Coverage for C:\src\imod-python\imod\mf6\rch.py: 100%
28 statements
« prev ^ index » next coverage.py v7.4.4, created at 2024-04-08 13:27 +0200
« prev ^ index » next coverage.py v7.4.4, created at 2024-04-08 13:27 +0200
1from typing import Optional, Tuple
3import numpy as np
5from imod.logging import init_log_decorator
6from imod.mf6.boundary_condition import BoundaryCondition
7from imod.mf6.interfaces.iregridpackage import IRegridPackage
8from imod.mf6.utilities.regrid import RegridderType
9from imod.mf6.validation import BOUNDARY_DIMS_SCHEMA, CONC_DIMS_SCHEMA
10from imod.schemata import (
11 AllInsideNoDataSchema,
12 AllNoDataSchema,
13 AllValueSchema,
14 CoordsSchema,
15 DimsSchema,
16 DTypeSchema,
17 IdentityNoDataSchema,
18 IndexesSchema,
19 OtherCoordsSchema,
20)
23class Recharge(BoundaryCondition, IRegridPackage):
24 """
25 Recharge Package.
26 Any number of RCH Packages can be specified for a single groundwater flow
27 model.
28 https://water.usgs.gov/water-resources/software/MODFLOW-6/mf6io_6.0.4.pdf#page=79
30 Parameters
31 ----------
32 rate: array of floats (xr.DataArray)
33 is the recharge flux rate (LT −1). This rate is multiplied inside the
34 program by the surface area of the cell to calculate the volumetric
35 recharge rate. A time-series name may be specified.
36 concentration: array of floats (xr.DataArray, optional)
37 if this flow package is used in simulations also involving transport, then this array is used
38 as the concentration for inflow over this boundary.
39 concentration_boundary_type: ({"AUX", "AUXMIXED"}, optional)
40 if this flow package is used in simulations also involving transport, then this keyword specifies
41 how outflow over this boundary is computed.
42 print_input: ({True, False}, optional)
43 keyword to indicate that the list of recharge information will be
44 written to the listing file immediately after it is read.
45 Default is False.
46 print_flows: ({True, False}, optional)
47 Indicates that the list of recharge flow rates will be printed to the
48 listing file for every stress period time step in which "BUDGET PRINT"is
49 specified in Output Control. If there is no Output Control option and
50 PRINT FLOWS is specified, then flow rates are printed for the last time
51 step of each stress period.
52 Default is False.
53 save_flows: ({True, False}, optional)
54 Indicates that recharge flow terms will be written to the file specified
55 with "BUDGET FILEOUT" in Output Control.
56 Default is False.
57 observations: [Not yet supported.]
58 Default is None.
59 validate: {True, False}
60 Flag to indicate whether the package should be validated upon
61 initialization. This raises a ValidationError if package input is
62 provided in the wrong manner. Defaults to True.
63 repeat_stress: Optional[xr.DataArray] of datetimes
64 Used to repeat data for e.g. repeating stress periods such as
65 seasonality without duplicating the values. The DataArray should have
66 dimensions ``("repeat", "repeat_items")``. The ``repeat_items``
67 dimension should have size 2: the first value is the "key", the second
68 value is the "value". For the "key" datetime, the data of the "value"
69 datetime will be used. Can also be set with a dictionary using the
70 ``set_repeat_stress`` method.
71 """
73 _pkg_id = "rch"
74 _period_data = ("rate",)
75 _keyword_map = {}
77 _init_schemata = {
78 "rate": [
79 DTypeSchema(np.floating),
80 IndexesSchema(),
81 CoordsSchema(("layer",)),
82 BOUNDARY_DIMS_SCHEMA,
83 ],
84 "concentration": [
85 DTypeSchema(np.floating),
86 IndexesSchema(),
87 CoordsSchema(
88 (
89 "species",
90 "layer",
91 )
92 ),
93 CONC_DIMS_SCHEMA,
94 ],
95 "print_flows": [DTypeSchema(np.bool_), DimsSchema()],
96 "save_flows": [DTypeSchema(np.bool_), DimsSchema()],
97 }
98 _write_schemata = {
99 "rate": [
100 OtherCoordsSchema("idomain"),
101 AllNoDataSchema(), # Check for all nan, can occur while clipping
102 AllInsideNoDataSchema(other="idomain", is_other_notnull=(">", 0)),
103 ],
104 "concentration": [IdentityNoDataSchema("rate"), AllValueSchema(">=", 0.0)],
105 }
107 _template = BoundaryCondition._initialize_template(_pkg_id)
108 _auxiliary_data = {"concentration": "species"}
110 _regrid_method = {
111 "rate": (RegridderType.OVERLAP, "mean"),
112 "concentration": (RegridderType.OVERLAP, "mean"),
113 }
115 @init_log_decorator()
116 def __init__(
117 self,
118 rate,
119 concentration=None,
120 concentration_boundary_type="auxmixed",
121 print_input=False,
122 print_flows=False,
123 save_flows=False,
124 observations=None,
125 validate: bool = True,
126 repeat_stress=None,
127 ):
128 dict_dataset = {
129 "rate": rate,
130 "concentration": concentration,
131 "concentration_boundary_type": concentration_boundary_type,
132 "print_input": print_input,
133 "print_flows": print_flows,
134 "save_flows": save_flows,
135 "observations": observations,
136 "repeat_stress": repeat_stress,
137 }
138 super().__init__(dict_dataset)
139 self._validate_init_schemata(validate)
141 def _validate(self, schemata, **kwargs):
142 # Insert additional kwargs
143 kwargs["rate"] = self["rate"]
144 errors = super()._validate(schemata, **kwargs)
146 return errors
148 def get_regrid_methods(self) -> Optional[dict[str, Tuple[RegridderType, str]]]:
149 return self._regrid_method