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TensorTuple

Struct TensorTuple

pub struct TensorTuple<T1, T2>(pub T1, pub T2)
where
    T1: Tensor,
    T2: Tensor;

Expand description

A fixed-size nested collection of different tensors.

Tuple Fields§

§0: T1§1: T2

Trait Implementations§

impl<T1, T2> Add<&TensorTuple<T1, T2>> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the + operator.

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

Performs the + operation. Read more

impl<T1, T2> Add for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the + operator.

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

Performs the + operation. Read more

impl<T1, T2> AddAssign<&TensorTuple<T1, T2>> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

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

Performs the += operation. Read more

impl<T1, T2> AddAssign for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn add_assign(&mut self, tensor_tuple: Self)

Performs the += operation. Read more

impl<T1, T2> AssertEq for TensorTuple<T1, T2>
where T1: Display + PartialEq + Tensor, T2: Display + PartialEq + Tensor,

fn eq(a: Self, b: TensorTuple<T1, T2>) -> Result<(), AssertionError>

fn eq_within_tols( tols: &Assert, a: Self, b: TensorTuple<T1, T2>, ) -> Result<(), AssertionError>

impl<T1, T2> Clone for TensorTuple<T1, T2>
where T1: Tensor + Clone, T2: Tensor + Clone,

fn clone(&self) -> TensorTuple<T1, T2>

Returns a duplicate of the value. Read more

1.0.0 (const: unstable) · Source§

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

Performs copy-assignment from source. Read more

impl<T1, T2> Debug for TensorTuple<T1, T2>
where T1: Tensor + Debug, T2: Tensor + Debug,

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

Formats the value using the given formatter. Read more

impl<T1, T2> Default for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn default() -> Self

Returns the “default value” for a type. Read more

impl<T1, T2> Display for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

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

Formats the value using the given formatter. Read more

impl<T1, T2> Div<&f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the / operator.

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

Performs the / operation. Read more

impl<T0, T1, T4, T5> Div<TensorTuple<T0, T1>> for &TensorTuple<T4, T5>
where T0: Tensor, T1: Tensor, T4: Tensor, T5: Tensor,

type Output = TensorTuple<T4, T5>

The resulting type after applying the / operator.

fn div(self, _tensor_tuple: TensorTuple<T0, T1>) -> Self::Output

Performs the / operation. Read more

impl<T1, T2> Div<f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the / operator.

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

Performs the / operation. Read more

impl<T1, T2> DivAssign<&f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

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

Performs the /= operation. Read more

impl<T1, T2> DivAssign<f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn div_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the /= operation. Read more

impl<B1, B2, S1, S2, const D: usize> ElasticViscoplasticElements<TensorTuple<S1, S2>, D> for Blocks<B1, B2>
where B1: ElasticViscoplasticElements<S1, D>, B2: ElasticViscoplasticElements<S2, D>, S1: Tensor, S2: Tensor,

fn initial_state(&self) -> TensorTuple<S1, S2>

fn nodal_forces_into( &self, nodal_coordinates: &NodalCoordinates<D>, state_variables: &TensorTuple<S1, S2>, nodal_forces: &mut NodalForcesSolid<D>, ) -> Result<(), ElementModelError>

fn nodal_stiffnesses_into( &self, nodal_coordinates: &NodalCoordinates<D>, state_variables: &TensorTuple<S1, S2>, nodal_stiffnesses: &mut NodalStiffnessesSolid<D>, ) -> Result<(), ElementModelError>

fn state_variables_evolution( &self, nodal_coordinates: &NodalCoordinates<D>, state_variables: &TensorTuple<S1, S2>, ) -> Result<TensorTuple<S1, S2>, ElementModelError>

fn nodal_forces( &self, nodal_coordinates: &NodalCoordinates<D>, state_variables: &S, ) -> Result<NodalForcesSolid<D>, ElementModelError>

fn nodal_stiffnesses( &self, nodal_coordinates: &NodalCoordinates<D>, state_variables: &S, ) -> Result<NodalStiffnessesSolid<D>, ElementModelError>

impl<'a, T1, T2> From<&'a TensorTuple<T1, T2>> for (&'a T1, &'a T2)
where T1: Tensor, T2: Tensor,

fn from(tensor_tuple: &'a TensorTuple<T1, T2>) -> Self

Converts to this type from the input type.

impl<T1, T2> From<(T1, T2)> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn from(tuple: (T1, T2)) -> Self

Converts to this type from the input type.

impl<T1, T2> From<TensorTuple<T1, T2>> for (T1, T2)
where T1: Tensor, T2: Tensor,

fn from(tensor_tuple: TensorTuple<T1, T2>) -> Self

Converts to this type from the input type.

impl<T1, T2> From<Vector> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn from(_vector: Vector) -> 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> Hessian for TensorTuple<TensorRank4<D, I, J, I, J>, TensorTuple<TensorRank4<D, K, L, I, J>, TensorTuple<TensorRank4<D, I, J, K, L>, TensorRank4<D, K, L, K, L>>>>

fn entry(&self, row: usize, column: usize) -> TensorRank0

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

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<B1, B2, S1, S2, const D: usize> HyperelasticViscoplasticElements<TensorTuple<S1, S2>, D> for Blocks<B1, B2>
where B1: HyperelasticViscoplasticElements<S1, D>, B2: HyperelasticViscoplasticElements<S2, D>, S1: Tensor, S2: Tensor,

fn helmholtz_free_energy( &self, nodal_coordinates: &NodalCoordinates<D>, state_variables: &TensorTuple<S1, S2>, ) -> Result<Scalar, ElementModelError>

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

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 K: usize, const L: usize> Mul<&TensorTuple<TensorRank2<D, I, J>, TensorRank2<D, K, L>>> for &Matrix

type Output = Vector

The resulting type after applying the * operator.

fn mul( self, tensor_tuple: &TensorTuple<TensorRank2<D, I, J>, TensorRank2<D, K, L>>, ) -> Self::Output

Performs the * operation. Read more

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

type Output = f64

The resulting type after applying the * operator.

fn mul( self, tensor_tuple: &TensorTuple<TensorRank2<D, I, J>, TensorRank2<D, K, L>>, ) -> Self::Output

Performs the * operation. Read more

impl<T1, T2> Mul<&f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the * operator.

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

Performs the * operation. Read more

impl<T1, T2> Mul<f64> for &TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the * operator.

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

Performs the * operation. Read more

impl<T1, T2> Mul<f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the * operator.

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

Performs the * operation. Read more

impl<T1, T2> MulAssign<&f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

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

Performs the *= operation. Read more

impl<T1, T2> MulAssign<f64> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn mul_assign(&mut self, tensor_rank_0: TensorRank0)

Performs the *= operation. Read more

impl<T1, T2> PartialEq for TensorTuple<T1, T2>
where T1: Tensor + PartialEq, T2: Tensor + PartialEq,

fn eq(&self, other: &TensorTuple<T1, T2>) -> bool

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

1.0.0 (const: unstable) · Source§

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> Solution for TensorTuple<TensorRank2<D, I, J>, TensorRank2<D, K, L>>

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<T1, T2> Sub<&TensorTuple<T1, T2>> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the - operator.

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

Performs the - operation. Read more

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

type Output = TensorTuple<TensorRank2<D, I, J>, TensorRank2<D, K, L>>

The resulting type after applying the - operator.

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

Performs the - operation. Read more

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

type Output = TensorTuple<TensorRank2<D, I, J>, TensorRank2<D, K, L>>

The resulting type after applying the - operator.

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

Performs the - operation. Read more

impl<T1, T2> Sub for &TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the - operator.

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

Performs the - operation. Read more

impl<T1, T2> Sub for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Output = TensorTuple<T1, T2>

The resulting type after applying the - operator.

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

Performs the - operation. Read more

impl<T1, T2> SubAssign<&TensorTuple<T1, T2>> for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

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

Performs the -= operation. Read more

impl<T1, T2> SubAssign for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

fn sub_assign(&mut self, tensor_tuple: Self)

Performs the -= operation. Read more

impl<T1, T2> Sum for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

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<T1, T2> Tensor for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

type Item = <T1 as Tensor>::Item

The type of item encountered when iterating over the tensor.

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

Returns the full contraction with another tensor.

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

Returns an iterator. Read more

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

Returns an iterator that allows modifying each value. Read more

fn len(&self) -> usize

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

fn norm_inf(&self) -> TensorRank0

Returns the infinity norm.

fn norm_l1(&self) -> TensorRank0

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 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, compared against zero.

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 is_zero(&self) -> bool

Checks whether the tensor is the zero tensor.

fn norm(&self) -> TensorRank0

Returns the tensor norm.

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

Returns the Minkowski (Lp) 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<C1, C2, Y1, Y2> Viscoplastic<TensorTuple<TensorTuple<TensorRank2<3, 2, 0>, Y1>, Y2>> for ElasticViscoplasticAdditiveViscoplastic<C1, C2, Y1, Y2>
where C1: ElasticViscoplastic<Y1>, C2: Viscoplastic<Y2>, Y1: Tensor, Y2: Tensor,

fn initial_state( &self, ) -> ViscoplasticStateVariables<TensorTuple<ViscoplasticStateVariables<Y1>, Y2>>

Returns the initial state of the variables.

fn plastic_evolution( &self, mandel_stress: MandelStressElastic, state_variables: &ViscoplasticStateVariables<TensorTuple<ViscoplasticStateVariables<Y1>, Y2>>, ) -> Result<ViscoplasticStateVariables<TensorTuple<ViscoplasticStateVariables<Y1>, Y2>>, ConstitutiveError>

Calculates and returns the plastic evolution. Read more

fn rate_sensitivity(&self) -> Scalar

Returns the rate_sensitivity parameter.

fn reference_flow_rate(&self) -> Scalar

Returns the reference flow rate.

fn plastic_stretching_rate( &self, deviatoric_mandel_stress: MandelStressElastic, yield_stress: Scalar, ) -> Result<StretchingRatePlastic, ConstitutiveError>

Calculates and returns the rate of plastic stretching. Read more

impl<T1, T2> StructuralPartialEq for TensorTuple<T1, T2>
where T1: Tensor, T2: Tensor,

Auto Trait Implementations§

impl<T1, T2> Freeze for TensorTuple<T1, T2>
where T1: Freeze, T2: Freeze,

impl<T1, T2> RefUnwindSafe for TensorTuple<T1, T2>
where T1: RefUnwindSafe, T2: RefUnwindSafe,

impl<T1, T2> Send for TensorTuple<T1, T2>
where T1: Send, T2: Send,

impl<T1, T2> Sync for TensorTuple<T1, T2>
where T1: Sync, T2: Sync,

impl<T1, T2> Unpin for TensorTuple<T1, T2>
where T1: Unpin, T2: Unpin,

impl<T1, T2> UnsafeUnpin for TensorTuple<T1, T2>
where T1: UnsafeUnpin, T2: UnsafeUnpin,

impl<T1, T2> UnwindSafe for TensorTuple<T1, T2>
where T1: UnwindSafe, T2: UnwindSafe,

Blanket Implementations§

impl<T> Any for T
where T: 'static + ?Sized,

fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

impl<'a, T> AssertEq<&'a T> for T
where T: Display + PartialEq + Tensor,

fn eq(a: T, b: &'a T) -> Result<(), AssertionError>

fn eq_within_tols(tols: &Assert, a: T, b: &'a T) -> Result<(), AssertionError>

impl<T> Borrow<T> for T
where T: ?Sized,

fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

impl<T> BorrowMut<T> for T
where T: ?Sized,

fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

impl<T> CloneToUninit for T
where T: Clone,

unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)

Performs copy-assignment from self to dest. Read more

impl<T> From<T> for T

fn from(t: T) -> T

Returns the argument unchanged.

impl<T, U> Into<U> for T
where U: From<T>,

fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

impl<T> ToOwned for T
where T: Clone,

type Owned = T

The resulting type after obtaining ownership.

fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more

fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more

impl<T> ToString for T
where T: Display + ?Sized,

fn to_string(&self) -> String

Converts the given value to a String. Read more

impl<T, U> TryFrom<U> for T
where U: Into<T>,

type Error = Infallible

The type returned in the event of a conversion error.

fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.

impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.

fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.