本文整理汇总了Java中org.apache.commons.math.stat.descriptive.SummaryStatistics.addValue方法的典型用法代码示例。如果您正苦于以下问题：Java SummaryStatistics.addValue方法的具体用法？Java SummaryStatistics.addValue怎么用？Java SummaryStatistics.addValue使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.commons.math.stat.descriptive.SummaryStatistics的用法示例。
在下文中一共展示了SummaryStatistics.addValue方法的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: getClassToObject
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
private SummaryStatistics getClassToObject() {
SummaryStatistics summary = new SummaryStatistics();
HashSet<String> classNameSet = new HashSet<String>();
for (GraphMetricItem gmi : listOfObjects.values()) {
// HACK: displayTypeName is not uniquely identified
// HACK: using gmi.declaredTypeName is a workaround, but some
// declared types are imprecise. See Hashtable<K, List<V>> in PX
classNameSet.add(gmi.declaredTypeName);
}
// System.out.println("classes that have more than one representative in the object graph");
for (String className : classNameSet) {
long count = 0;
for (GraphMetricItem gmj : listOfObjects.values()) {
if (gmj.declaredTypeName.equals(className)){
count++;
// if (count>1)
// System.out.println(gmj.declaredTypeName);
}
}
summary.addValue(count);
}
return summary;
}
示例2: computeStatistics
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
public static SummaryStatistics computeStatistics(UnexpectednessScorer scorer) {
int numNodes = scorer.graph.numNodes();
SummaryStatistics stats = new SummaryStatistics();
ProgressLogger pl = new ProgressLogger(LOGGER, "docs");
pl.expectedUpdates = numNodes;
pl.start("Finding statistics for values of " + scorer + "...");
for (int i = 0; i < numNodes; i++) {
for (double x : scorer.scores(i).values()) {
stats.addValue(x);
if (Double.isInfinite(x) || Double.isNaN(x))
throw new ArithmeticException(
"Scorer " + scorer + " has returned value "
+ x + " for a result of document " + i);
}
pl.lightUpdate();
}
pl.done();
return stats;
}
示例3: analyseImage
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
@Override
public void analyseImage(FImage image) {
final FImage limg = image.process(laplacian);
final FImage aimg = image.process(average);
final SummaryStatistics stats = new SummaryStatistics();
for (int r = 0; r < limg.height; r++) {
for (int c = 0; c < limg.width; c++) {
if (mask != null && mask.pixels[r][c] == 0)
continue;
if (aimg.pixels[r][c] != 0) {
stats.addValue(Math.abs(limg.pixels[r][c] / aimg.pixels[r][c]));
}
}
}
sharpnessVariation = stats.getStandardDeviation();
}
示例4: testTwoSampleTHomoscedastic
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
public void testTwoSampleTHomoscedastic() throws Exception {
double[] sample1 ={2, 4, 6, 8, 10, 97};
double[] sample2 = {4, 6, 8, 10, 16};
SummaryStatistics sampleStats1 = new SummaryStatistics();
for (int i = 0; i < sample1.length; i++) {
sampleStats1.addValue(sample1[i]);
}
SummaryStatistics sampleStats2 = new SummaryStatistics();
for (int i = 0; i < sample2.length; i++) {
sampleStats2.addValue(sample2[i]);
}
// Target comparison values computed using R version 1.8.1 (Linux version)
assertEquals("two sample homoscedastic t stat", 0.73096310086,
TestUtils.homoscedasticT(sample1, sample2), 10E-11);
assertEquals("two sample homoscedastic p value", 0.4833963785,
TestUtils.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10);
assertTrue("two sample homoscedastic t-test reject",
TestUtils.homoscedasticTTest(sample1, sample2, 0.49));
assertTrue("two sample homoscedastic t-test accept",
!TestUtils.homoscedasticTTest(sample1, sample2, 0.48));
}
示例5: testTwoSampleTHomoscedastic
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
public void testTwoSampleTHomoscedastic() throws Exception {
double[] sample1 ={2, 4, 6, 8, 10, 97};
double[] sample2 = {4, 6, 8, 10, 16};
SummaryStatistics sampleStats1 = new SummaryStatistics();
for (int i = 0; i < sample1.length; i++) {
sampleStats1.addValue(sample1[i]);
}
SummaryStatistics sampleStats2 = new SummaryStatistics();
for (int i = 0; i < sample2.length; i++) {
sampleStats2.addValue(sample2[i]);
}
// Target comparison values computed using R version 1.8.1 (Linux version)
assertEquals("two sample homoscedastic t stat", 0.73096310086,
testStatistic.homoscedasticT(sample1, sample2), 10E-11);
assertEquals("two sample homoscedastic p value", 0.4833963785,
testStatistic.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10);
assertTrue("two sample homoscedastic t-test reject",
testStatistic.homoscedasticTTest(sample1, sample2, 0.49));
assertTrue("two sample homoscedastic t-test accept",
!testStatistic.homoscedasticTTest(sample1, sample2, 0.48));
}
示例6: testNextGaussian
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
/** test failure modes and distribution of nextGaussian() */
public void testNextGaussian() {
try {
randomData.nextGaussian(0,0);
fail("zero sigma -- IllegalArgumentException expected");
} catch (IllegalArgumentException ex) {
;
}
SummaryStatistics u = new SummaryStatistics();
for (int i = 0; i<largeSampleSize; i++) {
u.addValue(randomData.nextGaussian(0,1));
}
double xbar = u.getMean();
double s = u.getStandardDeviation();
double n = (double) u.getN();
/* t-test at .001-level TODO: replace with externalized t-test, with
* test statistic defined in TestStatistic
*/
assertTrue(Math.abs(xbar)/(s/Math.sqrt(n))< 3.29);
}
示例7: testTwoSampleTHomoscedastic
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
public void testTwoSampleTHomoscedastic() throws Exception {
double[] sample1 ={2, 4, 6, 8, 10, 97};
double[] sample2 = {4, 6, 8, 10, 16};
SummaryStatistics sampleStats1 = new SummaryStatistics();
for (int i = 0; i < sample1.length; i++) {
sampleStats1.addValue(sample1[i]);
}
SummaryStatistics sampleStats2 = new SummaryStatistics();
for (int i = 0; i < sample2.length; i++) {
sampleStats2.addValue(sample2[i]);
}
// Target comparison values computed using R version 1.8.1 (Linux version)
assertEquals("two sample homoscedastic t stat", 0.73096310086,
testStatistic.homoscedasticT(sample1, sample2), 10E-11);
assertEquals("two sample homoscedastic p value", 0.4833963785,
testStatistic.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10);
assertTrue("two sample homoscedastic t-test reject",
testStatistic.homoscedasticTTest(sample1, sample2, 0.49));
assertTrue("two sample homoscedastic t-test accept",
!testStatistic.homoscedasticTTest(sample1, sample2, 0.48));
}
示例8: testTwoSampleTHomoscedastic
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
public void testTwoSampleTHomoscedastic() throws Exception {
double[] sample1 ={2, 4, 6, 8, 10, 97};
double[] sample2 = {4, 6, 8, 10, 16};
SummaryStatistics sampleStats1 = new SummaryStatistics();
for (int i = 0; i < sample1.length; i++) {
sampleStats1.addValue(sample1[i]);
}
SummaryStatistics sampleStats2 = new SummaryStatistics();
for (int i = 0; i < sample2.length; i++) {
sampleStats2.addValue(sample2[i]);
}
// Target comparison values computed using R version 1.8.1 (Linux version)
assertEquals("two sample homoscedastic t stat", 0.73096310086,
TestUtils.homoscedasticT(sample1, sample2), 10E-11);
assertEquals("two sample homoscedastic p value", 0.4833963785,
TestUtils.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10);
assertTrue("two sample homoscedastic t-test reject",
TestUtils.homoscedasticTTest(sample1, sample2, 0.49));
assertTrue("two sample homoscedastic t-test accept",
!TestUtils.homoscedasticTTest(sample1, sample2, 0.48));
}
示例9: testNextGaussian
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
/** test failure modes and distribution of nextGaussian() */
public void testNextGaussian() {
try {
randomData.nextGaussian(0, 0);
fail("zero sigma -- IllegalArgumentException expected");
} catch (IllegalArgumentException ex) {
// ignored
}
SummaryStatistics u = new SummaryStatistics();
for (int i = 0; i < largeSampleSize; i++) {
u.addValue(randomData.nextGaussian(0, 1));
}
double xbar = u.getMean();
double s = u.getStandardDeviation();
double n = u.getN();
/*
* t-test at .001-level TODO: replace with externalized t-test, with
* test statistic defined in TestStatistic
*/
assertTrue(Math.abs(xbar) / (s / Math.sqrt(n)) < 3.29);
}
示例10: calculate
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
@Override
public boolean calculate() {
if (System.currentTimeMillis() > nextRecord) {
ValueStat v = new ValueStat();
v.setKey(key);
if (workingValues.isEmpty()) {
v.setValue(0.0);
} else {
SummaryStatistics summary = new SummaryStatistics();
synchronized (workingValues) {
for (ValueStat vs : workingValues) {
summary.addValue(vs.getValue());
}
}
switch (operation) {
case AVERAGE:
v.setValue(summary.getMean());
break;
case SUM:
v.setValue(summary.getSum());
break;
}
}
history.add(v);
nextRecord = nextExtractionTime();
return true;
}
return false;
}
示例11: getTCO
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
private SummaryStatistics getTCO() {
SummaryStatistics summary = new SummaryStatistics();
for (GraphMetricItem gmi : listOfObjects.values()) {
summary.addValue(gmi.noTrLinks);
}
return summary;
}
示例12: getScattering
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
private SummaryStatistics getScattering() {
SummaryStatistics summary = new SummaryStatistics();
for (GraphMetricItem gmi : listOfObjects.values()) {
summary.addValue(gmi.objectScattering);
}
return summary;
}
示例13: getNoObjectsInDomains
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
private SummaryStatistics getNoObjectsInDomains() {
SummaryStatistics summary = new SummaryStatistics();
for (GraphMetricItem gmi : listOfDomains.values()) {
summary.addValue(gmi.getOutOwnDegree());
}
return summary;
}
示例14: getPublicDInObjects
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
private SummaryStatistics getPublicDInObjects() {
SummaryStatistics summary = new SummaryStatistics();
for (GraphMetricItem mi : listOfObjects.values()) {
if (mi.getType() != NodeType.ORoot)
summary.addValue(mi.noPublicDomains);
}
return summary;
}
示例15: getPrivateDInObjects
import org.apache.commons.math.stat.descriptive.SummaryStatistics; //导入方法依赖的package包/类
private SummaryStatistics getPrivateDInObjects() {
SummaryStatistics summary = new SummaryStatistics();
for (GraphMetricItem mi : listOfObjects.values()) {
if (mi.getType() != NodeType.ORoot)
summary.addValue(mi.noPrivateDomains);
}
return summary;
}