[
{
"path": ".gitignore",
"content": "*.class\n\n# Package Files #\n*.jar\n*.war\n*.ear\n*~\n.classpath\n.project\n.settings/\ntarget/\nlogs/\n/nbproject/private/\n\n/nbproject/"
},
{
"path": "README-old.asc",
"content": "# Clustering datasets\n\n## Datasets\n\nThis project contains collection of labeled clustering problems that can be found in the literature. Most of datasets were artificially created.\n\nAll datasets can be found link:https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial[data folder].\n\n### 2d-10c\n\n[align=\"right\",options=\"header\"]\n|===\n| data points | clusters | dimension\n| 2990 | 10 | 2\n|===\n\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-10c.png[\"2d-10c\",400,float=\"left\"]\n\n[.float .right]\n* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-10c.arff[ARFF]\n* link:https://github.com/deric/handl-data-generators[generator]\n\n> J. Handl and J. Knowles, “Multiobjective clustering with automatic\n> determination of the number of clusters,” UMIST, Tech. Rep., 2004.\n\n### atom\n\n[align=\"right\",options=\"header\"]\n|===\n| data points | clusters | dimension\n| 800 | 2 | 3\n|===\n\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/atom.png[\"atom\",400,float=\"left\"]\n\n[.float .right]\n* source: link:https://www.uni-marburg.de/fb12/datenbionik/data?language_sync=1[FCPS]\n* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/atom.arff[ARFF]\n\n### aggregation\n\n[align=\"right\",options=\"header\"]\n|===\n| data points | clusters | dimension\n| 788 | 7 | 2\n|===\n\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/aggregation.png[aggregation,400,float=\"left\"]\n\n[.float .right]\n* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/aggregation.arff[ARFF]\n* link:http://cs.joensuu.fi/sipu/datasets/[original source]\n\n> Gionis, A., H. Mannila, and P. Tsaparas, Clustering aggregation.\n> ACM Transactions on Knowledge Discovery from Data (TKDD), 2007. 1(1): p. 1-30.\n\n### chainlink\n\n[align=\"right\",options=\"header\"]\n|===\n| data points | clusters | dimension\n| 1000 | 2 | 3\n|===\n\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/chainlink.png[\"chainlink\",400,float=\"left\"]\n\n[.float .right]\n* source: link:https://www.uni-marburg.de/fb12/datenbionik/data?language_sync=1[FCPS]\n* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/chainlink.arff[ARFF]\n\n> Alfred Ultsch, Clustering with SOM: U*C,\n> in Proc. Workshop on Self Organizing Feature Maps ,pp 31-37 Paris 2005.\n\n### D31\n\n[align=\"right\",style=\"asciidoc\",options=\"noborders,wide\"]\n|===\n| data points | 3100\n| clusters | 31\n| dimensions | 2\n| image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/D31.png[\"D31\",400,float=\"left\"] | * link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/D31.arff[ARFF]\n|===\n\n> Veenman, C.J., M.J.T. Reinders, and E. Backer,\n> A maximum variance cluster algorithm. IEEE Trans. Pattern Analysis and Machine Intelligence 2002. 24(9): p. 1273-1280.\n\n### 3MC\n\n[align=\"right\",options=\"header\",style=\"literal\"]\n|===\n| data points | clusters | dimension\n| 400 | 3 | 2\n|===\n\n[.float .right]\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/3MC.png[\"3MC\",400,float=\"left\"]\n\n\n### DS577\n\n[align=\"right\",options=\"header\"]\n|===\n| data points | clusters | dimension\n| 577 | 3 | 2\n|===\n\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/DS577.png[\"D31\",400,float=\"left\"]\n\n[.float .right]\n* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/DS577.arff[ARFF]\n\n> M. C. Su, C. H. Chou, and C. C. Hsieh, “Fuzzy C-Means Algorithm with a Point Symmetry Distance,”\n> International Journal of Fuzzy Systems, vol. 7, no. 4, pp. 175-181, 2005.\n\n\n### cluto-t4_8k\n\n[align=\"right\",options=\"header\"]\n|===\n| data points | clusters | dimension\n| 8000 | 7 | 2\n|===\n\nimage::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t4_8k.png[\"cluto-t4_8k\",400,float=\"left\"]\n\n[.float .right]\n* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cluto-t4.8k.arff[ARFF]\n\n> G. Karypis, “CLUTO A Clustering Toolkit,”\n> Dept. of Computer Science, University of Minnesota, Tech. Rep. 02-017, 2002, available at\nhttp://www.cs.umn.edu/ ̃cluto.\n\n\n## Experiments\n\nThis project contains set of clustering methods benchmarks on various dataset. The project is dependent on [Clueminer project](https://github.com/deric/clueminer).\n\nin order to run benchmark compile dependencies into a single JAR file:\n\n mvn assembly:assembly\n\n# Consensus experiment\n\nallows running repeated runs of the same algorithm:\n\n```\n./run consensus --dataset \"triangle1\" --repeat 10\n```\nby default k-means algorithm is used.\n\nFor available datasets see [resources folder](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial).\n"
},
{
"path": "README.md",
"content": "# Clustering benchmarks\n\n## Datasets\n\nThis project contains collection of labeled clustering problems that can be found in the literature. Most of datasets were artificially created.\n\nThe benchmark includes:\n\n * [artificial datasets](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial)\n * [real world datasets](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/real-world)\n\n### Artificial data\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## Experiments\n\nThis project contains set of clustering methods benchmarks on various dataset. The project is dependent on [Clueminer project](https://github.com/deric/clueminer).\n\nin order to run benchmark compile dependencies into a single JAR file:\n\n mvn assembly:assembly\n\n# Consensus experiment\n\nallows running repeated runs of the same algorithm:\n\n```\n./run consensus --dataset \"triangle1\" --repeat 10\n```\nby default k-means algorithm is used.\n\nFor available datasets see [resources folder](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial).\n"
},
{
"path": "consensus",
"content": "#!/bin/bash\nmeth=(\"KmB-COMUSA-RAND\" \"KmB-COMUSA-MO\" \"KmB-COMUSA-RAND-fixed\")\nfor m in \"${meth[@]}\"; do\n ./run consensus --repeat 10 --method \"$m\" --dataset \"$@\"\ndone\n\n"
},
{
"path": "evolve-sc",
"content": "#!/bin/bash\nARGS=\"evolve-sc --test --generations 20 --population 50 $@\"\n`./run $ARGS`\n"
},
{
"path": "nb-configuration.xml",
"content": "\n\n \n \n unsupervised\n \n \n \n ${project.basedir}/../clueminer/license.txt\n \n\n"
},
{
"path": "pom.xml",
"content": "\n\n 4.0.0\n \n clueminer-parent\n org.clueminer\n 0.1.0-SNAPSHOT\n ../..\n \n\n org.clueminer\n clustering-benchmark\n 0.1.0-SNAPSHOT\n nbm\n\n clustering-benchmark\n\n \n UTF-8\n \n\n \n \n \n netbeans\n NetBeans\n http://bits.netbeans.org/maven2/\n \n false\n \n \n \n\n \n \n org.netbeans.api\n org-netbeans-api-annotations-common\n \n \n ${project.groupId}\n dataset-api\n ${project.version}\n \n \n ${project.groupId}\n clustering-impl\n ${project.version}\n \n \n ${project.groupId}\n clustering-api\n ${project.version}\n \n \n ${project.groupId}\n dataset-impl\n ${project.version}\n \n \n ${project.groupId}\n dataset-io\n ${project.version}\n \n \n ${project.groupId}\n fixtures\n ${project.version}\n \n \n ${project.groupId}\n dataset-benchmark\n ${project.version}\n \n \n org.netbeans.api\n org-openide-util-lookup\n \n \n org.netbeans.api\n org-openide-util\n \n \n ${project.groupId}\n utils\n ${project.version}\n \n \n ${project.groupId}\n clustering-evolution\n ${project.version}\n \n \n ${project.groupId}\n clustering-eval\n ${project.version}\n \n \n ${project.groupId}\n clustering-dist\n ${project.version}\n \n \n ${project.groupId}\n fixtures-clustering\n ${project.version}\n \n \n junit\n junit\n ${clueminer.junit.version}\n test\n \n \n com.beust\n jcommander\n 1.48\n \n \n ${project.groupId}\n core-lib-wrapper\n ${project.version}\n \n \n ${project.groupId}\n evolution-api\n ${project.version}\n \n \n org.clueminer\n chameleon\n ${project.version}\n \n \n ${project.groupId}\n gnuplot\n ${project.version}\n \n \n ${project.groupId}\n partitioning-api\n ${project.version}\n \n \n ${project.groupId}\n graph-api\n ${project.version}\n \n \n ${project.groupId}\n graph-impl\n ${project.version}\n \n \n ${project.groupId}\n partitioning-impl\n ${project.version}\n \n \n org.netbeans.api\n org-openide-util-ui\n \n \n\n \n \n \n org.codehaus.mojo\n nbm-maven-plugin\n true\n \n \n org.clueminer.clustering.benchmark\n org.clueminer.data\n \n \n \n\n \n \n org.apache.maven.plugins\n maven-compiler-plugin\n ${maven.compiler}\n \n 1.8\n 1.8\n \n \n org.clueminer.clustering.benchmark.Main\n org.clueminer.clustering.benchmark\n true\n \n \n \n \n\n \n org.apache.maven.plugins\n maven-jar-plugin\n 2.4\n \n \n true\n \n \n org.clueminer.clustering.benchmark.Main\n org.clueminer.clustering.benchmark\n true\n \n \n \n \n \n maven-assembly-plugin\n \n \n jar-with-dependencies\n \n \n \n org.clueminer.clustering.benchmark.Main\n \n \n \n \n \n maven-dependency-plugin\n \n \n install\n \n copy-dependencies\n \n \n ${project.build.directory}/lib\n \n \n \n \n\n \n \n\n"
},
{
"path": "run",
"content": "#!/bin/bash\nARGS=\"$@\"\nMAIN=\"org.clueminer.clustering.benchmark.Main\"\njarfile=\"$(ls -t target/*jar-with-dependencies.jar | head -1)\"\nif [[ -f \"$jarfile\" ]]; then\n java -jar $jarfile $ARGS\nelse\n mvn \"-Dexec.args=-classpath %classpath $MAIN $ARGS\" -Dexec.executable=java -Dexec.classpathScope=runtime org.codehaus.mojo:exec-maven-plugin:1.2.1:exec\nfi\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/AbsParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport com.beust.jcommander.Parameter;\nimport java.io.File;\nimport org.clueminer.utils.FileUtils;\nimport org.openide.util.NbBundle;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class AbsParams {\n\n @Parameter(names = \"--dir\", description = \"directory for results\", required = false)\n public String home = System.getProperty(\"user.home\") + File.separatorChar\n + NbBundle.getMessage(FileUtils.class, \"FOLDER_Home\");\n\n @Parameter(names = \"--repeat\", description = \"number of repetitions of each experiment\")\n public int repeat = 5;\n\n @Parameter(names = \"--log\", description = \"java log level\")\n public String log = \"INFO\";\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/Bench.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport com.beust.jcommander.JCommander;\nimport com.beust.jcommander.ParameterException;\nimport java.io.File;\nimport java.util.HashMap;\nimport java.util.Map;\nimport org.clueminer.data.DataLoader;\nimport org.clueminer.dataset.api.DataProvider;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.benchmark.DatasetFixture;\n\n/**\n *\n * @author Tomas Barton\n */\npublic abstract class Bench {\n\n protected static String benchmarkFolder;\n protected HashMap, Integer>> availableDatasets = new HashMap<>();\n protected DataProvider provider;\n\n public Bench() {\n //constructor without arguments\n }\n\n public static void ensureFolder(String folder) {\n File file = new File(folder);\n if (!file.exists()) {\n if (file.mkdirs()) {\n System.out.println(\"Directory \" + folder + \" created!\");\n } else {\n System.out.println(\"Failed to create \" + folder + \"directory!\");\n }\n }\n }\n\n public abstract void main(String[] args);\n\n public static void printUsage(String[] args, JCommander cmd, AbsParams params) {\n\n try {\n cmd.parse(args);\n\n } catch (ParameterException ex) {\n System.out.println(ex.getMessage());\n cmd.usage();\n System.exit(0);\n }\n }\n\n protected void loadDatasets() {\n Map, Integer> datasets = DatasetFixture.allDatasets();\n for (Map.Entry, Integer> entry : datasets.entrySet()) {\n Dataset d = entry.getKey();\n availableDatasets.put(d.getName(), entry);\n }\n }\n\n protected void loadBenchArtificial() {\n provider = DataLoader.createLoader(\"datasets\", \"artificial\");\n }\n\n protected void loadBenchRealWorld() {\n provider = DataLoader.createLoader(\"datasets\", \"real-world\");\n }\n\n /**\n * Load specific dataset by name\n *\n * @param name\n */\n protected void load(String name) {\n Map, Integer> datasets = DatasetFixture.allDatasets();\n for (Map.Entry, Integer> entry : datasets.entrySet()) {\n Dataset d = entry.getKey();\n if (d.getName().equalsIgnoreCase(name)) {\n availableDatasets.put(d.getName(), entry);\n }\n }\n }\n\n public static String safeName(String name) {\n return name.toLowerCase().replace(\" \", \"_\");\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/BenchParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport com.beust.jcommander.Parameter;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class BenchParams extends AbsParams {\n\n @Parameter(names = \"--n\", description = \"size of biggest dataset\", required = false)\n public int n = 20;\n\n @Parameter(names = \"--n-small\", description = \"size of smallest\", required = false)\n public int nSmall = 5;\n\n @Parameter(names = \"--steps\", description = \"number of datasets which will be generated\")\n public int steps = 4;\n\n @Parameter(names = \"--dimension\", description = \"number of attributes of each dataset\")\n public int dimension = 5;\n\n @Parameter(names = \"--linkage\", description = \"linkage method\")\n public String linkage = \"Single Linkage\";\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/ClusteringBenchmark.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport org.clueminer.clustering.aggl.linkage.CompleteLinkage;\nimport org.clueminer.clustering.aggl.linkage.SingleLinkage;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.api.AlgParams;\nimport org.clueminer.clustering.api.ClusteringAlgorithm;\nimport org.clueminer.clustering.api.ClusteringFactory;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.utils.Props;\n\n/**\n * Execute single clustering\n *\n * @author Tomas Barton\n * @param \n */\npublic class ClusteringBenchmark {\n\n public Container cluster(Dataset dataset, Props props) {\n ClusteringFactory cf = ClusteringFactory.getInstance();\n ClusteringAlgorithm algorithm = cf.getProvider(props.get(AlgParams.ALG));\n\n return new Container(algorithm, dataset, props);\n }\n\n public Container cluster(ClusteringAlgorithm algorithm, Dataset dataset, Props props) {\n return new Container(algorithm, dataset, props);\n }\n\n public Container hclust(final AgglomerativeClustering algorithm, final Dataset dataset, final String linkage) {\n Props props = new Props();\n props.put(AlgParams.LINKAGE, linkage);\n final Container runnable = new Container(algorithm, dataset, props);\n return runnable;\n }\n\n public Container singleLinkage(final AgglomerativeClustering algorithm, final Dataset dataset) {\n return hclust(algorithm, dataset, SingleLinkage.name);\n }\n\n public Container completeLinkage(final AgglomerativeClustering algorithm, final Dataset dataset) {\n return hclust(algorithm, dataset, CompleteLinkage.name);\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/Container.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport org.clueminer.clustering.TreeDiff;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.api.AlgParams;\nimport org.clueminer.clustering.api.Clustering;\nimport org.clueminer.clustering.api.ClusteringAlgorithm;\nimport org.clueminer.clustering.api.ClusteringType;\nimport org.clueminer.clustering.api.HierarchicalResult;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.exec.ClusteringExecutorCached;\nimport org.clueminer.utils.Props;\nimport org.slf4j.Logger;\nimport org.slf4j.LoggerFactory;\n\n/**\n *\n * @author Tomas Barton\n * @param \n */\npublic class Container implements Runnable {\n\n private HierarchicalResult result;\n private Clustering clustering;\n private final Dataset dataset;\n private Props params;\n private static final Logger LOG = LoggerFactory.getLogger(Container.class);\n private ClusteringExecutorCached executor;\n\n public Container(ClusteringAlgorithm algorithm, Dataset dataset) {\n this.executor = new ClusteringExecutorCached();\n executor.setAlgorithm(algorithm);\n this.dataset = dataset;\n this.params = new Props();\n }\n\n public Container(ClusteringAlgorithm algorithm, Dataset dataset, Props params) {\n this.executor = new ClusteringExecutorCached();\n executor.setAlgorithm(algorithm);\n this.dataset = dataset;\n this.params = params;\n }\n\n public HierarchicalResult hierarchical(AgglomerativeClustering algorithm, Dataset dataset, Props params) {\n params.put(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING);\n return algorithm.hierarchy(dataset, params);\n }\n\n @Override\n public void run() {\n if (executor.getAlgorithm() instanceof AgglomerativeClustering) {\n this.result = executor.hclustRows(dataset, params);\n } else {\n this.clustering = executor.clusterRows(dataset, params);\n }\n }\n\n public Clustering cluster(ClusteringAlgorithm algorithm, Dataset dataset, Props params) {\n return executor.clusterRows(dataset, params);\n }\n\n public boolean equals(Container other) {\n if (this.result == null || other.result == null) {\n throw new RuntimeException(\"got null result. this = \" + result + \" other = \" + other);\n }\n return TreeDiff.compare(this.result, other.result);\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/Experiment.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport java.util.Random;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.api.ClusteringAlgorithm;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.impl.ArrayDataset;\nimport org.clueminer.report.NanoBench;\nimport org.clueminer.utils.Props;\nimport org.openide.util.Exceptions;\nimport org.slf4j.Logger;\nimport org.slf4j.LoggerFactory;\n\n/**\n *\n * @author Tomas Barton\n * @param \n */\npublic class Experiment implements Runnable {\n\n protected final Random rand;\n protected final BenchParams params;\n private ClusteringAlgorithm[] algorithms;\n protected final String results;\n private static final Logger LOG = LoggerFactory.getLogger(Experiment.class);\n\n public Experiment(BenchParams params, String results) {\n rand = new Random();\n this.params = params;\n this.results = results;\n }\n\n public Experiment(BenchParams params, String results, ClusteringAlgorithm[] algorithms) {\n rand = new Random();\n this.params = params;\n this.results = results;\n this.algorithms = algorithms;\n }\n\n @Override\n public void run() {\n int inc = (params.n - params.nSmall) / params.steps;\n\n String[] names = new String[algorithms.length];\n int j = 0;\n for (ClusteringAlgorithm alg : algorithms) {\n names[j++] = alg.getName();\n }\n\n GnuplotReporter reporter = new GnuplotReporter(results,\n new String[]{\"algorithm\", \"linkage\", \"n\"}, names, params.nSmall + \"-\" + params.n,\n 10);\n LOG.info(\"increment = {}\", inc);\n ClusteringBenchmark bench = new ClusteringBenchmark();\n Container container;\n AgglomerativeClustering aggl;\n for (int i = params.nSmall; i <= params.n; i += inc) {\n Dataset dataset = generateData(i, params.dimension);\n for (ClusteringAlgorithm alg : algorithms) {\n String[] opts = new String[]{alg.getName(), params.linkage, String.valueOf(dataset.size())};\n\n if (alg instanceof AgglomerativeClustering) {\n aggl = (AgglomerativeClustering) alg;\n container = bench.hclust(aggl, dataset, params.linkage);\n } else {\n container = bench.cluster(alg, dataset, new Props());\n }\n\n NanoBench.create().measurements(params.repeat).collect(reporter, opts).measure(\n alg.getName() + \" - \" + dataset.size(),\n container\n );\n // Get the Java runtime\n Runtime runtime = Runtime.getRuntime();\n // Run the garbage collector\n runtime.gc();\n try {\n Thread.sleep(1000);\n } catch (InterruptedException ex) {\n Exceptions.printStackTrace(ex);\n }\n }\n }\n reporter.finish();\n }\n\n /**\n * Generate random dataset of doubles with given dimensions\n *\n * @param size\n * @param dim\n * @return\n */\n public Dataset generateData(int size, int dim) {\n LOG.info(\"generating data: {}x{}\", size, dim);\n Dataset dataset = new ArrayDataset<>(size, dim);\n for (int i = 0; i < dim; i++) {\n dataset.attributeBuilder().create(\"attr-\" + i, \"NUMERIC\");\n }\n for (int i = 0; i < size; i++) {\n dataset.instance(i).setName(String.valueOf(i));\n for (int j = 0; j < dim; j++) {\n dataset.set(i, j, rand.nextDouble());\n }\n }\n\n return dataset;\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/GnuplotReporter.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport com.google.common.collect.ObjectArrays;\nimport java.io.File;\nimport java.io.FileNotFoundException;\nimport java.io.IOException;\nimport java.io.PrintWriter;\nimport java.io.UnsupportedEncodingException;\nimport java.util.LinkedList;\nimport org.clueminer.gnuplot.GnuplotHelper;\nimport org.clueminer.gnuplot.PointTypeIterator;\nimport org.clueminer.report.BigORes;\nimport org.clueminer.report.Reporter;\nimport org.openide.util.Exceptions;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class GnuplotReporter extends GnuplotHelper implements Reporter {\n\n private final String dataDir;\n private final File dataFile;\n private final LinkedList plots;\n\n public GnuplotReporter(String folder, String[] opts, String[] algorithms, String suffix, int xCol) {\n this.dataDir = folder + File.separatorChar + \"data\";\n mkdir(dataDir);\n this.dataFile = new File(dataDir + File.separatorChar + \"results-\" + suffix + \".csv\");\n this.plots = new LinkedList<>();\n writeHeader(opts);\n\n String memPath = dataDir + File.separatorChar + \"mem\" + suffix + \".gpt\";\n String cpuPath = dataDir + File.separatorChar + \"cpu\" + suffix + \".gpt\";\n String cpu2Path = dataDir + File.separatorChar + \"cpu2\" + suffix + \".gpt\";\n String tpsPath = dataDir + File.separatorChar + \"tps\" + suffix + \".gpt\";\n String timePath = dataDir + File.separatorChar + \"time\" + suffix + \".gpt\";\n\n writePlotScript(new File(memPath),\n plotComplexity(8, \"memory (kB)\", xCol, 7, dataFile.getName(), algorithms, \"Memory usage of hierarchical clustering algorithms - \" + opts[1], false));\n writePlotScript(new File(cpuPath),\n plotCpu(8, \"CPU\", xCol, 2, dataFile.getName(), algorithms, \"CPU usage of hierarchical clustering algorithms - \" + opts[1], false));\n writePlotScript(new File(cpu2Path),\n plotComplexity(8, \"CPU time\", xCol, 2, dataFile.getName(), algorithms, \"CPU usage of hierarchical clustering algorithms - \" + opts[1], false));\n writePlotScript(new File(tpsPath),\n plotComplexity(8, \"tps\", xCol, 5, dataFile.getName(), algorithms, \"Transactuion per second - \" + opts[1], true));\n\n writePlotScript(new File(timePath),\n plotComplexity(8, \"time\", xCol, 4, dataFile.getName(), algorithms, \"Execution time - \" + opts[1], true));\n\n writeBashScript(folder);\n }\n\n private void writeHeader(String[] opts) {\n String[] head = new String[]{\"label\", \"avg time (ms)\", \"memory (MB)\", \"total time (s)\", \"tps\", \"repeats\", \"memory (kB)\"};\n String[] line = ObjectArrays.concat(head, opts, String.class);\n writeCsvLine(dataFile, line, false);\n }\n\n /**\n *\n * @param result\n */\n @Override\n public void finalResult(BigORes result) {\n String[] res = new String[]{result.getLabel(), result.avgTimeMs(),\n result.totalMemoryInMb(), result.totalTimeInS(), result.tps(),\n result.measurements(), result.totalMemoryInKb()\n };\n String[] line = ObjectArrays.concat(res, result.getOpts(), String.class);\n writeCsvLine(dataFile, line, true);\n }\n\n /**\n *\n * @param file to write Gnuplot script\n * @param dataFile\n * @param labelPos column of label which is used for data rows in chart\n * @param type\n * @param x\n * @param y\n */\n private void writePlotScript(File file, String script) {\n PrintWriter template;\n try {\n template = new PrintWriter(file, \"UTF-8\");\n template.write(script);\n template.close();\n } catch (FileNotFoundException | UnsupportedEncodingException ex) {\n Exceptions.printStackTrace(ex);\n }\n plots.add(withoutExtension(file));\n }\n\n private String plotCpu(int labelPos, String yLabel, int x, int y, String dataFile, String[] algorithms, String title, boolean logscale) {\n String res = \"set datafile separator \\\",\\\"\\n\"\n + \"set key outside bottom horizontal box\\n\"\n + \"set title \\\"\" + title + \"\\\"\\n\"\n + \"set xlabel \\\"data size\\\" font \\\"Times,12\\\"\\n\"\n + \"set ylabel \\\"\" + yLabel + \"\\\" font \\\"Times,12\\\"\\n\"\n // + \"set xtics 0,0.5 nomirror\\n\"\n // + \"set ytics 0,0.5 nomirror\\n\"\n + \"set mytics 2\\n\"\n + \"set mx2tics 2\\n\"\n + \"set grid\\n\"\n + \"set pointsize 0.5\\n\"\n + \"f(x) = 0.5 * x**2\\n\";\n if (logscale) {\n res += \"set logscale y 2\\n\";\n }\n int i = 0;\n PointTypeIterator pti = new PointTypeIterator();\n for (String alg : algorithms) {\n if (i == 0) {\n res += \"plot \";\n }\n res += \"\\\"< awk -F\\\\\\\",\\\\\\\" '{if($\" + labelPos + \" == \\\\\\\"\" + alg\n + \"\\\\\\\") print}' \" + dataFile + \"\\\" u \" + x + \":\" + y\n + \" t \\\"\" + alg + \"\\\" w linespoints pt \" + pti.next();\n res += \", \\\\\\n\";\n i++;\n }\n res += \"f(x) title 'x^2' with lines linestyle 18\\n\";\n return res;\n }\n\n private String plotComplexity(int labelPos, String yLabel, int x, int y, String dataFile, String[] algorithms, String title, boolean logscale) {\n String res = \"set datafile separator \\\",\\\"\\n\"\n + \"set key outside bottom horizontal box\\n\"\n + \"set title \\\"\" + title + \"\\\"\\n\"\n + \"set xlabel \\\"data size\\\" font \\\"Times,12\\\"\\n\"\n + \"set ylabel \\\"\" + yLabel + \"\\\" font \\\"Times,12\\\"\\n\"\n // + \"set xtics 0,0.5 nomirror\\n\"\n // + \"set ytics 0,0.5 nomirror\\n\"\n + \"set mytics 2\\n\"\n + \"set mx2tics 2\\n\"\n + \"set grid\\n\"\n + \"set pointsize 0.5\\n\";\n if (logscale) {\n res += \"set logscale y 2\\n\";\n }\n int i = 0;\n int last = algorithms.length - 1;\n PointTypeIterator pti = new PointTypeIterator();\n for (String alg : algorithms) {\n if (i == 0) {\n res += \"plot \";\n }\n res += \"\\\"< awk -F\\\\\\\",\\\\\\\" '{if($\" + labelPos + \" == \\\\\\\"\" + alg\n + \"\\\\\\\") print}' \" + dataFile + \"\\\" u \" + x + \":\" + y\n + \" t \\\"\" + alg + \"\\\" w linespoints pt \" + pti.next();\n if (i != last) {\n res += \", \\\\\\n\";\n } else {\n res += \"\\n\";\n }\n\n i++;\n }\n return res;\n }\n\n /**\n * Should be called when all plot files are written\n */\n public void finish() {\n //TODO maybe some cleanup?\n }\n\n private void writeBashScript(String dataDir) {\n try {\n bashPlotScript(plots.toArray(new String[plots.size()]), dataDir, \"data\", \"set term pdf font 'Times-New-Roman,8'\", \"pdf\");\n bashPlotScript(plots.toArray(new String[plots.size()]), dataDir, \"data\", \"set terminal pngcairo size 1024,768 enhanced font 'Verdana,10'\", \"png\");\n\n } catch (FileNotFoundException ex) {\n Exceptions.printStackTrace(ex);\n } catch (UnsupportedEncodingException ex) {\n Exceptions.printStackTrace(ex);\n } catch (IOException ex) {\n Exceptions.printStackTrace(ex);\n }\n }\n\n /**\n *\n * @param plots plot names without extension\n * @param dir base dir\n * @param gnuplotDir directory with gnuplot file\n * @param term\n * @param ext extentions of output format\n * @throws FileNotFoundException\n * @throws UnsupportedEncodingException\n * @throws IOException\n */\n public static void bashPlotScript(String[] plots, String dir, String gnuplotDir, String term, String ext)\n throws FileNotFoundException, UnsupportedEncodingException, IOException {\n //bash script to generate results\n String shFile = dir + File.separatorChar + \"_plot-\" + ext;\n try (PrintWriter template = new PrintWriter(shFile, \"UTF-8\")) {\n template.write(bashTemplate(gnuplotDir));\n template.write(\"TERM=\\\"\" + term + \"\\\"\\n\");\n int pos;\n for (String plot : plots) {\n pos = plot.indexOf(\".\");\n if (pos > 0) {\n //remove extension part\n plot = plot.substring(0, pos);\n }\n template.write(\"gnuplot -e \\\"${TERM}\\\" \" + plot + gnuplotExtension\n + \" > $PWD\" + File.separatorChar + \"..\" + File.separatorChar + plot + \".\" + ext + \"\\n\");\n }\n }\n Runtime.getRuntime().exec(\"chmod u+x \" + shFile);\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/Main.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport java.util.Arrays;\nimport java.util.HashMap;\nimport java.util.Map;\nimport org.clueminer.clustering.benchmark.chameleon2.Cham2Bench;\nimport org.clueminer.clustering.benchmark.consensus.ConsensusExp;\nimport org.clueminer.clustering.benchmark.cutoff.CutoffExp;\nimport org.clueminer.clustering.benchmark.exp.Data;\nimport org.clueminer.clustering.benchmark.exp.EvolveScores;\nimport org.clueminer.clustering.benchmark.exp.HclusPar;\nimport org.clueminer.clustering.benchmark.exp.HclusPar2;\nimport org.clueminer.clustering.benchmark.exp.Hclust;\nimport org.clueminer.clustering.benchmark.gen.NsgaGen;\nimport org.clueminer.clustering.benchmark.nsga.NsgaScore;\nimport org.clueminer.clustering.benchmark.partition.PartitionExp;\n\n/**\n *\n * @author deric\n */\npublic class Main {\n\n private static final Map map = new HashMap<>();\n private static Main instance;\n\n public Main() {\n map.put(\"hclust\", new Hclust());\n map.put(\"data\", new Data());\n map.put(\"hclust-par\", new HclusPar());\n map.put(\"hclust-par2\", new HclusPar2());\n map.put(\"evolve-sc\", new EvolveScores());\n map.put(\"nsga\", new NsgaScore());\n map.put(\"nsga-gen\", new NsgaGen());\n map.put(\"consensus\", new ConsensusExp());\n map.put(\"cutoff\", new CutoffExp());\n map.put(\"partition\", new PartitionExp());\n map.put(\"chameleon2\", new Cham2Bench());\n }\n\n /**\n * Entrypoint to all experiments\n *\n * @param args the command line arguments\n */\n public static void main(String[] args) {\n if (instance == null) {\n instance = new Main();\n }\n if (args.length == 0) {\n usage();\n }\n String exp = args[0];\n if (!Main.map.containsKey(exp)) {\n usage();\n }\n\n String[] other = Arrays.copyOfRange(args, 1, args.length);\n Bench bench = Main.map.get(exp);\n //run it\n bench.main(other);\n }\n\n private static void usage() {\n System.out.println(\"Usage: java -jar {jar name} [experiment name] [[optional arguments]]\");\n System.out.println(\"Valid experriments values are:\");\n for (String key : map.keySet()) {\n for (int i = 0; i < 5; i++) {\n System.out.print(\" \");\n }\n System.out.print(\"- \" + key + \"\\n\");\n }\n System.out.println(\"use '[experiment] --help' to find out more about optional arguments\");\n System.out.println(\"--------------------------\");\n System.exit(1);\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/ParamExperiment.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark;\n\nimport org.clueminer.clustering.api.AlgParams;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.report.NanoBench;\nimport org.clueminer.utils.Props;\nimport org.openide.util.Exceptions;\n\n/**\n *\n * @author deric\n * @param \n */\npublic class ParamExperiment extends Experiment {\n\n private Props[] configs;\n\n public ParamExperiment(BenchParams params, String results) {\n super(params, results);\n }\n\n public ParamExperiment(BenchParams params, String results, Props[] configs) {\n super(params, results);\n\n this.configs = configs;\n }\n\n @Override\n public void run() {\n int inc = (params.n - params.nSmall) / params.steps;\n\n String[] names = new String[configs.length];\n int j = 0;\n for (Props alg : configs) {\n names[j++] = alg.get(AlgParams.ALG);\n }\n\n //json props must be last column (in order to avoid issues with gnuplot parsing commas in json)\n GnuplotReporter reporter = new GnuplotReporter(results,\n new String[]{\"algorithm\", \"n\", \"config\"},\n names, params.nSmall + \"-\" + params.n, 9);\n System.out.println(\"increment = \" + inc);\n ClusteringBenchmark bench = new ClusteringBenchmark();\n Container container;\n for (int i = params.nSmall; i <= params.n; i += inc) {\n Dataset dataset = generateData(i, params.dimension);\n for (Props props : configs) {\n String[] opts = new String[]{props.get(AlgParams.ALG), String.valueOf(dataset.size()), props.toJson()};\n try {\n container = bench.cluster(dataset, props);\n NanoBench.create().measurements(params.repeat).collect(reporter, opts).measure(\n props.get(AlgParams.ALG) + \" - \" + dataset.size(),\n container\n );\n } catch (Exception ex) {\n Exceptions.printStackTrace(ex);\n }\n // Get the Java runtime\n Runtime runtime = Runtime.getRuntime();\n // Run the garbage collector\n runtime.gc();\n try {\n Thread.sleep(1000);\n } catch (InterruptedException ex) {\n Exceptions.printStackTrace(ex);\n }\n }\n }\n reporter.finish();\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/chameleon2/Cham2Bench.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.chameleon2;\n\nimport java.io.File;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.api.AlgParams;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport org.clueminer.clustering.benchmark.BenchParams;\nimport org.clueminer.clustering.benchmark.ParamExperiment;\nimport org.clueminer.clustering.benchmark.exp.Hclust;\nimport org.clueminer.log.ClmLog;\nimport org.clueminer.utils.Props;\n\n/**\n *\n * @author deric\n */\npublic class Cham2Bench extends Hclust {\n\n /**\n * @param args the command line arguments\n */\n @Override\n public void main(String[] args) {\n BenchParams params = parseArguments(args);\n ClmLog.setup(params.log);\n\n benchmarkFolder = params.home + File.separatorChar + \"chameleon2\";\n ensureFolder(benchmarkFolder);\n\n System.out.println(\"# n = \" + params.n);\n System.out.println(\"=== starting experiment:\");\n\n Props ch2 = new Props();\n ch2.put(AlgParams.ALG, \"Chameleon\");\n\n Props hc = new Props();\n hc.put(AlgParams.ALG, \"HC-LW(ms)\");\n hc.put(AlgParams.LINKAGE, \"Single\");\n\n Props dbscan = new Props();\n dbscan.put(AlgParams.ALG, \"DBSCAN\");\n\n Props km = new Props();\n km.put(AlgParams.ALG, \"k-means\");\n\n Props[] algorithms = new Props[]{\n ch2,\n hc,\n dbscan, km\n };\n ParamExperiment exp = new ParamExperiment(params, benchmarkFolder, algorithms);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/consensus/ConsensusExp.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.consensus;\n\nimport com.beust.jcommander.JCommander;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.benchmark.Bench;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.printUsage;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author deric\n */\npublic class ConsensusExp extends Bench {\n\n public static final String name = \"consensus\";\n\n protected static ConsensusParams parseArguments(String[] args) {\n ConsensusParams params = new ConsensusParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n @Override\n public void main(String[] args) {\n ConsensusParams params = parseArguments(args);\n ClmLog.setup(params.log);\n\n loadBenchArtificial();\n System.out.println(\"dataset: \" + params.dataset);\n\n benchmarkFolder = params.home + '/' + \"benchmark\" + '/' + name;\n ensureFolder(benchmarkFolder);\n System.out.println(\"writing results to: \" + benchmarkFolder);\n\n System.out.println(\"=== starting \" + name);\n ConsensusRun exp = new ConsensusRun(params, benchmarkFolder, provider.getDataset(params.dataset));\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/consensus/ConsensusParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.consensus;\n\nimport com.beust.jcommander.Parameter;\nimport org.clueminer.clustering.benchmark.AbsParams;\n\n/**\n *\n * @author deric\n */\npublic class ConsensusParams extends AbsParams {\n\n @Parameter(names = \"--dataset\", description = \"use specific dataset\")\n public String dataset = null;\n\n @Parameter(names = \"--algorithm\", description = \"clustering algorithm name\")\n public String algorithm = \"K-Means bagging\";\n\n @Parameter(names = \"--k\", description = \"expected number of clusters (some methods might not respect this)\")\n public int k = -1;\n\n @Parameter(names = \"--method\", description = \"Initialization and consensus approach\")\n public String method = \"\";\n\n @Parameter(names = \"--fixed\", description = \"whether to use 'correct' k as parameter\")\n public boolean fixedK = false;\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/consensus/ConsensusRun.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.consensus;\n\nimport com.google.common.base.Supplier;\nimport com.google.common.collect.Maps;\nimport com.google.common.collect.Table;\nimport com.google.common.collect.Tables;\nimport java.io.File;\nimport java.util.LinkedList;\nimport java.util.Map;\nimport org.clueminer.bagging.COMUSA;\nimport org.clueminer.bagging.CoAssociationReduce;\nimport org.clueminer.bagging.KMeansBagging;\nimport org.clueminer.clustering.aggl.linkage.AverageLinkage;\nimport org.clueminer.clustering.api.AlgParams;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.Clustering;\nimport org.clueminer.clustering.api.ClusteringAlgorithm;\nimport org.clueminer.clustering.api.ClusteringFactory;\nimport org.clueminer.clustering.api.Executor;\nimport org.clueminer.clustering.api.factory.EvaluationFactory;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.safeName;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.benchmark.ResultsCollector;\nimport org.clueminer.exec.ClusteringExecutorCached;\nimport org.clueminer.utils.Props;\nimport org.openide.util.Exceptions;\nimport org.slf4j.Logger;\nimport org.slf4j.LoggerFactory;\n\n/**\n *\n * @author deric\n */\npublic class ConsensusRun implements Runnable {\n\n private static ResultsCollector rc;\n private ConsensusParams params;\n private String benchmarkFolder;\n //table for keeping results from experiments\n private Table table;\n private static final Logger LOG = LoggerFactory.getLogger(ConsensusRun.class);\n private Dataset dataset;\n\n public ConsensusRun(ConsensusParams params, String benchmarkFolder, Dataset dataset) {\n this.params = params;\n this.benchmarkFolder = benchmarkFolder;\n this.dataset = dataset;\n\n createTable();\n rc = new ResultsCollector(table);\n }\n\n private void createTable() {\n table = Tables.newCustomTable(\n Maps.>newHashMap(),\n new Supplier>() {\n @Override\n public Map get() {\n return Maps.newHashMap();\n }\n });\n }\n\n @Override\n public void run() {\n try {\n String name;\n String algorithm;\n String folder;\n EvaluationFactory ef = EvaluationFactory.getInstance();\n LinkedList evals = new LinkedList<>();\n evals.add(ef.getProvider(\"NMI-sqrt\"));\n evals.add(ef.getProvider(\"NMI-sum\"));\n evals.add(ef.getProvider(\"Adjusted Rand\"));\n evals.add(ef.getProvider(\"Deviation\"));\n\n ClusteringAlgorithm alg = ClusteringFactory.getInstance().getProvider(params.algorithm);\n algorithm = safeName(alg.getName());\n Executor exec = new ClusteringExecutorCached(alg);\n\n createTable();\n name = safeName(dataset.getName());\n folder = benchmarkFolder + File.separatorChar + name;\n ensureFolder(folder);\n\n String csvRes = folder + File.separatorChar + algorithm + \"_\" + params.method + \"_\" + name + \".csv\";\n LOG.info(\"dataset: {} size: {} num attr: {}\", name, dataset.size(), dataset.attributeCount());\n //ensureFolder(benchmarkFolder + File.separatorChar + name);\n Clustering c;\n Props props = algorithmSetup(params.method);\n if (params.fixedK) {\n props.putBoolean(KMeansBagging.FIXED_K, true);\n }\n if (params.k > 0) {\n props.putInt(\"k\", params.k);\n } else if (!props.containsKey(\"k\") && props.getBoolean(KMeansBagging.FIXED_K, false)) {\n //use \"correct\" number of clusters if k not specified\n props.putInt(\"k\", dataset.getClasses().size());\n }\n double score;\n System.out.println(props.toString());\n for (int i = 0; i < params.repeat; i++) {\n c = exec.clusterRows(dataset, props);\n for (ClusterEvaluation eval : evals) {\n if (c.getEvaluationTable() != null) {\n score = c.getEvaluationTable().getScore(eval);\n } else {\n score = eval.score(c);\n }\n System.out.println(eval.getName() + \": \" + score + \", clusters: \" + c.size());\n table.put(\"run \" + i, eval.getName(), score);\n }\n }\n rc.writeAvgColsCsv(table, csvRes);\n\n } catch (Exception e) {\n Exceptions.printStackTrace(e);\n }\n }\n\n private Props algorithmSetup(String alg) {\n Props p = new Props();\n p.putInt(KMeansBagging.BAGGING, 10);\n switch (alg) {\n case \"KmB-COMUSA-RAND\":\n p.put(KMeansBagging.CONSENSUS, COMUSA.name);\n p.put(KMeansBagging.INIT_METHOD, \"RANDOM\");\n p.putDouble(COMUSA.RELAX, 1.0);\n p.putInt(KMeansBagging.MAX_K, 25);\n break;\n case \"KmB-COMUSA-MO\":\n p.put(KMeansBagging.CONSENSUS, COMUSA.name);\n p.put(KMeansBagging.INIT_METHOD, \"MO\");\n p.putDouble(COMUSA.RELAX, 1.0);\n p.put(\"mo_1\", \"AIC\");\n p.put(\"mo_2\", \"SD index\");\n p.putInt(KMeansBagging.MAX_K, 25);\n break;\n case \"KmB-COMUSA-RAND-fixed\":\n p.put(KMeansBagging.CONSENSUS, COMUSA.name);\n p.put(KMeansBagging.INIT_METHOD, \"RANDOM\");\n p.putDouble(COMUSA.RELAX, 1.0);\n p.putBoolean(KMeansBagging.FIXED_K, true);\n break;\n case \"KmB-CoAssocHAC-MO-avg\":\n p.put(KMeansBagging.CONSENSUS, CoAssociationReduce.name);\n p.put(KMeansBagging.INIT_METHOD, \"MO\");\n p.put(\"mo_1\", \"AIC\");\n p.put(\"mo_2\", \"SD index\");\n p.put(AlgParams.LINKAGE, AverageLinkage.name);\n break;\n case \"KmB-CoAssocHAC-MO-AIC_SD\":\n p.put(KMeansBagging.CONSENSUS, CoAssociationReduce.name);\n p.put(KMeansBagging.INIT_METHOD, \"MO\");\n p.put(\"mo_1\", \"AIC\");\n p.put(\"mo_2\", \"SD index\");\n break;\n default:\n break;\n\n }\n return p;\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/cutoff/CutoffComparison.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.cutoff;\n\nimport java.io.File;\nimport java.io.PrintWriter;\nimport java.util.ArrayList;\nimport java.util.HashMap;\nimport java.util.LinkedList;\nimport java.util.Map;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.api.Cluster;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.Clustering;\nimport org.clueminer.clustering.api.ClusteringFactory;\nimport org.clueminer.clustering.api.CutoffStrategy;\nimport org.clueminer.clustering.api.HierarchicalResult;\nimport org.clueminer.clustering.api.InternalEvaluator;\nimport org.clueminer.clustering.api.ScoreException;\nimport org.clueminer.clustering.api.factory.CutoffStrategyFactory;\nimport org.clueminer.clustering.api.factory.EvaluationFactory;\nimport org.clueminer.clustering.api.factory.InternalEvaluatorFactory;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.safeName;\nimport org.clueminer.io.csv.CSVWriter;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.eval.hclust.HillClimbCutoff;\nimport org.clueminer.utils.Props;\nimport org.openide.util.Exceptions;\nimport org.slf4j.LoggerFactory;\n\n/**\n *\n * @author Tomas Bruna\n */\npublic class CutoffComparison implements Runnable {\n\n private final CutoffParams params;\n private final String benchmarkFolder;\n private final ArrayList> datasets;\n private Map averages;\n private LinkedList externalEvals;\n private CSVWriter csv;\n private static final org.slf4j.Logger LOG = LoggerFactory.getLogger(CutoffComparison.class);\n\n public CutoffComparison(CutoffParams params, String benchmarkFolder, ArrayList> datasets) {\n this.params = params;\n this.benchmarkFolder = benchmarkFolder;\n this.datasets = datasets;\n loadExternalEvals();\n }\n\n @Override\n public void run() {\n try {\n String folder;\n AgglomerativeClustering alg = (AgglomerativeClustering) ClusteringFactory.getInstance().getProvider(params.algorithm);\n folder = benchmarkFolder + File.separatorChar + \"Cutoff comparison\";\n ensureFolder(folder);\n String csvRes = folder + File.separatorChar + \"Cutoff comparison with \" + safeName(alg.getName()) + \" on \" + datasets.size() + \" datasets.csv\";\n\n PrintWriter writer = new PrintWriter(csvRes, \"UTF-8\");\n csv = new CSVWriter(writer, ',');\n csv.writeLine(alg.getName());\n\n initAverages();\n for (Dataset dataset : datasets) {\n System.out.println(\"Running comparisons on \" + dataset.getName());\n //create dendrogram\n HierarchicalResult rowsResult = alg.hierarchy(dataset, new Props());\n writeHeader(dataset);\n\n String strategies[] = params.strategies.split(\",\");\n String internalEvals[] = params.internalEvals.split(\",\");\n //try different cutoff methods\n for (String strategy : strategies) {\n for (String internalEval : internalEvals) {\n CutoffStrategy cutoff = getCutoffStrategy(strategy.trim(), internalEval.trim());\n rowsResult.findCutoff(cutoff);\n Clustering c = rowsResult.getClustering();\n\n averages.get(strategy.trim() + internalEval.trim()).addValues(c);\n writeValues(cutoff, internalEval.trim(), c);\n\n if (!(cutoff instanceof HillClimbCutoff) || !(cutoff instanceof HillClimbCutoff)) {\n break;\n }\n }\n }\n csv.writeLine(\"\");\n csv.writeLine(\"\");\n }\n writeAverages();\n csv.close();\n } catch (Exception e) {\n Exceptions.printStackTrace(e);\n }\n }\n\n private void loadExternalEvals() {\n String evals[] = params.externalEvals.split(\",\");\n externalEvals = new LinkedList<>();\n EvaluationFactory ef = EvaluationFactory.getInstance();\n for (String eval : evals) {\n externalEvals.add(ef.getProvider(eval.trim()));\n }\n }\n\n private void writeHeader(Dataset dataset) {\n csv.writeLine(\"Dataset_\" + safeName(dataset.getName()));\n String row[] = new String[externalEvals.size() + 2];\n row[0] = \"Cutoff strategy\";\n row[1] = \"Internal eval\";\n int i = 2;\n for (ClusterEvaluation eval : externalEvals) {\n row[i] = eval.getName();\n i++;\n }\n csv.writeNext(row);\n }\n\n private void writeValues(CutoffStrategy cutoff, String internaEval, Clustering c) {\n String row[] = new String[externalEvals.size() + 2];\n row[0] = cutoff.getName();\n if (cutoff instanceof HillClimbCutoff || cutoff instanceof HillClimbCutoff) {\n row[1] = internaEval;\n } else {\n row[1] = \"\";\n }\n int i = 2;\n for (ClusterEvaluation eval : externalEvals) {\n double score;\n if (c.getEvaluationTable() != null) {\n score = c.getEvaluationTable().getScore(eval);\n } else {\n try {\n score = eval.score(c);\n } catch (ScoreException ex) {\n score = Double.NaN;\n LOG.info(\"failed to compute score {}: {}\", eval.getName(), ex.getMessage());\n }\n }\n row[i] = String.valueOf(score);\n i++;\n }\n csv.writeNext(row);\n }\n\n private void writeAverages() {\n csv.writeLine(\"AVERAGES\");\n String row[] = new String[externalEvals.size() + 2];\n for (Average average : averages.values()) {\n row[0] = average.name;\n row[1] = \"\";\n int i = 2;\n for (ClusterEvaluation eval : externalEvals) {\n row[i] = String.valueOf(average.getAverage(eval.getName()));\n i++;\n }\n csv.writeNext(row);\n }\n }\n\n private CutoffStrategy getCutoffStrategy(String strategy, String eval) {\n CutoffStrategy cutoffStrategy = CutoffStrategyFactory.getInstance().getProvider(strategy);\n InternalEvaluatorFactory> ief = InternalEvaluatorFactory.getInstance();\n InternalEvaluator evaluator = ief.getProvider(eval);\n cutoffStrategy.setEvaluator(evaluator);\n return cutoffStrategy;\n }\n\n private void initAverages() {\n averages = new HashMap<>();\n String strategies[] = params.strategies.split(\",\");\n String internalEvals[] = params.internalEvals.split(\",\");\n for (String strategy : strategies) {\n for (String internalEval : internalEvals) {\n CutoffStrategy cutoff = getCutoffStrategy(strategy.trim(), internalEval.trim());\n if (!(cutoff instanceof HillClimbCutoff) || !(cutoff instanceof HillClimbCutoff)) {\n averages.put(strategy.trim() + internalEval.trim(), new Average(strategy.trim()));\n break;\n } else {\n averages.put(strategy.trim() + internalEval.trim(), new Average(strategy.trim() + \" with \" + internalEval.trim()));\n }\n }\n }\n\n }\n\n private class Average {\n\n String name;\n LinkedList evals;\n Map sum;\n Map cnt;\n\n Average(String name) {\n this.name = name;\n sum = new HashMap<>();\n cnt = new HashMap<>();\n for (ClusterEvaluation eval : externalEvals) {\n sum.put(eval.getName(), 0.0);\n cnt.put(eval.getName(), 0);\n }\n }\n\n public double getAverage(String eval) {\n return sum.get(eval) / cnt.get(eval);\n }\n\n public void addValues(Clustering c) {\n double score;\n for (ClusterEvaluation eval : externalEvals) {\n if (c.getEvaluationTable() != null) {\n score = c.getEvaluationTable().getScore(eval);\n } else {\n try {\n score = eval.score(c);\n } catch (ScoreException ex) {\n score = Double.NaN;\n LOG.info(\"failed to compute score {}: {}\", eval.getName(), ex.getMessage());\n }\n }\n sum.put(eval.getName(), sum.get(eval.getName()) + score);\n cnt.put(eval.getName(), cnt.get(eval.getName()) + 1);\n }\n }\n\n }\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/cutoff/CutoffExp.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.cutoff;\n\nimport com.beust.jcommander.JCommander;\nimport java.util.ArrayList;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.benchmark.Bench;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.printUsage;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\n\n/**\n *\n * @author Tomas Bruna\n */\npublic class CutoffExp extends Bench {\n\n public static final String name = \"cutoff\";\n\n protected static CutoffParams parseArguments(String[] args) {\n CutoffParams params = new CutoffParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n @Override\n public void main(String[] args) {\n CutoffParams params = parseArguments(args);\n\n loadBenchArtificial();\n System.out.println(\"datasets: \" + params.datasets);\n\n benchmarkFolder = params.home + '/' + \"benchmark\" + '/' + name;\n ensureFolder(benchmarkFolder);\n System.out.println(\"writing results to: \" + benchmarkFolder);\n\n System.out.println(\"=== starting \" + name);\n Runnable exp = null;\n switch (params.mode) {\n case \"comparison\": {\n exp = new CutoffComparison(params, benchmarkFolder, createDatasetsArray(params.datasets));\n break;\n }\n case \"firstJump\": {\n exp = new FirstJumpOptimization(params, benchmarkFolder, createDatasetsArray(params.datasets));\n break;\n }\n default: {\n throw new IllegalArgumentException(\"Mode \" + params.mode + \" is not supported\");\n }\n }\n\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n private ArrayList> createDatasetsArray(String datasets) {\n String stringSets[] = datasets.split(\",\");\n ArrayList> sets = new ArrayList<>(stringSets.length);\n for (String dataset : stringSets) {\n sets.add(provider.getDataset(dataset.trim()));\n }\n return sets;\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/cutoff/CutoffParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.cutoff;\n\nimport com.beust.jcommander.Parameter;\nimport org.clueminer.clustering.benchmark.AbsParams;\n\n/**\n *\n * @author Tomas Bruna\n */\npublic class CutoffParams extends AbsParams {\n\n @Parameter(names = \"--datasets\", description = \"Datasets to test separated by ,\")\n public String datasets = \"triangle1, triangle2, flame, jain, long1, long2, long3, sizes1, sizes2, sizes3,\"\n + \" sizes4, sizes5, compound, atom, aggregation, lsun, pathbased, smile1, smile2, smile3, twodiamonds, \"\n + \"wingnut, target, st900, square1, square2, square3, square4, square5, spiral, spiral2, spherical_6_2, \"\n + \"spherical_5_2, longsquare, engytime, donutcurves, diamond9, complex8, complex9, chainlink, R15, D31, \"\n + \"2d-4c, 2d-20c-no0, 2d-10c\";\n\n @Parameter(names = \"--algorithm\", description = \"Clustering algorithm name\")\n public String algorithm = \"Chameleon\";\n\n @Parameter(names = \"--strategy\", description = \"Cutoff strategies to compare separated by ,\")\n public String strategies = \"hill-climb cutoff, hill-climb inc, First jump cutoff\";\n\n @Parameter(names = \"--internalEvals\", description = \"Iternal evaluations to compare separated by ,\")\n public String internalEvals = \"Silhouette, SD index\";\n\n @Parameter(names = \"--externalEvals\", description = \"External evaluations to determine quality of results\"\n + \" separated by ,\")\n public String externalEvals = \"NMI-sqrt, NMI-sum, Deviation, Adjusted Rand\";\n\n @Parameter(names = \"--startRange\", description = \"Range of the start parameter the in the First jump cutoff\")\n public String startRange = \"30-400\";\n\n @Parameter(names = \"--factorRange\", description = \"Range of the factor parameter in the First jump cutoff\")\n public String factorRange = \"1.01-6\";\n\n @Parameter(names = \"--mode\", description = \"Whether to compare different cutoff methods (option comparison)\"\n + \" or to try different parameters for the First jump cutoff (option firstJump)\")\n public String mode = \"comparison\";\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/cutoff/FirstJumpOptimization.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.cutoff;\n\nimport java.io.File;\nimport java.io.IOException;\nimport java.io.PrintWriter;\nimport java.util.ArrayList;\nimport java.util.LinkedList;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.Clustering;\nimport org.clueminer.clustering.api.ClusteringFactory;\nimport org.clueminer.clustering.api.CutoffStrategy;\nimport org.clueminer.clustering.api.HierarchicalResult;\nimport org.clueminer.clustering.api.ScoreException;\nimport org.clueminer.clustering.api.factory.CutoffStrategyFactory;\nimport org.clueminer.clustering.api.factory.EvaluationFactory;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.safeName;\nimport org.clueminer.io.csv.CSVWriter;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.eval.hclust.FirstJump;\nimport org.clueminer.utils.Props;\nimport org.openide.util.Exceptions;\n\n/**\n *\n * @author Tomas Bruna\n */\npublic class FirstJumpOptimization implements Runnable {\n\n private final CutoffParams params;\n private final String benchmarkFolder;\n private final ArrayList> datasets;\n private LinkedList dendrograms;\n FirstJump cutoff;\n ClusterEvaluation eval;\n\n public FirstJumpOptimization(CutoffParams params, String benchmarkFolder, ArrayList> datasets) {\n this.params = params;\n this.benchmarkFolder = benchmarkFolder;\n this.datasets = datasets;\n EvaluationFactory ef = EvaluationFactory.getInstance();\n eval = ef.getProvider(\"NMI-sqrt\");\n cutoff = (FirstJump) getCutoffStrategy(\"First jump cutoff\");\n }\n\n @Override\n public void run() {\n try {\n String folder;\n AgglomerativeClustering alg = (AgglomerativeClustering) ClusteringFactory.getInstance().getProvider(params.algorithm);\n folder = benchmarkFolder + File.separatorChar + \"FirstJumpParams\";\n ensureFolder(folder);\n String csvRes = folder + File.separatorChar + safeName(alg.getName()) + \"_\" + \"FirstJumpParams\" + \".csv\";\n\n PrintWriter writer = new PrintWriter(csvRes, \"UTF-8\");\n CSVWriter csv = new CSVWriter(writer, ',');\n csv.writeLine(\"Clustering_with_\" + alg.getName());\n\n computeDendrograms(alg);\n\n String startRange[] = params.startRange.split(\"-\");\n String factorRange[] = params.factorRange.split(\"-\");\n\n for (int i = Integer.valueOf(startRange[0]); i <= Integer.valueOf(startRange[1]); i += 10) {\n double j = Double.valueOf(factorRange[0]);\n while (j <= Double.valueOf(factorRange[1])) {\n csv.writeLine(\"AVERAGE_WITH_\" + i + \"_AND_\" + j + \": \" + testParameters(i, j));\n j += 0.1;\n }\n }\n csv.close();\n } catch (NumberFormatException | IOException e) {\n Exceptions.printStackTrace(e);\n }\n }\n\n /**\n * Try cutoff with specified parameters on all results\n *\n * @param i\n * @param j\n * @return\n */\n private double testParameters(int i, double j) {\n System.out.println(\"Testing \" + i + \" and \" + j);\n double score;\n Clustering c;\n cutoff.setStart(i);\n cutoff.setFactor(j);\n double sum = 0;\n int cnt = 0;\n //compute cutoff on all results\n for (HierarchicalResult rowsResult : dendrograms) {\n rowsResult.findCutoff(cutoff);\n c = rowsResult.getClustering();\n if (c.getEvaluationTable() != null) {\n score = c.getEvaluationTable().getScore(eval);\n } else {\n try {\n score = eval.score(c);\n } catch (ScoreException ex) {\n score = Double.NaN;\n Exceptions.printStackTrace(ex);\n }\n }\n sum += score;\n cnt++;\n }\n return sum / cnt;\n }\n\n /**\n * Cluster all datasets and save results\n *\n * @param alg\n */\n private void computeDendrograms(AgglomerativeClustering alg) {\n dendrograms = new LinkedList<>();\n for (Dataset dataset : datasets) {\n HierarchicalResult rowsResult = alg.hierarchy(dataset, new Props());\n dendrograms.add(rowsResult);\n }\n }\n\n private CutoffStrategy getCutoffStrategy(String strategy) {\n CutoffStrategy cutoffStrategy = CutoffStrategyFactory.getInstance().getProvider(strategy);\n return cutoffStrategy;\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/evolve/EvolveExp.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.evolve;\n\nimport com.google.common.base.Supplier;\nimport com.google.common.collect.Maps;\nimport com.google.common.collect.Table;\nimport com.google.common.collect.Tables;\nimport java.io.File;\nimport java.util.HashMap;\nimport java.util.Map;\nimport java.util.Map.Entry;\nimport org.clueminer.clustering.api.AlgParams;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.factory.ExternalEvaluatorFactory;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.safeName;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.benchmark.GnuplotWriter;\nimport org.clueminer.dataset.benchmark.ResultsCollector;\nimport org.clueminer.evolution.multim.MultiMuteEvolution;\nimport org.clueminer.evolution.utils.ConsoleDump;\nimport org.openide.util.Exceptions;\n\n/**\n * Evolution of hierarchical clusterings with different (unsupervised)\n * optimization criterion (single criterion)\n *\n * @author Tomas Barton\n */\npublic class EvolveExp implements Runnable {\n\n private static ResultsCollector rc;\n private EvolveParams params;\n private String benchmarkFolder;\n private ClusterEvaluation[] scores;\n private HashMap, Integer>> datasets;\n //table for keeping results from experiments\n private final Table table;\n\n public EvolveExp(EvolveParams params, String benchmarkFolder, ClusterEvaluation[] scores, HashMap, Integer>> availableDatasets) {\n this.params = params;\n this.benchmarkFolder = benchmarkFolder;\n this.scores = scores;\n this.datasets = availableDatasets;\n\n table = Tables.newCustomTable(\n Maps.>newHashMap(),\n new Supplier>() {\n @Override\n public Map get() {\n return Maps.newHashMap();\n }\n });\n rc = new ResultsCollector(table);\n }\n\n @Override\n public void run() {\n try {\n MultiMuteEvolution evolution;\n String name;\n\n ClusterEvaluation ext = fetchExternal(params.external);\n //evolution.setAlgorithm(new HACLW());\n System.out.println(\"datasets size: \" + datasets.size());\n for (Map.Entry, Integer>> e : datasets.entrySet()) {\n Dataset d = e.getValue().getKey();\n name = safeName(d.getName());\n String csvRes = benchmarkFolder + File.separatorChar + name + File.separatorChar + name + \".csv\";\n System.out.println(\"=== dataset \" + name);\n System.out.println(\"size: \" + d.size());\n ensureFolder(benchmarkFolder + File.separatorChar + name);\n for (ClusterEvaluation eval : scores) {\n evolution = new MultiMuteEvolution();\n evolution.setDataset(d);\n evolution.setEvaluator(eval);\n evolution.setExternal(ext);\n evolution.setGenerations(params.generations);\n evolution.setPopulationSize(params.population);\n GnuplotWriter gw = new GnuplotWriter(evolution, benchmarkFolder, name + File.separatorChar + safeName(eval.getName()));\n gw.setPlotDumpMod(50);\n gw.setCustomTitle(\"cutoff=\" + evolution.getDefaultParam(AlgParams.CUTOFF_STRATEGY) + \"(\" + evolution.getDefaultParam(AlgParams.CUTOFF_SCORE) + \")\");\n //collect data from evolution\n evolution.addEvolutionListener(new ConsoleDump());\n evolution.addEvolutionListener(gw);\n evolution.addEvolutionListener(rc);\n evolution.run();\n System.out.println(\"## updating results in: \" + csvRes);\n rc.writeToCsv(csvRes);\n }\n }\n } catch (Exception e) {\n Exceptions.printStackTrace(e);\n }\n }\n\n private ClusterEvaluation fetchExternal(String external) {\n return ExternalEvaluatorFactory.getInstance().getProvider(external);\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/evolve/EvolveParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.evolve;\n\nimport com.beust.jcommander.Parameter;\nimport org.clueminer.clustering.benchmark.AbsParams;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class EvolveParams extends AbsParams {\n\n @Parameter(names = \"--external\", description = \"reference criterion for comparing with internal criterion (Precision, Accuracy, NMI)\")\n public String external = \"AUC\";\n\n @Parameter(names = \"--test\", description = \"test only on one dataset\")\n public boolean test = false;\n\n @Parameter(names = \"--generations\", description = \"number of generations in evolution\")\n public int generations = 10;\n\n @Parameter(names = \"--population\", description = \"size of population in each generation\")\n public int population = 10;\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/exp/Data.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.exp;\n\nimport com.google.common.base.Supplier;\nimport com.google.common.collect.Maps;\nimport com.google.common.collect.Table;\nimport com.google.common.collect.Tables;\nimport java.io.File;\nimport java.util.HashMap;\nimport java.util.Map;\nimport org.clueminer.clustering.algorithm.KMeans;\nimport org.clueminer.clustering.api.Cluster;\nimport org.clueminer.clustering.api.ExternalEvaluator;\nimport org.clueminer.clustering.api.InternalEvaluator;\nimport org.clueminer.clustering.api.factory.InternalEvaluatorFactory;\nimport org.clueminer.clustering.benchmark.Bench;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.benchmark.GnuplotWriter;\nimport org.clueminer.dataset.benchmark.ResultsCollector;\nimport org.clueminer.eval.external.JaccardIndex;\nimport org.clueminer.evolution.attr.AttrEvolution;\nimport org.clueminer.evolution.utils.ConsoleDump;\nimport org.clueminer.utils.FileUtils;\nimport org.openide.util.NbBundle;\n\n/**\n *\n * @author tombart\n */\npublic class Data extends Bench {\n\n private AttrEvolution test;\n //table for keeping results from experiments\n private Table table;\n private static ResultsCollector rc;\n private static String csvOutput;\n private static Data instance;\n\n /**\n * @param args the command line arguments\n */\n @Override\n public void main(String[] args) {\n int i = 0, j;\n String arg;\n char flag;\n boolean vflag = false;\n String datasetName = \"\";\n\n while (i < args.length && args[i].startsWith(\"-\")) {\n arg = args[i++];\n\n // use this type of check for \"wordy\" arguments\n switch (arg) {\n // use this type of check for arguments that require arguments\n case \"-verbose\":\n System.out.println(\"verbose mode on\");\n vflag = true;\n break;\n // use this type of check for a series of flag arguments\n case \"-dataset\":\n if (i < args.length) {\n datasetName = args[i++];\n } else {\n System.err.println(\"-dataset requires a name\");\n }\n if (vflag) {\n System.out.println(\"dataset = \" + datasetName);\n }\n break;\n default:\n for (j = 1; j < arg.length(); j++) {\n flag = arg.charAt(j);\n switch (flag) {\n case 'x':\n if (vflag) {\n System.out.println(\"Option x\");\n }\n break;\n case 'n':\n if (vflag) {\n System.out.println(\"Option n\");\n }\n break;\n default:\n System.err.println(\"Run: illegal option \" + flag);\n break;\n }\n }\n break;\n }\n }\n if (i == args.length) {\n System.err.println(\"Usage: Benchmark [-verbose] [-xn] [-dataset name]\");\n }\n\n init();\n execute(datasetName);\n }\n\n private void init() {\n table = Tables.newCustomTable(\n Maps.>newHashMap(),\n new Supplier>() {\n @Override\n public Map get() {\n return Maps.newHashMap();\n }\n });\n\n String home = System.getProperty(\"user.home\") + File.separatorChar\n + NbBundle.getMessage(\n FileUtils.class,\n \"FOLDER_Home\");\n ensureFolder(home);\n benchmarkFolder = home + File.separatorChar + \"benchmark\";\n ensureFolder(benchmarkFolder);\n rc = new ResultsCollector(table);\n csvOutput = benchmarkFolder + File.separatorChar + \"results.csv\";\n\n //preload dataset names\n loadDatasets();\n }\n\n public void execute(String datasetName) {\n Map, Integer> datasets = new HashMap<>();\n if (availableDatasets.containsKey(datasetName)) {\n Map.Entry, Integer> entry = availableDatasets.get(datasetName);\n datasets.put(entry.getKey(), entry.getValue());\n } else {\n System.out.println(\"dataset \" + datasetName + \" not found\");\n System.out.println(\"known datasets: \");\n for (String d : availableDatasets.keySet()) {\n System.out.print(d + \" \");\n }\n System.out.println(\"---\");\n }\n // DatasetFixture.allDatasets();\n\n InternalEvaluatorFactory> factory = InternalEvaluatorFactory.getInstance();\n ExternalEvaluator ext = new JaccardIndex();\n\n String name;\n System.out.println(\"working folder: \" + benchmarkFolder);\n for (Map.Entry, Integer> entry : datasets.entrySet()) {\n Dataset dataset = entry.getKey();\n name = dataset.getName();\n String csvRes = benchmarkFolder + File.separatorChar + name + File.separatorChar + name + \".csv\";\n System.out.println(\"=== dataset \" + name);\n System.out.println(\"size: \" + dataset.size());\n System.out.println(dataset.toString());\n String dataDir = benchmarkFolder + File.separatorChar + name;\n (new File(dataDir)).mkdir();\n for (InternalEvaluator eval : factory.getAll()) {\n System.out.println(\"evaluator: \" + eval.getName());\n test = new AttrEvolution(dataset, 20);\n test.setAlgorithm(new KMeans());\n test.setK(entry.getValue());\n test.setEvaluator(eval);\n test.setExternal(ext);\n GnuplotWriter gw = new GnuplotWriter(test, benchmarkFolder, name + \"/\" + name + \"-\" + safeName(eval.getName()));\n gw.setPlotDumpMod(50);\n //collect data from evolution\n test.addEvolutionListener(new ConsoleDump());\n test.addEvolutionListener(gw);\n test.addEvolutionListener(rc);\n test.run();\n rc.writeToCsv(csvRes);\n }\n }\n }\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/exp/EvolveScores.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.exp;\n\nimport com.beust.jcommander.JCommander;\nimport java.util.List;\nimport java.util.Map;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.InternalEvaluator;\nimport org.clueminer.clustering.api.factory.InternalEvaluatorFactory;\nimport org.clueminer.clustering.benchmark.Bench;\nimport org.clueminer.clustering.benchmark.evolve.EvolveExp;\nimport org.clueminer.clustering.benchmark.evolve.EvolveParams;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class EvolveScores extends Bench {\n\n public static final String name = \"evolve-sc\";\n\n protected static EvolveParams parseArguments(String[] args) {\n EvolveParams params = new EvolveParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n @Override\n public void main(String[] args) {\n EvolveParams params = parseArguments(args);\n if (params.test) {\n load(\"iris\");\n } else {\n loadDatasets();\n }\n ClmLog.setup(params.log);\n System.out.println(\"loaded dataset\");\n int i = 0;\n for (Map.Entry, Integer>> e : availableDatasets.entrySet()) {\n System.out.println((i++) + \":\" + e.getKey());\n }\n\n benchmarkFolder = params.home + '/' + \"benchmark\" + '/' + name;\n ensureFolder(benchmarkFolder);\n System.out.println(\"writing results to: \" + benchmarkFolder);\n\n System.out.println(\"=== starting \" + name);\n List eval = InternalEvaluatorFactory.getInstance().getAll();\n ClusterEvaluation[] scores = eval.toArray(new ClusterEvaluation[eval.size()]);\n System.out.println(\"scores size: \" + scores.length);\n EvolveExp exp = new EvolveExp(params, benchmarkFolder, scores, availableDatasets);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/exp/HclusPar.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.exp;\n\nimport java.io.File;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.aggl.HCLW;\nimport org.clueminer.clustering.aggl.HCLWMS;\nimport org.clueminer.clustering.aggl.HacLwMsPar;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport org.clueminer.clustering.benchmark.BenchParams;\nimport org.clueminer.clustering.benchmark.Experiment;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author deric\n */\npublic class HclusPar extends Hclust {\n\n /**\n * @param args the command line arguments\n */\n @Override\n public void main(String[] args) {\n BenchParams params = parseArguments(args);\n ClmLog.setup(params.log);\n\n benchmarkFolder = params.home + File.separatorChar + \"benchmark\" + File.separatorChar + \"hclust-par\";\n ensureFolder(benchmarkFolder);\n\n System.out.println(\"# n = \" + params.n);\n System.out.println(\"=== starting experiment:\");\n AgglomerativeClustering[] algorithms = new AgglomerativeClustering[]{\n new HCLW(), new HCLWMS(), new HacLwMsPar(4), new HacLwMsPar(8), new HacLwMsPar(16), new HacLwMsPar(32)\n };\n Experiment exp = new Experiment(params, benchmarkFolder, algorithms);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/exp/HclusPar2.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.exp;\n\nimport java.io.File;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.aggl.HCLW;\nimport org.clueminer.clustering.aggl.HCLWMS;\nimport org.clueminer.clustering.aggl.HacLwMsPar;\nimport org.clueminer.clustering.aggl.HacLwMsPar2;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.benchmark.BenchParams;\nimport org.clueminer.clustering.benchmark.Experiment;\nimport static org.clueminer.clustering.benchmark.exp.Hclust.parseArguments;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class HclusPar2 extends Hclust {\n\n /**\n * @param args the command line arguments\n */\n @Override\n public void main(String[] args) {\n BenchParams params = parseArguments(args);\n ClmLog.setup(params.log);\n\n benchmarkFolder = params.home + File.separatorChar + \"hclust-par2\";\n ensureFolder(benchmarkFolder);\n\n System.out.println(\"# n = \" + params.n);\n System.out.println(\"=== starting experiment:\");\n AgglomerativeClustering[] algorithms = new AgglomerativeClustering[]{\n new HCLW(), new HCLWMS(), new HacLwMsPar(2), new HacLwMsPar(4), new HacLwMsPar2(2), new HacLwMsPar2(4)\n };\n Experiment exp = new Experiment(params, benchmarkFolder, algorithms);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/exp/Hclust.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.exp;\n\nimport com.beust.jcommander.JCommander;\nimport com.beust.jcommander.ParameterException;\nimport java.io.File;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.aggl.HC;\nimport org.clueminer.clustering.aggl.HCLW;\nimport org.clueminer.clustering.aggl.HCLWMS;\nimport org.clueminer.clustering.api.AgglomerativeClustering;\nimport org.clueminer.clustering.benchmark.Bench;\nimport org.clueminer.clustering.benchmark.BenchParams;\nimport org.clueminer.clustering.benchmark.Experiment;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author deric\n */\npublic class Hclust extends Bench {\n\n protected static Hclust instance;\n\n /**\n * @param args the command line arguments\n */\n @Override\n public void main(String[] args) {\n BenchParams params = parseArguments(args);\n ClmLog.setup(params.log);\n\n benchmarkFolder = params.home + File.separatorChar + \"benchmark\" + File.separatorChar + \"hclust\";\n ensureFolder(benchmarkFolder);\n\n System.out.println(\"# n = \" + params.n);\n System.out.println(\"=== starting experiment:\");\n AgglomerativeClustering[] algorithms = new AgglomerativeClustering[]{new HC(), new HCLW(), new HCLWMS()};\n Experiment exp = new Experiment(params, benchmarkFolder, algorithms);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n protected static BenchParams parseArguments(String[] args) {\n BenchParams params = new BenchParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n public static void printUsage(String[] args, JCommander cmd, BenchParams params) {\n /* if (args.length == 0) { StringBuilder sb = new StringBuilder();\n * cmd.usage(sb);\n * sb.append(\"\\n\").append(\"attributes marked with * are mandatory\");\n * System.out.println(sb);\n * System.err.println(\"missing mandatory arguments\");\n * System.exit(0);\n * } */\n try {\n cmd.parse(args);\n /**\n * TODO validate values of parameters\n */\n if (params.n <= 0 || params.dimension <= 0) {\n throw new ParameterException(\"invalid data dimensions \" + params.n + \" x \" + params.dimension);\n }\n\n if (params.steps <= 0) {\n throw new ParameterException(\"invalid steps size \" + params.steps);\n }\n\n if (params.nSmall == params.n) {\n throw new ParameterException(\"n can't be same as n-small! \" + params.nSmall);\n }\n\n } catch (ParameterException ex) {\n System.out.println(ex.getMessage());\n cmd.usage();\n System.exit(0);\n }\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/gen/NsgaGen.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.gen;\n\nimport com.beust.jcommander.JCommander;\nimport java.util.Map;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.api.Cluster;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.factory.InternalEvaluatorFactory;\nimport org.clueminer.clustering.benchmark.Bench;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.printUsage;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author deric\n */\npublic class NsgaGen extends Bench {\n\n public static final String name = \"nsga-gen\";\n\n protected static NsgaGenParams parseArguments(String[] args) {\n NsgaGenParams params = new NsgaGenParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n @Override\n public void main(String[] args) {\n NsgaGenParams params = parseArguments(args);\n if (params.dataset != null) {\n load(params.dataset);\n } else {\n loadDatasets();\n }\n ClmLog.setup(params.log);\n\n int i = 0;\n for (Map.Entry, Integer>> e : availableDatasets.entrySet()) {\n System.out.println((i++) + \":\" + e.getKey());\n }\n\n benchmarkFolder = params.home + '/' + \"benchmark\" + '/' + name;\n ensureFolder(benchmarkFolder);\n System.out.println(\"writing results to: \" + benchmarkFolder);\n\n System.out.println(\"=== starting \" + name);\n InternalEvaluatorFactory> factory = InternalEvaluatorFactory.getInstance();\n ClusterEvaluation c1 = factory.getProvider(params.c1);\n ClusterEvaluation c2 = factory.getProvider(params.c2);\n NsgaGenExp exp = new NsgaGenExp(params, benchmarkFolder, c1, c2, availableDatasets);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/gen/NsgaGenExp.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.gen;\n\nimport com.google.common.base.Supplier;\nimport com.google.common.collect.Maps;\nimport com.google.common.collect.Table;\nimport com.google.common.collect.Tables;\nimport java.io.File;\nimport java.util.HashMap;\nimport java.util.Map;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.factory.EvaluationFactory;\nimport static org.clueminer.clustering.benchmark.Bench.safeName;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.benchmark.GnuplotMO;\nimport org.clueminer.dataset.benchmark.ResultsCollector;\nimport org.clueminer.evolution.mo.MoEvolution;\nimport org.clueminer.evolution.utils.ConsoleDump;\nimport org.openide.util.Exceptions;\nimport org.slf4j.Logger;\nimport org.slf4j.LoggerFactory;\n\n/**\n *\n * @author deric\n */\npublic class NsgaGenExp implements Runnable {\n\n private static ResultsCollector rc;\n private NsgaGenParams params;\n private String benchmarkFolder;\n private HashMap, Integer>> datasets;\n //table for keeping results from experiments\n private Table table;\n private ClusterEvaluation c1;\n private ClusterEvaluation c2;\n private static final Logger LOG = LoggerFactory.getLogger(NsgaGenExp.class);\n\n public NsgaGenExp(NsgaGenParams params, String benchmarkFolder, ClusterEvaluation c1, ClusterEvaluation c2, HashMap, Integer>> availableDatasets) {\n this.params = params;\n this.benchmarkFolder = benchmarkFolder;\n this.c1 = c1;\n this.c2 = c2;\n this.datasets = availableDatasets;\n\n createTable();\n rc = new ResultsCollector(table);\n }\n\n private void createTable() {\n table = Tables.newCustomTable(\n Maps.>newHashMap(),\n new Supplier>() {\n @Override\n public Map get() {\n return Maps.newHashMap();\n }\n });\n }\n\n @Override\n public void run() {\n try {\n MoEvolution evolution = new MoEvolution();\n\n evolution.setPopulationSize(params.population);\n evolution.setNumSolutions(params.solutions);\n evolution.setExternal(EvaluationFactory.getInstance().getProvider(\"Jaccard\"));\n evolution.setMutationProbability(params.mutation);\n evolution.setCrossoverProbability(params.crossover);\n\n GnuplotMO gw = new GnuplotMO();\n //gw.setCustomTitle(\"cutoff=\" + evolution.getDefaultParam(AgglParams.CUTOFF_STRATEGY) + \"(\" + evolution.getDefaultParam(AgglParams.CUTOFF_SCORE) + \")\");\n //collect data from evolution\n evolution.addEvolutionListener(new ConsoleDump());\n evolution.addMOEvolutionListener(gw);\n evolution.addMOEvolutionListener(rc);\n evolution.addObjective(c1);\n evolution.addObjective(c2);\n\n int[] generations = new int[]{1, 10, 50, 100, 1000};\n\n String name;\n String folder;\n LOG.info(\"datasets size: {}\", datasets.size());\n for (Map.Entry, Integer>> e : datasets.entrySet()) {\n Dataset d = e.getValue().getKey();\n name = safeName(d.getName());\n folder = benchmarkFolder + File.separatorChar + name;\n gw.mkdir(folder);\n String csvRes = folder + File.separatorChar + \"_\" + name + \".csv\";\n LOG.info(\"dataset: {} size: {} num attr: {}\", name, d.size(), d.attributeCount());\n //ensureFolder(benchmarkFolder + File.separatorChar + name);\n\n evolution.setDataset(d);\n\n for (int i = 0; i < generations.length; i++) {\n int g = generations[i];\n evolution.setGenerations(g);\n gw.setCurrentDir(benchmarkFolder, name + \"-\" + g);\n //for (int k = 0; k < params.repeat; k++) {\n // logger.log(Level.INFO, \"run {0}: {1} & {2}\", new Object[]{k, c1.getName(), c2.getName()});\n evolution.run();\n rc.writeToCsv(csvRes);\n //}\n evolution.fireFinishedBatch();\n }\n createTable();\n }\n } catch (Exception e) {\n Exceptions.printStackTrace(e);\n }\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/gen/NsgaGenParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.gen;\n\nimport com.beust.jcommander.Parameter;\nimport org.clueminer.clustering.benchmark.AbsParams;\n\n/**\n *\n * @author deric\n */\npublic class NsgaGenParams extends AbsParams {\n\n @Parameter(names = \"--population\", description = \"size of population in each generation\")\n public int population = 20;\n\n @Parameter(names = \"--solutions\", description = \"number of final solutions which will be returned as result\")\n public int solutions = 10;\n\n @Parameter(names = \"--mutation\", description = \"probability of mutation\")\n public double mutation = 0.5;\n\n @Parameter(names = \"--crossover\", description = \"probability of crossover\")\n public double crossover = 0.5;\n\n @Parameter(names = \"--dataset\", description = \"use specific dataset\")\n public String dataset = null;\n\n @Parameter(names = \"--c1\", description = \"criterion 1\")\n public String c1 = \"Davies-Bouldin\";\n\n @Parameter(names = \"--c2\", description = \"criterion 2\")\n public String c2 = \"AIC\";\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaExp.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.nsga;\n\nimport com.google.common.base.Supplier;\nimport com.google.common.collect.Maps;\nimport com.google.common.collect.Table;\nimport com.google.common.collect.Tables;\nimport java.io.File;\nimport java.util.HashMap;\nimport java.util.Map;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.factory.EvaluationFactory;\nimport static org.clueminer.clustering.benchmark.Bench.safeName;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.benchmark.GnuplotMO;\nimport org.clueminer.dataset.benchmark.ResultsCollector;\nimport org.clueminer.evolution.mo.MoEvolution;\nimport org.clueminer.evolution.utils.ConsoleDump;\nimport org.openide.util.Exceptions;\nimport org.slf4j.Logger;\nimport org.slf4j.LoggerFactory;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class NsgaExp implements Runnable {\n\n private static ResultsCollector rc;\n private NsgaParams params;\n private String benchmarkFolder;\n private ClusterEvaluation[] scores;\n private HashMap, Integer>> datasets;\n //table for keeping results from experiments\n private Table table;\n private static final Logger LOG = LoggerFactory.getLogger(NsgaExp.class);\n\n public NsgaExp(NsgaParams params, String benchmarkFolder, ClusterEvaluation[] scores, HashMap, Integer>> availableDatasets) {\n this.params = params;\n this.benchmarkFolder = benchmarkFolder;\n this.scores = scores;\n this.datasets = availableDatasets;\n\n createTable();\n rc = new ResultsCollector(table);\n }\n\n @Override\n public void run() {\n try {\n MoEvolution evolution = new MoEvolution();\n evolution.setGenerations(params.generations);\n evolution.setPopulationSize(params.population);\n evolution.setNumSolutions(params.solutions);\n evolution.setExternal(EvaluationFactory.getInstance().getProvider(params.supervised));\n evolution.setMutationProbability(params.mutation);\n evolution.setCrossoverProbability(params.crossover);\n evolution.setkLimit(params.limitK);\n ClusterEvaluation c1, c2;\n\n GnuplotMO gw = new GnuplotMO();\n //gw.setCustomTitle(\"cutoff=\" + evolution.getDefaultParam(AgglParams.CUTOFF_STRATEGY) + \"(\" + evolution.getDefaultParam(AgglParams.CUTOFF_SCORE) + \")\");\n //collect data from evolution\n evolution.addEvolutionListener(new ConsoleDump());\n evolution.addMOEvolutionListener(gw);\n evolution.addMOEvolutionListener(rc);\n\n String name;\n LOG.info(\"datasets size: {}\", datasets.size());\n for (Map.Entry, Integer>> e : datasets.entrySet()) {\n Dataset d = e.getValue().getKey();\n name = safeName(d.getName());\n String csvRes = benchmarkFolder + File.separatorChar + name + File.separatorChar + \"_\" + name + \".csv\";\n LOG.info(\"dataset: {} size: {} num attr: {}\", name, d.size(), d.attributeCount());\n //ensureFolder(benchmarkFolder + File.separatorChar + name);\n\n gw.setCurrentDir(benchmarkFolder, name);\n\n evolution.setDataset(d);\n\n for (int i = 0; i < scores.length; i++) {\n c1 = scores[i];\n //lower triangular matrix without diagonal\n //(doesn't matter which criterion is first, we want to try\n //all combinations)\n for (int j = 0; j < i; j++) {\n c2 = scores[j];\n evolution.clearObjectives();\n evolution.addObjective(c1);\n evolution.addObjective(c2);\n //run!\n for (int k = 0; k < params.repeat; k++) {\n LOG.info(\"run {}: {} & {}\", k, c1.getName(), c2.getName());\n evolution.run();\n rc.writeToCsv(csvRes);\n }\n evolution.fireFinishedBatch();\n LOG.info(\"finished {} & {}\", c1.getName(), c2.getName());\n }\n }\n createTable();\n }\n } catch (Exception e) {\n Exceptions.printStackTrace(e);\n }\n }\n\n private void createTable() {\n table = Tables.newCustomTable(\n Maps.>newHashMap(),\n new Supplier>() {\n @Override\n public Map get() {\n return Maps.newHashMap();\n }\n });\n }\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.nsga;\n\nimport com.beust.jcommander.Parameter;\nimport org.clueminer.clustering.benchmark.AbsParams;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class NsgaParams extends AbsParams {\n\n @Parameter(names = \"--test\", description = \"test only on one dataset\")\n public boolean test = false;\n\n @Parameter(names = \"--generations\", description = \"number of generations in evolution\")\n public int generations = 10;\n\n @Parameter(names = \"--population\", description = \"size of population in each generation\")\n public int population = 20;\n\n @Parameter(names = \"--solutions\", description = \"number of final solutions which will be returned as result\")\n public int solutions = 10;\n\n @Parameter(names = \"--supervised\", description = \"supervised criterion for external evaluation\")\n public String supervised = \"Adjusted Rand\";\n\n @Parameter(names = \"--mutation\", description = \"probability of mutation\")\n public double mutation = 0.5;\n\n @Parameter(names = \"--crossover\", description = \"probability of crossover\")\n public double crossover = 0.5;\n\n @Parameter(names = \"--dataset\", description = \"use specific dataset\")\n public String dataset = null;\n\n @Parameter(names = \"--limit-k\", description = \"limit max. clusterings size to sqrt(n)\")\n public boolean limitK = false;\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaScore.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.nsga;\n\nimport com.beust.jcommander.JCommander;\nimport java.util.List;\nimport java.util.Map;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.api.ClusterEvaluation;\nimport org.clueminer.clustering.api.InternalEvaluator;\nimport org.clueminer.clustering.api.factory.InternalEvaluatorFactory;\nimport org.clueminer.clustering.benchmark.Bench;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.printUsage;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.log.ClmLog;\n\n/**\n *\n * @author Tomas Barton\n */\npublic class NsgaScore extends Bench {\n\n public static final String name = \"nsga-scores\";\n\n protected static NsgaParams parseArguments(String[] args) {\n NsgaParams params = new NsgaParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n @Override\n public void main(String[] args) {\n NsgaParams params = parseArguments(args);\n if (params.test || params.dataset != null) {\n if (params.test) {\n load(\"iris\");\n } else {\n load(params.dataset);\n }\n } else {\n loadDatasets();\n }\n System.out.println(\"loaded dataset\");\n ClmLog.setup(params.log);\n\n int i = 0;\n for (Map.Entry, Integer>> e : availableDatasets.entrySet()) {\n System.out.println((i++) + \":\" + e.getKey());\n }\n\n benchmarkFolder = params.home + '/' + \"benchmark\" + '/' + name;\n ensureFolder(benchmarkFolder);\n System.out.println(\"writing results to: \" + benchmarkFolder);\n\n System.out.println(\"=== starting \" + name);\n List eval = InternalEvaluatorFactory.getInstance().getAll();\n ClusterEvaluation[] scores = eval.toArray(new ClusterEvaluation[eval.size()]);\n System.out.println(\"scores size: \" + scores.length);\n NsgaExp exp = new NsgaExp(params, benchmarkFolder, scores, availableDatasets);\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/partition/PartitionBench.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.partition;\n\nimport java.util.Random;\nimport static org.clueminer.chameleon.Chameleon.K;\nimport static org.clueminer.chameleon.Chameleon.MAX_PARTITION;\nimport org.clueminer.clustering.benchmark.GnuplotReporter;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.impl.ArrayDataset;\nimport org.clueminer.graph.adjacencyMatrix.AdjMatrixGraph;\nimport org.clueminer.graph.api.Graph;\nimport org.clueminer.graph.knn.KNNGraphBuilder;\nimport org.clueminer.partitioning.api.Partitioning;\nimport org.clueminer.report.NanoBench;\nimport org.clueminer.utils.Props;\nimport org.openide.util.Exceptions;\n\n/**\n *\n * @author deric\n */\npublic class PartitionBench implements Runnable {\n\n protected final Random rand;\n protected final PartitionParams params;\n protected final Partitioning[] algorithms;\n protected final String results;\n\n public PartitionBench(PartitionParams params, String results, Partitioning[] algorithms) {\n rand = new Random();\n this.params = params;\n this.results = results;\n this.algorithms = algorithms;\n }\n\n @Override\n public void run() {\n int inc = (params.n - params.nSmall) / params.steps;\n\n String[] names = new String[algorithms.length];\n int j = 0;\n for (Partitioning alg : algorithms) {\n names[j++] = alg.getName();\n }\n\n GnuplotReporter reporter = new GnuplotReporter(results,\n new String[]{\"algorithm\", \"edges\", \"n\"}, names, params.nSmall + \"-\" + params.n, 10);\n System.out.println(\"increment = \" + inc);\n KNNGraphBuilder knn = new KNNGraphBuilder();\n Props pref = new Props();\n for (int i = params.nSmall; i <= params.n; i += inc) {\n Graph g = new AdjMatrixGraph(i);\n Dataset dataset = generateData(i, params.dimension);\n int datasetK = determineK(dataset);\n int maxPartitionSize = determineMaxPartitionSize(dataset);\n pref.putInt(MAX_PARTITION, maxPartitionSize);\n pref.putInt(K, datasetK);\n g = knn.getNeighborGraph(dataset, g, datasetK);\n\n for (Partitioning alg : algorithms) {\n String[] opts = new String[]{alg.getName(), String.valueOf(g.getEdgeCount()), String.valueOf(dataset.size())};\n NanoBench.create().measurements(params.repeat).collect(reporter, opts).measure(\n alg.getName() + \" - \" + dataset.size(),\n bench(alg, g, maxPartitionSize, pref)\n );\n // Get the Java runtime\n Runtime runtime = Runtime.getRuntime();\n // Run the garbage collector\n runtime.gc();\n try {\n Thread.sleep(1000);\n } catch (InterruptedException ex) {\n Exceptions.printStackTrace(ex);\n }\n }\n }\n reporter.finish();\n }\n\n public Runnable bench(final Partitioning algorithm, final Graph g, final int maxPartitionSize, final Props props) {\n\n final Runnable runnable = new Runnable() {\n\n @Override\n public void run() {\n algorithm.partition(maxPartitionSize, g, props);\n }\n\n };\n return runnable;\n }\n\n /**\n * Generate random dataset of doubles with given dimensions\n *\n * @param size\n * @param dim\n * @return\n */\n protected Dataset generateData(int size, int dim) {\n System.out.println(\"generating data: \" + size + \" x \" + dim);\n Dataset dataset = new ArrayDataset<>(size, dim);\n for (int i = 0; i < dim; i++) {\n dataset.attributeBuilder().create(\"attr-\" + i, \"NUMERIC\");\n }\n for (int i = 0; i < size; i++) {\n dataset.instance(i).setName(String.valueOf(i));\n for (int j = 0; j < dim; j++) {\n dataset.set(i, j, rand.nextDouble());\n }\n }\n\n return dataset;\n }\n\n private int determineK(Dataset dataset) {\n\n if (dataset.size() < 500) {\n return (int) (Math.log(dataset.size()) / Math.log(2));\n } else {\n return (int) (Math.log(dataset.size()) / Math.log(2)) * 2;\n }\n }\n\n private int determineMaxPartitionSize(Dataset dataset) {\n if (dataset.size() < 500) {\n return 5;\n } else if ((dataset.size() < 2000)) {\n return dataset.size() / 100;\n } else {\n return dataset.size() / 200;\n }\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/partition/PartitionExp.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.partition;\n\nimport com.beust.jcommander.JCommander;\nimport java.util.concurrent.ExecutorService;\nimport java.util.concurrent.Executors;\nimport org.clueminer.clustering.benchmark.Bench;\nimport static org.clueminer.clustering.benchmark.Bench.ensureFolder;\nimport static org.clueminer.clustering.benchmark.Bench.printUsage;\nimport org.clueminer.partitioning.api.Partitioning;\nimport org.clueminer.partitioning.impl.RecursiveBisection;\n\n/**\n * An experiment to test time complexity of graph partitioning methods\n *\n * @author deric\n */\npublic class PartitionExp extends Bench {\n\n public static final String name = \"partition\";\n\n protected static PartitionParams parseArguments(String[] args) {\n PartitionParams params = new PartitionParams();\n JCommander cmd = new JCommander(params);\n printUsage(args, cmd, params);\n return params;\n }\n\n @Override\n public void main(String[] args) {\n PartitionParams params = parseArguments(args);\n\n benchmarkFolder = params.home + '/' + \"benchmark\" + '/' + name;\n ensureFolder(benchmarkFolder);\n System.out.println(\"writing results to: \" + benchmarkFolder);\n\n System.out.println(\"=== starting \" + name);\n\n Partitioning[] algorithms = new Partitioning[]{\n new RecursiveBisection()\n };\n\n Runnable exp = new PartitionBench(params, name, algorithms);\n\n ExecutorService execService = Executors.newFixedThreadPool(1);\n execService.submit(exp);\n execService.shutdown();\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/clustering/benchmark/partition/PartitionParams.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.clustering.benchmark.partition;\n\nimport com.beust.jcommander.Parameter;\nimport org.clueminer.clustering.benchmark.AbsParams;\n\n/**\n *\n * @author deric\n */\npublic class PartitionParams extends AbsParams {\n\n @Parameter(names = \"--n\", description = \"size of biggest dataset\", required = false)\n public int n = 20;\n\n @Parameter(names = \"--n-small\", description = \"size of smallest\", required = false)\n public int nSmall = 5;\n\n @Parameter(names = \"--steps\", description = \"number of datasets which will be generated\")\n public int steps = 4;\n\n @Parameter(names = \"--dimension\", description = \"number of attributes of each dataset\")\n public int dimension = 5;\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/data/DataLoader.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.data;\n\nimport java.io.File;\nimport java.io.FileNotFoundException;\nimport java.io.FileOutputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.OutputStream;\nimport java.net.URL;\nimport java.util.Collection;\nimport java.util.HashMap;\nimport java.util.Iterator;\nimport java.util.Map;\nimport java.util.TreeMap;\nimport org.clueminer.dataset.api.DataProvider;\nimport org.clueminer.dataset.api.Dataset;\nimport org.clueminer.dataset.api.Instance;\nimport org.clueminer.dataset.impl.ArrayDataset;\nimport org.clueminer.exception.ParserError;\nimport org.clueminer.io.arff.ARFFHandler;\nimport org.openide.util.Exceptions;\n\n/**\n *\n * @author deric\n */\npublic class DataLoader implements DataProvider {\n\n private final Map datasets;\n private final Map fullPaths;\n private final Map> cache;\n private String prefix = \"datasets\" + File.separatorChar + \"artificial\";\n\n public DataLoader(Map datasets, String prefix, Map fullPaths) {\n this.datasets = datasets;\n this.cache = new HashMap<>(datasets.size());\n this.prefix = prefix;\n this.fullPaths = fullPaths;\n }\n\n @Override\n public String[] getDatasetNames() {\n return datasets.keySet().toArray(new String[0]);\n }\n\n @Override\n public Dataset getDataset(String name) {\n if (cache.containsKey(name)) {\n return cache.get(name);\n }\n if (!datasets.containsKey(name)) {\n throw new RuntimeException(\"unknown dataset \" + name);\n }\n\n Dataset dataset = loadDataset(name, datasets.get(name), fullPaths.get(name));\n cache.put(name, dataset);\n return dataset;\n }\n\n @Override\n public Dataset first() {\n Iterator it = datasets.keySet().iterator();\n if (!it.hasNext()) {\n throw new RuntimeException(\"no datasets were loaded\");\n }\n return getDataset(it.next());\n }\n\n @Override\n public int count() {\n return datasets.size();\n }\n\n /**\n * Tries to load dataset by its name. There must be a method for loading the\n * dataset in this class.\n *\n * @param name\n * @return\n */\n private Dataset loadDataset(String name, String type, String fullPath) {\n Dataset dataset = null;\n switch (type) {\n case \"arff\":\n //TODO: multi dimensions support\n dataset = new ArrayDataset(10, 2);\n dataset.setName(name);\n ARFFHandler arff = new ARFFHandler();\n try {\n arff.load(resource(name + \".\" + type, fullPath), dataset);\n } catch (FileNotFoundException | ParserError ex) {\n Exceptions.printStackTrace(ex);\n }\n break;\n default:\n throw new RuntimeException(\"unsupported format \" + type);\n }\n\n return dataset;\n }\n\n /**\n * Resource packed in jar is not possible to open directly, this method uses\n * a .tmp file which should be on exit deleted\n *\n * @param path\n * @param fullPath\n * @return\n */\n public File resource(String path, String fullPath) {\n String resource = prefix + File.separatorChar + path;\n File file;\n URL url = DataLoader.class.getResource(resource);\n if (url == null) {\n //probably on Windows\n file = new File(fullPath);\n if (file.exists()) {\n return file;\n }\n //non existing URL\n //no classpath, compiled as JAR\n //if path is in form: \"jar:path.jar!resource/data.arff\"\n int pos = fullPath.lastIndexOf(\"!\");\n if (pos > 0) {\n resource = fullPath.substring(pos + 1);\n if (!resource.startsWith(\"/\")) {\n //necessary for loading as a stream\n resource = \"/\" + resource;\n }\n }\n return loadResource(resource);\n }\n\n if (url.toString().startsWith(\"jar:\")) {\n return loadResource(resource);\n } else {\n file = new File(url.getFile());\n }\n return file;\n }\n\n private File loadResource(String resource) {\n File file = null;\n try {\n InputStream input = getClass().getResourceAsStream(resource);\n file = File.createTempFile(\"nodesfile\", \".tmp\");\n OutputStream out = new FileOutputStream(file);\n int read;\n byte[] bytes = new byte[1024];\n\n while ((read = input.read(bytes)) != -1) {\n out.write(bytes, 0, read);\n }\n file.deleteOnExit();\n } catch (IOException ex) {\n System.err.println(ex.toString());\n }\n return file;\n }\n\n public static DataProvider createLoader(String p1, String p2) {\n String path = p1 + File.pathSeparatorChar + p2;\n Map datasets = new TreeMap<>();\n Map paths = new HashMap<>();\n\n final Collection list = ResourceList.getResources(p1, p2);\n int idx, dot;\n String dataset;\n String ext;\n for (final String name : list) {\n idx = name.lastIndexOf(File.separatorChar);\n dot = name.lastIndexOf(\".\");\n if (dot > 0) {\n dataset = name.substring(idx + 1, dot);\n } else {\n dataset = name;\n }\n ext = name.substring(dot + 1);\n datasets.put(dataset, ext);\n paths.put(dataset, name);\n }\n\n return new DataLoader(datasets, path, paths);\n }\n\n @Override\n public Iterator> iterator() {\n return new DataLoaderIterator();\n }\n\n @Override\n public boolean hasDataset(String name) {\n for (String dataset : datasets.keySet()) {\n if (name.equals(dataset)) {\n return true;\n }\n }\n return false;\n }\n\n private class DataLoaderIterator implements Iterator> {\n\n private final Iterator it;\n\n public DataLoaderIterator() {\n it = datasets.keySet().iterator();\n }\n\n @Override\n public boolean hasNext() {\n return it.hasNext();\n }\n\n @Override\n public Dataset next() {\n return getDataset(it.next());\n }\n\n @Override\n public void remove() {\n throw new UnsupportedOperationException(\"not supported yet.\");\n }\n\n }\n\n}\n"
},
{
"path": "src/main/java/org/clueminer/data/ResourceList.java",
"content": "/*\n * Copyright (C) 2011-2016 clueminer.org\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License as published by\n * the Free Software Foundation, either version 3 of the License, or\n * (at your option) any later version.\n *\n * This program is distributed in the hope that it will be useful,\n * but WITHOUT ANY WARRANTY; without even the implied warranty of\n * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n * GNU General Public License for more details.\n *\n * You should have received a copy of the GNU General Public License\n * along with this program. If not, see .\n */\npackage org.clueminer.data;\n\nimport java.io.File;\nimport java.io.FileInputStream;\nimport java.io.FileNotFoundException;\nimport java.io.IOException;\nimport java.net.URISyntaxException;\nimport java.net.URL;\nimport java.net.URLDecoder;\nimport java.util.Collection;\nimport java.util.Enumeration;\nimport java.util.LinkedList;\nimport java.util.List;\nimport java.util.jar.JarEntry;\nimport java.util.jar.JarFile;\nimport java.util.regex.Pattern;\nimport java.util.zip.ZipEntry;\nimport java.util.zip.ZipInputStream;\nimport org.openide.util.Exceptions;\nimport org.openide.util.Utilities;\n\n/**\n * code from\n * @link http://stackoverflow.com/questions/3923129/get-a-list-of-resources-from-classpath-directory\n * @author deric\n */\npublic class ResourceList {\n\n private static final String OS = System.getProperty(\"os.name\").toLowerCase();\n\n /**\n * for all elements of java.class.path get a Collection of resources Pattern\n * pattern = Pattern.compile(\".*\"); gets all resources\n *\n * @param p1 first part of path\n * @param p2 second part of path\n * @return the resources in the order they are found\n */\n public static Collection getResources(String p1, String p2) {\n final List retval = new LinkedList<>();\n final String classPath = System.getProperty(\"java.class.path\", \".\");\n String pathSeparator;\n //platform independent regexp\n Pattern pattern = Pattern.compile(\"(.*)\" + p1 + \"(.)\" + p2 + \"(.*)\");\n if (isWindows()) {\n try {\n Enumeration en = ResourceList.class.getClassLoader().getResources(\"datasets\");\n if (en.hasMoreElements()) {\n URL metaInf = en.nextElement();\n File fileMetaInf = Utilities.toFile(metaInf.toURI());\n browseFiles(retval, fileMetaInf, pattern);\n }\n } catch (IOException | URISyntaxException ex) {\n Exceptions.printStackTrace(ex);\n }\n if (retval.size() > 0) {\n return retval;\n }\n pathSeparator = \";\";\n } else {\n pathSeparator = \":\";\n }\n //when running from IDE we can use classpath a directly read files from disk\n final String[] classPathElements = classPath.split(pathSeparator);\n for (final String element : classPathElements) {\n retval.addAll(getResources(element, pattern));\n }\n if (retval.isEmpty()) {\n //last resort, when compiled into JAR\n loadFromJar(retval, pattern);\n }\n return retval;\n }\n\n private static void browseFiles(final List retval, File fileMetaInf, final Pattern pattern) {\n File[] files = fileMetaInf.listFiles();\n for (File f : files) {\n if (f.isDirectory()) {\n browseFiles(retval, f, pattern);\n } else {\n String fileName = f.getAbsolutePath();\n final boolean accept = pattern.matcher(fileName).matches();\n if (accept) {\n retval.add(fileName);\n }\n }\n }\n }\n\n private static Collection getResources(final String element, final Pattern pattern) {\n final List retval = new LinkedList<>();\n final File file = new File(element);\n if (file.isDirectory()) {\n retval.addAll(getResourcesFromDirectory(file, pattern));\n } else if (file.exists()) {\n retval.addAll(getResourcesFromJarFile(file, pattern));\n } else {\n System.err.println(\"can't open file: \" + file);\n }\n return retval;\n }\n\n private static Collection getResourcesFromJarFile(final File file, final Pattern pattern) {\n final List retval = new LinkedList<>();\n ZipInputStream zip = null;\n try {\n zip = new ZipInputStream(new FileInputStream(file));\n } catch (FileNotFoundException ex) {\n Exceptions.printStackTrace(ex);\n }\n\n if (zip != null) {\n try {\n while (zip.available() == 1) {\n final ZipEntry ze = zip.getNextEntry();\n final String fileName = ze.getName();\n final boolean accept = pattern.matcher(fileName).matches();\n if (accept) {\n retval.add(fileName);\n }\n zip.closeEntry();\n }\n zip.close();\n } catch (IOException ex) {\n Exceptions.printStackTrace(ex);\n }\n }\n\n return retval;\n }\n\n private static Collection getResourcesFromDirectory(\n final File directory,\n final Pattern pattern) {\n final List retval = new LinkedList<>();\n final File[] fileList = directory.listFiles();\n for (final File file : fileList) {\n if (file.isDirectory()) {\n retval.addAll(getResourcesFromDirectory(file, pattern));\n } else {\n try {\n final String fileName = file.getCanonicalPath();\n final boolean accept = pattern.matcher(fileName).matches();\n if (accept) {\n retval.add(fileName);\n }\n } catch (final IOException e) {\n throw new Error(e);\n }\n }\n }\n return retval;\n }\n\n public static boolean isWindows() {\n return (OS.contains(\"win\"));\n }\n\n public static boolean isMac() {\n return (OS.contains(\"mac\"));\n }\n\n public static boolean isUnix() {\n return (OS.contains(\"nix\") || OS.contains(\"nux\") || OS.contains(\"aix\"));\n }\n\n public static boolean isSolaris() {\n return (OS.contains(\"sunos\"));\n }\n\n /**\n * List resources from compiled JAR and choose those matching some pattern\n *\n * @param retval\n * @param pattern\n */\n private static void loadFromJar(List retval, Pattern pattern) {\n try {\n Enumeration en = ResourceList.class.getClassLoader().getResources(\"datasets\");\n if (en.hasMoreElements()) {\n URL metaInf = en.nextElement();\n File file;\n\n String path = metaInf.getPath();\n String jarFilePath = path.substring(path.indexOf(\":\") + 1, path.indexOf(\"!\"));\n jarFilePath = URLDecoder.decode(jarFilePath, \"UTF-8\");\n file = new File(jarFilePath);\n\n try (JarFile jar = new JarFile(file)) {\n JarEntry entry;\n String fileName;\n Enumeration enumer = jar.entries();\n while (enumer.hasMoreElements()) {\n entry = enumer.nextElement();\n fileName = entry.getName();\n if (pattern.matcher(fileName).matches()) {\n //don't add directories\n if (!fileName.endsWith(\"/\")) {\n retval.add(\"jar:\" + jarFilePath + \"!\" + fileName);\n }\n }\n }\n\n }\n }\n } catch (IOException ex) {\n Exceptions.printStackTrace(ex);\n }\n }\n\n}\n"
},
{
"path": "src/main/nbm/manifest.mf",
"content": "Manifest-Version: 1.0\nOpenIDE-Module-Localizing-Bundle: org/clueminer/clustering/benchmark/Bundle.properties\n"
},
{
"path": "src/main/resources/datasets/artificial/2d-10c.arff",
"content": "@RELATION 2d-10c\n%\n@ATTRIBUTE a0 REAL\n@ATTRIBUTE a1 REAL\n@ATTRIBUTE CLASS 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},
{
"path": "src/main/resources/datasets/artificial/2d-20c-no0.arff",
"content": "% Data from J. Handl\n% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html\n%\n@RELATION 2d-20c-no0\n\n@ATTRIBUTE x REAL\n@ATTRIBUTE y REAL\n@ATTRIBUTE class 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},
{
"path": "src/main/resources/datasets/artificial/2d-3c-no123.arff",
"content": "% Data from J. Handl\n% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html\n%\n@RELATION 2d-3c-no123\n\n@ATTRIBUTE a0 REAL\n@ATTRIBUTE a1 REAL\n@ATTRIBUTE class 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},
{
"path": "src/main/resources/datasets/artificial/2d-4c-no4.arff",
"content": "% Data from J. Handl\n% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html\n%\n@RELATION 2d-4c-no4\n\n@ATTRIBUTE a0 REAL\n@ATTRIBUTE a1 REAL\n@ATTRIBUTE class 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},
{
"path": "src/main/resources/datasets/artificial/2d-4c-no9.arff",
"content": "% Data from J. Handl\n% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html\n%\n@RELATION 2d-4c-no9\n\n@ATTRIBUTE a0 REAL\n@ATTRIBUTE a1 REAL\n@ATTRIBUTE class 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},
{
"path": "src/main/resources/datasets/artificial/2d-4c.arff",
"content": "% Data from J. Handl\n% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html\n%\n@RELATION 2d-4c.arff\n\n@ATTRIBUTE a0 REAL\n@ATTRIBUTE a1 REAL\n@ATTRIBUTE class 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},
{
"path": "src/main/resources/datasets/artificial/2dnormals.arff",
"content": "% Data generated using R package 'mlbench'\n%\n% > library(\"mlbench\")\n% > set.seed(1234)\n% > data <
![\"2d-10c\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-10c.png\" "\\"2d-10c\\"")
![\"2d-20c-no0\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-20c-no0.png\" "\\"2d-20c-no0\\"")
\n![\"2d-3c-no123\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-3c-no123.png\" "\\"2d-3c-no123\\"")
\n![\"2d-4c-no4\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-4c-no4.png\" "\\"2d-4c-no4\\"")
\n![\"2d-4c-no9\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-4c-no9.png\" "\\"2d-4c-no9\\"")
\n![\"2d-4c\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-4c.png\" "\\"2d-4c\\"")
\n![\"2sp2glob\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2sp2glob.png\" "\\"2sp2glob\\"")
\n![\"3-spiral\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/3-spiral.png\" "\\"3-spiral\\"")
\n![\"3MC\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/3mc.png\" "\\"3MC\\"")
\n![\"D31\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/d31.png\" "\\"D31\\"")
\n![\"DS577\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds577.png\" "\\"DS577\\"")
\n![\"DS850\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds850.png\" "\\"DS850\\"")
\n![\"R15\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/r15.png\" "\\"R15\\"")
\n![\"aggregation\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/aggregation.png\" "\\"aggregation\\"")
\n![\"atom\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/atom.png\" "\\"atom\\"")
\n![\"banana\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/banana.png\" "\\"banana\\"")
\n![\"birch-rg1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/birch-rg1.png\" "\\"birch-rg1\\"")
\n![\"birch-rg2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/birch-rg2.png\" "\\"birch-rg2\\"")
\n![\"birch-rg3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/birch-rg3.png\" "\\"birch-rg3\\"")
\n![\"chainlink\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/chainlink.png\" "\\"chainlink\\"")
\n![\"cluto-t4.8k\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t4.8k.png\" "\\"cluto-t4.8k\\"")
\n![\"cluto-t5.8k\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t5.8k.png\" "\\"cluto-t5.8k\\"")
\n![\"cluto-t7.10k\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t7.10k.png\" "\\"cluto-t7.10k\\"")
\n![\"cluto-t8.8k\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t8.8k.png\" "\\"cluto-t8.8k\\"")
\n![\"complex8\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/complex8.png\" "\\"complex8\\"")
\n![\"complex9\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/complex9.png\" "\\"complex9\\"")
\n![\"compound\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/compound.png\" "\\"compound\\"")
\n![\"cure-t0-2000n-2D\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cure-t0-2000n-2d.png\" "\\"cure-t0-2000n-2D\\"")
\n![\"cure-t1-2000n-2D\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cure-t1-2000n-2d.png\" "\\"cure-t1-2000n-2D\\"")
\n![\"cure-t2-4k\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cure-t2-4k.png\" "\\"cure-t2-4k\\"")
\n![\"curves1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/curves1.png\" "\\"curves1\\"")
\n![\"curves2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/curves2.png\" "\\"curves2\\"")
\n![\"dartboard1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/dartboard1.png\" "\\"dartboard1\\"")
\n![\"dartboard2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/dartboard2.png\" "\\"dartboard2\\"")
\n![\"dense-disk-3000\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/dense-disk-3000.png\" "\\"dense-disk-3000\\"")
\n![\"dense-disk-5000\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/dense-disk-5000.png\" "\\"dense-disk-5000\\"")
\n![\"diamond9\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/diamond9.png\" "\\"diamond9\\"")
\n![\"disk-1000n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-1000n.png\" "\\"disk-1000n\\"")
\n![\"disk-3000n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-3000n.png\" "\\"disk-3000n\\"")
\n![\"disk-4000n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-4000n.png\" "\\"disk-4000n\\"")
\n![\"disk-4500n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-4500n.png\" "\\"disk-4500n\\"")
\n![\"disk-4600n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-4600n.png\" "\\"disk-4600n\\"")
\n![\"disk-5000n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-5000n.png\" "\\"disk-5000n\\"")
\n![\"disk-6000n\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/disk-6000n.png\" "\\"disk-6000n\\"")
\n![\"donut1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/donut1.png\" "\\"donut1\\"")
\n![\"donut2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/donut2.png\" "\\"donut2\\"")
\n![\"donut3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/donut3.png\" "\\"donut3\\"")
\n![\"donutcurves\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/donutcurves.png\" "\\"donutcurves\\"")
\n![\"ds2c2sc13\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds2c2sc13.png\" "\\"ds2c2sc13\\"")
\n![\"ds3c3sc6\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds3c3sc6.png\" "\\"ds3c3sc6\\"")
\n![\"ds4c2sc8\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds4c2sc8.png\" "\\"ds4c2sc8\\"")
\n![\"elliptical_10_2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/elliptical_10_2.png\" "\\"elliptical_10_2\\"")
\n![\"elly-2d10c13s\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/elly-2d10c13s.png\" "\\"elly-2d10c13s\\"")
\n![\"engytime\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/engytime.png\" "\\"engytime\\"")
\n![\"flame\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/flame.png\" "\\"flame\\"")
\n![\"fourty\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/fourty.png\" "\\"fourty\\"")
\n![\"golfball\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/golfball.png\" "\\"golfball\\"")
\n![\"hepta\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/hepta.png\" "\\"hepta\\"")
\n![\"insect\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/insect.png\" "\\"insect\\"")
\n![\"jain\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/jain.png\" "\\"jain\\"")
\n![\"long1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/long1.png\" "\\"long1\\"")
\n![\"long2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/long2.png\" "\\"long2\\"")
\n![\"long3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/long3.png\" "\\"long3\\"")
\n![\"longsquare\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/longsquare.png\" "\\"longsquare\\"")
\n![\"lsun\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/lsun.png\" "\\"lsun\\"")
\n![\"mopsi-finland\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/mopsi-finland.png\" "\\"mopsi-finland\\"")
\n![\"mopsi-joensuu\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/mopsi-joensuu.png\" "\\"mopsi-joensuu\\"")
\n![\"pathbased\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/pathbased.png\" "\\"pathbased\\"")
\n![\"rings\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/rings.png\" "\\"rings\\"")
\n![\"s-set1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/s-set1.png\" "\\"s-set1\\"")
\n![\"s-set2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/s-set2.png\" "\\"s-set2\\"")
\n![\"s-set3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/s-set3.png\" "\\"s-set3\\"")
\n![\"s-set4\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/s-set4.png\" "\\"s-set4\\"")
\n![\"sizes1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/sizes1.png\" "\\"sizes1\\"")
\n![\"sizes2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/sizes2.png\" "\\"sizes2\\"")
\n![\"sizes3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/sizes3.png\" "\\"sizes3\\"")
\n![\"sizes4\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/sizes4.png\" "\\"sizes4\\"")
\n![\"sizes5\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/sizes5.png\" "\\"sizes5\\"")
\n![\"smile1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/smile1.png\" "\\"smile1\\"")
\n![\"smile2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/smile2.png\" "\\"smile2\\"")
\n![\"smile3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/smile3.png\" "\\"smile3\\"")
\n![\"spherical_4_3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/spherical_4_3.png\" "\\"spherical_4_3\\"")
\n![\"spherical_5_2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/spherical_5_2.png\" "\\"spherical_5_2\\"")
\n![\"spherical_6_2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/spherical_6_2.png\" "\\"spherical_6_2\\"")
\n![\"spiral\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/spiral.png\" "\\"spiral\\"")
\n![\"spiralsquare\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/spiralsquare.png\" "\\"spiralsquare\\"")
\n![\"square1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/square1.png\" "\\"square1\\"")
\n![\"square2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/square2.png\" "\\"square2\\"")
\n![\"square3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/square3.png\" "\\"square3\\"")
\n![\"square4\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/square4.png\" "\\"square4\\"")
\n![\"square5\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/square5.png\" "\\"square5\\"")
\n![\"st900\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/st900.png\" "\\"st900\\"")
\n![\"target\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/target.png\" "\\"target\\"")
\n![\"tetra\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/tetra.png\" "\\"tetra\\"")
\n![\"triangle1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/triangle1.png\" "\\"triangle1\\"")
\n![\"triangle2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/triangle2.png\" "\\"triangle2\\"")
\n![\"twenty\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/twenty.png\" "\\"twenty\\"")
\n![\"twodiamonds\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/twodiamonds.png\" "\\"twodiamonds\\"")
\n![\"wingnut\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/wingnut.png\" "\\"wingnut\\"")
\n![\"xclara\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/xclara.png\" "\\"xclara\\"")
\n![\"zelnik1\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik1.png\" "\\"zelnik1\\"")
\n![\"zelnik2\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik2.png\" "\\"zelnik2\\"")
\n![\"zelnik3\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik3.png\" "\\"zelnik3\\"")
\n![\"zelnik4\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik4.png\" "\\"zelnik4\\"")
\n![\"zelnik5\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik5.png\" "\\"zelnik5\\"")
\n![\"zelnik6\"](\"https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik6.png\" "\\"zelnik6\\"")
\n\n\n## Experiments\n\nThis project contains set of clustering methods benchmarks on various dataset. The project is dependent on [Clueminer project](https://github.com/deric/clueminer).\n\nin order to run benchmark compile dependencies into a single JAR file:\n\n mvn assembly:assembly\n\n# Consensus experiment\n\nallows running repeated runs of the same algorithm:\n\n```\n./run consensus --dataset \"triangle1\" --repeat 10\n```\nby default k-means algorithm is used.\n\nFor available datasets see [resources folder](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial).\n"
},
{
"path": "consensus",
"content": "#!/bin/bash\nmeth=(\"KmB-COMUSA-RAND\" \"KmB-COMUSA-MO\" \"KmB-COMUSA-RAND-fixed\")\nfor m in \"${meth[@]}\"; do\n ./run consensus --repeat 10 --method \"$m\" --dataset \"$@\"\ndone\n\n"
},
{
"path": "evolve-sc",
"content": "#!/bin/bash\nARGS=\"evolve-sc --test --generations 20 --population 50 $@\"\n`./run $ARGS`\n"
},
{
"path": "nb-configuration.xml",
"content": "\n