ScanBox

This module simply provides

result parser for scanbox acquisition system
view the sequence / save as tiff file

Refer to API: neuralib.scanbox

Metadata information

from neuralib.scanbox import read_scanbox

file = ...  # scanbox .mat output file
sbx = read_scanbox(file)
print(sbx.asdict())  # print the information as dictionary

Metadata to Json

from neuralib.scanbox import sbx_to_json

file = ...  # scanbox .mat output file
output_file = ...  # *.json
sbx_to_json(file, outputfile)

Screen Shot file to tiff

from neuralib.scanbox import screenshot_to_tiff

file = ...  # scanbox .mat screenshot output file
output = ... # *.tiff
screenshot_to_tiff(file, output)

ScanBox Imaging View

Directly view the image sequence as mmap

Use CLI

$ python -m neuralib.scanbox.view -h

usage: view.py [-h] [--frames FRAMES] [--plane PLANE] [--channel CHANNEL] [--verbose] [--show] [--tiff TO_TIFF] PATH

positional arguments:
  PATH               directory containing .sbx/.mat scanbox output

options:
  -h, --help         show this help message and exit
  --frames FRAMES    indices of image sequences, if None, then all frames
  --plane PLANE      which optic plane
  --channel CHANNEL  which pmt channel
  --verbose          show meta verbose
  --show             play the selected imaging sequences
  --tiff TO_TIFF     save sequence as tiff output

Example playing the 100-200 frames

$ python -m neuralib.scanbox.view PATH -P <OPTIC_PLANE> -C <PMT_CHANNEL> -F 100,200

Example save 100-200 Frames as tiff

$ python -m neuralib.scanbox.view PATH -P <OPTIC_PLANE> -C <PMT_CHANNEL> -F 100,200 -O test.tiff

Use API call

from neuralib.scanbox.view import ScanBoxView

directory  = ...  # directory contain the .sbx and .mat output from scanbox
view = ScanBoxView(directory)

# play
view.show(slice(100,200), plane=0, channel=0)

# save as tiff
view.to_tiff(slice(100,200), plane=0, channel=0, output='test.tiff')