A Python implementation of OPIPP, a method for precisely generating artificial retinal mosaics, the spatial organization of retinal neurons. Here is a short introduction to the background.

We recommend the "import-analysis-simulation" pipeline for generating artificial mosaics and purpose a tutorial for each step, as

1. Importing retinal spatial pattern datasets from local files
2. Analyzing and visualizing spatial patterns of mosaics
3. Simulating artifical retinal mosaics

Users are welcome to extend and customize methods for feature calculation and mosaic simulation.

Here are useful tools that are not implemented in the current version. We plan to apply these methods in future development.

• Estimate parameters of mosaic simulation by R
• Parallel process for mosaic generation by MPI

pip install git+https://github.com/heliy/OPIPP

• python >=3.8
• numpy >= 1.20.0
• scipy >= 1.9.0
• matplotlib >= 3.2.0
• networkx >= 2.0.0

• TODO

• The example mosaic for retinal horizontal cells and related spatial features are from (Keeley et al., 2020).

• In the optimization, we use the adaptive simulated annealing algorithm from (Ingber, 1993).