DataProvider

class glotaran.optimization.data_provider.DataProvider(scheme: Scheme, dataset_group: DatasetGroup)[source]

Bases: object

A class to provide prepared data for optimization.

Initialize a data provider for a scheme and a dataset_group.

Parameters:

scheme (Scheme) – The optimization scheme.
dataset_group (DatasetGroup) – The dataset group.

Methods Summary

`add_model_weight`	Add model weight to data.
`get_axis_slice_from_interval`	Get a slice of indices from a min max tuple and for an axis.
`get_data`	Get data for a dataset.
`get_flattened_data`	Get flattened data for a dataset.
`get_flattened_weight`	Get flattened weight for a dataset.
`get_from_dataset`	Get a copy of data from a dataset with dimensions (model, global).
`get_global_axis`	Get the global axis for a dataset.
`get_global_dimension`	Get the global dimension for a dataset.
`get_model_axis`	Get the model axis for a dataset.
`get_model_dimension`	Get the model dimension for a dataset.
`get_weight`	Get weight for a dataset.
`infer_global_dimension`	Infer the name of the global dimension from tuple of dimensions.

Methods Documentation

add_model_weight(model: Model, dataset_label: str, model_dimension: str, global_dimension: str)[source]

Add model weight to data.

Parameters:

model (Model) – The model.
dataset_label (str) – The label of the data.
model_dimension (str) – The model dimension.
global_dimension (str) – The global dimension.

static get_axis_slice_from_interval(interval: tuple[float, float], axis: ArrayLike) → slice[source]

Get a slice of indices from a min max tuple and for an axis.

Parameters:

interval (tuple[float, float]) – The min max tuple.
axis (ArrayLike) – The axis to slice.

Returns:

The slice of indices.

Return type:

slice

get_data(dataset_label: str) → ArrayLike[source]

Get data for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The data.
Return type:: ArrayLike

get_flattened_data(dataset_label: str) → ArrayLike[source]

Get flattened data for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The flattened data.
Return type:: ArrayLike

get_flattened_weight(dataset_label: str) → ArrayLike | None[source]

Get flattened weight for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The flattened weight.
Return type:: ArrayLike | None

static get_from_dataset(dataset: xr.Dataset, name: str, model_dimension: str, global_dimension: str) → ArrayLike | None[source]

Get a copy of data from a dataset with dimensions (model, global).

Parameters:

dataset (xr.Dataset) – The dataset to retrieve from.
name (str) – The name of the data to retrieve.
model_dimension (str) – The model dimension.
global_dimension (str) – The global dimension.

Returns:

The copy of the data. None if name is not present in dataset.

Return type:

ArrayLike | None

get_global_axis(dataset_label: str) → ArrayLike[source]

Get the global axis for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The global axis.
Return type:: ArrayLike

get_global_dimension(dataset_label: str) → str[source]

Get the global dimension for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The global dimension.
Return type:: str

get_model_axis(dataset_label: str) → ArrayLike[source]

Get the model axis for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The model axis.
Return type:: ArrayLike

get_model_dimension(dataset_label: str) → str[source]

Get the model dimension for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The model dimension.
Return type:: str

get_weight(dataset_label: str) → ArrayLike | None[source]

Get weight for a dataset.

Parameters:: dataset_label (str) – The label of the data.
Returns:: The weight.
Return type:: ArrayLike | None

static infer_global_dimension(model_dimension: str, dimensions: tuple[str]) → str[source]

Infer the name of the global dimension from tuple of dimensions.

Parameters:

model_dimension (str) – The model dimension.
dimensions (tuple[str]) – The dimensions tuple to infer from.

Returns:

The inferred name of the global dimension.

Return type:

str