2526879b1f941c887eeb24a267b5ea010e20d5d7,PyNomaly/loop.py,LocalOutlierProbability,_ssd,#LocalOutlierProbability#Any#,137

Before Change

            if ssd == 0.0:
                warnings.warn("Sum of square distances equals zero. Execution halted.", RuntimeWarning)
                sys.exit()
            ssd_dict[cluster_id] = ssd
        data_store = np.hstack((data_store, np.array([[ssd_dict[x] for x in data_store[:, 0].tolist()]]).T))
        return data_store

    def _standard_distances(self, data_store):
        return np.hstack(

After Change

            ssd = np.sum(np.power(cluster_distances[0], 2), axis=1)
            for i, j in zip(indices[0], ssd):
                ssd_array[i] = j
        data_store = np.hstack((data_store, ssd_array))
        return data_store

    def _standard_distances(self, data_store):
        cardinality = np.array([self.n_neighbors] * self._n_observations())

Instances