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Jenetics - Java Genetic Algorithm Library
/*
* Java Genetic Algorithm Library (jenetics-3.1.0).
* Copyright (c) 2007-2015 Franz Wilhelmstötter
*
* Licensed 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.
*
* Author:
* Franz Wilhelmstötter ([email protected])
*/
package org.jenetics.stat;
import static java.util.Objects.requireNonNull;
import static org.jenetics.internal.util.Equality.eq;
import java.io.Serializable;
import java.util.function.ToDoubleFunction;
import java.util.stream.Collector;
import org.jenetics.internal.util.Equality;
import org.jenetics.internal.util.Hash;
/**
* Value objects which contains statistical moments.
*
* @see org.jenetics.stat.DoubleMomentStatistics
*
* @author Franz Wilhelmstötter
* @since 3.0
* @version 3.0
*/
public final class DoubleMoments implements Serializable {
private static final long serialVersionUID = 1L;
private final long _count;
private final double _min;
private final double _max;
private final double _sum;
private final double _mean;
private final double _variance;
private final double _skewness;
private final double _kurtosis;
/**
* Create an immutable object which contains statistical values.
*
* @param count the count of values recorded
* @param min the minimum value
* @param max the maximum value
* @param sum the sum of the recorded values
* @param mean the arithmetic mean of values
* @param variance the variance of values
* @param skewness the skewness of values
* @param kurtosis the kurtosis of values
*/
private DoubleMoments(
final long count,
final double min,
final double max,
final double sum,
final double mean,
final double variance,
final double skewness,
final double kurtosis
) {
_count = count;
_min = min;
_max = max;
_sum = sum;
_mean = mean;
_variance = variance;
_skewness = skewness;
_kurtosis = kurtosis;
}
/**
* Returns the count of values recorded.
*
* @return the count of recorded values
*/
public long getCount() {
return _count;
}
/**
* Return the minimum value recorded, or {@code Integer.MAX_VALUE} if no
* values have been recorded.
*
* @return the minimum value, or {@code Integer.MAX_VALUE} if none
*/
public double getMin() {
return _min;
}
/**
* Return the maximum value recorded, or {@code Integer.MIN_VALUE} if no
* values have been recorded.
*
* @return the maximum value, or {@code Integer.MIN_VALUE} if none
*/
public double getMax() {
return _max;
}
/**
* Return the sum of values recorded, or zero if no values have been
* recorded.
*
* @return the sum of values, or zero if none
*/
public double getSum() {
return _sum;
}
/**
* Return the arithmetic mean of values recorded, or zero if no values have
* been recorded.
*
* @return the arithmetic mean of values, or zero if none
*/
public double getMean() {
return _mean;
}
/**
* Return the variance of values recorded, or {@code Double.NaN} if no
* values have been recorded.
*
* @return the variance of values, or {@code NaN} if none
*/
public double getVariance() {
return _variance;
}
/**
* Return the skewness of values recorded, or {@code Double.NaN} if less
* than two values have been recorded.
*
* @see Skewness
*
* @return the skewness of values, or {@code NaN} if less than two values
* have been recorded
*/
public double getSkewness() {
return _skewness;
}
/**
* Return the kurtosis of values recorded, or {@code Double.NaN} if less
* than four values have been recorded.
*
* @see Kurtosis
*
* @return the kurtosis of values, or {@code NaN} if less than four values
* have been recorded
*/
public double getKurtosis() {
return _kurtosis;
}
@Override
public int hashCode() {
return Hash.of(DoubleMoments.class)
.and(_count)
.and(_sum)
.and(_min)
.and(_max)
.and(_mean)
.and(_variance)
.and(_skewness)
.and(_kurtosis).value();
}
@Override
public boolean equals(final Object obj) {
return Equality.of(this, obj).test(moments ->
eq(_count, moments._count) &&
eq(_sum, moments._sum) &&
eq(_min, moments._min) &&
eq(_max, moments._max) &&
eq(_mean, moments._mean) &&
eq(_variance, moments._variance) &&
eq(_skewness, moments._skewness) &&
eq(_kurtosis, moments._kurtosis)
);
}
@Override
public String toString() {
return String.format(
"IntMoments[N=%d, ∧=%s, ∨=%s, Σ=%s, μ=%s, s²=%s, S=%s, K=%s]",
getCount(), getMin(), getMax(), getSum(),
getMean(), getVariance(), getSkewness(), getKurtosis()
);
}
/**
* Create an immutable object which contains statistical values.
*
* @param count the count of values recorded
* @param min the minimum value
* @param max the maximum value
* @param sum the sum of the recorded values
* @param mean the arithmetic mean of values
* @param variance the variance of values
* @param skewness the skewness of values
* @param kurtosis the kurtosis of values
* @return an immutable object which contains statistical values
*/
public static DoubleMoments of(
final long count,
final double min,
final double max,
final double sum,
final double mean,
final double variance,
final double skewness,
final double kurtosis
) {
return new DoubleMoments(
count,
min,
max,
sum,
mean,
variance,
skewness,
kurtosis
);
}
/**
* Return a new value object of the statistical moments, currently
* represented by the {@code statistics} object.
*
* @param statistics the creating (mutable) statistics class
* @return the statistical moments
*/
public static DoubleMoments of(final DoubleMomentStatistics statistics) {
return new DoubleMoments(
statistics.getCount(),
statistics.getMin(),
statistics.getMax(),
statistics.getSum(),
statistics.getMean(),
statistics.getVariance(),
statistics.getSkewness(),
statistics.getKurtosis()
);
}
/**
* Return a {@code Collector} which applies an double-producing mapping
* function to each input element, and returns moments-statistics for the
* resulting values.
*
* {@code
* final Stream stream = ...
* final DoubleMoments moments = stream
* .collect(toDoubleMoments(v -> v.doubleValue()));
* }
*
* @param mapper a mapping function to apply to each element
* @param the type of the input elements
* @return a {@code Collector} implementing the moments-statistics reduction
* @throws java.lang.NullPointerException if the given {@code mapper} is
* {@code null}
*/
public static Collector
toDoubleMoments(final ToDoubleFunction super T> mapper) {
requireNonNull(mapper);
return Collector.of(
DoubleMomentStatistics::new,
(a, b) -> a.accept(mapper.applyAsDouble(b)),
DoubleMomentStatistics::combine,
DoubleMoments::of
);
}
}
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