dlib C++ Library - isotonic_regression.cpp

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