1 // Copyright (C) 2018 Davis E. King (davis@dlib.net) 2 // License: Boost Software License See LICENSE.txt for the full license. 3 4 5 #include <dlib/optimization.h> 6 #include <dlib/global_optimization.h> 7 #include <sstream> 8 #include <string> 9 #include <cstdlib> 10 #include <ctime> 11 #include <vector> 12 13 #include "tester.h" 14 15 16 namespace 17 { 18 19 using namespace test; 20 using namespace dlib; 21 using namespace std; 22 23 logger dlog("test.isotonic_regression"); 24 25 // ---------------------------------------------------------------------------------------- 26 27 class optimization_tester : public tester 28 { 29 public: optimization_tester()30 optimization_tester ( 31 ) : 32 tester ("test_isotonic_regression", 33 "Runs tests on the isotonic_regression object.") 34 {} 35 perform_test()36 void perform_test ( 37 ) 38 { 39 dlib::rand rnd; 40 41 for (int round = 0; round < 100; ++round) 42 { 43 print_spinner(); 44 std::vector<double> vect; 45 for (int i = 0; i < 5; ++i) 46 vect.push_back(put_in_range(-1,1,rnd.get_random_gaussian())); 47 48 49 auto f = [&](const matrix<double,0,1>& x) 50 { 51 double dist = 0; 52 double sum = 0; 53 for (long i = 0; i < x.size(); ++i) 54 { 55 sum += x(i); 56 dist += (sum-vect[i])*(sum-vect[i]); 57 } 58 return dist; 59 }; 60 61 auto objval = [vect](const matrix<double,0,1>& x) 62 { 63 return sum(squared(mat(vect)-x)); 64 }; 65 66 auto is_monotonic = [](const matrix<double,0,1>& x) 67 { 68 for (long i = 1; i < x.size(); ++i) 69 { 70 if (x(i-1) > x(i)) 71 return false; 72 } 73 return true; 74 }; 75 76 matrix<double,0,1> lower(5), upper(5); 77 lower = 0; 78 lower(0) = -4; 79 upper = 4; 80 // find the solution with find_min_global() and then check that it matches 81 auto result = find_min_global(f, lower, upper, max_function_calls(40)); 82 83 for (long i = 1; i < result.x.size(); ++i) 84 result.x(i) += result.x(i-1); 85 86 isotonic_regression mr; 87 mr(vect); 88 89 dlog << LINFO << "err: "<< objval(mat(vect)) - objval(result.x); 90 91 DLIB_CASSERT(is_monotonic(mat(vect))); 92 DLIB_CASSERT(is_monotonic(result.x)); 93 // isotonic_regression should be at least as good as find_min_global(). 94 DLIB_CASSERT(objval(mat(vect)) - objval(result.x) < 1e-13); 95 } 96 97 } 98 } a; 99 100 } 101 102 103 104