def LorenDiff(ppm, y):
baseline = Sim.Spin.Spin(R1=y[-1], R2=0, x0=0.0, c=1.0)
water = Sim.Spin.Spin(R1=0, R2=100, x0=0.0, c=1e3)
s1 = Sim.Spin.Spin(R1=0, R2=1e4, x0=-3.0, c=1e3)
baseline.set_lb_ub('c', None, None)
baseline.set_lb_ub('x0', None, None)
baseline.set_lb_ub('R1', None, None)
baseline.set_lb_ub('R2', None, None)
water.set_lb_ub('R2', None, None)
water.set_lb_ub('c', None, None)
water.set_lb_ub('x0', None, None)
s1.set_lb_ub('R2', None, None)
s1.set_lb_ub('c', None, None)
s1.set_lb_ub('x0', None, None)
spins = [baseline, water, s1]
x0 = []
for s in spins:
for v in s.get_opt_vals():
x0.append(v)
opt = optimize.minimize(_calc_RMSD,
x0,
args=(y, ppm, spins),
method='Nelder-Mead',
jac=False,
options={
'maxiter': 1e4,
'maxfev': 1e4
})
ls = np.zeros_like(ppm)
xxx = np.ndarray.tolist(opt.x)
for i, s in enumerate(spins):
s.set_opt_vals(xxx)
if i == 0: ls += Shapes.logistic_basline(ppm, s)
else: ls += Shapes.Guassian(ppm, s)
return ls
