Calling different anonymous functions from a for loop

Hello,

I have four functions that I need to call various values for and I was wondering if I can make this process faster by creating a four loop to iterate through the various functions. For example, I have four functions q(nu) listed below

q_1 = 1; % Lax-Friedrichs 
q_2 = @(x) abs(x); % FIrst-order Upwind 
q_3 = @(x) x^2; % Lax-Wendroff 
q_4 = @(x) (1/3)+(2/3)*x^2; % Minimun Dispersion 

And I have four values of nu,

nu = [1.0; 0.75; 0.50; .25];

is it possible to take these equations and put them in an array to call each function when I need it?

For example, I know this isnt how the code would be written, but I am just trying to show what I mean most clearly.

q_array = [q_1; q_2; q_3; q_4];
for i = 1:4
    for j = 1:4 
        q_array(i(j));
    end
end

In this, the idea would be to call each nu value for the first q, then call each nu value for the second q and so on.

I just dont know if Matlab syntax supports this since it q_array would turn each anonymous function into an argument and no longer a function, and I know having each array element of q_array as an anonymous function deosnt work because I tried this and it doesnt work.

q_array = [1; @(x) abs(x); @(x) x^2; @(x) (1/3)+(2/3)*x^2];

Answer 1

[Walter Roberson]

q_array = {@(x)ones(size(x)); @(x) abs(x); @(x) x.^2; @(x) (1/3)+(2/3)*x.^2} ;

Now you can

q_array{i}(nu(j))

However I also vectorized the functions so instead of an inner loop,

q_array{i}(nu)

[Braden Kerr]

Thank you, this does exactly what I need. Conceptually, why does vectorizing the functions allow for the skipping of the inner loop?

[Walter Roberson]

That what vectorizing is for, to apply the same calculation to each element individually but in an efficient way

[Braden Kerr]

Got it, thanks