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()