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artiq/examples/master/repository/flopping_f_simulation.py

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Python

from math import sqrt, cos, pi
import time
import random
import numpy as np
from scipy.optimize import curve_fit
from artiq import *
def model(x, F0):
t = 0.02
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
class FloppingF(EnvExperiment):
"""Flopping F simulation"""
def build(self):
self.attr_argument("frequency_scan", Scannable(
default=LinearScan(1000, 2000, 100)))
self.attr_argument("F0", NumberValue(1500, min=1000, max=2000))
self.attr_argument("noise_amplitude", NumberValue(0.1, min=0, max=100))
self.frequency = self.set_result("flopping_f_frequency", [], True)
self.brightness = self.set_result("flopping_f_brightness", [], True)
self.attr_device("scheduler")
def run(self):
for frequency in self.frequency_scan:
brightness = model(frequency, self.F0) + self.noise_amplitude*random.random()
self.frequency.append(frequency)
self.brightness.append(brightness)
time.sleep(0.1)
self.scheduler.submit(self.scheduler.pipeline_name, self.scheduler.expid,
self.scheduler.priority, time.time() + 20, False)
def analyze(self):
popt, pcov = curve_fit(model_numpy,
self.frequency.read, self.brightness.read,
p0=[self.get_parameter("flopping_freq")])
perr = np.sqrt(np.diag(pcov))
if perr < 0.1:
self.set_parameter("flopping_freq", float(popt))