you can inspect the `.env` field of a method to get a reference to the closure variables
On Wed, Oct 15, 2014 at 6:26 PM, Nikolas Tezak <[email protected]> wrote: > Hi Isaiah, thanks for your reply! Yeah, I figured my use case is probably > a little exotic. I have thought very hard about using macros, but either I > haven't quite understood them yet (likely!) or they aren't the best > solution in this instance. > Maybe some sort of symbolic approach could work where I only store > Expression objects for each circuit element that get concatenated and > compiled when a whole circuit is simulated. > > Anyway, thanks! > Nik > > On Wednesday, October 15, 2014 11:11:42 AM UTC-7, Isaiah wrote: >> >> Given the constructed sys1_ode method is there someway to dynamically >>> access the captured variables, i.e. those that come from its closure? >> >> >> I'm not sure I entirely follow, but: you can use the variables p1 and p2 >> inside the inner function and it will Just Work (scoping rules). But it is >> not possible to interrogate the closure environment from inside the >> enclosed function. >> >> Also, have you considered macros? They won't help to interrogate the >> closure environment, but are a much better option for AST rewriting than >> using code_lowered. >> >> On Tue, Oct 14, 2014 at 2:14 PM, Nikolas Tezak <[email protected]> >> wrote: >> >>> Hi all, >>> >>> in my research I run numerical simulations (ODEs and SDEs) for circuit >>> models that can be composed, i.e., >>> each system has an ode that modifies in-place the elements of an output >>> array based on the current state variable. >>> Moreover, dimensionality of each system may vary. >>> >>> function sys1_ode(t, x, xdot) >>> xdot[1] = # some function of x, t >>> xdot[2] = # some other function of x, t >>> end >>> >>> >>> function sys2_ode(t, x, xdot) >>> xdot[1] = # some expression with x, t >>> xdot[2] = # some other expression with x, t >>> xdot[3] = # some other expression with x, t >>> end >>> >>> >>> What I would like to do is use metaprogramming to construct a combined >>> ode for both systems where the state vectors are just stacked. For each >>> system I compute the offset within the state vector (0 for sys1 and 2 for >>> sys2) and then modify and recombine the function code as follows >>> >>> function sys12_ode(t, x, xdot) >>> xdot[1+0] = # some expression with x[1:2], t >>> xdot[2+0] = # some other expression with x[1:2], t >>> xdot[1+2] = # some expression with x[1+2:3+2], t >>> >>> xdot[2+2] = # some expression with x[1+2:3+2], t >>> xdot[3+2] = # some expression with x[1+2:3+2], t >>> >>> end >>> >>> >>> So far, that would seem to be quite straightforward and I think I could >>> get this working by calling code_lowered(sys1_ode) and using the rewritten >>> output to construct an AST for the combined function. >>> >>> The difficulty now arises when my sys1 and sys2 odes are defined with >>> some internal parameters that are not passed as an argument but rather >>> through a closure from the surrounding scope, i.e. I have some ode factory: >>> >>> funcion make_sys1_ode(p1, p2) >>> function sys1_ode(t, x, xdot) >>> xdot[1] = # some expression with x, t AND p1, p2 >>> xdot[2] = # some expression with of x, t AND p1, p2 >>> end >>> sys1_ode >>> end >>> >>> Given the constructed sys1_ode method is there someway to dynamically >>> access the captured variables, i.e. those that come from its closure? >>> Otherwise, I suppose I could resort to passing parameters via an extra >>> ODE argument, but it would be super nice if I could avoid this. >>> The reason why I am trying to implement things this way is to speed up >>> ODE evaluation for very large complex (i.e. nested) circuits by expanding >>> out all ODE bodies into a single function. >>> >>> I hope this write-up makes sense. >>> Thanks, >>> Nik >>> >>> >>
