### Analyse one to define the list of pixok name = 'ExtSrc' fnum = 150 fff = 0.333 dc = 0.33 #### Saturation value: 2.235174179076e-08 tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as1[0], 1, name=name, initpars=None, lowcut=0.05, highcut=15., reselect_ok=False, okfile='ScanAz2019-01-30_OK_Asic1.fits') tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as2[0], 2, name=name,
#### Analyse one to define the list of pixok name = 'ExtSrc(Auto)' fnum = 150 fff = 0.333 dc = 0.33 # Saturation value: 2.235174179076e-08 tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as1[0], 1, name=name, initpars=None, lowcut=0.05, highcut=15., rangepars=[[0., 1.], [0., 0.5], [0., 1. / fff], [0., 1000.]], stop_each=False, reselect_ok=False, okfile='ScanAz2019-01-30_OK_Asic1.fits') tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as2[0], 2,
### Analyse one to define the list of pixok name = 'ExtSrc(Auto)' fnum = 150 fff = 0.333 dc = 0.33 #### Saturation value: 2.235174179076e-08 tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as1, 1, name=name, timerange=time_ranges[:, 0], initpars=None, lowcut=0.05, highcut=15., rangepars=[[0., 1.], [0., 0.5], [0., 1. / fff], [0., 5000.]], reselect_ok=False, okfile='ScanAz2019-02-01_nuscan_OK_Asic1.fits') tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as2, 2,
pars = [] for i in range(len(infos)): the_info = infos[i] fnum = the_info['fnum'] asic1 = the_info['asic'] fff = the_info['fff'] dc = the_info['dc'] initpars = the_info['initpars'] tt, folded1, okfinal1, allparams1, allerr1, allchi21, ndf1 = ft.run_asic( fnum, 0, fff, dc, asic1, 1, reselect_ok=False, lowcut=0.05, highcut=15., nbins=50, rangepars=[[0., 1.], [0., 0.5], [0., 1. / fff], [0., 5000.]], initpars=initpars, okfile='TES_OK_ExtSrc150GHz_asic1.fits') pars.append(allparams1) img_amp = np.zeros((128, len(infos))) + np.nan img_tau = np.zeros((128, len(infos))) + np.nan for i in range(len(infos)): img_amp[okfinal1, i] = pars[i][okfinal1, 3] img_tau[okfinal1, i] = pars[i][okfinal1, 1] # Time response tau
# ## Therefore at the end we have a fit of two # ## variables for each TES: time constant and # ## signal amplitude # ## Once the reselect_ok=True case has been done, # ## a file is created with the list of valid TES # ## and the code can be ran in a much faster way # ## with reslect_ok=False # ################################################# #### Asic 1 # run ASIC analysis code tt, folded1, okfinal1, allparams1, allerr1, allchi21, ndf1 = ft.run_asic( fib, Vtes, fff, dc, asic1, 1, reselect_ok=False, notch=notch, rangepars=[[0., 1.], [0., 0.5], [0., 1. / fff], [0., 20.]]) # run ASIC plotter plt.savefig('fib{}_ASIC1_summary.png'.format(fib)) #### Asic 2 tt, folded2, okfinal2, allparams2, allerr2, allchi22, ndf2 = ft.run_asic( fib, Vtes, fff, dc, asic2, 2,
the_info = infos[i] name = the_info['name'] fnum = the_info['fnum'] asic1 = the_info['asic'] fff = the_info['fff'] dc = the_info['dc'] initpars = the_info['initpars'] tt, folded1, okfinal1, allparams1, allerr1, allchi21, ndf1 = ft.run_asic( fnum, 0, fff, dc, asic1, 1, reselect_ok=False, lowcut=0.05, highcut=15., nbins=50, nointeractive=False, doplot=True, lastpassallfree=False, okfile='TES_OK_ExtSrc150GHz_asic1.fits', name=name, initpars=initpars) pars.append(allparams1) img_amp = np.zeros((128, len(infos))) + np.nan img_tau = np.zeros((128, len(infos))) + np.nan for i in xrange(len(infos)): img_amp[okfinal1, i] = pars[i][okfinal1, 3] img_tau[okfinal1, i] = pars[i][okfinal1, 1]
def make_amp(dir, name='Integrating_sphere', fnum=150, fff=0.15, dc=0.33): """ Parameters ---------- dir : str Directory for data files name : str Name of the data set fnum : float Frequency of the calibration source in GHz. fff : float Modulation frequency of the calibration source. dc : float Duty cycle of the modulation. Returns ------- """ as1 = glob.glob(dir + '/Sums/*asic1*.fits') as2 = glob.glob(dir + '/Sums/*asic2*.fits') # Asic 1 tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as1[0], 1, name=name, initpars=None, lowcut=0.05, highcut=15., rangepars=[[0., 1.], [0., 0.5], [0., 1. / fff], [0., 10000.]], stop_each=False, reselect_ok=False, okfile='TES_OK_2019-02-15_Sphere_Asic1.fits') amps1 = params[:, 3] # Asic 2 tt, folded, okfinal, params, err, chi2, ndf = ft.run_asic( fnum, 0, fff, dc, as2[0], 2, name=name, initpars=None, lowcut=0.05, highcut=15., reselect_ok=False, rangepars=[[0., 1.], [0., 0.5], [0., 1. / fff], [0., 10000.]], okfile='TES_OK_2019-02-15_Sphere_Asic2.fits') amps2 = params[:, 3] # Put the 2 asics together amps = np.append(amps1, amps2) return amps