def get_zeta_i_j(self, X):
		'''
		Parameters
		----------
		X : np.array
			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
			positive class, while X[:,1] is the negative class. None by default

		Returns
		-------
		np.array of z-scores
		'''
		y_i, y_j = X.T[0], X.T[1]
		return self.get_zeta_i_j_given_separate_counts(y_i, y_j)

		Parameters
		----------
		X : np.array
			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
			positive class, while X[:,1] is the negative class. None by default

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