neuralib.imaging.cellular
- final class neuralib.imaging.cellular.CellularCoordinates[source]
Container with coordinates information (in mm) for each ROIs
Dimension parameters:
N: number of neurons
P: number of plane types
- neuron_idx: ndarray
neuron index. Array[float, N]
- ap: ndarray
anterior posterior coordinates (default in mm). Array[float, N]
- ml: ndarray
medial lateral coordinates (default in mm). Array[float, N]
- plane_index: int | ndarray | None
optic plane index. i.e., used for depth analysis. If array type, Array[int, P]
- source_plane_index: ndarray | None
neuron’s corresponding image plane. Array[float, N]
- value: ndarray | None
metric (i.e., used in topographical analysis). Array[float, N]
- unit: Literal['mm', 'um']
unit of the coordinates. {‘mm’, ‘um’}
- __init__(neuron_idx, ap, ml, *, plane_index=None, source_plane_index=None, value=None, unit='mm')
Method generated by attrs for class CellularCoordinates.
- Parameters:
neuron_idx (ndarray)
ap (ndarray)
ml (ndarray)
plane_index (int | ndarray | None)
source_plane_index (ndarray | None)
value (ndarray | None)
unit (Literal['mm', 'um'])
- Return type:
None
- with_value(value)[source]
assign
valueforCellularCoordinates- Parameters:
value (ndarray) – value array for the corresponding coordinates. Array[float, N]
- Returns:
- Return type:
Self
- with_selection(mask)[source]
masking for cell selection
- Parameters:
mask (ndarray) – numpy bool array. Array[bool, N]
- Return type:
Self
- in_relative_bregma(fov)[source]
TODO check register cellular coordinates to IBL coordinates space
- Parameters:
fov (ObjectiveFov) –
ObjectiveFov- Return type:
Self