Struct SparseMatrix 

pub struct SparseMatrix { /* private fields */ }

Sparse matrix representation with multiple format support

Implementations

impl SparseMatrix

pub fn from_triplets( shape: (usize, usize), rows: Vec<usize>, cols: Vec<usize>, data: Vec<Float>, format: SparseFormat, ) -> Result<Self>

Create sparse matrix from triplet format (row, col, value)

pub fn zeros(shape: (usize, usize), format: SparseFormat) -> Self

Create empty sparse matrix

pub fn shape(&self) -> (usize, usize)

Get matrix dimensions

pub fn nnz(&self) -> usize

Get number of non-zero elements

pub fn density(&self) -> Float

Calculate sparsity density (fraction of non-zero elements)

pub fn format(&self) -> SparseFormat

Get current storage format

pub fn convert_to(&mut self, target_format: SparseFormat) -> Result<()>

Convert to different sparse format

pub fn column_means(&self) -> Result<Array1<Float>>

Get column means for CSR matrix

pub fn column_variances(&self, means: &Array1<Float>) -> Result<Array1<Float>>

Get column variances for CSR matrix

pub fn to_dense(&self) -> Result<Array2<Float>>

Convert to dense array (use with caution for large sparse matrices)

Trait Implementations

impl Clone for SparseMatrix

fn clone(&self) -> SparseMatrix

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SparseMatrix

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

Formats the value using the given formatter.

impl Fit<SparseMatrix, ()> for SparseStandardScaler<Untrained>

type Fitted = SparseStandardScalerFitted

The fitted model type

fn fit(self, x: &SparseMatrix, _y: &()) -> Result<Self::Fitted>

Fit the model to the provided data with validation

fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>

where Self: Sized,

Fit with custom validation and early stopping

impl Transform<SparseMatrix> for SparseStandardScalerFitted

fn transform(&self, x: &SparseMatrix) -> Result<SparseMatrix>

Transform the input data