add baseline testing for utl-ncf options

autotest/test_netcdf_gwe_cnd.py

@@ -24,7 +24,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -59,7 +59,7 @@ def check_output(idx, test, export, gridded_input):
     name = "gwe-" + test.name
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{name}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{name}.nc") as ds:
         assert ds.data_model == "NETCDF4"
 
     if gridded_input == "netcdf":

autotest/test_netcdf_gwf_disv.py

@@ -14,7 +14,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 wkt = (
     'PROJCS["NAD83 / UTM zone 18N", '
@@ -54,7 +54,15 @@ def build_models(idx, test, export, gridded_input):
         gwf.name_file.nc_mesh2d_filerecord = f"{name}.nc"
 
     # netcdf config
-    ncf = flopy.mf6.ModflowUtlncf(gwf.disv, wkt=wkt, filename=f"{name}.disv.ncf")
+    ncf = flopy.mf6.ModflowUtlncf(
+        gwf.disv,
+        deflate=9,
+        shuffle=True,
+        chunk_time=1,
+        chunk_face=3,
+        wkt=wkt,
+        filename=f"{name}.disv.ncf",
+    )
 
     # output control
     oc = flopy.mf6.ModflowGwfoc(
@@ -74,8 +82,14 @@ def check_output(idx, test, export, gridded_input):
     name = test.name
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{name}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{name}.nc") as ds:
         assert ds.data_model == "NETCDF4"
+        cmpr = ds.variables["head_l1"].filters()
+        chnk = ds.variables["head_l1"].chunking()
+        assert cmpr["shuffle"]
+        assert cmpr["complevel"] == 9
+        assert chnk == [1, 3]
+        assert ds.variables["projection"].getncattr("wkt").lower() == wkt.lower()
 
     if gridded_input == "netcdf":
         # re-run the simulation with model netcdf input

autotest/test_netcdf_gwf_lak_wetlakbedarea02.py

@@ -24,7 +24,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -63,7 +63,7 @@ def check_output(idx, test, export, gridded_input):
     gwfname = "gwf-" + name
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{gwfname}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{gwfname}.nc") as ds:
         assert ds.data_model == "NETCDF4"
 
     if gridded_input == "netcdf":

autotest/test_netcdf_gwf_rch01.py

@@ -24,7 +24,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -60,7 +60,7 @@ def check_output(idx, test, export, gridded_input):
     name = "rch"
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{name}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{name}.nc") as ds:
         assert ds.data_model == "NETCDF4"
 
     if gridded_input == "netcdf":

autotest/test_netcdf_gwf_rch03.py

@@ -24,7 +24,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -61,7 +61,7 @@ def check_output(idx, test, export, gridded_input):
     name = "rch"
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{name}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{name}.nc") as ds:
         assert ds.data_model == "NETCDF4"
 
     if gridded_input == "netcdf":

autotest/test_netcdf_gwf_sto01.py

@@ -12,7 +12,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 htol = [None for _ in range(len(cases))]
 
@@ -53,15 +53,28 @@ def build_models(idx, test, export, gridded_input):
 
     if export == "ugrid":
         gwf.name_file.nc_mesh2d_filerecord = f"{name}.nc"
+        ncf = flopy.mf6.ModflowUtlncf(
+            gwf.dis,
+            deflate=5,
+            shuffle=True,
+            chunk_time=1,
+            chunk_face=10,
+            wkt=wkt,
+            filename=f"{name}.dis.ncf",
+        )
     elif export == "structured":
         gwf.name_file.nc_structured_filerecord = f"{name}.nc"
-
-    # netcdf config
-    ncf = flopy.mf6.ModflowUtlncf(
-        gwf.dis,
-        wkt=wkt,
-        filename=f"{name}.dis.ncf",
-    )
+        ncf = flopy.mf6.ModflowUtlncf(
+            gwf.dis,
+            deflate=5,
+            shuffle=True,
+            chunk_time=1,
+            chunk_z=1,
+            chunk_y=5,
+            chunk_x=5,
+            wkt=wkt,
+            filename=f"{name}.dis.ncf",
+        )
 
     return sim, dummy
 
@@ -70,8 +83,22 @@ def check_output(idx, test, export, gridded_input):
     from test_gwf_sto01 import check_output as check
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / "gwf_sto01.nc") as ds:
+    with nc.Dataset(test.workspace / "gwf_sto01.nc") as ds:
         assert ds.data_model == "NETCDF4"
+        if export == "structured":
+            cmpr = ds.variables["head"].filters()
+            chnk = ds.variables["head"].chunking()
+            assert chnk == [1, 1, 5, 5]
+            assert (
+                ds.variables["projection"].getncattr("crs_wkt").lower() == wkt.lower()
+            )
+        elif export == "ugrid":
+            cmpr = ds.variables["head_l1"].filters()
+            chnk = ds.variables["head_l1"].chunking()
+            assert chnk == [1, 10]
+            assert ds.variables["projection"].getncattr("wkt").lower() == wkt.lower()
+        assert cmpr["shuffle"]
+        assert cmpr["complevel"] == 5
 
     if gridded_input == "netcdf":
         # re-run the simulation with model netcdf input

autotest/test_netcdf_gwf_vsc03_sfr.py

@@ -24,7 +24,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -63,7 +63,7 @@ def check_output(idx, test, export, gridded_input):
     name = "gwf-" + test.name
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{name}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{name}.nc") as ds:
         assert ds.data_model == "NETCDF4"
 
     if gridded_input == "netcdf":

autotest/test_netcdf_gwt_dsp01.py

@@ -12,7 +12,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -30,14 +30,26 @@ def build_models(idx, test, export, gridded_input):
 
     if export == "ugrid":
         gwt.name_file.nc_mesh2d_filerecord = f"{gwtname}.nc"
+        ncf = flopy.mf6.ModflowUtlncf(
+            gwt.dis,
+            deflate=3,
+            shuffle=False,
+            chunk_time=1,
+            chunk_face=5,
+            filename=f"{gwtname}.dis.ncf",
+        )
     elif export == "structured":
         gwt.name_file.nc_structured_filerecord = f"{gwtname}.nc"
-
-    # netcdf config
-    ncf = flopy.mf6.ModflowUtlncf(
-        gwt.dis,
-        filename=f"{gwtname}.dis.ncf",
-    )
+        ncf = flopy.mf6.ModflowUtlncf(
+            gwt.dis,
+            deflate=3,
+            shuffle=False,
+            chunk_time=1,
+            chunk_z=1,
+            chunk_y=1,
+            chunk_x=20,
+            filename=f"{gwtname}.dis.ncf",
+        )
 
     oc = flopy.mf6.ModflowGwtoc(
         gwt,
@@ -58,8 +70,18 @@ def check_output(idx, test, export, gridded_input):
     gwtname = "gwt_" + name
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{gwtname}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{gwtname}.nc") as ds:
         assert ds.data_model == "NETCDF4"
+        if export == "structured":
+            cmpr = ds.variables["concentration"].filters()
+            chnk = ds.variables["concentration"].chunking()
+            assert chnk == [1, 1, 1, 20]
+        elif export == "ugrid":
+            cmpr = ds.variables["concentration_l1"].filters()
+            chnk = ds.variables["concentration_l1"].chunking()
+            assert chnk == [1, 5]
+        assert not cmpr["shuffle"]
+        assert cmpr["complevel"] == 3
 
     if gridded_input == "netcdf":
         # re-run the simulation with model netcdf input

autotest/test_netcdf_gwt_prudic2004t2.py

@@ -12,7 +12,7 @@
 
 xa = pytest.importorskip("xarray")
 xu = pytest.importorskip("xugrid")
-netcdf4 = pytest.importorskip("netCDF4")
+nc = pytest.importorskip("netCDF4")
 
 
 def build_models(idx, test, export, gridded_input):
@@ -49,7 +49,7 @@ def check_output(idx, test, export, gridded_input):
     gwtname = "gwt_" + name
 
     # verify format of generated netcdf file
-    with netcdf4.Dataset(test.workspace / f"{gwtname}.nc") as ds:
+    with nc.Dataset(test.workspace / f"{gwtname}.nc") as ds:
         assert ds.data_model == "NETCDF4"
 
     if gridded_input == "netcdf":