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// Copyright (c) the JPEG XL Project Authors. All rights reserved.
//
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
#include "lib/jxl/enc_optimize.h"
#include <algorithm>
#include "lib/jxl/base/status.h"
namespace jxl {
namespace optimize {
namespace {
// simplex vector must be sorted by first element of its elements
std::vector<double> Midpoint(const std::vector<std::vector<double>>& simplex) {
JXL_CHECK(!simplex.empty());
JXL_CHECK(simplex.size() == simplex[0].size());
int dim = simplex.size() - 1;
std::vector<double> result(dim + 1, 0);
for (int i = 0; i < dim; i++) {
for (int k = 0; k < dim; k++) {
result[i + 1] += simplex[k][i + 1];
}
result[i + 1] /= dim;
}
return result;
}
// first element ignored
std::vector<double> Subtract(const std::vector<double>& a,
const std::vector<double>& b) {
JXL_CHECK(a.size() == b.size());
std::vector<double> result(a.size());
result[0] = 0;
for (size_t i = 1; i < result.size(); i++) {
result[i] = a[i] - b[i];
}
return result;
}
// first element ignored
std::vector<double> Add(const std::vector<double>& a,
const std::vector<double>& b) {
JXL_CHECK(a.size() == b.size());
std::vector<double> result(a.size());
result[0] = 0;
for (size_t i = 1; i < result.size(); i++) {
result[i] = a[i] + b[i];
}
return result;
}
// first element ignored
std::vector<double> Average(const std::vector<double>& a,
const std::vector<double>& b) {
JXL_CHECK(a.size() == b.size());
std::vector<double> result(a.size());
result[0] = 0;
for (size_t i = 1; i < result.size(); i++) {
result[i] = 0.5 * (a[i] + b[i]);
}
return result;
}
// vec: [0] will contain the objective function, [1:] will
// contain the vector position for the objective function.
// fun: the function evaluates the value.
void Eval(std::vector<double>* vec,
const std::function<double(const std::vector<double>&)>& fun) {
std::vector<double> args(vec->begin() + 1, vec->end());
(*vec)[0] = fun(args);
}
void Sort(std::vector<std::vector<double>>* simplex) {
std::sort(simplex->begin(), simplex->end());
}
// Main iteration step of Nelder-Mead like optimization.
void Reflect(std::vector<std::vector<double>>* simplex,
const std::function<double(const std::vector<double>&)>& fun) {
Sort(simplex);
const std::vector<double>& last = simplex->back();
std::vector<double> mid = Midpoint(*simplex);
std::vector<double> diff = Subtract(mid, last);
std::vector<double> mirrored = Add(mid, diff);
Eval(&mirrored, fun);
if (mirrored[0] > (*simplex)[simplex->size() - 2][0]) {
// Still the worst, shrink towards the best.
std::vector<double> shrinking = Average(simplex->back(), (*simplex)[0]);
Eval(&shrinking, fun);
simplex->back() = shrinking;
} else if (mirrored[0] < (*simplex)[0][0]) {
// new best
std::vector<double> even_further = Add(mirrored, diff);
Eval(&even_further, fun);
if (even_further[0] < mirrored[0]) {
mirrored = even_further;
}
simplex->back() = mirrored;
} else {
// not a best, not a worst point
simplex->back() = mirrored;
}
}
// Initialize the simplex at origin.
std::vector<std::vector<double>> InitialSimplex(
int dim, double amount, const std::vector<double>& init,
const std::function<double(const std::vector<double>&)>& fun) {
std::vector<double> best(1 + dim, 0);
std::copy(init.begin(), init.end(), best.begin() + 1);
Eval(&best, fun);
std::vector<std::vector<double>> result{best};
for (int i = 0; i < dim; i++) {
best = result[0];
best[i + 1] += amount;
Eval(&best, fun);
result.push_back(best);
Sort(&result);
}
return result;
}
// For comparing the same with the python tool
/*void RunSimplexExternal(
int dim, double amount, int max_iterations,
const std::function<double((const vector<double>&))>& fun) {
vector<double> vars;
for (int i = 0; i < dim; i++) {
vars.push_back(atof(getenv(StrCat("VAR", i).c_str())));
}
double result = fun(vars);
std::cout << "Result=" << result;
}*/
} // namespace
std::vector<double> RunSimplex(
int dim, double amount, int max_iterations, const std::vector<double>& init,
const std::function<double(const std::vector<double>&)>& fun) {
std::vector<std::vector<double>> simplex =
InitialSimplex(dim, amount, init, fun);
for (int i = 0; i < max_iterations; i++) {
Sort(&simplex);
Reflect(&simplex, fun);
}
return simplex[0];
}
std::vector<double> RunSimplex(
int dim, double amount, int max_iterations,
const std::function<double(const std::vector<double>&)>& fun) {
std::vector<double> init(dim, 0.0);
return RunSimplex(dim, amount, max_iterations, init, fun);
}
} // namespace optimize
} // namespace jxl
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