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qc.py
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qc.py
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import numpy as np;
from astropy.io import fits as pyfits;
from . import log, headers, setup;
from .headers import HM, HMQ, HMP, HMW, rep_nan;
def flux (hdr, y0, photo):
'''
Add QC to hdr about flux
'''
log.info ('Compute QC for xchan flux');
for t in range(6):
val = np.mean (photo[:,:,y0,t], axis=(0,1));
hdr[HMQ+'FLUX%i MEAN'%t] = (val,'[adu/frame/channel] at lbd0');
val = np.sum (np.mean (photo[:,:,:,t], axis=(0,1)));
hdr[HMQ+'BANDFLUX%i MEAN'%t] = (val,'[adu/frame] in band');
def snr (hdr, y0, base_snr0, base_snr):
'''
Add QC to hdr about snr.
'''
log.info ('Compute QC for SNR');
for b,name in enumerate (setup.base_name ()):
val = rep_nan (np.mean (base_snr0[:,:,:,b]));
hdr[HMQ+'SNR'+name+' MEAN'] = (val,'Broad-band SNR');
val = rep_nan (np.mean (base_snr[:,:,:,b]));
hdr[HMQ+'SNRB'+name+' MEAN'] = (val,'Broad-band bootstrapped SNR');
def power (hdr, y0, base_power, bias_power, norm_power):
'''
Add QC to hdr about snr.
'''
# QC for power
log.info ('Compute QC for power');
for b,name in enumerate (setup.base_name ()):
val = rep_nan (np.mean (norm_power[:,:,y0,b], axis=(0,1)));
hdr[HMQ+'NORM'+name+' MEAN'] = (val,'Norm Power at lbd0');
val = rep_nan (np.mean (base_power[:,:,y0,b], axis=(0,1)));
hdr[HMQ+'POWER'+name+' MEAN'] = (val,'Fringe Power at lbd0');
val = rep_nan (np.std (base_power[:,:,y0,b], axis=(0,1)));
hdr[HMQ+'POWER'+name+' STD'] = (val,'Fringe Power at lbd0');
# QC for bias
log.info ('Compute QC for bias');
qc_power = np.mean (bias_power[:,:,y0,:], axis=(0,1));
hdr[HMQ+'BIASMEAN MEAN'] = (np.mean (qc_power),'Bias Power at lbd0');
hdr[HMQ+'BIASMEAN STD'] = (np.std (qc_power),'Bias Power at lbd0');
hdr[HMQ+'BIASMEAN MED'] = (np.median (qc_power),'Bias Power at lbd0');