133 feat generalize ar calculations chi center polarizations reflections #147
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…tions-reflections' of https://github.com/usnistgov/PyHyperScattering into 133-feat-generalize-ar-calculations-chi-center-polarizations-reflections
cbishop4
commented
Sep 4, 2024
| img (xarray): xarray to work on | ||
| chi (numeric): q about which slice should be centered, in deg | ||
| chi_width (numeric): width of slice in each direction, in deg | ||
| def slice_chi(self, chi, chi_width=5, do_avg: bool = True): |
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Couldn't the handling on this be greatly simplified by making use of the _reRange_chi function later? Or is there a reason we don't want to do that?
| @@ -161,6 +484,434 @@ def collate_AR_stack(sample,energy): | |||
| print(f' Pol 0: {pol0}') | |||
| print(f' Pol 90: {pol90}')''' | |||
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| def _reRange_chi(self, chi): | |||
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As somewhat noted above, I think this could maybe be applied more to other functions to greatly simplify them. @pbeaucage , are you married to the "nshift" handling within the slice_chi function? It might be easier to just take everything and anytime you're trying to index chi, you just change those things you're trying to index with to valid values
| if (AR_para < AR_perp).all() or (AR_perp < AR_para).all(): | ||
| warnings.warn('One polarization has a systematically higher/lower AR than the other. Typically this indicates bad intensity values.',stacklevel=2) | ||
| # User wants to infer chi centers from beam polarization metadata | ||
| if infer_chi_from_pol == True: |
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Elegant, I like it
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Had a conversation with @pbeaucage about the failing test_AR_unity - looking to refactor that now. |
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Hackathon final push for Bijal's AR work.