75 lines
2.2 KiB
C++
75 lines
2.2 KiB
C++
/*
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* This Source Code Form is subject to the terms of the Mozilla Public
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* License, v. 2.0. If a copy of the MPL was not distributed with this
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* file, You can obtain one at http://mozilla.org/MPL/2.0/.
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*
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* Copyright 2018 Danny Robson <danny@nerdcruft.net>
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*/
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#pragma once
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#include "debug/assert.hpp"
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#include "iterator/zip.hpp"
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#include "point.hpp"
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#include <iterator>
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namespace cruft {
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// a simplistic implementation of Lloyd's algorithm
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//
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// returns index of the closest output for each input
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template <typename OutputT, typename InputT, typename FunctionT>
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std::vector<size_t>
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kmeans (cruft::view<InputT> src, cruft::view<OutputT> dst, FunctionT const &&metric)
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{
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CHECK_GE (src.size (), dst.size ());
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using coord_t = typename std::iterator_traits<InputT>::value_type;
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const int iterations = 100;
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std::vector<coord_t> means (src.begin (), src.begin () + dst.size ());
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std::vector<coord_t> accum (dst.size ());
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std::vector<size_t> count (dst.size ());
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std::vector<size_t> closest (src.size ());
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for (auto i = 0; i < iterations; ++i) {
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std::fill (std::begin (accum), std::end (accum), 0);
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std::fill (std::begin (count), std::end (count), 0);
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for (auto const& [j,p]: iterator::izip (src)) {
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size_t bucket = 0;
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for (size_t k = 1; k < dst.size (); ++k) {
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if (metric (p, means[k]) < metric (p, means[bucket]))
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bucket = k;
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}
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accum[bucket] += p;
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count[bucket] += 1;
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closest[j] = bucket;
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}
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for (size_t j = 0; j < dst.size (); ++j)
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means[j] = accum[j] / count[j];
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}
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std::copy (std::begin (means), std::end (means), std::begin (dst));
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return closest;
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}
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template <typename OutputT, typename InputT>
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auto
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kmeans (InputT &&src, OutputT &&dst)
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{
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return kmeans (
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std::forward<InputT> (src),
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std::forward<OutputT> (dst),
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[] (auto a, auto b) {
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return norm (a - b);
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});
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}
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}
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