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plot.py
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plot.py
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import csv
from matplotlib import pyplot as plt
results_path = './saved_models/'
def plot_results(file_path=results_path):
epochs, results_dic = getAllResults(file_path, model_types=['combined','perceptron'])
xaxis = range(1, epochs + 2)
ymin = 0
ymax = 1
fig1 = plt.figure(1)
plt.subplot(2, 1, 1)
plt.gca().set_title('Training')
plt.ylabel('Loss')
plt.plot(xaxis, results_dic['combined']['train_loss'], 'ro-', label='SRN')
plt.plot(xaxis, results_dic['perceptron']['train_loss'], 'go-', label='no Perceptron layer', color='DarkBlue')
ax = plt.subplot(2, 1, 2)
plt.gca().set_ylim([ymin, ymax])
plt.xlabel('Epochs')
plt.ylabel('Accuracy')
plt.plot(xaxis, results_dic['combined']['train_acc'], 'ro-', label='SRN')
plt.plot(xaxis, results_dic['perceptron']['train_acc'], 'go-', label='no Perceptron layer', color='DarkBlue')
handles, labels = ax.get_legend_handles_labels()
fig1.legend(handles, labels, loc='upper right')
fig1.suptitle("Ablation Study of PQ-3H")
fig1.tight_layout()
fig1.subplots_adjust(top=0.85)
fig2 = plt.figure(2)
plt.subplot(2, 1, 1)
plt.gca().set_title('Validation')
plt.ylabel('Loss')
plt.plot(xaxis, results_dic['combined']['val_loss'], 'ro-', label='SRN')
plt.plot(xaxis, results_dic['perceptron']['val_loss'], 'go-', label='no Perceptron layer', color='DarkBlue')
ax = plt.subplot(2, 1, 2)
plt.gca().set_ylim([ymin, ymax])
plt.xlabel('Epochs')
plt.ylabel('Accuracy')
plt.plot(xaxis, results_dic['combined']['val_acc'], 'ro-', label='SRN')
plt.plot(xaxis, results_dic['perceptron']['val_acc'], 'go-', label='no Perceptron layer', color='DarkBlue')
handles, labels = ax.get_legend_handles_labels()
fig2.legend(handles, labels, loc='upper right')
fig2.suptitle("Ablation Study of PQ-3H")
fig2.tight_layout()
fig2.subplots_adjust(top=0.85)
plt.show()
def getAllResults(file_path, model_types):
all_results_dic = {}
epochs = 0
for model_type in model_types:
file_name = model_type + '_results.csv'
try:
with open(file_path + file_name) as data_file:
reader = csv.reader(data_file, delimiter=',')
final_row = ''
for row in reader:
final_row = row
except FileNotFoundError:
print('Can\'t find {} results file!'.format(model_type))
continue
all_results_dic[model_type] = parseResults(final_row[1:])
epochs = max(epochs, int(final_row[0].strip()[-1]))
return epochs, all_results_dic
def parseResults(results):
results_dic = {}
result_names = iter(['train_acc','train_loss','val_acc','val_loss'])
name = next(result_names)
values = []
for result in results:
try:
result = result.strip()
if result[-1] == ']':
values.append(float(result[:-1]))
results_dic[name] = values
name = next(result_names)
values = []
elif result[0] == '[':
values.append(float(result[1:]))
else:
values.append(float(result))
except StopIteration:
break
return results_dic
if __name__ == '__main__':
plot_results()