List of usage examples for org.apache.commons.math.stat.descriptive DescriptiveStatistics getMin
public double getMin()
From source file:datafu.hourglass.jobs.StagedOutputJob.java
/** * Writes Hadoop counters and other task statistics to a file in the file system. * //ww w . j a va 2 s . c om * @param fs * @throws IOException */ private void writeCounters(final FileSystem fs) throws IOException { final Path actualOutputPath = FileOutputFormat.getOutputPath(this); SimpleDateFormat timestampFormat = new SimpleDateFormat("yyyyMMddHHmmss"); String suffix = timestampFormat.format(new Date()); if (_countersParentPath != null) { if (!fs.exists(_countersParentPath)) { _log.info("Creating counter parent path " + _countersParentPath); fs.mkdirs(_countersParentPath, FsPermission.valueOf("-rwxrwxr-x")); } // make the name as unique as possible in this case because this may be a directory // where other counter files will be dropped _countersPath = new Path(_countersParentPath, ".counters." + suffix); } else { _countersPath = new Path(actualOutputPath, ".counters." + suffix); } _log.info(String.format("Writing counters to %s", _countersPath)); FSDataOutputStream counterStream = fs.create(_countersPath); BufferedOutputStream buffer = new BufferedOutputStream(counterStream, 256 * 1024); OutputStreamWriter writer = new OutputStreamWriter(buffer); for (String groupName : getCounters().getGroupNames()) { for (Counter counter : getCounters().getGroup(groupName)) { writeAndLog(writer, String.format("%s=%d", counter.getName(), counter.getValue())); } } JobID jobID = this.getJobID(); org.apache.hadoop.mapred.JobID oldJobId = new org.apache.hadoop.mapred.JobID(jobID.getJtIdentifier(), jobID.getId()); long minStart = Long.MAX_VALUE; long maxFinish = 0; long setupStart = Long.MAX_VALUE; long cleanupFinish = 0; DescriptiveStatistics mapStats = new DescriptiveStatistics(); DescriptiveStatistics reduceStats = new DescriptiveStatistics(); boolean success = true; JobClient jobClient = new JobClient(this.conf); Map<String, String> taskIdToType = new HashMap<String, String>(); TaskReport[] setupReports = jobClient.getSetupTaskReports(oldJobId); if (setupReports.length > 0) { _log.info("Processing setup reports"); for (TaskReport report : jobClient.getSetupTaskReports(oldJobId)) { taskIdToType.put(report.getTaskID().toString(), "SETUP"); if (report.getStartTime() == 0) { _log.warn("Skipping report with zero start time"); continue; } setupStart = Math.min(setupStart, report.getStartTime()); } } else { _log.error("No setup reports"); } TaskReport[] mapReports = jobClient.getMapTaskReports(oldJobId); if (mapReports.length > 0) { _log.info("Processing map reports"); for (TaskReport report : mapReports) { taskIdToType.put(report.getTaskID().toString(), "MAP"); if (report.getFinishTime() == 0 || report.getStartTime() == 0) { _log.warn("Skipping report with zero start or finish time"); continue; } minStart = Math.min(minStart, report.getStartTime()); mapStats.addValue(report.getFinishTime() - report.getStartTime()); } } else { _log.error("No map reports"); } TaskReport[] reduceReports = jobClient.getReduceTaskReports(oldJobId); if (reduceReports.length > 0) { _log.info("Processing reduce reports"); for (TaskReport report : reduceReports) { taskIdToType.put(report.getTaskID().toString(), "REDUCE"); if (report.getFinishTime() == 0 || report.getStartTime() == 0) { _log.warn("Skipping report with zero start or finish time"); continue; } maxFinish = Math.max(maxFinish, report.getFinishTime()); reduceStats.addValue(report.getFinishTime() - report.getStartTime()); } } else { _log.error("No reduce reports"); } TaskReport[] cleanupReports = jobClient.getCleanupTaskReports(oldJobId); if (cleanupReports.length > 0) { _log.info("Processing cleanup reports"); for (TaskReport report : cleanupReports) { taskIdToType.put(report.getTaskID().toString(), "CLEANUP"); if (report.getFinishTime() == 0) { _log.warn("Skipping report with finish time of zero"); continue; } cleanupFinish = Math.max(cleanupFinish, report.getFinishTime()); } } else { _log.error("No cleanup reports"); } if (minStart == Long.MAX_VALUE) { _log.error("Could not determine map-reduce start time"); success = false; } if (maxFinish == 0) { _log.error("Could not determine map-reduce finish time"); success = false; } if (setupStart == Long.MAX_VALUE) { _log.error("Could not determine setup start time"); success = false; } if (cleanupFinish == 0) { _log.error("Could not determine cleanup finish time"); success = false; } // Collect statistics on successful/failed/killed task attempts, categorized by setup/map/reduce/cleanup. // Unfortunately the job client doesn't have an easier way to get these statistics. Map<String, Integer> attemptStats = new HashMap<String, Integer>(); _log.info("Processing task attempts"); for (TaskCompletionEvent event : getTaskCompletionEvents(jobClient, oldJobId)) { String type = taskIdToType.get(event.getTaskAttemptId().getTaskID().toString()); String status = event.getTaskStatus().toString(); String key = String.format("%s_%s_ATTEMPTS", status, type); if (!attemptStats.containsKey(key)) { attemptStats.put(key, 0); } attemptStats.put(key, attemptStats.get(key) + 1); } if (success) { writeAndLog(writer, String.format("SETUP_START_TIME_MS=%d", setupStart)); writeAndLog(writer, String.format("CLEANUP_FINISH_TIME_MS=%d", cleanupFinish)); writeAndLog(writer, String.format("COMPLETE_WALL_CLOCK_TIME_MS=%d", cleanupFinish - setupStart)); writeAndLog(writer, String.format("MAP_REDUCE_START_TIME_MS=%d", minStart)); writeAndLog(writer, String.format("MAP_REDUCE_FINISH_TIME_MS=%d", maxFinish)); writeAndLog(writer, String.format("MAP_REDUCE_WALL_CLOCK_TIME_MS=%d", maxFinish - minStart)); writeAndLog(writer, String.format("MAP_TOTAL_TASKS=%d", (long) mapStats.getN())); writeAndLog(writer, String.format("MAP_MAX_TIME_MS=%d", (long) mapStats.getMax())); writeAndLog(writer, String.format("MAP_MIN_TIME_MS=%d", (long) mapStats.getMin())); writeAndLog(writer, String.format("MAP_AVG_TIME_MS=%d", (long) mapStats.getMean())); writeAndLog(writer, String.format("MAP_STD_TIME_MS=%d", (long) mapStats.getStandardDeviation())); writeAndLog(writer, String.format("MAP_SUM_TIME_MS=%d", (long) mapStats.getSum())); writeAndLog(writer, String.format("REDUCE_TOTAL_TASKS=%d", (long) reduceStats.getN())); writeAndLog(writer, String.format("REDUCE_MAX_TIME_MS=%d", (long) reduceStats.getMax())); writeAndLog(writer, String.format("REDUCE_MIN_TIME_MS=%d", (long) reduceStats.getMin())); writeAndLog(writer, String.format("REDUCE_AVG_TIME_MS=%d", (long) reduceStats.getMean())); writeAndLog(writer, String.format("REDUCE_STD_TIME_MS=%d", (long) reduceStats.getStandardDeviation())); writeAndLog(writer, String.format("REDUCE_SUM_TIME_MS=%d", (long) reduceStats.getSum())); writeAndLog(writer, String.format("MAP_REDUCE_SUM_TIME_MS=%d", (long) mapStats.getSum() + (long) reduceStats.getSum())); for (Map.Entry<String, Integer> attemptStat : attemptStats.entrySet()) { writeAndLog(writer, String.format("%s=%d", attemptStat.getKey(), attemptStat.getValue())); } } writer.close(); buffer.close(); counterStream.close(); }
From source file:de.tudarmstadt.ukp.experiments.argumentation.sequence.feature.coreference.CoreferenceFeatures.java
@Override protected List<Feature> extract(JCas jCas, Sentence sentence, String sentencePrefix) throws TextClassificationException { List<List<CoreferenceLink>> coreferenceChains = extractCoreferenceChains(jCas); FrequencyDistribution<String> featuresAcrossAllChains = new FrequencyDistribution<>(); DescriptiveStatistics chainLength = new DescriptiveStatistics(); DescriptiveStatistics distanceToPreviousSentence = new DescriptiveStatistics(); DescriptiveStatistics distanceToNextSentence = new DescriptiveStatistics(); DescriptiveStatistics interSentencesCorLinks = new DescriptiveStatistics(); for (List<CoreferenceLink> chain : coreferenceChains) { SortedMap<Integer, List<CoreferenceLink>> sentencesAndLinks = extractSentencesAndLinksFromChain(chain, jCas);/* w ww .ja v a 2 s .c o m*/ int currentSentencePos = getCurrentSentencePos(jCas, sentence); log.debug(sentencesAndLinks.keySet() + ", current " + currentSentencePos); // is the sentence in chain that spans more sentences? boolean partOfChain = sentencesAndLinks.containsKey(currentSentencePos) && sentencesAndLinks.size() > 1; // is part of a chain? if (partOfChain) { log.debug(chainToString(chain)); featuresAcrossAllChains.inc(FN_PART_OF_CHAIN); // starts the chain? if (sentencesAndLinks.firstKey().equals(currentSentencePos)) { featuresAcrossAllChains.inc(FN_STARTS_THE_CHAIN); } else if (sentencesAndLinks.lastKey().equals(currentSentencePos)) { // ends the chain? featuresAcrossAllChains.inc(FN_ENDS_THE_CHAIN); } else { // in the middle of chain? featuresAcrossAllChains.inc(FN_IN_THE_MIDDLE_OF_CHAIN); } // length of the chain chainLength.addValue(sentencesAndLinks.size()); List<CoreferenceLink> currentSentenceLinks = sentencesAndLinks.get(currentSentencePos); CoreferenceLink currentSentenceFirstLink = currentSentenceLinks.get(0); CoreferenceLink currentSentenceLastLink = currentSentenceLinks.get(currentSentenceLinks.size() - 1); // transition to the previous link, i.e. NOMINAL -> PRONOMINAL if (!sentencesAndLinks.firstKey().equals(currentSentencePos)) { // find the previous sentence List<CoreferenceLink> previousSentenceLinks = null; int prevSentNo = currentSentencePos; while (previousSentenceLinks == null && prevSentNo >= 0) { prevSentNo--; if (sentencesAndLinks.containsKey(prevSentNo)) { previousSentenceLinks = sentencesAndLinks.get(prevSentNo); } } if (previousSentenceLinks == null) { throw new IllegalStateException("Oops :))"); } // distance to previous sentence distanceToPreviousSentence.addValue(currentSentencePos - prevSentNo); // get the last link from the previous sentence CoreferenceLink prevSentenceLastLink = previousSentenceLinks .get(previousSentenceLinks.size() - 1); // add type type transition String prevSentenceLastLinkReferenceType = prevSentenceLastLink.getReferenceType(); String currentSentenceFirstLinkReferenceType = currentSentenceFirstLink.getReferenceType(); String transitionType = prevSentenceLastLinkReferenceType + GLUE + currentSentenceFirstLinkReferenceType; featuresAcrossAllChains.addSample(FN_TRANSITION_IN_TYPE_TYPE + transitionType, 1); // add token - type transition String glueCoreferenceCurrentSentence = glueCoreferenceLinkTokens(currentSentenceFirstLink); String typeToken = prevSentenceLastLinkReferenceType + GLUE + glueCoreferenceCurrentSentence; featuresAcrossAllChains.addSample(FN_TRANSITION_IN_TYPE_TOKEN + typeToken, 1); // add type - token transition String glueCoreferencePrevSentence = glueCoreferenceLinkTokens(prevSentenceLastLink); String tokenType = glueCoreferencePrevSentence + GLUE + currentSentenceFirstLinkReferenceType; featuresAcrossAllChains.addSample(FN_TRANSITION_IN_TOKEN_TYPE + tokenType, 1); // add token token transition String tokenToken = glueCoreferencePrevSentence + GLUE + glueCoreferenceCurrentSentence; featuresAcrossAllChains.addSample(FN_TRANSITION_IN_TOKEN_TOKEN + tokenToken, 1); // exact matching token-token reference? if (glueCoreferencePrevSentence.equals(glueCoreferenceCurrentSentence)) { featuresAcrossAllChains.addSample(FN_TRANSITION_IN_TOKEN_TOKEN_MATCH, 1); } } // transition to the previous link, i.e. NOMINAL -> PRONOMINAL if (!sentencesAndLinks.lastKey().equals(currentSentencePos)) { // find the previous sentence List<CoreferenceLink> nextSentenceLinks = null; int nextSentNo = currentSentencePos; while (nextSentenceLinks == null && nextSentNo <= sentencesAndLinks.lastKey()) { nextSentNo++; if (sentencesAndLinks.containsKey(nextSentNo)) { nextSentenceLinks = sentencesAndLinks.get(nextSentNo); } } if (nextSentenceLinks == null) { throw new IllegalStateException("Oops :))"); } // distance to next sentence distanceToNextSentence.addValue(nextSentNo - currentSentencePos); // get the last link from the previous sentence CoreferenceLink nextSentenceFirstLink = nextSentenceLinks.get(0); // add type type transition String currentSentenceLastLinkReferenceType = currentSentenceLastLink.getReferenceType(); String nextSentenceFirstLinkReferenceType = nextSentenceFirstLink.getReferenceType(); String transitionType = currentSentenceLastLinkReferenceType + GLUE + nextSentenceFirstLinkReferenceType; featuresAcrossAllChains.addSample(FN_TRANSITION_OUT_TYPE_TYPE + transitionType, 1); // add token - type transition String glueCoreferenceCurrentSent = glueCoreferenceLinkTokens(currentSentenceLastLink); String typeToken = glueCoreferenceCurrentSent + GLUE + nextSentenceFirstLinkReferenceType; featuresAcrossAllChains.addSample(FN_TRANSITION_OUT_TOKEN_TYPE + typeToken, 1); // add type - token transition String glueCoreferenceNextSent = glueCoreferenceLinkTokens(nextSentenceFirstLink); String tokenType = currentSentenceLastLinkReferenceType + GLUE + glueCoreferenceNextSent; featuresAcrossAllChains.addSample(FN_TRANSITION_OUT_TYPE_TOKEN + tokenType, 1); // add token token transition String tokenToken = glueCoreferenceCurrentSent + GLUE + glueCoreferenceNextSent; featuresAcrossAllChains.addSample(FN_TRANSITION_OUT_TOKEN_TOKEN + tokenToken, 1); // exact matching token-token reference? if (glueCoreferenceNextSent.equals(glueCoreferenceCurrentSent)) { featuresAcrossAllChains.addSample(FN_TRANSITION_OUT_TOKEN_TOKEN_MATCH, 1); } } } // number of inter-sentence coreference links if (sentencesAndLinks.containsKey(currentSentencePos)) { int coreferenceLinks = sentencesAndLinks.get(currentSentencePos).size(); interSentencesCorLinks.addValue(coreferenceLinks); } /* List<Integer> positions = positionsOfSentenceInCurrentChain(chain, sentence); // ok, we're in a chain if (!positions.isEmpty()) { log.debug(printChain(chain)); log.debug(sentence.getCoveredText()); log.debug(positions); Integer lastPosition = positions.get(positions.size() - 1); Integer firstPosition = positions.get(0); if (lastPosition == positions.size() - 1) { log.debug("Last sentence of chain"); } log.debug("-----"); } */ } List<Feature> result = new ArrayList<>(); log.debug(featuresAcrossAllChains); if (distanceToNextSentence.getN() > 0) { log.debug("Next:" + distanceToNextSentence); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_DIST_TO_NEXT_MIN, distanceToNextSentence.getMin())); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_DIST_TO_NEXT_MAX, distanceToNextSentence.getMax())); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_DIST_TO_NEXT_AVG, distanceToNextSentence.getMean())); } if (distanceToPreviousSentence.getN() > 0) { log.debug("Prev: " + distanceToPreviousSentence); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_DIST_TO_PREV_MIN, distanceToPreviousSentence.getMin())); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_DIST_TO_PREV_MAX, distanceToPreviousSentence.getMax())); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_DIST_TO_PREV_AVG, distanceToPreviousSentence.getMean())); } if (interSentencesCorLinks.getN() > 0) { result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_INTER_SENT_COR_MIN, interSentencesCorLinks.getMin())); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_INTER_SENT_COR_MAX, interSentencesCorLinks.getMax())); result.add(new Feature(sentencePrefix + FEATURE_NAME + FN_INTER_SENT_COR_AVG, interSentencesCorLinks.getMean())); } log.debug("----"); for (String feat : featuresAcrossAllChains.getKeys()) { // binary result.add(new Feature(sentencePrefix + FEATURE_NAME + feat, 1)); } return result; }
From source file:org.a3badran.platform.logging.writer.MetricsWriter.java
private Map<String, Long> getAllMetrics() { Map<String, Long> metrics = new HashMap<String, Long>(); for (Entry<String, DescriptiveStatistics> entry : sampleMetrics.entrySet()) { // create a copy to reduce locking String name = entry.getKey(); DescriptiveStatistics stats = entry.getValue().copy(); metrics.put(name + ".sampleCount", (long) stats.getN()); metrics.put(name + ".max", (long) stats.getMax()); metrics.put(name + ".min", (long) stats.getMin()); metrics.put(name + ".avg", (long) stats.getMean()); metrics.put(name + ".50p", (long) stats.getPercentile(50)); metrics.put(name + ".90p", (long) stats.getPercentile(90)); metrics.put(name + ".99p", (long) stats.getPercentile(99)); }/*w w w . j a v a 2 s . c om*/ for (Entry<String, DescriptiveStatistics> cEntry : sampleCounterMetrics.entrySet()) { // create a copy to reduce locking String cName = cEntry.getKey(); DescriptiveStatistics cStats = cEntry.getValue().copy(); metrics.put(cName + ".max", (long) cStats.getMax()); metrics.put(cName + ".min", (long) cStats.getMin()); metrics.put(cName + ".avg", (long) cStats.getMean()); metrics.put(cName + ".50p", (long) cStats.getPercentile(50)); metrics.put(cName + ".90p", (long) cStats.getPercentile(90)); metrics.put(cName + ".99p", (long) cStats.getPercentile(99)); } for (Entry<String, AtomicLong> entry : scopeTotalMetrics.entrySet()) { metrics.put(entry.getKey(), entry.getValue().longValue()); } for (Entry<String, AtomicLong> entry : appTotalMetrics.entrySet()) { metrics.put(entry.getKey(), entry.getValue().longValue()); } return metrics; }
From source file:org.apache.jackrabbit.oak.benchmark.AbstractTest.java
private void runTest(RepositoryFixture fixture, Repository repository, List<Integer> concurrencyLevels) throws Exception { setUp(repository, CREDENTIALS);// w w w . j a v a2s. c o m try { // Run a few iterations to warm up the system long warmupEnd = System.currentTimeMillis() + WARMUP; boolean stop = false; while (System.currentTimeMillis() < warmupEnd && !stop) { if (!stop) { // we want to execute this at lease once. after that we consider the // `haltRequested` flag. stop = haltRequested; } execute(); } if (concurrencyLevels == null || concurrencyLevels.isEmpty()) { concurrencyLevels = Arrays.asList(1); } for (Integer concurrency : concurrencyLevels) { // Run the test DescriptiveStatistics statistics = runTest(concurrency); if (statistics.getN() > 0) { System.out.format("%-28.28s %6d %6.0f %6.0f %6.0f %6.0f %6.0f %6d%n", fixture.toString(), concurrency, statistics.getMin(), statistics.getPercentile(10.0), statistics.getPercentile(50.0), statistics.getPercentile(90.0), statistics.getMax(), statistics.getN()); if (out != null) { out.format("%-28.28s, %6d, %6.0f, %6.0f, %6.0f, %6.0f, %6.0f, %6d%n", fixture.toString(), concurrency, statistics.getMin(), statistics.getPercentile(10.0), statistics.getPercentile(50.0), statistics.getPercentile(90.0), statistics.getMax(), statistics.getN()); } } } } finally { tearDown(); } }
From source file:org.apache.jackrabbit.performance.AbstractPerformanceTest.java
private void writeReport(String test, String name, DescriptiveStatistics statistics) throws IOException { File report = new File("target", test + ".txt"); boolean needsPrefix = !report.exists(); PrintWriter writer = new PrintWriter(new FileWriterWithEncoding(report, "UTF-8", true)); try {/*w ww.ja va 2 s.c o m*/ if (needsPrefix) { writer.format("# %-34.34s min 10%% 50%% 90%% max%n", test); } writer.format("%-36.36s %6.0f %6.0f %6.0f %6.0f %6.0f%n", name, statistics.getMin(), statistics.getPercentile(10.0), statistics.getPercentile(50.0), statistics.getPercentile(90.0), statistics.getMax()); } finally { writer.close(); } }
From source file:org.fusesource.eca.processor.StatisticsCalculator.java
protected void process(StatisticsType type, Number value, ObjectNode statsNode) throws Exception { EventCache<Number> cache = this.eventCache; if (value != null && cache != null) { cache.add(value);/* w w w .j av a2s .c o m*/ if (type.equals(StatisticsType.RATE)) { calculateRate(statsNode); } else { List<Number> list = this.eventCache.getWindow(); DescriptiveStatistics descriptiveStatistics = new DescriptiveStatistics(); if (list != null && !list.isEmpty()) { for (Number number : list) { descriptiveStatistics.addValue(number.doubleValue()); } switch (type) { case MEAN: statsNode.put("mean", descriptiveStatistics.getMean()); break; case GEOMETRIC_MEAN: statsNode.put("gemetric mean", descriptiveStatistics.getGeometricMean()); break; case STDDEV: statsNode.put("std-dev", descriptiveStatistics.getStandardDeviation()); break; case MIN: statsNode.put("minimum", descriptiveStatistics.getMin()); break; case MAX: statsNode.put("maximum", descriptiveStatistics.getMax()); break; case SKEWNESS: statsNode.put("skewness", descriptiveStatistics.getSkewness()); break; case KUTOSIS: statsNode.put("kurtosis", descriptiveStatistics.getKurtosis()); break; case VARIANCE: statsNode.put("variance", descriptiveStatistics.getVariance()); break; case COUNT: statsNode.put("count", list.size()); default: statsNode.put("number", descriptiveStatistics.getN()); statsNode.put("mean", descriptiveStatistics.getMean()); statsNode.put("gemetric mean", descriptiveStatistics.getGeometricMean()); statsNode.put("minimum", descriptiveStatistics.getMin()); statsNode.put("maximum", descriptiveStatistics.getMax()); statsNode.put("std-dev", descriptiveStatistics.getStandardDeviation()); statsNode.put("median", descriptiveStatistics.getPercentile(50)); statsNode.put("skewness", descriptiveStatistics.getSkewness()); statsNode.put("kurtosis", descriptiveStatistics.getKurtosis()); statsNode.put("variance", descriptiveStatistics.getVariance()); calculateRate(statsNode); statsNode.put("count", list.size()); } } } } }
From source file:org.matsim.contrib.common.stats.StatsWriter.java
/** * Writes a table with columns map-key and statistical indicators mean, median, min, max and number of samples. Rows * are sorted according to the natural order of the map keys. * * @param statsMap a map with {@code DescriptiveStatistics} objects * @param keyLabel the header for the first column (containing the map keys) * @param file the filename//w w w .j ava 2 s .c o m * @throws IOException */ public static void writeStatistics(TDoubleObjectHashMap<DescriptiveStatistics> statsMap, String keyLabel, String file) throws IOException { double[] keys = statsMap.keys(); Arrays.sort(keys); BufferedWriter writer = new BufferedWriter(new FileWriter(file)); writer.write(keyLabel); writer.write(TAB); writer.write("mean"); writer.write(TAB); writer.write("median"); writer.write(TAB); writer.write("min"); writer.write(TAB); writer.write("max"); writer.write(TAB); writer.write("n"); writer.newLine(); for (double key : keys) { DescriptiveStatistics stats = statsMap.get(key); writer.write(String.valueOf(key)); writer.write(TAB); writer.write(String.valueOf(stats.getMean())); writer.write(TAB); writer.write(String.valueOf(stats.getPercentile(50))); writer.write(TAB); writer.write(String.valueOf(stats.getMin())); writer.write(TAB); writer.write(String.valueOf(stats.getMax())); writer.write(TAB); writer.write(String.valueOf(stats.getN())); writer.newLine(); } writer.close(); }
From source file:org.matsim.contrib.socnetgen.sna.graph.analysis.AnalyzerTask.java
protected void printStats(DescriptiveStatistics stats, String key) { logger.info(String.format(//from w ww .j av a 2s . c o m "Statistics for property %1$s:\n\tmean = %2$.4f, min = %3$.4f, max = %4$.4f, N = %5$s, Var = %6$.4f", key, stats.getMean(), stats.getMin(), stats.getMax(), stats.getN(), stats.getVariance())); }
From source file:org.matsim.contrib.socnetgen.sna.graph.analysis.DegreeTest.java
public void test() { SparseGraphBuilder builder = new SparseGraphBuilder(); SparseGraph graph = builder.createGraph(); SparseVertex v1 = builder.addVertex(graph); SparseVertex v2 = builder.addVertex(graph); SparseVertex v3 = builder.addVertex(graph); SparseVertex v4 = builder.addVertex(graph); SparseVertex v5 = builder.addVertex(graph); SparseVertex v6 = builder.addVertex(graph); builder.addEdge(graph, v1, v2);/*from w w w . j a v a2 s . c o m*/ builder.addEdge(graph, v2, v3); builder.addEdge(graph, v3, v4); builder.addEdge(graph, v4, v5); builder.addEdge(graph, v5, v6); builder.addEdge(graph, v6, v1); builder.addEdge(graph, v2, v5); Degree degree = Degree.getInstance(); DescriptiveStatistics stats = degree.statistics(graph.getVertices()); assertEquals(2.33, stats.getMean(), 0.01); assertEquals(2.0, stats.getMin()); assertEquals(3.0, stats.getMax()); TObjectDoubleHashMap<? extends Vertex> values = degree.values(graph.getVertices()); TObjectDoubleIterator<? extends Vertex> it = values.iterator(); int count2 = 0; int count3 = 0; for (int i = 0; i < values.size(); i++) { it.advance(); if (it.value() == 2) count2++; else if (it.value() == 3) count3++; } assertEquals(4, count2); assertEquals(2, count3); assertEquals(-0.166, degree.assortativity(graph), 0.001); }
From source file:org.matsim.contrib.socnetgen.sna.graph.analysis.TransitivityTest.java
@SuppressWarnings("unchecked") public void test() { SparseGraphBuilder builder = new SparseGraphBuilder(); SparseGraph graph = builder.createGraph(); SparseVertex v1 = builder.addVertex(graph); SparseVertex v2 = builder.addVertex(graph); SparseVertex v3 = builder.addVertex(graph); SparseVertex v4 = builder.addVertex(graph); builder.addEdge(graph, v1, v2);/*from w w w . j a va 2 s . co m*/ builder.addEdge(graph, v1, v4); builder.addEdge(graph, v1, v3); builder.addEdge(graph, v2, v4); Transitivity degree = Transitivity.getInstance(); DescriptiveStatistics distr = degree.localClusteringDistribution(graph.getVertices()); assertEquals(7 / 12.0, distr.getMean(), 0.01); assertEquals(0.0, distr.getMin()); assertEquals(1.0, distr.getMax()); TObjectDoubleHashMap<Vertex> values = (TObjectDoubleHashMap<Vertex>) degree .localClusteringCoefficients((Set<? extends Vertex>) graph.getVertices()); assertEquals(1 / 3.0, values.get(v1)); assertEquals(1.0, values.get(v2)); assertEquals(1.0, values.get(v4)); assertEquals(0.0, values.get(v3)); assertEquals(3 / 5.0, degree.globalClusteringCoefficient(graph)); }