revert shapely hard dependecy

.github/workflows/unittests.yml

@@ -19,39 +19,39 @@
      strategy:
        matrix:
          os: ['ubuntu-latest']
-         environment-file: [ci/37.yaml, ci/38.yaml, ci/39.yaml, ci/310.yaml]
+         environment-file: [ci/37-minimal.yaml, ci/37.yaml, ci/38.yaml, ci/39.yaml, ci/310.yaml]
          include:
            - environment-file: ci/310.yaml
              os: macos-latest
            - environment-file: ci/310.yaml
              os: windows-latest
-     
+
      steps:
        - name: checkout repo
          uses: actions/checkout@v3
-       
+
        - name: setup micromamba
          uses: mamba-org/provision-with-micromamba@main
          with:
            environment-file: ${{ matrix.environment-file }}
            micromamba-version: 'latest'
-      
+
        - name: run tests - bash
          shell: bash -l {0}
          run: |
            ${{ env.FETCH_EXAMPLES }}
            ${{ env.RUN_TEST }}
          if: matrix.os != 'windows-latest'
-       
+
        - name: run tests - powershell
          shell: powershell
          run: |
            ${{ env.FETCH_EXAMPLES }}
            ${{ env.RUN_TEST }}
          if: matrix.os == 'windows-latest'
-      
+
        - name: codecov
-         uses: codecov/codecov-action@v2 
+         uses: codecov/codecov-action@v2
          with:
            token: ${{ secrets.CODECOV_TOKEN }}
            file: ./coverage.xml

ci/37-minimal.yaml

@@ -0,0 +1,17 @@
+name: test
+channels:
+  - conda-forge
+dependencies:
+  - python=3.7
+  - appdirs
+  - beautifulsoup4
+  - jinja2
+  - pandas>=1.0
+  - scipy>=1.0
+  - xarray
+  # testing
+  - codecov
+  - matplotlib
+  - pytest
+  - pytest-cov
+  - pytest-xdist

libpysal/cg/tests/test_voronoi.py

@@ -5,6 +5,14 @@
 from ..voronoi import voronoi, voronoi_frames
 from ..shapes import Polygon, asShape
 
+import pytest
+
+try:
+    import shapely
+    HAS_SHAPELY = True
+except ImportError:
+    HAS_SHAPELY = False
+
 
 class Voronoi(unittest.TestCase):
     def setUp(self):
@@ -29,6 +37,7 @@ def test_voronoi(self):
 
         np.testing.assert_array_almost_equal(vertices, self.vertices)
 
+    @pytest.mark.skipif(not HAS_SHAPELY, reason="shapely needed")
     def test_voronoi_frames(self):
         r_df, p_df = voronoi_frames(self.points)
         region = r_df.iloc[0]["geometry"]

libpysal/weights/tests/test_contiguity.py

@@ -9,6 +9,7 @@
 from ... import examples as pysal_examples
 import unittest as ut
 import numpy as np
+import pytest
 
 PANDAS_EXTINCT = pandas is None
 try:
@@ -18,6 +19,12 @@
 except ImportError:
     GEOPANDAS_EXTINCT = True
 
+try:
+    import shapely
+    HAS_SHAPELY = True
+except ImportError:
+    HAS_SHAPELY = False
+
 
 class Contiguity_Mixin(object):
     polygon_path = pysal_examples.get_path("columbus.shp")
@@ -90,6 +97,7 @@ def test_from_array(self):
         # test named, sparse from point array
         pass
 
+
     @ut.skipIf(PANDAS_EXTINCT, "Missing pandas")
     def test_from_dataframe(self):
         # basic
@@ -102,7 +110,12 @@ def test_from_dataframe(self):
         w = self.cls.from_dataframe(df, geom_col="the_geom")
         self.assertEqual(w[self.known_wi], self.known_w)
 
+
+    @ut.skipIf(GEOPANDAS_EXTINCT, "Missing geopandas")
+    def test_from_geodataframe(self):
+        df = pdio.read_files(self.polygon_path)
         # named active geometry
+        df.rename(columns={"geometry": "the_geom"}, inplace=True)
         df = df.set_geometry("the_geom")
         w = self.cls.from_dataframe(df)
         self.assertEqual(w[self.known_wi], self.known_w)
@@ -148,7 +161,7 @@ def setUp(self):
             (1, -90.0, 60.0): 1,
             (1, -30.0, -180.0): 1,
             (1, -30.0, 60.0): 1,
-            (1, 30.0, -180.0): 1, 
+            (1, 30.0, -180.0): 1,
             (1, 30.0, -60.0): 1,
             (1, 30.0, 60.0): 1
             }
@@ -192,6 +205,7 @@ def setUp(self):
 
 
 class Test_Voronoi(ut.TestCase):
+    @pytest.mark.skipif(not HAS_SHAPELY, reason="shapely needed")
     def test_voronoiW(self):
         np.random.seed(12345)
         points = np.random.random((5, 2)) * 10 + 10

libpysal/weights/tests/test_distance.py

@@ -12,6 +12,12 @@
 import unittest as ut
 
 PANDAS_EXTINCT = pandas is None
+try:
+    import geopandas
+
+    GEOPANDAS_EXTINCT = False
+except ImportError:
+    GEOPANDAS_EXTINCT = True
 # All instances should test these four methods, and define their own functional
 # tests based on common codepaths/estimated weights use cases.
 
@@ -107,7 +113,11 @@ def test_from_dataframe(self):
         self.assertEqual(w.neighbors[self.known_wi0], self.known_w0)
         self.assertEqual(w.neighbors[self.known_wi1], self.known_w1)
 
+    @ut.skipIf(GEOPANDAS_EXTINCT, "Missing geopandas")
+    def test_from_geodataframe(self):
+        df = pdio.read_files(self.polygon_path)
         # named active geometry
+        df.rename(columns={"geometry": "the_geom"}, inplace=True)
         df = df.set_geometry("the_geom")
         w = d.KNN.from_dataframe(df, k=4)
         self.assertEqual(w.neighbors[self.known_wi0], self.known_w0)
@@ -176,7 +186,6 @@ def test_from_array(self):
     @ut.skipIf(PANDAS_EXTINCT, "Missing pandas")
     def test_from_dataframe(self):
         import pandas as pd
-        import geopandas as gpd
 
         geom_series = pdio.shp.shp2series(self.grid_path)
         random_data = np.random.random(size=len(geom_series))
@@ -185,6 +194,17 @@ def test_from_dataframe(self):
         for k, v in w:
             self.assertEqual(v, self.grid_rook_w[k])
 
+    @ut.skipIf(GEOPANDAS_EXTINCT, "Missing geopandas")
+    def test_from_geodataframe(self):
+        import geopandas as gpd
+        import pandas as pd
+
+        geom_series = pdio.shp.shp2series(self.grid_path)
+        random_data = np.random.random(size=len(geom_series))
+        df = pd.DataFrame({"obs": random_data, "geometry": geom_series})
+        w = d.DistanceBand.from_dataframe(df, 1)
+        for k, v in w:
+            self.assertEqual(v, self.grid_rook_w[k])
         # named geometry
         df = gpd.GeoDataFrame(df)
         df.rename(columns={"geometry": "the_geom"}, inplace=True)
@@ -329,6 +349,9 @@ def test_from_dataframe(self):
         for k, v in list(w[self.known_wi5 - 1].items()):
             np.testing.assert_allclose(v, self.known_w5[k + 1], rtol=RTOL)
 
+    @ut.skipIf(GEOPANDAS_EXTINCT, "Missing geopandas")
+    def test_from_geodataframe(self):
+        df = pdio.read_files(self.polygon_path)
         # named geometry
         df.rename(columns={"geometry": "the_geom"}, inplace=True)
         w = d.Kernel.from_dataframe(df, geom_col="the_geom")

libpysal/weights/tests/test_gabriel.py

@@ -1,6 +1,9 @@
 from .. import gabriel
 from ... import examples
-import geopandas, numpy
+import numpy
+import pytest
+
+geopandas = pytest.importorskip("geopandas")
 
 path = examples.get_path("columbus.shp")
 df = geopandas.read_file(path)

libpysal/weights/util.py

@@ -1,4 +1,3 @@
-from shapely.geometry.base import BaseGeometry
 from ..io.fileio import FileIO as psopen
 from .weights import W, WSP
 from .set_operations import w_subset
@@ -23,6 +22,12 @@
 except ImportError:
     warn("geopandas not available. Some functionality will be disabled.")
 
+try:
+    from shapely.geometry.base import BaseGeometry
+    HAS_SHAPELY = True
+except ImportError:
+    HAS_SHAPELY = False
+
 __all__ = [
     "lat2W",
     "block_weights",
@@ -1071,14 +1076,22 @@ def get_points_array(iterable):
     """
     first_choice, backup = tee(iterable)
     try:
-        data = np.vstack(
-            [
-                np.array(shape.centroid.coords)[0]
-                if isinstance(shape, BaseGeometry)
-                else np.array(shape.centroid)
-                for shape in first_choice
-            ]
-        )
+        if HAS_SHAPELY:
+            data = np.vstack(
+                [
+                    np.array(shape.centroid.coords)[0]
+                    if isinstance(shape, BaseGeometry)
+                    else np.array(shape.centroid)
+                    for shape in first_choice
+                ]
+            )
+        else:
+            data = np.vstack(
+                [
+                    np.array(shape.centroid)
+                    for shape in first_choice
+                ]
+            )
     except AttributeError:
         data = np.vstack([shape for shape in backup])
     return data