joseki

Joseki.

Submodules

• joseki.accessor
• joseki.constants
• joseki.core
• joseki.data
• joseki.profiles
• joseki.units

Attributes

unit_registry

Functions

identifiers()	List all registered profile identifiers.
interp(ds, z_new[, method, conserve_column])	Interpolate atmospheric profile on new altitudes.
load_dataset(path, *args, **kwargs)	Thin wrapper around xarray.load_dataset.
make(identifier[, z, interp_method, conserve_column, ...])	Create a profile with the specified identifier.
merge(datasets[, new_title])	Merge multiple profiles into a single profile.
open_dataset(path, *args, **kwargs)	Thin wrapper around xarray.open_dataset.

Package Contents

joseki.identifiers()

List all registered profile identifiers.

Returns:

List of all registered profile identifiers.

Return type:

List[str]

joseki.interp(ds, z_new, method=DEFAULT_METHOD, conserve_column=False, **kwargs)

Interpolate atmospheric profile on new altitudes.

Parameters:

• ds (xarray.Dataset) – Atmospheric profile to interpolate.

• z_new (pint.Quantity) – Altitudes values at which to interpolate the atmospheric profile.

• method (Dict[str, str]) – Mapping of variable and interpolation method. If a variable is not in the mapping, the linear interpolation is used. By default, linear interpolation is used for all variables.

• conserve_column (bool) – If True, ensure that column densities are conserved.

• kwargs (Any) – Parameters passed to scipy.interpolate.interp1d() (except ‘kind’ and ‘bounds_error’).

Returns:

Interpolated atmospheric profile.

Return type:

xarray.Dataset

joseki.load_dataset(path, *args, **kwargs)

Thin wrapper around xarray.load_dataset.

Parameters:

path (os.PathLike) – Path to the dataset.

Returns:

Profile.

Return type:

xarray.Dataset

joseki.make(identifier, z=None, interp_method=DEFAULT_METHOD, conserve_column=False, molecules=None, regularize=None, rescale_to=None, check_x_sum=False, **kwargs)

Create a profile with the specified identifier.

Parameters:

• identifier (str) – Profile identifier.

• z (pint.Quantity | dict | xarray.DataArray | None) – Altitude values.

• interp_method (Mapping[str, str] | None) – Mapping of variable and interpolation method.

• conserve_column (bool) – If True, ensure that column densities are conserved during interpolation.

• molecules (List[str] | None) – List of molecules to include in the profile.

• regularize (bool | dict | None) – Regularize the altitude grid with specified options which are passed to [regularize](reference.md#src.joseki.profiles.core.regularize).

• rescale_to (dict | None) – Rescale molecular concentrations to the specified target values which are passed to [rescale_to](reference.md#src.joseki.accessor.JosekiAccessor.rescale_to).

• check_x_sum (bool) – If True, check that the mole fraction sums are less or equal to 1.

• kwargs (Any) – Additional keyword arguments passed to the profile constructor.

Returns:

Profile as xarray.Dataset.

Return type:

xarray.Dataset

See also

• joseki.profiles.core.regularize()

• joseki.accessor.JosekiAccessor.rescale_to()

joseki.merge(datasets, new_title=None)

Merge multiple profiles into a single profile.

Parameters:

• datasets (Iterable[xarray.Dataset]) – Iterable of profiles.

• new_title (str | None) – New title for the merged profile. If None, the title of the first profile is used.

Returns:

Merged profile.

Return type:

xarray.Dataset

Notes

The first profile in the iterable is used as the base profile; when variables with the same name are encountered in subsequent profiles, the variable from the first profile is used.

joseki.open_dataset(path, *args, **kwargs)

Thin wrapper around xarray.open_dataset.

Parameters:

path (os.PathLike) – Path to the dataset.

Returns:

Profile.

Return type:

xarray.Dataset

joseki.unit_registry