StochPy is a versatile stochastic modeling package which is designed for stochastic simulation of molecular control networks
- File releases 2.3 and earlier: http://sourceforge.net/projects/stochpy
- File releases 2.4+: PyPI and Github.
- Source code: https://github.com/SystemsBioinformatics/stochpy
StochPy is open source software distributed under the BSD 3-Clause License, see LICENSE file for more details.
Documentation can be found in the user guide (see Documentation directory or in sourceforge)
The following software is required before installing StochPy (see user guide for more details):
- Python 2.6+ or Python 3.4+
- NumPy 1.x+
- SciPy
- Matplotlib (optional)
- libsbml (optional)
- libxml2 (optional)
- mpmath (optional)
Install StochPy and dependencies with PIP using the following command (in your StochPy Python virtual environment):
pip install scipy matplotlib python-libsbml jedi==0.17.2 ipython stochpyIf you are using Anaconda, create a custom conda environment for StochPy, for example:
conda create -n "stochpy39" -c sbmlteam python=3.9 pip scipy matplotlib sympy ipythonactivate your new environment, install StochPy (only required once per environment) and start ipython.
conda activate stochpy39
pip install stochpy
ipython
In the directory where you downloaded/cloned the StochPy source, for example, the git main branch:
sudo python setup.py installUse the available windows installer or use PyPI (described above).
You can run ipython and import stochpy:
import stochpy
smod = stochpy.SSA()smod.DoStochSim(IsTrackPropensities=True)
smod.data_stochsim.simulation_endtime
smod.data_stochsim.simulation_timesteps
smod.GetWaitingtimes()
smod.PrintWaitingtimesMeans()smod.PlotSpeciesTimeSeries()
smod.PlotWaitingtimesDistributions()
smod.PlotPropensitiesTimeSeries()smod.Export2File()
smod.Export2File(analysis='distribution')
smod.Export2File(analysis='distribution',datatype='species')
smod.Export2File(analysis='mean',datatype='species')
smod.Export2File(analysis='std',datatype='species')
smod.Export2File(analysis='autocorrelation',datatype='species')smod.DoStochSim(trajectories=3) # multiple trajectories
smod.data_stochsim.simulation_trajectory
smod.PrintSpeciesMeans()
smod.PrintSpeciesStandardDeviations()smod.GetTrajectoryData(1)
smod.PrintSpeciesMeans()
smod.PrintSpeciesStandardDeviations()smod.DoStochSim(trajectories=1,end=1000000,mode='steps')
smod.PrintSpeciesMeans()
smod.PrintSpeciesStandardDeviations()smod.PlotSpeciesDistributions()
smod.PlotSpeciesDistributions(bin_size=5) # larger bin size
smod.PlotSpeciesDistributions(bin_size=10) # again a larger bin size
smod.Export2File(analysis='distribution',datatype='species')smod.ChangeParameter('Ksyn',20.0)
smod.ChangeParameter('Kdeg',0.2)
smod.DoStochSim()
smod.PrintSpeciesMeans() # should be ~Ksyn/Kdegsmod.Model('dsmts-001-01.xml.psc')
smod.DoStochSim(trajectories=1000,end=50,mode='time')
smod.GetRegularGrid(npoints=51)
smod.PlotAverageSpeciesTimeSeries()
smod.PrintAverageSpeciesTimeSeries()
smod.Export2File(datatype='species',analysis='timeseries',IsAverage=True)smod.Model('Autoreg.psc')
smod.DoStochSim(trajectories=1,end=1000,mode='steps')
smod.Method('NextReactionMethod')
smod.DoStochSim(trajectories=1,end=1000,mode='steps')
smod.data_stochsim.species
smod.PlotWaitingtimesDistributions()
smod.Method('FirstReactionMethod')
smod.DoStochSim(trajectories=1,end=1000,mode='steps')
smod.Method('TauLeaping')
smod.DoStochSim(trajectories=1,end=1000,mode='steps')smod.Model('DecayingDimerizing.psc')
smod.DoStochSim(method = 'Direct',trajectories=1,end=50,mode='time')
smod.DoStochSim(method = 'NextReactionMethod',trajectories=1,end=50,mode='time')
smod.DoStochSim(method = 'FirstReactionMethod',trajectories=1,end=50,mode='time')
smod.PlotWaitingtimesDistributions()
smod.DoStochSim(method = 'TauLeaping',trajectories=1,end=50,mode='time',epsilon=0.03) # Should outperform all other implementations
smod.PlotSpeciesTimeSeries()
#smod.PlotWaitingtimesDistributions() # Should give an errorsmod.Model('chain500.psc')
smod.DoStochSim(method = 'Direct',trajectories=1,end=10000,mode='steps')
smod.DoStochSim(method = 'NextReactionMethod',trajectories=1,end=10000,mode='steps') # should outperform the direct method and all other implementationssmod.Model('dsmts-003-03.xml.psc')
smod.DoStochSim(method = 'NextReactionMethod')
smod.DoTestsuite()smod.Model('dsmts-003-04.xml.psc')
smod.DoStochSim(method = 'FirstReactionMethod')
smod.DoTestsuite()smod.Model('dsmts-001-11.xml.psc')
smod.DoStochSim(method = 'Direct',trajectories=1000,end=50,mode ='time')
smod.PrintAverageSpeciesTimeSeries()Timo R. Maarleveld, Brett G. Olivier, and Frank J. Bruggeman Centrum Wiskunde en Informatica, Amsterdam, Netherlands VU University, Amsterdam, Netherlands
e-mail: tmd200@users.sourceforge.net
StochPy: A Comprehensive, User-Friendly Tool for Simulating Stochastic Biological Processes http://dx.doi.org/10.1371/journal.pone.0079345
Copyright (c) 2011-2021, Timo R. Maarleveld, Brett G. Olivier, and Frank J. Bruggeman Vrije Universiteit Amsterdam. All rights reserved.
StochPy is open source software distributed under the BSD 3-Clause License see LICENSE file for more details.