Source code for imod.msw.output_control

import pandas as pd

from imod.msw.fixed_format import VariableMetaData
from imod.msw.pkgbase import MetaSwapPackage
from imod.msw.timeutil import to_metaswap_timeformat

# I did not use long variable names here (e.g. "precipitation"), as MetaSWAP
# uses these 2 to 4 character names to print its output to. This also has the
# benefit that the user is able to set additional variable names via kwargs
# (there are more than 130 possible variable names to choose from in MetaSWAP)
[docs]class VariableOutputControl(MetaSwapPackage): """ Control which variables will be created as output. The variable names used in this class provide a condensed water balance. You can use additional keyword arguments to set more variables by using their specific name, e.g. `vcr = True` for the water balance error. For all possibilities see the SIMGRO Input and Output description. All budgets will be written in m unit to in `.idf` files and to mm unit in `.csv` files. Parameters ---------- Pm: bool Write measured precipitation Psgw: bool Write sprinkling precipitation, from groundwater Pssw: bool Write sprinkling precipitation, from surface water qrun: bool Write runon qdr: bool Write net infiltration of surface water qspgw: bool Groundwater extraction for sprinkling from layer qmodf: bool Sum of all MODFLOW stresses on groundwater ETact: bool Write total actual evapotranspiration, which is the sum of the sprinkling evaporation (Esp), interception evaporation (Eic), ponding evaporation (Epd) bare soil evaporation (Ebs), and actual transpiration (Tact). **kwargs: bool Additional variables to let MetaSWAP write """ _file_name = "sel_key_svat_per.inp" _settings = {} _metadata_dict = { "variable": VariableMetaData(10, None, None, str), "option": VariableMetaData(10, 0, 3, int), }
[docs] def __init__( self, Pm=True, Psgw=True, Pssw=True, qrun=True, qdr=True, qspgw=True, qmodf=True, ETact=True, **kwargs, ): super().__init__() # Convert to integer, as MetaSWAP expects its values as integers. self.dataset["Pm"] = int(Pm) self.dataset["Psgw"] = int(Psgw) self.dataset["Pssw"] = int(Pssw) self.dataset["qrun"] = int(qrun) self.dataset["qdr"] = int(qdr) self.dataset["qspgw"] = int(qspgw) self.dataset["qmodf"] = int(qmodf) self.dataset["ETact"] = int(ETact) # Set additional settings for key, value in kwargs.items(): self.dataset[key] = int(value)
def _render(self, file, *args): variable, option = zip( *[(var, self.dataset[var].values) for var in self.dataset.data_vars] ) dataframe = pd.DataFrame(data=dict(variable=variable, option=option)) self._check_range(dataframe) return self.write_dataframe_fixed_width(file, dataframe)
[docs]class TimeOutputControl(MetaSwapPackage): """ Specify the accumulation periods which will be used to write output. For example, say the model computes on a daily timestep, but timesteps two days apart are specified, the summed fluxes of each two days are written by MetaSWAP. Parameters ---------- time: xr.DataArray Timesteps at which to write output. """ _file_name = "tiop_sim.inp" _settings = {} _metadata_dict = { "time_since_start_year": VariableMetaData(15, 0.0, 366.0, float), "year": VariableMetaData(6, 1, 9999, int), "option": VariableMetaData(6, 1, 7, int), }
[docs] def __init__(self, time): super().__init__() self.dataset["times"] = time
def _render(self, file, *args): year, time_since_start_year = to_metaswap_timeformat(self.dataset["times"]) dataframe = pd.DataFrame( data=dict(time_since_start_year=time_since_start_year, year=year) ) dataframe["time_since_start_year"] += 1 dataframe["option"] = 7 self._check_range(dataframe) return self.write_dataframe_fixed_width(file, dataframe)