StatisticalSummary.java
- /*
- * 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
- *
- * https://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.
- */
- /*
- * This is not the original file distributed by the Apache Software Foundation
- * It has been modified by the Hipparchus project
- */
- package org.hipparchus.stat.descriptive;
- import java.util.Arrays;
- import org.hipparchus.util.MathUtils;
- /**
- * Reporting interface for basic univariate statistics.
- */
- public interface StatisticalSummary {
- /**
- * Computes aggregated statistical summaries.
- * <p>
- * This method can be used to combine statistics computed over partitions or
- * subsamples - i.e., the returned StatisticalSummary should contain
- * the same values that would have been obtained by computing a single
- * StatisticalSummary over the combined dataset.
- *
- * @param statistics StatisticalSummary instances to aggregate
- * @return summary statistics for the combined dataset
- * @throws org.hipparchus.exception.NullArgumentException if the input is null
- */
- static StatisticalSummary aggregate(StatisticalSummary... statistics) {
- MathUtils.checkNotNull(statistics);
- return aggregate(Arrays.asList(statistics));
- }
- /**
- * Computes aggregated statistical summaries.
- * <p>
- * This method can be used to combine statistics computed over partitions or
- * subsamples - i.e., the returned StatisticalSummary should contain
- * the same values that would have been obtained by computing a single
- * StatisticalSummary over the combined dataset.
- *
- * @param statistics iterable of StatisticalSummary instances to aggregate
- * @return summary statistics for the combined dataset
- * @throws org.hipparchus.exception.NullArgumentException if the input is null
- */
- static StatisticalSummary aggregate(Iterable<? extends StatisticalSummary> statistics) {
- MathUtils.checkNotNull(statistics);
- long n = 0;
- double min = Double.NaN;
- double max = Double.NaN;
- double sum = Double.NaN;
- double mean = Double.NaN;
- double m2 = Double.NaN;
- for (StatisticalSummary current : statistics) {
- if (current.getN() == 0) {
- continue;
- }
- if (n == 0) {
- n = current.getN();
- min = current.getMin();
- sum = current.getSum();
- max = current.getMax();
- m2 = current.getVariance() * (n - 1);
- mean = current.getMean();
- } else {
- if (current.getMin() < min) {
- min = current.getMin();
- }
- if (current.getMax() > max) {
- max = current.getMax();
- }
- sum += current.getSum();
- final double oldN = n;
- final double curN = current.getN();
- n += curN;
- final double meanDiff = current.getMean() - mean;
- mean = sum / n;
- final double curM2 = current.getVariance() * (curN - 1d);
- m2 = m2 + curM2 + meanDiff * meanDiff * oldN * curN / n;
- }
- }
- final double variance = n == 0 ? Double.NaN :
- n == 1 ? 0d :
- m2 / (n - 1);
- return new StatisticalSummaryValues(mean, variance, n, max, min, sum);
- }
- /**
- * Returns the <a href="http://www.xycoon.com/arithmetic_mean.htm">
- * arithmetic mean </a> of the available values
- * @return The mean or Double.NaN if no values have been added.
- */
- double getMean();
- /**
- * Returns the variance of the available values.
- * @return The variance, Double.NaN if no values have been added
- * or 0.0 for a single value set.
- */
- double getVariance();
- /**
- * Returns the standard deviation of the available values.
- * @return The standard deviation, Double.NaN if no values have been added
- * or 0.0 for a single value set.
- */
- double getStandardDeviation();
- /**
- * Returns the maximum of the available values
- * @return The max or Double.NaN if no values have been added.
- */
- double getMax();
- /**
- * Returns the minimum of the available values
- * @return The min or Double.NaN if no values have been added.
- */
- double getMin();
- /**
- * Returns the number of available values
- * @return The number of available values
- */
- long getN();
- /**
- * Returns the sum of the values that have been added to Univariate.
- * @return The sum or Double.NaN if no values have been added
- */
- double getSum();
- }