Remapping Matrix Values (3d to 2d) for Convolution
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From: Anthony Hopf on 4 Apr 2010 12:32 This is my first post... and I'm hoping I am overlooking something, but thank you in advance for any help. I am starting off with a 3d matrix of points that are values in space, a simulated volume. Each point is indexed with x, y and z values, e.g. Value = Matrix(xval,yval,zval). I have also calculated the r, theta, and phi values to each point in the simulated volume. Each of these values also have their own matrix, e.g. rvalue = r(xval,yval,zval). What I would like to do is remap the original Matrix from above using the r, theta, and phi values mentioned for a constant r value to a 2d matrix. I would like to set an r value with a filter like: r > 11e3-dx & r < 11e3+dx. This will likely give me a value for each theta and phi value at that r value. Now I can filter the Matrix only keeping the new values and setting all of the other to NaN, still a 3d matrix. What I would like to do now is take these values in Matrix and map them to a 2d matrix that way I can do a 2d convolution over them and place them back into the 3d matrix. I realize I don't need to filter the points and replace the other points with NaN's but it was a way for me to visualize what I was doing. My initial thought was to create a for loop that goes through each point and if it meets the criteria place it in the 2d matrix mapped to theta and phi values for a given r value... but this will take forever with a matrix that is 450x450x30. The other issue is that phi ranges -pi to pi so I would need to "unwrap" the 3d space. Does anyone have any ideas that may help? |