def get_zeta_i_j_given_separate_counts(self, y_i, y_j):
		'''
		Parameters
		----------
		y_i, np.array(int)
			Arrays of word counts of words occurring in positive class
		y_j, np.array(int)

		Returns
		-------
		np.array of z-scores
		'''
		yp_i = y_i + self.alpha_w
		yp_j = y_j + self.alpha_w
		np_i = np.sum(yp_i)
		np_j = np.sum(yp_j)

		delta_i_j = np.log(yp_i / (np_i - yp_i)) - np.log(yp_j / (np_j - yp_j))
		var_delta_i_j = (1. / (yp_i)
		                 + 1. / (np_i - yp_i)
		                 + 1. / (yp_j)
		                 + 1. / (np_j - yp_j))
		zeta_i_j = delta_i_j / np.sqrt(var_delta_i_j)
		return zeta_i_j

		Parameters
		----------
		y_i, np.array(int)
			Arrays of word counts of words occurring in positive class
		y_j, np.array(int)

		Returns
		-------
		np.array of z-scores
		
scattertext/termsignificance/LogOddsRatioUninformativeDirichletPrior.py