fix(to_geodataframe): add logic for implicit stress period data

autotest/test_export.py

@@ -977,6 +977,77 @@ def test_export_huge_shapefile(function_tmpdir):
     gdf.to_file(function_tmpdir / "huge.shp")
 
 
+@requires_pkg("geopandas")
+def test_to_geodataframe_incomplete_stress_period_data():
+    sim = flopy.mf6.MFSimulation()
+    tdis = flopy.mf6.ModflowTdis(
+        sim,
+        nper=2,
+        perioddata=[(1, 1, 1), (1, 1, 1)],
+    )
+    ims = flopy.mf6.ModflowIms(sim)
+
+    gwf = flopy.mf6.ModflowGwf(sim, modelname="dev_gdf")
+
+    dis = flopy.mf6.ModflowGwfdis(
+        gwf, nlay=1, nrow=10, ncol=11, delc=100, delr=100, top=100, botm=0, idomain=1
+    )
+
+    npf = flopy.mf6.ModflowGwfnpf(
+        gwf,
+        k=10,
+    )
+
+    ic = flopy.mf6.ModflowGwfic(gwf, strt=99)
+
+    chd_rec = [(0, i, 0, 95) for i in range(10)]
+    chd = flopy.mf6.ModflowGwfchd(gwf, stress_period_data={0: chd_rec})
+
+    ghb_rec = [(0, i, 10, 85.0, 10.0) for i in range(10)]
+    ghb = flopy.mf6.ModflowGwfghb(gwf, stress_period_data={0: ghb_rec, 1: ghb_rec})
+
+    rch_rec = np.full((10, 11), 0.0005)
+    rch_rec[:, 0] = 0
+    rch_rec[:, -1] = 0
+    rch = flopy.mf6.ModflowGwfrcha(gwf, recharge={0: rch_rec})
+
+    wel_rec = [
+        (0, 4, 5, -1500.0),
+    ]
+    wel = flopy.mf6.ModflowGwfwel(gwf, stress_period_data={0: wel_rec})
+
+    recharge = rch.recharge.array[0].ravel()
+    gdf = rch.to_geodataframe(kper=1)
+
+    np.testing.assert_allclose(
+        recharge,
+        gdf["rcha_recharge_1"].values,
+        err_msg="GeoDataFrame does not match recharge values from package",
+    )
+
+    wel_data = wel.stress_period_data.to_array(kper=0, mask=True)["q"].ravel()
+    gdf = wel.to_geodataframe(kper=1)
+    np.testing.assert_allclose(
+        wel_data,
+        gdf["wel_q_0_1"].values,
+        err_msg="GeoDataFrame does not match pumping values from wel package",
+    )
+
+    gdf = gwf.to_geodataframe(kper=1)
+
+    np.testing.assert_allclose(
+        recharge,
+        gdf["rcha_recharge_1"].values,
+        err_msg="GeoDataFrame from gwf does not match recharge values from package",
+    )
+
+    np.testing.assert_allclose(
+        wel_data,
+        gdf["wel_q_0_1"].values,
+        err_msg="GeoDataFrame from gwf does not match pumping values from wel package",
+    )
+
+
 @requires_pkg("netCDF4", "pyproj")
 def test_polygon_from_ij(function_tmpdir):
     """test creation of a polygon from an i, j location using get_vertices()."""

flopy/mf6/data/mfdataarray.py

@@ -823,6 +823,7 @@ def _get_data(self, layer=None, apply_mult=False, **kwargs):
                     and kwargs["array"]
                     and isinstance(self, MFTransientArray)
                     and data is not []  # noqa: F632
+                    and data is not None
                 ):
                     data = np.expand_dims(data, 0)
                 return data
@@ -1889,7 +1890,10 @@ def _get_array(self, num_sp, apply_mult, **kwargs):
                 if sp in self._data_storage:
                     self.get_data_prep(sp)
                     data = super().get_data(apply_mult=apply_mult, **kwargs)
-                    data = np.expand_dims(data, 0)
+                    if data is not None:
+                        data = np.expand_dims(data, 0)
+                    else:
+                        data = output
                 else:
                     # if there is no previous data provide array of
                     # zeros, otherwise provide last array of data found
@@ -2057,6 +2061,13 @@ def to_geodataframe(self, gdf=None, kper=0, full_grid=True, shorten_attr=False,
                 name = f"{self.path[1]}_{self.name}"
 
             data = self.get_data(key=kper, apply_mult=True)
+            if data is None:
+                per_with_data = np.array([i for i, v in self.empty_keys.items() if not v])
+                per_with_data = per_with_data[per_with_data < kper]
+                if len(per_with_data) == 0:
+                    return gdf
+                data = self.get_data(key=per_with_data[-1], apply_mult=True)
+
             if data.size == ncpl:
                 name = f"{name}_{kper}"
                 gdf[name] = data.ravel()

flopy/mf6/data/mfdatalist.py

@@ -1697,9 +1697,17 @@ def to_geodataframe(self, gdf=None, kper=0, full_grid=True, shorten_attr=False,
             if gdf is None:
                 gdf = modelgrid.to_geodataframe()
 
+            if self.data is None:
+                return gdf
+
             data = self.to_array(kper=kper, mask=True)
             if data is None:
-                return gdf
+                # get data from the last stress period where data was specified
+                per_with_data = np.array([i for i, v in self.data.items() if v is not None])
+                per_with_data = per_with_data[per_with_data < kper]
+                if len(per_with_data) == 0:
+                    return gdf
+                data = self.to_array(kper=per_with_data[-1], mask=True)
 
             col_names = []
             for name, array3d in data.items():

flopy/mf6/data/mfdataplist.py

@@ -1968,7 +1968,17 @@ def to_geodataframe(
             if gdf is None:
                 gdf = modelgrid.to_geodataframe()
 
+            if self.data is None:
+                return gdf
+
             data = self.to_array(kper=kper, mask=True)
+            if data is None:
+                # get data from the last stress period where data was specified
+                per_with_data = np.array([i for i, v in self.data.items() if v is not None])
+                per_with_data = per_with_data[per_with_data < kper]
+                if len(per_with_data) == 0:
+                    return gdf
+                data = self.to_array(kper=per_with_data[-1], mask=True)
 
             col_names = []
             for name, array3d in data.items():

flopy/utils/rasters.py

@@ -1,5 +1,6 @@
 import warnings
 from os import PathLike
+from pathlib import Path
 from typing import Union
 
 import numpy as np
@@ -828,21 +829,21 @@ def get_array(self, band, masked=True):
 
         return array
 
-    def write(self, name):
+    def write(self, name: Union[str, PathLike]):
         """
         Method to write raster data to a .tif
         file
 
         Parameters
         ----------
-        name : str
+        name : PathLike
             output raster .tif file name
 
         """
         rasterio = import_optional_dependency("rasterio")
 
-        if not name.endswith(".tif"):
-            name += ".tif"
+        if not str(name).endswith(".tif"):
+            name = Path(f"{name!s}.tif")
 
         with rasterio.open(name, "w", **self._meta) as foo:
             for band, arr in self.__arr_dict.items():