ium_470607/lab5/eval/eval.py

import csv
import matplotlib.pyplot as plt
import pandas as pd
from tensorflow.keras.models import load_model


X_test = pd.read_csv('test.csv')

Y_test = X_test.pop('stabf')
Y_test = pd.get_dummies(Y_test)

model = load_model('grid-stability-dense.h5')

results = model.evaluate(X_test, Y_test, batch_size=64)

with open('eval.csv', 'a', newline='') as fp:
    wr = csv.writer(fp, dialect='excel')
    wr.writerow(results)

metrics = pd.read_csv('eval.csv', header=None, names=['loss', 'accuracy'])

fig = plt.figure()
plt.plot(metrics.accuracy)
plt.ylabel('Accuracy')
plt.xlabel('Build no.')

fig.savefig('plot.png')