feat: docstrings and overall design for expectation maximization iterative refinement #21
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currently only 2D ffts in compSPI.transforms. can use torch.fft for 3d fft and convert back to numpy array |
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I added my comments. Refactor and pull out the functions to be defined outside. I just wrote it like this to start it off because it's more readable - things defined right where they are used. |
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im not sure whats going on with black... |
added 11 commits
March 30, 2022 18:41
…constructSPI into itr_ref_docstrings
…constructSPI into itr_ref_docstrings
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This PR should be into master. |
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I had it into reconstructSPI_infrastructure due to it being a branch off of that - upon reflection you're right that doesn't imply this PR needs to be into master! |
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Fixes #10
References
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http://doi.org/10.1016/j.jsb.2012.09.006
An Introduction to Maximum-Likelihood Methods in Cryo-EM.
In Methods in Enzymology (1st ed., Vol. 482, pp. 263–294). Elsevier Inc.
http://doi.org/10.1016/S0076-6879(10)82011-7