# Rust Casadi Interface
[](https://travis-ci.org/alphaville/icasadi)
This is an interface to CasADi functions of the form `phi(u; p)`, where `u` is a decision variable and `p` a parameter.
- Using CasADi's MATLAB or Python interface, you may define a cost function
- We provide helper functions which generate C code for the given function and its Jacobian
- Then `icasadi` offers a convenient interface to the C code from Rust
- This is a `no-std` library which can be used on embedded devices
- And `icasadi` can be used in embedded numerical optimization modules written in Rust
This library is available on [crates.io](https://crates.io/crates/icasadi) at https://crates.io/crates/icasadi
## Code generation in Python
Coming very soon
## Code generation in MATLAB
Here is an example of such a function (MATLAB example)
```matlab
% File: matlab/example.m
nu = 10; % number of decision variables
np = 2; % number of parameters
u = casadi.SX.sym('u', nu); % decision variables
p = casadi.SX.sym('p', np); % parameters
phi = (p'*p) * cos(sin(u))' * u; % cost function phi(u; p)
```
We may then create C code for this function and its Jacobian using
```matlab
[cost, grad_cost] = casadi_generate_c_code(u, p, phi);
```
This will create two functions:
- `cost` : which maps `(u, p)` to `phi(u; p)`,
- `grad_cost` : the Jacobian matrix of `phi` with respect to `u` evaluated
at `(u, p)`
Here is an example of use:
```rust
// File: main.rs
extern crate icasadi;
fn main() {
let u = [1.0, 2.0, 3.0, -5.0, 1.0, 10.0, 14.0, 17.0, 3.0, 5.0];
let p = [1.0, -1.0];
let mut cost_value = 0.0;
let mut jac = [0.0; 10];
icasadi_cost(u, p, &phival); // compute the cost
icasadi_grad(u, p, cost_jacobian); // compute the Jacobian of the cost
println!("cost value = {}", cost_value);
println!("jacobian = {:#?}", jac);
}
```
## Compiling, Running, Testing
To build the project, run
```
$ cargo build
```
To compile the main function (`main.rs`), run
```
$ cargo run
```
To run the unit tests, do
```
$ cargo test
```