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import geopandas as gpd
import numpy as np
import pytest
import shapely
from libpysal.weights import Queen
from packaging.version import Version
import momepy as mm
class TestDistribution:
def setup_method(self):
test_file_path = mm.datasets.get_path("bubenec")
self.df_buildings = gpd.read_file(test_file_path, layer="buildings")
self.df_streets = gpd.read_file(test_file_path, layer="streets")
self.df_tessellation = gpd.read_file(test_file_path, layer="tessellation")
self.df_buildings["height"] = np.linspace(10.0, 30.0, 144)
self.df_buildings["volume"] = mm.Volume(self.df_buildings, "height").series
self.df_streets["nID"] = mm.unique_id(self.df_streets)
self.df_buildings["nID"] = mm.get_network_id(
self.df_buildings, self.df_streets, "nID"
)
def test_Orientation(self):
self.df_buildings["orient"] = mm.Orientation(self.df_buildings).series
check = 41.05146788287027
assert self.df_buildings["orient"][0] == pytest.approx(check, abs=1e-3)
self.df_streets["orient"] = mm.Orientation(self.df_streets).series
check = 40.7607
assert self.df_streets["orient"][0] == pytest.approx(check)
def test_SharedWalls(self):
self.df_buildings["swr"] = mm.SharedWalls(self.df_buildings).series
nonconsecutive = self.df_buildings.drop(2)
result = mm.SharedWalls(nonconsecutive).series
check = 39.395484381507075
assert self.df_buildings["swr"][10] == check
assert result[10] == check
def test_SharedWallsRatio(self):
self.df_buildings["swr"] = mm.SharedWallsRatio(self.df_buildings).series
self.df_buildings["swr_array"] = mm.SharedWallsRatio(
self.df_buildings, perimeters=self.df_buildings.geometry.length
).series
nonconsecutive = self.df_buildings.drop(2)
result = mm.SharedWallsRatio(nonconsecutive).series
check = 0.3424804411228673
assert self.df_buildings["swr"][10] == check
assert self.df_buildings["swr_array"][10] == check
assert result[10] == check
def test_StreetAlignment(self):
self.df_buildings["orient"] = orient = mm.Orientation(self.df_buildings).series
self.df_buildings["street_alignment"] = mm.StreetAlignment(
self.df_buildings, self.df_streets, "orient", network_id="nID"
).series
self.df_buildings["street_alignment2"] = mm.StreetAlignment(
self.df_buildings,
self.df_streets,
"orient",
left_network_id="nID",
right_network_id="nID",
).series
self.df_buildings["street_a_arr"] = mm.StreetAlignment(
self.df_buildings,
self.df_streets,
orient,
left_network_id=self.df_buildings["nID"],
right_network_id=self.df_streets["nID"],
).series
with pytest.raises(
ValueError,
match=(
"Network ID not set. Use either network_id or "
"left_network_id and right_network_id."
),
):
self.df_buildings["street_alignment"] = mm.StreetAlignment(
self.df_buildings, self.df_streets, "orient"
)
with pytest.raises(ValueError, match="right_network_id not set."):
self.df_buildings["street_alignment"] = mm.StreetAlignment(
self.df_buildings, self.df_streets, "orient", left_network_id="nID"
)
with pytest.raises(ValueError, match="left_network_id not set."):
self.df_buildings["street_alignment"] = mm.StreetAlignment(
self.df_buildings, self.df_streets, "orient", right_network_id="nID"
)
check = 0.29073888476702336
assert self.df_buildings["street_alignment"][0] == pytest.approx(
check, abs=1e-3
)
assert self.df_buildings["street_alignment2"][0] == pytest.approx(
check, abs=1e-3
)
assert self.df_buildings["street_a_arr"][0] == pytest.approx(check, abs=1e-3)
def test_CellAlignment(self):
self.df_buildings["orient"] = blgori = mm.Orientation(self.df_buildings).series
self.df_tessellation["orient"] = tessori = mm.Orientation(
self.df_tessellation
).series
self.df_buildings["c_align"] = mm.CellAlignment(
self.df_buildings, self.df_tessellation, "orient", "orient", "uID", "uID"
).series
self.df_buildings["c_align_array"] = mm.CellAlignment(
self.df_buildings, self.df_tessellation, blgori, tessori, "uID", "uID"
).series
check = abs(
self.df_buildings["orient"][0]
- self.df_tessellation[
self.df_tessellation["uID"] == self.df_buildings["uID"][0]
]["orient"].iloc[0]
)
assert self.df_buildings["c_align"][0] == pytest.approx(check)
def test_Alignment(self):
self.df_buildings["orient"] = mm.Orientation(self.df_buildings).series
sw = Queen.from_dataframe(self.df_tessellation, ids="uID")
self.df_buildings["align_sw"] = mm.Alignment(
self.df_buildings, sw, "uID", self.df_buildings["orient"]
).series
test_value = (
22.744936872392813
if Version(shapely.geos_version_string) < Version("3.12")
else 18.29842494
)
assert self.df_buildings["align_sw"][0] == pytest.approx(test_value, rel=1e-3)
sw_drop = Queen.from_dataframe(self.df_tessellation[2:], ids="uID")
assert (
mm.Alignment(self.df_buildings, sw_drop, "uID", self.df_buildings["orient"])
.series.isna()
.any()
)
def test_NeighborDistance(self):
sw = Queen.from_dataframe(self.df_tessellation, ids="uID")
self.df_buildings["dist_sw"] = mm.NeighborDistance(
self.df_buildings, sw, "uID"
).series
check = 29.18589019096464
assert self.df_buildings["dist_sw"][0] == pytest.approx(check)
sw_drop = Queen.from_dataframe(self.df_tessellation[:-2], ids="uID")
self.df_buildings["dist_sw"] = mm.NeighborDistance(
self.df_buildings, sw_drop, "uID"
).series
check = 29.18589019096464
assert self.df_buildings["dist_sw"][0] == pytest.approx(check)
assert self.df_buildings["dist_sw"].isna().any()
def test_MeanInterbuildingDistance(self):
sw = Queen.from_dataframe(self.df_tessellation, ids="uID")
self.df_buildings["m_dist"] = mm.MeanInterbuildingDistance(
self.df_buildings, sw, "uID", order=3
).series
check = 29.305457092042744
assert self.df_buildings["m_dist"][0] == pytest.approx(check)
sw_drop = Queen.from_dataframe(self.df_tessellation[2:], ids="uID")
assert (
mm.MeanInterbuildingDistance(self.df_buildings, sw_drop, "uID")
.series.isna()
.any()
)
def test_NeighboringStreetOrientationDeviation(self):
self.df_streets["dev"] = mm.NeighboringStreetOrientationDeviation(
self.df_streets
).series
check = 7.527840590385933
assert self.df_streets["dev"].mean() == pytest.approx(check)
def test_BuildingAdjacency(self):
sw = Queen.from_dataframe(
self.df_buildings, ids="uID", silence_warnings=True, use_index=False
)
swh = mm.sw_high(k=3, gdf=self.df_tessellation, ids="uID")
self.df_buildings["adj_sw"] = mm.BuildingAdjacency(
self.df_buildings,
spatial_weights=sw,
unique_id="uID",
spatial_weights_higher=swh,
).series
self.df_buildings["adj_sw_none"] = mm.BuildingAdjacency(
self.df_buildings, unique_id="uID", spatial_weights_higher=swh
).series
check = 0.2613824113909074
assert self.df_buildings["adj_sw"].mean() == pytest.approx(check)
assert self.df_buildings["adj_sw_none"].mean() == pytest.approx(check)
swh_drop = mm.sw_high(k=3, gdf=self.df_tessellation[2:], ids="uID")
assert (
mm.BuildingAdjacency(
self.df_buildings, unique_id="uID", spatial_weights_higher=swh_drop
)
.series.isna()
.any()
)
def test_Neighbors(self):
sw = Queen.from_dataframe(self.df_tessellation, ids="uID")
sw_drop = Queen.from_dataframe(self.df_tessellation[2:], ids="uID")
self.df_tessellation["nei_sw"] = mm.Neighbors(
self.df_tessellation, sw, "uID"
).series
self.df_tessellation["nei_wei"] = mm.Neighbors(
self.df_tessellation, sw, "uID", weighted=True
).series
check = 5.180555555555555
check_w = 0.029066398893536072
assert self.df_tessellation["nei_sw"].mean() == check
assert self.df_tessellation["nei_wei"].mean() == check_w
assert mm.Neighbors(self.df_tessellation, sw_drop, "uID").series.isna().any()
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