def amplitude(f_GHz):
res=simulate_resonance(SI(f_GHz*1e9,"1/s"))
osc=[[r[0].value,r[2][0],r[2][1],r[2][2]]
for r in res[400:]] # skip lead_in
(f,params)=nmag.fit_oscillation(osc)
a=math.sqrt(sum([p[1]*p[1] for p in params]))
return -a # we minimize -(amplitude)!
def amplitude(f_GHz):
res = simulate_resonance(SI(f_GHz * 1e9, "1/s"))
osc = [[r[0].value, r[2][0], r[2][1], r[2][2]]
for r in res[400:]] # skip lead_in
(f, params) = nmag.fit_oscillation(osc)
a = math.sqrt(sum([p[1] * p[1] for p in params]))
return -a # we minimize -(amplitude)!
def amplitude(freq_GHz):
a_data=simulate_resonance(SI(freq_GHz*1e9,"1/s"))
o_data=[[a[0].value,a[2][0],a[2][1],a[2][2]] for a in a_data]
(fit_freq,fit_params)=nmag.fit_oscillation(o_data[5000:]) # skip lead-in
a=math.sqrt(sum([p[1]*p[1] for p in fit_params]))
print "Freq: %.2f GHz -- Amplitude: %f"%(freq_GHz,a)
r.write("Freq: %.2f GHz -- Amplitude: %f\n"%(freq_GHz,a)) # DDD
r.flush() # DDD
r2.write(" ]\n\n\n")
r2.flush()
return -a # we minimize the *negative* amplitude here!
def amplitude(freq_GHz):
a_data = simulate_resonance(SI(freq_GHz * 1e9, "1/s"))
o_data = [[a[0].value, a[2][0], a[2][1], a[2][2]] for a in a_data]
(fit_freq,
fit_params) = nmag.fit_oscillation(o_data[5000:]) # skip lead-in
a = math.sqrt(sum([p[1] * p[1] for p in fit_params]))
print "Freq: %.2f GHz -- Amplitude: %f" % (freq_GHz, a)
r.write("Freq: %.2f GHz -- Amplitude: %f\n" % (freq_GHz, a)) # DDD
r.flush() # DDD
r2.write(" ]\n\n\n")
r2.flush()
return -a # we minimize the *negative* amplitude here!
