def selectfft():
reslist2 = list()
selection2 = lstbox2.curselection()
plt.figure()
if datatype=='demod':
plt.title('%s ASD from %s %s' %(mm,dd,yyyy))
if datatype=='raw':
plt.title('ASD from %s %s %s' %(mm,dd,yyyy))
for i in selection2:
entry2 = lstbox2.get(i)
reslist2.append(entry2)
for val in reslist2:
chan=nametochan(val[:6])
if datatype=='demod':
component=val[-1]
if ((component != 'T') and (component != 'Q') and (component != 'U')):
component='T'
freq,psd=cu.nps(d[chan][component],samprate,minfreq=minfreq)
if datatype=='raw':
freq,psd=cu.nps(d[chan].flatten(),samprate*256,minfreq=minfreq)
plt.plot(freq,np.sqrt(psd)*1e9,label=val)
plt.xlabel('Frequency [Hz]')
plt.ylabel(r'ASD [$\frac{nV}{\sqrt{Hz}}$]')
plt.legend()
plt.show(block=False)
#base rotation rate
rotrate = 25
samprate = rotrate * 256
bbgain = {}
bbgain['ch0'] = 100.
bbgain['ch2'] = 100.
bbgain['ch4'] = 100.
tamb = 295
#arbitrary, but hopefully low impact on the gain
tsky = 40
epsilons = {}
calsecco = {}
calfoam = {}
for ch in chans:
zsky1 = cu.nps(cal[ch].flatten()[ssky1], samprate, minfreq=1)
zsky3 = cu.nps(cal[ch].flatten()[ssky3], samprate, minfreq=1)
zfoam1 = cu.nps(cal[ch].flatten()[sfoam1], samprate, minfreq=1)
zfoam2 = cu.nps(cal[ch].flatten()[sfoam2], samprate, minfreq=1)
zecco = cu.nps(cal[ch].flatten()[secco], samprate, minfreq=1)
epsilon = np.sqrt(
(zfoam1[1][zfoam1[0] == 50] + zfoam2[1][zfoam2[0] == 50])) / (np.sqrt(
zsky1[1][zsky1[0] == 50]) + np.sqrt(zsky3[1][zsky3[0] == 50]))
epsilons[ch] = epsilon[0]
for ch in ['ch1', 'ch3', 'ch5']:
calsecco[ch] = (tamb - tsky) / (np.mean(cal[ch].flatten()[secco]) /
np.mean(cal[ch].flatten()[ssky2]))
calsecco['ch0'] = calsecco['ch1'] / bbgain['ch0']
calsecco['ch2'] = calsecco['ch3'] / bbgain['ch2']
calsecco['ch4'] = calsecco['ch5'] / bbgain['ch4']
#base rotation rate
rotrate=25
samprate=rotrate*256
bbgain={}
bbgain['ch0']=100.
bbgain['ch2']=100.
bbgain['ch4']=100.
tamb=295
#arbitrary, but hopefully low impact on the gain
tsky=40
epsilons={}
calsecco={}
calfoam={}
for ch in chans:
zsky1=cu.nps(cal[ch].flatten()[ssky1],samprate,minfreq=1)
zsky3=cu.nps(cal[ch].flatten()[ssky3],samprate,minfreq=1)
zfoam1=cu.nps(cal[ch].flatten()[sfoam1],samprate,minfreq=1)
zfoam2=cu.nps(cal[ch].flatten()[sfoam2],samprate,minfreq=1)
zecco=cu.nps(cal[ch].flatten()[secco],samprate,minfreq=1)
epsilon=np.sqrt((zfoam1[1][zfoam1[0]==50] + zfoam2[1][zfoam2[0]==50]))/(np.sqrt(zsky1[1][zsky1[0]==50]) + np.sqrt(zsky3[1][zsky3[0]==50]))
epsilons[ch]=epsilon[0]
plt.figure(figsize=(12,6))
plt.plot(zsky1[0],np.sqrt(zsky1[1]),label='Sky1')
plt.plot(zsky3[0],np.sqrt(zsky3[1]),label='Sky3')
plt.plot(zfoam1[0],np.sqrt(zfoam1[1]),label='Foam1')
plt.plot(zfoam2[0],np.sqrt(zfoam2[1]),label='Foam2')
plt.plot(zecco[0],np.sqrt(zecco[1]),label='eccosorb')
plt.title('Sky tests Nov , 2012 (thRu pit door). 10 GHz COFE detector '+ch+' emissivity='+np.str(epsilon[0]))
plt.xlabel('Frequency, Hz')
plt.ylabel('Amplitude Spectral Density, V/sqrt(Hz)')
#base rotation rate
rotrate=25
samprate=rotrate*256
bbgain={}
bbgain['ch0']=100.
bbgain['ch2']=100.
bbgain['ch4']=100.
tamb=295
#arbitrary, but hopefully low impact on the gain
tsky=40
epsilons={}
calsecco={}
calfoam={}
for ch in chans:
zsky1=cu.nps(cal[ch].flatten()[ssky1],samprate,minfreq=1)
zsky3=cu.nps(cal[ch].flatten()[ssky3],samprate,minfreq=1)
zfoam1=cu.nps(cal[ch].flatten()[sfoam1],samprate,minfreq=1)
zfoam2=cu.nps(cal[ch].flatten()[sfoam2],samprate,minfreq=1)
zecco=cu.nps(cal[ch].flatten()[secco],samprate,minfreq=1)
epsilon=np.sqrt((zfoam1[1][zfoam1[0]==50] + zfoam2[1][zfoam2[0]==50]))/(np.sqrt(zsky1[1][zsky1[0]==50]) + np.sqrt(zsky3[1][zsky3[0]==50]))
epsilons[ch]=epsilon[0]
for ch in ['ch1','ch3','ch5']:
calsecco[ch]=(tamb-tsky)/(np.mean(cal[ch].flatten()[secco])/np.mean(cal[ch].flatten()[ssky2]))
calsecco['ch0']=calsecco['ch1']/bbgain['ch0']
calsecco['ch2']=calsecco['ch3']/bbgain['ch2']
calsecco['ch4']=calsecco['ch5']/bbgain['ch4']
#now get the other sky data
get_ipython().magic(u"cd 'c:/cofe/cofe_ground_fall_2012/data/20121113'")
#base rotation rate
rotrate = 25
samprate = rotrate * 256
bbgain = {}
bbgain['ch0'] = 100.
bbgain['ch2'] = 100.
bbgain['ch4'] = 100.
tamb = 295
#arbitrary, but hopefully low impact on the gain
tsky = 40
epsilons = {}
calsecco = {}
calfoam = {}
for ch in chans:
zsky1 = cu.nps(cal[ch].flatten()[ssky1], samprate, minfreq=1)
zsky3 = cu.nps(cal[ch].flatten()[ssky3], samprate, minfreq=1)
zfoam1 = cu.nps(cal[ch].flatten()[sfoam1], samprate, minfreq=1)
zfoam2 = cu.nps(cal[ch].flatten()[sfoam2], samprate, minfreq=1)
zecco = cu.nps(cal[ch].flatten()[secco], samprate, minfreq=1)
epsilon = np.sqrt(
(zfoam1[1][zfoam1[0] == 50] + zfoam2[1][zfoam2[0] == 50])) / (np.sqrt(
zsky1[1][zsky1[0] == 50]) + np.sqrt(zsky3[1][zsky3[0] == 50]))
epsilons[ch] = epsilon[0]
plt.figure(figsize=(12, 6))
plt.plot(zsky1[0], np.sqrt(zsky1[1]), label='Sky1')
plt.plot(zsky3[0], np.sqrt(zsky3[1]), label='Sky3')
plt.plot(zfoam1[0], np.sqrt(zfoam1[1]), label='Foam1')
plt.plot(zfoam2[0], np.sqrt(zfoam2[1]), label='Foam2')
plt.plot(zecco[0], np.sqrt(zecco[1]), label='eccosorb')
plt.title('Sky tests Nov , 2012 (thRu pit door). 10 GHz COFE detector ' +
