% Test neqfft.m on random data.
% Determine optimal parameters for given accuracy.
% Accuracy eps.
eps = 1.0d-5;
% Loop over ten cases of varying sizes.
p = [ 1:10 ];
% Initialize timing and parameter arrays --- same size as p.
tcpu = 1.0d+6*p;
scpu = 1.0d+6*p;
kmin = 1.0d+6*p;
qmin = 1.0d+6*p;

% Loop through cases.
for i = p
n = floor( 20*2^(0.5*i) )
m = floor( 20*2^(0.5*i) )
% Random coeffs on [0,1] and points on [0,2pi].
c = rand( 1, n );
x = 2*pi*rand( 1, m );

% Try a large range of degrees 2k-1 and oversamplings q.
for k = 2:2:30
for q = 2:10

% Test only if error bound is smaller than eps but not too much smaller.
errbd = (pi/q)^(2*k);
if errbd < eps 
if errbd > eps^2 

% Carry out nonequidistant FFT, fast (t) and slow (t), and record times and errors.
[ t, s, errbd, err, tc, sc ] = neqfft( n, c, m, x, k, q );

% Record only runs which satisfied accuracy requirement.
if err < eps
   kmin(i) = k;
   qmin(i) = q;
   tcpu(i) = min( tcpu(i), tc );
   scpu(i) = min( scpu(i), sc );
end

end
end

end
end 

end


hold on;
plot( 20*2.^(0.5*p), tcpu );
plot( 20*2.^(0.5*p), scpu );
p
scpu
tcpu
eps
kmin
qmin