Matlab Continuously Busy When Running Code

Hello again,

I have finally got my code to somewhat run. Now when I run my code with a certain function call it says it is busy, but will never end. When I manually stop the program I get this:

Operation terminated by user during test (line 57)

In newton_part_a (line 52)

fguess2 = myfunc(deltax2);

I'm just wondering what is happening here?

This is the command I am putting in:

newton_part_a(@test, [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1], 0.00001, 0.0001)

Here is my file:

if true
  %Define a function that will read in:
%an m file containing n number of nonlinear functions
%an initial guess for the functions
%A value that will determine if convergence to a solution has occured
%(tolerance)
%The value for iteration for each guess
function K = newton_part_a(myfunc, guess, epsilon, step)

n = length(guess); %define the number of functions based on the test file input

deltay = zeros(1,n); % delta F for initial Newton Raphson guess yguess = myfunc(guess); %Initial values for y matrix in forward substitution initialguess = zeros(1,n); Jacob = zeros(n,n); %Set up the initial Jacobian Matrix to a matrix of zeros func = 1; %set func to 1 so that while loop has a valid argument

while func %Find new value of delta y for i = 1:n %for number of equations in myfun, set delta y deltay(i) = initialguess(i) - yguess(i); end %Exit loop if delta y has converged to an acceptable tolerance (epsilon) if abs(deltay) < epsilon func = 0; break; end

%Develop the Jacobian matrix for i=1:n %Fill in the empty matrix by moving column by column, line by line for j =1:n x1 = guess(j); %set arguments for jacobian elements xplus = x1 + step; xminus = x1 - step;

        deltax1 = guess;
        deltax1(j) = xplus;
        deltax2 = guess;
        deltax2(j) = xminus;

fguess1 = myfunc(deltax1);
fguess2 = myfunc(deltax2);

guess1 = fguess1(i); 
guess2 = fguess2(i);
%Find each element of the jacobian  
J = (guess1 - guess2)/ (2*step);
Jacob(i,j) = J; 
  end
end
%Sparse Jacobian to make function faster
JJ = sparse(Jacob);

[L,U,P] = lu(JJ); %define lower and upper matrixes for LU factorization

b = deltay;
c = zeros(n,1);
b = deltay*P;
%forward substitution 
for i=1:n
    c(i)= (b(i)-L(i, :)*c)/L(i,i); 
end
%set a matrix of zeros for new guess
newguess = zeros(n,1);
%backward substitution
for i=n:-1:1
    newguess(i) = (c(i)-U(i,:)*newguess)/U(i,i);
    guess(i) = guess(i) + newguess(i);
end

yguess = myfunc(guess);
end
%Output the value of the variables after convergence has occured
K = guess;
end
end