Source code for rameau.core.groundwater.groundwater
# Copyright 2025, BRGM
#
# This file is part of Rameau.
#
# Rameau is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# Rameau is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE. See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with
# Rameau. If not, see <https://www.gnu.org/licenses/>.
#
"""
Groundwater parameters.
"""
from __future__ import annotations
import numpy as np
from typing import Union, Optional
from rameau.wrapper import CGroundwater
from rameau.core.parameter import Parameter
from rameau.core.groundwater import StorageParameters, GroundwaterReservoir
from rameau.core._abstract_wrapper import AbstractWrapper
from rameau._typing import ParameterType
from rameau.core._utils import _build_type, _build_parameter
from rameau.core._descriptor import (
_DerivedTypeDecriptor,
_FloatDescriptor,
_IntDescriptor,
_VectorDescriptor,
_VectorDerivedTypeDescriptor
)
[docs]
class GroundwaterParameters(AbstractWrapper):
"""Groundwater parameters.
Parameters
----------
reservoirs: `list`, optional
List of `GroundwaterReservoir`.
storage: `dict` or `StorageParameters`, optional
Parameters linked to the storage coefficient calculation.
base_level: `dict` or `Parameter`, optional
Groundwater base level (m NGF).
weight: `float`, optional
Weight given to groundwater level during the model optimisation.
A value of zero means no groundwater level optimisation.
obslim: `[float, float]`, optional
Bounds applied to the observed groundwater level during the
model optimisation.
observed_reservoir: `int`, optional
Reservoir index for which reservoir level in mm will be converted
to piezometer head in m NGF. Index starts from 1 from the upper
to the deeper groundwater reservoir.
Returns
-------
`GroundwaterParameters`
"""
_computed_attributes = (
"storage", "base_level", "weight", "obslim",
"observed_reservoir", "reservoirs"
)
_c_class = CGroundwater
reservoirs: list[GroundwaterReservoir] = _VectorDerivedTypeDescriptor(
0, GroundwaterReservoir
) #type: ignore
storage: StorageParameters = _DerivedTypeDecriptor(0, StorageParameters) #type: ignore
base_level: Parameter = _DerivedTypeDecriptor(0, Parameter) #type: ignore
weight: float = _FloatDescriptor(0) #type: ignore
obslim: list[float] = _VectorDescriptor(0, float) #type: ignore
observed_reservoir: int = _IntDescriptor(0) #type: ignore
def __init__(
self,
reservoirs: Optional[list[GroundwaterReservoir]] = None,
storage: Optional[Union[dict, StorageParameters]]= None,
base_level: ParameterType = None,
weight: float = 0.0,
obslim: list = [0.0, 0.0],
observed_reservoir: int = 1,
) -> None:
self._init_c()
if storage is not None:
self.storage = _build_type(storage, StorageParameters)
if base_level is not None:
self.base_level = _build_parameter(base_level)
self.weight = weight
self.obslim = obslim
self.observed_reservoir = observed_reservoir
if reservoirs is None:
reservoirs = [GroundwaterReservoir()]
tmp = []
if isinstance(reservoirs, list):
if not bool(reservoirs):
raise ValueError("Empty list not allowed.")
elif isinstance(reservoirs, np.ndarray):
if reservoirs.size == 0:
raise ValueError("Empty numpy.ndarray not allowed.")
else:
raise TypeError(f"Type {type(reservoirs)} not allowed.")
for res in reservoirs:
if isinstance(res, dict):
tmp.append(GroundwaterReservoir(**res))
else:
tmp.append(res)
self.reservoirs = tmp
