Struct TensorRank2SparseVec2DSymmetric 

pub struct TensorRank2SparseVec2DSymmetric<const D: usize, I, J, U = Dimensionless>(/* private fields */);

A vector of sparse vectors of rank-2 tensors, storing only the symmetric half.

The underlying block matrix is known to be symmetric under index-pair transpose, meaning block(a, b) == block(b, a)ᵀ for every pair of block indices. Only the canonical (row <= column) half of the blocks is stored; entries on the other side are reconstructed by transposing on lookup instead of being duplicated in memory.

Implementations

impl<const D: usize, I, J, U> TensorRank2SparseVec2DSymmetric<D, I, J, U>

pub fn zero(len: usize) -> Self

Trait Implementations

impl<const D: usize, I, J, U> Add for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Output = TensorRank2SparseVec2DSymmetric<D, I, J, U>

The resulting type after applying the + operator.

fn add(self, other: Self) -> Self

Performs the + operation.

impl<const D: usize, I, J, U> Add<&TensorRank2SparseVec2DSymmetric<D, I, J, U>> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Output = TensorRank2SparseVec2DSymmetric<D, I, J, U>

The resulting type after applying the + operator.

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

Performs the + operation.

impl<const D: usize, I, J, U> AddAssign for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn add_assign(&mut self, other: Self)

Performs the += operation.

impl<const D: usize, I, J, U> AddAssign<&TensorRank2SparseVec2DSymmetric<D, I, J, U>> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn add_assign(&mut self, other: &Self)

Performs the += operation.

impl<const D: usize, I, J> AssertEq for TensorRank2SparseVec2DSymmetric<D, I, J>

fn eq( a: Self, b: TensorRank2SparseVec2DSymmetric<D, I, J>, ) -> Result<(), AssertionError>

fn eq_within_tols( tols: &Assert, a: Self, b: TensorRank2SparseVec2DSymmetric<D, I, J>, ) -> Result<(), AssertionError>

impl<const D: usize, I, J> AssertFd for TensorRank2SparseVec2DSymmetric<D, I, J>

fn eq_within_fd_tol( tols: &Assert, a: Self, b: TensorRank2SparseVec2DSymmetric<D, I, J>, ) -> Result<(), AssertionError>

impl<const D: usize, I, J, U> Clone for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<const D: usize, I, J, U> Debug for TensorRank2SparseVec2DSymmetric<D, I, J, U>

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

Formats the value using the given formatter.

impl<const D: usize, I, J, U> Default for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn default() -> Self

Returns the “default value” for a type.

impl<const D: usize, I, J, U> Display for TensorRank2SparseVec2DSymmetric<D, I, J, U>

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

Formats the value using the given formatter.

impl<const D: usize, I, J, U, V> Div<TensorRank2SparseVec2DSymmetric<D, I, J, V>> for &TensorRank1Vec<D, I, U>

where U: UnitDiv<V>,

type Output = TensorVector<TensorRank1<D, J, <U as UnitDiv<V>>::Output>>

The resulting type after applying the / operator.

fn div( self, _tensor_rank_2_sparse_symmetric_vec_2d: TensorRank2SparseVec2DSymmetric<D, I, J, V>, ) -> Self::Output

Performs the / operation.

impl<const D: usize, I, J, U> Div<f64> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Output = TensorRank2SparseVec2DSymmetric<D, I, J, U>

The resulting type after applying the / operator.

fn div(self, scalar: TensorRank0) -> Self

Performs the / operation.

impl<const D: usize, I, J, U> DivAssign<&f64> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn div_assign(&mut self, scalar: &TensorRank0)

Performs the /= operation.

impl<const D: usize, I, J, U> DivAssign<f64> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn div_assign(&mut self, scalar: TensorRank0)

Performs the /= operation.

impl<const D: usize, I, J, U> FiniteDifference for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn error_fd( &self, comparator: &Self, epsilon: TensorRank0, ) -> Option<(bool, usize)>

impl<const D: usize, I, J, U> Hessian for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn entry(&self, row: usize, column: usize) -> Scalar

The entry at the given (row, column) position.

fn quadratic_form(&self, vector: &Vector) -> Scalar

The quadratic form of the Hessian with a vector.

fn fill_into(self, square_matrix: &mut SquareMatrix)

Fills the Hessian into a square matrix.

fn retain_from(self, retained: &[bool]) -> SquareMatrix

Return only the retained indices.

impl<const D: usize, I, U> HessianAccumulate<D, I, U> for TensorRank2SparseVec2DSymmetric<D, I, I, U>

fn accumulate(&mut self, a: usize, b: usize, block: TensorRank2<D, I, I, U>)

impl<const D: usize, I, J, U> Mul<f64> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Output = TensorRank2SparseVec2DSymmetric<D, I, J, U>

The resulting type after applying the * operator.

fn mul(self, scalar: TensorRank0) -> Self

Performs the * operation.

impl<const D: usize, I, J, U> MulAssign<&f64> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn mul_assign(&mut self, scalar: &TensorRank0)

Performs the *= operation.

impl<const D: usize, I, J, U> MulAssign<f64> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn mul_assign(&mut self, scalar: TensorRank0)

Performs the *= operation.

impl<const D: usize, I, J, U> PartialEq for TensorRank2SparseVec2DSymmetric<D, I, J, U>

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl<B, const D: usize> SecondOrderMinimize<Quantity<Energy>, TensorVector<TensorRank1<D, Current, Force>>, TensorRank2SparseVec2DSymmetric<D, Current, Current, ForcePerLength>, TensorVector<TensorRank1<D, Current, Length>>> for Model<B, D>

where B: HyperelasticElements<D>,

fn minimize( &self, equality_constraint: EqualityConstraint, solver: impl SecondOrderOptimization<Quantity<Energy>, NodalForcesSolid<D>, NodalStiffnessesSolidSymmetric<D>, NodalCoordinates<D>>, ) -> Result<NodalCoordinates<D>, OptimizationError>

impl<const D: usize, I, J, U> Sub for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Output = TensorRank2SparseVec2DSymmetric<D, I, J, U>

The resulting type after applying the - operator.

fn sub(self, other: Self) -> Self

Performs the - operation.

impl<const D: usize, I, J, U> Sub<&TensorRank2SparseVec2DSymmetric<D, I, J, U>> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Output = TensorRank2SparseVec2DSymmetric<D, I, J, U>

The resulting type after applying the - operator.

fn sub(self, other: &Self) -> Self

Performs the - operation.

impl<const D: usize, I, J, U> SubAssign for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn sub_assign(&mut self, other: Self)

Performs the -= operation.

impl<const D: usize, I, J, U> SubAssign<&TensorRank2SparseVec2DSymmetric<D, I, J, U>> for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn sub_assign(&mut self, other: &Self)

Performs the -= operation.

impl<const D: usize, I, J, U> Sum for TensorRank2SparseVec2DSymmetric<D, I, J, U>

fn sum<T>(iter: T) -> Self

where T: Iterator<Item = Self>,

Takes an iterator and generates Self from the elements by “summing up” the items.

impl<const D: usize, I, J, U> Tensor for TensorRank2SparseVec2DSymmetric<D, I, J, U>

type Item = TensorRank2SparseVec<D, I, J, U>

The type of item encountered when iterating over the tensor.

type Unit = U

The physical unit the tensor carries.

fn iter(&self) -> impl Iterator<Item = &Self::Item>

Returns an iterator.

fn iter_mut(&mut self) -> impl Iterator<Item = &mut Self::Item>

Returns an iterator that allows modifying each value.

fn len(&self) -> usize

Returns the number of elements, also referred to as the ‘length’.

fn size(&self) -> usize

Returns the total number of entries.

fn error_count_zero(&self, tol_abs: Scalar, tol_rel: Scalar) -> Option<usize>

Returns number of nonzero entries given absolute and relative tolerances.

fn error_count( &self, other: &Self, tol_abs: Scalar, tol_rel: Scalar, ) -> Option<usize>

Returns number of different entries given absolute and relative tolerances.

fn full_contraction(&self, tensor: &Self) -> TensorRank0

Returns the full contraction with another tensor.

fn is_zero(&self) -> bool

Checks whether the tensor is the zero tensor.

fn norm(&self) -> Quantity<Self::Unit>

Returns the tensor norm.

fn norm_inf(&self) -> Quantity<Self::Unit>

Returns the infinity norm.

fn norm_l1(&self) -> Quantity<Self::Unit>

Returns the L1 (Manhattan) norm.

fn norm_p_sum(&self, p: TensorRank0) -> TensorRank0

Returns the sum of p-th powers of absolute values (used internally by norm_p).

fn norm_p(&self, p: TensorRank0) -> Quantity<Self::Unit>

Returns the Minkowski (Lp) norm.

fn norm_squared(&self) -> Quantity<Square<Self::Unit>>

where Self::Unit: UnitMul<Self::Unit>,

Returns the tensor norm squared, which carries the square of its unit.

fn normalize(&mut self)

Normalizes the tensor in place.

fn sub_abs(&self, other: &Self) -> Self

Returns the positive difference of the two tensors.

fn sub_rel(&self, other: &Self) -> Self

Returns the relative difference of the two tensors.