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visualizations.py
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visualizations.py
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import matplotlib.pyplot as plt
import numpy as np
def plot_accuracy(history):
# Accuracy plot
plt.plot(history.history['accuracy'])
plt.plot(history.history['val_accuracy'])
plt.yticks(np.arange(0.5, 1, 0.02))
plt.grid(which='major', linestyle=':', alpha=0.6)
plt.ylim([0.7, 1])
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(['train', 'val'], loc='upper left')
plt.show()
def plot_loss(history):
plt.plot(history.history['loss'])
plt.plot(history.history['val_loss'])
plt.title('model loss')
plt.ylabel('loss')
plt.xlabel('epoch')
plt.legend(['train', 'val'], loc='upper left')
plt.show()
def plot_accuracies(histories, networks):
"""This function receives list of training accuracy histories, and a list of network, such that histories[i]
contains the accuracy obtained by training network[i]. Hence, histories and networks are lists with the same
length."""
for i in range(len(histories)):
plt.plot(histories[i])
plt.yticks(np.arange(0.5, 1, 0.02))
plt.grid(which='major', linestyle=':', alpha=0.6)
plt.ylim([0.7, 1])
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(networks, loc='lower right')
plt.show()