coco
104 lines
2.8 KiB
C++
104 lines
2.8 KiB
C++
// Copyright (C) 2018 Davis E. King (davis@dlib.net)
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// License: Boost Software License See LICENSE.txt for the full license.
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#include <dlib/optimization.h>
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#include <dlib/global_optimization.h>
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#include <sstream>
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#include <string>
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#include <cstdlib>
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#include <ctime>
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#include <vector>
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#include "tester.h"
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namespace
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{
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using namespace test;
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using namespace dlib;
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using namespace std;
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logger dlog("test.isotonic_regression");
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// ----------------------------------------------------------------------------------------
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class optimization_tester : public tester
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{
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public:
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optimization_tester (
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) :
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tester ("test_isotonic_regression",
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"Runs tests on the isotonic_regression object.")
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{}
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void perform_test (
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)
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{
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dlib::rand rnd;
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for (int round = 0; round < 100; ++round)
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{
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print_spinner();
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std::vector<double> vect;
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for (int i = 0; i < 5; ++i)
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vect.push_back(put_in_range(-1,1,rnd.get_random_gaussian()));
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auto f = [&](const matrix<double,0,1>& x)
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{
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double dist = 0;
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double sum = 0;
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for (long i = 0; i < x.size(); ++i)
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{
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sum += x(i);
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dist += (sum-vect[i])*(sum-vect[i]);
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}
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return dist;
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};
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auto objval = [vect](const matrix<double,0,1>& x)
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{
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return sum(squared(mat(vect)-x));
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};
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auto is_monotonic = [](const matrix<double,0,1>& x)
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{
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for (long i = 1; i < x.size(); ++i)
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{
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if (x(i-1) > x(i))
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return false;
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}
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return true;
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};
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matrix<double,0,1> lower(5), upper(5);
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lower = 0;
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lower(0) = -4;
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upper = 4;
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// find the solution with find_min_global() and then check that it matches
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auto result = find_min_global(f, lower, upper, max_function_calls(40));
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for (long i = 1; i < result.x.size(); ++i)
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result.x(i) += result.x(i-1);
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isotonic_regression mr;
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mr(vect);
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dlog << LINFO << "err: "<< objval(mat(vect)) - objval(result.x);
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DLIB_CASSERT(is_monotonic(mat(vect)));
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DLIB_CASSERT(is_monotonic(result.x));
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// isotonic_regression should be at least as good as find_min_global().
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DLIB_CASSERT(objval(mat(vect)) - objval(result.x) < 1e-13);
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}
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}
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} a;
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}
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