1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.imaging.formats.tiff;
18
19 /**
20 * Collects and stores a set of simple statistics from the input raster.
21 */
22 public class TiffRasterStatistics {
23
24 private final int nSample;
25 private final int nNull;
26 private final float minValue;
27 private final float maxValue;
28 private final float meanValue;
29 private final float excludedValue;
30
31 /**
32 * Constructs an instance of this class, tabulating results from the input raster data.
33 *
34 * @param raster the input data
35 * @param excludedValue an optional value to ignore; use Float.NaN if no value is to be ignored.
36 */
37 TiffRasterStatistics(final TiffRasterData raster, final float excludedValue) {
38 this.excludedValue = excludedValue;
39 float vMin = Float.POSITIVE_INFINITY;
40 float vMax = Float.NEGATIVE_INFINITY;
41 double vSum = 0;
42 int nS = 0;
43 int nN = 0;
44 final float[] data = raster.getData();
45 for (final float test : data) {
46 if (Float.isNaN(test)) {
47 nN++;
48 continue;
49 }
50 if (test == excludedValue) {
51 continue;
52 }
53
54 nS++;
55 vSum += test;
56 if (test < vMin) {
57 vMin = test;
58 }
59 if (test > vMax) {
60 vMax = test;
61 }
62 }
63
64 minValue = vMin;
65 maxValue = vMax;
66 nSample = nS;
67 nNull = nN;
68 if (nSample == 0) {
69 meanValue = 0;
70 } else {
71 meanValue = (float) (vSum / nSample);
72 }
73 }
74
75 /**
76 * Gets the count of the number of null samples in the collection.
77 *
78 * @return the a positive number, potentially zero
79 */
80 public int getCountOfNulls() {
81 return nNull;
82 }
83
84 /**
85 * Gets the count of the number of non-null and non-excluded samples in the collection.
86 *
87 * @return the a positive number, potentially zero
88 */
89 public int getCountOfSamples() {
90 return nSample;
91 }
92
93 /**
94 * Gets the value that was set for exclusion, or a Float.NaN if not was set.
95 *
96 * @return the excluded value (if any).
97 */
98 public float getExcludedValue() {
99 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 }