# Validation functions¶

Validation functions for the differential privacy library

## General functions¶

diffprivlib.validation.check_epsilon_delta(epsilon, delta, allow_zero=False)[source]

Checks that epsilon and delta are valid values for differential privacy. Throws an error if checks fail, otherwise returns nothing.

As well as the requirements of epsilon and delta separately, both cannot be simultaneously zero, unless allow_zero is set to True.

Parameters
• epsilon (float) – Epsilon parameter for differential privacy. Must be non-negative.

• delta (float) – Delta parameter for differential privacy. Must be on the unit interval, [0, 1].

• allow_zero (bool, default: False) – Allow epsilon and delta both be zero.

diffprivlib.validation.check_bounds(bounds, shape=0, min_separation=0.0, dtype=<class 'float'>)[source]

Input validation for the bounds parameter.

Checks that bounds is composed of a list of tuples of the form (lower, upper), where lower <= upper and both are numeric. Also checks that bounds contains the appropriate number of dimensions, and that there is a min_separation between the bounds.

Parameters
• bounds (tuple) – Tuple of bounds of the form (min, max). min and max can either be scalars or 1-dimensional arrays.

• shape (int, default: 0) – Number of dimensions to be expected in bounds.

• min_separation (float, default: 0.0) – The minimum separation between lower and upper of each dimension. This separation is enforced if not already satisfied.

• dtype (data-type, default: float) – Data type of the returned bounds.

Returns

bounds

Return type

tuple

diffprivlib.validation.clip_to_norm(array, clip)[source]

Clips the examples of a 2-dimensional array to a given maximum norm.

Parameters
• array (np.ndarray) – Array to be clipped. After clipping, all examples have a 2-norm of at most clip.

• clip (float) – Norm at which to clip each example

Returns

array – The clipped array.

Return type

np.ndarray

diffprivlib.validation.clip_to_bounds(array, bounds)[source]

Clips the examples of a 2-dimensional array to given bounds.

Parameters
• array (np.ndarray) – Array to be clipped. After clipping, all examples have a 2-norm of at most clip.

• bounds (tuple) – Tuple of bounds of the form (min, max) which the array is to be clipped to. min and max must be scalar, unless array is 2-dimensional.

Returns

array – The clipped array.

Return type

np.ndarray