| /* |
| * 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.math.stat.descriptive.moment; |
| |
| import java.io.Serializable; |
| import java.util.Arrays; |
| |
| import org.apache.commons.math.DimensionMismatchException; |
| import org.apache.commons.math.linear.MatrixUtils; |
| import org.apache.commons.math.linear.RealMatrix; |
| |
| /** |
| * Returns the covariance matrix of the available vectors. |
| * @since 1.2 |
| * @version $Revision: 922714 $ $Date: 2010-03-14 02:35:14 +0100 (dim. 14 mars 2010) $ |
| */ |
| public class VectorialCovariance implements Serializable { |
| |
| /** Serializable version identifier */ |
| private static final long serialVersionUID = 4118372414238930270L; |
| |
| /** Sums for each component. */ |
| private final double[] sums; |
| |
| /** Sums of products for each component. */ |
| private final double[] productsSums; |
| |
| /** Indicator for bias correction. */ |
| private final boolean isBiasCorrected; |
| |
| /** Number of vectors in the sample. */ |
| private long n; |
| |
| /** Constructs a VectorialCovariance. |
| * @param dimension vectors dimension |
| * @param isBiasCorrected if true, computed the unbiased sample covariance, |
| * otherwise computes the biased population covariance |
| */ |
| public VectorialCovariance(int dimension, boolean isBiasCorrected) { |
| sums = new double[dimension]; |
| productsSums = new double[dimension * (dimension + 1) / 2]; |
| n = 0; |
| this.isBiasCorrected = isBiasCorrected; |
| } |
| |
| /** |
| * Add a new vector to the sample. |
| * @param v vector to add |
| * @exception DimensionMismatchException if the vector does not have the right dimension |
| */ |
| public void increment(double[] v) throws DimensionMismatchException { |
| if (v.length != sums.length) { |
| throw new DimensionMismatchException(v.length, sums.length); |
| } |
| int k = 0; |
| for (int i = 0; i < v.length; ++i) { |
| sums[i] += v[i]; |
| for (int j = 0; j <= i; ++j) { |
| productsSums[k++] += v[i] * v[j]; |
| } |
| } |
| n++; |
| } |
| |
| /** |
| * Get the covariance matrix. |
| * @return covariance matrix |
| */ |
| public RealMatrix getResult() { |
| |
| int dimension = sums.length; |
| RealMatrix result = MatrixUtils.createRealMatrix(dimension, dimension); |
| |
| if (n > 1) { |
| double c = 1.0 / (n * (isBiasCorrected ? (n - 1) : n)); |
| int k = 0; |
| for (int i = 0; i < dimension; ++i) { |
| for (int j = 0; j <= i; ++j) { |
| double e = c * (n * productsSums[k++] - sums[i] * sums[j]); |
| result.setEntry(i, j, e); |
| result.setEntry(j, i, e); |
| } |
| } |
| } |
| |
| return result; |
| |
| } |
| |
| /** |
| * Get the number of vectors in the sample. |
| * @return number of vectors in the sample |
| */ |
| public long getN() { |
| return n; |
| } |
| |
| /** |
| * Clears the internal state of the Statistic |
| */ |
| public void clear() { |
| n = 0; |
| Arrays.fill(sums, 0.0); |
| Arrays.fill(productsSums, 0.0); |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public int hashCode() { |
| final int prime = 31; |
| int result = 1; |
| result = prime * result + (isBiasCorrected ? 1231 : 1237); |
| result = prime * result + (int) (n ^ (n >>> 32)); |
| result = prime * result + Arrays.hashCode(productsSums); |
| result = prime * result + Arrays.hashCode(sums); |
| return result; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public boolean equals(Object obj) { |
| if (this == obj) |
| return true; |
| if (!(obj instanceof VectorialCovariance)) |
| return false; |
| VectorialCovariance other = (VectorialCovariance) obj; |
| if (isBiasCorrected != other.isBiasCorrected) |
| return false; |
| if (n != other.n) |
| return false; |
| if (!Arrays.equals(productsSums, other.productsSums)) |
| return false; |
| if (!Arrays.equals(sums, other.sums)) |
| return false; |
| return true; |
| } |
| |
| } |