Closed AnGWar26 closed 4 years ago
Merging #256 into master will decrease coverage by
24.54%
. The diff coverage is13.54%
.
@@ Coverage Diff @@
## master #256 +/- ##
===========================================
- Coverage 79.24% 54.70% -24.55%
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Files 12 12
Lines 853 998 +145
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- Hits 676 546 -130
- Misses 177 452 +275
Impacted Files | Coverage Δ | |
---|---|---|
geosnap/_community.py | 39.28% <5.69%> (-26.18%) |
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geosnap/analyze/analytics.py | 65.75% <43.75%> (-6.43%) |
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geosnap/analyze/dynamics.py | 22.58% <0.00%> (-77.42%) |
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geosnap/io/storage.py | 24.66% <0.00%> (-70.67%) |
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geosnap/io/util.py | 48.83% <0.00%> (-30.24%) |
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geosnap/_data.py | 74.11% <0.00%> (+3.52%) |
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cool, lets talk about this a bit during the meeting on tuesday. It'll be a little easier to describe what i mean about stashing the index so we dont have to fillna
Also i think it would be better to switch the ordering of the plotting nomenclature, e.g. instead of ***_plot(...)
, i think it would be better to do plot_***(...)
Handle input when an aspatial model is passed to a spatial diagnostic Currently throws what might be a cryptic error to most users 'NoneType' object has no attribute 'sparse', referring to the absence of a W object
one thing we could do is add a little metadata attribute to the ModelResults class that stores whether the model is spatial or aspatial. That way we can add a simple check if users pass the wrong type of model to the wrong diagnostic
awesome! looks like this has everything we talked about yesterday. Everything working as expected?
As far as I can tell everything works as expected, and at this point I would designate this ready for review. However, this is such a big PR (+500 lines), and with your understanding of these statistics being better than mine, I would encourage you to test it out yourself before merging.
Let me know if these needs anymore changes.
Thought it would be best if I gave you the opportunity to comment on this as I work @knaaptime.
Todo:
gdf.fillna(0)
before running the clusterer, need to find solution that handles NaN values and keeps the index the same length as the dataframe.'NoneType' object has no attribute 'sparse'
, referring to the absence of a W objectdtype=object
Updated 8/19