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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 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
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//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/single_linkage_clustering.h"
#include <unordered_map>
#include <unordered_set>
#include "ceres/graph.h"
#include "ceres/graph_algorithms.h"
namespace ceres::internal {
int ComputeSingleLinkageClustering(
const SingleLinkageClusteringOptions& options,
const WeightedGraph<int>& graph,
std::unordered_map<int, int>* membership) {
CHECK(membership != nullptr);
membership->clear();
// Initially each vertex is in its own cluster.
const std::unordered_set<int>& vertices = graph.vertices();
for (const int v : vertices) {
(*membership)[v] = v;
}
for (const int vertex1 : vertices) {
const std::unordered_set<int>& neighbors = graph.Neighbors(vertex1);
for (const int vertex2 : neighbors) {
// Since the graph is undirected, only pay attention to one side
// of the edge and ignore weak edges.
if ((vertex1 > vertex2) ||
(graph.EdgeWeight(vertex1, vertex2) < options.min_similarity)) {
continue;
}
// Use a union-find algorithm to keep track of the clusters.
const int c1 = FindConnectedComponent(vertex1, membership);
const int c2 = FindConnectedComponent(vertex2, membership);
if (c1 == c2) {
continue;
}
if (c1 < c2) {
(*membership)[c2] = c1;
} else {
(*membership)[c1] = c2;
}
}
}
// Make sure that every vertex is connected directly to the vertex
// identifying the cluster.
int num_clusters = 0;
for (auto& m : *membership) {
m.second = FindConnectedComponent(m.first, membership);
if (m.first == m.second) {
++num_clusters;
}
}
return num_clusters;
}
} // namespace ceres::internal