user.py
def update_profile(self, vec, predict=True):
		"""
		Update the profile of the user with the new vec param
		:param vec: (np.array) vector of the tweet to add
		:param predict: (boolean) whether to predict localisation, gender, etc or not
		:return:
		"""
		self.nb_click += 1
		for i in range(len(self.vec)):
			self.vec[i] = (self.vec[i] * (self.nb_click - 1)) / self.nb_click + (vec[i] / self.nb_click)

		if predict:
			self.predict_profile()

		Update the profile of the user with the new vec param
		:param vec: (np.array) vector of the tweet to add
		:param predict: (boolean) whether to predict localisation, gender, etc or not
		:return:
		
Update the profile of the user with the new vec param
Update the profile of the user with the new vec param
def update_profile(self, vec, predict=True):
		self.nb_click += 1
		for i in range(len(self.vec)):
			self.vec[i] = (self.vec[i] * (self.nb_click - 1)) / self.nb_click + (vec[i] / self.nb_click)
		if predict:
			self.predict_profile()
def update_profile ( self , vec , predict = True ) : self . nb_click += 1 for i in range ( len ( self . vec ) ) : self . vec [ i ] = ( self . vec [ i ] * ( self . nb_click - 1 ) ) / self . nb_click + ( vec [ i ] / self . nb_click ) if predict : self . predict_profile ( )
Update the profile of the user with the new vec param
Update the profile of the user with the new vec param
"""
		Update the profile of the user with the new vec param
		:param vec: (np.array) vector of the tweet to add
		:param predict: (boolean) whether to predict localisation, gender, etc or not
		:return:
		"""
None
self
vec
(np.array) vector of the tweet to add
( np . array ) vector of the tweet to add
predict
(boolean) whether to predict localisation, gender, etc or not
( boolean ) whether to predict localisation gender etc or not