import cftime
import numpy as np
from imod.mf6.pkgbase import Package
def iso8601(datetime):
datetype = type(datetime)
if issubclass(datetype, np.datetime64):
return np.datetime_as_string(datetime)
elif issubclass(datetype, cftime.datetime):
return datetime.isoformat()
else:
raise TypeError(f"Expected np.datetime64 or cftime.datetime, got {datetype}")
[docs]class TimeDiscretization(Package):
"""
Timing for all models of the simulation is controlled by the Temporal
Discretization (TDIS) Package.
https://water.usgs.gov/water-resources/software/MODFLOW-6/mf6io_6.0.4.pdf#page=17
Paremeters
----------
timestep_duration: float
is the length of a stress period. (PERLEN)
n_timesteps: int, optional
is the number of time steps in a stress period (nstp).
Default value: 1
timestep_multiplier: float, optional
is the multiplier for the length of successive time steps. The length of
a time step is calculated by multiplying the length of the previous time
step by timestep_multiplier (TSMULT).
Default value: 1.0
"""
__slots__ = ("timestep_duration", "n_timesteps", "timestep_multiplier")
_pkg_id = "tdis"
_keyword_map = {}
_template = Package._initialize_template(_pkg_id)
def __init__(self, timestep_duration, n_timesteps=1, timestep_multiplier=1.0):
super().__init__()
self["timestep_duration"] = timestep_duration
self["n_timesteps"] = n_timesteps
self["timestep_multiplier"] = timestep_multiplier
[docs] def render(self):
start_date_time = iso8601(self["time"].values[0])
d = {
"time_units": "days",
"start_date_time": start_date_time,
}
timestep_duration = self["timestep_duration"]
n_timesteps = self["n_timesteps"]
timestep_multiplier = self["timestep_multiplier"]
nper = timestep_duration.size # scalar will also have size 1
d["nper"] = nper
# Broadcast everything to a 1D array so it's iterable
# also fills in a scalar value everywhere
broadcast_array = np.ones(nper, dtype=np.int32)
timestep_duration = np.atleast_1d(timestep_duration) * broadcast_array
n_timesteps = np.atleast_1d(n_timesteps) * broadcast_array
timestep_multiplier = np.atleast_1d(timestep_multiplier) * broadcast_array
# Zip through the arrays
perioddata = []
for (perlen, nstp, tsmult) in zip(
timestep_duration, n_timesteps, timestep_multiplier
):
perioddata.append((perlen, nstp, tsmult))
d["perioddata"] = perioddata
return self._template.render(d)
[docs] def write(self, directory, name):
timedis_content = self.render()
timedis_path = directory / f"{name}.tdis"
with open(timedis_path, "w") as f:
f.write(timedis_content)