Thank you, that seems to be a great suggestion. So to be clear, you mean
that instead of structuring my program:
stringForMyFunction=genStringForMyFunction(systemDetails)
eval(parse(stringForMyFunction))
t,y = ode23s(MyFunction, start, time)
do it like this:
stringForMyAnonFunction=genStringForMyAnonFunction(systemDetails)
newString = string(" t,y = ode23s(", stringForMyAnonFunction,
",start,time)");
eval(parse(newString))
With eval it is always tricky dealing with it being in global scope, but I
don't see any obvious problems doing the second case compared to the first.
Although, I guess I am still using the poor form of parse/eval on a string
(which I still don't fully understand the problem with).
On Fri, Aug 12, 2016 at 12:42 PM, Kristoffer Carlsson <[email protected]
> wrote:
> Can you use anonymous functions?
>
>
> On Friday, August 12, 2016 at 7:35:11 PM UTC+2, Garrett Jenkinson wrote:
>>
>> I have written a bit of a hack of a library for evolutionary computation,
>> where I continually evolve a system of "cells" that have different reaction
>> networks governed by ordinary differential equations. Basically, when I
>> need to solve the ODE for a cell, I have it generate a string that after
>> parse/eval'ing is a function to be passed onto ode23s in ODE.jl for
>> solving.
>>
>> In 0.4 everything works, however, I cannot run too many iterations due to
>> #14113, so I was looking forward to 0.5 where this is resolved, but then I
>> found out that the strategy of overwriting the same function over and over
>> is not recommended due to #265 and my code crashes in 0.5 as a result. I
>> also see #16593 is saying that parsing/evaling on a string is bad form
>> (although TBH I don't understand why this is so).
>>
>> So I am looking for thoughts/advice on the "correct" way to perform
>> evolutionary computations in julia. I do not mind writing my library from
>> scratch to do it properly.
>>
>> My initial thought to avoid constantly overwriting the function that I
>> generate was to install a counter to always give a unique name to the
>> generated function. But this seems like poor form since I don't see how
>> garbage collection would know to remove old and unused functions from
>> previous generations, so it seems like the explosion of functions defined
>> in global scope would cause an unnecessary amount of memory usage for a
>> long running evolution simulation. Is there a way to mark a function as
>> available to be garbage collected, or am I wrong that this will cause
>> memory issues?
>>
>> Julia's speed and metaprogramming facilities seem ripe for evolutionary
>> computation, but I'm just not clear on what the julianic approach should
>> look like, since my attempted efforts seem to be considered poor form or
>> even incorrect.
>>
>> Thanks in advance for any thoughts.
>>
>
