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Hello,
If I understand correctly, the headbang triples spatial smoothing is not beign supported because the current one doesn't work too well in python 3. After reviewing, I think I may have stumbled across a few bugs that make getting the old unittests to pass very difficult.
I decided to re-write it. Please let me know if this is something you'd consider replacing. Right now, I've saved this in another module (it is easier that way because i work with python 3 and the
2to3
process makes it hard to save a diff only for the changing part of the file. I'd incorporate this inpysal.esda.smoothing
.I've followed the algorithm described in this paper.
Right now, I've only re-written the
Headbanging_Triples
algorithm. I haven't experimented with theHeadbanging_Median_Rate
class yet. (It may be we can fully recycle that.)Please let me know if this is something of interest to this project. Happy to finish it, or close this PR if you don't want to maintain.
Right now, I'm missing docstrings (I probably could just copy from the old method... but there's a few small simplifications to the API I woudl argue for... mainly dropping the requirement for
data
andk
as they are already provided by the spatial weightw
.Also, the current unittests use the old nose template. There's a lot happening in the
setUp
function that doesn't really do anything.