Struct opendp::metrics::LpDistance

pub struct LpDistance<const P: usize, Q>(PhantomData<fn() -> Q>);

The $L_p$ distance between two vector-valued aggregates.

Proof Definition

$d$-closeness

For any two vectors $u, v \in \texttt{D}$ and $d$ of generic type $\texttt{Q}$, we say that $u, v$ are $d$-close under the the $L_p$ distance metric (abbreviated as $d_{LP}$) whenever

d_{LP}(u, v) = \|u_i - v_i\|_p \leq d

If $u$ and $v$ are different lengths, then

d_{LP}(u, v) = \infty

Compatible Domains

• VectorDomain<D> for any valid D
• MapDomain<D> for any valid D

Tuple Fields

0: PhantomData<fn() -> Q>

Trait Implementations

impl<const P: usize, Q> Clone for LpDistance<P, Q>

fn clone(&self) -> Self

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<const P: usize, Q> Debug for LpDistance<P, Q>

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<const P: usize, Q> Default for LpDistance<P, Q>

fn default() -> Self

Returns the “default value” for a type.

impl<const P: usize, Q> Metric for LpDistance<P, Q>

type Distance = Q

Proof Definition

impl<const P: usize, Q> PartialEq for LpDistance<P, Q>

fn eq(&self, _other: &Self) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<const P: usize, T> BAryTreeMetric for LpDistance<P, T>

impl<const P: usize, Q> LipschitzMulFloatMetric for LpDistance<P, Q>