DatasetModel

class glotaran.model.dataset_model.DatasetModel

Bases: object

A DatasetModel describes a dataset in terms of a glotaran model. It contains references to model items which describe the physical model for a given dataset.

A general dataset descriptor assigns one or more megacomplexes and a scale parameter.

Methods Summary

ensure_unique_megacomplexes	Ensure that unique megacomplexes Are only used once per dataset.
finalize_data
get_coordinates	Gets the dataset model's coordinates.
get_data	Gets the dataset model's data.
get_global_axis	Gets the dataset model's global axis.
get_global_dimension	Returns the dataset model's global dimension.
get_model_axis	Gets the dataset model's model axis.
get_model_dimension	Returns the dataset model's model dimension.
get_weight	Gets the dataset model's weight.
has_global_model	Indicates if the dataset model can model the global dimension.
is_index_dependent	Indicates if the dataset model is index dependent.
iterate_global_megacomplexes	Iterates of der dataset model's global megacomplexes.
iterate_megacomplexes	Iterates of der dataset model's megacomplexes.
overwrite_global_dimension	Overwrites the dataset model's global dimension.
overwrite_index_dependent	Overrides the index dependency of the dataset
overwrite_model_dimension	Overwrites the dataset model's model dimension.
set_coordinates	Sets the dataset model's coordinates.
set_data	Sets the dataset model's data.
swap_dimensions	Swaps the dataset model's global and model dimension.

Methods Documentation

ensure_unique_megacomplexes(model: Model) → list[str]

Ensure that unique megacomplexes Are only used once per dataset.

Parameters

model (Model) – Model object using this dataset model.

Returns

Error messages to be shown when the model gets validated.

Return type

list[str]

finalize_data(dataset: xarray.core.dataset.Dataset) → None

get_coordinates() → dict[Hashable, np.ndarray]

Gets the dataset model’s coordinates.

get_data() → numpy.ndarray

Gets the dataset model’s data.

get_global_axis() → numpy.ndarray

Gets the dataset model’s global axis.

get_global_dimension() → str

Returns the dataset model’s global dimension.

get_model_axis() → numpy.ndarray

Gets the dataset model’s model axis.

get_model_dimension() → str

Returns the dataset model’s model dimension.

get_weight() → np.ndarray | None

Gets the dataset model’s weight.

has_global_model() → bool

Indicates if the dataset model can model the global dimension.

is_index_dependent() → bool

Indicates if the dataset model is index dependent.

iterate_global_megacomplexes() → Generator[tuple[Parameter | int | None, Megacomplex | str], None, None]

Iterates of der dataset model’s global megacomplexes.

iterate_megacomplexes() → Generator[tuple[Parameter | int | None, Megacomplex | str], None, None]

Iterates of der dataset model’s megacomplexes.

overwrite_global_dimension(global_dimension: str) → None

Overwrites the dataset model’s global dimension.

overwrite_index_dependent(index_dependent: bool)

Overrides the index dependency of the dataset

overwrite_model_dimension(model_dimension: str) → None

Overwrites the dataset model’s model dimension.

set_coordinates(coords: dict[str, np.ndarray])

Sets the dataset model’s coordinates.

set_data(dataset: xarray.core.dataset.Dataset) → glotaran.model.dataset_model.DatasetModel

Sets the dataset model’s data.

swap_dimensions() → None

Swaps the dataset model’s global and model dimension.