switch

KDEy/experiments.py

@@ -1,4 +1,5 @@
 import os
+import pickle
 
 import numpy as np
 from sklearn.linear_model import LogisticRegression
@@ -67,6 +68,10 @@ def plot_bandwidth(val_choice, test_results):
 
         bandwidths, results = zip(*test_results[dataset_name])
 
+        print(dataset_name)
+        print(bandwidths)
+        print(results)
+
         # Crear la gráfica
         plt.figure(figsize=(8, 6))
 
@@ -74,12 +79,12 @@ def plot_bandwidth(val_choice, test_results):
         plt.plot(bandwidths, results, marker='o')
 
         # Agregar la línea vertical en bandwidth_chosen
-        plt.axvline(x=val_choice[dataset_name], color='r', linestyle='--', label=f'Bandwidth elegido: {val_choice[dataset_name]}')
+        plt.axvline(x=val_choice[dataset_name], color='r', linestyle='--', label=f'bandwidth mod-sel: {val_choice[dataset_name]}')
 
         # Agregar etiquetas y título
         plt.xlabel('Bandwidth')
-        plt.ylabel('Resultado')
-        plt.title('Gráfica de Bandwidth vs Resultado')
+        plt.ylabel('MAE')
+        plt.title('bandwidth vs score')
 
         # Mostrar la leyenda
         plt.legend()
@@ -89,16 +94,25 @@ def plot_bandwidth(val_choice, test_results):
         # plt.show()
         os.makedirs('./plots', exist_ok=True)
         plt.savefig(f'./plots/{dataset_name}.png')
+        plt.close()
 
 
 
 for dataset in datasets():
+    print('NAME', dataset.name)
+    print(len(dataset.training))
+    print(len(dataset.test))
+
     if DEBUG:
         result_path = f'./results/debug/{dataset.name}.pkl'
     else:
         result_path = f'./results/{dataset.name}.pkl'
 
-    modsel_choice, dataset_results = qp.util.pickled_resource(result_path, experiment_dataset, dataset)
+    #modsel_choice, dataset_results = qp.util.pickled_resource(result_path, experiment_dataset, dataset)
+    if os.path.exists(result_path):
+        modsel_choice, dataset_results = pickle.load(open(result_path, 'rb'))
+    else:
+        continue
     val_choice[dataset.name] = modsel_choice
     test_results[dataset.name] = dataset_results