本文整理汇总了Java中org.apache.commons.math3.stat.descriptive.DescriptiveStatistics类的典型用法代码示例。如果您正苦于以下问题:Java DescriptiveStatistics类的具体用法?Java DescriptiveStatistics怎么用?Java DescriptiveStatistics使用的例子?那么, 这里精选的类代码示例或许可以为您提供帮助。
DescriptiveStatistics类属于org.apache.commons.math3.stat.descriptive包,在下文中一共展示了DescriptiveStatistics类的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testStatisticalTests
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
/**
*Generates random double array, applies t-test to it
* @throws Exception
*/
@Test
public void testStatisticalTests() throws Exception {
double[] x = new double[1000];
for (int i = 0; i < x.length; i++) {
x[i] = Math.random()*100+1;
}
System.out.println("Testing array: " + Arrays.toString(x));
//One-sample t-test
double mu = new DescriptiveStatistics(x).getMean();
System.out.println("Mean: " + mu);
System.out.println("t-statistic for true mean (50): " + TestUtils.t(50, x));
System.out.println("p-value for true mean (50): " + TestUtils.tTest(50,x));
System.out.println("t-statistic for false mean (75): " + TestUtils.t(75,x));
System.out.println("p-value for false mean (75): " + TestUtils.tTest(75,x));
}
示例2: phi
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
/**
* Compute phi for the specified node id.
* @param nodeId node id
* @return phi value
*/
public double phi(NodeId nodeId) {
checkNotNull(nodeId, "NodeId must not be null");
if (!states.containsKey(nodeId)) {
return bootstrapPhiValue;
}
History nodeState = states.get(nodeId);
synchronized (nodeState) {
long latestHeartbeat = nodeState.latestHeartbeatTime();
DescriptiveStatistics samples = nodeState.samples();
if (latestHeartbeat == -1 || samples.getN() < minSamples) {
return 0.0;
}
return computePhi(samples, latestHeartbeat, System.currentTimeMillis());
}
}
示例3: convertDescriptiveStatisticsMap
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
public static Map<String, List<DescriptiveStatistics>> convertDescriptiveStatisticsMap(
Map<TopicPartition, DescriptiveStatistics> tpsMap) {
Map<String, List<DescriptiveStatistics>> result = new TreeMap<>();
for (Map.Entry<TopicPartition, DescriptiveStatistics> entry : tpsMap.entrySet()) {
String topicName = entry.getKey().topic();
int partitionId = entry.getKey().partition();
if (!result.containsKey(topicName)) {
result.put(topicName, new ArrayList<>());
}
List<DescriptiveStatistics> partitionArray = result.get(topicName);
while (partitionArray.size() < partitionId + 1) {
partitionArray.add(null);
}
partitionArray.set(partitionId, entry.getValue());
}
return result;
}
示例4: getValue
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
public Map<String, HashMap<String, Double>> getValue() {
while (true) {
try {
Map<String, HashMap<String, Double>> ret = new HashMap<>();
for (Map.Entry<LatencySourceDescriptor, DescriptiveStatistics> source : latencyStats.entrySet()) {
HashMap<String, Double> sourceStatistics = new HashMap<>(6);
sourceStatistics.put("max", source.getValue().getMax());
sourceStatistics.put("mean", source.getValue().getMean());
sourceStatistics.put("min", source.getValue().getMin());
sourceStatistics.put("p50", source.getValue().getPercentile(50));
sourceStatistics.put("p95", source.getValue().getPercentile(95));
sourceStatistics.put("p99", source.getValue().getPercentile(99));
ret.put(source.getKey().toString(), sourceStatistics);
}
return ret;
// Concurrent access onto the "latencyStats" map could cause
// ConcurrentModificationExceptions. To avoid unnecessary blocking
// of the reportLatency() method, we retry this operation until
// it succeeds.
} catch (ConcurrentModificationException ignore) {
LOG.debug("Unable to report latency statistics", ignore);
}
}
}
示例5: setUp
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Before
public void setUp()
{
results.clear();
Arrays.stream(Metric.values()).forEach(m -> results.put(m, new DescriptiveStatistics(new Random().doubles(10, 0, 100).toArray())));
Random random = new Random();
when(evaluationMock.precision(anyInt())).thenReturn(random.nextDouble());
when(evaluationMock.recall(anyInt())).thenReturn(random.nextDouble());
when(evaluationMock.areaUnderPRC(anyInt())).thenReturn(random.nextDouble());
when(evaluationMock.areaUnderROC(anyInt())).thenReturn(random.nextDouble());
when(methodEvaluationMock.getEvaluation()).thenReturn(evaluationMock);
when(methodEvaluationMock.getTrainStart()).thenReturn(System.currentTimeMillis() - 1000);
when(methodEvaluationMock.getTrainEnd()).thenReturn(System.currentTimeMillis() - 750);
when(methodEvaluationMock.getTestStart()).thenReturn(System.currentTimeMillis() - 500);
when(methodEvaluationMock.getTestEnd()).thenReturn(System.currentTimeMillis() - 250);
}
示例6: getChart
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
public final PairList<String, Map<Number, Number>> getChart(final CharSequence label) {
final Map<Number, DescriptiveStatistics> points = new HashMap<>();
for (int i = 0; i < arrays[0].length; ++i) {
final double key = arrays[1][i];
if (!points.containsKey(key)) {
points.put(key, new DescriptiveStatistics());
}
points.get(key).addValue(arrays[0][i]);
}
final Map<Number, Number> average = new HashMap<>();
final Map<Number, Number> median = new HashMap<>();
for (final Entry<Number, DescriptiveStatistics> entry : points.entrySet()) {
average.put(entry.getKey(), entry.getValue().getMean());
median.put(entry.getKey(), entry.getValue().getPercentile(50));
}
final PairList<String, Map<Number, Number>> list = new PairList<>();
list.add("Average " + label, average);
list.add("Median " + label, median);
return list;
}
示例7: acrossLabels
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
public final DescriptiveStatistics acrossLabels(
final List<? extends Predictions<? extends E[], ? extends Collection<? extends P>>>[] predictions) {
final DescriptiveStatistics stats = new DescriptiveStatistics();
for (final List<? extends Predictions<? extends E[], ? extends Collection<? extends P>>> predz : Check
.size(predictions, 1, 9999999)) {
for (final Predictions<? extends E[], ? extends Collection<? extends P>> preds : predz) {
for (final double val : label(preds.getPredictions(),
(E[][]) preds.getExpected(),
preds.getWeights(),
preds.getSamples(),
preds.getLabelIndex()).getValues()) {
stats.addValue(val);
}
}
}
Check.num(stats.getN(), 1, 999999999);
return stats;
}
示例8: label
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
public DescriptiveStatistics label(final Serializable[] preds, final Object[] expected, final double[] weights,
final ISamples<?, ?> samples, final int labelIndex) {
int count = 0;
int correct = 0;
for (int i = 0; i < preds.length; ++i) {
final double[] predAndAct = toDouble(preds[i], expected[i]);
if (predAndAct[0] >= thresholdTrue) {
++count;
if (predAndAct[1] >= thresholdTrue) {
++correct;
}
}
}
return new DescriptiveStatistics(new double[] { correct == 0 ? 0 : correct * 1.0 / count });
}
示例9: acrossLabels
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
public DescriptiveStatistics acrossLabels(
final List<? extends Predictions<? extends Number, ? extends Number>>[] predictions) {
final DescriptiveStatistics stats = new DescriptiveStatistics();
for (final List<? extends Predictions<? extends Number, ? extends Number>> predz : predictions) {
for (final Predictions<? extends Number, ? extends Number> preds : predz) {
final Number[] pred = preds.getPredictions();
final Number[] exp = preds.getExpected();
final int labelIndex = preds.getLabelIndex();
for (int i = 0; i < pred.length; ++i) {
if (exp[i] != null) {
stats.addValue(instance(pred[i], exp[i], preds.getSample(i), labelIndex));
}
}
}
}
return stats;
}
示例10: acrossLabels
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
public final DescriptiveStatistics acrossLabels(
final List<? extends Predictions<? extends E, ? extends T>>[] predictions) {
final DescriptiveStatistics stats = new DescriptiveStatistics();
for (final List<? extends Predictions<? extends E, ? extends T>> predz : predictions) {
for (final Predictions<? extends E, ? extends T> preds : predz) {
for (final double val : label(preds.getPredictions(),
preds.getExpected(),
preds.getWeights(),
preds.getSamples(),
preds.getLabelIndex()).getValues()) {
stats.addValue(val);
}
}
}
return stats;
}
示例11: compute
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
protected void compute() {
final Split best = findBestSplit();
// TODO: Do crossval here to reject split, if necessary
if (best == null || best.getImprovement() < 0.00000000001) {
return;
}
final DescriptiveStatistics[] nodeStats = nodeStats(best);
final IStats statsNaN = best.getStatsNaN();
final TreeNode[] children = new TreeNode[statsNaN.getN() >= context.minObs ? 3 : 2];
children[0] = new TreeNode(prediction(nodeStats[0]), best.getStatsL());
children[1] = new TreeNode(prediction(nodeStats[1]), best.getStatsR());
if (children.length == 3) {
children[2] = new TreeNode(prediction(nodeStats[2]), statsNaN);
}
final boolean[][] split = parent.split(best, children, context.orderedInstances, subset);
if (depth < context.maxDepth) {
for (int i = 0; i < children.length; ++i) {
if (split[i].length >= context.minObs * 2) {
new GrowJob(children[i], context, split[i], depth + 1, nodePrediction, splitCriterionFactory,
statisticsFactory, parallelize).compute();
}
}
}
}
示例12: isSignificant
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
public boolean isSignificant(double singletonKL[],double p){
DescriptiveStatistics ds=new DescriptiveStatistics((double[])singletonKL);
double mean=ds.getMean();
double std=ds.getStandardDeviation();
double z=(Math.log(contextShiftingScore)-mean)/std;
//double pValue1;
// Compute z value of the scores based on the null distribution of scores of kmers computed from aptamers with small counts
if (z>0.0)
pvalue = computePValue(z);
else
pvalue=1.0;
if (pvalue<=p)
return true;
else
return false;
}
示例13: statistics
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
public ReflexValue statistics(List<ReflexValue> params) {
if (params.size() != 1) {
throw new ReflexException(-1, "statistics needs one list parameter");
}
if (!params.get(0).isList()) {
throw new ReflexException(-1, "statistics needs one list parameter");
}
DescriptiveStatistics stats = new DescriptiveStatistics();
List<ReflexValue> values = params.get(0).asList();
for (ReflexValue v : values) {
stats.addValue(v.asDouble());
}
Map<String, ReflexValue> ret = new HashMap<String, ReflexValue>();
ret.put("mean", new ReflexValue(stats.getMean()));
ret.put("std", new ReflexValue(stats.getStandardDeviation()));
ret.put("median", new ReflexValue(stats.getPercentile(50)));
return new ReflexValue(ret);
}
示例14: statBasedSelectMetricHistory
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
/**
* filter snapshots using statistically significant points only
* @param selectedLists list of snapshots
*/
private void statBasedSelectMetricHistory(final LinkedList<InMemoryHistoryNode> selectedLists)
throws ClassCastException {
logger.debug("selecting snapshots which are far away from mean value");
DescriptiveStatistics descStats = getDescriptiveStatistics(selectedLists);
Double mean = descStats.getMean();
Double std = descStats.getStandardDeviation();
Iterator<InMemoryHistoryNode> ite = selectedLists.iterator();
while (ite.hasNext()) {
InMemoryHistoryNode currentNode = ite.next();
double value = ((Number) currentNode.getValue()).doubleValue();
// remove all elements which lies in 95% value band
if (value < mean + standardDeviationFactor * std && value > mean - standardDeviationFactor * std) {
ite.remove();
}
}
}
示例15: process
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; //导入依赖的package包/类
@Override
public Data process(Data item) {
int[][] singlePulses = (int[][]) item.get(singlePulsesKey);
double[] arrivalTimes = new double[singlePulses.length];
for (int pix = 0; pix < singlePulses.length; pix++) {
if (singlePulses[pix].length == 0) {
arrivalTimes[pix] = 0.; // use zero instead of NaN - plotter likes no NaN
} else {
DescriptiveStatistics stat = new DescriptiveStatistics();
for (int slice : singlePulses[pix]) {
stat.addValue((double) slice);
}
arrivalTimes[pix] = stat.getPercentile(50);
}
}
item.put(arrivalTimeKey, arrivalTimes);
return item;
}