# DiffEqOperators

The `AbstractDiffEqOperator`

interface is an interface for declaring parts of a differential equation as linear or affine. This then allows the solvers to exploit linearity to achieve maximal performance.

### Note: this functionality is under heavy development. Interfaces may change. Treat this as experimental until the end of Summer 2018.

## Using DiffEqOperators

`AbstractDiffEqOperator`

s act like functions. When defined, `A`

has function calls `A(u,p,t)`

and `A(du,u,p,t)`

that act like `A*u`

. These operators update via a function `update_coefficients!(A,u,p,t)`

.

## Constructors

### Wrapping an Array: DiffEqArrayOperator

`DiffEqArrayOperator`

is for defining an operator directly from an array. The operator is of the form

for some scalar `α`

and time plus possibly state dependent `A`

. The constructor is:

```
DiffEqArrayOperator(A::AbstractMatrix{T},α=1.0,
update_func = DEFAULT_UPDATE_FUNC)
```

`A`

is the operator array. `α`

is the scalar coefficient. If `α`

is a function `α(t)`

, then it will update the coefficient as necessary. `update_func(A,u,p,t)`

is the function called by `update_coefficients!(A,u,p,t)`

(along with `α`

if it's a function). If left as its default, then `update_func`

is trivial which signifies `A`

is a constant.

### AffineDiffEqOperator

For `As = (A1,A2,...,An)`

and `Bs = (B1,B2,...,Bn)`

where each of the `Ai`

and `Bi`

are `DiffEqLinearOperator`

s, the following constructor:

`function AffineDiffEqOperator{T}(As,Bs,u_cache=nothing)`

builds an operator `L = (A1 + A2 + ... An)*u + B1 + B2 + ... + Bn`

. `u_cache`

is for designating a type of internal cache for non-allocating evaluation of `L(du,u,p,t)`

. If not given, the function `L(du,u,p,t)`

is not available. Note that in solves which exploit this structure, this function call is not necessary. It's only used as the fallback in ODE solvers which were not developed for this structure.

## Formal Properties of DiffEqOperators

These are the formal properties that an `AbstractDiffEqOperator`

should obey for it to work in the solvers.

### AbstractDiffEqOperator Interface Description

Function call and multiplication:

`L(du,u,p,t)`

for inplace and`du = L(u,p,t)`

for out-of-place, meaning`L*u`

and`A_mul_B!`

.If the operator is not a constant, update it with

`(u,p,t)`

. A mutating form, i.e.`update_coefficients!(A,u,p,t)`

that changes the internal coefficients, and a out-of-place form`B = update_coefficients(A,u,p,t)`

.`is_constant(A)`

trait for whether the operator is constant or not.

### AbstractDiffEqLinearOpeartor Interface Description

`AbstractDiffEqLinearOperator <: AbstractDiffEqOperator`

Can absorb under multiplication by a scalar. In all algorithms things like

`dt*L`

show up all the time, so the linear operator must be able to absorb such constants.`is_constant(A)`

trait for whether the operator is constant or not.Optional:

`diagonal`

,`symmetric`

, etc traits from LinearMaps.jl.Optional:

`expm(A)`

. Required for simple exponential integration.Optional:

`expmv(A,u,t) = expm(t*A)*u`

and`expmv!(v,A::DiffEqOperator,u,t)`

Required for sparse-saving exponential integration.Optional: factorizations.

`A_ldiv_B`

,`factorize`

et. al. This is only required for algorithms which use the factorization of the operator (Crank-Nicholson), and only for when the default linear solve is used.