chart_gen.py

import os
import matplotlib.pyplot as plt

def plot_and_save(history, name, show_plots=False, folder="imgs"):
	"""
	 Create a charts comparing accuracy and loss of training and validation 
	 phases for each epoch 

	 Args:
	     history (Hisotry): The History object returned from a fit function
		 name (str): Prefix name for the created images
		 show_plots (bool): Plot charts when True, otherwise just save on disk
		 folder (str): Local folder name to save created images. If doesn't 
		 	exists, it will be created

	 Returns:
	     str[]: Names of created images

	 Raises:
 		None: This function don't raise any exception

	 """

	plt.switch_backend('agg')
	os.makedirs(folder, exist_ok=True)

	# summarize history for accuracy
	fig, ax = plt.subplots()
	plt.plot(history.history['acc'])

	if 'val_acc' in history.history:
		plt.plot(history.history['val_acc'])
		plt.legend(['train', 'test'])
	else:
		plt.legend(['train'])

	plt.title('model accuracy')
	plt.ylabel('accuracy')
	plt.xlabel('epoch')


	if show_plots:
		plt.show()

	# summarize history for loss
	fig2, ax2 = plt.subplots()
	plt.plot(history.history['loss'])

	if 'val_acc' in history.history:
		plt.plot(history.history['val_loss'])
		plt.legend(['train', 'test'])
	else:
		plt.legend(['train'])

	plt.title('model loss')
	plt.ylabel('loss')
	plt.xlabel('epoch')

	if show_plots:
		plt.show()

	fig.savefig(os.path.join(folder, name[:-3]+"_acc.jpg"))
	fig2.savefig(os.path.join(folder, name[:-3]+"_loss.jpg")

	return name[:-3]+"_acc.jpg", name[:-3]+"_loss.jpg"