73675264dd48387319f62780b52d81389016cc1f,neurosynth/base/dataset.py,FeatureTable,get_features_by_ids,#FeatureTable#Any#Any#Any#Any#,602

Before Change

    def get_features_by_ids(self, ids=None, threshold=0.0001, func="sum", get_weights=False):
        """ Returns features that mach to ids"""
        id_indices = np.in1d(self.ids, ids)
        data = self.data.toarray()
        ids_weights = reduce(lambda x,y: x+y, data[id_indices,:])/len(id_indices)
        above_thresh = (ids_weights >= threshold)
        features_to_keep = np.array(self.feature_names)[np.where(above_thresh)]
        if get_weights:
            return dict(zip(features_to_keep, list(ids_weights[above_thresh])))
        else:
            return features_to_keep

After Change

    def get_features_by_ids(self, ids=None, threshold=0.0001, func=np.mean, get_weights=False):
        """ Returns features for which the mean loading across all specified studies (in ids)
        is >= threshold. """
        weights = self.data.ix[ids].apply(func, 0)
        above_thresh = weights[weights >= threshold]
        return above_thresh if get_weights else list(above_thresh.index)

Instances