| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150 | // Ceres Solver - A fast non-linear least squares minimizer// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.// http://code.google.com/p/ceres-solver///// Redistribution and use in source and binary forms, with or without// modification, are permitted provided that the following conditions are met://// * Redistributions of source code must retain the above copyright notice,//   this list of conditions and the following disclaimer.// * Redistributions in binary form must reproduce the above copyright notice,//   this list of conditions and the following disclaimer in the documentation//   and/or other materials provided with the distribution.// * Neither the name of Google Inc. nor the names of its contributors may be//   used to endorse or promote products derived from this software without//   specific prior written permission.//// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE// POSSIBILITY OF SUCH DAMAGE.//// Author: Sameer Agarwal (sameeragarwal@google.com)//         David Gallup (dgallup@google.com)// This include must come before any #ifndef check on Ceres compile options.#include "ceres/internal/port.h"#ifndef CERES_NO_SUITESPARSE#include "ceres/canonical_views_clustering.h"#include "ceres/collections_port.h"#include "ceres/graph.h"#include "gtest/gtest.h"namespace ceres {namespace internal {const int kVertexIds[] = {0, 1, 2, 3};class CanonicalViewsTest : public ::testing::Test { protected:  virtual void SetUp() {    // The graph structure is as follows.    //    // Vertex weights:   0      2      2      0    //                   V0-----V1-----V2-----V3    // Edge weights:        0.8    0.9    0.3    const double kVertexWeights[] = {0.0, 2.0, 2.0, -1.0};    for (int i = 0; i < 4; ++i) {      graph_.AddVertex(i, kVertexWeights[i]);    }    // Create self edges.    // CanonicalViews requires that every view "sees" itself.    for (int i = 0; i < 4; ++i) {      graph_.AddEdge(i, i, 1.0);    }    // Create three edges.    const double kEdgeWeights[] = {0.8, 0.9, 0.3};    for (int i = 0; i < 3; ++i) {      // The graph interface is directed, so remember to create both      // edges.      graph_.AddEdge(kVertexIds[i], kVertexIds[i + 1], kEdgeWeights[i]);    }  }  void ComputeClustering() {    ComputeCanonicalViewsClustering(options_, graph_, ¢ers_, &membership_);  }  WeightedGraph<int> graph_;  CanonicalViewsClusteringOptions options_;  std::vector<int> centers_;  HashMap<int, int> membership_;};TEST_F(CanonicalViewsTest, ComputeCanonicalViewsTest) {  options_.min_views = 0;  options_.size_penalty_weight = 0.5;  options_.similarity_penalty_weight = 0.0;  options_.view_score_weight = 0.0;  ComputeClustering();  // 2 canonical views.  EXPECT_EQ(centers_.size(), 2);  EXPECT_EQ(centers_[0], kVertexIds[1]);  EXPECT_EQ(centers_[1], kVertexIds[3]);  // Check cluster membership.  EXPECT_EQ(FindOrDie(membership_, kVertexIds[0]), 0);  EXPECT_EQ(FindOrDie(membership_, kVertexIds[1]), 0);  EXPECT_EQ(FindOrDie(membership_, kVertexIds[2]), 0);  EXPECT_EQ(FindOrDie(membership_, kVertexIds[3]), 1);}// Increases size penalty so the second canonical view won't be// chosen.TEST_F(CanonicalViewsTest, SizePenaltyTest) {  options_.min_views = 0;  options_.size_penalty_weight = 2.0;  options_.similarity_penalty_weight = 0.0;  options_.view_score_weight = 0.0;  ComputeClustering();  // 1 canonical view.  EXPECT_EQ(centers_.size(), 1);  EXPECT_EQ(centers_[0], kVertexIds[1]);}// Increases view score weight so vertex 2 will be chosen.TEST_F(CanonicalViewsTest, ViewScoreTest) {  options_.min_views = 0;  options_.size_penalty_weight = 0.5;  options_.similarity_penalty_weight = 0.0;  options_.view_score_weight = 1.0;  ComputeClustering();  // 2 canonical views.  EXPECT_EQ(centers_.size(), 2);  EXPECT_EQ(centers_[0], kVertexIds[1]);  EXPECT_EQ(centers_[1], kVertexIds[2]);}// Increases similarity penalty so vertex 2 won't be chosen despite// it's view score.TEST_F(CanonicalViewsTest, SimilarityPenaltyTest) {  options_.min_views = 0;  options_.size_penalty_weight = 0.5;  options_.similarity_penalty_weight = 3.0;  options_.view_score_weight = 1.0;  ComputeClustering();  // 2 canonical views.  EXPECT_EQ(centers_.size(), 1);  EXPECT_EQ(centers_[0], kVertexIds[1]);}}  // namespace internal}  // namespace ceres#endif  // CERES_NO_SUITESPARSE
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