def simulateAndPlot(r, start, end, steps, selection=None): import tellurium as te if selection is None: result = r.simulate(start, end, steps) else: result = r.simulate(start, end, steps, selection) te.plotWithLegend(r, result)
def simulateAndPlot(rr, startTime=0, endTime=5, numberOfPoints=500): """ Carry out a simulation and plot the results. Returns the result to the caller Example: simulateAndPlot (rr) simulateAndPlot (rr, 0, 10, 100) """ result = rr.simulate(startTime, endTime, numberOfPoints) tellurium.plotWithLegend(rr, result) return result
def simulateAndPlot(r, *args, **kwargs): """ Simulate with r.simulate with given arguments and plot with tellurium. """ result = r.simulate(*args, **kwargs) import tellurium as te te.plotWithLegend(r, result)
rr = te.loada(''' $Xo -> S1; k1*Xo; S1 -> $X1; k2*S1; S1 -> $X2; k3*S1; // Initial Value Xo = 10; X1 = 0; X2 = 0; k1 = 3; k2 = 1.5; k3 = 0.5; // Initial Starting Point S1 = 1; ''') #rr.steadyState() print rr.S1 m1 = rr.simulate(0, 20, 100, ["time", "S1"]) rr.Xo = rr.Xo + 0.75 m2 = rr.simulate(20, 40, 100, ["time", "S1"]) m3 = numpy.vstack((m1, m2)) rr.Xo = rr.Xo - 0.75 m4 = rr.simulate(40, 60, 100, ["time", "S1"]) result = numpy.vstack((m3, m4)) #Plotting te.plotWithLegend(rr, result) plt.title('Concentration of S1 with Perturbation', fontsize=14) plt.xlabel('Time(s)', fontsize=14) plt.ylabel('Concentration(M)', fontsize=14)
# -*- coding: utf-8 -*- """ Created on Tue Mar 11 14:53:42 2014 @author: mgaldzic """ import tellurium as te #Single gene expressing protein and protein undergoing degradation model = ''' model mygene() # Reactions: J1: -> P; Vm*T^4/(K+T^4) J2: P -> ; k1*P; # Species initializations: P = 0; T = 5; Vm = 10 K = 0.5; k1 = 4.5; end ''' r = te.loadAntimonyModel(model) result = r.simulate(0, 10, 50) te.plotWithLegend (r, result)
# Incoherent Type I Genetic Network, Pulse generator rr = te.loada (''' $G1 -> P2; t1*a1*P1/(1 + a1*P1); P2 -> $w; gamma_1*P2; $G3 -> P3; t2*b1*P1/(1 + b1*P1 + b2*P2 + b3*P1*P2^8); P3 -> $w; gamma_2*P3; P2 = 0; P3 = 0; P1 = 0.01; G3 = 0; G1 = 0; t1 = 5; a1 = 0.1; t2 = 1; b1 = 1; b2 = 0.1; b3 = 10; gamma_1 = 0.1; gamma_2 = 0.1; ''') # Time course response for a step pulse rr.P1 = 0.0; m1 = rr.simulate(0, 10, 100, ["Time", "P1", "P3"]) rr.P1 = 0.4 # Input stimulus m2 = rr.simulate(10, 50, 200, ["Time", "P1", "P3"]) m = numpy.vstack((m1, m2)) te.plotWithLegend(rr, m)