PERF: refactor SharedWallsRatio

benchmarks/bench_distribution.py

@@ -27,7 +27,7 @@ def time_Orientation(self):
         mm.Orientation(self.df_buildings)
 
     def time_SharedWallsRatio(self):
-        mm.SharedWallsRatio(self.df_buildings, "uID")
+        mm.SharedWallsRatio(self.df_buildings)
 
     def time_StreetAlignment(self):
         mm.StreetAlignment(

momepy/distribution.py

@@ -6,13 +6,18 @@
 
 import math
 import statistics
+import warnings
+from distutils.version import LooseVersion
 
 import numpy as np
 import pandas as pd
+import geopandas as gpd
 from tqdm import tqdm  # progress bar
 
 from .utils import _azimuth
 
+GPD_08 = str(gpd.__version__) >= LooseVersion("0.8.0")
+
 __all__ = [
     "Orientation",
     "SharedWallsRatio",
@@ -119,8 +124,7 @@ class SharedWallsRatio:
     ----------
     gdf : GeoDataFrame
         GeoDataFrame containing gdf to analyse
-    unique_id : str, list, np.array, pd.Series
-        the name of the dataframe column, ``np.array``, or ``pd.Series`` with unique id
+    unique_id : (deprecated)
     perimeters : str, list, np.array, pd.Series (default None)
         the name of the dataframe column, ``np.array``, or ``pd.Series`` where is stored perimeter value
 
@@ -130,63 +134,47 @@ class SharedWallsRatio:
         Series containing resulting values
     gdf : GeoDataFrame
         original GeoDataFrame
-    id : Series
-        Series containing used unique ID
     perimeters : GeoDataFrame
         Series containing used perimeters values
-    sindex : rtree spatial index
-        spatial index of gdf
 
     Examples
     --------
-    >>> buildings_df['swr'] = momepy.SharedWallsRatio(buildings_df, 'uID').series
+    >>> buildings_df['swr'] = momepy.SharedWallsRatio(buildings_df).series
     100%|██████████| 144/144 [00:00<00:00, 648.72it/s]
     >>> buildings_df['swr'][10]
     0.3424804411228673
     """
 
-    def __init__(self, gdf, unique_id, perimeters=None):
-        self.gdf = gdf
+    def __init__(self, gdf, unique_id=None, perimeters=None):
+        if not GPD_08:
+            raise ImportError(
+                "The 'geopandas' >= 0.8.0 package is required to use SharedWallsRatio."
+            )
+        if unique_id:
+            warnings.warn(
+                "unique_id is deprecated and will be removed in v0.4.", FutureWarning,
+            )
 
-        gdf = gdf.copy()
-        self.sindex = gdf.sindex  # define rtree index
-        # define empty list for results
-        results_list = []
+        self.gdf = gdf
 
         if perimeters is None:
-            gdf["mm_p"] = gdf.geometry.length
-            perimeters = "mm_p"
+            self.perimeters = gdf.geometry.length
+        elif isinstance(perimeters, str):
+            self.perimeters = gdf[perimeters]
         else:
-            if not isinstance(perimeters, str):
-                gdf["mm_p"] = perimeters
-                perimeters = "mm_p"
-
-        self.perimeters = gdf[perimeters]
-
-        if not isinstance(unique_id, str):
-            gdf["mm_uid"] = unique_id
-            unique_id = "mm_uid"
-        self.id = gdf[unique_id]
-
-        gdf["_bounds"] = gdf.geometry.bounds.apply(list, axis=1)
-        for i, row in tqdm(
-            enumerate(
-                gdf[[perimeters, "_bounds", gdf._geometry_column_name]].itertuples()
-            ),
-            total=gdf.shape[0],
-        ):
-            neighbors = list(self.sindex.intersection(row[2]))
-            neighbors.remove(i)
-
-            # if no neighbour exists
-            length = 0
-            if not neighbors:
-                results_list.append(0)
-            else:
-                length = gdf.iloc[neighbors].intersection(row[3]).length.sum()
-                results_list.append(length / row[1])
-
-        self.series = pd.Series(results_list, index=gdf.index)
+            self.perimeters = perimeters
+
+        inp, res = gdf.sindex.query_bulk(gdf.geometry, predicate="intersects")
+        left = gdf.geometry.take(inp).reset_index(drop=True)
+        right = gdf.geometry.take(res).reset_index(drop=True)
+        intersections = left.intersection(right).length
+        results = (
+            intersections.groupby(inp).sum().reset_index(drop=True)
+            - self.perimeters.reset_index(drop=True)
+        ) / self.perimeters.reset_index(drop=True)
+        results.index = gdf.index
+
+        self.series = results
 
 
 class StreetAlignment:

tests/test_distribution.py

@@ -1,9 +1,13 @@
+from distutils.version import LooseVersion
+
 import geopandas as gpd
 import momepy as mm
 import numpy as np
 import pytest
 from libpysal.weights import Queen
 
+GPD_08 = str(gpd.__version__) >= LooseVersion("0.8.0")
+
 
 class TestDistribution:
     def setup_method(self):
@@ -28,21 +32,20 @@ def test_Orientation(self):
         check = 40.7607
         assert self.df_streets["orient"][0] == pytest.approx(check)
 
+    @pytest.mark.skipif(not GPD_08, reason="requires geopandas > 0.7")
     def test_SharedWallsRatio(self):
-        self.df_buildings["swr"] = mm.SharedWallsRatio(self.df_buildings, "uID").series
-        self.df_buildings["swr_uid"] = mm.SharedWallsRatio(
-            self.df_buildings, range(len(self.df_buildings))
-        ).series
+        self.df_buildings["swr"] = mm.SharedWallsRatio(self.df_buildings).series
         self.df_buildings["swr_array"] = mm.SharedWallsRatio(
-            self.df_buildings, "uID", self.df_buildings.geometry.length
+            self.df_buildings, perimeters=self.df_buildings.geometry.length
         ).series
         nonconsecutive = self.df_buildings.drop(2)
-        result = mm.SharedWallsRatio(nonconsecutive, "uID").series
+        result = mm.SharedWallsRatio(nonconsecutive).series
         check = 0.3424804411228673
         assert self.df_buildings["swr"][10] == check
-        assert self.df_buildings["swr_uid"][10] == check
         assert self.df_buildings["swr_array"][10] == check
         assert result[10] == check
+        with pytest.warns(FutureWarning):
+            mm.SharedWallsRatio(self.df_buildings, "uID")
 
     def test_StreetAlignment(self):
         self.df_buildings["orient"] = orient = mm.Orientation(self.df_buildings).series