neuralib.scanner.core.AbstractConfocalScanner

class neuralib.scanner.core.AbstractConfocalScanner[source]

Bases: object

ABC for the confocal image data

__init__()

Methods

`__init__`()
`get_dim_code`()	get the DimCode
`get_pixel2mm_factor`()
`load`(filepath)

Attributes

`height`	Y
`n_channels`	number of fluorescence channels.
`n_zstacks`	number of stacks in z axis.
`width`	X
`n_scenes`	positions scan
`meta`	metadata dict

n_scenes: int: positions scan

meta: dict[str, Any]: metadata dict

abstract classmethod load(filepath)[source]

Parameters:: filepath (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader)

abstract property width: dict[int, int]: X

abstract property height: dict[int, int]: Y

abstract property n_channels: dict[int, int]: number of fluorescence channels. C

abstract property n_zstacks: dict[int, int]: number of stacks in z axis. Z

abstract get_dim_code()[source]

get the DimCode

Dimension parameters (DimCode):

V - view

H - phase

I - illumination

S - scene

R - rotation

T - time

C - channel

Z - z plane (height)

M - mosaic tile, mosaic images only

Y - image height

X - image width

A - samples, BGR/RGB images only

Return type:: DIMCODE

get_pixel2mm_factor()[source]