[SciPy-User] 2D slice of transformed data
Chris Weisiger
cweisiger@msg.ucsf....
Wed Mar 23 17:00:39 CDT 2011
In preface, I'm not remotely an expert at array manipulation here. I'm an
experienced programmer, but not an experienced *scientific* programmer. I'm
sure what I want to do is possible, and I'm pretty certain it's even
possible to do efficiently, but figuring out the actual implementation is
giving me fits.
I have two four-dimensional arrays of data: time, Z, Y, X. These represent
microscopy data taken of the same sample with two different cameras. Their
views don't quite match up if you overlay them, so we have a
three-dimensional transform to align one array with the other. That
transformation consists of X, Y, and Z translations (shifts), rotation about
the Z axis, and equal scaling in X and Y -- thus, the transformation has 5
parameters. I can perform the transformation on the data without difficulty
with ndimage.affine_transform, but because we typically have hundreds of
millions of pixels in one array, it takes a moderately long time. A
representative array would be 30x50x512x512 or thereabouts.
I'm writing a program to allow users to adjust the transformation and see
how well-aligned the data looks from several perspectives. In addition to
the traditional XY view, we also want to show XZ and YZ views, as well as
kymographs (e.g. TX, TY, TZ views). Thus, I need to be able to show 2D
slices of the transformed data in a timely fashion. These slices are always
perpendicular to two axes (e.g. an XY slice passing through T = 0, Z = 20,
or a TZ slice passing through X = 256, Y = 256), never diagonal. It seems
like the fast way to do this would be to take each pixel in the desired
slice, apply the reverse transform, and figure out where in the original
data it came from. But I'm having trouble figuring out how to efficiently do
this.
I could construct a 3D array with shape (length of axis 1), (length of axis
2), (4), such that each position in the array is a 4-tuple of the
coordinates of the pixel in the desired slice. For example, if doing a YX
slice at T = 10, Z = 20, the array would look like [[[10, 20, 0, 0], [10,
20, 1, 0], [10, 20, 2, 0], ...], [[10, 20, 0, 1], 10, 20, 1, 1], ...]]. Then
perhaps there'd be some way to efficiently apply the inverse transform to
each coordinate tuple, then using ndimage.map_coordinates to turn those into
pixel data. But I haven't managed to figure that out yet.
By any chance is this already solved? If not, any suggestions / assistance
would be wonderful.
-Chris
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