Example code for "Engineering and quantifying spatiotemporal mosaic self-patterning"

This script requires Python 3.6 or greater and several additional python packages. It is recommended to install and test the code in a virtual environment for maximum reproducibility:

# Create the virtual environment
python3 -m venv ~/morpho_env
source ~/morpho_env/bin/activate

# Install the required packages
pip3 install -r requirements.txt

The code below assumes that python3 refers to the python binary installed in the virtual environment.

To run the tracking algorithm on a single folder, do:

python3 track_by_overlap.py [/path/to/folder]

To supply a user determined threshold to segment the images, do:

python3 track_by_overlap.py -t [threshold] [/path/to/folder]

Other options are available through the command line help:

python3 track_by_overlap.py -h

This repository contains the images to reproduce the panels in Figure 2. To segment the 5 examples frames of the 25% labeled colony:

python3 track_by_overlap.py example_25pct

Which should produce the following plot while segmenting frame 1:

The segmented frames 1, 3, and 5 correspond to the panels in Figure 2A.

To segment the example frames of the 1%, 5%, and 10% labeled colonies:

python3 track_by_overlap.py -t 0.05 example_1pct
python3 track_by_overlap.py -t 0.05 example_5pct
python3 track_by_overlap.py -t 0.05 example_10pct

The first segmented frame of each folder corresponds to the panels in Figure 2B.