MatrixProviderUnlinked

class glotaran.optimization.matrix_provider.MatrixProviderUnlinked(group: DatasetGroup, data_provider: DataProvider)[source]

Bases: MatrixProvider

A class to provide matrix calculations for optimization of unlinked dataset groups.

Initialize a matrix provider for an unlinked dataset group.

Parameters:

dataset_group (DatasetGroup) – The dataset group.
data_provider (DataProvider) – The data provider.

Attributes Summary

`group`	Get the dataset group.
`number_of_clps`	Return number of conditionally linear parameters.

Methods Summary

`apply_constraints`	Apply constraints on a matrix.
`apply_relations`	Apply relations on a matrix.
`calculate`	Calculate the matrices for optimization.
`calculate_dataset_matrices`	Calculate the matrices of the datasets in the dataset group.
`calculate_dataset_matrix`	Calculate the matrix for a dataset on an index on the global axis.
`calculate_full_matrices`	Calculate the full matrices of the datasets in the dataset group.
`calculate_global_matrices`	Calculate the global matrices of the datasets in the dataset group.
`calculate_prepared_matrices`	Calculate the prepared matrices of the datasets in the dataset group.
`combine_megacomplex_matrices`	Calculate the matrix for a dataset on an index on the global axis.
`does_interval_item_apply`	Check if an interval item applies on an index.
`get_full_matrix`	Get the full matrix of a dataset.
`get_global_matrix_container`	Get the global matrix container for a dataset.
`get_matrix_container`	Get the matrix container for a dataset on an index on the global axis.
`get_prepared_matrix_container`	Get the prepared matrix container for a dataset on an index on the global axis.
`get_result`	Get the results of the matrix calculations.
`reduce_matrix`	Reduce a matrix.

Methods Documentation

apply_constraints(matrices: list[MatrixContainer], global_axis: ArrayLike) → list[MatrixContainer]

Apply constraints on a matrix.

Parameters:

matrices (list[MatrixContainer],) – The matrices.
global_axis (ArrayLike) – The global axis.

Returns:

The resulting matrix container.

Return type:

MatrixContainer

apply_relations(matrices: list[MatrixContainer], global_axis: ArrayLike) → list[MatrixContainer]

Apply relations on a matrix.

Parameters:

matrices (list[MatrixContainer],) – The matrices.
global_axis (ArrayLike) – The global axis.

Returns:

The resulting matrix container.

Return type:

MatrixContainer

calculate()[source]: Calculate the matrices for optimization.

calculate_dataset_matrices(): Calculate the matrices of the datasets in the dataset group.

static calculate_dataset_matrix(dataset_model: DatasetModel, global_axis: ArrayLike, model_axis: ArrayLike, global_matrix: bool = False) → MatrixContainer

Calculate the matrix for a dataset on an index on the global axis.

Parameters:

dataset_model (DatasetModel) – The dataset model.
global_axis (ArrayLike) – The global axis.
model_axis (ArrayLike) – The model axis.
global_matrix (bool) – Calculate the global megacomplexes if True.

Returns:

The resulting matrix container.

Return type:

MatrixContainer

calculate_full_matrices()[source]: Calculate the full matrices of the datasets in the dataset group.

calculate_global_matrices()[source]: Calculate the global matrices of the datasets in the dataset group.

calculate_prepared_matrices()[source]: Calculate the prepared matrices of the datasets in the dataset group.

static combine_megacomplex_matrices(matrix_left: ArrayLike, matrix_right: ArrayLike, clp_labels_left: list[str], clp_labels_right: list[str]) → tuple[list[str], ArrayLike]

Calculate the matrix for a dataset on an index on the global axis.

Parameters:

matrix_left (ArrayLike) – The left matrix.
matrix_right (ArrayLike) – The right matrix.
clp_labels_left (list[str]) – The left clp labels.
clp_labels_right (list[str]) – The right clp labels.

Returns:

The combined clp labels and matrix.

Return type:

tuple[list[str], ArrayLike]

static does_interval_item_apply(prop: IntervalItem, index: int | None) → bool

Check if an interval item applies on an index.

Parameters:

prop (IntervalItem) – The interval property.
index (int | None) – The index to check.

Returns:

Whether the property applies.

Return type:

bool

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

Get the full matrix of a dataset.

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

get_global_matrix_container(dataset_label: str) → MatrixContainer[source]

Get the global matrix container for a dataset.

Parameters:: dataset_label (str) – The label of the dataset.
Returns:: The matrix container.
Return type:: MatrixContainer

get_matrix_container(dataset_label: str) → MatrixContainer

Get the matrix container for a dataset on an index on the global axis.

Parameters:: dataset_label (str) – The label of the dataset.
Returns:: The matrix container.
Return type:: MatrixContainer

get_prepared_matrix_container(dataset_label: str, global_index: int) → MatrixContainer[source]

Get the prepared matrix container for a dataset on an index on the global axis.

Parameters:

dataset_label (str) – The label of the dataset.
global_index (int) – The index on the global axis.

Returns:

The matrix container.

Return type:

MatrixContainer

get_result() → tuple[dict[str, DataArray], dict[str, DataArray]]

Get the results of the matrix calculations.

Returns:

tuple[dict[str, xr.DataArray], dict[str, xr.DataArray]] – A tuple of the matrices and global matrices.
.. # noqa (DAR202)
.. # noqa (DAR401)

property group: DatasetGroup

Get the dataset group.

Returns:: The dataset group.
Return type:: DatasetGroup

property number_of_clps: int

Return number of conditionally linear parameters.

Return type:: int

reduce_matrix(matrix: MatrixContainer, global_axis: ArrayLike) → list[MatrixContainer]

Reduce a matrix.

Applies constraints and relations.

Parameters:

matrix (MatrixContainer) – The matrix.
global_axis (ArrayLike) – The global axis.

Returns:

The resulting matrix container.

Return type:

MatrixContainer