Java tutorial
/** * Copyright 2014 Brigham Young University * * 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. */ package edu.byu.nlp.util; import com.google.common.base.Preconditions; /** * @author pfelt * * Utility class for operations on matrices * encoded as column major arrays: double[] */ public class ColumnMajorMatrices { public static void normalizeRows(double[] weights, int numRows) { Preconditions.checkNotNull(weights); Preconditions.checkArgument(weights.length % numRows == 0); int rowLength = weights.length / numRows; double[] rowSums = new double[numRows]; int index = 0; for (int col = 0; col < rowLength; col++) { for (int row = 0; row < numRows; row++) { rowSums[row] += weights[index++]; } } index = 0; for (int col = 0; col < rowLength; col++) { for (int row = 0; row < rowSums.length; row++) { weights[index++] /= rowSums[row]; } } } }