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]
:x: dict which contains feature names and values
        :return: pairs of values which shows number of feature makes filter function true or false