Struct WeightedDimensionVector 

pub struct WeightedDimensionVector {
    pub vector: Vector,
    pub weights: Vec<f32>,
}

Weighted dimension vector where each dimension has an importance weight

Fields

vector: Vector

The vector values

weights: Vec<f32>

Importance weights for each dimension

Implementations

impl WeightedDimensionVector

pub fn new(values: Vec<f32>, weights: Vec<f32>) -> Result<Self>

Create a new weighted dimension vector

pub fn uniform(values: Vec<f32>) -> Self

Create with uniform weights

pub fn normalize_weights(&mut self)

Normalize weights to sum to 1.0

pub fn weighted_cosine_similarity( &self, other: &WeightedDimensionVector, ) -> Result<f32>

Compute weighted cosine similarity

pub fn top_dimensions(&self, k: usize) -> Vec<(usize, f32, f32)>

Get the most important dimensions

Trait Implementations

impl Clone for WeightedDimensionVector

fn clone(&self) -> WeightedDimensionVector

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for WeightedDimensionVector

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for WeightedDimensionVector

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for WeightedDimensionVector

fn eq(&self, other: &WeightedDimensionVector) -> bool

Tests for self and other values to be equal, and is used by ==.

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

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

impl Serialize for WeightedDimensionVector

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for WeightedDimensionVector