For The Gillespie Simulation. Seperate in classes so parts can be changed independantly, DO NOT CHANGE THE DATA-STRUCTURE ONCE DECIDED UPON. It should be expandable without restructuring.
- Put the data in a
pandas.DdtaFrame
(the Rows can be named and it is not static compared to the numpy array (my argument)) - Implement the Matrix Multiplication to calculate the partition function (R) -> Nora
- Implement the random select function from a module
- Think about ways to test and Implement tests
- Implement the second plot shown in the script
- Think about how to input the parameters ()
- Write save/ read functions for config files (yaml, json whatever)
- Reduce repetition in how the concentrations are updated
- Think about the interface - tkinter works but is tedious
- Write Reusable elements for the interface
- Think of a way to properly connect the elements that allows signals to be propelled throughout the "tree"
- Work out the threading
- Limit the Input Values to be sensible
- Determine what sensible parameters are
- Save data as .csv,.h5 or smth
- allow the simmulation to run cuntinously until User-Input interrupt and
continuusly plot.
- Allow to modify Parameters while Running
- Write the command line stuff