replace string concatenation with StringBuffer.append calls.

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@635150 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Brent Worden 2008-03-09 03:30:30 +00:00
parent 7d28e0f53d
commit 80416d808e
2 changed files with 226 additions and 225 deletions

View File

@ -411,15 +411,17 @@ public class DescriptiveStatistics implements StatisticalSummary, Serializable {
*/
public String toString() {
StringBuffer outBuffer = new StringBuffer();
outBuffer.append("DescriptiveStatistics:\n");
outBuffer.append("n: " + getN() + "\n");
outBuffer.append("min: " + getMin() + "\n");
outBuffer.append("max: " + getMax() + "\n");
outBuffer.append("mean: " + getMean() + "\n");
outBuffer.append("std dev: " + getStandardDeviation() + "\n");
outBuffer.append("median: " + getPercentile(50) + "\n");
outBuffer.append("skewness: " + getSkewness() + "\n");
outBuffer.append("kurtosis: " + getKurtosis() + "\n");
String endl = "\n";
outBuffer.append("DescriptiveStatistics:").append(endl);
outBuffer.append("n: ").append(getN()).append(endl);
outBuffer.append("min: ").append(getMin()).append(endl);
outBuffer.append("max: ").append(getMax()).append(endl);
outBuffer.append("mean: ").append(getMean()).append(endl);
outBuffer.append("std dev: ").append(getStandardDeviation())
.append(endl);
outBuffer.append("median: ").append(getPercentile(50)).append(endl);
outBuffer.append("skewness: ").append(getSkewness()).append(endl);
outBuffer.append("kurtosis: ").append(getKurtosis()).append(endl);
return outBuffer.toString();
}

View File

@ -1,18 +1,15 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* contributor license agreements. See the NOTICE file distributed with this
* work for additional information regarding copyright ownership. The ASF
* licenses this file to You under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
* http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law
* or agreed to in writing, software distributed under the License is
* distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the specific language
* governing permissions and limitations under the License.
*/
package org.apache.commons.math.stat.descriptive;
@ -31,79 +28,77 @@ import org.apache.commons.math.stat.descriptive.summary.SumOfSquares;
import org.apache.commons.math.util.MathUtils;
/**
* <p>Computes summary statistics for a stream of data values added using the
* <p>
* Computes summary statistics for a stream of data values added using the
* {@link #addValue(double) addValue} method. The data values are not stored in
* memory, so this class can be used to compute statistics for very large
* data streams.</p>
*
* <p>The {@link StorelessUnivariateStatistic} instances used to maintain
* summary state and compute statistics are configurable via setters.
* For example, the default implementation for the variance can be overridden by
* calling {@link #setVarianceImpl(StorelessUnivariateStatistic)}. Actual
* parameters to these methods must implement the
* {@link StorelessUnivariateStatistic} interface and configuration must be
* completed before <code>addValue</code> is called. No configuration is
* necessary to use the default, commons-math provided implementations.</p>
*
* <p>Note: This class is not thread-safe. Use
* memory, so this class can be used to compute statistics for very large data
* streams.
* </p>
* <p>
* The {@link StorelessUnivariateStatistic} instances used to maintain summary
* state and compute statistics are configurable via setters. For example, the
* default implementation for the variance can be overridden by calling
* {@link #setVarianceImpl(StorelessUnivariateStatistic)}. Actual parameters to
* these methods must implement the {@link StorelessUnivariateStatistic}
* interface and configuration must be completed before <code>addValue</code>
* is called. No configuration is necessary to use the default, commons-math
* provided implementations.
* </p>
* <p>
* Note: This class is not thread-safe. Use
* {@link SynchronizedSummaryStatistics} if concurrent access from multiple
* threads is required.</p>
*
* @version $Revision$ $Date$
* threads is required.
* </p>
* @version $Revision$ $Date: 2008-02-10 13:28:59 -0600 (Sun, 10 Feb
* 2008) $
*/
public class SummaryStatistics implements StatisticalSummary, Serializable {
/** Serialization UID */
private static final long serialVersionUID = -3346512372447011854L;
/**
* Create an instance of a <code>SummaryStatistics</code>
*
* @param cls the type of <code>SummaryStatistics</code> object to
* create.
* @return a new instance.
* @param cls the type of <code>SummaryStatistics</code> object to create.
* @return a new instance.
* @deprecated to be removed in commons-math 2.0
* @throws InstantiationException is thrown if the object can not be
* created.
* created.
* @throws IllegalAccessException is thrown if the type's default
* constructor is not accessible.
* constructor is not accessible.
*/
public static SummaryStatistics newInstance(Class cls) throws
InstantiationException, IllegalAccessException {
public static SummaryStatistics newInstance(Class cls) throws InstantiationException, IllegalAccessException {
return (SummaryStatistics)cls.newInstance();
}
/**
* Create an instance of a <code>SummaryStatistics</code>
*
* @return a new SummaryStatistics instance.
* @deprecated to be removed in commons-math 2.0
* @deprecated to be removed in commons-math 2.0
*/
public static SummaryStatistics newInstance() {
SummaryStatistics instance = null;
try {
DiscoverClass dc = new DiscoverClass();
instance = (SummaryStatistics) dc.newInstance(
SummaryStatistics.class,
"org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl");
} catch(Throwable t) {
instance = (SummaryStatistics)dc.newInstance(SummaryStatistics.class, "org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl");
} catch (Throwable t) {
return new SummaryStatisticsImpl();
}
return instance;
}
/**
* Construct a SummaryStatistics instance
*/
public SummaryStatistics() {
}
/** count of values that have been added */
protected long n = 0;
/** SecondMoment is used to compute the mean and variance */
protected SecondMoment secondMoment = new SecondMoment();
/** sum of values that have been added */
protected Sum sum = new Sum();
@ -127,46 +122,43 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/** variance of values that have been added */
protected Variance variance = new Variance();
/** Sum statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic sumImpl = sum;
/** Sum of squares statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic sumsqImpl = sumsq;
/** Minimum statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic minImpl = min;
/** Maximum statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic maxImpl = max;
/** Sum of log statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic sumLogImpl = sumLog;
/** Geometric mean statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic geoMeanImpl = geoMean;
/** Mean statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic meanImpl = mean;
/** Variance statistic implementation - can be reset by setter. */
private StorelessUnivariateStatistic varianceImpl = variance;
/**
* Return a {@link StatisticalSummaryValues} instance reporting current
* statistics.
*
* @return Current values of statistics
* @return Current values of statistics
*/
public StatisticalSummary getSummary() {
return new StatisticalSummaryValues(getMean(), getVariance(), getN(),
getMax(), getMin(), getSum());
return new StatisticalSummaryValues(getMean(), getVariance(), getN(), getMax(), getMin(), getSum());
}
/**
* Add a value to the data
*
* @param value the value to add
* @param value the value to add
*/
public void addValue(double value) {
sumImpl.increment(value);
@ -178,7 +170,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
// If mean, variance or geomean have been overridden,
// need to increment these
if (!(meanImpl instanceof Mean)) {
meanImpl.increment(value);
meanImpl.increment(value);
}
if (!(varianceImpl instanceof Variance)) {
varianceImpl.increment(value);
@ -189,7 +181,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
n++;
}
/**
/**
* Returns the number of available values
* @return The number of available values
*/
@ -208,8 +200,8 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the sum of the squares of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* Double.NaN is returned if no values have been added.
* </p>
* @return The sum of squares
*/
public double getSumsq() {
@ -219,23 +211,23 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the mean of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* Double.NaN is returned if no values have been added.
* </p>
* @return the mean
*/
public double getMean() {
if (mean == meanImpl) {
return new Mean(secondMoment).getResult();
} else {
return meanImpl.getResult();
}
if (mean == meanImpl) {
return new Mean(secondMoment).getResult();
} else {
return meanImpl.getResult();
}
}
/**
* Returns the standard deviation of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* Double.NaN is returned if no values have been added.
* </p>
* @return the standard deviation
*/
public double getStandardDeviation() {
@ -253,9 +245,9 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the variance of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* @return the variance
* Double.NaN is returned if no values have been added.
* </p>
* @return the variance
*/
public double getVariance() {
if (varianceImpl == variance) {
@ -268,9 +260,9 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the maximum of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* @return the maximum
* Double.NaN is returned if no values have been added.
* </p>
* @return the maximum
*/
public double getMax() {
return maxImpl.getResult();
@ -279,9 +271,9 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the minimum of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* @return the minimum
* Double.NaN is returned if no values have been added.
* </p>
* @return the minimum
*/
public double getMin() {
return minImpl.getResult();
@ -290,49 +282,51 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the geometric mean of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* @return the geometric mean
* Double.NaN is returned if no values have been added.
* </p>
* @return the geometric mean
*/
public double getGeometricMean() {
return geoMeanImpl.getResult();
}
/**
* Returns the sum of the logs of the values that have been added.
* <p>
* Double.NaN is returned if no values have been added.</p>
*
* Double.NaN is returned if no values have been added.
* </p>
* @return the sum of logs
* @since 1.2
*/
public double getSumOfLogs() {
return sumLogImpl.getResult();
}
/**
* Generates a text report displaying
* summary statistics from values that
* Generates a text report displaying summary statistics from values that
* have been added.
* @return String with line feeds displaying statistics
* @since 1.2
*/
public String toString() {
StringBuffer outBuffer = new StringBuffer();
outBuffer.append("SummaryStatistics:\n");
outBuffer.append("n: " + getN() + "\n");
outBuffer.append("min: " + getMin() + "\n");
outBuffer.append("max: " + getMax() + "\n");
outBuffer.append("mean: " + getMean() + "\n");
outBuffer.append("geometric mean: " + getGeometricMean() + "\n");
outBuffer.append("variance: " + getVariance() + "\n");
outBuffer.append("sum of squares: " + getSumsq() + "\n");
outBuffer.append("standard deviation: " + getStandardDeviation() + "\n");
outBuffer.append("sum of logs: " + getSumOfLogs() + "\n");
String endl = "\n";
outBuffer.append("SummaryStatistics:").append(endl);
outBuffer.append("n: ").append(getN()).append(endl);
outBuffer.append("min: ").append(getMin()).append(endl);
outBuffer.append("max: ").append(getMax()).append(endl);
outBuffer.append("mean: ").append(getMean()).append(endl);
outBuffer.append("geometric mean: ").append(getGeometricMean())
.append(endl);
outBuffer.append("variance: ").append(getVariance()).append(endl);
outBuffer.append("sum of squares: ").append(getSumsq()).append(endl);
outBuffer.append("standard deviation: ").append(getStandardDeviation())
.append(endl);
outBuffer.append("sum of logs: ").append(getSumOfLogs()).append(endl);
return outBuffer.toString();
}
/**
/**
* Resets all statistics and storage
*/
public void clear() {
@ -351,35 +345,30 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
varianceImpl.clear();
}
}
/**
* Returns true iff <code>object</code> is a <code>SummaryStatistics</code>
* instance and all statistics have the same values as this.
* Returns true iff <code>object</code> is a
* <code>SummaryStatistics</code> instance and all statistics have the
* same values as this.
* @param object the object to test equality against.
* @return true if object equals this
*/
public boolean equals(Object object) {
if (object == this ) {
if (object == this) {
return true;
}
if (object instanceof SummaryStatistics == false) {
return false;
}
SummaryStatistics stat = (SummaryStatistics) object;
return (MathUtils.equals(stat.getGeometricMean(),
this.getGeometricMean()) &&
MathUtils.equals(stat.getMax(), this.getMax()) &&
MathUtils.equals(stat.getMean(),this.getMean()) &&
MathUtils.equals(stat.getMin(),this.getMin()) &&
MathUtils.equals(stat.getN(), this.getN()) &&
MathUtils.equals(stat.getSum(), this.getSum()) &&
MathUtils.equals(stat.getSumsq(),this.getSumsq()) &&
MathUtils.equals(stat.getVariance(),this.getVariance()));
SummaryStatistics stat = (SummaryStatistics)object;
return (MathUtils.equals(stat.getGeometricMean(), this.getGeometricMean()) && MathUtils.equals(stat.getMax(), this.getMax())
&& MathUtils.equals(stat.getMean(), this.getMean()) && MathUtils.equals(stat.getMin(), this.getMin()) && MathUtils.equals(stat.getN(), this.getN())
&& MathUtils.equals(stat.getSum(), this.getSum()) && MathUtils.equals(stat.getSumsq(), this.getSumsq()) && MathUtils.equals(stat.getVariance(),
this.getVariance()));
}
/**
* Returns hash code based on values of statistics
*
* @return hash code
*/
public int hashCode() {
@ -398,7 +387,6 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
// Getters and setters for statistics implementations
/**
* Returns the currently configured Sum implementation
*
* @return the StorelessUnivariateStatistic implementing the sum
* @since 1.2
*/
@ -407,15 +395,18 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the Sum.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param sumImpl the StorelessUnivariateStatistic instance to use
* for computing the Sum
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the Sum.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param sumImpl the StorelessUnivariateStatistic instance to use for
* computing the Sum
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setSumImpl(StorelessUnivariateStatistic sumImpl) {
@ -425,7 +416,6 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the currently configured sum of squares implementation
*
* @return the StorelessUnivariateStatistic implementing the sum of squares
* @since 1.2
*/
@ -434,26 +424,27 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the sum of squares.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param sumsqImpl the StorelessUnivariateStatistic instance to use
* for computing the sum of squares
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the sum of squares.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param sumsqImpl the StorelessUnivariateStatistic instance to use for
* computing the sum of squares
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setSumsqImpl(
StorelessUnivariateStatistic sumsqImpl) {
public void setSumsqImpl(StorelessUnivariateStatistic sumsqImpl) {
checkEmpty();
this.sumsqImpl = sumsqImpl;
}
/**
* Returns the currently configured minimum implementation
*
* @return the StorelessUnivariateStatistic implementing the minimum
* @since 1.2
*/
@ -462,15 +453,18 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the minimum.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param minImpl the StorelessUnivariateStatistic instance to use
* for computing the minimum
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the minimum.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param minImpl the StorelessUnivariateStatistic instance to use for
* computing the minimum
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setMinImpl(StorelessUnivariateStatistic minImpl) {
@ -480,7 +474,6 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the currently configured maximum implementation
*
* @return the StorelessUnivariateStatistic implementing the maximum
* @since 1.2
*/
@ -489,15 +482,18 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the maximum.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param maxImpl the StorelessUnivariateStatistic instance to use
* for computing the maximum
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the maximum.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param maxImpl the StorelessUnivariateStatistic instance to use for
* computing the maximum
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setMaxImpl(StorelessUnivariateStatistic maxImpl) {
@ -507,7 +503,6 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the currently configured sum of logs implementation
*
* @return the StorelessUnivariateStatistic implementing the log sum
* @since 1.2
*/
@ -516,19 +511,21 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the sum of logs.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param sumLogImpl the StorelessUnivariateStatistic instance to use
* for computing the log sum
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the sum of logs.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param sumLogImpl the StorelessUnivariateStatistic instance to use for
* computing the log sum
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setSumLogImpl(
StorelessUnivariateStatistic sumLogImpl) {
public void setSumLogImpl(StorelessUnivariateStatistic sumLogImpl) {
checkEmpty();
this.sumLogImpl = sumLogImpl;
geoMean.setSumLogImpl(sumLogImpl);
@ -536,7 +533,6 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
/**
* Returns the currently configured geometric mean implementation
*
* @return the StorelessUnivariateStatistic implementing the geometric mean
* @since 1.2
*/
@ -545,26 +541,27 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the geometric mean.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param geoMeanImpl the StorelessUnivariateStatistic instance to use
* for computing the geometric mean
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the geometric mean.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param geoMeanImpl the StorelessUnivariateStatistic instance to use for
* computing the geometric mean
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setGeoMeanImpl(
StorelessUnivariateStatistic geoMeanImpl) {
public void setGeoMeanImpl(StorelessUnivariateStatistic geoMeanImpl) {
checkEmpty();
this.geoMeanImpl = geoMeanImpl;
}
/**
* Returns the currently configured mean implementation
*
* @return the StorelessUnivariateStatistic implementing the mean
* @since 1.2
*/
@ -573,26 +570,27 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the mean.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param meanImpl the StorelessUnivariateStatistic instance to use
* for computing the mean
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the mean.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param meanImpl the StorelessUnivariateStatistic instance to use for
* computing the mean
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setMeanImpl(
StorelessUnivariateStatistic meanImpl) {
public void setMeanImpl(StorelessUnivariateStatistic meanImpl) {
checkEmpty();
this.meanImpl = meanImpl;
}
/**
* Returns the currently configured variance implementation
*
* @return the StorelessUnivariateStatistic implementing the variance
* @since 1.2
*/
@ -601,30 +599,31 @@ public class SummaryStatistics implements StatisticalSummary, Serializable {
}
/**
* <p>Sets the implementation for the variance.</p>
* <p>This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.</p>
*
* @param varianceImpl the StorelessUnivariateStatistic instance to use
* for computing the variance
* @throws IllegalStateException if data has already been added
* (i.e if n > 0)
* <p>
* Sets the implementation for the variance.
* </p>
* <p>
* This method must be activated before any data has been added - i.e.,
* before {@link #addValue(double) addValue} has been used to add data;
* otherwise an IllegalStateException will be thrown.
* </p>
* @param varianceImpl the StorelessUnivariateStatistic instance to use for
* computing the variance
* @throws IllegalStateException if data has already been added (i.e if n >
* 0)
* @since 1.2
*/
public void setVarianceImpl(
StorelessUnivariateStatistic varianceImpl) {
public void setVarianceImpl(StorelessUnivariateStatistic varianceImpl) {
checkEmpty();
this.varianceImpl = varianceImpl;
}
/**
* Throws IllegalStateException if n > 0.
*/
private void checkEmpty() {
if (n > 0) {
throw new IllegalStateException(
"Implementations must be configured before values are added.");
throw new IllegalStateException("Implementations must be configured before values are added.");
}
}