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Read, stitch and compress Leica LAS MatrixS Screener experiments

Project description

build-status-image pypi-version wheel

Overview

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)

Features

  • Access experiment as a python object
  • Compress to PNGs without loosing precision, metadata or colormap
  • ImageJ stitching (Fiji is installed via fijibin)

Installation

Install using pip

pip install leicaexperiment

Examples

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/')

stitch specific well

from leicaexperiment import Experiment

# path should contain AditionalData and slide--S*
stitched_images = experiment.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 attribute

# select specific parts
selected_wells = [well for well in experiment.wells if 'U00' in well]
for well in selected_wells:
    do stuff...

def condition(path):
    x_above = attribute(path, 'X') > 1
    x_below = attribute(path, 'X') < 5
    return x_above and x_below

selected_fields = [field for field in experiment.fields if condition(field)]
for field in selected_fields:
    do stuff..

subtract data

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, compress

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

API reference

API reference is at http://leicaexperiment.rtfd.org.

Development

Install dependencies and link development version of leicaexperiment to pip:

git clone https://github.com/arve0/leicaexperiment
cd leicaexperiment
pip install -r dev-requirements.txt

run test

tox

extra output, jump into pdb upon error

DEBUG=leicaexperiment tox -- --pdb -s

build api reference

make docs

Project details


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