neurosynth/base/dataset.py
def get_feature_counts(self, threshold=0.001):
        """ Returns a dictionary, where the keys are the feature names
        and the values are the number of studies tagged with the feature. """
        counts = np.sum(self.get_feature_data() >= threshold, 0)
        return dict(zip(self.get_feature_names(), list(counts)))
def get_feature_counts(self, threshold=0.001):
        counts = np.sum(self.get_feature_data() >= threshold, 0)
        return dict(zip(self.get_feature_names(), list(counts)))
def get_feature_counts ( self , threshold = 0.001 ) : counts = np . sum ( self . get_feature_data ( ) >= threshold , 0 ) return dict ( zip ( self . get_feature_names ( ) , list ( counts ) ) )
Returns a dictionary, where the keys are the feature names
        and the values are the number of studies tagged with the feature.
Returns a dictionary where the keys are the feature names and the values are the number of studies tagged with the feature .