abod.py 文件源码

def anomaly_score(self, X=None):
        """Compute anomaly scores for test samples.

        Parameters
        ----------
        X : array-like of shape (n_samples, n_features), default None
            Test samples.

        Returns
        -------
        y_score : array-like of shape (n_samples,)
            Anomaly scores for test samples.
        """

        check_is_fitted(self, '_knn')

        if X is None:
            X        = self._knn._fit_X
            ind      = self._knn.kneighbors(None, return_distance=False)
        else:
            X        = check_array(X)
            ind      = self._knn.kneighbors(X, return_distance=False)

        n_samples, _ = X.shape

        try:
            result   = Parallel(self.n_jobs)(
                delayed(_abof)(
                    X[s], ind[s], self._knn._fit_X
                ) for s in gen_even_slices(n_samples, self.n_jobs)
            )
        except FloatingPointError as e:
            raise ValueError('X must not contain training samples') from e

        return -np.concatenate(result)