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DOC: add examples to build_contiguity and build_triangulation #703

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Apr 16, 2024
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DOC: add examples to build_contiguity and build_triangulation #703

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add build_contiguity example
lisawink Apr 10, 2024
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add triangulation example
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88 changes: 88 additions & 0 deletions libpysal/graph/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -403,6 +403,56 @@ def build_contiguity(cls, geometry, rook=True, by_perimeter=False, strict=False)
-------
Graph
libpysal.graph.Graph encoding contiguity weights

Examples
--------

>>> import geopandas as gpd
>>> from geodatasets import get_path
>>> nybb = gpd.read_file(get_path('nybb')).set_index("BoroName")
>>> nybb
BoroCode ... geometry
BoroName ...
Staten Island 5 ... MULTIPOLYGON (((970217.022 145643.332, 970227....
Queens 4 ... MULTIPOLYGON (((1029606.077 156073.814, 102957...
Brooklyn 3 ... MULTIPOLYGON (((1021176.479 151374.797, 102100...
Manhattan 1 ... MULTIPOLYGON (((981219.056 188655.316, 980940....
Bronx 2 ... MULTIPOLYGON (((1012821.806 229228.265, 101278...
[5 rows x 4 columns]

>>> contiguity = graph.Graph.build_contiguity(nybb)
>>> contiguity.adjacency
focal neighbor
Staten Island Staten Island 0
Queens Brooklyn 1
Manhattan 1
Bronx 1
Brooklyn Queens 1
Manhattan 1
Manhattan Queens 1
Brooklyn 1
Bronx 1
Bronx Queens 1
Manhattan 1
Name: weight, dtype: int64

Weight by perimeter instead of binary weights:

>>> contiguity_perimeter = graph.Graph.build_contiguity(nybb, by_perimeter=True)
>>> contiguity_perimeter.adjacency
focal neighbor
Staten Island Staten Island 0.000000
Queens Brooklyn 50867.502055
Manhattan 103.745207
Bronx 5.777002
Brooklyn Queens 50867.502055
Manhattan 5736.546898
Manhattan Queens 103.745207
Brooklyn 5736.546898
Bronx 5258.300879
Bronx Queens 5.777002
Manhattan 5258.300879
Name: weight, dtype: float64
"""
ids = _evaluate_index(geometry)

Expand Down Expand Up @@ -840,6 +890,44 @@ def build_triangulation(
-------
Graph
libpysal.graph.Graph encoding triangulation weights

Examples
--------

>>> import geopandas as gpd
>>> from geodatasets import get_path
>>> nybb = gpd.read_file(get_path('nybb')).set_index("BoroName")
>>> nybb
BoroCode ... geometry
BoroName ...
Staten Island 5 ... MULTIPOLYGON (((970217.022 145643.332, 970227....
Queens 4 ... MULTIPOLYGON (((1029606.077 156073.814, 102957...
Brooklyn 3 ... MULTIPOLYGON (((1021176.479 151374.797, 102100...
Manhattan 1 ... MULTIPOLYGON (((981219.056 188655.316, 980940....
Bronx 2 ... MULTIPOLYGON (((1012821.806 229228.265, 101278...
[5 rows x 4 columns]

Note that the method requires point geometry (or an array of coordinates
representing points) as an input.

>>> triangulation = graph.Graph.build_triangulation(nybb.centroid)
>>> triangulation.adjacency
focal neighbor
Staten Island Brooklyn 1
Manhattan 1
Queens Brooklyn 1
Manhattan 1
Bronx 1
Brooklyn Staten Island 1
Queens 1
Manhattan 1
Manhattan Staten Island 1
Queens 1
Brooklyn 1
Bronx 1
Bronx Queens 1
Manhattan 1
Name: weight, dtype: int64
"""
ids = _evaluate_index(data)

Expand Down