Define compiled code for ordinary differential equation.

`specify_ode(code, fname = NULL, pname = c("dy", "x", "y", "p"))`

- code
string with the body of the function definition (see details)

- fname
Optional name of the exported C++ function

- pname
Vector of variable names (results, inputs, states, parameters)

pointer (externalptr) to C++ function

The model (`code`

) should be specified as the body of of C++ function.
The following variables are defined bye default (see the argument `pname`

)

- dy
Vector with derivatives, i.e. the rhs of the ODE (the result).

- x
Vector with the first element being the time, and the following elements additional exogenous input variables,

- y
Vector with the dependent variable

- p
Parameter vector

\(y'(t) = f_{p}(x(t), y(t))\) All variables are treated as Armadillo (http://arma.sourceforge.net/) vectors/matrices.

As an example consider the *Lorenz Equations*
\(\frac{dx_{t}}{dt} = \sigma(y_{t}-x_{t})\)
\(\frac{dy_{t}}{dt} = x_{t}(\rho-z_{t})-y_{t}\)
\(\frac{dz_{t}}{dt} = x_{t}y_{t}-\beta z_{t}\)

We can specify this model as
```
ode <- 'dy(0) = p(0)*(y(1)-y(0));
dy(1) = y(0)*(p(1)-y(2));
dy(2) = y(0)*y(1)-p(2)*y(2);'
```

`dy <- specify_ode(ode)`

As an example of model with exogenous inputs consider the following ODE:
\(y'(t) = \beta_{0} + \beta_{1}y(t) + \beta_{2}y(t)x(t) + \beta_{3}x(t)\cdot t\)
This could be specified as
```
mod <- 'double t = x(0);
dy = p(0) + p(1)*y + p(2)*x(1)*y + p(3)*x(1)*t;'
```

`dy <- specify_ode(mod)`

##'

solve_ode