Struct TensorRank4

pub struct TensorRank4<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize>(/* private fields */);

A d-dimensional tensor of rank 4.

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

Implementations

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> TensorRank4<D, I, J, K, L>

pub fn as_tensor_rank_2(&self) -> TensorRank2<9, 88, 99>

pub fn dyad_ij_kl( tensor_rank_2_a: &TensorRank2<D, I, J>, tensor_rank_2_b: &TensorRank2<D, K, L>, ) -> Self

pub fn dyad_ik_jl( tensor_rank_2_a: &TensorRank2<D, I, K>, tensor_rank_2_b: &TensorRank2<D, J, L>, ) -> Self

pub fn dyad_il_jk( tensor_rank_2_a: &TensorRank2<D, I, L>, tensor_rank_2_b: &TensorRank2<D, J, K>, ) -> Self

pub fn dyad_il_kj( tensor_rank_2_a: &TensorRank2<D, I, L>, tensor_rank_2_b: &TensorRank2<D, K, J>, ) -> Self

Trait Implementations

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

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

The resulting type after applying the + operator.

fn add(self, tensor_rank_4: &Self) -> Self::Output

Performs the + operation.

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

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

The resulting type after applying the + operator.

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

Performs the + operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Add for TensorRank4<D, I, J, K, L>

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

The resulting type after applying the + operator.

fn add(self, tensor_rank_4: Self) -> Self::Output

Performs the + operation.

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

fn add_assign(&mut self, tensor_rank_4: &Self)

Performs the += operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> AddAssign for TensorRank4<D, I, J, K, L>

fn add_assign(&mut self, tensor_rank_4: Self)

Performs the += operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Clone for TensorRank4<D, I, J, K, L>

fn clone(&self) -> TensorRank4<D, I, J, K, L>

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, 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> ContractSecondFourthIndicesWithFirstIndicesOf<&TensorRank1<D, J>, &TensorRank1<D, L>> for TensorRank4<D, I, J, K, L>

type Output = TensorRank2<D, I, K>

fn contract_second_fourth_indices_with_first_indices_of( &self, tensor_rank_1_a: &TensorRank1<D, J>, tensor_rank_1_b: &TensorRank1<D, L>, ) -> 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> Debug for TensorRank4<D, I, J, K, L>

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

Formats the value using the given formatter.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Display for TensorRank4<D, I, J, K, L>

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

Formats the value using the given formatter.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Div<&f64> for TensorRank4<D, I, J, K, L>

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

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, const K: usize, const L: usize> Div<f64> for &TensorRank4<D, I, J, K, L>

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

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, const K: usize, const L: usize> Div<f64> for TensorRank4<D, I, J, K, L>

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

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, const K: usize, const L: usize> DivAssign<&f64> for TensorRank4<D, I, J, K, L>

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

Performs the /= operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> DivAssign<f64> for TensorRank4<D, I, J, K, L>

fn div_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the /= operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> From<TensorRank4<D, I, J, K, L>> for Vec<Vec<Vec<Vec<f64>>>>

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, const K: usize, const L: usize> From<Vec<Vec<Vec<Vec<f64>>>>> for TensorRank4<D, I, J, K, L>

fn from(vec_rank_4: Vec<Vec<Vec<Vec<f64>>>>) -> 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> FromIterator<TensorRank3<D, J, K, L>> for TensorRank4<D, I, J, K, L>

fn from_iter<Ii: IntoIterator<Item = TensorRank3<D, J, K, L>>>( into_iterator: Ii, ) -> Self

Creates a value from an iterator.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize, const W: usize> FromIterator<TensorRank4<D, I, J, K, L>> for TensorRank4List<D, I, J, K, L, W>

fn from_iter<Ii: IntoIterator<Item = TensorRank4<D, I, J, K, L>>>( into_iterator: Ii, ) -> Self

Creates a value from an iterator.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Hessian for TensorRank4<D, I, J, K, L>

fn is_positive_definite(&self) -> bool

Checks whether the Hessian is positive-definite.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Index<usize> for TensorRank4<D, I, J, K, L>

type Output = TensorRank3<D, J, K, L>

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, const K: usize, const L: usize> IndexMut<usize> for TensorRank4<D, I, J, K, L>

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, 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> Mul<&f64> for TensorRank4<D, I, J, K, L>

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

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 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> Mul<f64> for TensorRank4<D, I, J, K, L>

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

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 L: usize> MulAssign<&f64> for TensorRank4<D, I, J, K, L>

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

Performs the *= operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> MulAssign<f64> for TensorRank4<D, I, J, K, L>

fn mul_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the *= operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> PartialEq for TensorRank4<D, I, J, K, L>

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, const K: usize, const L: usize> Sub<&TensorRank4<D, I, J, K, L>> for TensorRank4<D, I, J, K, L>

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

The resulting type after applying the - operator.

fn sub(self, tensor_rank_4: &Self) -> Self::Output

Performs the - operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Sub for TensorRank4<D, I, J, K, L>

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

The resulting type after applying the - operator.

fn sub(self, tensor_rank_4: Self) -> Self::Output

Performs the - operation.

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

fn sub_assign(&mut self, tensor_rank_4: &Self)

Performs the -= operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> SubAssign for TensorRank4<D, I, J, K, L>

fn sub_assign(&mut self, tensor_rank_4: Self)

Performs the -= operation.

impl<const D: usize, const I: usize, const J: usize, const K: usize, const L: usize> Sum for TensorRank4<D, I, J, K, L>

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, const K: usize, const L: usize> Tensor for TensorRank4<D, I, J, K, L>

type Item = TensorRank3<D, J, K, L>

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, const K: usize, const L: usize> TensorArray for TensorRank4<D, I, J, K, L>

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

The type of array corresponding to the tensor.

type Item = TensorRank3<D, J, K, L>

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.