Struct Mat 

pub struct Mat(/* private fields */);

A matrix backed by libmat’s C implementation.

Owns its underlying C allocation and frees it on drop. Uses column-major storage.

Implementations

impl Mat

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

Creates a zero-initialized matrix with the given dimensions.

pub fn from_slice(rows: usize, cols: usize, data: &[f32]) -> Self

Creates a matrix from a slice of values in column-major order.

pub fn eye(dim: usize) -> Self

Creates an identity matrix of the given dimension.

pub fn mul(&self, other: &Mat) -> Self

Returns the matrix product self * other.

pub fn add(&self, other: &Mat) -> Self

Returns the element-wise sum self + other.

pub fn at(&self, row: usize, col: usize) -> f32

Returns the element at (row, col).

pub fn equals(&self, other: &Mat) -> bool

Returns true if all elements are equal.

pub fn print(&self)

Prints the matrix to stdout.

pub fn rows(&self) -> usize

Returns the number of rows.

pub fn cols(&self) -> usize

Returns the number of columns.

pub fn eigvals(&self) -> Mat

Computes eigenvalues of a general square matrix.

Uses Hessenberg reduction followed by implicit QR iteration. For complex eigenvalues (conjugate pairs), only the real part is stored.

pub fn eigvals_sym(&self) -> Mat

Computes eigenvalues of a symmetric matrix.

Faster than eigvals for symmetric input. Uses tridiagonal reduction + implicit QR iteration.

pub fn eigen_sym(&self) -> Eigen

Computes eigendecomposition of a symmetric matrix: A = V * diag(eigenvalues) * V^T.

Returns an Eigen where eigenvectors columns are orthogonal eigenvectors and eigenvalues are sorted in ascending order.

pub fn eigen(&self) -> Eigen

Computes eigendecomposition of a general square matrix.

Returns an Eigen where eigenvectors columns are the eigenvectors and eigenvalues holds eigenvalues (real parts for complex conjugate pairs).

Trait Implementations

impl Drop for Mat

fn drop(&mut self)

Executes the destructor for this type.