Minor tweak

dlib/global_optimization/find_max_global.h

@@ -138,7 +138,7 @@ template <typename T> static auto go(T&& f, const matrix<double, 0, 1>& a) -> de
             {
                 for (long j = 0; j < specs[i].lower.size(); ++j)
                 {
-                    if (!specs[i].is_integer_variable[j] && specs[i].lower(j) > 0 && specs[i].upper(j)/specs[i].lower(j) > 1000)
+                    if (!specs[i].is_integer_variable[j] && specs[i].lower(j) > 0 && specs[i].upper(j)/specs[i].lower(j) >= 1000)
                     {
                         log_scale[i].push_back(true);
                         specs[i].lower(j) = std::log(specs[i].lower(j));

dlib/global_optimization/find_max_global_abstract.h

@@ -124,7 +124,7 @@ namespace dlib
                 - More than max_runtime time has elapsed since the start of this function.
             - Any variables that satisfy the following conditions are optimized on a log-scale:
                 - The lower bound on the variable is > 0
-                - The ratio of the upper bound to lower bound is > 1000
+                - The ratio of the upper bound to lower bound is >= 1000
                 - The variable is not an integer variable
               We do this because it's common to optimize machine learning models that have
               parameters with bounds in a range such as [1e-5 to 1e10] (e.g. the SVM C
@@ -207,7 +207,7 @@ namespace dlib
                 - More than max_runtime time has elapsed since the start of this function.
             - Any variables that satisfy the following conditions are optimized on a log-scale:
                 - The lower bound on the variable is > 0
-                - The ratio of the upper bound to lower bound is > 1000
+                - The ratio of the upper bound to lower bound is >= 1000
                 - The variable is not an integer variable
               We do this because it's common to optimize machine learning models that have
               parameters with bounds in a range such as [1e-5 to 1e10] (e.g. the SVM C