siibra.features.connectivity.regional_connectivity

Module Contents

Classes

RegionalConnectivity

Parcellation-averaged connectivity, providing one or more matrices of a
class siibra.features.connectivity.regional_connectivity.RegionalConnectivity(cohort: str, modality: str, regions: list, connector: siibra.retrieval.repositories.RepositoryConnector, decode_func: Callable, filename: str, anchor: siibra.features.anchor.AnatomicalAnchor, description: str = '', datasets: list = [], subject: str = 'average', feature: str = None, id: str = None)
Inheritance diagram of siibra.features.connectivity.regional_connectivity.RegionalConnectivity

Parcellation-averaged connectivity, providing one or more matrices of a given modality for a given parcellation.

property data: pandas.DataFrame

Returns a matrix as a pandas dataframe.

Returns:

A square matrix with region names as the column and row names.

Return type:

pd.DataFrame

property feature

If applicable, returns the type of feature for which the matrix represents.

property name

Returns a short human-readable name of this feature.

property subject

Returns the subject identifiers for which the matrix represents.

__len__()
__str__()

Return str(self).

compute_centroids(space)

Computes the list of centroid coordinates corresponding to matrix rows, in the given reference space.

Parameters:

space (Space, str) –

Return type:

list[tuple(float, float, float)]

get_profile(region: str | siibra.core.region.Region, min_connectivity: float = 0, max_rows: int = None, direction: Literal[column, row] = 'column')

Extract a regional profile from the matrix, to obtain a tabular data feature with the connectivity as the single column. Rows are be sorted by descending connection strength.

Parameters:

  • region (str, Region) –

  • min_connectivity (float, default: 0) – Regions with connectivity less than this value are discarded.

  • max_rows (int, default: None) – Max number of regions with highest connectivity.

  • direction (str, default: 'column') – Choose the direction of profile extraction particularly for non-symmetric matrices. (‘column’ or ‘row’)

get_profile_colorscale(region: str | siibra.core.region.Region, min_connectivity: float = 0, max_rows: int = None, direction: Literal[column, row] = 'column', colorgradient: str = 'jet') → Iterator[Tuple[siibra.core.region.Region, Tuple[int, int, int]]]

Extract the colorscale corresponding to the regional profile from the matrix sorted by the values. See get_profile for further details.

Note:

Requires plotly.

param region:

type region:

str, Region

param min_connectivity:

Regions with connectivity less than this value are discarded.

type min_connectivity:

float, default: 0

param max_rows:

Max number of regions with highest connectivity.

type max_rows:

int, default: None

param direction:

Choose the direction of profile extraction particularly for non-symmetric matrices. (‘column’ or ‘row’)

type direction:

str, default: ‘column’

param colorgradient:

The gradient used to extract colorscale.

type colorgradient:

str, default: ‘jet’

returns:

Color values are in RGB 255.

rtype:

Iterator[Tuple[_region.Region, Tuple[int, int, int]]]

plot(regions: str | siibra.core.region.Region | List[str | siibra.core.region.Region] = None, min_connectivity: float = 0, max_rows: int = None, direction: Literal[column, row] = 'column', logscale: bool = False, *args, backend='matplotlib', **kwargs)
Parameters:

  • regions (Union[str, _region.Region], None) – If None, returns the full connectivity matrix. If a region is provided, returns the profile for that region. If list of regions is provided, returns the matrix for the selected regions.

  • min_connectivity (float, default 0) – Only for region profile.

  • max_rows (int, default None) – Only for region profile.

  • direction ('column' or 'row', default: 'column') – Only for matrix.

  • logscale (bool, default: False) –

  • backend (str, default: "matplotlib" for profiles and "nilearn" for matrices) –