Best way to convert from a 1D matrix to a 3D matrix with isotropic distribution

1 次查看（过去 30 天）

Catherine Scott 2014-2-4

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/114796-best-way-to-convert-from-a-1d-matrix-to-a-3d-matrix-with-isotropic-distribution

评论： Catherine Scott 2014-2-4

I have 1D data which has values at equally spaced intervals from r=0 to r=r, where r is a distance i.e.

 r         x
0  1.16000
2  1.21000
5  1.24000
7  1.25000
9  1.24000
2  1.22000
4  1.21000
6  1.18000 
etc

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!

2 个评论
显示无隐藏无

Azzi Abdelmalek 2014-2-4

The conversion is based on what? How can use cart2pol with one 1-D array?

Catherine Scott 2014-2-4

A good point, I don't actually need to convert to spherical polar coordinates because I already have r (which is rho in the Matlab documentation) and I can assume that the data I have is at theta=phi=0 (where theta= azimuth and phi=elevation). The next bit still stands I believe, so I would then loop over all possible values of theta and phi, then convert to cartesian (using sph2cart). So is there a more efficient method for this part? Apologies for the mix up and thanks for the comment.

请先登录，再进行评论。

请先登录，再回答此问题。