unbounded

lytex · Sep 4, 2024 · 9cf2ffd · 9cf2ffd
1 parent f23db61
commit 9cf2ffd
Showing 1 changed file with 16 additions and 16 deletions.
diff --git a/new_train.py b/new_train.py
@@ -516,25 +516,25 @@ def main(sigma = 20, sigma_upper = 5,
 
         lightcurves = [lc for lc in lightcurves if lc is not None]
 
-        model_1_lazy = lambda : get_model_wrapper(lightcurves, use_wavelet=use_wavelet, binary_classification=binary_classification, frac=frac,  test_size=test_size,
-                                             global_level_list=global_level_list, local_level_list=local_level_list,
-                                            l1=l1, l2=l2, dropout=dropout,
-                                            num_bins_global=num_bins_global,
-                                            num_bins_local=num_bins_local)
+    model_1_lazy = lambda : get_model_wrapper(lightcurves, use_wavelet=use_wavelet, binary_classification=binary_classification, frac=frac,  test_size=test_size,
+                                         global_level_list=global_level_list, local_level_list=local_level_list,
+                                        l1=l1, l2=l2, dropout=dropout,
+                                        num_bins_global=num_bins_global,
+                                        num_bins_local=num_bins_local)
+
+    if k_fold is None:
+        model_1, history_1, num2class, X_val, y_val, X_test, y_test, recall_val = train_model(model_1_lazy, lightcurves,
+                                                           use_wavelet=use_wavelet, binary_classification=binary_classification,
+                                                           k_fold=k_fold, global_level_list=global_level_list, local_level_list=local_level_list, epochs=epochs, batch_size=batch_size, test_size=test_size)
 
-        if k_fold is None:
-            model_1, history_1, num2class, X_val, y_val, X_test, y_test, recall_val = train_model(model_1_lazy, lightcurves,
-                                                               use_wavelet=use_wavelet, binary_classification=binary_classification,
-                                                               k_fold=k_fold, global_level_list=global_level_list, local_level_list=local_level_list, epochs=epochs, batch_size=batch_size, test_size=test_size)
 
-
-            precision_val, recall_val, F1_val, Fβ_val, auc_val, cm_val, num2class = get_metrics(num2class, X_val, y_val, model_1, β=β, binary_classification=binary_classification, plot=True)
-        else:
-            # TODO añadir en el caso de k-fold
-            precision_val, recall_val, F1_val, Fβ_val, auc_val, cm_val, num2class = get_metrics(num2class, X_val, y_val, model_1, β=β, binary_classification=binary_classification, plot=True)
+        precision_val, recall_val, F1_val, Fβ_val, auc_val, cm_val, num2class = get_metrics(num2class, X_val, y_val, model_1, β=β, binary_classification=binary_classification, plot=True)
+    else:
+        # TODO añadir en el caso de k-fold
+        precision_val, recall_val, F1_val, Fβ_val, auc_val, cm_val, num2class = get_metrics(num2class, X_val, y_val, model_1, β=β, binary_classification=binary_classification, plot=True)
+
+    precision, recall, F1, Fβ, auc, cm, num2class = get_metrics(num2class, X_test, y_test, model_1, β=β, binary_classification=binary_classification, plot=True)
 
-        precision, recall, F1, Fβ, auc, cm, num2class = get_metrics(num2class, X_test, y_test, model_1, β=β, binary_classification=binary_classification, plot=True)
-
 
 
     if apply_candidates: