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)')