COMPAT: geopandas 1.0 compatibility

momepy/distribution.py

@@ -5,10 +5,12 @@
 
 import math
 
+import geopandas as gpd
 import networkx as nx
 import numpy as np
 import pandas as pd
 import shapely
+from packaging.version import Version
 from tqdm.auto import tqdm  # progress bar
 
 from .utils import _azimuth
@@ -27,6 +29,8 @@
     "Neighbors",
 ]
 
+GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
+
 
 class Orientation:
     """
@@ -134,7 +138,10 @@ class SharedWalls:
     def __init__(self, gdf):
         self.gdf = gdf
 
-        inp, res = gdf.sindex.query_bulk(gdf.geometry, predicate="intersects")
+        if GPD_GE_013:
+            inp, res = gdf.sindex.query(gdf.geometry, predicate="intersects")
+        else:
+            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
@@ -689,7 +696,10 @@ def __init__(self, gdf):
         self.gdf = gdf
         self.orientation = gdf.geometry.apply(self._orient)
 
-        inp, res = gdf.sindex.query_bulk(gdf.geometry, predicate="intersects")
+        if GPD_GE_013:
+            inp, res = gdf.sindex.query(gdf.geometry, predicate="intersects")
+        else:
+            inp, res = gdf.sindex.query_bulk(gdf.geometry, predicate="intersects")
         itself = inp == res
         inp = inp[~itself]
         res = res[~itself]

momepy/elements.py

@@ -9,6 +9,7 @@
 import numpy as np
 import pandas as pd
 import shapely
+from packaging.version import Version
 from scipy.spatial import Voronoi
 from shapely.geometry.base import BaseGeometry
 from shapely.ops import polygonize
@@ -24,6 +25,8 @@
     "get_network_ratio",
 ]
 
+GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
+
 
 def buffered_limit(gdf, buffer=100):
     """
@@ -448,9 +451,14 @@ def _enclosed_tessellation(
         enclosures["position"] = range(len(enclosures))
 
         # determine which polygons should be split
-        inp, res = buildings.sindex.query_bulk(
-            enclosures.geometry, predicate="intersects"
-        )
+        if GPD_GE_013:
+            inp, res = buildings.sindex.query(
+                enclosures.geometry, predicate="intersects"
+            )
+        else:
+            inp, res = buildings.sindex.query_bulk(
+                enclosures.geometry, predicate="intersects"
+            )
         unique, counts = np.unique(inp, return_counts=True)
         splits = unique[counts > 1]
         single = unique[counts == 1]
@@ -998,9 +1006,14 @@ def enclosures(
             )
         additional = pd.concat([gdf.geometry for gdf in additional_barriers])
 
-        inp, res = enclosures.sindex.query_bulk(
-            additional.geometry, predicate="intersects"
-        )
+        if GPD_GE_013:
+            inp, res = enclosures.sindex.query(
+                additional.geometry, predicate="intersects"
+            )
+        else:
+            inp, res = enclosures.sindex.query_bulk(
+                additional.geometry, predicate="intersects"
+            )
         unique = np.unique(res)
 
         new = []
@@ -1042,9 +1055,14 @@ def enclosures(
                 "`limit` requires a GeoDataFrame or GeoSeries with Polygon or "
                 "MultiPolygon geometry to be used with `clip=True`."
             )
-        _, encl_index = final_enclosures.representative_point().sindex.query_bulk(
-            limit.geometry, predicate="contains"
-        )
+        if GPD_GE_013:
+            _, encl_index = final_enclosures.representative_point().sindex.query(
+                limit.geometry, predicate="contains"
+            )
+        else:
+            _, encl_index = final_enclosures.representative_point().sindex.query_bulk(
+                limit.geometry, predicate="contains"
+            )
         keep = np.unique(encl_index)
         return final_enclosures.iloc[keep]
 

momepy/preprocessing.py

@@ -12,6 +12,7 @@
 import numpy as np
 import pandas as pd
 import shapely
+from packaging.version import Version
 from scipy.signal import find_peaks
 from scipy.stats import gaussian_kde
 from shapely.geometry import LineString, Point
@@ -33,6 +34,8 @@
     "FaceArtifacts",
 ]
 
+GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
+
 
 def preprocess(
     buildings, size=30, compactness=0.2, islands=True, loops=2, verbose=True
@@ -855,9 +858,14 @@ def _selecting_incoming_lines(rab_multipolygons, edges, angle_threshold=0):
     """
     # selecting the lines that are touching but not covered by
     touching = gpd.sjoin(edges, rab_multipolygons, predicate="touches")
-    edges_idx, rabs_idx = rab_multipolygons.sindex.query_bulk(
-        edges.geometry, predicate="covered_by"
-    )
+    if GPD_GE_013:
+        edges_idx, _ = rab_multipolygons.sindex.query(
+            edges.geometry, predicate="covered_by"
+        )
+    else:
+        edges_idx, _ = rab_multipolygons.sindex.query_bulk(
+            edges.geometry, predicate="covered_by"
+        )
     idx_drop = edges.index.take(edges_idx)
     touching_idx = touching.index
     ls = list(set(touching_idx) - set(idx_drop))

momepy/tests/test_elements.py

@@ -13,6 +13,7 @@
 
 import momepy as mm
 
+GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
 
 class TestElements:
     def setup_method(self):
@@ -146,10 +147,13 @@ def test_Blocks_inner(self):
         assert not blocks.tessellation_id.isna().any()
         assert not blocks.buildings_id.isna().any()
         assert len(blocks.blocks) == 9
-        assert (
-            len(blocks.blocks.sindex.query_bulk(blocks.blocks.geometry, "overlaps")[0])
-            == 0
-        )
+        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")