def __init__(self,
	             term_doc_matrix,
	             category_a_list,
	             category_b_list,
	             not_category_a_list,
	             not_category_b_list,
	             labels=None,
	             term_ranker=AbsoluteFrequencyRanker,
	             scorer=None):
		'''
		Parameters
		----------
		term_doc_matrix : TermDocMatrix
			TermDocMatrix (or descendant) which will be used in constructing square.
		category_a_list : list
			Category names for term A
		category_b_list : list
			Category names for term B (in opposition to A)
		not_category_a_list : list
			List of category names that belong to not A
		not_category_b_list : list
			List of category names that belong to not A
		labels : dict
			None by default. Labels are dictionary of {'a_and_b': 'A and B', ...} to be shown
			above each category.
		term_ranker : TermRanker
			Class for returning a term-frequency convention_df
		scorer : termscoring class, optional
			Term scoring class for lexicon mining. Default: `scattertext.termscoring.ScaledFScore`
		'''

		self.category_a_list_ = category_a_list
		self.category_b_list_ = category_b_list
		self.not_category_a_list_ = not_category_a_list
		self.not_category_b_list_ = not_category_b_list
		assert (set(self._get_all_categories()) & set(term_doc_matrix.get_categories())
		        == set(self._get_all_categories()))
		self._build_square(term_doc_matrix, term_ranker, labels, scorer)
def __init__ ( self , term_doc_matrix , category_a_list , category_b_list , not_category_a_list , not_category_b_list , labels = None , term_ranker = AbsoluteFrequencyRanker , scorer = None ) : self . category_a_list_ = category_a_list self . category_b_list_ = category_b_list self . not_category_a_list_ = not_category_a_list self . not_category_b_list_ = not_category_b_list assert ( set ( self . _get_all_categories ( ) ) & set ( term_doc_matrix . get_categories ( ) ) == set ( self . _get_all_categories ( ) ) ) self . _build_square ( term_doc_matrix , term_ranker , labels , scorer )
Parameters
		----------
		term_doc_matrix : TermDocMatrix
			TermDocMatrix (or descendant) which will be used in constructing square.
		category_a_list : list
			Category names for term A
		category_b_list : list
			Category names for term B (in opposition to A)
		not_category_a_list : list
			List of category names that belong to not A
		not_category_b_list : list
			List of category names that belong to not A
		labels : dict
			None by default. Labels are dictionary of {'a_and_b': 'A and B', ...} to be shown
			above each category.
		term_ranker : TermRanker
			Class for returning a term-frequency convention_df
		scorer : termscoring class, optional
			Term scoring class for lexicon mining. Default: `scattertext.termscoring.ScaledFScore`