Struct CompensatedSquaredL2 

pub struct CompensatedSquaredL2 { /* private fields */ }

A DistanceFunction containing scaling parameters to enable distance the SquaredL2 distance function over CompensatedVectors belonging to the same quantization space.

Implementations

impl CompensatedSquaredL2

pub fn new(scale_squared: f32) -> Self

Construct a new CompensatedSquaredL2 with the given scaling factor.

Trait Implementations

impl AsFunctor<CompensatedSquaredL2> for ScalarQuantizer

fn as_functor(&self) -> CompensatedSquaredL2

impl Clone for CompensatedSquaredL2

fn clone(&self) -> CompensatedSquaredL2

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CompensatedSquaredL2

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

Formats the value using the given formatter.

impl<const NBITS: usize> DistanceFunction<VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, Result<MathematicalValue<f32>, UnequalLengths>> for CompensatedSquaredL2

where Unsigned: Representation<NBITS>, SquaredL2: for<'a, 'b> PureDistanceFunction<BitSlice<'a, NBITS, Unsigned>, BitSlice<'b, NBITS, Unsigned>, MathematicalResult<u32>>,

Compute the squared euclidean distance between the two compensated vectors.

The value returned by this function is scaled properly, meaning that distances returned by this method are compatible with full-precision distances.

Validity

The results of this function are only meaningful if both x, y, and Self belong to the same quantizer.

Panics

Panics if x.len() != y.len().

fn evaluate_similarity( &self, x: CompensatedVectorRef<'_, NBITS>, y: CompensatedVectorRef<'_, NBITS>, ) -> MathematicalResult<f32>

Perform a distance computation between the left-hand and right-hand arguments.

impl<const NBITS: usize> DistanceFunction<VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, Result<f32, UnequalLengths>> for CompensatedSquaredL2

where Unsigned: Representation<NBITS>, Self: for<'a, 'b> DistanceFunction<CompensatedVectorRef<'a, NBITS>, CompensatedVectorRef<'b, NBITS>, MathematicalResult<f32>>,

Compute the squared euclidean distance between the two compensated vectors.

The value returned by this function is scaled properly, meaning that distances returned by this method are compatible with full-precision distances.

Validity

The results of this function are only meaningful if both x, y, and Self belong to the same quantizer.

Panics

Panics if x.len() != y.len().

fn evaluate_similarity( &self, x: CompensatedVectorRef<'_, NBITS>, y: CompensatedVectorRef<'_, NBITS>, ) -> Result<f32>

Perform a distance computation between the left-hand and right-hand arguments.

impl Copy for CompensatedSquaredL2