Struct SparseTensor 

pub struct SparseTensor {
    pub rows: usize,
    pub cols: usize,
    pub col_ptrs: Vec<usize>,
    pub row_indices: Vec<usize>,
    /* private fields */
}

Fields

rows: usize

cols: usize

col_ptrs: Vec<usize>

Column pointers into row_indices and the numeric value storage; length is cols + 1.

row_indices: Vec<usize>

Zero-based row indices, sorted within each column.

Implementations

impl SparseTensor

pub fn new( rows: usize, cols: usize, col_ptrs: Vec<usize>, row_indices: Vec<usize>, values: Vec<f64>, ) -> Result<Self, String>

pub fn new_f32( rows: usize, cols: usize, col_ptrs: Vec<usize>, row_indices: Vec<usize>, values: Vec<f32>, ) -> Result<Self, String>

Constructs a sparse matrix backed by native single-precision values.

pub fn new_integer( rows: usize, cols: usize, col_ptrs: Vec<usize>, row_indices: Vec<usize>, integer_data: IntegerStorage, ) -> Result<Self, String>

Constructs a sparse matrix backed by an exact integer value buffer.

pub fn new_logical( rows: usize, cols: usize, col_ptrs: Vec<usize>, row_indices: Vec<usize>, ) -> Result<Self, String>

Constructs a sparse logical matrix whose CSC pattern is the complete authoritative set of true elements.

pub fn zeros(rows: usize, cols: usize) -> Self

pub fn zeros_f32(rows: usize, cols: usize) -> Self

Creates an all-zero sparse matrix retaining the single class.

pub fn zeros_logical(rows: usize, cols: usize) -> Self

Creates an all-false sparse logical matrix.

pub fn zeros_with_integer_storage( rows: usize, cols: usize, storage: &IntegerStorage, ) -> Self

Creates an all-zero sparse matrix retaining an exact integer class.

pub fn new_integer_like( rows: usize, cols: usize, col_ptrs: Vec<usize>, row_indices: Vec<usize>, values: Vec<IntValue>, prototype: &IntegerStorage, ) -> Result<Self, String>

Creates a typed sparse matrix using the class of prototype.

pub fn nnz(&self) -> usize

pub fn shape(&self) -> Vec<usize>

pub fn to_dense(&self) -> Result<Tensor, String>

pub fn to_dense_logical(&self) -> Result<LogicalArray, String>

pub fn get(&self, row: usize, col: usize) -> Option<f64>

pub fn logical_at(&self, row: usize, col: usize) -> Option<bool>

pub fn integer_at(&self, row: usize, col: usize) -> Option<IntValue>

Returns an exact stored integer value when this sparse matrix is typed.

pub fn integer_storage(&self) -> Option<&IntegerStorage>

pub fn as_f64_slice(&self) -> Option<&[f64]>

Borrows stored nonzero values when this sparse matrix is double.

pub fn as_f32_slice(&self) -> Option<&[f32]>

Borrows stored nonzero values when this sparse matrix is single.

pub fn is_logical(&self) -> bool

pub fn value_byte_size(&self) -> usize

pub fn materialize_f64(&self) -> Vec<f64>

Explicitly materializes stored nonzero values in the f64 computation domain.

Integer values outside the exact binary64 range may lose precision.

pub fn numeric_value_at(&self, index: usize) -> Option<NumericScalar>

Reads one stored nonzero value without routing integers through floating point.

pub fn numeric_dtype(&self) -> Option<NumericDType>

pub fn with_updated_linear_values( &self, updates: &[(usize, f64)], ) -> Result<Self, String>

Applies floating updates in one CSC merge. Repeated indices use the final assignment value and zeros are elided without densifying.

pub fn with_updated_f32_linear_values( &self, updates: &[(usize, f32)], ) -> Result<Self, String>

Applies native single-precision updates in one CSC merge.

pub fn with_updated_integer_linear_values( &self, updates: &[(usize, IntValue)], ) -> Result<Self, String>

Applies exact integer updates in one CSC merge. Values must already be in this sparse matrix’s class; coercion belongs to the VM layer.

pub fn with_updated_logical_linear_values( &self, updates: &[(usize, bool)], ) -> Result<Self, String>

pub fn with_updated_value( &self, row: usize, col: usize, value: f64, ) -> Result<Self, String>

pub fn with_updated_f32_value( &self, row: usize, col: usize, value: f32, ) -> Result<Self, String>

pub fn with_updated_integer_value( &self, row: usize, col: usize, value: IntValue, ) -> Result<Self, String>

pub fn with_updated_logical_value( &self, row: usize, col: usize, value: bool, ) -> Result<Self, String>

pub fn with_expanded_shape( &self, rows: usize, cols: usize, ) -> Result<Self, String>

Expands sparse dimensions without materializing implicit zero entries.

pub fn with_deleted_rows(&self, rows: &[usize]) -> Result<Self, String>

Deletes complete sparse matrix rows without materializing dense storage.

pub fn with_deleted_columns(&self, columns: &[usize]) -> Result<Self, String>

Deletes complete sparse matrix columns without materializing dense storage.

pub fn class_name(&self) -> &'static str

Trait Implementations

impl Clone for SparseTensor

fn clone(&self) -> SparseTensor

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SparseTensor

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

Formats the value using the given formatter.

impl Display for SparseTensor

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

Formats the value using the given formatter.

impl PartialEq for SparseTensor

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

Equality operator ==.

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

Inequality operator !=.

impl StructuralPartialEq for SparseTensor