cedalion.io.forward_model

Module for saving and loading forward model computation results.

Functions

load_Adot(fn)	Load Adot from a netCDF file.
load_fluence(fn)	Load forward model computation results.
save_Adot(fn, Adot)	Save Adot to a netCDF file.
save_fluence(fn, fluence_all, fluence_at_optodes)	Save forward model computation results.

Classes

FluenceFile(fname[, mode])

cedalion.io.forward_model.save_Adot(fn: str, Adot: DataArray)

Save Adot to a netCDF file.

Parameters:

• fn (str) – File name to save the data to.

• Adot (xr.DataArray) – Data to save.

Returns:

None

cedalion.io.forward_model.load_Adot(fn: str)

Load Adot from a netCDF file.

Parameters:

fn (str) – File name to load the data from.

Returns:

Data loaded from the file.

Return type:

xr.DataArray

cedalion.io.forward_model.save_fluence(fn: str, fluence_all, fluence_at_optodes)

Save forward model computation results.

This method uses a lossy compression algorithm to reduce file size.

cedalion.io.forward_model.load_fluence(fn: str)

Load forward model computation results.

Parameters:

fn (str) – File name to load the data from.

Returns:

Fluence data loaded from the file.

Return type:

Tuple[xr.DataArray, xr.DataArray]

class cedalion.io.forward_model.FluenceFile(fname: str | Path, mode='r')

Bases: object

create_fluence_dataset(

optode_pos: Annotated[DataArray, DataArraySchema(dims='label', coords='label', 'label', 'type')],

wavelengths: ndarray,

fluence_shape: tuple[int, int, int],

units: str,

)

get_fluence(label: str, wavelength: float) → ndarray

set_fluence_by_label(label: str, wavelength: float, fluence: ndarray)

set_fluence_by_index(i_label: int, i_wl: int, fluence: ndarray)

get_fluence_at_optodes()

set_fluence_at_optodes(fluence_at_optodes: DataArray)

get_fluence_all()