001 /* 002 * Copyright (C) 2008-2010 by Holger Arndt 003 * 004 * This file is part of the Universal Java Matrix Package (UJMP). 005 * See the NOTICE file distributed with this work for additional 006 * information regarding copyright ownership and licensing. 007 * 008 * UJMP is free software; you can redistribute it and/or modify 009 * it under the terms of the GNU Lesser General Public License as 010 * published by the Free Software Foundation; either version 2 011 * of the License, or (at your option) any later version. 012 * 013 * UJMP is distributed in the hope that it will be useful, 014 * but WITHOUT ANY WARRANTY; without even the implied warranty of 015 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 016 * GNU Lesser General Public License for more details. 017 * 018 * You should have received a copy of the GNU Lesser General Public 019 * License along with UJMP; if not, write to the 020 * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, 021 * Boston, MA 02110-1301 USA 022 */ 023 024 package org.ujmp.core.doublematrix.calculation.general.statistical; 025 026 import org.ujmp.core.Coordinates; 027 import org.ujmp.core.Matrix; 028 import org.ujmp.core.annotation.Annotation; 029 import org.ujmp.core.annotation.DefaultAnnotation; 030 import org.ujmp.core.doublematrix.calculation.AbstractDoubleCalculation; 031 import org.ujmp.core.doublematrix.calculation.general.missingvalues.CountMissing; 032 import org.ujmp.core.exceptions.MatrixException; 033 import org.ujmp.core.util.MathUtil; 034 035 public class Var extends AbstractDoubleCalculation { 036 private static final long serialVersionUID = -6376910948253374396L; 037 038 private Matrix mean = null; 039 040 private Matrix missingCount = null; 041 042 private boolean ignoreNaN = false; 043 044 public Var(int dimension, boolean ignoreNaN, Matrix matrix) { 045 super(dimension, matrix); 046 this.ignoreNaN = ignoreNaN; 047 Annotation aold = matrix.getAnnotation(); 048 if (aold != null) { 049 Annotation a = new DefaultAnnotation(getSize()); 050 a.setMatrixAnnotation(aold.getMatrixAnnotation()); 051 if (dimension == ROW) { 052 a.setDimensionMatrix(ROW, aold.getDimensionMatrix(ROW)); 053 } else if (dimension == COLUMN) { 054 a.setDimensionMatrix(COLUMN, aold.getDimensionMatrix(COLUMN)); 055 } 056 setAnnotation(a); 057 } 058 } 059 060 public double getDouble(long... coordinates) throws MatrixException { 061 if (mean == null) { 062 mean = new Mean(getDimension(), ignoreNaN, getSource()).calcNew(); 063 } 064 if (missingCount == null) { 065 missingCount = new CountMissing(getDimension(), getSource()).calcNew(); 066 } 067 068 double sum = 0; 069 070 if (ignoreNaN) { 071 double count = 0; 072 switch (getDimension()) { 073 case ROW: 074 for (long r = getSource().getSize()[ROW] - 1; r != -1; r--) { 075 sum += Math.pow(MathUtil.ignoreNaN(getSource().getAsDouble(r, 076 coordinates[COLUMN])) 077 - mean.getAsDouble(0, coordinates[COLUMN]), 2.0); 078 } 079 count = getSource().getRowCount() 080 - missingCount.getAsDouble(0, coordinates[COLUMN]) - 1; 081 count = count == 0 ? 1 : count; 082 return sum / count; 083 case COLUMN: 084 for (long c = getSource().getSize()[COLUMN] - 1; c != -1; c--) { 085 sum += Math.pow(MathUtil 086 .ignoreNaN(getSource().getAsDouble(coordinates[ROW], c)) 087 - mean.getAsDouble(coordinates[ROW], 0), 2.0); 088 } 089 count = getSource().getColumnCount() 090 - missingCount.getAsDouble(coordinates[ROW], 0) - 1; 091 count = count == 0 ? 1 : count; 092 return sum / count; 093 case ALL: 094 for (long r = getSource().getSize()[ROW] - 1; r != -1; r--) { 095 for (long c = getSource().getSize()[COLUMN] - 1; c != -1; c--) { 096 sum += Math.pow(MathUtil.ignoreNaN(getSource().getAsDouble(r, c)) 097 - mean.getAsDouble(0, 0), 2.0); 098 } 099 } 100 count = (Coordinates.product(getSource().getSize()) 101 - missingCount.getAsDouble(0, 0) - 1); 102 count = count == 0 ? 1 : count; 103 return sum / count; 104 default: 105 return 0.0; 106 } 107 } else { 108 double count = 0; 109 switch (getDimension()) { 110 case ROW: 111 for (long r = getSource().getSize()[ROW] - 1; r != -1; r--) { 112 sum += Math.pow((getSource().getAsDouble(r, coordinates[COLUMN])) 113 - mean.getAsDouble(0, coordinates[COLUMN]), 2.0); 114 } 115 count = getSource().getRowCount() - 1; 116 count = count == 0 ? 1 : count; 117 return sum / count; 118 case COLUMN: 119 for (long c = getSource().getSize()[COLUMN] - 1; c != -1; c--) { 120 sum += Math.pow((getSource().getAsDouble(coordinates[ROW], c)) 121 - mean.getAsDouble(coordinates[ROW], 0), 2.0); 122 } 123 count = getSource().getColumnCount() - 1; 124 count = count == 0 ? 1 : count; 125 return sum / count; 126 case ALL: 127 for (long r = getSource().getSize()[ROW] - 1; r != -1; r--) { 128 for (long c = getSource().getSize()[COLUMN] - 1; c != -1; c--) { 129 sum += Math.pow((getSource().getAsDouble(r, c)) - mean.getAsDouble(0, 0), 130 2.0); 131 } 132 } 133 count = Coordinates.product(getSource().getSize()) - 1; 134 count = count == 0 ? 1 : count; 135 return sum / count; 136 default: 137 return 0.0; 138 } 139 140 } 141 142 } 143 144 public long[] getSize() { 145 switch (getDimension()) { 146 case ROW: 147 return new long[] { 1, getSource().getSize()[COLUMN] }; 148 case COLUMN: 149 return new long[] { getSource().getSize()[ROW], 1 }; 150 case ALL: 151 return new long[] { 1, 1 }; 152 } 153 return null; 154 } 155 156 }