RMAP#

class analysis.RMAP.ConnectivityChannelSelector(whole_brain_connectome: bool = True, func_connectivity: bool = True)[source]#
get_available_connectomes() → list[source]#

Return list of saved connectomes in the package folder/ConnectivityDecoding/connectome_folder/ folder.

Returns:

list_connectomes

Return type:

list

get_closest_node(coord: list | ndarray) → tuple[list, list][source]#

Given a list or np.array of coordinates, return the closest nodes in the grid and their indices.

Parameters:

coord (np.ndarray) – MNI coordinates with shape (num_channels, 3)

Returns:

Grid coordinates, grid indices

Return type:

Tuple[list, list]

get_rmap_correlations(fps: list | ndarray, RMAP_use: ndarray | None = None) → list[source]#

Calculate correlations of passed fingerprints with the RMAP

Parameters:

  • fps (Union[list, np.array]) – List of fingerprints

  • RMAP_use (np.ndarray, optional) – Passed RMAP, by default None

Returns:

correlation values

Return type:

List

load_connectome(whole_brain_connectome: bool | None = None, func_connectivity: bool | None = None) → None[source]#

Load connectome, if not available download connectome from Zenodo.

Parameters:

  • whole_brain_connectome (bool, optional) – if true whole brain connectome if false cortical hull grid connectome, by default None

  • func_connectivity (bool, optional) – if true fMRI if false dMRI, by default None

plot_grid() → None[source]#

Plot the loaded template grid that passed coordinates are matched to.

class analysis.RMAP.RMAPCross_Val_ChannelSelector[source]#
load_fingerprint(path_nii) → None[source]#

Return Nifti fingerprint