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import math
import geopandas as gpd
import numpy as np
import pytest
from shapely.geometry import MultiLineString, MultiPolygon, Point, Polygon
import momepy as mm
from momepy.shape import _circle_area
class TestShape:
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
def test_FormFactor(self):
self.df_buildings["ff"] = mm.FormFactor(
self.df_buildings, "volume", heights="height"
).series
check = 5.4486362624193
assert self.df_buildings["ff"].mean() == pytest.approx(check)
self.df_buildings["ff"] = mm.FormFactor(
self.df_buildings,
mm.Volume(self.df_buildings, "height").series,
areas=self.df_buildings.geometry.area,
heights=self.df_buildings["height"],
).series
assert self.df_buildings["ff"].mean() == pytest.approx(check)
def test_FractalDimension(self):
self.df_buildings["fd"] = mm.FractalDimension(self.df_buildings).series
check = (
2
* math.log(self.df_buildings.geometry[0].length / 4)
/ math.log(self.df_buildings.geometry[0].area)
)
assert self.df_buildings["fd"][0] == check
self.df_buildings["fd2"] = mm.FractalDimension(
self.df_buildings,
areas=self.df_buildings.geometry.area,
perimeters=self.df_buildings.geometry.length,
).series
assert self.df_buildings["fd2"][0] == check
def test_VolumeFacadeRatio(self):
self.df_buildings["peri"] = self.df_buildings.geometry.length
self.df_buildings["vfr"] = mm.VolumeFacadeRatio(
self.df_buildings, "height", "volume", "peri"
).series
check = self.df_buildings.volume[0] / (
self.df_buildings.peri[0] * self.df_buildings.height[0]
)
assert self.df_buildings["vfr"][0] == check
peri = self.df_buildings.geometry.length
volume = mm.Volume(self.df_buildings, "height").series
self.df_buildings["vfr2"] = mm.VolumeFacadeRatio(
self.df_buildings, "height", volume, peri
).series
assert self.df_buildings["vfr2"][0] == check
self.df_buildings["peri"] = self.df_buildings.geometry.length
self.df_buildings["vfr3"] = mm.VolumeFacadeRatio(
self.df_buildings, "height"
).series
assert self.df_buildings["vfr3"][0] == check
def test_CircularCompactness(self):
self.df_buildings["area"] = self.df_buildings.geometry.area
self.df_buildings["circom"] = mm.CircularCompactness(
self.df_buildings, "area"
).series
check = self.df_buildings.area[0] / (
_circle_area(
list(self.df_buildings.geometry[0].convex_hull.exterior.coords)
)
)
assert self.df_buildings["circom"][0] == check
area = self.df_buildings.geometry.area
self.df_buildings["circom2"] = mm.CircularCompactness(
self.df_buildings, area
).series
assert self.df_buildings["circom2"][0] == check
self.df_buildings["circom3"] = mm.CircularCompactness(self.df_buildings).series
assert self.df_buildings["circom3"][0] == check
def test_SquareCompactness(self):
self.df_buildings["sqcom"] = mm.SquareCompactness(self.df_buildings).series
check = (
(4 * math.sqrt(self.df_buildings.geometry.area[0]))
/ (self.df_buildings.geometry.length[0])
) ** 2
assert self.df_buildings["sqcom"][0] == check
self.df_buildings["sqcom2"] = mm.SquareCompactness(
self.df_buildings,
areas=self.df_buildings.geometry.area,
perimeters=self.df_buildings.geometry.length,
).series
assert self.df_buildings["sqcom2"][0] == check
def test_Convexity(self):
self.df_buildings["conv"] = mm.Convexity(self.df_buildings).series
check = (
self.df_buildings.geometry.area[0]
/ self.df_buildings.geometry.convex_hull.area[0]
)
assert self.df_buildings["conv"][0] == check
self.df_buildings["conv2"] = mm.Convexity(
self.df_buildings, areas=self.df_buildings.geometry.area
).series
assert self.df_buildings["conv2"][0] == check
def test_CourtyardIndex(self):
cas = self.df_buildings["cas"] = mm.CourtyardArea(self.df_buildings).series
self.df_buildings["cix"] = mm.CourtyardIndex(self.df_buildings, "cas").series
self.df_buildings["cix_array"] = mm.CourtyardIndex(
self.df_buildings, cas, self.df_buildings.geometry.area
).series
check = self.df_buildings.cas[80] / self.df_buildings.geometry.area[80]
assert self.df_buildings["cix"][80] == check
assert self.df_buildings["cix_array"][80] == check
def test_Rectangularity(self):
self.df_buildings["rect"] = mm.Rectangularity(self.df_buildings).series
self.df_buildings["rect_array"] = mm.Rectangularity(
self.df_buildings, self.df_buildings.geometry.area
).series
check = (
self.df_buildings.geometry[0].area
/ self.df_buildings.geometry[0].minimum_rotated_rectangle.area
)
assert self.df_buildings["rect"][0] == check
assert self.df_buildings["rect_array"][0] == check
def test_ShapeIndex(self):
la = self.df_buildings["la"] = mm.LongestAxisLength(self.df_buildings).series
self.df_buildings["shape_index"] = mm.ShapeIndex(self.df_buildings, "la").series
self.df_buildings["shape_index_array"] = mm.ShapeIndex(
self.df_buildings, la, self.df_buildings.geometry.area
).series
check = math.sqrt(self.df_buildings.area[0] / math.pi) / (
0.5 * self.df_buildings.la[0]
)
assert self.df_buildings["shape_index"][0] == check
assert self.df_buildings["shape_index_array"][0] == check
def test_Corners(self):
self.df_buildings["corners"] = mm.Corners(self.df_buildings).series
check = 24
assert self.df_buildings["corners"][0] == check
def test_Squareness(self):
self.df_buildings["squ"] = mm.Squareness(self.df_buildings).series
check = pytest.approx(3.707, rel=1e-3)
assert self.df_buildings["squ"][0] == check
self.df_buildings["squ"] = mm.Squareness(self.df_buildings.exterior).series
assert self.df_buildings["squ"].isna().all()
df_buildings_multi = self.df_buildings.copy()
df_buildings_multi["geometry"] = df_buildings_multi["geometry"].apply(
lambda geom: MultiPolygon([geom])
)
self.df_buildings["squm"] = mm.Squareness(df_buildings_multi).series
assert self.df_buildings["squm"][0] == check
def test_EquivalentRectangularIndex(self):
self.df_buildings["eri"] = mm.EquivalentRectangularIndex(
self.df_buildings
).series
self.df_buildings["eri_array"] = mm.EquivalentRectangularIndex(
self.df_buildings,
areas=self.df_buildings.geometry.area,
perimeters=self.df_buildings.geometry.length,
).series
check = pytest.approx(0.7879, rel=1e-3)
assert self.df_buildings["eri"][0] == check
assert self.df_buildings["eri_array"][0] == check
def test_Elongation(self):
self.df_buildings["elo"] = mm.Elongation(self.df_buildings).series
check = pytest.approx(0.908, rel=1e-3)
assert self.df_buildings["elo"][0] == check
def test_CentroidCorners(self):
self.df_buildings.loc[144] = [145, Point(0, 0).buffer(10), 0, 0]
self.df_buildings.loc[145] = [
145,
Polygon([s + (0,) for s in Point(0, 0).buffer(10).exterior.coords]),
0,
0,
]
check = pytest.approx(15.961, rel=1e-3)
check_devs = pytest.approx(3.081, rel=1e-3)
cc = mm.CentroidCorners(self.df_buildings)
self.df_buildings["ccd"] = cc.mean
self.df_buildings["ccddev"] = cc.std
assert self.df_buildings["ccd"][0] == check
assert self.df_buildings["ccddev"][0] == check_devs
df_buildings_multi = self.df_buildings.copy()
df_buildings_multi["geometry"] = df_buildings_multi["geometry"].apply(
lambda geom: MultiPolygon([geom])
)
cc = mm.CentroidCorners(df_buildings_multi)
df_buildings_multi["ccd"] = cc.mean
df_buildings_multi["ccddev"] = cc.std
assert df_buildings_multi["ccd"][0] == check
assert df_buildings_multi["ccddev"][0] == check_devs
def test_Linearity(self):
self.df_streets["lin"] = mm.Linearity(self.df_streets).series
euclidean = Point(self.df_streets.geometry[0].coords[0]).distance(
Point(self.df_streets.geometry[0].coords[-1])
)
check = euclidean / self.df_streets.geometry[0].length
assert self.df_streets["lin"][0] == pytest.approx(check, rel=1e-6)
self.df_streets.loc[len(self.df_streets)] = MultiLineString(
[[(0, 0), (-1, 1)], [(10, 10), (11, 11)]]
)
def test_CompactnessWeightedAxis(self):
self.df_buildings["cwa"] = mm.CompactnessWeightedAxis(self.df_buildings).series
self.df_buildings["cwa_array"] = mm.CompactnessWeightedAxis(
self.df_buildings,
areas=self.df_buildings.geometry.area,
perimeters=self.df_buildings.geometry.length,
longest_axis=mm.LongestAxisLength(self.df_buildings).series,
).series
check = pytest.approx(26.327, rel=1e-3)
assert self.df_buildings["cwa"][0] == check
assert self.df_buildings["cwa_array"][0] == check
def test__circle_area(self):
poly = Polygon([(0, 1, 0), (1, 1, 0), (2, 4, 0)])
check = _circle_area(poly.exterior.coords)
assert check == pytest.approx(10.210, rel=1e-3)
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