feat(GeoDataFrame support): geopandas support for shapefile exporting

autotest/test_binaryfile.py

@@ -274,7 +274,7 @@ def test_load_binary_head_file(example_data_path):
 
 def test_plot_binary_head_file(example_data_path):
     hf = HeadFile(example_data_path / "freyberg" / "freyberg.githds")
-    hf.mg.set_coord_info(xoff=1000.0, yoff=200.0, angrot=15.0)
+    hf.modelgrid.set_coord_info(xoff=1000.0, yoff=200.0, angrot=15.0)
 
     assert isinstance(hf.plot(), Axes)
     plt.close()

autotest/test_formattedfile.py

@@ -69,7 +69,7 @@ def test_headfile_build_index(example_data_path):
 def test_formattedfile_reference(example_data_path):
     h = FormattedHeadFile(example_data_path / "mf2005_test" / "test1tr.githds")
     assert isinstance(h, FormattedHeadFile)
-    h.mg.set_coord_info(xoff=1000.0, yoff=200.0, angrot=15.0)
+    h.modelgrid.set_coord_info(xoff=1000.0, yoff=200.0, angrot=15.0)
 
     assert isinstance(h.plot(masked_values=[6999.000]), Axes)
     plt.close()

autotest/test_geospatial_util.py

@@ -374,7 +374,7 @@ def test_polygon_collection(polygon, poly_w_hole, multipolygon):
     points = gc1.points
     geojson = gc1.geojson
     fp_geo = gc1.flopy_geometry
-    gdf = gc1.geo_dataframe
+    gdf = gc1.geodataframe
 
     collections = [shp, shply, points, geojson, fp_geo, gdf]
     for col in collections:
@@ -408,7 +408,7 @@ def test_point_collection(point, multipoint):
     points = gc1.points
     geojson = gc1.geojson
     fp_geo = gc1.flopy_geometry
-    gdf = gc1.geo_dataframe
+    gdf = gc1.geodataframe
 
     collections = [shp, shply, points, geojson, fp_geo, gdf]
     for col in collections:
@@ -436,7 +436,7 @@ def test_linestring_collection(linestring, multilinestring):
     points = gc1.points
     geojson = gc1.geojson
     fp_geo = gc1.flopy_geometry
-    gdf = gc1.geo_dataframe
+    gdf = gc1.geodataframe
 
     collections = [shp, shply, points, geojson, fp_geo, gdf]
     for col in collections:
@@ -481,7 +481,7 @@ def test_mixed_collection(
     points = gc1.points
     geojson = gc1.geojson
     fp_geo = gc1.flopy_geometry
-    gdf = gc1.geo_dataframe
+    gdf = gc1.geodataframe
 
     collections = [shp, shply, lshply, points, geojson, fp_geo, gdf]
     for col in collections:
@@ -525,7 +525,7 @@ def test_geopandas_dtypes(
     col = Collection(col)
 
     gc1 = GeoSpatialCollection(col)
-    gdf = gc1.geo_dataframe
+    gdf = gc1.geodataframe
 
     collections = [gdf, gdf.geometry, gdf.geometry.values]
     for col in collections:

autotest/test_grid.py

@@ -1585,14 +1585,14 @@ def test_unstructured_convert(unstructured_grid):
 
 
 @requires_pkg("geopandas")
-def test_geo_dataframe(structured_grid, vertex_grid, unstructured_grid):
+def test_geodataframe(structured_grid, vertex_grid, unstructured_grid):
     geopandas = import_optional_dependency("geopandas")
     grids = (structured_grid, vertex_grid, unstructured_grid)
 
     for grid in grids:
-        gdf = grid.geo_dataframe
+        gdf = grid.to_geodataframe()
         if not isinstance(gdf, geopandas.GeoDataFrame):
-            raise TypeError("geo_dataframe not returning GeoDataFrame object")
+            raise TypeError("geodataframe not returning GeoDataFrame object")
 
         geoms = gdf.geometry.values
         for node, geom in enumerate(geoms):

autotest/test_modpathfile.py

@@ -308,9 +308,9 @@ def test_get_destination_endpoint_data(
 
 @pytest.mark.parametrize("longfieldname", [True, False])
 @requires_exe("mf6", "mp7")
-@requires_pkg("pyshp", "shapely", name_map={"pyshp": "shapefile"})
+@requires_pkg("geopandas", "shapely")
 def test_write_shapefile(function_tmpdir, mp7_small, longfieldname):
-    from shapefile import Reader
+    import geopandas as gpd
 
     # setup and run model, then copy outputs to function_tmpdir
     sim, forward_model_name, _, _, _ = mp7_small
@@ -330,13 +330,7 @@ def test_write_shapefile(function_tmpdir, mp7_small, longfieldname):
     # define shapefile path
     shp_file = ws / "pathlines.shp"
 
-    # add a column to the pathline recarray
-    fieldname = "newfield" + ("longname" if longfieldname else "")
-    fieldval = "x"
-    pathlines = [
-        rfn.append_fields(pl, fieldname, list(repeat(fieldval, len(pl))), dtypes="|U1")
-        for pl in pathlines
-    ]
+    pline_names = [name[:10] for name in pathlines[0].dtype.names]
 
     # write the pathline recarray to shapefile
     pathline_file.write_shapefile(
@@ -350,8 +344,7 @@ def test_write_shapefile(function_tmpdir, mp7_small, longfieldname):
     assert shp_file.is_file()
 
     # load shapefile
-    with Reader(shp_file) as reader:
-        fieldnames = [f[0] for f in reader.fields[1:]]
-        fieldname = "newfiname_" if longfieldname else fieldname
-        assert fieldname in fieldnames
-        assert all(r[fieldname] == fieldval for r in reader.iterRecords())
+    gdf = gpd.read_file(shp_file)
+    fieldnames = list(gdf)
+    for fname in pline_names:
+        assert fname in fieldnames

flopy/discretization/grid.py

@@ -593,7 +593,7 @@ def xyzvertices(self):
     def cross_section_vertices(self):
         return self.xyzvertices[0], self.xyzvertices[1]
 
-    def geo_dataframe(self, features, featuretype="Polygon"):
+    def to_geodataframe(self, features, featuretype="Polygon"):
         """
         Method returns a geopandas GeoDataFrame of the Grid
 
@@ -606,23 +606,22 @@ def geo_dataframe(self, features, featuretype="Polygon"):
         gc = GeoSpatialCollection(
             features, shapetype=[featuretype for _ in range(len(features))]
         )
-        gdf = gc.geo_dataframe
+        gdf = gc.geodataframe
         gdf["node"] = gdf.index + 1
         if self.crs is not None:
             gdf = gdf.set_crs(crs=self.crs)
 
         return gdf
 
-    @property
-    def grid_line_geo_dataframe(self):
+    def grid_line_geodataframe(self):
         """
         Method to get a GeoDataFrame of grid lines
 
         Returns
         -------
             GeoDataFrame
         """
-        gdf = self.geo_dataframe(self.grid_lines, featuretype="LineString")
+        gdf = self.to_geodataframe(self.grid_lines, featuretype="LineString")
         gdf = gdf.rename(columns={"node": "number"})
         return gdf
 

flopy/discretization/structuredgrid.py

@@ -759,8 +759,7 @@ def map_polygons(self):
 
         return self._polygons
 
-    @property
-    def geo_dataframe(self):
+    def to_geodataframe(self):
         """
         Returns a geopandas GeoDataFrame of the model grid
 
@@ -769,11 +768,28 @@ def geo_dataframe(self):
             GeoDataFrame
         """
         polys = [[list(zip(*i))] for i in zip(*self.cross_section_vertices)]
-        gdf = super().geo_dataframe(polys)
+        gdf = super().to_geodataframe(polys)
         gdf["row"] = sorted(list(range(1, self.nrow + 1)) * self.ncol)
         gdf["col"] = list(range(1, self.ncol + 1)) * self.nrow
         return gdf
 
+    @property
+    def geo_dataframe(self):
+        """
+        Returns a geopandas GeoDataFrame of the model grid
+
+        Returns
+        -------
+            GeoDataFrame
+        """
+        import warnings
+
+        warnings.warn(
+            "geo_dataframe has been deprecated, use to_geodataframe() instead",
+            DeprecationWarning,
+        )
+        return self.to_geodataframe()
+
     def convert_grid(self, factor):
         """
         Method to scale the model grid based on user supplied scale factors

flopy/discretization/unstructuredgrid.py

@@ -580,8 +580,7 @@ def map_polygons(self):
 
         return copy.copy(self._polygons)
 
-    @property
-    def geo_dataframe(self):
+    def to_geodataframe(self):
         """
         Returns a geopandas GeoDataFrame of the model grid
 
@@ -590,9 +589,26 @@ def geo_dataframe(self):
             GeoDataFrame
         """
         polys = [[self.get_cell_vertices(nn)] for nn in range(self.nnodes)]
-        gdf = super().geo_dataframe(polys)
+        gdf = super().to_geodataframe(polys)
         return gdf
 
+    @property
+    def geo_dataframe(self):
+        """
+        Returns a geopandas GeoDataFrame of the model grid
+
+        Returns
+        -------
+            GeoDataFrame
+        """
+        import warnings
+
+        warnings.warn(
+            "geo_dataframe has been deprecated, use to_geodataframe() instead",
+            DeprecationWarning,
+        )
+        return self.to_geodataframe()
+
     def neighbors(self, node=None, **kwargs):
         """
         Method to get nearest neighbors of a cell

flopy/discretization/vertexgrid.py

@@ -300,8 +300,7 @@ def map_polygons(self):
 
         return copy.copy(self._polygons)
 
-    @property
-    def geo_dataframe(self):
+    def to_geodataframe(self):
         """
         Returns a geopandas GeoDataFrame of the model grid
 
@@ -313,9 +312,26 @@ def geo_dataframe(self):
         featuretype = "Polygon"
         if self._cell1d is not None:
             featuretype = "multilinestring"
-        gdf = super().geo_dataframe(cells, featuretype)
+        gdf = super().to_geodataframe(cells, featuretype)
         return gdf
 
+    @property
+    def geo_dataframe(self):
+        """
+        Returns a geopandas GeoDataFrame of the model grid
+
+        Returns
+        -------
+            GeoDataFrame
+        """
+        import warnings
+
+        warnings.warn(
+            "geo_dataframe has been deprecated, use to_geodataframe() instead",
+            DeprecationWarning,
+        )
+        return self.to_geodataframe()
+
     def convert_grid(self, factor):
         """
         Method to scale the model grid based on user supplied scale factors