anonymous function for if-else statements
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Hi, Is it possible to write an anonymous function or a function handle that replicates the behavior of if-else statements?
Consider the simple problem
if condition
a=b(x);
else
a=c(x);
end
it is possible to write the following function that will replicate that behavior
function out=ifelse(condition,answer1,answer2)
if condition
out=answer1;
else
out=answer2;
end
A critical difference between the first and the second pieces of code is the fact that in the second one, both answer1 and answer 2 need to be computed/evaluated before passing them to the ifelse function. For small problems this is not really a problem. However, in a situation where b(x) or c(x) are expensive to compute, it is best to avoid un-necessary operations.
One workaround would be
function out=ifelse2(condition,input1,input2)
if condition
out=eval(input1);
else
out=eval(input2);
end
In this case though we have to use "eval".
Is there any other way to deal with this, possibly using some kind of anonymous function or a function handle?
Thanks
1 Comment
Jan
on 19 Jul 2017
Don't use eval. If you talk about expensive functions, the performance degradation by eval must be important.
Answers (4)
Walter Roberson
on 19 Jul 2017
SelectCell = @(C, idx) C{idx}
condfunc = @(x, scalarcondition, varargin) feval(SelectCell(varargin, scalarcondition+1),x)
Example:
condfunc(x, condition, @b, @c)
5 Comments
Patrick Mboma
on 20 Jul 2017
Patrick Mboma
on 20 Jul 2017
Walter Roberson
on 20 Jul 2017
When the scalarcondition is logical, then false corresponds to 0 and true corresponds to 1, and adding one to that takes it into the range 1 or 2, which is suitable for indexing a two element array. However, you might want to use 2-scalarcondition instead, to reverse the order of the tests (the first one corresponds to false in the way I wrote the code.)
Patrick Mboma
on 20 Jul 2017
Sean de Wolski
on 19 Jul 2017
2 votes
In R2016b and newer you can have subfunctions in scripts as well as functions. I would recommend using them instead.
4 Comments
Patrick Mboma
on 19 Jul 2017
Walter Roberson
on 20 Jul 2017
This requires R2016b or later. It also requires that the script file be named something different than the name of any of the functions defined in the script.
Patrick Mboma
on 20 Jul 2017
Andrei Bobrov
on 20 Jul 2017
@Patrick Mboma: yes.
Jan
on 19 Jul 2017
@(x) condition * b(x) + (~condition) * c(x)
But you see, that b(x) and c(x) are evaluated also. The best strategy is not to use anonymous functions, but normal functions. Then you have the full power and the best speed.
9 Comments
Patrick Mboma
on 19 Jul 2017
Walter Roberson
on 20 Jul 2017
Are the "generic problems" being dynamically generated?
Can these functions output +/- inf, or nan ?
Patrick Mboma
on 20 Jul 2017
Jan
on 20 Jul 2017
Writing M-files is fine and in your case it might be more efficient than creating anonymous functions dynamically. Better write a "generic function", which describes the "generic problem" and control the details by input arguments. The simpler, the better.
Patrick Mboma
on 20 Jul 2017
Walter Roberson
on 20 Jul 2017
I am not sure what "generic form" means in this case...
The reason I ask about nan and inf is that some of the useful methods for conditional computation fail if nan or inf is involved, as they rely upon multiplication by 0 to ignore the computed value that is not wanted; that fails if the value to be ignored is nan or inf because 0*nan and 0*inf are both nan instead of 0.
Patrick Mboma
on 21 Jul 2017
Walter Roberson
on 21 Jul 2017
I would use the Symbolic Toolbox for the kind of situation you describe.
Patrick Mboma
on 21 Jul 2017
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