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import geopandas as gpd
import numpy as np
import pandas as pd
import pytest
from shapely.geometry import LineString, Point, Polygon
import momepy as mm
from momepy import sw_high
from momepy.shape import _make_circle
class TestDimensions:
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)
def test_Area(self):
self.df_buildings["area"] = mm.Area(self.df_buildings).series
check = self.df_buildings.geometry[0].area
assert self.df_buildings["area"][0] == check
def test_Perimeter(self):
self.df_buildings["perimeter"] = mm.Perimeter(self.df_buildings).series
check = self.df_buildings.geometry[0].length
assert self.df_buildings["perimeter"][0] == check
def test_Volume(self):
self.df_buildings["area"] = self.df_buildings.geometry.area
self.df_buildings["volume"] = mm.Volume(
self.df_buildings, "height", "area"
).series
check = self.df_buildings.geometry[0].area * self.df_buildings.height[0]
assert self.df_buildings["volume"][0] == check
area = self.df_buildings.geometry.area
height = np.linspace(10.0, 30.0, 144)
self.df_buildings["volume"] = mm.Volume(self.df_buildings, height, area).series
check = self.df_buildings.geometry[0].area * self.df_buildings.height[0]
assert self.df_buildings["volume"][0] == check
self.df_buildings["volume"] = mm.Volume(self.df_buildings, "height").series
check = self.df_buildings.geometry[0].area * self.df_buildings.height[0]
assert self.df_buildings["volume"][0] == check
with pytest.raises(KeyError, match="nonexistent"):
self.df_buildings["volume"] = mm.Volume(
self.df_buildings, "height", "nonexistent"
)
def test_FloorArea(self):
self.df_buildings["area"] = self.df_buildings.geometry.area
self.df_buildings["floor_area"] = mm.FloorArea(
self.df_buildings, "height", "area"
).series
check = self.df_buildings.geometry[0].area * (self.df_buildings.height[0] // 3)
assert self.df_buildings["floor_area"][0] == check
area = self.df_buildings.geometry.area
height = np.linspace(10.0, 30.0, 144)
self.df_buildings["floor_area"] = mm.FloorArea(
self.df_buildings, height, area
).series
assert self.df_buildings["floor_area"][0] == check
self.df_buildings["floor_area"] = mm.FloorArea(
self.df_buildings, "height"
).series
assert self.df_buildings["floor_area"][0] == check
with pytest.raises(KeyError, match="nonexistent"):
self.df_buildings["floor_area"] = mm.FloorArea(
self.df_buildings, "height", "nonexistent"
)
def test_CourtyardArea(self):
self.df_buildings["area"] = self.df_buildings.geometry.area
self.df_buildings["courtyard_area"] = mm.CourtyardArea(
self.df_buildings, "area"
).series
check = (
Polygon(self.df_buildings.geometry[80].exterior).area
- self.df_buildings.geometry[80].area
)
assert self.df_buildings["courtyard_area"][80] == check
area = self.df_buildings.geometry.area
self.df_buildings["courtyard_area"] = mm.CourtyardArea(
self.df_buildings, area
).series
assert self.df_buildings["courtyard_area"][80] == check
self.df_buildings["courtyard_area"] = mm.CourtyardArea(self.df_buildings).series
assert self.df_buildings["courtyard_area"][80] == check
with pytest.raises(KeyError, match="nonexistent"):
self.df_buildings["courtyard_area"] = mm.CourtyardArea(
self.df_buildings, "nonexistent"
)
def test_LongestAxisLength(self):
self.df_buildings["long_axis"] = mm.LongestAxisLength(self.df_buildings).series
check = (
_make_circle(self.df_buildings.geometry[0].convex_hull.exterior.coords)[2]
* 2
)
assert self.df_buildings["long_axis"][0] == check
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,
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, match="nonexistent is not supported as mode."):
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, match="nonexistent is not supported as mode."):
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] == pytest.approx(249.503, rel=1e-3)
assert self.df_tessellation["mesh_array"][0] == pytest.approx(
2623.996, rel=1e-3
)
assert self.df_tessellation["mesh_id"][38] == pytest.approx(2250.224, rel=1e-3)
assert self.df_tessellation["mesh_iq"][38] == pytest.approx(2118.609, rel=1e-3)
assert all_m.mean[0] == pytest.approx(2922.957, rel=1e-3)
assert all_m.median[0] == pytest.approx(2623.996, rel=1e-3)
assert all_m.mode[0] == pytest.approx(249.503, rel=1e-3)
assert all_m.series[0] == pytest.approx(2922.957, rel=1e-3)
assert two.mean[0] == pytest.approx(2922.957, rel=1e-3)
assert two.median[0] == pytest.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",
)
.series.isna()
.any()
)
def test_StreetProfile(self):
results = mm.StreetProfile(self.df_streets, self.df_buildings, heights="height")
assert results.w[0] == 47.9039130128257
assert results.wd[0] == 0.026104885468705645
assert results.h[0] == 15.26806526806527
assert results.p[0] == 0.31872271611668607
assert results.o[0] == 0.9423076923076923
assert results.hd[0] == 9.124556701878003
height = np.linspace(10.0, 30.0, 144)
results2 = mm.StreetProfile(
self.df_streets, self.df_buildings, heights=height, tick_length=100
)
assert results2.w[0] == 70.7214870365335
assert results2.wd[0] == pytest.approx(8.50508193935929)
assert results2.h[0] == pytest.approx(23.87158296249206)
assert results2.p[0] == pytest.approx(0.3375435664999579)
assert results2.o[0] == 0.5769230769230769
assert results2.hd[0] == pytest.approx(5.9307227575674)
results3 = mm.StreetProfile(self.df_streets, self.df_buildings)
assert results3.w[0] == 47.9039130128257
assert results3.wd[0] == 0.026104885468705645
assert results3.o[0] == 0.9423076923076923
# avoid infinity
blg = gpd.GeoDataFrame(
{"height": [2, 5]},
geometry=[
Point(0, 0).buffer(10, cap_style=3),
Point(30, 0).buffer(10, cap_style=3),
],
)
lines = gpd.GeoDataFrame(
geometry=[LineString([(-8, -8), (8, 8)]), LineString([(15, -10), (15, 10)])]
)
assert mm.StreetProfile(lines, blg, "height", 2).p.equals(
pd.Series([np.nan, 0.35])
)
def test_WeightedCharacter(self):
sw = sw_high(k=3, gdf=self.df_tessellation, ids="uID")
weighted = mm.WeightedCharacter(self.df_buildings, "height", sw, "uID").series
assert weighted[38] == pytest.approx(18.301, rel=1e-3)
self.df_buildings["area"] = self.df_buildings.geometry.area
sw = sw_high(k=3, gdf=self.df_tessellation, ids="uID")
weighted = mm.WeightedCharacter(
self.df_buildings, "height", sw, "uID", "area"
).series
assert weighted[38] == pytest.approx(18.301, rel=1e-3)
area = self.df_buildings.geometry.area
sw = sw_high(k=3, gdf=self.df_tessellation, ids="uID")
weighted = mm.WeightedCharacter(
self.df_buildings, self.df_buildings.height, sw, "uID", area
).series
assert weighted[38] == pytest.approx(18.301, rel=1e-3)
sw_drop = sw_high(k=3, gdf=self.df_tessellation[2:], ids="uID")
assert (
mm.WeightedCharacter(self.df_buildings, "height", sw_drop, "uID")
.series.isna()
.any()
)
def test_CoveredArea(self):
sw = sw_high(gdf=self.df_tessellation, k=1, ids="uID")
covered_sw = mm.CoveredArea(self.df_tessellation, sw, "uID").series
assert covered_sw[0] == pytest.approx(24115.667, rel=1e-3)
sw_drop = sw_high(k=3, gdf=self.df_tessellation[2:], ids="uID")
assert mm.CoveredArea(self.df_tessellation, sw_drop, "uID").series.isna().any()
def test_PerimeterWall(self):
sw = sw_high(gdf=self.df_buildings, k=1)
wall = mm.PerimeterWall(self.df_buildings).series
wall_sw = mm.PerimeterWall(self.df_buildings, sw).series
assert wall[0] == wall_sw[0]
assert wall[0] == pytest.approx(137.210, rel=1e-3)
def test_SegmentsLength(self):
absol = mm.SegmentsLength(self.df_streets).sum
mean = mm.SegmentsLength(self.df_streets, mean=True).mean
assert max(absol) == pytest.approx(1907.502238338006)
assert max(mean) == pytest.approx(249.5698434867373)
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