def calc_n_sigma_for_w_and_dw(a1, a2):
w, domega = generate_w0_anddelta_w_from_fit(*a1, *a2)
omega_nsigma = n_sigma(*w_theo, *w)
delta_omega_nsigma = n_sigma(*domega, *w0_theo)
print("omega is", w)
print("delta omega is", domega)
print("nsigma_omega", omega_nsigma)
print("nsigma_delta_omega", delta_omega_nsigma)
return w, domega
def lin_fit(a1: FitObject,
a2: FitObject,
x: FitObject = default,
y: FitObject = partical):
theo = a1.val + a2.val * x.val
d1 = a1.err**2
d2 = x.val * a2.err
d3 = x.err * a2.val
dtheo = calc_sigma_div(d1, d2, d3)
print("theoretical:", theo, dtheo, dtheo / theo)
print("messured: ", y)
return n_sigma(theo, dtheo, y.val, y.err)
def square_fit(a1: FitObject,
a2: FitObject,
a3: FitObject,
x: FitObject = default,
y: FitObject = partical):
theo = a1.val + a2.val * x.val + a3.val * x.val**2
d1 = a1.err**2
d2 = x.val * a2.err
d3 = (a2.val + 2 * a3.val * x.val) * x.err
d4 = x.val**2 * a3.err
dtheo = calc_sigma_div(d1, d2, d3, d4)
print("theoretical:", theo, dtheo, dtheo / theo)
print("messured: ", y)
return n_sigma(theo, dtheo, y.val, y.err)
delta_omega_nsigma = n_sigma(*domega, *w0_theo)
print("omega is", w)
print("delta omega is", domega)
print("nsigma_omega", omega_nsigma)
print("nsigma_delta_omega", delta_omega_nsigma)
return w, domega
if __name__ == '__main__':
L = 0.8261
C = 1.5e-9
Rr = 6000
dl = 46.305e-3
dc = 0.048e-9
a1 = (0.0002135697, 3.270912e-06)
a2 = (7.665073e-06, 9.395436e-08)
w_theo = get_omega(L=L, DL=dl, C=C, DC=dc)
w0_theo = get_delta_omega(Rr, drt=150, L=L, dl=dl)
print("w_theo", w_theo)
print("w0_theo", w0_theo)
w1, domega1 = calc_n_sigma_for_w_and_dw(a1, a2)
a1 = (0.0002112431, 1.45986e-06)
a2 = (7.733287e-06, 4.128126e-08)
w2, domega2 = calc_n_sigma_for_w_and_dw(a1, a2)
print("omegas nsigma", n_sigma(*w2, *w1))
print("delta_omegas nsigma", n_sigma(*domega2, *domega1))