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/*
* 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.
*/
package org.apache.commons.math4.legacy.distribution;
import org.apache.commons.math4.legacy.exception.NotStrictlyPositiveException;
import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
import org.apache.commons.rng.UniformRandomProvider;
/**
* Base class for multivariate probability distributions.
*
* @since 3.1
*/
public abstract class AbstractMultivariateRealDistribution
implements MultivariateRealDistribution {
/** The number of dimensions or columns in the multivariate distribution. */
private final int dimension;
/**
* @param n Number of dimensions.
*/
protected AbstractMultivariateRealDistribution(int n) {
dimension = n;
}
/** {@inheritDoc} */
@Override
public int getDimension() {
return dimension;
}
/** {@inheritDoc} */
@Override
public abstract Sampler createSampler(UniformRandomProvider rng);
/**
* Utility function for creating {@code n} vectors generated by the
* given {@code sampler}.
*
* @param n Number of samples.
* @param sampler Sampler.
* @return an array of size {@code n} whose elements are random vectors
* sampled from this distribution.
*/
public static double[][] sample(int n,
MultivariateRealDistribution.Sampler sampler) {
if (n <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
n);
}
final double[][] samples = new double[n][];
for (int i = 0; i < n; i++) {
samples[i] = sampler.sample();
}
return samples;
}
}