modelmimic.mimic.MimicModelRun

class documentation

class MimicModelRun: (source)

Constructor: MimicModelRun(name, variables, ntimes, size, ...)

Undocumented

Method	`__init__`	Initalize a pseudo model run to mimic an EAM (or other) model run.
Method	`get_file_times`	Get the time strings for output files
Method	`make_ensemble`	Turn base data into ensemble of data.
Method	`write_to_nc`	Write generated data to a netCDF file.
Instance Variable	`axes`	Undocumented
Instance Variable	`base_data`	Undocumented
Instance Variable	`dims`	Undocumented
Instance Variable	`ens_data`	Undocumented
Instance Variable	`name`	Undocumented
Instance Variable	`ninst`	Undocumented
Instance Variable	`ntimes`	Undocumented
Instance Variable	`size`	Undocumented
Instance Variable	`vars`	Undocumented
Method	`__repr__`	Undocumented

def __init__(self, name: str, variables: list, ntimes: int = 12, size: tuple = (5, 10), ninst: int = 1, dims: tuple = ('nlev', 'ncol')): (source) ¶

Initalize a pseudo model run to mimic an EAM (or other) model run.

Parameters
name:`str`	Name of model run, probably BASE or TEST
variables:`list[str]`	List of variable names to generate mimic data for
ntimes:`int`	Undocumented
size:`tuple`	Shape for the data
ninst:`int`, optional	Number of instances, by default 1
dims:`tuple`	Undocumented

def get_file_times(self, sim_start: str = '0001-01-01', timestep: str = 'month', step_mult: int = 1): (source) ¶

Get the time strings for output files

Parameters
sim_start:`str`, optional	Start of the simulated simulation, by default "0001-01-01"
timestep:`str`, optional	Increment of time used, either "month" or "sec". By default "month".
step_mult:`int`, optional	Multiple of increment. By default 1.

def make_ensemble(self, popmean: float = 0.0, popvar: float = 1e-05, seed: bool = False): (source) ¶

Turn base data into ensemble of data.

Parameters
popmean:`float`	Undocumented
popvar:`float`	Undocumented
seed:`bool`, optional	Seed to pass to numpy.random, will use each instance number so results will be bit-for-bit, by default False

def write_to_nc(self, out_path: Path = None, sim_start: str = '0001-01-01', timestep: str = 'month', step_mult: int = 1, hist_file_pattern: str = 'eam_{inst:04d}.h0.{time}', casename: bool = True, file_suffix: str = None, **kwargs): (source) ¶

Write generated data to a netCDF file.

axes = (source) ¶

Undocumented

base_data: dict = (source) ¶

Undocumented

dims = (source) ¶

Undocumented

ens_data = (source) ¶

Undocumented

name = (source) ¶

Undocumented

ninst = (source) ¶