIterator(numSamplesPerTask),
action);
}
return tasks;
}
/**
* Creates a training task.
*
* @param numSamples Number of training samples.
* @return the created task.
*/
public Runnable createSequentialTask(long numSamples) {
return createParallelTasks(1, numSamples)[0];
}
/**
* Computes the U-matrix.
*
* @return the U-matrix of the network.
*/
public double[][] computeU() {
return MapUtils.computeU(sofm, distance);
}
/**
* Computes the hit histogram.
*
* @return the histogram.
*/
public int[][] computeHitHistogram() {
return MapUtils.computeHitHistogram(createIterable(),
sofm,
distance);
}
/**
* Computes the quantization error.
*
* @return the quantization error.
*/
public double computeQuantizationError() {
return MapUtils.computeQuantizationError(createIterable(),
sofm.getNetwork(),
distance);
}
/**
* Computes the topographic error.
*
* @return the topographic error.
*/
public double computeTopographicError() {
return MapUtils.computeTopographicError(createIterable(),
sofm.getNetwork(),
distance);
}
/**
* Creates the features' initializers.
* They are sampled from a uniform distribution around the barycentre of
* the rings.
*
* @return an array containing the initializers for the x, y and
* z coordinates of the features array of the neurons.
*/
private FeatureInitializer[] makeInitializers() {
final SummaryStatistics[] centre = new SummaryStatistics[] {
new SummaryStatistics(),
new SummaryStatistics(),
new SummaryStatistics()
};
for (Vector3D p : rings.getPoints()) {
centre[0].addValue(p.getX());
centre[1].addValue(p.getY());
centre[2].addValue(p.getZ());
}
final double[] mean = new double[] {
centre[0].getMean(),
centre[1].getMean(),
centre[2].getMean()
};
final double s = 0.1;
final double[] dev = new double[] {
s * centre[0].getStandardDeviation(),
s * centre[1].getStandardDeviation(),
s * centre[2].getStandardDeviation()
};
return new FeatureInitializer[] {
FeatureInitializerFactory.uniform(mean[0] - dev[0], mean[0] + dev[0]),
FeatureInitializerFactory.uniform(mean[1] - dev[1], mean[1] + dev[1]),
FeatureInitializerFactory.uniform(mean[2] - dev[2], mean[2] + dev[2])
};
}
/**
* Creates an iterable that will present the points coordinates.
*
* @return the iterable.
*/
private Iterable<double[]> createIterable() {
return new Iterable<double[]>() {
public Iterator<double[]> iterator() {
return new Iterator<double[]>() {
/** Data. */
final Vector3D[] points = rings.getPoints();
/** Number of samples. */
private int n = 0;
/** {@inheritDoc} */
public boolean hasNext() {
return n < points.length;
}
/** {@inheritDoc} */
public double[] next() {
return points[n++].toArray();
}
/** {@inheritDoc} */
public void remove() {
throw new MathUnsupportedOperationException();
}
};
}
};
}
/**
* Creates an iterator that will present a series of points coordinates in
* a random order.
*
* @param numSamples Number of samples.
* @return the iterator.
*/
private Iterator<double[]> createRandomIterator(final long numSamples) {
return new Iterator<double[]>() {
/** Data. */
final Vector3D[] points = rings.getPoints();
/** RNG. */
final UniformRandomProvider rng = RandomSource.create(RandomSource.KISS);
/** Number of samples. */
private long n = 0;
/** {@inheritDoc} */
public boolean hasNext() {
return n < numSamples;
}
/** {@inheritDoc} */
public double[] next() {
++n;
return points[rng.nextInt(points.length)].toArray();
}
/** {@inheritDoc} */
public void remove() {
throw new MathUnsupportedOperationException();
}
};
}
/**
* Prints the U-matrix of the map to the given file name.
*
* @param fileName File.
* @param sofm Classifier.
*/
private static void printU(String fileName,
ChineseRingsClassifier sofm) {
PrintWriter out = null;
try {
out = new PrintWriter(fileName);
final double[][] uMatrix = sofm.computeU();
for (int i = 0; i < uMatrix.length; i++) {
for (int j = 0; j < uMatrix[0].length; j++) {
out.print(uMatrix[i][j] + " ");
}
out.println();
}
out.println("# Quantization error: " + sofm.computeQuantizationError());
out.println("# Topographic error: " + sofm.computeTopographicError());
} catch (IOException e) {
// Do nothing.
} finally {
if (out != null) {
out.close();
}
}
}
/**
* Prints the hit histogram of the map to the given file name.
*
* @param fileName File.
* @param sofm Classifier.
*/
private static void printHit(String fileName,
ChineseRingsClassifier sofm) {
PrintWriter out = null;
try {
out = new PrintWriter(fileName);
final int[][] histo = sofm.computeHitHistogram();
for (int i = 0; i < histo.length; i++) {
for (int j = 0; j < histo[0].length; j++) {
out.print(histo[i][j] + " ");
}
out.println();
}
} catch (IOException e) {
// Do nothing.
} finally {
if (out != null) {
out.close();
}
}
}
}