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Read, stitch and compress Leica LAS Matrix Screener experiments

Project description

build-status-image pypi-version wheel


This is a python module for interfacing with Leica LAS AF/X Matrix Screener experiments.

The module can be used to:

  • stitch wells from an experiment exported with the LAS AF Data Exporter

  • batch compress images lossless

  • programmatically select slides/wells/fields/images given by attributes like

    • slide (S)

    • well position (U, V)

    • field position (X, Y)

    • z-stack position (Z)

    • channel (C)


  • Access experiment as a python object

  • Compress to PNGs without loosing precision, metadata or colormap

  • ImageJ stitching (Fiji is installed via fijibin)


Install using pip

pip install leicaexperiment


stitch experiment

from leicaexperiment import Experiment

# path should contain AditionalData and slide--S*
experiment = Experiment('path/to/experiment')

# if path is omitted, experiment path is used for output files
stitched_images = experiment.stitch('/path/to/output/files/')

# get information about placement of images in the stitch
xs, ys, attrs = experiment.stitch_coordinates(well_x=0, well_y=0)

stitch specific well

from leicaexperiment import stitch

stitched_images = stitch('/path/to/well')

do stuff on all images

from leicaexperiment import Experiment

experiment = Experiment('path/to/experiment--')

for image in experiment.images:
    do stuff...

do stuff on specific wells/fields

from leicaexperiment import Experiment
from PIL import Image

experiment = Experiment('path/to/experiment--')

# on images in well --U00--V00
for well in experiment.well_images(0, 0):
    do stuff...

# rotate top left image in first row
rows = experiment.well_rows
for r in rows:
    img_path = experiment.image(r, 0, 0, 0)
    img =
    img = img.rotate(90)

subtract attributes from file names

from leicaexperiment import attribute

# get all channels
channels = [attribute(image, 'C') for image in experiment.images]
min_ch, max_ch = min(channels), max(channels)

batch lossless compress of experiment

from leicaexperiment import Experiment

e = Experiment('/path/to/experiment')
pngs = e.compress()

API reference

API reference is at


Install dependencies and link development version of leicaexperiment to pip:

git clone
cd leicaexperiment
pip install -r requirements.txt

run test

pip install tox

extra output, jump into pdb upon error

DEBUG=leicaexperiment tox -- --pdb -s

build api reference

pip install -r docs/requirements.txt
make docs

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