Java tutorial
/******************************************************************************* * Copyright (c) 2014, 2015 IBM Corporation * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. *******************************************************************************/ package hulo.localization.utils; import org.apache.commons.math3.linear.LUDecomposition; import org.apache.commons.math3.linear.MatrixUtils; import org.apache.commons.math3.linear.RealMatrix; public class ArrayUtils { public static int[] toIntArray(Integer[] array) { int n = array.length; int[] intArray = new int[n]; for (int i = 0; i < n; i++) { intArray[i] = array[i]; } return intArray; } public static Integer[] toIntegerArray(int[] intArray) { int n = intArray.length; Integer[] IntegerArray = new Integer[n]; for (int i = 0; i < n; i++) { IntegerArray[i] = intArray[i]; } return IntegerArray; } public static double[] column(double[][] array, int j) { int rows = array.length; double[] colvec = new double[rows]; for (int i = 0; i < rows; i++) { colvec[i] = array[i][j]; } return colvec; } public static double[] row(double[][] array, int i) { return array[i]; } public static double min(double[] a) { double min = a[0]; for (int i = 0; i < a.length; i++) { min = Math.min(min, a[i]); } return min; } public static double max(double[] a) { double max = a[0]; for (int i = 0; i < a.length; i++) { max = Math.max(max, a[i]); } return max; } public static String arrayToString(double[] array) { StringBuilder sb = new StringBuilder(); int n = array.length; for (int i = 0; i < n; i++) { if (0 < i) sb.append(","); sb.append(array[i]); } return sb.toString(); } public static String arrayToString(double[][] array) { StringBuilder sb = new StringBuilder(); int n = array.length; for (int i = 0; i < n; i++) { if (0 < i) sb.append("\n"); sb.append(arrayToString(array[i])); } return sb.toString(); } public static double[] toDouble(float[] array) { int n = array.length; double[] a2 = new double[n]; for (int i = 0; i < n; i++) { a2[i] = array[i]; } return a2; } public static float mean(float[] array) { return (float) mean(toDouble(array)); } public static double sum(double[] x) { int n = x.length; double s = 0; for (int i = 0; i < n; i++) { s += x[i]; } return s; } public static double[] sum(double[][] X, int axis) { if (axis == 0) { return sumAxis0(X); } else if (axis == 1) { return sumAxis1(X); } else { String message = "axis>=2 is not supported in sum method."; throw new RuntimeException(message); } } static double[] sumAxis0(double[][] X) { int m = X[0].length; double[] array = new double[m]; for (int j = 0; j < m; j++) { double[] x = column(X, j); array[j] = sum(x); } return array; } static double[] sumAxis1(double[][] X) { int n = X.length; double[] array = new double[n]; for (int i = 0; i < n; i++) { double[] x = row(X, i); array[i] = sum(x); } return array; } public static double[] min(double[][] array) { int np = array[0].length; double[] minArray = new double[np]; for (int j = 0; j < np; j++) { double[] column = ArrayUtils.column(array, j); minArray[j] = ArrayUtils.min(column); } return minArray; } public static double[] max(double[][] array) { int np = array[0].length; double[] maxArray = new double[np]; for (int j = 0; j < np; j++) { double[] column = ArrayUtils.column(array, j); maxArray[j] = ArrayUtils.max(column); } return maxArray; } public static double mean(double[] array) { int n = array.length; double sum = 0; for (int i = 0; i < n; i++) { sum += array[i]; } double mean = sum / ((double) n); return mean; } public static double[] mean(double[][] array) { int n = array.length; int m = array[0].length; double[] mean = new double[m]; for (int i = 0; i < n; i++) { for (int j = 0; j < m; j++) { mean[j] += array[i][j]; } } for (int j = 0; j < m; j++) { mean[j] /= n; } return mean; } public static double var(double[] array) { double mean = mean(array); int n = array.length; double var = 0; for (int i = 0; i < n; i++) { double val = array[i] - mean; var += val * val; } return var / n; } public static double[] var(double[][] array) { double[] mean = mean(array); int n = array.length; int m = array[0].length; double[] var = new double[m]; for (int i = 0; i < n; i++) { for (int j = 0; j < m; j++) { double val = array[i][j] - mean[j]; var[j] += val * val; } } for (int j = 0; j < m; j++) { var[j] /= n; } return var; } public static double stdev(double[] array) { double var = var(array); return Math.sqrt(var); } public static double[] stdev(double[][] array) { double[] var = var(array); for (int i = 0; i < var.length; i++) { var[i] = Math.sqrt(var[i]); } return var; } public static double[] addScalar(double[] array, double scalar) { int n = array.length; double[] arrayNew = new double[n]; for (int i = 0; i < n; i++) { arrayNew[i] = array[i] + scalar; } return arrayNew; } public static double[] multiply(double[][] X1, double[] x2) { RealMatrix M1 = MatrixUtils.createRealMatrix(X1); return M1.operate(x2); } public static double[][] multiply(double[][] X1, double[][] X2) { RealMatrix M1 = MatrixUtils.createRealMatrix(X1); RealMatrix M2 = MatrixUtils.createRealMatrix(X2); RealMatrix M3 = M1.multiply(M2); return M3.getData(); } public static double[][] normalize(double[][] X) { int n = X.length; int m = X[0].length; double eps = 1e-12; double[] mean = mean(X); double[] stds = stdev(X); double[][] Xnew = new double[n][m]; for (int i = 0; i < n; i++) { for (int j = 0; j < m; j++) { Xnew[i][j] = (X[i][j] - mean[j]) / (stds[j] + eps); } } return Xnew; } public static double[] flatten(double[][] Y) { int n = Y.length; int m = Y[0].length; double[] y = new double[n * m]; for (int i = 0; i < n; i++) { for (int j = 0; j < m; j++) { y[i * m + j] = Y[i][j]; } } return y; } public static double[][] inverseMat(double[][] mat) { RealMatrix realMatrix = MatrixUtils.createRealMatrix(mat); LUDecomposition lu = new LUDecomposition(realMatrix); RealMatrix invMat = lu.getSolver().getInverse(); return invMat.getData(); } }