Programmatically producing polar or quasi-polar plots with a variable for color in matlab

Question

I would like to create plots using matlab that represent a numerical assessment of quality in a radial fashion.

The best method I've found seems to not work properly. One runs the following code:

theta = (0 : (360/11) : 360)*pi/180;
r = 0 : 2 : 20 ;
[TH,R] = meshgrid(theta,r);
[X,Y] = pol2cart(TH,R);
Z = meshgrid(Data);
surf(X,Y,Z);

Data is a vector of data containing 11 numbers, an example dataset being the following:

Data = 0.884, 0.882, 0.879, 0.880, 0.8776, 0.871, 0.8587, 0.829, 0.811, 0.803, 0.780 

the output of surf here is this:

I would like to produce a more refined version of this type of image:

which I have generated with the following code:

for theta = 0 : pi/100 : pi;  
    v = [InterpolatedImageHeight;LengthVector];
    x_center = InterpolatedImageHeight((HorizontalRes+1)/2);
    y_center = 0; %InterpolatedImageHeight((HorizontalRes+1)/2);
    center = repmat([x_center; y_center], 1, length(InterpolatedImageHeight));
    R = [cos(theta) -sin(theta); sin(theta) cos(theta)];
    vo = R*(v - center) + center;
    x_rotated = vo(1,:);
    y_rotated = vo(2,:);
    scatter(x_rotated,y_rotated,DotSize,InterpolatedData,'filled'); %x,y,area,color,properties
end

The issue with this is that it is a scatter plot where I am essentially using plot(r,Data), plotting many many copies, and increasing the dot size. The graphic itself has many seams, this takes an enormous amount of memory, and is time intensive where surf or mesh will run extremely fast and take minimal memory.

How does one produce concentric rings with a variable input for color?

Answer 1

based on the code by Darren Rowland in this thread I have come up with the following solution:

x = interp1(1:length(data),datax,(datax(1):datax(end)/f:datax(end)),'linear'); 
y = interp1(1:length(datay),datay,datay(1):datay(end)/f:datay(end),'spline');
theta = linspace(0,2*pi,n);

xr = x.'*cos(theta);
zr = x.'*sin(theta);
yr = repmat(y.',1,n);

figure;
surf(xy,yr,zr,zr*numcolors);

which is elegant, runs quickly, and produces beautiful figures. This is a sample of the output with some extra chart elements: