1 // Ceres Solver - A fast non-linear least squares minimizer
2 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
3 // http://code.google.com/p/ceres-solver/
4 //
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6 // modification, are permitted provided that the following conditions are met:
7 //
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9 // this list of conditions and the following disclaimer.
10 // * Redistributions in binary form must reproduce the above copyright notice,
11 // this list of conditions and the following disclaimer in the documentation
12 // and/or other materials provided with the distribution.
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14 // used to endorse or promote products derived from this software without
15 // specific prior written permission.
16 //
17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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28 //
29 // Author: Sameer Agarwal (sameeragarwal@google.com)
30 // David Gallup (dgallup@google.com)
31
32 // This include must come before any #ifndef check on Ceres compile options.
33 #include "ceres/internal/port.h"
34
35 #ifndef CERES_NO_SUITESPARSE
36
37 #include "ceres/canonical_views_clustering.h"
38
39 #include "ceres/collections_port.h"
40 #include "ceres/graph.h"
41 #include "gtest/gtest.h"
42
43 namespace ceres {
44 namespace internal {
45
46 const int kVertexIds[] = {0, 1, 2, 3};
47 class CanonicalViewsTest : public ::testing::Test {
48 protected:
SetUp()49 virtual void SetUp() {
50 // The graph structure is as follows.
51 //
52 // Vertex weights: 0 2 2 0
53 // V0-----V1-----V2-----V3
54 // Edge weights: 0.8 0.9 0.3
55 const double kVertexWeights[] = {0.0, 2.0, 2.0, -1.0};
56 for (int i = 0; i < 4; ++i) {
57 graph_.AddVertex(i, kVertexWeights[i]);
58 }
59 // Create self edges.
60 // CanonicalViews requires that every view "sees" itself.
61 for (int i = 0; i < 4; ++i) {
62 graph_.AddEdge(i, i, 1.0);
63 }
64
65 // Create three edges.
66 const double kEdgeWeights[] = {0.8, 0.9, 0.3};
67 for (int i = 0; i < 3; ++i) {
68 // The graph interface is directed, so remember to create both
69 // edges.
70 graph_.AddEdge(kVertexIds[i], kVertexIds[i + 1], kEdgeWeights[i]);
71 }
72 }
73
ComputeClustering()74 void ComputeClustering() {
75 ComputeCanonicalViewsClustering(options_, graph_, ¢ers_, &membership_);
76 }
77
78 Graph<int> graph_;
79
80 CanonicalViewsClusteringOptions options_;
81 vector<int> centers_;
82 HashMap<int, int> membership_;
83 };
84
TEST_F(CanonicalViewsTest,ComputeCanonicalViewsTest)85 TEST_F(CanonicalViewsTest, ComputeCanonicalViewsTest) {
86 options_.min_views = 0;
87 options_.size_penalty_weight = 0.5;
88 options_.similarity_penalty_weight = 0.0;
89 options_.view_score_weight = 0.0;
90 ComputeClustering();
91
92 // 2 canonical views.
93 EXPECT_EQ(centers_.size(), 2);
94 EXPECT_EQ(centers_[0], kVertexIds[1]);
95 EXPECT_EQ(centers_[1], kVertexIds[3]);
96
97 // Check cluster membership.
98 EXPECT_EQ(FindOrDie(membership_, kVertexIds[0]), 0);
99 EXPECT_EQ(FindOrDie(membership_, kVertexIds[1]), 0);
100 EXPECT_EQ(FindOrDie(membership_, kVertexIds[2]), 0);
101 EXPECT_EQ(FindOrDie(membership_, kVertexIds[3]), 1);
102 }
103
104 // Increases size penalty so the second canonical view won't be
105 // chosen.
TEST_F(CanonicalViewsTest,SizePenaltyTest)106 TEST_F(CanonicalViewsTest, SizePenaltyTest) {
107 options_.min_views = 0;
108 options_.size_penalty_weight = 2.0;
109 options_.similarity_penalty_weight = 0.0;
110 options_.view_score_weight = 0.0;
111 ComputeClustering();
112
113 // 1 canonical view.
114 EXPECT_EQ(centers_.size(), 1);
115 EXPECT_EQ(centers_[0], kVertexIds[1]);
116 }
117
118
119 // Increases view score weight so vertex 2 will be chosen.
TEST_F(CanonicalViewsTest,ViewScoreTest)120 TEST_F(CanonicalViewsTest, ViewScoreTest) {
121 options_.min_views = 0;
122 options_.size_penalty_weight = 0.5;
123 options_.similarity_penalty_weight = 0.0;
124 options_.view_score_weight = 1.0;
125 ComputeClustering();
126
127 // 2 canonical views.
128 EXPECT_EQ(centers_.size(), 2);
129 EXPECT_EQ(centers_[0], kVertexIds[1]);
130 EXPECT_EQ(centers_[1], kVertexIds[2]);
131 }
132
133 // Increases similarity penalty so vertex 2 won't be chosen despite
134 // it's view score.
TEST_F(CanonicalViewsTest,SimilarityPenaltyTest)135 TEST_F(CanonicalViewsTest, SimilarityPenaltyTest) {
136 options_.min_views = 0;
137 options_.size_penalty_weight = 0.5;
138 options_.similarity_penalty_weight = 3.0;
139 options_.view_score_weight = 1.0;
140 ComputeClustering();
141
142 // 2 canonical views.
143 EXPECT_EQ(centers_.size(), 1);
144 EXPECT_EQ(centers_[0], kVertexIds[1]);
145 }
146
147 } // namespace internal
148 } // namespace ceres
149
150 #endif // CERES_NO_SUITESPARSE
151