Source code for imod.mf6.dis

import pathlib
from copy import deepcopy
from typing import Any, List, Optional

import numpy as np

import imod
from imod.logging import init_log_decorator, standard_log_decorator
from imod.mf6.interfaces.imaskingsettings import IMaskingSettings
from imod.mf6.interfaces.iregridpackage import IRegridPackage
from imod.mf6.package import Package
from imod.mf6.regrid.regrid_schemes import DiscretizationRegridMethod, RegridMethodType
from imod.mf6.utilities.grid import create_smallest_target_grid
from imod.mf6.utilities.imod5_converter import convert_ibound_to_idomain
from imod.mf6.utilities.regrid import (
    RegridderWeightsCache,
    _regrid_package_data,
)
from imod.mf6.validation import DisBottomSchema
from imod.schemata import (
    ActiveCellsConnectedSchema,
    AllValueSchema,
    AnyValueSchema,
    DimsSchema,
    DTypeSchema,
    IdentityNoDataSchema,
    IndexesSchema,
    UniqueValuesSchema,
    ValidationError,
)
from imod.typing.grid import GridDataArray


[docs] class StructuredDiscretization(Package, IRegridPackage, IMaskingSettings): """ Discretization information for structered grids is specified using the file. (DIS6) Only one discretization input file (DISU6, DISV6 or DIS6) can be specified for a model. https://water.usgs.gov/water-resources/software/MODFLOW-6/mf6io_6.0.4.pdf#page=35 Parameters ---------- top: array of floats (xr.DataArray) is the top elevation for each cell in the top model layer. bottom: array of floats (xr.DataArray) is the bottom elevation for each cell. idomain: array of integers (xr.DataArray) Indicates the existence status of a cell. Horizontal discretization information will be derived from the x and y coordinates of the DataArray. If the idomain value for a cell is 0, the cell does not exist in the simulation. Input and output values will be read and written for the cell, but internal to the program, the cell is excluded from the solution. If the idomain value for a cell is 1, the cell exists in the simulation. if the idomain value for a cell is -1, the cell does not exist in the simulation. Furthermore, the first existing cell above will be connected to the first existing cell below. This type of cell is referred to as a "vertical pass through" cell. validate: {True, False} Flag to indicate whether the package should be validated upon initialization. This raises a ValidationError if package input is provided in the wrong manner. Defaults to True. """ _pkg_id = "dis" _init_schemata = { "top": [ DTypeSchema(np.floating), DimsSchema("y", "x") | DimsSchema(), IndexesSchema(), ], "bottom": [ DTypeSchema(np.floating), DimsSchema("layer", "y", "x") | DimsSchema("layer"), IndexesSchema(), ], "idomain": [ DTypeSchema(np.integer), DimsSchema("layer", "y", "x"), IndexesSchema(), ], } _write_schemata = { "idomain": ( ActiveCellsConnectedSchema(is_notnull=("!=", 0)), AnyValueSchema(">", 0), ), "top": ( AllValueSchema(">", "bottom", ignore=("idomain", "<=", 0)), IdentityNoDataSchema(other="idomain", is_other_notnull=(">", 0)), # No need to check coords: dataset ensures they align with idomain. ), "bottom": (DisBottomSchema(other="idomain", is_other_notnull=(">", 0)),), } _grid_data = {"top": np.float64, "bottom": np.float64, "idomain": np.int32} _keyword_map = {"bottom": "botm"} _template = Package._initialize_template(_pkg_id) _regrid_method = DiscretizationRegridMethod() @property def skip_variables(self) -> List[str]: return ["bottom"]
[docs] @init_log_decorator() def __init__(self, top, bottom, idomain, validate: bool = True): dict_dataset = { "idomain": idomain, "top": top, "bottom": bottom, } super().__init__(dict_dataset) self._validate_init_schemata(validate)
def _delrc(self, dx): """ dx means dx or dy """ if isinstance(dx, (int, float)): return f"constant {dx}" elif isinstance(dx, np.ndarray): arrstr = str(dx)[1:-1] return f"internal\n {arrstr}" else: raise ValueError(f"Unhandled type of {dx}") def render(self, directory, pkgname, globaltimes, binary): disdirectory = pathlib.Path(directory) / pkgname d: dict[str, Any] = {} x = self.dataset["idomain"].coords["x"] y = self.dataset["idomain"].coords["y"] dx, xmin, _ = imod.util.spatial.coord_reference(x) dy, ymin, _ = imod.util.spatial.coord_reference(y) d["xorigin"] = xmin d["yorigin"] = ymin d["nlay"] = self.dataset["idomain"].coords["layer"].size d["nrow"] = y.size d["ncol"] = x.size d["delr"] = self._delrc(np.abs(dx)) d["delc"] = self._delrc(np.abs(dy)) _, d["top"] = self._compose_values( self["top"], disdirectory, "top", binary=binary ) d["botm_layered"], d["botm"] = self._compose_values( self["bottom"], disdirectory, "botm", binary=binary ) d["idomain_layered"], d["idomain"] = self._compose_values( self["idomain"], disdirectory, "idomain", binary=binary ) return self._template.render(d) def _validate(self, schemata, **kwargs): # Insert additional kwargs kwargs["bottom"] = self["bottom"] errors = super()._validate(schemata, **kwargs) return errors @classmethod @standard_log_decorator() def from_imod5_data( cls, imod5_data: dict[str, dict[str, GridDataArray]], regridder_types: Optional[RegridMethodType] = None, regrid_cache: RegridderWeightsCache = RegridderWeightsCache(), validate: bool = True, ) -> "StructuredDiscretization": """ Construct package from iMOD5 data, loaded with the :func:`imod.formats.prj.open_projectfile_data` function. Method regrids all variables to a target grid with the smallest extent and smallest cellsize available in all the grids. Consequently it converts iMODFLOW data to MODFLOW 6 data. .. note:: The method expects the iMOD5 model to be fully 3D, not quasi-3D. Parameters ---------- imod5_data: dict Dictionary with iMOD5 data. This can be constructed from the :func:`imod.formats.prj.open_projectfile_data` method. regridder_types: DiscretizationRegridMethod, optional Optional dataclass with regridder types for a specific variable. Use this to override default regridding methods. regrid_cache: RegridderWeightsCache, optional stores regridder weights for different regridders. Can be used to speed up regridding, if the same regridders are used several times for regridding different arrays. Returns ------- Modflow 6 StructuredDiscretization package. """ data = { "idomain": imod5_data["bnd"]["ibound"].astype(np.int32), "top": imod5_data["top"]["top"], "bottom": imod5_data["bot"]["bottom"], } target_grid = create_smallest_target_grid(*data.values()) if regridder_types is None: regridder_types = StructuredDiscretization.get_regrid_methods() new_package_data = _regrid_package_data( data, target_grid, regridder_types, regrid_cache ) # Validate iMOD5 data if validate: UniqueValuesSchema([-1, 0, 1]).validate(imod5_data["bnd"]["ibound"]) if not np.all( new_package_data["top"][1:].data == new_package_data["bottom"][:-1].data ): raise ValidationError( "Model discretization not fully 3D. Make sure TOP[n+1] matches BOT[n]" ) thickness = new_package_data["top"] - new_package_data["bottom"] new_package_data["idomain"] = convert_ibound_to_idomain( new_package_data["idomain"], thickness ) # TOP 3D -> TOP 2D # Assume iMOD5 data provided as fully 3D and not Quasi-3D new_package_data["top"] = new_package_data["top"].sel(layer=1, drop=True) return cls(**new_package_data, validate=True) @classmethod def get_regrid_methods(cls) -> DiscretizationRegridMethod: return deepcopy(cls._regrid_method)