An image analysis tool for measuring microorganism colony growth.
ColonyScanalyser will analyse and collate statistical data from agar plate images. It provides fast, high-throughput image processing.
ColonyScanalyser can provide information on:
- Colony appearance time
- Growth parameters (lag time, rate, carrying capacity)
- Growth and appearance time distribution
- Colony colour (e.g. staining or other visual indicators)
ColonyScanalyser is suitable for analysing series of images from a fixed point that show the development of microorganism colonies over time.
Several image plots will be output after analysis is complete to enable quick verification of the data. A complete set of data is provided in CSV format for further study.
- Install the prerequisites and package
- Locate your image series in a folder e.g.
/user/images/series1 - Run the analysis using ColonyScanalyser
scanalyser /user/images/series1
There are various command line arguments that can alter the way the package is run. To see a list of arguments and information on each, run the command
scanalyser --help
A full set of documentation is available at https://erik-white.github.io/ColonyScanalyser/
ColonyScanalyser requires Python version 3.7 or greater, and the Pip package manager. Pip is included with Python version 3.4 and up.
The remaining Python package dependencies are automatically handled by Pip when installing the Colonyscanalyser package.
Optionally use a virtual environment, such as Pipenv, or a containerised instance of the package.
For testing:
pip install colonyscanalyser
From github (requires git install)
git clone https://github.com/erik-white/colonyscanalyser.git
cd colonyscanalyser
pip install -e .
Install the package with the extra test packages:
pip install colonyscanalyser[test]
Run the tests:
pytest --cov colonyscanalyser
Please read the contribution guidelines for details on our code of conduct, and the process for submitting pull requests to us.
We use SemVer for versioning. For the versions available, see the releases.
This project is licensed under the GPLv3 - see the licence file for details
- Levin-Reisman et al. for their work developing the ScanLag technique
- Fabio Zanini for his original attempts at a Python implementation