Struct opensrdk_linear_algebra::matrix::Matrix

pub struct Matrix<T = f64> where
    T: Number,  { /* fields omitted */ }

Matrix

Implementations

impl Matrix<f64>

pub fn diinv(self) -> Self

Inverse

for diagonal matrix

impl Matrix<c64>

pub fn diinv(self) -> Self

Inverse

for diagonal matrix

impl Matrix<f64>

pub fn dipowf(self, exp: f64) -> Self

Pow integer

for diagonal matrix

impl Matrix<c64>

pub fn dipowf(self, exp: f64) -> Self

Pow integer

for diagonal matrix

impl Matrix<f64>

pub fn dipowi(self, exp: i32) -> Self

Pow integer

for diagonal matrix

impl Matrix<c64>

pub fn dipowi(self, exp: i32) -> Self

Pow integer

for diagonal matrix

impl Matrix

pub fn geinv(self) -> Result<Matrix, String>

Inverse

for square matrix

impl Matrix<c64>

pub fn geinv(self) -> Result<Matrix<c64>, String>

Inverse

for square matrix

impl Matrix

pub fn gemm(
    self,
    lhs: &Matrix,
    rhs: &Matrix,
    alpha: f64,
    beta: f64
) -> Result<Matrix, String>

impl Matrix<c64>

pub fn gemm(
    self,
    lhs: &Matrix<c64>,
    rhs: &Matrix<c64>,
    alpha: c64,
    beta: c64
) -> Result<Matrix<c64>, String>

impl Matrix

pub fn gesvd(&self) -> Result<(Matrix, Matrix, Matrix), String>

Singular Value Decomposition

https://en.wikipedia.org/wiki/Singular_value_decomposition

M = U * Sigma * V^T (u, sigma, vt)

impl Matrix

pub fn getrf(self) -> Result<(Matrix, Vec<i32>), String>

LU decomposition

for f64

impl Matrix<c64>

pub fn getrf(self) -> Result<(Matrix<c64>, Vec<i32>), String>

LU decomposition

for c64

impl Matrix

pub fn getri(self, ipiv: &[i32]) -> Result<Matrix, String>

Inverse

with matrix decomposed by getrf

impl Matrix<c64>

pub fn getri(self, ipiv: &[i32]) -> Result<Matrix<c64>, String>

Inverse

with matrix decomposed by getrf

impl Matrix

pub fn getrs(&self, ipiv: &[i32], b_t: Matrix) -> Result<Matrix, String>

Solve equation

with matrix decomposed by getrf Ax = b

impl Matrix<c64>

pub fn getrs(
    &self,
    ipiv: &[i32],
    b_t: Matrix<c64>
) -> Result<Matrix<c64>, String>

Solve equation

with matrix decomposed by getrf Ax = b

impl Matrix<c64>

pub fn adjoint(&self) -> Matrix<c64>

impl Matrix

Diagonal matrix

pub fn diag<T>(vec: &[T]) -> Matrix<T> where
    T: Number, 

impl<T> Matrix<T> where
    T: Number, 

pub fn identity(n: usize) -> Self

Identity

impl<T> Matrix<T> where
    T: Number, 

pub fn linear_prod(&self, rhs: &Matrix<T>) -> T

Linear product

pub fn hadamard_prod(self, rhs: &Matrix<T>) -> Matrix<T>

Hamadard product

impl<T> Matrix<T> where
    T: Number, 

pub fn t(&self) -> Matrix<T>

Transpose

impl<T> Matrix<T> where
    T: Number, 

pub fn tr(&self) -> T

Trace

impl Matrix

pub fn poinv(self) -> Result<Matrix, String>

Inverse

for positive definite matrix

impl Matrix

pub fn posv_cgm(
    vec_mul: impl Fn(&[f64]) -> Result<Vec<f64>, String>,
    b: Vec<f64>,
    iterations: usize
) -> Result<Vec<f64>, String>

Solve equations with Conjugate Gradient Method

for positiveDefinite matrix

impl Matrix

pub fn potrf(self) -> Result<Matrix, String>

Cholesky decomposition

for positive definite f64 matrix

https://en.wikipedia.org/wiki/Cholesky_decomposition

A = L * L^T

impl Matrix<c64>

pub fn potrf(self) -> Result<Matrix<c64>, String>

Cholesky decomposition

for positive definite c64 matrix

https://en.wikipedia.org/wiki/Cholesky_decomposition

A = L * L^*

impl Matrix

pub fn potri(self) -> Result<Matrix, String>

Inverse

with matrix decomposed by potrf

impl Matrix<c64>

pub fn potri(self) -> Result<Matrix<c64>, String>

Inverse

with matrix decomposed by potrf

impl Matrix

pub fn potrs(&self, b_t: Matrix) -> Result<Matrix, String>

Solve equation

with matrix decomposed by potrf Ax = b

impl Matrix<c64>

pub fn potrs(&self, b_t: Matrix<c64>) -> Result<Matrix<c64>, String>

Solve equation

with matrix decomposed by potrf Ax = b

impl Matrix

pub fn sytrd(self) -> Result<(Matrix, SymmetricTridiagonalMatrix), String>

Tridiagonalize

for symmetric matrix

pub fn sytrd_k(
    n: usize,
    k: usize,
    vec_mul: impl Fn(&[f64]) -> Result<Vec<f64>, String>,
    probe: Option<Vec<f64>>
) -> Result<(SymmetricTridiagonalMatrix, Matrix), String>

Lanczos algorithm

for symmetric matrix only k iteration

impl<T> Matrix<T> where
    T: Number, 

pub fn trdet(&self) -> T

Determinant

for triangle matrix To apply this method to none triangle matrix, use LU decomposition or Cholesky decomposition.

impl<T> Matrix<T> where
    T: Number, 

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

pub fn from(rows: usize, elems: Vec<T>) -> Self

pub fn row(v: Vec<T>) -> Self

pub fn col(v: Vec<T>) -> Self

pub fn same_size(&self, rhs: &Matrix<T>) -> bool

pub fn rows(&self) -> usize

pub fn cols(&self) -> usize

pub fn elems(self) -> Vec<T>

pub fn elems_ref(&self) -> &[T]

impl Matrix<f64>

pub fn to_complex(&self) -> Matrix<c64>

impl Matrix<c64>

pub fn to_real(&self) -> Matrix<f64>

Trait Implementations

impl<T: Number, '_> Add<&'_ Matrix<T>> for Matrix<T>

type Output = Matrix<T>

The resulting type after applying the + operator.

fn add(self, rhs: &Matrix<T>) -> Self::Output

Performs the + operation.

impl<T: Number> Add<Matrix<T>> for Matrix<T>

type Output = Matrix<T>

The resulting type after applying the + operator.

fn add(self, rhs: Matrix<T>) -> Self::Output

Performs the + operation.

impl<T: Number, '_> Add<Matrix<T>> for &'_ Matrix<T>

type Output = Matrix<T>

The resulting type after applying the + operator.

fn add(self, rhs: Matrix<T>) -> Self::Output

Performs the + operation.

impl<T: Clone> Clone for Matrix<T> where
    T: Number, 

fn clone(&self) -> Matrix<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for Matrix<T> where
    T: Number, 

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

Formats the value using the given formatter.

impl<T: Default> Default for Matrix<T> where
    T: Number, 

fn default() -> Matrix<T>

Returns the "default value" for a type.

impl<T: Hash> Hash for Matrix<T> where
    T: Number, 

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given [Hasher].

fn hash_slice<H>(data: &[Self], state: &mut H) where
    H: Hasher, 

Feeds a slice of this type into the given [Hasher].

impl<T> Index<usize> for Matrix<T> where
    T: Number, 

type Output = [T]

The returned type after indexing.

fn index(&self, index: usize) -> &Self::Output

Performs the indexing (container[index]) operation.

impl<T> IndexMut<usize> for Matrix<T> where
    T: Number, 

fn index_mut(&mut self, index: usize) -> &mut Self::Output

Performs the mutable indexing (container[index]) operation.

impl<'_> Mul<&'_ Matrix<Complex<f64>>> for Matrix<c64>

type Output = Matrix<c64>

The resulting type after applying the * operator.

fn mul(self, rhs: &Matrix<c64>) -> Self::Output

Performs the * operation.

impl<'_, '_> Mul<&'_ Matrix<Complex<f64>>> for &'_ Matrix<c64>

type Output = Matrix<c64>

The resulting type after applying the * operator.

fn mul(self, rhs: &Matrix<c64>) -> Self::Output

Performs the * operation.

impl<'_> Mul<&'_ Matrix<f64>> for Matrix<f64>

type Output = Matrix<f64>

The resulting type after applying the * operator.

fn mul(self, rhs: &Matrix<f64>) -> Self::Output

Performs the * operation.

impl<'_, '_> Mul<&'_ Matrix<f64>> for &'_ Matrix<f64>

type Output = Matrix<f64>

The resulting type after applying the * operator.

fn mul(self, rhs: &Matrix<f64>) -> Self::Output

Performs the * operation.

impl Mul<Complex<f64>> for Matrix<c64>

type Output = Matrix<c64>

The resulting type after applying the * operator.

fn mul(self, rhs: c64) -> Self::Output

Performs the * operation.

impl Mul<Matrix<Complex<f64>>> for c64

type Output = Matrix<c64>

The resulting type after applying the * operator.

fn mul(self, rhs: Matrix<c64>) -> Self::Output

Performs the * operation.

impl Mul<Matrix<Complex<f64>>> for Matrix<c64>

type Output = Matrix<c64>

The resulting type after applying the * operator.

fn mul(self, rhs: Matrix<c64>) -> Self::Output

Performs the * operation.

impl<'_> Mul<Matrix<Complex<f64>>> for &'_ Matrix<c64>

type Output = Matrix<c64>

The resulting type after applying the * operator.

fn mul(self, rhs: Matrix<c64>) -> Self::Output

Performs the * operation.

impl Mul<Matrix<f64>> for f64

type Output = Matrix<f64>

The resulting type after applying the * operator.

fn mul(self, rhs: Matrix<f64>) -> Self::Output

Performs the * operation.

impl Mul<Matrix<f64>> for Matrix<f64>

type Output = Matrix<f64>

The resulting type after applying the * operator.

fn mul(self, rhs: Matrix<f64>) -> Self::Output

Performs the * operation.

impl<'_> Mul<Matrix<f64>> for &'_ Matrix<f64>

type Output = Matrix<f64>

The resulting type after applying the * operator.

fn mul(self, rhs: Matrix<f64>) -> Self::Output

Performs the * operation.

impl Mul<f64> for Matrix<f64>

type Output = Matrix<f64>

The resulting type after applying the * operator.

fn mul(self, rhs: f64) -> Self::Output

Performs the * operation.

impl<T: Number, '_> Sub<&'_ Matrix<T>> for Matrix<T>

type Output = Matrix<T>

The resulting type after applying the - operator.

fn sub(self, rhs: &Matrix<T>) -> Self::Output

Performs the - operation.

impl<T: Number> Sub<Matrix<T>> for Matrix<T>

type Output = Matrix<T>

The resulting type after applying the - operator.

fn sub(self, rhs: Matrix<T>) -> Self::Output

Performs the - operation.

impl<T: Number, '_> Sub<Matrix<T>> for &'_ Matrix<T>

type Output = Matrix<T>

The resulting type after applying the - operator.

fn sub(self, rhs: Matrix<T>) -> Self::Output

Performs the - operation.

impl<T> SubMatrix<T> for Matrix<T> where
    T: Number, 

fn size(&self) -> (usize, usize)

fn index(&self, i: usize, j: usize) -> T

impl<T, '_> SubMatrix<T> for &'_ Matrix<T> where
    T: Number, 

fn size(&self) -> (usize, usize)

fn index(&self, i: usize, j: usize) -> T