leicaexperiment

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/')

# 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 = Image.open(img_path)
    img = img.rotate(90)
    img.save(img_path)

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()
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 requirements.txt

run test

pip install tox
tox

extra output, jump into pdb upon error

DEBUG=leicaexperiment tox -- --pdb -s

build api reference

pip install -r docs/requirements.txt
make docs

Metadata

Release files for leicaexperiment 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for leicaexperiment 0.2.0
File	Size	Uploaded
leicaexperiment-0.2.0.tar.gz	1.3 MB	Apr 28, 2015	Details

Built distribution (wheel)

Table of built distributions (wheels) for leicaexperiment 0.2.0
File	Interpreter	ABI	Platform	Reset
leicaexperiment-0.2.0-py2.py3-none-any.whl 11.9 kB Apr 28, 2015	Python 3, Python 2	none	any	Details

Total release size: 1.3 MB

Release files / leicaexperiment-0.2.0.tar.gz

Download URL	leicaexperiment-0.2.0.tar.gz
Size	1.3 MB
Tags	Source
SHA-256 checksum How to use checksums	`78cda68457d79ce09d65159f97588b1920f2b8fd9528608c52847e0c80772632`
BLAKE2b-256 checksum How to use checksums	`5863d3abf11d82be400633385e18962c0dc48f33eafc83cc2b1d4e44d1e81b8a`
Upload date	Apr 28, 2015
Uploaded using Trusted Publishing? What is trusted publishing?	No

Release files / leicaexperiment-0.2.0-py2.py3-none-any.whl

Download URL	leicaexperiment-0.2.0-py2.py3-none-any.whl
Size	11.9 kB
Tags	Python 2 Python 3
SHA-256 checksum How to use checksums	`22824af7bf5a17323a28d7343f99acdfd01444c5215b0ea44b5c591fd9ca36cd`
BLAKE2b-256 checksum How to use checksums	`d58793d65217ef326ee95e42eb39a33c7803e1b45b83b4c53296303b7c6181d2`
Upload date	Apr 28, 2015
Uploaded using Trusted Publishing? What is trusted publishing?	No