Tumor
A spatial Markov model of agents making decisions based upon their surroundings. Stochastic optimization via Markov Chain Monte Carlo (Metropolis-Hastings algorithm). Interactive visualization of data using the JavaScript library D3.
Install / Use
/learn @petermchale/TumorREADME
tumor
A Python package for agent-based Monte Carlo simulations of tumor growth. Rendered version of notebook includes inline animations and interactive plots, and illustrates how to
- simulate the model in Python 3.x
- statistically analyze data generated by the model
- visualize the results of the analysis to maximize insight <img src="data/tumor.gif">
In the movie above, there are two types of cells - green cells that replicate ('cycle' in biological terms) and red cells that do not (called 'quiescent' by biologists). To run a similar movie on your own computer, download this repository, open Terminal (on a Mac), and execute the following commands at the command line:
cd <path to repository>/data/animation/
python ../../tumor_package/animate.py
