Python package for stochastic simulations
Project description
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
Project details
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