Struct newton_rootfinder::solver::JacobianMatrix
source · [−]pub struct JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,{ /* private fields */ }
Implementations
sourceimpl<D> JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,
impl<D> JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,
pub fn new() -> Self
pub fn force_jacobian_computation(&mut self)
pub fn compute_jacobian(&self) -> bool
pub fn is_jacobian_approximated(&self) -> bool
pub fn update_jacobian_with_exact_value(
&mut self,
matrix: OMatrix<f64, D, D>
) -> Result<(), NonInvertibleJacobian>
pub fn update_jacobian_with_approximated_value(
&mut self,
matrix: OMatrix<f64, D, D>
) -> Result<(), NonInvertibleJacobian>
sourcepub fn update_inverse(&mut self, inverse: OMatrix<f64, D, D>)
pub fn update_inverse(&mut self, inverse: OMatrix<f64, D, D>)
When updating the inverse, the jacobian does not have to be recomputed but becomes invalid
sourcepub fn get_inverse(&self) -> &Option<OMatrix<f64, D, D>>
pub fn get_inverse(&self) -> &Option<OMatrix<f64, D, D>>
Need to have Some and None for the inverse ? it is always valid !
pub fn get_jacobian(&self) -> &Option<OMatrix<f64, D, D>>
sourcepub fn invalidate_jacobian(&mut self)
pub fn invalidate_jacobian(&mut self)
Invalidate a jacobian For example, if there is an error computing it
Trait Implementations
sourceimpl<D> Debug for JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,
impl<D> Debug for JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,
sourceimpl<D> Default for JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,
impl<D> Default for JacobianMatrix<D>where
D: DimMin<D, Output = D>,
DefaultAllocator: Allocator<f64, D, D>,
DefaultAllocator: Allocator<(usize, usize), D>,
Auto Trait Implementations
impl<D> !RefUnwindSafe for JacobianMatrix<D>
impl<D> !Send for JacobianMatrix<D>
impl<D> !Sync for JacobianMatrix<D>
impl<D> !Unpin for JacobianMatrix<D>
impl<D> !UnwindSafe for JacobianMatrix<D>
Blanket Implementations
sourceimpl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
fn to_subset(&self) -> Option<SS>
fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
self
from the equivalent element of its
superset. Read morefn is_in_subset(&self) -> bool
fn is_in_subset(&self) -> bool
Checks if
self
is actually part of its subset T
(and can be converted to it).fn to_subset_unchecked(&self) -> SS
fn to_subset_unchecked(&self) -> SS
Use with care! Same as
self.to_subset
but without any property checks. Always succeeds.fn from_subset(element: &SS) -> SP
fn from_subset(element: &SS) -> SP
The inclusion map: converts
self
to the equivalent element of its superset.