def main():
"""Simulate temperature dependent aggregation and disaggregation.
Clearly need to explicitly write temperature into the simulate method in
the future.
"""
# Rates
k1 = 0.01 #disaggregation rate
k2 = 0.1 #chaperone degradation rate
k3 = 0.00001 #dimerization rate
k4 = 0.01 #heat induced chaperone production rate
k5 = 0.01 #heat inactivation rate of assembler
T1 = 200
T2 = 220
# Species
A = Species("A", 100)
AA = Species("AA", 0)
iAA = Species("iAA", 0)
C = Species("C", 10)
# Temperature independent reactions
disagg = Reactivation("Disagg", [iAA, C], [A, C], k1)
deg = UniDeg("C Degredation", [C], [None], k2)
# Simulation and Temperature-Dependent Reaction
# Temperature ramp = 300, 320, 300
nuc = Temp_Dimerization("Nucleation", [A], [AA], k3, T1)
hip = HeatInducedProduction("Heat Induced Production", [iAA], [C], k4, T1)
inactivation = HeatInducedInactivation("Inactivation", [AA], [iAA], k5, T1)
sp_list = [A, AA, iAA, C]
rxn_list = [nuc, inactivation, disagg, hip, deg]
system = Network(sp_list, rxn_list)
x = system.simulate(0, 20, "None")
#nuc = Temp_Dimerization("Nucleation", [A], [AA], k3, 30)
#hip = HeatInducedProduction("Heat Induced Production", [iAA], [C], k4, T2)
#inactivation = HeatInducedInactivation("Inactivation", [AA], [iAA], k5, T2)
#y = system.simulate(x[-1,0], 50, "None")
#nuc = Temp_Dimerization("Nucleation", [A], [AA], k3, 10)
#hip = HeatInducedProduction("Heat Induced Production", [iAA], [C], k4, T1)
#inactivation = HeatInducedInactivation("Inactivation", [AA], [iAA], k5, T1)
#z = system.simulate(y[-1,0], 70, "None")
#final = np.vstack((x, y, z))
#x2 = [i[-1,0] for i in [x, y, z]]
#y2 = [T1, T2, T1]
fig, axis = plt.subplots(figsize=(10, 10))
for i in range(1, len(sp_list) + 1):
axis.step(x[:, 0], x[:, i], label=sp_list[i - 1].name)
plt.legend(loc=0)
plt.xlim(0, x[-1, 0])
plt.xlabel("Time")
plt.ylabel("Molecular species count")
#axis2 = axis.twinx()
#axis2.step(x2,y2, c='darkgray')
#plt.ylim(T1,T2)
#plt.fill_between([x2[0], x2[1]], [220,220], alpha=0.5, color='darkgray')
#plt.ylabel("Temperature (T)")
#plt.savefig("reactivation_plot.pdf")
plt.show()
def main():
"""Simulate temperature dependent aggregation and disaggregation.
Clearly need to explicitly write temperature into the simulate method in
the future.
"""
# Rates
k1 = 0.01 #disaggregation rate
k2 = 0.1 #chaperone degradation rate
k3 = 0.00001 #dimerization rate
k4 = 0.01 #heat induced chaperone production rate
k5 = 0.01 #heat inactivation rate of assembler
T1 = 200
T2 = 220
# Species
A = Species("A", 100)
AA = Species("AA", 0)
iAA = Species("iAA", 0)
C = Species("C", 10)
# Temperature independent reactions
disagg = Reactivation("Disagg", [iAA, C], [A, C], k1)
deg = UniDeg("C Degredation", [C], [None], k2)
# Simulation and Temperature-Dependent Reaction
# Temperature ramp = 300, 320, 300
nuc = Temp_Dimerization("Nucleation", [A], [AA], k3, T1)
hip = HeatInducedProduction("Heat Induced Production", [iAA], [C], k4, T1)
inactivation = HeatInducedInactivation("Inactivation", [AA], [iAA], k5, T1)
sp_list = [A, AA, iAA, C]
rxn_list= [nuc, inactivation, disagg, hip, deg]
system = Network(sp_list, rxn_list)
x = system.simulate(0, 20, "None")
#nuc = Temp_Dimerization("Nucleation", [A], [AA], k3, 30)
#hip = HeatInducedProduction("Heat Induced Production", [iAA], [C], k4, T2)
#inactivation = HeatInducedInactivation("Inactivation", [AA], [iAA], k5, T2)
#y = system.simulate(x[-1,0], 50, "None")
#nuc = Temp_Dimerization("Nucleation", [A], [AA], k3, 10)
#hip = HeatInducedProduction("Heat Induced Production", [iAA], [C], k4, T1)
#inactivation = HeatInducedInactivation("Inactivation", [AA], [iAA], k5, T1)
#z = system.simulate(y[-1,0], 70, "None")
#final = np.vstack((x, y, z))
#x2 = [i[-1,0] for i in [x, y, z]]
#y2 = [T1, T2, T1]
fig, axis = plt.subplots(figsize=(10,10))
for i in range(1,len(sp_list)+1):
axis.step(x[:,0], x[:,i], label=sp_list[i-1].name)
plt.legend(loc=0)
plt.xlim(0,x[-1,0])
plt.xlabel("Time")
plt.ylabel("Molecular species count")
#axis2 = axis.twinx()
#axis2.step(x2,y2, c='darkgray')
#plt.ylim(T1,T2)
#plt.fill_between([x2[0], x2[1]], [220,220], alpha=0.5, color='darkgray')
#plt.ylabel("Temperature (T)")
#plt.savefig("reactivation_plot.pdf")
plt.show()
def main():
"""Generate and simulate a model of lemmings approaching and jumping off
a cliff.
"""
L = Species("Lemming", 0)
arrival = ConstInduction("Induction", None, [L], 1.0)
jump = UniDeg("Degredation", [L], None, 0.1)
cliff = Network([L], [arrival, jump])
x = cliff.simulate(0, 200, "dummy_file2.dat")
y = x[:,1]
print "Mean: %f, Mean/Variance: %f \n (Poisson mean/var = 1)" % (np.mean(y), np.mean(y)/np.var(y))
plt.subplot(121)
plt.step(x[:,0], y)
plt.title("Lemmings vs. time")
plt.xlabel("Time (s)")
plt.ylabel("Number of Lemmings")
plt.subplot(122)
plt.title("Count distribution")
plt.hist(y, normed=True)
plt.xlabel("Lemming population")
plt.show()