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ENH: plot_density for KDE plotting of point patterns based on statsmodels #118

Merged
merged 4 commits into from
Sep 18, 2023
Merged

ENH: plot_density for KDE plotting of point patterns based on statsmodels #118

merged 4 commits into from
Sep 18, 2023

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martinfleis
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Resolves gdsbook/book#305. Essentially replaces seaborn.kdeplot which does not work as expected with our own solution.

Tests will come once I'll figure out how to do them.

import geopandas as gpd
from pointpats.kde import plot_density

gdf = gpd.read_file('https://martinfleischmann.net/sds/chapter_06/data/brno_pedestrian_accidents.gpkg')


gdf.plot(markersize=0.5, figsize=(9,9))
plot_density(gdf, 500)

4d2bc015-5f66-441c-8b69-c488ecd58d2c

gdf.plot(markersize=0.5, figsize=(9,9))
plot_density(gdf, 500, levels=25, cmap="magma_r", linewidths=1)

60e0adc4-0c3b-4f59-a7f8-1a7d07c824a8

gdf.plot(markersize=0.1, figsize=(9,9), zorder=2, color='k')
plot_density(gdf, 500, levels=25, cmap="magma_r", fill=True)

d68543e7-cbcb-458d-872e-ce62ea3f3da1

gdf.plot(markersize=0.5, figsize=(9,9))
plot_density(gdf, 1000, cmap="magma_r", linewidths=1)

ceb74c5e-0c3c-4f63-ad6b-b4d2f127b72a

I would love to have this in the next release alongside #111 so I can use both during teaching starting in two weeks.

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codecov bot commented Sep 17, 2023 •
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Codecov Report

Merging #118 (26b45b3) into main (8fd02a6) will increase coverage by 0.7%.
The diff coverage is 86.4%.

Impacted file tree graph

@@           Coverage Diff           @@
##            main    #118     +/-   ##
=======================================
+ Coverage   63.5%   64.2%   +0.7%     
=======================================
  Files         11      12      +1     
  Lines       1404    1448     +44     
=======================================
+ Hits         892     930     +38     
- Misses       512     518      +6
Files Changed Coverage Δ
pointpats/kde.py 86.0% <86.0%> (ø)
pointpats/__init__.py 100.0% <100.0%> (ø)

@knaaptime
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funny. I'm also right in the middle of using this for some bike/ped accident work

knaaptime
knaaptime reviewed Sep 17, 2023
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pointpats/kde.py Outdated Show resolved Hide resolved
@martinfleis
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I was struggling to make it work decently fast on large data so I included also an implementation on top of KDEpy. That is fast, offers a selection of kernels but can behave funny in some edge cases. While statsmodels seems to be robust default.

@martinfleis
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The tests are not perfect but testing matplotlib is just a pain in the ass, so this at least ensures that the stuff works and args are used. It should be ready for review.

@knaaptime knaaptime merged commit 0725890 into pysal:main Sep 18, 2023
@martinfleis martinfleis deleted the kde branch September 18, 2023 05:27
@knaaptime knaaptime mentioned this pull request Sep 23, 2023
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@knaaptime
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right now this gives back a matplotlib.contour.QuadContourSet. Is there any way to have it return an axes object, e.g. to play nicely with contextily?

@martinfleis martinfleis mentioned this pull request Sep 26, 2023
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@knaaptime knaaptime knaaptime left review comments

@jGaboardi jGaboardi jGaboardi approved these changes

@sjsrey sjsrey sjsrey approved these changes

@ljwolf ljwolf Awaiting requested review from ljwolf

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Successfully merging this pull request may close these issues.

seaborn.kdeplot is not suitable for point patterns
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@martinfleis @knaaptime @sjsrey @jGaboardi