1 files changed, 103 insertions, 0 deletions
diff --git a/ml/dlib/dlib/test/isotonic_regression.cpp b/ml/dlib/dlib/test/isotonic_regression.cpp
new file mode 100644
index 000000000..2ab46903c
--- /dev/null
+++ b/ml/dlib/dlib/test/isotonic_regression.cpp
@@ -0,0 +1,103 @@
+// 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;
+
+}
+
+
+