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