matlab - Logical short-circuit inside a function handle

Question

I have a function handle that operates on 2d arrays of arbitrary size:

R2T = @(DL1,DL2) arrayfun(@(DL1,DL2)...
                 1/(fzero(@(x)fFitObj1(x)./fFitObj2(x)-...
                 DL1./DL2,[minLim maxLim])) ...
                 ,DL1,DL2) - C1;

Here's a bottom-up breakdown of what it does:

• fzero(@(x)fFitObj1(x)./fFitObj2(x)-DL1./DL2,[minLim maxLim]) - This bit looks for a zero of the considered function on the interval [minLim maxLim], where fFitObj1 and fFitObj2 are function handles available from before, C1 is some known constant and DL1, DL2 are provided.
• @(DL1,DL2)1/(fzero(...)) - a wrapper for fzero that allows DL1 and DL2 to be provided from outside.
• arrayfun(@(DL1,DL2)...,DL1,DL2) - another wrapper which allows fzero to correctly operate element-by-element when DL1, DL2 are provided as a matrix.
• R2T = @(DL1,DL2) arrayfun(...) - C1; - yet another wrapper that allows to provide DL1, DL2 from outside.

My problem is that sometimes the matrices DL1, DL2 may contain NaN values, in which case fzero returns the following error:

Error using fzero (line 242)
Function values at interval endpoints must be finite and real.

This is why I naturally thought of the available operations with short-circuiting, so I tried to incorporate a any(isnan([DL1,DL2])) into this so that fzero won't even be evaluated if its inputs would be NaN - but whatever I try (e.g. a custom-made ternary operator) the fzero seems to be evaluated and the code errors.

The desired result: I'd like to implement a lazy evaluation of the fzero to only occur when the inputs are valid (in this case, not NaN), and return NaN otherwise as demonstrated in the Edit below.

Related resources:

• http://www.mathworks.com/matlabcentral/newsreader/view_thread/147044

---

Edit:

Here's a piece of code that illustrates the problem (MATLAB 2014a):

clear variables; clc;

LIM = [0 5];
fFitObj1 = @(x)x.^2; fFitObj2 = @(x)1;
C1 = 100;

[DL1A,DL2A,DL1B] = deal(ones(2));
DL1B(4) = NaN; DL2B = DL1B;

R2T = @(DL1,DL2) arrayfun(@(DL1,DL2)...
                 1/(fzero(@(x)fFitObj1(x)./fFitObj2(x)-...
                 DL1./DL2,LIM)) ...
                 ,DL1,DL2) - C1;
             
R2T(DL1A,DL2A) %//case A, runs fine
%{
// ans =
// 
//   -99   -99
//   -99   -99
%}   
R2T(DL1B,DL2B) %//case B, errors due to NaN
%{
// Error using fzero (line 242)
// Function values at interval endpoints must be finite and real.
// 
// Error in @(DL1,DL2)1/(fzero(@(x)fFitObj1(x)./fFitObj2(x)-DL1./DL2,LIM))
//
//
// Error in @(DL1,DL2)arrayfun(@(DL1,DL2)1/(fzero( .....
%}

The desired result, in case B is:

 ans =
 
   -99   -99
   -99   NaN

Answer 1

As already mentioned in the comments: Doing this inline is madness and you are much better off using a separate function / .m file.

It will be

• Faster
• Easier to read
• Easier to write
• Easier to debug

You could do this for example in a similar way to this:

function out = R2TComputation(DL1, DL2, minLim, maxLim, C1)
...%Compute whatever R2T would compute.

To get the same interface as your original anonymous function has, you can simply create

R2T = @(DL1, DL2) R2TComputation(DL1, DL2, minLim, maxLim, C1)

which will capture the current values of minLim, maxLim and C1 at the time you create this handle R2T.

---

Yet another option would be to use a nested function instead of the external one. It would have access to the parent function's variables, yet still be able to use if, else and all the other basic tools you need. Only downside: It is not meant to be accessed from within other files.

... % Main function stuff
     function out = R2T(DL1, DL2)
         if ...
            out = ...
         ...
     end
... % Use R2T ...

---

However, for the sake of freedom of shooting oneself in the foot, here is an inline version of if-else, which I wrote in the spirit of Loren's blog post and I do not recommend using, as there are hardly any benefits of using a single expression instead of the corresponding if-else statements.

ifelse = @(cond, varargin) varargin{1+~cond}(); %Only for the insane

If you want it to do lazy evaluation, you need to pass an anonymous function with zero parameters, which ifelse will then evaluate (That's what the last two parentheses () in ifelse are for):

ifelse(true, 42, @()disp('OMG! WTF! THIS IS CRAZY!!111'))

If you simply wrote the function call to disp as an argument to ifelse without @(), the function would be called before we even access ifelse. This is because MATLAB (as most other languages) first computes the return value of the function, which is then passed to ifelse as a parameter.

In your case the resulting code would be:

R2T = @(DL1,DL2) arrayfun(@(DL1,DL2)...
                 ifelse(~any(isnan([DL1, DL2])), ...
                        @() 1/(fzero(@(x)fFitObj1(x)./fFitObj2(x)-DL1./DL2,LIM)), ...
                        NaN), ...
                 DL1, DL2) - C1;