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 raster data. 033 * 034 * @param raster the input data 035 * @param excludedValue an optional value to ignore; use Float.NaN if no value is to be ignored. 036 */ 037 TiffRasterStatistics(final AbstractTiffRasterData raster, final float excludedValue) { 038 this.excludedValue = excludedValue; 039 float vMin = Float.POSITIVE_INFINITY; 040 float vMax = Float.NEGATIVE_INFINITY; 041 double vSum = 0; 042 int nS = 0; 043 int nN = 0; 044 final float[] data = raster.getData(); 045 for (final float test : data) { 046 if (Float.isNaN(test)) { 047 nN++; 048 continue; 049 } 050 if (test == excludedValue) { 051 continue; 052 } 053 054 nS++; 055 vSum += test; 056 if (test < vMin) { 057 vMin = test; 058 } 059 if (test > vMax) { 060 vMax = test; 061 } 062 } 063 064 minValue = vMin; 065 maxValue = vMax; 066 nSample = nS; 067 nNull = nN; 068 if (nSample == 0) { 069 meanValue = 0; 070 } else { 071 meanValue = (float) (vSum / nSample); 072 } 073 } 074 075 /** 076 * Gets the count of the number of null samples in the collection. 077 * 078 * @return the a positive number, potentially zero 079 */ 080 public int getCountOfNulls() { 081 return nNull; 082 } 083 084 /** 085 * Gets the count of the number of non-null and non-excluded samples in the collection. 086 * 087 * @return the a positive number, potentially zero 088 */ 089 public int getCountOfSamples() { 090 return nSample; 091 } 092 093 /** 094 * Gets the value that was set for exclusion, or a Float.NaN if not was set. 095 * 096 * @return the excluded value (if any). 097 */ 098 public float getExcludedValue() { 099 return excludedValue; 100 } 101 102 /** 103 * Gets the maximum value found in the source data 104 * 105 * @return the maximum value found in the source data 106 */ 107 public float getMaxValue() { 108 return maxValue; 109 } 110 111 /** 112 * Gets the mean value for all sample values in the raster. Null-data values and excluded values are not considered. 113 * 114 * @return the mean value of the samples 115 */ 116 public float getMeanValue() { 117 return meanValue; 118 } 119 120 /** 121 * Gets the minimum value found in the source data 122 * 123 * @return the minimum value found in the source data 124 */ 125 public float getMinValue() { 126 return minValue; 127 } 128 129 /** 130 * Indicates if a sample value was set to be deliberately excluded from the statistics. 131 * 132 * @return true if a value was set for exclusion; otherwise, false 133 */ 134 public boolean isAnExcludedValueSet() { 135 return !Float.isNaN(excludedValue); 136 } 137}