def get_cc(experiment):
ob = experiment.objectives['elongation_rate']
s = slicing.Slicer.from_objective_bind(ob)
rs, names, concentration_mesh = s.minimum_values('atp_concentration')
cc = zero_crossings(concentration_mesh[0], rs)[0]
return cc
def get_cc(experiment):
ob = experiment.objectives['elongation_rate']
s = slicing.Slicer.from_objective_bind(ob)
rs, names, concentration_mesh = s.minimum_values('atp_concentration')
cc = zero_crossings(concentration_mesh[0], rs)[0]
return cc
def D_vs_concentration(session, cc_scale=False, **kwargs):
# e = session.get_experiment('critical_concentration')
e = session.get_experiment('fujiwara_2002')
D_ob = e.objectives['final_diffusion_coefficient']
D_s = slicing.Slicer.from_objective_bind(D_ob)
Ds, name, concentration_mesh = D_s.minimum_values('atp_concentration')
j_ob = e.objectives['final_elongation_rate']
j_s = slicing.Slicer.from_objective_bind(j_ob)
js, name, concentration_mesh = j_s.minimum_values('atp_concentration')
concentration_mesh = concentration_mesh[0]
if cc_scale:
cc = zero_crossings(concentration_mesh, js)[0]
concentration_mesh = numpy.array(concentration_mesh) / cc
print 'cc =', cc
# pylab.figure()
pylab.subplot(2,1,1)
measurements.line((concentration_mesh, Ds), **kwargs)
if cc_scale:
pylab.axvline(x=1, color='black')
pylab.ylabel('Tip Diffusion Coefficient (mon**2 /s)')
pylab.subplot(2,1,2)
zero_concentrations = [concentration_mesh[0], concentration_mesh[-1]]
zero_values = [0, 0]
measurements.line((zero_concentrations, zero_values))
measurements.line((concentration_mesh, js), **kwargs)
if cc_scale:
pylab.axvline(x=1, color='black')
pylab.ylabel('Elongation Rate (mon /s )')
if cc_scale:
pylab.xlabel('[G-ATP-actin] (critical concentrations)')
else:
pylab.xlabel('[G-ATP-actin] (uM)')
