neuralib.registration.coordinates.CellularCoordinates

class neuralib.registration.coordinates.CellularCoordinates[source]

Bases: object

Cellular Coordinates container

__init__(neuron_idx, ap, ml, unit='mm', plane_index=None, value=None)

Method generated by attrs for class CellularCoordinates.

Parameters:

  • neuron_idx (ndarray)

  • ap (ndarray)

  • ml (ndarray)

  • unit (Literal['mm', 'um'])

  • plane_index (ndarray | None)

  • value (ndarray | None)

Return type:

None

Methods

__init__(neuron_idx, ap, ml[, unit, ...])

Method generated by attrs for class CellularCoordinates.

relative_origin(fov[, origin])

coordinates relative to FieldOfView origin point

with_masking(mask)

do neuronal selection by bool masking :param mask: Array[bool, N]

with_value(value)

assign value foreach neuron

Attributes

neuron_idx

neuron index.

ap

anterior posterior coordinates (default in mm).

ml

medial lateral coordinates (default in mm).

unit

unit of the ap/ml value

plane_index

neuron's corresponding image plane.

value

metric (i.e., used in topographical analysis).
neuron_idx: ndarray

neuron index. Array[float, N]

ap: ndarray

anterior posterior coordinates (default in mm). Array[float, N]

__init__(neuron_idx, ap, ml, unit='mm', plane_index=None, value=None)

Method generated by attrs for class CellularCoordinates.

Parameters:

  • neuron_idx (ndarray)

  • ap (ndarray)

  • ml (ndarray)

  • unit (Literal['mm', 'um'])

  • plane_index (ndarray | None)

  • value (ndarray | None)

Return type:

None

ml: ndarray

medial lateral coordinates (default in mm). Array[float, N]

unit: Literal['mm', 'um']

unit of the ap/ml value

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]

relative_origin(fov, origin='am')[source]

coordinates relative to FieldOfView origin point

Parameters:
Returns:

Return type:

Self

with_value(value)[source]

assign value foreach neuron

Parameters:

value (ndarray)

Return type:

Self

with_masking(mask)[source]

do neuronal selection by bool masking :param mask: Array[bool, N]

Parameters:

mask (ndarray)

Return type:

Self