pycif.plugins.models.lmdz_ico — API reference

pycif.plugins.models.lmdz_ico — API reference#

Configuration reference: lmdz_ico plugin

pycif.plugins.models.lmdz_ico.compile.run_command(*args: str | PathLike, cwd: str | PathLike | None = None, logfile: TextIO | None = None) → None[source]#
pycif.plugins.models.lmdz_ico.compile.get_make_command(self) → list[str][source]#
pycif.plugins.models.lmdz_ico.compile.compile(self) → None[source]#
pycif.plugins.models.lmdz_ico.flushrun.to_output(path: Path) → Path[source]#
pycif.plugins.models.lmdz_ico.flushrun.remove_file(runsubdir: Path, filename: str, input_only: bool = True) → None[source]#
pycif.plugins.models.lmdz_ico.flushrun.remove_spec_files(runsubdir: Path, filename: str, species: list[str], input_only: bool = True) → None[source]#
pycif.plugins.models.lmdz_ico.flushrun.flush(self, runsubdir: Path, input_only: bool = True) → None[source]#

Clean a simulation sub directory

Parameters#

runsubdirPath

Path to the simulation sub directory

input_onlybool, optional

Only remove input files and not output files, by default True

pycif.plugins.models.lmdz_ico.flushrun.flushrun(self, rundir, mode, transform_id, full_flush=True)[source]#

Cleaning the simulation directories to limit space usage

pycif.plugins.models.lmdz_ico.ini_mapper.get_input_intervals(self, input_dates: dict[datetime, ndarray]) → dict[datetime, ndarray][source]#
pycif.plugins.models.lmdz_ico.ini_mapper.ini_mapper(self, transform_type, general_mapper={}, backup_comps={}, transforms_order=[], ref_transform='', transform_name='', **kwargs) → dict[str, dict[tuple[str, str], dict[str, Any] | list[str] | list[tuple[str, str]]]][source]#
pycif.plugins.models.lmdz_ico.ini_periods.is_month_start(datetime: Timestamp) → bool[source]#
pycif.plugins.models.lmdz_ico.ini_periods.ini_periods(self, **kwargs) → None[source]#
pycif.plugins.models.lmdz_ico.perturb_model.append_attribute(plugin: Any, key: str, attr: Any) → None[source]#
pycif.plugins.models.lmdz_ico.perturb_model.remove_attribute(plugin: Any, key: str) → None[source]#
pycif.plugins.models.lmdz_ico.perturb_model.perturb_model(self, nsamples: int, transf_mapper)[source]#
pycif.plugins.models.lmdz_ico.run.run_dispersion(self, runsubdir: Path) → None[source]#
pycif.plugins.models.lmdz_ico.run.run(self, runsubdir: str | PathLike, mode: Literal['fwd', 'tl', 'adj'], workdir: str | PathLike, ddi: datetime, do_simu: bool = True, approx_transf: bool = False, ref_fwd_dir: str | PathLike | None = None, overlap: bool = False, **kwargs)[source]#

Run LMDZ model in forward or adjoint mode

Parameters:

  • runsubdir (str) – working directory for the current run

  • mode (str) – forward or backward

  • workdir (str) – pycif working directory

  • do_simu (bool) – if False, considers that the simulation was already run

pycif.plugins.models.lmdz_ico.run.dump_trajq(self, runsubdir: str | PathLike, ddi: datetime) → None[source]#
pycif.plugins.models.lmdz_ico.run.check_approx_threshold(self, ddi, mode, runsubdir)[source]#