sklearn_utils/preprocessing/functional_enrichment_analysis.py
def _filtered_values(self, x: dict, feature_set: list=None):
        '''
        :x: dict which contains feature names and values
        :return: pairs of values which shows number of feature makes filter function true or false
        '''
        feature_set = feature_set or x
        n = sum(self.filter_func(x[i]) for i in feature_set if i in x)
        return [len(feature_set) - n, n]
def _filtered_values(self, x: dict, feature_set: list=None):
        '''
        :x: dict which contains feature names and values
        :return: pairs of values which shows number of feature makes filter function true or false
        '''
        feature_set = feature_set or x
        n = sum(self.filter_func(x[i]) for i in feature_set if i in x)
        return [len(feature_set) - n, n]
def _filtered_values ( self , x : dict , feature_set : list = None ) : feature_set = feature_set or x n = sum ( self . filter_func ( x [ i ] ) for i in feature_set if i in x ) return [ len ( feature_set ) - n , n ]
:x: dict which contains feature names and values
        :return: pairs of values which shows number of feature makes filter function true or false
: x : dict which contains feature names and values : return : pairs of values which shows number of feature makes filter function true or false