def analysis():
fres_desr,data_desr,udata_desr = sc.plot_dark_esr(sc.get_latest_data('dark',date='20130311'),d='20130311')
fres_zero,data_zero,udata_zero = sc.plot_dark_esr(sc.get_latest_data('init_',date='20130311'),d='20130311')
fres_min1,data_min1,udata_min1 = sc.plot_dark_esr(sc.get_latest_data('init_',date='20130305'),d='20130305')
esr_data={}
xfit=np.linspace(fres_desr['x'].min(),fres_desr['x'].max(),501)
esr_data['xfit']=xfit
esr_data['desrfit'] = fres_desr['fitfunc'](xfit)
esr_data['zerofit'] = fres_zero['fitfunc'](xfit)
esr_data['min1fit'] = fres_min1['fitfunc'](xfit)
esr_data['xdesr'] = fres_desr['x']
esr_data['xzero'] = fres_zero['x']
esr_data['xmin1'] = fres_min1['x']
esr_data['datadesr'] = data_desr
esr_data['datazero'] = data_zero
esr_data['datamin1'] =data_min1
esr_data['udatadesr'] = udata_desr
esr_data['udatazero'] = udata_zero
esr_data['udatamin1'] = udata_min1
print os.path.join(basepath,name)
print type(esr_data)
np.savez(os.path.join(basepath,name), **esr_data)
def analysis():
fres_desr, data_desr, udata_desr = sc.plot_dark_esr(sc.get_latest_data(
'dark', date='20130311'),
d='20130311')
fres_zero, data_zero, udata_zero = sc.plot_dark_esr(sc.get_latest_data(
'init_', date='20130311'),
d='20130311')
fres_min1, data_min1, udata_min1 = sc.plot_dark_esr(sc.get_latest_data(
'init_', date='20130305'),
d='20130305')
esr_data = {}
xfit = np.linspace(fres_desr['x'].min(), fres_desr['x'].max(), 501)
esr_data['xfit'] = xfit
esr_data['desrfit'] = fres_desr['fitfunc'](xfit)
esr_data['zerofit'] = fres_zero['fitfunc'](xfit)
esr_data['min1fit'] = fres_min1['fitfunc'](xfit)
esr_data['xdesr'] = fres_desr['x']
esr_data['xzero'] = fres_zero['x']
esr_data['xmin1'] = fres_min1['x']
esr_data['datadesr'] = data_desr
esr_data['datazero'] = data_zero
esr_data['datamin1'] = data_min1
esr_data['udatadesr'] = udata_desr
esr_data['udatazero'] = udata_zero
esr_data['udatamin1'] = udata_min1
print os.path.join(basepath, name)
print type(esr_data)
np.savez(os.path.join(basepath, name), **esr_data)
def main():
if power_and_mw_ok():
counter.set_is_running(False)
if not SE:
generate_sequence()
else:
generate_sequence_SE()
awg.set_runmode('SEQ')
awg.start()
while awg.get_state() != 'Waiting for trigger':
qt.msleep(1)
data = meas.Measurement(name,'rabi')
microwaves.set_status('on')
spin_control(name,data,par)
end_measurement()
sc.plot_rabi(sc.get_latest_data(name))
else:
print 'Measurement aborted.'
zfoldernames=['154355']
zd='20130403'
th=''
dir='up'
'''
# 1 msmnt
d='20130405'
foldernames=['141755','144145','150814','153230','155539','161924','164248','171312']
zd=d
zfoldernames=['130443','173349']
th=''
'''
tau=50.
utau=1
for n in foldernames:
datapath=sc.get_latest_data(n,date=d)
files = os.listdir(datapath)
f='Spin_RO'
for k in files:
if f in k:
spin_ro_file = k
data = np.load(datapath+'\\'+spin_ro_file)
if (n==foldernames[0]):
phase=np.zeros(len(data['FS']))
rep=np.zeros(len(data['FS']))
reps_array=data['SN']+data['FF']+data['FS']
reps=reps_array[0]
data_norm={}
data_norm['sweep_par']=data['sweep_par']
from numpy import *
import pylab as plt
from analysis.lib.fitting import fit, common
from analysis.lib.tools import plot
from analysis.lib.spin import spin_control as sc
datafolders=['no_Ey','1u_Ey','2u_Ey','3u_Ey']
RO_time=[0,1,2,3]
for i in datafolders:
result= sc.plot_rabi(sc.get_latest_data(i))
amp.append(2*result[0]['params'][1])
phase.append(result[0]['params'][3])
plt.figure(1)
plt.plot(RO_time,amp,'bo')
plt.xlabel ('RO time [us]', fontsize = 16)
plt.ylabel ('Contrast', fontsize = 16)
plt.ylim ([0, 1])
plt.show()
plt.figure(2)
plt.plot(RO_time,phase,'bo')
plt.xlabel ('RO time [us]', fontsize = 16)
plt.ylabel ('Phase [degree]', fontsize = 16)
plt.ylim ([0, 1])
plt.show()
from numpy import *
import pylab as plt
from analysis.lib.fitting import fit, common
from analysis.lib.tools import plot
from analysis.lib.spin import spin_control as sc
#datafolders=['1154','1252','1258','1303','1310','1347','1351','1316','1326', '1453']
#RO_time=[0,1,2,3,4,5,6,7,9, 11]
datafolders=['144831','145714','150926','151701','152503','153402','154024']
RO_power=[0,12,5,20,30,25,8]
amp=[]
phase=[]
for i in datafolders:
result= sc.plot_rabi(sc.get_latest_data(i))
result= sc.plot_rabi(sc.get_latest_data(i))
#qt.sleep(4)
amp.append(abs(2*result[0]['params'][1]))
phase.append(result[0]['params'][3])
'''
datafoldersCond=['1502','4us','6us','8us', '10us', '12us']
RO_timeCond=[2,4,6,8, 10, 12]
ampCond=[]
phaseCond=[]
for i in datafoldersCond:
result= sc.plot_rabi(sc.get_latest_data(i,datapath=r'D:\measuring\data\20121219'))
#qt.sleep(4)
ampCond.append(abs(2*result[0]['params'][1]))
phaseCond.append(result[0]['params'][3])
'''
result=fit.fit1d(np.array(RO_power), np.array(amp/amp[0]), common.fit_exp_decay_with_offset,
th=''
dir='up'
# 1 msmnt
d='20130405'
foldernames=['141755','144145','150814','153230','155539','161924','164248','171312']
zd=d
zfoldernames=['130443','173349']
th=''
'''
tau = 50.
utau = 1
p = r'D:\machielblok\Desktop\PhD\QTlab\data\output\multiple_msmnts'
t = 'uncollapse_crimson_50ns'
for n in foldernames:
datapath = sc.get_latest_data(n, date=d)
files = os.listdir(datapath)
f = 'Spin_RO'
for k in files:
if f in k:
spin_ro_file = k
data = np.load(datapath + '\\' + spin_ro_file)
if (n == foldernames[0]):
phase = np.zeros(len(data['FS']))
rep = np.zeros(len(data['FS']))
reps_array = data['SN'] + data['FF'] + data['FS']
reps = reps_array[0]
data_norm = {}
data_norm['sweep_par'] = data['sweep_par']