- added image module with sub image and normalize

- improved tests

src/tests/test_linear.py

@@ -1,6 +1,7 @@
 from rbm.matrix import Mat, np
 from rbm.entity import Entity, EntityParams, TrainingParams
 from rbm.model import Model
+from rbm.image import normalize
 
 WORK_DIR = "../../results"
 USE_OPTIMIZER = True
@@ -45,12 +46,10 @@ def linear():
 	training_batch = np.random.randn(N_CASES, N_VIS, dtype=np.float64)
 
 	# Normalize training data
-	mean_training_batch = np.reshape(np.repeat(np.mean(training_batch, axis=1), N_VIS, axis=0), training_batch.shape)
-	var_training_batch = np.reshape(np.repeat(np.std(training_batch, axis=1), N_VIS, axis=0), training_batch.shape)
-	training_batch = (training_batch - mean_training_batch) / var_training_batch
+	training_batch_norm = normalize(training_batch)
 
 	# Train layer
-	model.train(training_batch)
+	model.train(training_batch_norm)
 
 	# Save weights
 	model.save()