How to use the momepy.AverageCharacter function in momepy
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martinfleis / momepy / tests / test_dimension.py View on Github 
self.df_tessellation["area"] = area = self.df_tessellation.geometry.area
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode="mode",
).mode
self.df_tessellation["mesh_array"] = mm.AverageCharacter(
self.df_tessellation,
values=area,
spatial_weights=spatial_weights,
unique_id="uID",
mode="median",
).median
self.df_tessellation["mesh_id"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(10, 90),
unique_id="uID",
).mean
self.df_tessellation["mesh_iq"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(25, 75),
unique_id="uID",
).series
all_m = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,).mode
self.df_tessellation["mesh_array"] = mm.AverageCharacter(
self.df_tessellation,
values=area,
spatial_weights=spatial_weights,
unique_id="uID",
mode="median",
).median
self.df_tessellation["mesh_id"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(10, 90),
unique_id="uID",
).mean
self.df_tessellation["mesh_iq"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(25, 75),
unique_id="uID",
).series
all_m = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
)
two = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",).series
all_m = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
)
two = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
mode=["mean", "median"],
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode="nonexistent",
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode=["nonexistent", "mean"],
)
assert self.df_tessellation["mesh_ar"][0] == approx(249.503, rel=1e-3)
assert self.df_tessellation["mesh_array"][0] == approx(2623.996, rel=1e-3)unique_id="uID",
mode=["nonexistent", "mean"],
)
assert self.df_tessellation["mesh_ar"][0] == approx(249.503, rel=1e-3)
assert self.df_tessellation["mesh_array"][0] == approx(2623.996, rel=1e-3)
assert self.df_tessellation["mesh_id"][38] == approx(2250.224, rel=1e-3)
assert self.df_tessellation["mesh_iq"][38] == approx(2118.609, rel=1e-3)
assert all_m.mean[0] == approx(2922.957, rel=1e-3)
assert all_m.median[0] == approx(2623.996, rel=1e-3)
assert all_m.mode[0] == approx(249.503, rel=1e-3)
assert all_m.series[0] == approx(2922.957, rel=1e-3)
assert two.mean[0] == approx(2922.957, rel=1e-3)
assert two.median[0] == approx(2623.996, rel=1e-3)
sw_drop = sw_high(k=3, gdf=self.df_tessellation[2:], ids="uID")
assert (
mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=sw_drop,
unique_id="uID",
)def test_AverageCharacter(self):
spatial_weights = sw_high(k=3, gdf=self.df_tessellation, ids="uID")
self.df_tessellation["area"] = area = self.df_tessellation.geometry.area
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode="mode",
).mode
self.df_tessellation["mesh_array"] = mm.AverageCharacter(
self.df_tessellation,
values=area,
spatial_weights=spatial_weights,
unique_id="uID",
mode="median",
).median
self.df_tessellation["mesh_id"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(10, 90),
unique_id="uID",
).mean
self.df_tessellation["mesh_iq"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,def test_AverageCharacter(self):
spatial_weights = sw_high(k=3, gdf=self.df_tessellation, ids="uID")
self.df_tessellation["area"] = area = self.df_tessellation.geometry.area
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode="mode",
).mode
self.df_tessellation["mesh_array"] = mm.AverageCharacter(
self.df_tessellation,
values=area,
spatial_weights=spatial_weights,
unique_id="uID",
mode="median",
).median
self.df_tessellation["mesh_id"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,).median
self.df_tessellation["mesh_id"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(10, 90),
unique_id="uID",
).mean
self.df_tessellation["mesh_iq"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(25, 75),
unique_id="uID",
).series
all_m = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
)
two = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
mode=["mean", "median"],
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",unique_id="uID",
).mean
self.df_tessellation["mesh_iq"] = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
rng=(25, 75),
unique_id="uID",
).series
all_m = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
)
two = mm.AverageCharacter(
self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
mode=["mean", "median"],
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode="nonexistent",
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(self.df_tessellation,
spatial_weights=spatial_weights,
values="area",
unique_id="uID",
mode=["mean", "median"],
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode="nonexistent",
)
with pytest.raises(ValueError):
self.df_tessellation["mesh_ar"] = mm.AverageCharacter(
self.df_tessellation,
values="area",
spatial_weights=spatial_weights,
unique_id="uID",
mode=["nonexistent", "mean"],
)
assert self.df_tessellation["mesh_ar"][0] == approx(249.503, rel=1e-3)
assert self.df_tessellation["mesh_array"][0] == approx(2623.996, rel=1e-3)
assert self.df_tessellation["mesh_id"][38] == approx(2250.224, rel=1e-3)
assert self.df_tessellation["mesh_iq"][38] == approx(2118.609, rel=1e-3)
assert all_m.mean[0] == approx(2922.957, rel=1e-3)
assert all_m.median[0] == approx(2623.996, rel=1e-3)
assert all_m.mode[0] == approx(249.503, rel=1e-3)
assert all_m.series[0] == approx(2922.957, rel=1e-3)
assert two.mean[0] == approx(2922.957, rel=1e-3)
assert two.median[0] == approx(2623.996, rel=1e-3)
Popular momepy functions
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