if Parameters.getboolean('Inputs', 'rotate'):
for i in range(nhorns):
ra[i,:], dec[i,:] = Pointing.Rotate(ra[i,:], dec[i,:], r0, d0, pang[i,:])
# Get the spectral data
# Level 1 v2 format: feed, sb, chan, samp
# Averaging Channels to improve signal to noise:
if Parameters.getboolean('Averaging', 'average'):
stride = Parameters.getint('Averaging','stride')
badChans = json.loads(Parameters.get('Averaging','badChannels'))
dnu = 2./tod.shape[2]
nu = np.arange(tod.shape[2])*dnu + dnu/2.
print(nu, dnu)
tod, anu = Filters.AverageFreqs(tod, nu, stride, badChans)
dataout['nu'] = anu
# Next make atmospheric corrections
if Parameters.getboolean('Atmosphere', 'remove'):
stride = Parameters.getint('Atmosphere','stride')
A = Atmosphere.SimpleRemoval(tod, el, stride)
dataout['atmos']= A
if Parameters.getboolean('Filters','median'):
stride = Parameters.getint('Filters','stride')
Filters.MedianFilter(tod, stride)
