pyssa 0.9.1

Python package for stochastic simulations

pyssa : Python package for stochastic simulations

Introduction

pyssa is a Python package for stochastic simulations. It offers a simple API to define models, perform stochastic simulations with them and visualize the results in a convenient manner.

Currently under active development in the develop branch.

Install

Install with pip:

$ pip install pyssa

Documentation

• General: https://pyssa.readthedocs.io.

Usage

A short summary follows, but a more detailed tutorial can be found at https://pyssa.readthedocs.io/en/latest/tutorial.html

from pyssa.simulation import Simulation
V_r = np.array([[1, 0], [0, 1], [0, 0]])  # Reactant matrix
V_p = np.array([[0, 0], [1, 0], [0, 1]])  # Product matrix
X0 = np.array([100, 0, 0])  # Initial state
k = np.array([1.0, 1.0])  # Rate constants
sim = Simulation(V_r, V_p, X0, k)  # Declare the simulation object
# Run the simulation
sim.simulate(max_t=150, max_iter=1000, chem_flag=True, n_rep=10)

Change simulation algorithm

You can change the algorithm used to perform the simulation by changing the algorithm parameter

sim.simulate(max_t=150, max_iter=1000, chem_flag=True, n_rep=10, algorithm="tau_adaptive")

Run simulations in parallel

You can run the simulations on multiple cores by specifying the n_procs parameter

sim.simulate(max_t=150, max_iter=1000, chem_flag=True, n_rep=10, n_procs=4)

Plot simulation results

sim.plot()

Accessing simulation results

results = sim.results

You can also access the final states of all the simulation runs by

final_times, final_states = results.final

License

Copyright (c) 2018-2020, Dileep Kishore, Srikiran Chandrasekaran. Released under: Apache Software License 2.0

Credits

• Cython
• pytest
• Cookiecutter
• audreyr/cookiecutter-pypackage
• black