Squashed 'third_party/ceres/' content from commit e51e9b4
Change-Id: I763587619d57e594d3fa158dc3a7fe0b89a1743b
git-subtree-dir: third_party/ceres
git-subtree-split: e51e9b46f6ca88ab8b2266d0e362771db6d98067
diff --git a/internal/ceres/canonical_views_clustering_test.cc b/internal/ceres/canonical_views_clustering_test.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2015 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// 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)
+
+#include "ceres/canonical_views_clustering.h"
+
+#include <unordered_map>
+#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_;
+ std::unordered_map<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