001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017package org.apache.commons.imaging.formats.tiff; 018 019/** 020 * Collects and stores a set of simple statistics from the input raster. 021 */ 022public class TiffRasterStatistics { 023 024 private final int nSample; 025 private final int nNull; 026 private final float minValue; 027 private final float maxValue; 028 private final float meanValue; 029 private final float excludedValue; 030 031 /** 032 * Constructs an instance of this class, tabulating results from the input 033 * raster data. 034 * 035 * @param raster the input data 036 * @param excludedValue an optional value to ignore; use Float.NaN if no 037 * value is to be ignored. 038 */ 039 TiffRasterStatistics(final TiffRasterData raster, final float excludedValue) { 040 this.excludedValue = excludedValue; 041 float vMin = Float.POSITIVE_INFINITY; 042 float vMax = Float.NEGATIVE_INFINITY; 043 double vSum = 0; 044 int nS = 0; 045 int nN = 0; 046 final float[] data = raster.getData(); 047 for (final float test : data) { 048 if (Float.isNaN(test)) { 049 nN++; 050 continue; 051 } 052 if (test == excludedValue) { 053 continue; 054 } 055 056 nS++; 057 vSum += test; 058 if (test < vMin) { 059 vMin = test; 060 } 061 if (test > vMax) { 062 vMax = test; 063 } 064 } 065 066 minValue = vMin; 067 maxValue = vMax; 068 nSample = nS; 069 nNull = nN; 070 if (nSample == 0) { 071 meanValue = 0; 072 } else { 073 meanValue = (float) (vSum / nSample); 074 } 075 } 076 077 /** 078 * Get the count of the number of non-null and non-excluded samples in the 079 * collection. 080 * 081 * @return the a positive number, potentially zero 082 */ 083 public int getCountOfSamples() { 084 return nSample; 085 } 086 087 /** 088 * Get the count of the number of null samples in the collection. 089 * 090 * @return the a positive number, potentially zero 091 */ 092 public int getCountOfNulls() { 093 return nNull; 094 } 095 096 /** 097 * Get the minimum value found in the source data 098 * 099 * @return the minimum value found in the source data 100 */ 101 public float getMinValue() { 102 return minValue; 103 } 104 105 /** 106 * Get the maximum value found in the source data 107 * 108 * @return the maximum value found in the source data 109 */ 110 public float getMaxValue() { 111 return maxValue; 112 } 113 114 /** 115 * Get the mean value for all sample values in the raster. Null-data values 116 * and excluded values are not considered. 117 * 118 * @return the mean value of the samples 119 */ 120 public float getMeanValue() { 121 return meanValue; 122 } 123 124 /** 125 * Indicates if a sample value was set to be deliberately excluded from the 126 * statistics. 127 * 128 * @return true if a value was set for exclusion; otherwise, false 129 */ 130 public boolean isAnExcludedValueSet() { 131 return !Float.isNaN(excludedValue); 132 } 133 134 /** 135 * Get the value that was set for exclusion, or a Float.NaN if not was 136 * set. 137 * 138 * @return the excluded value (if any). 139 */ 140 public float getExcludedValue() { 141 return excludedValue; 142 } 143}