1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
|
/*=========================================================================
Program: Visualization Toolkit
Module: vtkImageHistogramStatistics.cxx
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notice for more information.
=========================================================================*/
#include "vtkImageHistogramStatistics.h"
#include "vtkObjectFactory.h"
#include "vtkIdTypeArray.h"
#include <math.h>
vtkStandardNewMacro(vtkImageHistogramStatistics);
//----------------------------------------------------------------------------
// Constructor sets default values
vtkImageHistogramStatistics::vtkImageHistogramStatistics()
{
this->AutomaticBinning = true;
this->GenerateHistogramImage = false;
this->Minimum = 0;
this->Maximum = 0;
this->Median = 0;
this->Mean = 0;
this->StandardDeviation = 0;
this->AutoRange[0] = 0;
this->AutoRange[1] = 1;
this->AutoRangePercentiles[0] = 1;
this->AutoRangePercentiles[1] = 99;
this->AutoRangeExpansionFactors[0] = 0.1;
this->AutoRangeExpansionFactors[1] = 0.1;
}
//----------------------------------------------------------------------------
vtkImageHistogramStatistics::~vtkImageHistogramStatistics()
{
}
//----------------------------------------------------------------------------
void vtkImageHistogramStatistics::PrintSelf(ostream& os, vtkIndent indent)
{
this->Superclass::PrintSelf(os,indent);
os << indent << "Minimum: " << this->Minimum << "\n";
os << indent << "Maximum: " << this->Maximum << "\n";
os << indent << "Median: " << this->Median << "\n";
os << indent << "Mean: " << this->Mean << "\n";
os << indent << "StandardDeviation: " << this->StandardDeviation << "\n";
os << indent << "AutoRange: " << this->AutoRange[0] << " "
<< this->AutoRange[1] << "\n";
os << indent << "AutoRangePercentiles: "
<< this->AutoRangePercentiles[0] << " "
<< this->AutoRangePercentiles[1] << "\n";
os << indent << "AutoRangeExpansionFactors: "
<< this->AutoRangeExpansionFactors[0] << " "
<< this->AutoRangeExpansionFactors[1] << "\n";
}
//----------------------------------------------------------------------------
int vtkImageHistogramStatistics::RequestData(
vtkInformation* request,
vtkInformationVector** inputVector,
vtkInformationVector* outputVector)
{
this->Superclass::RequestData(request, inputVector, outputVector);
double lowPercentile = this->AutoRangePercentiles[0]*0.01;
double highPercentile = this->AutoRangePercentiles[1]*0.01;
vtkIdType total = this->Total;
vtkIdType sum = 0;
vtkIdType lowSum = static_cast<vtkIdType>(total*lowPercentile);
vtkIdType highSum = static_cast<vtkIdType>(total*highPercentile);
vtkIdType midSum = total/2;
vtkIdType lowVal = 0;
vtkIdType highVal = 0;
vtkIdType midVal = 0;
vtkIdType minVal = -1;
vtkIdType maxVal = 0;
double mom1 = 0;
double mom2 = 0;
vtkIdType nx = this->Histogram->GetNumberOfTuples();
vtkIdType *histogram = this->Histogram->GetPointer(0);
for (int ix = 0; ix < nx; ++ix)
{
vtkIdType c = histogram[ix];
sum += c;
double dc = static_cast<double>(c);
mom1 += dc*ix;
mom2 += dc*ix*ix;
lowVal = (sum > lowSum ? lowVal : ix);
highVal = (sum > highSum ? highVal : ix);
midVal = (sum > midSum ? midVal : ix);
minVal = (sum > 0 ? minVal : ix);
maxVal = (c == 0 ? maxVal : ix);
}
if (minVal < maxVal)
{
minVal++;
}
double binSpacing = this->BinSpacing;
double binOrigin = this->BinOrigin;
// do the basic statistics
this->Minimum = minVal*binSpacing + binOrigin;
this->Maximum = maxVal*binSpacing + binOrigin;
this->Median = midVal*binSpacing + binOrigin;
this->Mean = 0.0;
this->StandardDeviation = 0.0;
if (total > 0)
{
this->Mean = mom1/total*binSpacing + binOrigin;
}
if (total > 1)
{
double term2 = mom1*mom1/total;
if ((mom2 - term2) > 1e-10*mom2)
{
// use the fast method to compute standard deviation
this->StandardDeviation = sqrt((mom2 - term2)/(total - 1))*binSpacing;
}
else
{
// use more accurate method to avoid cancellation error
double xmean = mom1/total;
for (int ix = 0; ix < nx; ++ix)
{
double ixd = xmean - ix;
mom2 += ixd*ixd*histogram[ix];
}
this->StandardDeviation = sqrt(mom2/(total - 1))*binSpacing;
}
}
// do the autorange: first expand range by 10% at each end
double lowEF = this->AutoRangeExpansionFactors[0];
double highEF = this->AutoRangeExpansionFactors[1];
int lowExpansion = static_cast<int>(lowEF*(highVal - lowVal));
int highExpansion = static_cast<int>(highEF*(highVal - lowVal));
lowVal -= lowExpansion;
highVal += highExpansion;
this->AutoRange[0] = lowVal*binSpacing + binOrigin;
this->AutoRange[1] = highVal*binSpacing + binOrigin;
// clamp the auto range to the full data range
if (this->AutoRange[0] < this->Minimum)
{
this->AutoRange[0] = this->Minimum;
}
if (this->AutoRange[1] > this->Maximum)
{
this->AutoRange[1] = this->Maximum;
}
return 1;
}
|
