[SHORT] Fix up codes for FFT class, making it more user friendly and fix grid search #111
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mri/operators/fourier/cartesian.py
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| for ch in range(self.n_coils)]) | ||
| axes = tuple(np.arange(1, img.ndim)) | ||
| return self.mask * np.fft.ifftshift( | ||
| np.fft.fftn( |
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Did you check (and if so how) that fftn is indeed faster than the loop?
Indeed I had this problem, summarized in this SO question a long time ago.
Finally, it might be nice to consider some parallelization on this (maybe for now as a TODO).
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Well, there was a TODO for parallelization, but then I assumed that the fftn through numpy might as well handle this well and in practice this should not be that big a gain, but you do have a valid point. I will check this and get back here.
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Also added n_jobs and connected the argument to workers. This way, user has control on exact speed
chaithyagr
changed the title
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Looks like scipy for some reason gives different result, causing issues when we compare Noncartesian to cartesian in some tests |
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Also, I had a minute issue in gridsearch scripts which came up while using it, the n_coils term is missing and since it is a single line, I am merging it to this PR |
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LGTM @chaithyagr , I'll let you merge when you think it's time |
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merging, I see that the code worked on circleci well. |
This PR Covers:
axesparameter ofnp.fft.fftnto do FFT in vectorized way, than using loopsn_coilsto parameters in grid search