mirror of https://github.com/m-labs/artiq.git
flopping_f_simulation: use ufuncs in model()
This commit is contained in:
parent
5d58258bf2
commit
2a5eaea411
|
@ -13,14 +13,9 @@ def model(x, F0):
|
|||
tpi = 0.03
|
||||
A = 80
|
||||
B = 40
|
||||
return A+(B-A)/2/(4*tpi**2*(x-F0)**2+1)*(1-cos(pi*t/tpi*sqrt(4*tpi**2*(x-F0)**2+1)))
|
||||
|
||||
|
||||
def model_numpy(xdata, F0):
|
||||
r = np.zeros(len(xdata))
|
||||
for i, x in enumerate(xdata):
|
||||
r[i] = model(x, F0)
|
||||
return r
|
||||
return A + (B - A)/2/(4*tpi**2*(x - F0)**2+1)*(
|
||||
1 - np.cos(np.pi*t/tpi*np.sqrt(4*tpi**2*(x - F0)**2 + 1))
|
||||
)
|
||||
|
||||
|
||||
class FloppingF(EnvExperiment):
|
||||
|
@ -68,8 +63,7 @@ class FloppingF(EnvExperiment):
|
|||
assert frequency.shape == brightness.shape
|
||||
self.set_dataset("flopping_f_frequency", frequency,
|
||||
broadcast=True, save=False)
|
||||
popt, pcov = curve_fit(model_numpy,
|
||||
frequency, brightness,
|
||||
popt, pcov = curve_fit(model, frequency, brightness,
|
||||
p0=[self.get_dataset("flopping_freq", 1500.0)])
|
||||
perr = np.sqrt(np.diag(pcov))
|
||||
if perr < 0.1:
|
||||
|
|
Loading…
Reference in New Issue