### 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