Issue #963 dump meta swap model nc

docs/api/changelog.rst

@@ -102,6 +102,9 @@ Added
 - Functionality to dump and load MODFLOW 6 simulations to/from zarr and zipstore
   formats. See :meth:`imod.mf6.Modflow6Simulation.dump` and
   :meth:`imod.mf6.Modflow6Simulation.from_file` for more information.
+- Functionality to dump and load MetaSwap models to/from netcdf
+  format. See :meth:`imod.msw.MetaSwapModel.dump` and
+  :meth:`imod.msw.MetaSwapModel.from_file` for more information.
 
 Changed
 ~~~~~~~

docs/api/msw.rst

@@ -11,6 +11,7 @@ Model objects & methods
 
     MetaSwapModel
     MetaSwapModel.write
+    MetaSwapModel.dump
     MetaSwapModel.from_imod5_data
     MetaSwapModel.regrid_like
     MetaSwapModel.clip_box
@@ -172,4 +173,4 @@ Mappings
     CouplerMapping.clip_box
     CouplerMapping.from_imod5_data
     CouplerMapping.get_regrid_methods
-    CouplerMapping.write
+    CouplerMapping.write

imod/common/utilities/dump_model.py

@@ -0,0 +1,86 @@
+import collections
+from pathlib import Path
+from typing import Any, Optional
+
+import tomli_w
+
+from imod.common.interfaces.imodel import IModel
+from imod.common.serializer import EngineType
+from imod.logging.logging_decorators import standard_log_decorator
+from imod.mf6.validation_settings import ValidationSettings
+from imod.schemata import ValidationError
+
+
+@standard_log_decorator()
+def dump_model(
+    model: IModel,
+    directory,
+    modelname,
+    validate: bool = True,
+    mdal_compliant: bool = False,
+    crs: Optional[Any] = None,
+    engine: EngineType = "netcdf4",
+) -> Path:
+    """
+    Dump  model to files. Writes a model definition as .TOML file, which
+    points to data for each package. Each package is stored as a separate
+    NetCDF. Structured grids are saved as regular NetCDFs, unstructured
+    grids are saved as UGRID NetCDF. Structured grids are always made GDAL
+    compliant, unstructured grids can be made MDAL compliant optionally.
+
+    Parameters
+    ----------
+    directory: str or Path
+        directory to dump simulation into.
+    modelname: str
+        modelname, will be used to create a subdirectory.
+    validate: bool, optional
+        Whether to validate simulation data. Defaults to True.
+    mdal_compliant: bool, optional
+        Convert data with
+        :func:`imod.prepare.spatial.mdal_compliant_ugrid2d` to MDAL
+        compliant unstructured grids. Defaults to False.
+    crs: Any, optional
+        Anything accepted by rasterio.crs.CRS.from_user_input
+        Requires ``rioxarray`` installed.
+    engine : str, optional
+        File engine used to write packages. Options are ``'netcdf4'``,
+        ``'zarr'``, and ``'zarr.zip'``. NetCDF4 is readable by many other
+        softwares, for example QGIS. Zarr is optimized for big data, cloud
+        storage and parallel access. The ``'zarr.zip'`` option is an
+        experimental option which creates a zipped zarr store in a single
+        file, which is easier to copy and automatically compresses data as
+        well. Default is ``'netcdf4'``.
+
+    """
+    modeldirectory = Path(directory) / modelname
+    modeldirectory.mkdir(exist_ok=True, parents=True)
+
+    # validation currently only supports MF6, but we want to keep the option to turn it on for other
+    validation_context = ValidationSettings(validate=validate)
+    if validation_context.validate:
+        statusinfo = model.validate(modelname, validation_context)
+        if statusinfo.has_errors():
+            raise ValidationError(statusinfo.to_string())
+
+    toml_content: dict = collections.defaultdict(dict)
+
+    for pkgname, pkg in model.items():
+        pkg_path = pkg.to_file(
+            modeldirectory,
+            pkgname,
+            mdal_compliant=mdal_compliant,
+            crs=crs,
+            engine=engine,
+        )
+        toml_content[type(pkg).__name__][pkgname] = pkg_path.name
+
+    # simulation settings are only relevant/present for MetaSwap models (msw)
+    if hasattr(model, "simulation_settings"):
+        toml_content["simulation_settings"] = model.simulation_settings
+
+    toml_path = modeldirectory / f"{modelname}.toml"
+    with open(toml_path, "wb") as f:
+        tomli_w.dump(toml_content, f)
+
+    return toml_path

imod/common/utilities/value_filters.py

@@ -1,10 +1,22 @@
+import numbers
 from typing import Any
 
 import numpy as np
 import xarray as xr
 from xarray.core.utils import is_scalar
 
-from imod.typing import GridDataset
+from imod.typing import GridDataArray, GridDataset
+
+
+def is_scalar_nan(da: GridDataArray):
+    """
+    Test if is_scalar_nan, carefully avoid loading grids in memory
+    """
+    scalar_data: bool = is_scalar(da)
+    if scalar_data:
+        stripped_value = da.to_numpy()[()]
+        return isinstance(stripped_value, numbers.Real) and np.isnan(stripped_value)  # type: ignore[call-overload]
+    return False
 
 
 def is_valid(value: Any) -> bool:

imod/mf6/model.py

@@ -12,7 +12,6 @@
 import jinja2
 import numpy as np
 import tomli
-import tomli_w
 import xarray as xr
 import xugrid as xu
 from jinja2 import Template
@@ -22,6 +21,7 @@
 from imod.common.serializer import EngineType
 from imod.common.statusinfo import NestedStatusInfo, StatusInfo, StatusInfoBase
 from imod.common.utilities.clip import clip_box_dataset
+from imod.common.utilities.dump_model import dump_model
 from imod.common.utilities.mask import mask_all_packages
 from imod.common.utilities.regrid import _regrid_like
 from imod.common.utilities.schemata import (
@@ -617,60 +617,57 @@ def dump(
         engine: EngineType = "netcdf4",
     ) -> Path:
         """
-        Dump simulation to files. Writes a model definition as .TOML file, which
-        points to data for each package. Each package is stored as a separate
-        NetCDF. Structured grids are saved as regular NetCDFs, unstructured
-        grids are saved as UGRID NetCDF. Structured grids are always made GDAL
-        compliant, unstructured grids can be made MDAL compliant optionally.
-
-        Parameters
-        ----------
-        directory: str or Path
-            directory to dump simulation into.
-        modelname: str
-            modelname, will be used to create a subdirectory.
-        validate: bool, optional
-            Whether to validate simulation data. Defaults to True.
-        mdal_compliant: bool, optional
-            Convert data with
-            :func:`imod.prepare.spatial.mdal_compliant_ugrid2d` to MDAL
-            compliant unstructured grids. Defaults to False.
-        crs: Any, optional
-            Anything accepted by rasterio.crs.CRS.from_user_input
-            Requires ``rioxarray`` installed.
-        engine : str, optional
-            File engine used to write packages. Options are ``'netcdf4'``,
-            ``'zarr'``, and ``'zarr.zip'``. NetCDF4 is readable by many other
-            softwares, for example QGIS. Zarr is optimized for big data, cloud
-            storage and parallel access. The ``'zarr.zip'`` option is an
-            experimental option which creates a zipped zarr store in a single
-            file, which is easier to copy and automatically compresses data as
-            well. Default is ``'netcdf4'``.
+         Dump simulation to files. Writes a model definition as .TOML file, which
+         points to data for each package. Each package is stored as a separate
+         NetCDF. Structured grids are saved as regular NetCDFs, unstructured
+         grids are saved as UGRID NetCDF. Structured grids are always made GDAL
+         compliant, unstructured grids can be made MDAL compliant optionally.
+
+         Parameters
+         ----------
+         directory: str or Path
+             directory to dump simulation into.
+         modelname: str
+             modelname, will be used to create a subdirectory.
+         validate: bool, optional
+             Whether to validate simulation data. Defaults to True.
+         mdal_compliant: bool, optional
+             Convert data with
+             :func:`imod.prepare.spatial.mdal_compliant_ugrid2d` to MDAL
+             compliant unstructured grids. Defaults to False.
+         crs: Any, optional
+             Anything accepted by rasterio.crs.CRS.from_user_input
+             Requires ``rioxarray`` installed.
+         engine : str, optional
+             File engine used to write packages. Options are ``'netcdf4'``,
+             ``'zarr'``, and ``'zarr.zip'``. NetCDF4 is readable by many other
+             softwares, for example QGIS. Zarr is optimized for big data, cloud
+             storage and parallel access. The ``'zarr.zip'`` option is an
+             experimental option which creates a zipped zarr store in a single
+             file, which is easier to copy and automatically compresses data as
+             well. Default is ``'netcdf4'``.
 
+        Returns
+         -------
+         Path
+             Path to the created toml file which contains the paths to the dumped package files. The package files are dumped in the same directory as the toml file.
+
+         Example
+         -------
+         >>> tmp_path = tmpdir_factory.mktemp(name)
+         >>> toml_path = mf6_model.dump(tmp_path, name, engine=engine, validate=False)
+         >>> back = ModflowModel.from_file(tmp_path, name)
         """
-        modeldirectory = pathlib.Path(directory) / modelname
-        modeldirectory.mkdir(exist_ok=True, parents=True)
-        validation_context = ValidationSettings(validate=validate)
-        if validation_context.validate:
-            statusinfo = self.validate(modelname, validation_context)
-            if statusinfo.has_errors():
-                raise ValidationError(statusinfo.to_string())
 
-        toml_content: dict[str, Any] = collections.defaultdict(dict)
-
-        for pkgname, pkg in self.items():
-            pkg_path = pkg.to_file(
-                modeldirectory,
-                pkgname,
-                mdal_compliant=mdal_compliant,
-                crs=crs,
-                engine=engine,
-            )
-            toml_content[type(pkg).__name__][pkgname] = pkg_path.name
-
-        toml_path = modeldirectory / f"{modelname}.toml"
-        with open(toml_path, "wb") as f:
-            tomli_w.dump(toml_content, f)
+        toml_path = dump_model(
+            self,
+            directory,
+            modelname,
+            validate=validate,
+            mdal_compliant=mdal_compliant,
+            crs=crs,
+            engine=engine,
+        )
 
         return toml_path
 

imod/mf6/pkgbase.py

@@ -1,16 +1,14 @@
 import abc
-import numbers
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Mapping, Optional, Self, final
 
-import numpy as np
 import xarray as xr
 import xugrid as xu
-from xarray.core.utils import is_scalar
 
 import imod
 from imod.common.interfaces.ipackagebase import IPackageBase
 from imod.common.serializer import EngineType, create_package_serializer
+from imod.common.utilities.value_filters import is_scalar_nan
 from imod.typing.grid import (
     GridDataArray,
     GridDataset,
@@ -32,17 +30,6 @@
 UTIL_PACKAGES = ("ats", "hpc")
 
 
-def _is_scalar_nan(da: GridDataArray):
-    """
-    Test if is_scalar_nan, carefully avoid loading grids in memory
-    """
-    scalar_data: bool = is_scalar(da)
-    if scalar_data:
-        stripped_value = da.to_numpy()[()]
-        return isinstance(stripped_value, numbers.Real) and np.isnan(stripped_value)  # type: ignore[call-overload]
-    return False
-
-
 class PackageBase(IPackageBase, abc.ABC):
     """
     This class is used for storing a collection of Xarray DataArrays or UgridDataArrays
@@ -148,7 +135,7 @@ def from_file(cls, path: str | Path, **kwargs) -> Self:
 
         # Replace NaNs by None
         for key, value in dataset.items():
-            if _is_scalar_nan(value):
+            if is_scalar_nan(value):
                 dataset[key] = None
 
         # to_netcdf converts strings into NetCDF "variable‑length UTF‑8 strings"