Пример #1
0
 def setMoodScore(self, MoodScore):
     if (MoodScore >= 0 and MoodScore < len(mood_tools.getEmotions())):
         self.MoodScore = MoodScore
         self.save()
         return True
     else:
         return False
Пример #2
0
 def setMood(self, mood_int):
     if not (isinstance(mood_int, type(2))):
         return False
     if mood_int >= 0 and mood_int < len(mood_tools.getEmotions()):
         self.mood = mood_int
         self.save()
         return True
     else:
         return False
Пример #3
0
 def __init__(self, weights=None, biases=None):
     self._emotions = getEmotions()
     self.nclasses = len(self._emotions)
     # Weights
     if weights:
         if len(weights) != 208:
             raise ValueError("There must be 208 weights for the model")
         self.setWeights(weights)
     else:
         self.setWeights("static/base_weights.json", True)
     # biases
     if biases:
         if len(biases) != 21:
             raise ValueError("Number of biases must be 21")
         self.setBias(biases)
     else:
         self.setBias("static/base_biases.json", True)
     # network
     if len(self._network) == 0:
         for i in range(4):
             self._network.append([])
         weightCounter = 0
         biasCounter = 0
         for i in range(11):
             self._network[0].append({
                 'weights':
                 np.arange(weightCounter, weightCounter + 11, 1)
             })
             weightCounter += 11
             self._network[0][i]['bias'] = i
             biasCounter += 1
         for i in range(6):
             self._network[1].append({
                 'weights':
                 np.arange(weightCounter, weightCounter + 11, 1)
             })
             weightCounter += 11
             self._network[1][i]['bias'] = i
             biasCounter += 1
         for i in range(3):
             self._network[2].append({
                 'weights':
                 np.arange(weightCounter, weightCounter + 6, 1)
             })
             weightCounter += 6
             self._network[2][i]['bias'] = i
             biasCounter += 1
         self._network[3].append(
             {'weights': np.arange(weightCounter, weightCounter + 3, 1)})
         self._network[3][0]['bias'] = biasCounter
Пример #4
0
 def updateReminders(self, MoodScore):
     #mood_int can be either the predicted mood or actual mood to get reminder
     moods = mood_tools.getEmotions()
     try:
         mood_str = moods[MoodScore]
         allReminders = mood_tools.getReminders()
         newReminders = allReminders[mood_str]
     except:
         return False
     currentReminders = self.reminderList.split(';')
     nonRepeated = []
     for i in newReminders:
         try:
             currentReminders.index(i)
         except:
             nonRepeated.append(i)
     currentReminders.extend(nonRepeated)
     self.reminderList = ";".join(currentReminders)
     self.save()
     return True
Пример #5
0
 def test_getEmotions(self):
     emotions = getEmotions()
     model1 = MoodNeuralNetwork()
     emotions2 = model1.getEmotions()
     self.assertEqual(emotions, emotions2)
     self.assertTrue(model1.getEmotions())
Пример #6
0
 def getMoodToday(self, MoodScore):
     try:
         mood = mood_tools.getEmotions()[MoodScore]
         return mood
     except:
         return False