Feature: individual process models run from separated parameters.

autotest/test_atmosphere.py

@@ -9,9 +9,16 @@
 from pywatershed.parameters import PrmsParameters
 
 
-@pytest.fixture(scope="function")
-def params(domain):
-    return PrmsParameters.load(domain["param_file"])
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSAtmosphere.nc"
+        )
+
+    return params
 
 
 @pytest.fixture(scope="function")

autotest/test_canopy.py

@@ -58,9 +58,16 @@ def test_simple():
     return
 
 
-@pytest.fixture(scope="function")
-def params(domain):
-    return PrmsParameters.load(domain["param_file"])
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSCanopy.nc"
+        )
+
+    return params
 
 
 @pytest.fixture(scope="function")
@@ -136,45 +143,5 @@ def test_compare_prms(domain, control, tmp_path, calc_method):
 
     if not all_success:
         raise Exception("pywatershed results do not match prms results")
-    # is comparing along the way slower or faster than comparing netcdf?
-
-    # prms_output_dataframes = {}
-    # for cv in comparison_variables:
-    #     fname = prms_output_files[cv]
-    #     print(f"loading {fname}")
-    #     csvobj = CsvFile(fname)
-    #     df = csvobj.to_dataframe()
-    #     prms_output_dataframes[cv] = df
-
-    # # get a dictionary of dataframes for process model output
-    # pyws_output_dataframes = cnp.get_output_dataframes()
-
-    # # compare prms and pywatershed data
-    # for cv in comparison_variables:
-    #     prms_data = prms_output_dataframes[cv]
-    #     pyws_data = pyws_output_dataframes[cv]
-
-    #     print(f"\n{50*'*'}")
-    #     print(f"{cv}  min  max")
-    #     a1 = prms_data.to_numpy()
-    #     a2 = pyws_data.to_numpy()
-    #     diff = a1 - a2
-    #     diffmin = diff.min()
-    #     diffmax = diff.max()
-    #     print(f"prms   {a1.min()}    {a1.max()}")
-    #     print(f"pywatershed  {a2.min()}    {a2.max()}")
-    #     print(f"diff   {diffmin}  {diffmax}")
-
-    #     atol = 1.0e-5
-    #     errmsg = f"Canopy variable {cv} does not match to within {atol}"
-    #     assert np.allclose(diffmin, 0.0, atol=atol), errmsg
-    #     assert np.allclose(diffmax, 0.0, atol=atol), errmsg
-
-    # # save cnp output as dataframes in temp/domain_name
-    # saveoutput = False
-    # if saveoutput:
-    #     pth = pathlib.Path(".", "temp", domain["domain_name"])
-    #     pth.mkdir(parents=True, exist_ok=True)
-    #     cnp.output_to_csv(pth)
 
     return

autotest/test_channel.py

@@ -12,18 +12,31 @@
 calc_methods = ("numpy", "numba", "fortran")
 
 
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSChannel.nc"
+        )
+
+    return params
+
+
+@pytest.fixture(scope="function")
+def control(domain, params):
+    return Control.load(domain["control_file"], params=params)
+
+
 @pytest.mark.parametrize("calc_method", calc_methods)
-def test_compare_prms(domain, tmp_path, calc_method):
+def test_compare_prms(domain, control, tmp_path, calc_method):
     if not has_prmschannel_f and calc_method == "fortran":
         pytest.skip(
             "PRMSChannel fortran code not available, skipping its test."
         )
 
     tmp_path = pl.Path(tmp_path)
-    params = PrmsParameters.load(domain["param_file"])
-
-    # Set information from the control file
-    control = Control.load(domain["control_file"], params=params)
 
     # load csv files into dataframes
     output_dir = domain["prms_output_dir"]

autotest/test_groundwater.py

@@ -13,18 +13,31 @@
 calc_methods = ("numpy", "numba", "fortran")
 
 
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSGroundwater.nc"
+        )
+
+    return params
+
+
+@pytest.fixture(scope="function")
+def control(domain, params):
+    return Control.load(domain["control_file"], params=params)
+
+
 @pytest.mark.parametrize("calc_method", calc_methods)
-def test_compare_prms(domain, tmp_path, calc_method):
+def test_compare_prms(domain, control, tmp_path, calc_method):
     if not has_prmsgroundwater_f and calc_method == "fortran":
         pytest.skip(
             "PRMSGroundwater fortran code not available, skipping its test."
         )
 
     tmp_path = pl.Path(tmp_path)
-    params = PrmsParameters.load(domain["param_file"])
-
-    # Set information from the control file
-    control = Control.load(domain["control_file"], params=params)
 
     # load csv files into dataframes
     output_dir = domain["prms_output_dir"]

autotest/test_param_separate.py

@@ -2,11 +2,10 @@
 
 import numpy as np
 import pytest
-import xarray as xr
 
 import pywatershed
 from pywatershed.base.control import Control
-from pywatershed.base.data_model import xr_ds_to_dd
+from pywatershed.base.data_model import open_datasetdict
 from pywatershed.parameters import PrmsParameters
 from pywatershed.utils import separate_domain_params_to_ncdf
 
@@ -52,16 +51,21 @@ def test_param_sep(domain, control, use_xr, tmp_path):
 
     # check roundtrip to file and back
     for proc_class, proc_file in proc_nc_files.items():
-        params_file = xr_ds_to_dd(xr.open_dataset(proc_file))
-        assert set(params_file["data_vars"].keys()) == set(
-            proc_class.get_parameters()
+        params_file = open_datasetdict(proc_file)
+        # some coords in the file may not be in the parameters
+        coords_not_in_params = set(params_file.variables.keys()).difference(
+            set(proc_class.get_parameters())
+        )
+        # assert that any coords not in the class params are in the file coords
+        assert not len(
+            coords_not_in_params.difference(set(params_file["coords"].keys()))
         )
 
         # checking dim equality is not necessary, it is covered by the
         # metadata check
         for param in proc_class.get_parameters():
             np.testing.assert_equal(
-                params_file["data_vars"][param],
+                params_file.variables[param],
                 control.params.parameters[param],
             )
             np.testing.assert_equal(

autotest/test_runoff.py

@@ -11,9 +11,16 @@
 calc_methods = ("numpy", "numba")
 
 
-@pytest.fixture(scope="function")
-def params(domain):
-    return PrmsParameters.load(domain["param_file"])
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSRunoff.nc"
+        )
+
+    return params
 
 
 @pytest.fixture(scope="function")

autotest/test_snow.py

@@ -9,20 +9,26 @@
 from pywatershed.hydrology.PRMSSnow import PRMSSnow
 from pywatershed.parameters import PrmsParameters
 
+calc_methods = ("numpy", "numba")
 
-@pytest.fixture(scope="function")
-def params(domain):
-    return PrmsParameters.load(domain["param_file"])
+
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSSnow.nc"
+        )
+
+    return params
 
 
 @pytest.fixture(scope="function")
 def control(domain, params):
     return Control.load(domain["control_file"], params=params)
 
 
-calc_methods = ("numpy", "numba")
-
-
 @pytest.mark.xfail
 @pytest.mark.parametrize("calc_method", calc_methods)
 class TestPRMSSnow:

autotest/test_soilzone.py

@@ -11,9 +11,16 @@
 calc_methods = ("numpy", "numba")
 
 
-@pytest.fixture(scope="function")
-def params(domain):
-    return PrmsParameters.load(domain["param_file"])
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSSoilzone.nc"
+        )
+
+    return params
 
 
 @pytest.fixture(scope="function")

autotest/test_solar_geom.py

@@ -6,9 +6,16 @@
 from pywatershed.parameters import PrmsParameters
 
 
-@pytest.fixture(scope="function")
-def params(domain):
-    return PrmsParameters.load(domain["param_file"])
+@pytest.fixture(scope="function", params=["params_sep", "params_one"])
+def params(domain, request):
+    if request.param == "params_one":
+        params = PrmsParameters.load(domain["param_file"])
+    else:
+        params = PrmsParameters.from_netcdf(
+            domain["dir"] / "parameters_PRMSSolarGeometry.nc"
+        )
+
+    return params
 
 
 @pytest.fixture(scope="function")

pywatershed/atmosphere/PRMSAtmosphere.py

@@ -206,15 +206,12 @@ def _calculate_all_time(self):
 
     @staticmethod
     def get_dimensions():
-        return (
-            "nhru",
-            "nmonth",
-            "ntime",
-        )
+        return ("nhru", "nmonth", "ndoy", "ntime")
 
     @staticmethod
     def get_parameters():
         return (
+            "doy",
             "radadj_intcp",
             "radadj_slope",
             "tmax_index",

pywatershed/atmosphere/PRMSSolarGeometry.py

@@ -49,12 +49,14 @@ def __init__(
         netcdf_separate_files: bool = True,
         netcdf_output_vars: list = None,
     ):
-        # This is a singular case of having a constant parameter dimensions
-        self.ndoy = doy
-
         budget_type = None
         self._set_budget(budget_type)
         self.netcdf_output_dir = netcdf_output_dir
+
+        # self._time is needed by storageUnit for timeseries arrays
+        # TODO: this is redundant because the parameter doy is set
+        #       on load of prms file. Could pass the name to use for
+        #       self._time to super or come up with some other work around.
         self._time = doy
 
         super().__init__(
@@ -123,6 +125,7 @@ def get_dimensions() -> tuple:
     @staticmethod
     def get_parameters() -> tuple:
         return (
+            "doy",
             "hru_slope",
             "radj_sppt",
             "radj_wppt",
@@ -441,7 +444,7 @@ def _write_netcdf_timeseries(self) -> None:
                 nc.add_all_data(
                     var,
                     self[var].data,
-                    self._time,
+                    self.doy,
                     time_coord="doy",
                 )
                 nc.close()
@@ -462,7 +465,7 @@ def _write_netcdf_timeseries(self) -> None:
                 nc.add_all_data(
                     var,
                     self[var].data,
-                    self._time,
+                    self.doy,
                     time_coord="doy",
                 )