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%matplotlib inline
import moose
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy


    

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def displayPlots():
    '''Plotting concentration of reacting entities over time.'''
    for x in moose.wildcardFind( '/model/graphs/conc#/#' ):
        t = numpy.arange( 0, x.vector.size, 1 ) #sec
        plt.plot( t, x.vector, label=x.name )
        plt.xlabel("Time (s)")
        plt.ylabel("Concentration (mM)")
    plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,
           ncol=3, mode="expand", borderaxespad=0.)
    plt.show()


    

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solver = "gsl"  # Pick any of gsl, gssa, ee..
#moose.seed(124) # Important for stochastic simulation
mfile = 'M1719.g'
runtime = 100.0 #s
volume = 0.2e-18 #m^3


    

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moose.loadModel( mfile, '/model', solver )


    

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compartment = moose.element( 'model/kinetics' )
compartment.volume = volume #
r = moose.element( '/model/kinetics/equil' )

moose.reinit()
moose.start( runtime ) 
r.Kf *= 1.1 # small tap to break symmetry
moose.start( runtime ) 
r.Kf = r.Kb
moose.start( runtime ) 

r.Kb *= 2.0 # Moderate push does not tip it back.
moose.start( runtime ) 
r.Kb = r.Kf
moose.start( runtime ) 

r.Kb *= 5.0 # Strong push does tip it over
moose.start( runtime ) 
r.Kb = r.Kf
moose.start( runtime ) 
r.Kf *= 5.0 # Strong push tips it back.
moose.start( runtime ) 
r.Kf = r.Kb
moose.start( runtime ) 

displayPlots()


    

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