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']