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
|
/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
// Software Guide : BeginLatex
//
// \index{itk::Statistics::MinimumDecisionRule}
//
// The \code{Evaluate()} method of the \doxygen{MinimumDecisionRule}
// returns the index of the smallest discriminant score among the
// vector of discriminant scores that it receives as input.
//
// To begin this example, we include the class header file. We also include
// the header file for the \code{std::vector} class that will be the
// container for the discriminant scores.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkMinimumDecisionRule.h"
#include <vector>
// Software Guide : EndCodeSnippet
int main(int, char*[])
{
// Software Guide : BeginLatex
//
// The instantiation of the function is done through the usual
// \code{New()} method and a smart pointer.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::Statistics::MinimumDecisionRule DecisionRuleType;
DecisionRuleType::Pointer decisionRule = DecisionRuleType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We create the discriminant score vector and fill it with three
// values. The call \code{Evaluate( discriminantScores )} will return 0
// because the first value is the smallest value.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
DecisionRuleType::MembershipVectorType discriminantScores;
discriminantScores.push_back( 0.1 );
discriminantScores.push_back( 0.3 );
discriminantScores.push_back( 0.6 );
std::cout << "MinimumDecisionRule: The index of the chosen = "
<< decisionRule->Evaluate( discriminantScores )
<< std::endl;
// Software Guide : EndCodeSnippet
return EXIT_SUCCESS;
}
|
