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README.md

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+StochPy Stochastic modeling in Python
+=====================================
+
+Copyright (c) 2011-2016, Timo R. Maarleveld, Brett G. Olivier, and Frank J. Bruggeman
+All rights reserved.
+
+StochPy is distributed under a BSD style licence.
+
+File releases: http://sourceforge.net/projects/stochpy
+Source code: https://github.com/SystemsBioinformatics/stochpy
+
+Author information
+------------------
+
+Timo R. Maarleveld, Brett G. Olivier, and Frank J. Bruggeman
+Centrum Wiskunde en Informatica, Amsterdam, Netherlands
+VU University, Amsterdam, Netherlands
+
+e-mail: [email protected]
+
+Documentation can be found in the user guide (see Documentation directory or http://stochpy.sourceforge.net/html/userguide.html) 
+
+Publication
+~~~~~~~~~~~
+
+StochPy: A Comprehensive, User-Friendly Tool for Simulating Stochastic Biological Processes
+http://dx.doi.org/10.1371/journal.pone.0079345
+
+Installation
+------------
+The following software is required before installling StochPy (see user guide for more details):
+
+- Python 2.6+ or Python 3.4+
+- NumPy 1.x+
+- Matplotlib (optional)
+- libsbml (optional)
+- libxml2 (optional)
+- mpmath (optional)
+
+Linux/MAC OS/Cygwin
+~~~~~~~~~~~~~~~~~~~
+
+1) cd to directory StochPy-2.1.0
+2) sudo python setup.py install
+
+Windows
+~~~~~~~
+Use the available windows installer or the setup file
+
+Usage
+-----
+
+import stochpy
+smod = stochpy.SSA()
+
+# 1: Basic Simulation with the Direct method
+smod.DoStochSim(IsTrackPropensities=True)
+smod.data_stochsim.simulation_endtime
+smod.data_stochsim.simulation_timesteps
+smod.GetWaitingtimes()
+smod.PrintWaitingtimesMeans()
+# 2: Do some Plotting
+smod.PlotSpeciesTimeSeries()
+smod.PlotWaitingtimesDistributions()
+smod.PlotPropensitiesTimeSeries()
+# 3: Write data to a text file
+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')
+# 4: Show the means from the data of 3-th trajectory
+smod.DoStochSim(trajectories=3) # multiple trajectories
+smod.data_stochsim.simulation_trajectory
+smod.PrintSpeciesMeans()
+smod.PrintSpeciesStandardDeviations()
+# 5: Switch to data from trajectory 1 and show the means of each species
+smod.GetTrajectoryData(1)
+smod.PrintSpeciesMeans()
+smod.PrintSpeciesStandardDeviations()
+# 6: Do one long simulation
+smod.DoStochSim(trajectories=1,end=1000000,mode='steps')
+smod.PrintSpeciesMeans()
+smod.PrintSpeciesStandardDeviations()
+# 7: Plot the PDF for different bin sizes
+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')
+
+# 8: Usage of the Reload Function: Ksyn = 20, kdeg = 0.2
+smod.ChangeParameter('Ksyn',20.0)
+smod.ChangeParameter('Kdeg',0.2)
+smod.DoStochSim()
+smod.PrintSpeciesMeans()   # should be ~Ksyn/Kdeg
+
+# 9: Use another model to show the Interpolation features
+smod.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)
+
+# 9: Test each method for different models: 
+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 error
+
+smod.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 implementations
+
+# 10: Use the Next Reaction Method to test a model with a time event
+smod.Model('dsmts-003-03.xml.psc') 
+smod.DoStochSim(method = 'NextReactionMethod')
+smod.DoTestsuite()
+
+# 11: Use the First Reaction method to test a model with a concentration event 
+smod.Model('dsmts-003-04.xml.psc')
+smod.DoStochSim(method = 'FirstReactionMethod')
+smod.DoTestsuite()
+
+# 12: Volume Models
+smod.Model('dsmts-001-11.xml.psc') 
+smod.DoStochSim(method = 'Direct',trajectories=1000,end=50,mode ='time')
+smod.PrintAverageSpeciesTimeSeries()