Test

app.py

@@ -564,8 +564,13 @@ def compute_global_regression(df_combined, embedding_cols, tsne_params, df_f1, r
                          perplexity=tsne_params["perplexity"], 
                          learning_rate=tsne_params["learning_rate"])
     
-    # reduced = reducer.fit_transform(df_combined[embedding_cols].values)
-    reduced = reducer.fit_transform(df_combined[df_combined["version"] == "real"][embedding_cols].values)
+    reduced = reducer.fit_transform(df_combined[embedding_cols].values)
+    # reduced = reducer.fit_transform(df_combined[df_combined["version"] == "real"][embedding_cols].values)
+
+    real_mask = df_combined["version"] == "real"
+    reduced_real = reducer.fit_transform(df_combined[real_mask][embedding_cols].values)
+    reduced[real_mask.values] = reduced_real
+    
     # Guardamos el embedding completo (por ejemplo, 4 dimensiones en PCA)
     df_combined['embedding'] = list(reduced)
     # Si el embedding es 2D, asignamos x e y para visualización