def test_setEmotions(self):
emotions = ['Love', 'Sad', 'Hesitant', 'Calm', 'Happy']
model1 = MoodNeuralNetwork()
emotions2 = model1.getEmotions()
self.assertNotEqual(emotions, emotions2)
self.assertTrue(model1.setEmotions(emotions))
self.assertEqual(emotions, model1.getEmotions())
def test_getEmotions(self):
emotions = getEmotions()
model1 = MoodNeuralNetwork()
emotions2 = model1.getEmotions()
self.assertEqual(emotions, emotions2)
self.assertTrue(model1.getEmotions())
import json
from mood_model.mood_neural_network import MoodNeuralNetwork
baseModel = MoodNeuralNetwork()
emotions = baseModel.getEmotions()
emotion_map = {}
for i in range(len(emotions)):
emotion_map[emotions[i]] = i
with open('notifications.txt',
'r') as file: # Use file to refer to the file object
data = file.read().splitlines()
print(data)
reminders = {}
curr = ""
for i in range(len(data)):
if data[i] in emotion_map:
reminders[data[i]] = []
curr = data[i]
else:
reminders[curr].append(data[i])
print(reminders)
print(reminders['Sad'])
with open('notifications.json', 'w') as fp:
json.dump(reminders, fp)