FIX: Output rewritten properly using macros from message.h.

src/LearningMethods/GradientDescent.cpp

@@ -6,6 +6,7 @@
  */
 
 #include "GradientDescent.h"
+#include "message.h"
 
 namespace lib4neuro {
     GradientDescent::GradientDescent(double epsilon, size_t n_to_restart, int max_iters, size_t batch) {
@@ -49,10 +50,8 @@ namespace lib4neuro {
                     ef.get_dataset()->get_normalization_strategy());
         }
 
-        std::cout << "Finding a solution via a Gradient Descent method with adaptive step-length" << std::endl;
-        std::cout
-                << "********************************************************************************************************************************************"
-                << std::endl;
+        COUT_INFO("Finding a solution via a Gradient Descent method with adaptive step-length..." << std::endl);
+
         double grad_norm = this->tolerance * 10.0, gamma, sx, beta;
         double grad_norm_prev;
         size_t i;
@@ -131,16 +130,18 @@ namespace lib4neuro {
             params_current = ptr_mem;
 
             val = ef.eval(params_current);
-            if (iter_counter % 1 == 0) {
-                printf("Iteration %12d. Step size: %15.8f, C: %15.8f, Gradient norm: %15.8f. Total error: %10.8f\r",
-                       (int) iter_counter, gamma, c, grad_norm, val);
-                std::cout.flush();
-            }
+
+            COUT_DEBUG(std::string("Iteration: ") << (unsigned int)(iter_counter)
+                       << ". Step size: " << gamma
+                       << ". C: " << c
+                       << ". Gradient norm: " << grad_norm
+                       << ". Total error: " << val
+                       << "." << std::endl);
         }
-        printf("Iteration %12d. Step size: %15.8f, C: %15.8f, Gradient norm: %15.8f. Total error: %10.8f\n",
-               (int) iter_counter, gamma, c, grad_norm, val);
-        std::cout.flush();
 
+        if(iter_idx == 0) {
+            COUT_INFO("Maximum number of iterations (" << this->maximum_niters << ") was reached!" << std::endl);
+        }
 
         *this->optimal_parameters = *params_current;