Python script to generate test data for CellProfiler-Analyst.
Generates 3 channel monochrome cell images with nuclei and centromeres. Each image varies the amount of overlap between the centromeres.
The Python script depends on scipy and Python Imaging Library (PIL).
It also calls a command-line program, fast_delaunay
,
to generate uniform spatial distributions.
To compile fast_delaunay
one needs the GNU Triangulated Surface Library (libgts).
With libgts installed, one can build fast_delaunay
using:
make -f fast-poisson-disk.makefile
Then run the Python script with to generate the *.tif
images with:
python cellgen.py path/to/output/directory
Or leave off the path to output the images in the current directory:
python cellgen.py
If you prefer to use docker to install the dependencies and run the program, create the docker image with:
docker build -t cellgen .
Then run the program with:
docker run -v /path/to/output/directory:/data -it cellgen
To create the *.tif
images in the current directory:
docker run -v $PWD:/data -it cellgen