Struct TensorRank2 

pub struct TensorRank2<const D: usize, const I: usize, const J: usize>(/* private fields */);

A d-dimensional tensor of rank 2.

D is the dimension, I, J are the configurations.

Implementations

impl<const I: usize, const J: usize> TensorRank2<3, I, J>

pub const fn const_from(array: [[TensorRank0; 3]; 3]) -> Self

Associated function for const type conversion.

impl<const I: usize, const J: usize> TensorRank2<4, I, J>

pub const fn const_from(array: [[TensorRank0; 4]; 4]) -> Self

Associated function for const type conversion.

impl<const D: usize, const I: usize, const J: usize> TensorRank2<D, I, J>

pub const fn as_ptr(&self) -> *const TensorRank1<D, J>

Returns a raw pointer to the slice’s buffer.

pub fn as_tensor_rank_1(&self) -> TensorRank1<9, 88>

Returns the rank-2 tensor reshaped as a rank-1 tensor.

pub fn determinant(&self) -> TensorRank0

Returns the determinant of the rank-2 tensor.

pub fn inverse(&self) -> TensorRank2<D, J, I>

Returns the inverse of the rank-2 tensor.

pub fn inverse_and_determinant(&self) -> (TensorRank2<D, J, I>, TensorRank0)

Returns the inverse and determinant of the rank-2 tensor.

pub fn inverse_transpose(&self) -> Self

Returns the inverse transpose of the rank-2 tensor.

pub fn inverse_transpose_and_determinant(&self) -> (Self, TensorRank0)

Returns the inverse transpose and determinant of the rank-2 tensor.

pub fn lu_decomposition( &self, ) -> (TensorRank2<D, I, 88>, TensorRank2<D, 88, J>, Vec<usize>)

Returns the LU decomposition of the rank-2 tensor.

pub fn lu_decomposition_inverse( &self, ) -> (TensorRank2<D, I, 88>, TensorRank2<D, 88, J>, Vec<usize>)

Returns the inverse of the LU decomposition of the rank-2 tensor.

impl<const I: usize> TensorRank2<3, I, I>

pub fn logm(&self) -> Result<Self, TensorError>

Returns the matrix logarithm of the 3x3 symmetric tensor.

pub fn dlogm(&self) -> Result<TensorRank4<3, I, I, I, I>, TensorError>

Returns the derivative of the matrix logarithm of the 3x3 symmetric tensor.

pub fn invariants(&self) -> TensorRank0List<3>

Returns the invariants of the 3x3 symmetric tensor.

Trait Implementations

impl<const D: usize, const I: usize, const J: usize> Add<&TensorRank2<D, I, J>> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the + operator.

fn add(self, tensor_rank_2: &Self) -> Self::Output

Performs the + operation.

impl<const D: usize, const I: usize, const J: usize> Add<TensorRank2<D, I, J>> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the + operator.

fn add(self, tensor_rank_2: TensorRank2<D, I, J>) -> Self::Output

Performs the + operation.

impl<const D: usize, const I: usize, const J: usize> Add for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the + operator.

fn add(self, tensor_rank_2: Self) -> Self::Output

Performs the + operation.

impl<const D: usize, const I: usize, const J: usize> AddAssign<&TensorRank2<D, I, J>> for TensorRank2<D, I, J>

fn add_assign(&mut self, tensor_rank_2: &Self)

Performs the += operation.

impl<const D: usize, const I: usize, const J: usize> AddAssign for TensorRank2<D, I, J>

fn add_assign(&mut self, tensor_rank_2: Self)

Performs the += operation.

impl<const D: usize, const I: usize, const J: usize> Clone for TensorRank2<D, I, J>

fn clone(&self) -> TensorRank2<D, I, J>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize, const N: usize, const O: usize, const P: usize> ContractAllIndicesWithFirstIndicesOf<&TensorRank2<D, I, M>, &TensorRank2<D, J, N>, &TensorRank2<D, K, O>, &TensorRank2<D, L, P>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank4<D, M, N, O, P>

fn contract_all_indices_with_first_indices_of( self, tensor_rank_2_a: &TensorRank2<D, I, M>, tensor_rank_2_b: &TensorRank2<D, J, N>, tensor_rank_2_c: &TensorRank2<D, K, O>, tensor_rank_2_d: &TensorRank2<D, L, P>, ) -> Self::Output

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize, const N: usize> ContractFirstSecondIndicesWithSecondIndicesOf<&TensorRank2<D, I, M>, &TensorRank2<D, J, N>> for TensorRank4<D, M, N, K, L>

type Output = TensorRank4<D, I, J, K, L>

fn contract_first_second_indices_with_second_indices_of( self, tensor_rank_2_a: &TensorRank2<D, I, M>, tensor_rank_2_b: &TensorRank2<D, J, N>, ) -> Self::Output

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize, const O: usize, const P: usize> ContractFirstThirdFourthIndicesWithFirstIndicesOf<&TensorRank2<D, I, M>, &TensorRank2<D, K, O>, &TensorRank2<D, L, P>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank4<D, M, J, O, P>

fn contract_first_third_fourth_indices_with_first_indices_of( self, tensor_rank_2_a: &TensorRank2<D, I, M>, tensor_rank_2_b: &TensorRank2<D, K, O>, tensor_rank_2_c: &TensorRank2<D, L, P>, ) -> Self::Output

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const N: usize> ContractSecondIndexWithFirstIndexOf<&TensorRank2<D, J, N>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank4<D, I, N, K, L>

fn contract_second_index_with_first_index_of( self, tensor_rank_2: &TensorRank2<D, J, N>, ) -> Self::Output

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> ContractThirdFourthIndicesWithFirstSecondIndicesOf<&TensorRank2<D, K, L>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank2<D, I, J>

fn contract_third_fourth_indices_with_first_second_indices_of( self, tensor_rank_2: &TensorRank2<D, K, L>, ) -> Self::Output

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> ContractThirdIndexWithFirstIndexOf<&TensorRank2<D, M, K>> for TensorRank4<D, I, J, M, L>

type Output = TensorRank4<D, I, J, K, L>

fn contract_third_index_with_first_index_of( &self, tensor_rank_2: &TensorRank2<D, M, K>, ) -> Self::Output

impl<const D: usize, const I: usize, const J: usize> Debug for TensorRank2<D, I, J>

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

Formats the value using the given formatter.

impl<const D: usize, const I: usize, const J: usize> Default for TensorRank2<D, I, J>

fn default() -> Self

Returns the “default value” for a type.

impl<const D: usize, const I: usize, const J: usize> Display for TensorRank2<D, I, J>

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

Formats the value using the given formatter.

impl<const D: usize, const I: usize, const J: usize> Div<&f64> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the / operator.

fn div(self, tensor_rank_0: &TensorRank0) -> Self::Output

Performs the / operation.

impl<const D: usize, const I: usize, const J: usize> Div<&f64> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the / operator.

fn div(self, tensor_rank_0: &TensorRank0) -> Self::Output

Performs the / operation.

impl<const D: usize, const I: usize, const J: usize> Div<TensorRank2<D, I, J>> for &TensorRank1<D, I>

type Output = TensorRank1<D, J>

The resulting type after applying the / operator.

fn div(self, tensor_rank_2: TensorRank2<D, I, J>) -> Self::Output

Performs the / operation.

impl<const I: usize, const J: usize, const K: usize, const L: usize> Div<TensorRank4<3, I, J, K, L>> for &TensorRank2<3, I, J>

type Output = TensorRank2<3, K, L>

The resulting type after applying the / operator.

fn div(self, tensor_rank_4: TensorRank4<3, I, J, K, L>) -> Self::Output

Performs the / operation.

impl<const D: usize, const I: usize, const J: usize> Div<f64> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the / operator.

fn div(self, tensor_rank_0: TensorRank0) -> Self::Output

Performs the / operation.

impl<const D: usize, const I: usize, const J: usize> Div<f64> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the / operator.

fn div(self, tensor_rank_0: TensorRank0) -> Self::Output

Performs the / operation.

impl<const D: usize, const I: usize, const J: usize> DivAssign<&f64> for TensorRank2<D, I, J>

fn div_assign(&mut self, tensor_rank_0: &TensorRank0)

Performs the /= operation.

impl<const D: usize, const I: usize, const J: usize> DivAssign<f64> for TensorRank2<D, I, J>

fn div_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the /= operation.

impl<C1, C2> ElasticIV<TensorRank2<3, 2, 0>, TensorRank4<3, 2, 0, 1, 0>, TensorRank4<3, 1, 0, 2, 0>, TensorRank4<3, 2, 0, 2, 0>> for Multiplicative<C1, C2>

where C1: Elastic, C2: Elastic,

fn cauchy_stress_foo( &self, deformation_gradient: &DeformationGradient, deformation_gradient_2: &DeformationGradient2, ) -> Result<CauchyStress, ConstitutiveError>

Calculates and returns the Cauchy stress.

\boldsymbol{\sigma} = \frac{1}{J_2}\,\boldsymbol{\sigma}_1

fn cauchy_tangent_stiffness_foo( &self, deformation_gradient: &DeformationGradient, deformation_gradient_2: &DeformationGradient2, ) -> Result<CauchyTangentStiffness, ConstitutiveError>

Calculates and returns the tangent stiffness associated with the Cauchy stress.

\boldsymbol{\mathcal{T}} = \frac{1}{J_2}\,\boldsymbol{\mathcal{T}}_1\cdot\mathbf{F}_2^{-T}

fn first_piola_kirchhoff_stress_foo( &self, deformation_gradient: &DeformationGradient, deformation_gradient_2: &DeformationGradient2, ) -> Result<FirstPiolaKirchhoffStress, ConstitutiveError>

Calculates and returns the first Piola-Kirchhoff stress.

\mathbf{P} = \mathbf{P}_1\cdot\mathbf{F}_2^{-T}

fn second_piola_kirchhoff_stress_foo( &self, deformation_gradient: &DeformationGradient, deformation_gradient_2: &DeformationGradient2, ) -> Result<SecondPiolaKirchhoffStress, ConstitutiveError>

Calculates and returns the second Piola-Kirchhoff stress.

\mathbf{S} = \mathbf{F}_2^{-1}\cdot\mathbf{S}_1\cdot\mathbf{F}_2^{-T}

fn internal_variables_residual( &self, deformation_gradient: &DeformationGradient, deformation_gradient_2: &DeformationGradient2, ) -> Result<DeformationGradient2, ConstitutiveError>

Calculates and returns the residual associated with the second deformation gradient.

\mathbf{R} = \mathbf{P}_2 - \mathbf{M}_1\cdot\mathbf{F}_2^{-T}

fn internal_variables_tangents( &self, deformation_gradient: &DeformationGradient, deformation_gradient_2: &DeformationGradient2, ) -> Result<(TensorRank4<3, 2, 0, 1, 0>, TensorRank4<3, 1, 0, 2, 0>, FirstPiolaKirchhoffTangentStiffness2), ConstitutiveError>

Calculates and returns the tangents associated with the internal variables.

\frac{\partial P_{iJ}}{\partial F_{KL}^2} = -P_{iL}F_{KJ}^{2-T} - \mathcal{C}_{iJmL}F_{mK}^1

\frac{\partial R_{IJ}}{\partial F_{kL}} = -F_{IL}^{2-T}P_{kJ} - F_{mI}^1\mathcal{C}_{mJkL}

\frac{\partial R_{IJ}}{\partial F_{KL}^2} = \mathcal{C}_{IJKL}^2 + F_{IM}^1P_{ML}{F_{KJ}^{2-T}} - \frac{\partial R_{IJ}}{\partial F_{mL}}\,F_{mK}^1

fn internal_variables_initial(&self) -> DeformationGradient2

Returns the initial value for the internal variables.

fn internal_variables_constraints(&self) -> (&[usize], usize)

Returns the constraint indices for the internal variables.

fn first_piola_kirchhoff_tangent_stiffness_foo( &self, deformation_gradient: &DeformationGradient, internal_variables: &V, ) -> Result<FirstPiolaKirchhoffTangentStiffness, ConstitutiveError>

Calculates and returns the tangent stiffness associated with the first Piola-Kirchhoff stress.

fn second_piola_kirchhoff_tangent_stiffness_foo( &self, deformation_gradient: &DeformationGradient, internal_variables: &V, ) -> Result<SecondPiolaKirchhoffTangentStiffness, ConstitutiveError>

Calculates and returns the tangent stiffness associated with the second Piola-Kirchhoff stress.

impl<const J: usize> From<&TensorRank2<3, 2, J>> for &TensorRank2<3, 1, J>

fn from(tensor_rank_2: &TensorRank2<3, 2, J>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> From<&TensorRank4<D, I, J, K, L>> for TensorRank2<9, 88, 99>

fn from(tensor_rank_4: &TensorRank4<D, I, J, K, L>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<[[f64; D]; D]> for TensorRank2<D, I, J>

fn from(array: [[TensorRank0; D]; D]) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<(&TensorRank1<D, I>, &TensorRank1<D, J>)> for TensorRank2<D, I, J>

fn from((vector_a, vector_b): (&TensorRank1<D, I>, &TensorRank1<D, J>)) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<(&TensorRank1<D, I>, TensorRank1<D, J>)> for TensorRank2<D, I, J>

fn from((vector_a, vector_b): (&TensorRank1<D, I>, TensorRank1<D, J>)) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<(TensorRank1<D, I>, &TensorRank1<D, J>)> for TensorRank2<D, I, J>

fn from((vector_a, vector_b): (TensorRank1<D, I>, &TensorRank1<D, J>)) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<(TensorRank1<D, I>, TensorRank1<D, J>)> for TensorRank2<D, I, J>

fn from((vector_a, vector_b): (TensorRank1<D, I>, TensorRank1<D, J>)) -> Self

Converts to this type from the input type.

impl From<TensorRank2<3, 0, 0>> for TensorRank2<3, 1, 1>

fn from(tensor_rank_2: TensorRank2<3, 0, 0>) -> Self

Converts to this type from the input type.

impl From<TensorRank2<3, 0, 0>> for TensorRank2<3, 2, 2>

fn from(tensor_rank_2: TensorRank2<3, 0, 0>) -> Self

Converts to this type from the input type.

impl<const J: usize> From<TensorRank2<3, 0, J>> for TensorRank2<3, 1, J>

fn from(tensor_rank_2: TensorRank2<3, 0, J>) -> Self

Converts to this type from the input type.

impl<const J: usize> From<TensorRank2<3, 1, J>> for TensorRank2<3, 0, J>

fn from(tensor_rank_2: TensorRank2<3, 1, J>) -> Self

Converts to this type from the input type.

impl<const J: usize> From<TensorRank2<3, 1, J>> for TensorRank2<3, 2, J>

fn from(tensor_rank_2: TensorRank2<3, 1, J>) -> Self

Converts to this type from the input type.

impl<const J: usize> From<TensorRank2<3, 2, J>> for TensorRank2<3, 1, J>

fn from(tensor_rank_2: TensorRank2<3, 2, J>) -> Self

Converts to this type from the input type.

impl<const I: usize> From<TensorRank2<3, I, 0>> for TensorRank2<3, I, 2>

fn from(tensor_rank_2: TensorRank2<3, I, 0>) -> Self

Converts to this type from the input type.

impl<const I: usize> From<TensorRank2<3, I, 1>> for TensorRank2<3, I, 0>

fn from(tensor_rank_2: TensorRank2<3, I, 1>) -> Self

Converts to this type from the input type.

impl<const I: usize> From<TensorRank2<3, I, 2>> for TensorRank2<3, I, 0>

fn from(tensor_rank_2: TensorRank2<3, I, 2>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<TensorRank2<D, I, J>> for Vec<Vec<TensorRank0>>

fn from(tensor: TensorRank2<D, I, J>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<TensorRank2<D, I, J>> for Vector

fn from(tensor_rank_2: TensorRank2<D, I, J>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> From<TensorRank4<D, I, J, K, L>> for TensorRank2<9, 88, 99>

fn from(tensor_rank_4: TensorRank4<D, I, J, K, L>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<Vec<Vec<f64>>> for TensorRank2<D, I, J>

fn from(vec: Vec<Vec<TensorRank0>>) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> From<Vector> for TensorRank2<D, I, J>

fn from(_vector: Vector) -> Self

Converts to this type from the input type.

impl<const D: usize, const I: usize, const J: usize> FromIterator<TensorRank1<D, J>> for TensorRank2<D, I, J>

fn from_iter<Ii: IntoIterator<Item = TensorRank1<D, J>>>( into_iterator: Ii, ) -> Self

Creates a value from an iterator.

impl<const D: usize, const I: usize, const J: usize, const K: usize> FromIterator<TensorRank2<D, J, K>> for TensorRank3<D, I, J, K>

fn from_iter<Ii: IntoIterator<Item = TensorRank2<D, J, K>>>( into_iterator: Ii, ) -> Self

Creates a value from an iterator.

impl<const D: usize, const I: usize, const J: usize> Hessian for TensorRank2<D, I, J>

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, const I: usize, const J: usize> Index<usize> for TensorRank2<D, I, J>

type Output = TensorRank1<D, J>

The returned type after indexing.

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

Performs the indexing (container[index]) operation.

impl<const D: usize, const I: usize, const J: usize> IndexMut<usize> for TensorRank2<D, I, J>

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

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

impl<const D: usize, const I: usize, const J: usize> IntoIterator for TensorRank2<D, I, J>

type Item = TensorRank1<D, J>

The type of the elements being iterated over.

type IntoIter = IntoIter<<TensorRank2<D, I, J> as IntoIterator>::Item, D>

Which kind of iterator are we turning this into?

fn into_iter(self) -> Self::IntoIter

Creates an iterator from a value.

impl<const D: usize, const I: usize, const J: usize> Jacobian for TensorRank2<D, I, J>

fn fill_into(self, vector: &mut Vector)

Fills the Jacobian into a vector.

fn fill_into_chained(self, other: Vector, vector: &mut Vector)

Fills the Jacobian chained with a vector into another vector.

fn retain_from(self, _retained: &[bool]) -> Vector

Return only the retained indices.

fn zero_out(&mut self, _indices: &[usize])

Zero out the specified indices.

impl<const D: usize, const I: usize, const J: usize, const W: usize> Mul<&TensorList<TensorRank1<D, J>, W>> for &TensorRank2<D, I, J>

type Output = TensorList<TensorRank1<D, I>, W>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_list: &TensorRank1List<D, J, W>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const W: usize> Mul<&TensorList<TensorRank1<D, J>, W>> for TensorRank2<D, I, J>

type Output = TensorList<TensorRank1<D, I>, W>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_list: &TensorRank1List<D, J, W>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&TensorRank1<D, J>> for &TensorRank2<D, I, J>

type Output = TensorRank1<D, I>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1: &TensorRank1<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&TensorRank1<D, J>> for TensorRank2<D, I, J>

type Output = TensorRank1<D, I>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1: &TensorRank1<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&TensorRank2<D, I, J>> for &Matrix

type Output = Vector

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, I, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&TensorRank2<D, I, J>> for &Vector

type Output = f64

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, I, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<&TensorRank2<D, J, K>> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, K>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const W: usize, const X: usize> Mul<&TensorRank2<D, J, K>> for TensorRank2List2D<D, I, J, W, X>

type Output = TensorList<TensorList<TensorRank2<D, I, K>, W>, X>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<&TensorRank2<D, J, K>> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, K>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<&TensorRank2<D, J, K>> for TensorRank2Vec2D<D, I, J>

type Output = TensorVector<TensorVector<TensorRank2<D, I, K>>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> Mul<&TensorRank2<D, L, M>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank4<D, I, J, K, M>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: &TensorRank2<D, L, M>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> Mul<&TensorRank4<D, M, J, K, L>> for &TensorRank2<D, I, M>

type Output = TensorRank4<D, I, J, K, L>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_4: &TensorRank4<D, M, J, K, L>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> Mul<&TensorRank4<D, M, J, K, L>> for TensorRank2<D, I, M>

type Output = TensorRank4<D, I, J, K, L>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_4: &TensorRank4<D, M, J, K, L>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&TensorVector<TensorRank1<D, J>>> for &TensorRank2<D, I, J>

type Output = TensorVector<TensorRank1<D, I>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_vec: &TensorRank1Vec<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&TensorVector<TensorRank1<D, J>>> for TensorRank2<D, I, J>

type Output = TensorVector<TensorRank1<D, I>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_vec: &TensorRank1Vec<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&f64> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_0: &TensorRank0) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<&f64> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_0: &TensorRank0) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const W: usize, const X: usize> Mul<TensorList<TensorList<TensorRank2<D, J, K>, W>, X>> for &TensorRank2<D, I, J>

type Output = TensorList<TensorList<TensorRank2<D, I, K>, W>, X>

The resulting type after applying the * operator.

fn mul( self, tensor_rank_2_list_2d: TensorRank2List2D<D, J, K, W, X>, ) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const W: usize, const X: usize> Mul<TensorList<TensorList<TensorRank2<D, J, K>, W>, X>> for TensorRank2<D, I, J>

type Output = TensorList<TensorList<TensorRank2<D, I, K>, W>, X>

The resulting type after applying the * operator.

fn mul( self, tensor_rank_2_list_2d: TensorRank2List2D<D, J, K, W, X>, ) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const W: usize> Mul<TensorList<TensorRank1<D, J>, W>> for &TensorRank2<D, I, J>

type Output = TensorList<TensorRank1<D, I>, W>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_list: TensorRank1List<D, J, W>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const W: usize> Mul<TensorList<TensorRank1<D, J>, W>> for TensorRank2<D, I, J>

type Output = TensorList<TensorRank1<D, I>, W>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_list: TensorRank1List<D, J, W>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<TensorRank1<D, J>> for &TensorRank2<D, I, J>

type Output = TensorRank1<D, I>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1: TensorRank1<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<TensorRank1<D, J>> for TensorRank2<D, I, J>

type Output = TensorRank1<D, I>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1: TensorRank1<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<TensorRank2<D, J, K>> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, K>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const W: usize, const X: usize> Mul<TensorRank2<D, J, K>> for TensorRank2List2D<D, I, J, W, X>

type Output = TensorList<TensorList<TensorRank2<D, I, K>, W>, X>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<TensorRank2<D, J, K>> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, K>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<TensorRank2<D, J, K>> for TensorRank2Vec2D<D, I, J>

type Output = TensorVector<TensorVector<TensorRank2<D, I, K>>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: TensorRank2<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> Mul<TensorRank2<D, L, M>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank4<D, I, J, K, M>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2: TensorRank2<D, L, M>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> Mul<TensorRank4<D, M, J, K, L>> for &TensorRank2<D, I, M>

type Output = TensorRank4<D, I, J, K, L>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_4: TensorRank4<D, M, J, K, L>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const M: usize> Mul<TensorRank4<D, M, J, K, L>> for TensorRank2<D, I, M>

type Output = TensorRank4<D, I, J, K, L>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_4: TensorRank4<D, M, J, K, L>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<TensorVector<TensorRank1<D, J>>> for &TensorRank2<D, I, J>

type Output = TensorVector<TensorRank1<D, I>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_vec: TensorRank1Vec<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<TensorVector<TensorRank1<D, J>>> for TensorRank2<D, I, J>

type Output = TensorVector<TensorRank1<D, I>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_1_vec: TensorRank1Vec<D, J>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<TensorVector<TensorVector<TensorRank2<D, J, K>>>> for &TensorRank2<D, I, J>

type Output = TensorVector<TensorVector<TensorRank2<D, I, K>>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2_list_2d: TensorRank2Vec2D<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize> Mul<TensorVector<TensorVector<TensorRank2<D, J, K>>>> for TensorRank2<D, I, J>

type Output = TensorVector<TensorVector<TensorRank2<D, I, K>>>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_2_list_2d: TensorRank2Vec2D<D, J, K>) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<f64> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_0: TensorRank0) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> Mul<f64> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the * operator.

fn mul(self, tensor_rank_0: TensorRank0) -> Self::Output

Performs the * operation.

impl<const D: usize, const I: usize, const J: usize> MulAssign<&TensorRank2<D, J, J>> for TensorRank2<D, I, J>

fn mul_assign(&mut self, tensor_rank_2: &TensorRank2<D, J, J>)

Performs the *= operation.

impl<const D: usize, const I: usize, const J: usize> MulAssign<&f64> for TensorRank2<D, I, J>

fn mul_assign(&mut self, tensor_rank_0: &TensorRank0)

Performs the *= operation.

impl<const D: usize, const I: usize, const J: usize> MulAssign<TensorRank2<D, J, J>> for TensorRank2<D, I, J>

fn mul_assign(&mut self, tensor_rank_2: TensorRank2<D, J, J>)

Performs the *= operation.

impl<const D: usize, const I: usize, const J: usize> MulAssign<f64> for TensorRank2<D, I, J>

fn mul_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the *= operation.

impl<const D: usize, const I: usize, const J: usize> PartialEq for TensorRank2<D, I, J>

fn eq(&self, other: &TensorRank2<D, I, J>) -> 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<const D: usize, const I: usize, const J: usize> Rank2 for TensorRank2<D, I, J>

type Transpose = TensorRank2<D, J, I>

The type that is the transpose of the tensor.

fn deviatoric(&self) -> Self

Returns the deviatoric component of the rank-2 tensor.

fn deviatoric_and_trace(&self) -> (Self, TensorRank0)

Returns the deviatoric component and trace of the rank-2 tensor.

fn is_diagonal(&self) -> bool

Checks whether the tensor is a diagonal tensor.

fn is_identity(&self) -> bool

Checks whether the tensor is the identity tensor.

fn is_symmetric(&self) -> bool

Checks whether the tensor is a symmetric tensor.

fn squared_trace(&self) -> TensorRank0

Returns the trace of the rank-2 tensor squared.

fn trace(&self) -> TensorRank0

Returns the trace of the rank-2 tensor.

fn transpose(&self) -> Self::Transpose

Returns the transpose of the rank-2 tensor.

fn second_invariant(&self) -> TensorRank0

Returns the second invariant of the rank-2 tensor.

impl<const D: usize, const I: usize, const J: usize> Solution for TensorRank2<D, I, J>

fn decrement_from(&mut self, other: &Vector)

Decrements the solution from another vector.

fn decrement_from_chained(&mut self, other: &mut Vector, vector: Vector)

Decrements the solution chained with a vector from another vector.

fn decrement_from_retained(&mut self, _retained: &[bool], _other: &Vector)

Decrements the solution from another vector on retained entries.

impl<const D: usize, const I: usize, const J: usize> Sub<&TensorRank2<D, I, J>> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_2: &Self) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize> Sub<&Vector> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the - operator.

fn sub(self, vector: &Vector) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize> Sub<TensorRank2<D, I, J>> for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_2: TensorRank2<D, I, J>) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize> Sub<Vector> for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the - operator.

fn sub(self, vector: Vector) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize> Sub for &TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_2: Self) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize> Sub for TensorRank2<D, I, J>

type Output = TensorRank2<D, I, J>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_2: Self) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize> SubAssign<&TensorRank2<D, I, J>> for TensorRank2<D, I, J>

fn sub_assign(&mut self, tensor_rank_2: &Self)

Performs the -= operation.

impl<const D: usize, const I: usize, const J: usize> SubAssign for TensorRank2<D, I, J>

fn sub_assign(&mut self, tensor_rank_2: Self)

Performs the -= operation.

impl<const D: usize, const I: usize, const J: usize> Sum for TensorRank2<D, I, J>

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

where Ii: Iterator<Item = Self>,

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

impl<const D: usize, const I: usize, const J: usize> Tensor for TensorRank2<D, I, J>

type Item = TensorRank1<D, J>

The type of item encountered when iterating over the tensor.

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( &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) -> TensorRank0

Returns the tensor norm.

fn norm_inf(&self) -> TensorRank0

Returns the infinity norm.

fn norm_squared(&self) -> TensorRank0

Returns the tensor norm squared.

fn normalize(&mut self)

Normalizes the tensor.

fn normalized(self) -> Self

Returns the tensor normalized.

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.

impl<const D: usize, const I: usize, const J: usize> TensorArray for TensorRank2<D, I, J>

type Array = [[f64; D]; D]

The type of array corresponding to the tensor.

type Item = TensorRank1<D, J>

The type of item encountered when iterating over the tensor.

fn as_array(&self) -> Self::Array

Returns the tensor as an array.

fn identity() -> Self

Returns the identity tensor.

fn new(array: Self::Array) -> Self

Returns a tensor given an array.

fn zero() -> Self

Returns the zero tensor.

impl<const D: usize, const I: usize, const J: usize> StructuralPartialEq for TensorRank2<D, I, J>