Más tests

test/test_discriminador.py

@@ -1,5 +1,6 @@
 import unittest
-import numpy as np
+from unittest.mock import patch
+from io import StringIO
 from keras.datasets import cifar100
 from src.gan.discriminador import Discriminator
 from src.prueba.entrenamiento import Training
@@ -10,6 +11,7 @@ def setUp(self):
         self.input_shape = (32, 32, 3)
         self.discriminador = Discriminator(self.input_shape)
         self.dataset = Training.load_images(cifar100)
+        self.stdout = StringIO()
 
     def test_model_structure(self):
         model = self.discriminador.model
@@ -31,6 +33,23 @@ def test_fake_training(self):
         loss, accuracy = self.discriminador.evaluate(dataset, labels)
         self.assertTrue(accuracy > initial_accuracy)
 
+    def test_build_model(self):
+        model = self.discriminador.build_model()
+        self.assertIsNotNone(model)
+
+    def test_summary(self):
+        with patch("sys.stdout", self.stdout):
+            self.discriminador.summary()
+            printed_output = self.stdout.getvalue().strip()
+
+        self.assertNotEqual(printed_output, "")
+
+    def test_evaluate(self):
+        dataset, labels = Training.load_real_data(self.dataset, 100)
+        result = self.discriminador.evaluate(dataset, labels)
+        self.assertIsInstance(result, list)
+        self.assertEqual(len(result), 2)
 
-if __name__ == "__main__":
-    unittest.main()
+    def test_trainable(self):
+        trainable = self.discriminador.trainable
+        self.assertIsNotNone(trainable)

test/test_gan.py

@@ -13,7 +13,3 @@ def setUp(self):
     def test_gan_structure(self):
         model = self.gan
         self.assertIsNotNone(model)
-
-
-if __name__ == "__main__":
-    unittest.main()

test/test_generador.py

@@ -1,13 +1,15 @@
 import unittest
+from unittest.mock import patch
 import numpy as np
 from src.gan.generador import Generator
-
+from io import StringIO
 
 class TestGenerador(unittest.TestCase):
     def setUp(self):
         self.latent_dim = 100
         self.output_shape = (32, 32, 3)
         self.gen = Generator(self.latent_dim, self.output_shape)
+        self.stdout = StringIO()
 
     def test_model_structure(self):
         model = self.gen.model
@@ -31,6 +33,9 @@ def test_generalization(self):
         # Verifica la calidad de las imágenes generadas y su similitud con las imágenes reales
         return None
 
+    def test_summary(self):
+        with patch('sys.stdout', self.stdout):
+            self.gen.summary()
+            printed_output = self.stdout.getvalue().strip()
 
-if __name__ == "__main__":
-    unittest.main()
+        self.assertNotEqual(printed_output, "")

test/test_servidor.py

@@ -38,7 +38,3 @@ def test_client_handler(self, mock_handler):
 
         mock_handler.assert_called_once_with(mock_client_socket)
         mock_handler.return_value.handle.assert_called_once()
-
-
-if __name__ == "__main__":
-    unittest.main()