MYNT-EYE-S-SDK/3rdparty/ceres-solver-1.11.0/internal/ceres/single_linkage_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)
// This include must come before any #ifndef check on Ceres compile options.
#include "ceres/internal/port.h"
#ifndef CERES_NO_SUITESPARSE
#include "ceres/single_linkage_clustering.h"
#include "ceres/collections_port.h"
#include "ceres/graph.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
TEST(SingleLinkageClustering, GraphHasTwoComponents) {
WeightedGraph<int> graph;
const int kNumVertices = 6;
for (int i = 0; i < kNumVertices; ++i) {
graph.AddVertex(i);
}
// Graph structure:
//
// 0-1-2-3 4-5
graph.AddEdge(0, 1, 1.0);
graph.AddEdge(1, 2, 1.0);
graph.AddEdge(2, 3, 1.0);
graph.AddEdge(4, 5, 1.0);
SingleLinkageClusteringOptions options;
HashMap<int, int> membership;
ComputeSingleLinkageClustering(options, graph, &membership);
EXPECT_EQ(membership.size(), kNumVertices);
EXPECT_EQ(membership[1], membership[0]);
EXPECT_EQ(membership[2], membership[0]);
EXPECT_EQ(membership[3], membership[0]);
EXPECT_NE(membership[4], membership[0]);
EXPECT_NE(membership[5], membership[0]);
EXPECT_EQ(membership[4], membership[5]);
}
TEST(SingleLinkageClustering, ComponentWithWeakLink) {
WeightedGraph<int> graph;
const int kNumVertices = 6;
for (int i = 0; i < kNumVertices; ++i) {
graph.AddVertex(i);
}
// Graph structure:
//
// 0-1-2-3 4-5
graph.AddEdge(0, 1, 1.0);
graph.AddEdge(1, 2, 1.0);
graph.AddEdge(2, 3, 1.0);
// This component should break up into two.
graph.AddEdge(4, 5, 0.5);
SingleLinkageClusteringOptions options;
HashMap<int, int> membership;
ComputeSingleLinkageClustering(options, graph, &membership);
EXPECT_EQ(membership.size(), kNumVertices);
EXPECT_EQ(membership[1], membership[0]);
EXPECT_EQ(membership[2], membership[0]);
EXPECT_EQ(membership[3], membership[0]);
EXPECT_NE(membership[4], membership[0]);
EXPECT_NE(membership[5], membership[0]);
EXPECT_NE(membership[4], membership[5]);
}
TEST(SingleLinkageClustering, ComponentWithWeakLinkAndStrongLink) {
WeightedGraph<int> graph;
const int kNumVertices = 6;
for (int i = 0; i < kNumVertices; ++i) {
graph.AddVertex(i);
}
// Graph structure:
//
// 0-1-2-3 4-5
graph.AddEdge(0, 1, 1.0);
graph.AddEdge(1, 2, 1.0);
graph.AddEdge(2, 3, 0.5); // Weak link
graph.AddEdge(0, 3, 1.0);
// This component should break up into two.
graph.AddEdge(4, 5, 1.0);
SingleLinkageClusteringOptions options;
HashMap<int, int> membership;
ComputeSingleLinkageClustering(options, graph, &membership);
EXPECT_EQ(membership.size(), kNumVertices);
EXPECT_EQ(membership[1], membership[0]);
EXPECT_EQ(membership[2], membership[0]);
EXPECT_EQ(membership[3], membership[0]);
EXPECT_EQ(membership[4], membership[5]);
}
} // namespace internal
} // namespace ceres
#endif // CERES_NO_SUITESPARSE