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import uuid
from random import shuffle
import geopandas as gpd
import numpy as np
import pandas as pd
import pytest
from geopandas.testing import assert_geodataframe_equal
from packaging.version import Version
from pandas.testing import assert_index_equal
from shapely import affinity
from shapely.geometry import LineString, MultiPoint, Polygon
import momepy as mm
GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
class TestElements:
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_tessellation = gpd.read_file(test_file_path, layer="tessellation")
self.df_streets = gpd.read_file(test_file_path, layer="streets")
self.df_streets["nID"] = range(len(self.df_streets))
self.limit = mm.buffered_limit(self.df_buildings, 50)
self.enclosures = mm.enclosures(
self.df_streets,
gpd.GeoSeries([self.limit.exterior], crs=self.df_streets.crs),
)
def test_Tessellation(self):
tes = mm.Tessellation(self.df_buildings, "uID", self.limit, segment=2)
tessellation = tes.tessellation
assert len(tessellation) == len(self.df_tessellation)
bands = mm.Tessellation(
self.df_streets, "nID", mm.buffered_limit(self.df_streets, 50), segment=5
).tessellation
assert len(bands) == len(self.df_streets)
def test_enclosed_tess(self):
# test_enclosed_tessellation
enc1 = mm.Tessellation(
self.df_buildings, "uID", enclosures=self.enclosures
).tessellation
assert len(enc1) == 155
assert isinstance(enc1, gpd.GeoDataFrame)
enc1_loop = mm.Tessellation(
self.df_buildings, "uID", enclosures=self.enclosures, use_dask=False
).tessellation
assert len(enc1) == 155
assert isinstance(enc1, gpd.GeoDataFrame)
assert len(enc1_loop) == 155
assert isinstance(enc1_loop, gpd.GeoDataFrame)
assert_geodataframe_equal(enc1, enc1_loop)
def test_limit_enclosures_combo_error(self):
with pytest.raises(ValueError, match="Both `limit` and `enclosures` cannot"):
mm.Tessellation(
self.df_buildings, "uID", limit=self.limit, enclosures=self.enclosures
)
def test_custom_enclosure_id(self):
# non-standard enclosure ids
encl = self.enclosures.copy()
ids = list(range(len(encl) * 2))
shuffle(ids)
encl["eID"] = ids[: len(encl)]
encl.index = ids[: len(encl)]
enc = mm.Tessellation(self.df_buildings, "uID", enclosures=encl).tessellation
assert len(enc) == 155
assert isinstance(enc, gpd.GeoDataFrame)
def test_erroroneous_geom(self):
df = self.df_buildings
b = df.total_bounds
x = np.mean([b[0], b[2]])
y = np.mean([b[1], b[3]])
df = pd.concat(
[
df,
gpd.GeoDataFrame(
{"uID": [145, 146, 147]},
geometry=[
Polygon([(x, y), (x, y + 1), (x + 1, y)]),
MultiPoint([(x, y), (x + 1, y)]).buffer(0.55),
affinity.rotate(df.geometry.iloc[0], 12),
],
index=[144, 145, 146],
crs=df.crs,
),
]
)
with (
pytest.warns(
UserWarning, match="Tessellation does not fully match buildings."
),
pytest.warns(
UserWarning, match="Tessellation contains MultiPolygon elements."
),
):
tess = mm.Tessellation(df, "uID", self.limit)
assert tess.collapsed == {145}
assert len(tess.multipolygons) == 3
def test_crs_error(self):
with pytest.raises(ValueError, match="Geometry is in a geographic CRS"):
mm.Tessellation(self.df_buildings.to_crs(4326), "uID", self.limit)
def test_Blocks(self):
blocks = mm.Blocks(
self.df_tessellation, self.df_streets, self.df_buildings, "bID", "uID"
)
assert not blocks.tessellation_id.isna().any()
assert not blocks.buildings_id.isna().any()
assert len(blocks.blocks) == 8
with pytest.raises(ValueError, match="'uID' column cannot be"):
mm.Blocks(
self.df_tessellation, self.df_streets, self.df_buildings, "uID", "uID"
)
def test_Blocks_non_default_index(self):
tessellation = self.df_tessellation.copy()
tessellation.index = tessellation.index * 3
buildings = self.df_buildings.copy()
buildings.index = buildings.index * 5
blocks = mm.Blocks(tessellation, self.df_streets, buildings, "bID", "uID")
assert_index_equal(tessellation.index, blocks.tessellation_id.index)
assert_index_equal(buildings.index, blocks.buildings_id.index)
def test_Blocks_inner(self):
streets = self.df_streets.copy()
streets.loc[35, "geometry"] = (
self.df_buildings.geometry.iloc[141]
.representative_point()
.buffer(20)
.exterior
)
blocks = mm.Blocks(
self.df_tessellation, streets, self.df_buildings, "bID", "uID"
)
assert not blocks.tessellation_id.isna().any()
assert not blocks.buildings_id.isna().any()
assert len(blocks.blocks) == 9
if GPD_GE_013:
assert (
len(blocks.blocks.sindex.query(blocks.blocks.geometry, "overlaps")[0])
== 0
)
else:
assert (
len(
blocks.blocks.sindex.query_bulk(blocks.blocks.geometry, "overlaps")[
0
]
)
== 0
)
def test_get_network_id(self):
buildings_id = mm.get_network_id(self.df_buildings, self.df_streets, "nID")
assert not buildings_id.isna().any()
def test_get_network_id_duplicate(self):
self.df_buildings["nID"] = range(len(self.df_buildings))
buildings_id = mm.get_network_id(self.df_buildings, self.df_streets, "nID")
assert not buildings_id.isna().any()
def test_get_node_id(self):
nx = mm.gdf_to_nx(self.df_streets)
nodes, edges = mm.nx_to_gdf(nx)
self.df_buildings["nID"] = mm.get_network_id(
self.df_buildings, self.df_streets, "nID"
)
ids1 = mm.get_node_id(self.df_buildings, nodes, edges, "nodeID", "nID")
assert not ids1.isna().any()
# test for NaNs within `object` nIDs column
edges["nID"] = edges["nID"].astype(str)
_df_buildings = self.df_buildings.copy()
_df_buildings["nID"] = _df_buildings["nID"].astype(str)
_df_buildings.loc[[0, 1], "nID"] = pd.NA
ids2 = mm.get_node_id(_df_buildings, nodes, edges, "nodeID", "nID")
assert ids2.isna().sum() == 2
np.testing.assert_array_equal(ids2[ids2.isna()].index, [0, 1])
def test_get_node_id_ratio(self):
nx = mm.gdf_to_nx(self.df_streets)
nodes, edges = mm.nx_to_gdf(nx)
convex_hull = edges.dissolve().convex_hull.item()
enclosures = mm.enclosures(
edges, limit=gpd.GeoSeries([convex_hull], crs=edges.crs)
)
enclosed_tess = mm.Tessellation(
self.df_buildings, unique_id="uID", enclosures=enclosures
).tessellation
links = mm.get_network_ratio(enclosed_tess, edges)
enclosed_tess[links.columns] = links
ids = mm.get_node_id(
enclosed_tess,
nodes,
edges,
node_id="nodeID",
edge_keys="edgeID_keys",
edge_values="edgeID_values",
)
assert not ids.isna().any()
def test_enclosures(self):
basic = mm.enclosures(self.df_streets)
assert len(basic) == 7
assert isinstance(basic, gpd.GeoDataFrame)
limited = mm.enclosures(self.df_streets, self.limit)
assert len(limited) == 20
assert isinstance(limited, gpd.GeoDataFrame)
limited2 = mm.enclosures(
self.df_streets, gpd.GeoSeries([self.limit], crs=self.df_streets.crs)
)
assert len(limited2) == 20
assert isinstance(limited2, gpd.GeoDataFrame)
b = self.limit.bounds
additional_barrier = gpd.GeoSeries(
[LineString([(b[0], b[1]), (b[2], b[3])])], crs=self.df_streets.crs
)
additional = mm.enclosures(
self.df_streets,
gpd.GeoSeries([self.limit], crs=self.df_streets.crs),
[additional_barrier],
)
assert len(additional) == 28
assert isinstance(additional, gpd.GeoDataFrame)
with pytest.raises(TypeError, match="`additional_barriers` expects a list"):
additional = mm.enclosures(
self.df_streets,
gpd.GeoSeries([self.limit], crs=self.df_streets.crs),
additional_barrier,
)
# test clip
limit = self.df_streets.dissolve().convex_hull.buffer(-100).item()
encl = mm.enclosures(
self.df_streets,
limit=gpd.GeoSeries([limit], crs=self.df_streets.crs),
clip=True,
)
assert len(encl) == 18
def test_get_network_ratio(self):
convex_hull = self.df_streets.dissolve().convex_hull.item()
enclosures = mm.enclosures(
self.df_streets, limit=gpd.GeoSeries([convex_hull], crs=self.df_streets.crs)
)
enclosed_tess = mm.Tessellation(
self.df_buildings, unique_id="uID", enclosures=enclosures
).tessellation
links = mm.get_network_ratio(enclosed_tess, self.df_streets, initial_buffer=10)
assert links.edgeID_values.apply(lambda x: sum(x)).sum() == len(enclosed_tess)
m = enclosed_tess["uID"] == 110
assert sorted(links.loc[m].iloc[0]["edgeID_keys"]) == [0, 34]
# ensure index is preserved
enclosed_tess.index = [str(uuid.uuid4()) for _ in range(len(enclosed_tess))]
links2 = mm.get_network_ratio(enclosed_tess, self.df_streets, initial_buffer=10)
assert_index_equal(enclosed_tess.index, links2.index, check_order=False)
expected_head = [[0, 34], [34], [34], [0], [0, 15, 3, 14, 4, 7]]
expected_tail = [[28], [29], [28], [32], [21]]
for i, idx in enumerate(expected_head):
assert sorted(links2.edgeID_keys.iloc[i]) == sorted(idx)
for i, idx in enumerate(expected_tail):
assert sorted(links2.edgeID_keys.tail(5).iloc[i]) == sorted(idx)
|
