def run(self):
wlm = wlm_web()
global data
data = [[0] * data_len] * 8
count = 0
while True:
count += 1
wlm_data = wlm.get_data()
for i in range(8):
data[i] = data[i][1:] + [round(wlm_data[i], 6)]
# print('wavelength is %.6f' % wlm_data[3])
# print(T_value, P_value)
time.sleep(0.1)
from scipy.optimize import curve_fit
from save_data import save_file
from progressbar import *
import matplotlib.pyplot as plt
from wlm_web import wlm_web
import time
from image_processing import has_ion
from ttl_client import shutter
from current_client import current_web
# from load_ion_client import reload_ion
if os.name == "nt":
import msvcrt
wm = wlm_web()
curr = current_web()
shutter_370 = shutter(com=0)
flip_mirror = shutter(com=1)
shutter_399 = shutter(com=2)
ccd_on = flip_mirror.off
pmt_on = flip_mirror.on
def reload_ion():
t1 = time.time()
print('RELOADING...')
pmt_on()
time.sleep(0.3)
def run(self):
# dds_435 = dds_controller()
# flip_time = 75
# microwave_fre = 400.0
self.pre_set()
wm = wlm_web()
init_fre = 103
lock_point = 871.034931
N = 4000
# progressbar
widgets = ['Progress: ',Percentage(), ' ', Bar('#'),' ', Timer(),
' ', ETA(), ' ']
pbar = ProgressBar(widgets=widgets, maxval=10*N).start()
file_name = 'data\\'+str(init_fre)+'-'+str(float(init_fre+N*0.0005))+'.csv'
file = open(file_name,'w+')
file.close()
data = np.zeros((4,N))
for i in range(N):
file = open(file_name,'a')
AOM_435 =init_fre+0.0005*i #- 0.001*N/2
wl_871 = wm.get_data()[0]
is_871_locked = abs(wl_871-lock_point) < 0.000004
while not is_871_locked:
time.sleep(5)
wl_871 = wm.get_data()[0]
is_871_locked = abs(wl_871-lock_point) < 0.000004
code = "conda activate base && python dds.py " + str(AOM_435)
os.system(code)
temp = self.run_sequence()
data[0,i]=AOM_435
# accuracy
data[1,i]=temp[0]*2
# count
data[2,i]=temp[1]
data[3,i]=wm.get_data()[0]
print("Accuracy:%.1f%%" % (temp[0]*2))
print('Photon Count:%d' % temp[1])
pbar.update(10*i+1)
print('\n')
content =str(data[0,i])+','+str(data[1,i])+','+str(data[2,i])+','+str(data[3,i])+'\n'
# print(content)
file.write(content)
file.close()
np.save('microwave',data)
file.close()
save_file(data,__file__[:-3])
plt.figure(1)
ax1 = plt.subplot(121)
ax1.plot(data[0],data[1])
ax2 = plt.subplot(122)
ax2.plot(data[0],data[2])
plt.show()