Struct oxygengine_physics_2d::prelude::nalgebra::CsMatrix

pub struct CsMatrix<T, R = Dynamic, C = Dynamic, S = CsVecStorage<T, R, C>>where
    T: Scalar,
    R: Dim,
    C: Dim,
    S: CsStorage<T, R, C>,{ /* private fields */ }

A compressed sparse column matrix.

Implementations

impl<T, R, C> CsMatrix<T, R, C, CsVecStorage<T, R, C>>where T: Scalar, R: Dim, C: Dim, DefaultAllocator: Allocator<usize, C, Const<1>>,

pub fn new_uninitialized_generic( nrows: R, ncols: C, nvals: usize ) -> CsMatrix<T, R, C, CsVecStorage<T, R, C>>

Creates a new compressed sparse column matrix with the specified dimension and nvals possible non-zero values.

impl<T, R, C, S> CsMatrix<T, R, C, S>where T: Scalar, R: Dim, C: Dim, S: CsStorage<T, R, C>,

pub fn len(&self) -> usize

The size of the data buffer.

pub fn nrows(&self) -> usize

The number of rows of this matrix.

pub fn ncols(&self) -> usize

The number of rows of this matrix.

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

The shape of this matrix.

pub fn is_square(&self) -> bool

Whether this matrix is square or not.

pub fn is_sorted(&self) -> bool

Should always return true.

This method is generally used for debugging and should typically not be called in user code. This checks that the row inner indices of this matrix are sorted. It takes O(n) time, where nisself.len(). All operations of CSC matrices on nalgebra assume, and will return, sorted indices. If at any time this is_sortedmethod returnsfalse`, then, something went wrong and an issue should be open on the nalgebra repository with details on how to reproduce this.

pub fn transpose(&self) -> CsMatrix<T, C, R, CsVecStorage<T, C, R>>where DefaultAllocator: Allocator<usize, R, Const<1>>,

Computes the transpose of this sparse matrix.

impl<T, R, C, S> CsMatrix<T, R, C, S>where T: Scalar, R: Dim, C: Dim, S: CsStorageMut<T, R, C>,

pub fn values_mut(&mut self) -> impl Iterator<Item = &mut T>

Iterator through all the mutable values of this sparse matrix.

impl<'a, T> CsMatrix<T, Dynamic, Dynamic, CsVecStorage<T, Dynamic, Dynamic>>where T: Scalar + Zero + ClosedAdd<T>,

pub fn from_triplet( nrows: usize, ncols: usize, irows: &[usize], icols: &[usize], vals: &[T] ) -> CsMatrix<T, Dynamic, Dynamic, CsVecStorage<T, Dynamic, Dynamic>>

Creates a column-compressed sparse matrix from a sparse matrix in triplet form.

impl<'a, T, R, C> CsMatrix<T, R, C, CsVecStorage<T, R, C>>where T: Scalar + Zero + ClosedAdd<T>, R: Dim, C: Dim, DefaultAllocator: Allocator<usize, C, Const<1>> + Allocator<T, R, Const<1>>,

pub fn from_triplet_generic( nrows: R, ncols: C, irows: &[usize], icols: &[usize], vals: &[T] ) -> CsMatrix<T, R, C, CsVecStorage<T, R, C>>

Creates a column-compressed sparse matrix from a sparse matrix in triplet form.

impl<T, D, S> CsMatrix<T, D, D, S>where T: RealField, D: Dim, S: CsStorage<T, D, D>,

pub fn solve_lower_triangular<R2, C2, S2>( &self, b: &Matrix<T, R2, C2, S2> ) -> Option<Matrix<T, R2, C2, <DefaultAllocator as Allocator<T, R2, C2>>::Buffer>>where R2: Dim, C2: Dim, S2: Storage<T, R2, C2>, DefaultAllocator: Allocator<T, R2, C2>, ShapeConstraint: SameNumberOfRows<D, R2>,

Solve a lower-triangular system with a dense right-hand-side.

pub fn tr_solve_lower_triangular<R2, C2, S2>( &self, b: &Matrix<T, R2, C2, S2> ) -> Option<Matrix<T, R2, C2, <DefaultAllocator as Allocator<T, R2, C2>>::Buffer>>where R2: Dim, C2: Dim, S2: Storage<T, R2, C2>, DefaultAllocator: Allocator<T, R2, C2>, ShapeConstraint: SameNumberOfRows<D, R2>,

Solve a lower-triangular system with self transposed and a dense right-hand-side.

pub fn solve_lower_triangular_mut<R2, C2, S2>( &self, b: &mut Matrix<T, R2, C2, S2> ) -> boolwhere R2: Dim, C2: Dim, S2: StorageMut<T, R2, C2>, ShapeConstraint: SameNumberOfRows<D, R2>,

Solve in-place a lower-triangular system with a dense right-hand-side.

pub fn tr_solve_lower_triangular_mut<R2, C2, S2>( &self, b: &mut Matrix<T, R2, C2, S2> ) -> boolwhere R2: Dim, C2: Dim, S2: StorageMut<T, R2, C2>, ShapeConstraint: SameNumberOfRows<D, R2>,

Solve a lower-triangular system with self transposed and a dense right-hand-side.

pub fn solve_lower_triangular_cs<D2, S2>( &self, b: &CsMatrix<T, D2, Const<1>, S2> ) -> Option<CsMatrix<T, D2, Const<1>, CsVecStorage<T, D2, Const<1>>>>where D2: Dim, S2: CsStorage<T, D2, Const<1>>, DefaultAllocator: Allocator<bool, D, Const<1>> + Allocator<T, D2, Const<1>> + Allocator<usize, D2, Const<1>>, ShapeConstraint: SameNumberOfRows<D, D2>,

Solve a lower-triangular system with a sparse right-hand-side.

Trait Implementations

impl<'a, 'b, T, R1, R2, C1, C2, S1, S2> Add<&'b CsMatrix<T, R2, C2, S2>> for &'a CsMatrix<T, R1, C1, S1>where T: Scalar + ClosedAdd<T> + ClosedMul<T> + Zero + One, R1: Dim, C1: Dim, R2: Dim, C2: Dim, S1: CsStorage<T, R1, C1>, S2: CsStorage<T, R2, C2>, ShapeConstraint: DimEq<R1, R2> + DimEq<C1, C2>, DefaultAllocator: Allocator<usize, C2, Const<1>> + Allocator<usize, R1, Const<1>> + Allocator<T, R1, Const<1>>,

type Output = CsMatrix<T, R1, C2, CsVecStorage<T, R1, C2>>

The resulting type after applying the + operator.

fn add( self, rhs: &'b CsMatrix<T, R2, C2, S2> ) -> <&'a CsMatrix<T, R1, C1, S1> as Add<&'b CsMatrix<T, R2, C2, S2>>>::Output

Performs the + operation.

impl<T, R, C, S> Clone for CsMatrix<T, R, C, S>where T: Clone + Scalar, R: Clone + Dim, C: Clone + Dim, S: Clone + CsStorage<T, R, C>,

fn clone(&self) -> CsMatrix<T, R, C, S>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T, R, C, S> Debug for CsMatrix<T, R, C, S>where T: Debug + Scalar, R: Debug + Dim, C: Debug + Dim, S: Debug + CsStorage<T, R, C>,

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

Formats the value using the given formatter.

impl<'a, T, R, C, S> From<CsMatrix<T, R, C, S>> for Matrix<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer>where T: Scalar + Zero, R: Dim, C: Dim, S: CsStorage<T, R, C>, DefaultAllocator: Allocator<T, R, C>,

fn from( m: CsMatrix<T, R, C, S> ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer>

Converts to this type from the input type.

impl<'a, T, R, C, S> From<Matrix<T, R, C, S>> for CsMatrix<T, R, C, CsVecStorage<T, R, C>>where T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>, DefaultAllocator: Allocator<T, R, C> + Allocator<usize, C, Const<1>>,

fn from(m: Matrix<T, R, C, S>) -> CsMatrix<T, R, C, CsVecStorage<T, R, C>>

Converts to this type from the input type.

impl<'a, 'b, T, R1, R2, C1, C2, S1, S2> Mul<&'b CsMatrix<T, R2, C2, S2>> for &'a CsMatrix<T, R1, C1, S1>where T: Scalar + ClosedAdd<T> + ClosedMul<T> + Zero, R1: Dim, C1: Dim, R2: Dim, C2: Dim, S1: CsStorage<T, R1, C1>, S2: CsStorage<T, R2, C2>, ShapeConstraint: AreMultipliable<R1, C1, R2, C2>, DefaultAllocator: Allocator<usize, C2, Const<1>> + Allocator<usize, R1, Const<1>> + Allocator<T, R1, Const<1>>,

type Output = CsMatrix<T, R1, C2, CsVecStorage<T, R1, C2>>

The resulting type after applying the * operator.

fn mul( self, rhs: &'b CsMatrix<T, R2, C2, S2> ) -> <&'a CsMatrix<T, R1, C1, S1> as Mul<&'b CsMatrix<T, R2, C2, S2>>>::Output

Performs the * operation.

impl<'a, 'b, T, R, C, S> Mul<T> for CsMatrix<T, R, C, S>where T: Scalar + ClosedAdd<T> + ClosedMul<T> + Zero, R: Dim, C: Dim, S: CsStorageMut<T, R, C>,

type Output = CsMatrix<T, R, C, S>

The resulting type after applying the * operator.

fn mul(self, rhs: T) -> <CsMatrix<T, R, C, S> as Mul<T>>::Output

Performs the * operation.

impl<T, R, C, S> PartialEq<CsMatrix<T, R, C, S>> for CsMatrix<T, R, C, S>where T: PartialEq<T> + Scalar, R: PartialEq<R> + Dim, C: PartialEq<C> + Dim, S: PartialEq<S> + CsStorage<T, R, C>,

fn eq(&self, other: &CsMatrix<T, R, C, S>) -> bool

This method tests for self and other values to be equal, and is used by ==.

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

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

impl<T, R, C, S> StructuralPartialEq for CsMatrix<T, R, C, S>where T: Scalar, R: Dim, C: Dim, S: CsStorage<T, R, C>,