MATLAB Answers

How to make and use many fast functions in Matlab?

9 views (last 30 days)
Hello fellow Earth hitchhikers, I have just stumbled upon how slow are anonymous functions in Matlab. However, I can't find a convenient alternative. I need to generate about 12 of these channels, each of them having 8 small functions. Here is one for example.
channels = []; = 'CHNAF';
channel.area = 10;
channel.g = 0.013;
channel.E = 87.39;
channel.alphaa = @(V,ion) 0.9*(V+19)/(1-exp(-(V+19)/10));
channel.betaa = @(V,ion) 36*exp(-0.055*(V + 44));
channel.infa = @(a,b,V) a/(a+b);
channel.taua = @(a,b,V) 1/(a+b); = 3;
channel.alphai = @(V,ion) 0.315*exp(-0.3*(V + 44));
channel.betai = @(V,ion) 4.5/(1 + exp(-(V + 11)/5));
channel.infi = @(a,b,V) a/(a+b);
channel.taui = @(a,b,V) 1/(a+b); = 1;
channels = [channels channel];
The generation is not a problem. But I want to use these functions and the following code makes it very very slow.
ch = channels(1);
curr = ch.area*ch.g*ch.m^*ch.h^*(V-ch.E);
adot = (ch.infa(ch.alphaa(V,ion),ch.betaa(V,ion),V) -h.m)/ch.taua(ch.alphaa(V,ion),ch.betaa(V,ion),V);
idot = (ch.infi(ch.alphai(V,ion),ch.betai(V,ion),V) - ch.h)/ch.taui(ch.alphai(V,ion),ch.betai(V,ion),V);
As noted in this thread it's the use of anonymous functions aka `fun = @(x) x;` that makes it so. *What can I do to make it faster?* (Note I am solving an ODE with those, so they are called thousands times).
Two possible concerns you might have.
1. I do have lots of dummy functions and variables there. Ion or V are not always used. Sometimes or are zero, so there is no need to call any functions. I need those for the sake of generality and simplicity.
2. I can get rid of alpha and beta functions by doing `infaNEW = @(V,ion) ch.infa(ch.alphaa(V,ion),ch.betaa(V,ion),V)` This way I'll decrease the number of functions.
Both these enhancements are likely increasing performance 2 fold each, not 20 fold as anonymous functions are slowing me down. Maybe a more direct question: *Is there a way to convert anonymous functions to the normal ones, maybe automatically printing them to .m files?*
P.S I must admit, I was impatient and posted the same post on StackExchange.

Accepted Answer

Walter Roberson
Walter Roberson on 26 Dec 2013
You can convert anonymous functions to regular functions, yes, but the overhead will not be much different. It is the function call overhead that is slowing you down, not the fact that the functions are anonymous.
If you have the Symbolic toolbox, you could pass symbolic V and ion into your formulas, getting out expressions with the various functions expanded "in place"; simplify() that to optimize it a little, and then use matlabFunction() to convert the symbolic expression into an single anonymous function.
syms V ion
curr = ch.area*ch.g*ch.m^*ch.h^*(V-ch.E);
adot = (ch.infa(ch.alphaa(V,ion),ch.betaa(V,ion),V) -h.m)/ch.taua(ch.alphaa(V,ion),ch.betaa(V,ion),V);
idot = (ch.infi(ch.alphai(V,ion),ch.betai(V,ion),V) - ch.h)/ch.taui(ch.alphai(V,ion),ch.betai(V,ion),V);
triple = [curr,adot,idot];
triplefcn = matlabFunction(simplify(triple), 'vars', [V, ion]);
now a call to triplefcn passing in actual V and ion will return an array with curr, adot, idot as the columns. (It will be vectorized, too, which your current expressions are not.)
Walter Roberson
Walter Roberson on 5 Aug 2018
In my later tests, I found that anonymous functions are indeed slower than regular functions.

Sign in to comment.

More Answers (1)

Adam Wyatt
Adam Wyatt on 5 Aug 2018
My recommendation would be to write a class which would significantly reduce the redundancy in your code. You can use dependent variables to act as the anonymous functions. The most recent versions of Matlab are quite good at optimizing the class - there is a small penalty but the code will be much easier to read, use and modify!

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!