# DeepMusic v1.0
# Inspired from Keras code from Francois Chollet
# Jean-Pierre Briot
# 15/04/2019
# Metrics

import matplotlib.pyplot as plt

import config

def keras_verbose():
	if config.deep_music_training_verbose:
		return(2)
	else:
		return(-1)

def show_metrics(model, history, X_train, y_train, X_test, y_test):
	train_loss_and_metrics = model.evaluate(X_train, y_train, verbose=2)
	test_loss_and_metrics = model.evaluate(X_test, y_test, verbose=2)
	print("Train Loss", train_loss_and_metrics[0])
	print("Train Accuracy", train_loss_and_metrics[1])
	print("Test Loss", test_loss_and_metrics[0])
	print("Test Accuracy", test_loss_and_metrics[1])
	plt.plot(history.history['acc'])
	plt.plot(history.history['val_acc'])
	plt.title('model accuracy')
	plt.ylabel('accuracy')
	plt.xlabel('epoch')
	plt.legend(['train', 'test'], loc='upper left')
	plt.show()
	plt.plot(history.history['loss'])
	plt.plot(history.history['val_loss'])
	plt.title('model loss')
	plt.ylabel('loss')
	plt.xlabel('epoch')
	plt.legend(['train', 'test'], loc='upper left')
	plt.show()