dtrain: output data

1 files changed, 18 insertions, 13 deletions

diff --git a/training/dtrain/dtrain.cc b/training/dtrain/dtrain.cc
index ddd27211..3e9902ab 100644
--- a/training/dtrain/dtrain.cc
+++ b/training/dtrain/dtrain.cc
@@ -143,10 +143,15 @@ main(int argc, char** argv)
   time_t total_time = 0.;
 
   // output
-  WriteFile raw_out;
-  if (output_raw) raw_out.Init(output_raw_fn);
-  WriteFile updates_out;
-  if (output_updates) updates_out.Init(output_raw_fn);
+  WriteFile out_up, out_raw;
+  if (output_raw) {
+    out_raw.Init(output_raw_fn);
+    *out_raw << setprecision(numeric_limits<double>::digits10+1);
+  }
+  if (output_updates) {
+    out_up.Init(output_updates_fn);
+    *out_up << setprecision(numeric_limits<double>::digits10+1);
+  }
 
 
   for (size_t t = 0; t < T; t++) // T iterations
@@ -220,25 +225,25 @@ main(int argc, char** argv)
     list_sz += observer->effective_size;
 
     if (output_raw)
-      output_sample(sample);
+      output_sample(sample, *out_raw, i);
 
     // update model
     if (!noup) {
 
     SparseVector<weight_t> updates;
     if (structured)
-      num_up += update_structured(sample, updates, margin/*,
-                                  output_updates, updates_out.get()*/); // FIXME
+      num_up += update_structured(sample, updates, margin,
+                                  output_updates, *out_up, i);
     else if (all_pairs)
-      num_up += updates_all(sample, updates, max_up, threshold/*,
-                            output_updates, updates_out.get()*/); // FIXME
+      num_up += updates_all(sample, updates, max_up, threshold,
+                            output_updates, *out_up, i);
     else if (pro)
-      num_up += updates_pro(sample, updates, cut, max_up, threshold/*,
-                            output_updates, updates_out.get()*/); // FIXME
+      num_up += updates_pro(sample, updates, cut, max_up, threshold,
+                            output_updates, *out_up, i);
     else
       num_up += updates_multipartite(sample, updates, cut, margin,
-                                       max_up, threshold, adjust_cut/*,
-                                       output_updates, updates_out.get()*/); // FIXME
+                                     max_up, threshold, adjust_cut,
+                                     output_updates, *out_up, i);
     SparseVector<weight_t> lambdas_copy;
     if (l1_reg)
       lambdas_copy = lambdas;