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secondo/Algebras/ImageSimilarity/compare_kmeans.cpp
2026-01-23 17:03:45 +08:00

121 lines
3.1 KiB
C++

/*
----
This file is NOT part of SECONDO.
Authors: Greg Hamerly and Jonathan Drake
Feedback: hamerly@cs.baylor.edu
See: http://cs.baylor.edu/~hamerly/software/kmeans.php
Copyright 2014
----
//paragraph [1] Title: [{\Large \bf \begin{center}] [\end{center}}]
//[TOC] [\tableofcontents]
[1] Implementation of the CompareKmeans algorithm
1 Implementation of the CompareKmeans algorithm
*/
/* Authors: Greg Hamerly and Jonathan Drake
* Feedback: hamerly@cs.baylor.edu
* See: http://cs.baylor.edu/~hamerly/software/kmeans.php
* Copyright 2014
*/
#include "compare_kmeans.h"
#include "general_functions.h"
#include <cassert>
#include <cmath>
#include <algorithm>
void CompareKmeans::free() {
OriginalSpaceKmeans::free();
delete [] centersDist2div4;
centersDist2div4 = NULL;
}
void CompareKmeans::update_center_dists(int threadId) {
// find the inter-center distances
for (int c1 = 0; c1 < k; ++c1) {
#ifdef USE_THREADS
if (c1 % numThreads != threadId) {
continue;
}
#endif
centersDist2div4[c1 * k + c1]
= std::numeric_limits<double>::max();
for (int c2 = c1 + 1; c2 < k; ++c2) {
centersDist2div4[c1 * k + c2] = centersDist2div4[c2
* k + c1] = centerCenterDist2(c1, c2) / 4.0;
}
}
}
void CompareKmeans::initialize(Dataset const *aX, unsigned short aK,
unsigned short *initialAssignment, int aNumThreads) {
OriginalSpaceKmeans::initialize(aX, aK, initialAssignment,
aNumThreads);
centersDist2div4 = new double[k * k];
std::fill(centersDist2div4, centersDist2div4 + k * k, 0.0);
}
int CompareKmeans::runThread(int threadId, int maxIterations) {
int iterations = 0;
int startNdx = start(threadId);
int endNdx = end(threadId);
while ((iterations < maxIterations) && ! converged) {
++iterations;
update_center_dists(threadId);
synchronizeAllThreads();
for (int i = startNdx; i < endNdx; ++i) {
int minClass = assignment[i];
double minDist2 = pointCenterDist2(i, minClass);
for (int j = 0; j < k; ++j) {
// center-center squared distances are already divided by 4.0
if (centersDist2div4[j * k + minClass] > minDist2)
continue;
if (j == minClass) continue;
const double dist2 = pointCenterDist2(i, j);
if (dist2 < minDist2) {
minDist2 = dist2;
minClass = j;
} else if (dist2 == minDist2) {
if (j < minClass) {
minClass = j;
}
}
}
if (assignment[i] != minClass) {
changeAssignment(i, minClass, threadId);
}
}
verifyAssignment(iterations, startNdx, endNdx);
synchronizeAllThreads();
if (threadId == 0) {
int furthestMovingCenter = move_centers();
converged = (0.0 == centerMovement[furthestMovingCenter]);
}
synchronizeAllThreads();
}
return iterations;
}