Vectorized function as output of matlabFunction

Hi.

I am trying to automatize a process in which I have a symbolic function that has to be converted in an anonymous function. Basically, I have something like this:

syms x y z t
var = [x y z t];
f = x.^2+y;
gf = gradient(f, var);
gf_fun = matlabFunction(gf, 'vars', {var});

having as output

gf_fun =
  function_handle with value:
    @(in1)[in1(:,1).*2.0;1.0;0.0;0.0]

Now, I'd like to evaluate gf_fun in several var points at a time, but, of course, I got strange results, due to how gf_fun is written. For example, if I want to evaluate gf_fun in 6 (different) points simultaneously, what I get is

rng('deafult')
vv = ones(6,4);

gf_fun(vv)
ans =
    1.3575
    1.5155
    1.4863
    0.7845
    1.3110
    0.3424
    1.0000
         0
         0

instead of a matrix with dimensions 4x6, with each colomn being the evaluation of a single point.

I know that a workaround will be the use of a for loop, meaning that

results = zeros(4,6);
for i = 1:6
    results(:,i) = gf_fun(vv(i,:));
end

but I have to avoid it due to code performances reasons.

Is there a way to automatize all the process, having a matrix as output of gf_fun while evaluating different point at a time?

Thank you for you help!

Answer 1

[Srivardhan Gadila]

Hi CaG,

You can use the function “splitapply” . You can refer to the function at https://www.mathworks.com/help/matlab/ref/splitapply.html.

I think you already noticed about the function "gf_fun", which

can provide different output based on the input dimension i.e., whether the input is row a vector or a column vector.

The following code provides the required output:

gff = @(x) gf_fun(x')            %transpose the input
results = splitapply(gff,vv',1:6);