Struct TensorRank3 

pub struct TensorRank3<const D: usize, I, J, K, U = Dimensionless>(/* private fields */);

A d-dimensional tensor of rank 3.

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

Trait Implementations

impl<const D: usize, I, J, K, U> Add<&TensorRank3<D, I, J, K, U>> for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the + operator.

fn add(self, tensor_rank_3: &Self) -> Self::Output

Performs the + operation.

impl<const D: usize, I, J, K, U> Add<TensorRank3<D, I, J, K, U>> for &TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the + operator.

fn add(self, tensor_rank_3: TensorRank3<D, I, J, K, U>) -> Self::Output

Performs the + operation.

impl<const D: usize, I, J, K, U> Add for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the + operator.

fn add(self, tensor_rank_3: Self) -> Self::Output

Performs the + operation.

impl<const D: usize, I, J, K, U> AddAssign<&TensorRank3<D, I, J, K, U>> for TensorRank3<D, I, J, K, U>

fn add_assign(&mut self, tensor_rank_3: &Self)

Performs the += operation.

impl<const D: usize, I, J, K, U> AddAssign for TensorRank3<D, I, J, K, U>

fn add_assign(&mut self, tensor_rank_3: Self)

Performs the += operation.

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

fn eq(a: Self, b: TensorRank3<D, I, J, K>) -> Result<(), AssertionError>

fn eq_within_tols( tols: &Assert, a: Self, b: TensorRank3<D, I, J, K>, ) -> Result<(), AssertionError>

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

fn eq_within_fd_tol( tols: &Assert, a: Self, b: TensorRank3<D, I, J, K>, ) -> Result<(), AssertionError>

impl<const D: usize, I, J, K, U> Clone for TensorRank3<D, I, J, K, 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, K, U> Debug for TensorRank3<D, I, J, K, U>

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

Formats the value using the given formatter.

impl<const D: usize, I, J, K, U> Default for TensorRank3<D, I, J, K, U>

fn default() -> Self

Returns the “default value” for a type.

impl<const D: usize, I, J, K, U> Display for TensorRank3<D, I, J, K, U>

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

Formats the value using the given formatter.

impl<const D: usize, I, J, K, U> Div<&f64> for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the / operator.

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

Performs the / operation.

impl<const D: usize, I, J, K, U> Div<f64> for &TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the / operator.

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

Performs the / operation.

impl<const D: usize, I, J, K, U> Div<f64> for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the / operator.

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

Performs the / operation.

impl<const D: usize, I, J, K, U> DivAssign<&f64> for TensorRank3<D, I, J, K, U>

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

Performs the /= operation.

impl<const D: usize, I, J, K, U> DivAssign<f64> for TensorRank3<D, I, J, K, U>

fn div_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the /= operation.

impl<const D: usize, I, J, K, U> FiniteDifference for TensorRank3<D, I, J, K, U>

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

impl<const D: usize, I, J, K, U> From<[[[f64; D]; D]; D]> for TensorRank3<D, I, J, K, U>

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

Converts to this type from the input type.

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

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

Creates a value from an iterator.

impl<const D: usize, I, J, K, L, U> FromIterator<TensorRank3<D, J, K, L, U>> for TensorRank4<D, I, J, K, L, U>

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

Creates a value from an iterator.

impl<const D: usize, I, J, K, U> Index<usize> for TensorRank3<D, I, J, K, U>

type Output = TensorRank2<D, J, K, U>

The returned type after indexing.

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

Performs the indexing (container[index]) operation.

impl<const D: usize, I, J, K, U> IndexMut<usize> for TensorRank3<D, I, J, K, U>

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

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

impl<const D: usize, I, J, K, U> IntoIterator for TensorRank3<D, I, J, K, U>

type Item = TensorRank2<D, J, K, U>

The type of the elements being iterated over.

type IntoIter = IntoIter<<TensorRank3<D, I, J, K, U> 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, I, J, K, U> Mul<&f64> for &TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the * operator.

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

Performs the * operation.

impl<const D: usize, I, J, K, U> Mul<&f64> for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the * operator.

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

Performs the * operation.

impl<const D: usize, I, J, K, U> Mul<f64> for &TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the * operator.

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

Performs the * operation.

impl<const D: usize, I, J, K, U> Mul<f64> for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the * operator.

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

Performs the * operation.

impl<const D: usize, I, J, K, U> MulAssign<&f64> for TensorRank3<D, I, J, K, U>

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

Performs the *= operation.

impl<const D: usize, I, J, K, U> MulAssign<f64> for TensorRank3<D, I, J, K, U>

fn mul_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the *= operation.

impl<const D: usize, I, J, K, U> PartialEq for TensorRank3<D, I, J, K, 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<const D: usize, I, J, K, U> Sub<&TensorRank3<D, I, J, K, U>> for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_3: &Self) -> Self::Output

Performs the - operation.

impl<const D: usize, I, J, K, U> Sub for &TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_3: Self) -> Self::Output

Performs the - operation.

impl<const D: usize, I, J, K, U> Sub for TensorRank3<D, I, J, K, U>

type Output = TensorRank3<D, I, J, K, U>

The resulting type after applying the - operator.

fn sub(self, tensor_rank_3: Self) -> Self::Output

Performs the - operation.

impl<const D: usize, I, J, K, U> SubAssign<&TensorRank3<D, I, J, K, U>> for TensorRank3<D, I, J, K, U>

fn sub_assign(&mut self, tensor_rank_3: &Self)

Performs the -= operation.

impl<const D: usize, I, J, K, U> SubAssign for TensorRank3<D, I, J, K, U>

fn sub_assign(&mut self, tensor_rank_3: Self)

Performs the -= operation.

impl<'a, const D: usize, I, J, K, U> Sum<&'a TensorRank3<D, I, J, K, U>> for TensorRank3<D, I, J, K, U>

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

where Ii: Iterator<Item = &'a Self>,

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

impl<const D: usize, I, J, K, U> Sum for TensorRank3<D, I, J, K, U>

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, I, J, K, U> Tensor for TensorRank3<D, I, J, K, U>

type Item = TensorRank2<D, J, K, 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.

impl<const D: usize, I, J, K, U> TensorArray for TensorRank3<D, I, J, K, U>

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

The type of array corresponding to the tensor.

type Item = TensorRank2<D, J, K, U>

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 zero() -> Self

Returns the zero tensor.