Function opendp::transformations::then_identity

source · 
pub fn then_identity<D, M>() -> PartialTransformation<D, D, M, M>
where
    D: Domain,
    D::Carrier: Clone,
    M: Metric,
    M::Distance: Clone,
    (D, M): MetricSpace,
Expand description

Make a Transformation representing the identity function.

WARNING: In Python, this function does not ensure that the domain and metric form a valid metric space. However, if the domain and metric do not form a valid metric space, then the resulting Transformation won’t be chainable with any valid Transformation, so it cannot be used to introduce an invalid metric space into a chain of valid Transformations.

§Generics

  • D - Domain of the identity function. Must be VectorDomain<AtomDomain<T>> or AtomDomain<T>
  • M - Metric. Must be a dataset metric if D is a VectorDomain or a sensitivity metric if D is an AtomDomain