Type Alias RightCauchyGreenDeformation

pub type RightCauchyGreenDeformation = TensorRank2<3, 0, 0>;

The right Cauchy-Green deformation $\mathbf{C}$.

Aliased Type

struct RightCauchyGreenDeformation(/* private fields */);

Implementations

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

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

Returns a rank-2 tensor constructed from a dyad of the given vectors.

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>)

Returns the LU decomposition of the rank-2 tensor.

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

Returns the inverse of the LU decomposition of the rank-2 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 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 copy 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> 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> 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 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> 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 From<TensorRank2<3, 0, 1>> for TensorRank2<3, 0, 0>

fn from(tensor_rank_2: TensorRank2<3, 0, 1>) -> Self

Converts to this type from the input type.

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

fn from(tensor_rank_2: TensorRank2<3, 1, 0>) -> 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<f64>>) -> 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> Hessian for TensorRank2<D, I, J>

fn is_positive_definite(&self) -> bool

Checks whether the Hessian is positive-definite.

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> 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 W: usize> Mul<&TensorRank1List<D, J, W>> for TensorRank2<D, I, J>

type Output = TensorRank1List<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<&TensorRank1Vec<D, J>> for TensorRank2<D, I, J>

type Output = TensorRank1Vec<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<&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> 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<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 W: usize> Mul<TensorRank1List<D, J, W>> for TensorRank2<D, I, J>

type Output = TensorRank1List<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<TensorRank1Vec<D, J>> for TensorRank2<D, I, J>

type Output = TensorRank1Vec<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<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<TensorRank2List2D<D, J, K, W, X>> for TensorRank2<D, I, J>

type Output = TensorRank2List2D<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> Mul<TensorRank2Vec2D<D, J, K>> for TensorRank2<D, I, J>

type Output = TensorRank2Vec2D<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> 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<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: &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<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 cholesky_decomposition(&self) -> Result<TensorRank2<D, I, J>, TensorError>

Returns the Cholesky decomposition of the rank-2 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 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> 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 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 full_contraction(&self, tensor: &Self) -> TensorRank0

Returns the full contraction with another tensor.

fn get_at(&self, _indices: &[usize]) -> &TensorRank0

Returns a reference to the entry at the specified indices.

fn get_at_mut(&mut self, _indices: &[usize]) -> &mut TensorRank0

Returns a mutable reference to the entry at the specified indices.

fn is_zero(&self) -> bool

Checks whether the tensor is the zero tensor.

fn norm(&self) -> TensorRank0

Returns the tensor 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.

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.