Best way to convert from a 1D matrix to a 3D matrix with isotropic distribution
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I have 1D data which has values at equally spaced intervals from r=0 to r=r, where r is a distance i.e.
This data is isotropic (from r=0) in three dimensions, so I want to go from a 1D dataset to 3D. I thought that the best option may be to convert to spherical polar coordinates using the function cart2pol and writing a For loop to loop around all values of theta and phi, filling in the values, then convert back to cartesian coodinates. However, I know that for loops can be time consuming computationally in Matlab and wondered if there was a better way of doing it? I am using Matlab version R2011B with the image processing toolbox. Thanks!