Mechanism construction for d-privacy

qif.mechanism.d_privacy

Functions

distance_matrix(n_rows: int, n_cols: int, d: Metric[int, float]) → ndarray

geometric(n_rows: int, epsilon: float = 1, n_cols: int = 0, first_x: int = 0, first_y: int = 0) → ndarray

exponential(n_rows: int, d: Metric[int, float], n_cols: int = 0) → ndarray

randomized_response(n_rows: int, epsilon: float = 1, n_cols: int = 0) → ndarray

tight_constraints(n_rows: int, d: Metric[int, float]) → ndarray

exact_distance(n_rows: int, d: Metric[int, float]) → ndarray

min_loss_given_d(pi: ndarray, n_cols: int, d_priv: Metric[int, float], loss: Metric[int, float], vars: str = 'all', d_priv_ch: Metric[int, bool] = ..., inf: float = ...) → ndarray