CSLC: use scipy for computing coherence#35
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johntruckenbrodt wants to merge 63 commits intoOPERA-Cal-Val:mainfrom
Open
CSLC: use scipy for computing coherence#35johntruckenbrodt wants to merge 63 commits intoOPERA-Cal-Val:mainfrom
johntruckenbrodt wants to merge 63 commits intoOPERA-Cal-Val:mainfrom
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Update packages in environment.yml
Update nodejs in environment.yml, as earlier version (14.18.3) is not supported on the Mac M1.
Landslide example
Fix minor spelling typo.
Removing conflict with main
…ic-plots Notebook and sample plots of HLS and DSWx over Lake Mead
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scottstanie
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See OPERA-Cal-Val/OPERA_Applications#35 `uniform_filter` seems to run faster for all input/filter sizes.
scottstanie
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* Deprecate `moving_window_mean` in favor of `uniform_filter` See OPERA-Cal-Val/OPERA_Applications#35 `uniform_filter` seems to run faster for all input/filter sizes. * call `nearest` for mode, now there are not as obvious edge effects
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Not sure if I thought the other numpy way was faster or what, but thanks for pointing this out @johntruckenbrodt ! |
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Just stumbled across this. Using
scipy.ndimage.uniform_filtershould be more performant than the custom functioncslc_utils.moving_window_mean. The results are nearly identical.