PySparNN custom distance metric

pysparnn_custom.py

import sklearn


class UserCustomDistance(MatrixMetricSearch):
    def __init__(self, features, records_data):
        super(UserCustomDistance, self).__init__(features, records_data)
        self.matrix = self.matrix
        self.max_overlap = self.matrix.shape[0]  # for testing purpose

    @staticmethod
    def features_to_matrix(features):
        return features

    @staticmethod
    def vstack(matrix_list):
        return _np.vstack(matrix_list)

    def _transform_value(self, v):
        return v

    def user_distance_metric(self, u, v):
	"""Calculates overlap between two sparse vectors.
	Subtracts this overlap from the max_overlap for distance
	"""
        rep = _sparse.csr_matrix(_np.minimum(u.A, v.A))
        return self.max_overlap - rep.sum()

    def _distance(self, a_matrix):
        return sklearn.metrics.pairwise.pairwise_distances(
		a_matrix, self.matrix, lambda u, v: self.user_distance_metric(u, v))