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Computes the covariance between the time series of each of the WVR
channels with the specified channel-averaged spw, normalized by the
variance of the WVR channel. This is meant to explore the conditions in
which the WVR discrepancy is high to see if it is correlated with clouds.
wvrCorrelation(vis, spw=None, antenna=0, field=None, sigma=3, plotfile='', scaleAstronomicalReceiver=True,
pwv=None, normalizeToWVR3=False, buildpdf=False, verbose=False)
- spw: spw ID (integer or string), if None then use first science spw
- antenna: antenna ID or name or list. '' ==> all antennas
- sigma: threshold to clip outlier points in the astronomical receiver datastream
- pwv: the pwv (in mm) for the observation, in case ASDM_CALWVR is not present
- normalizeToWVR3: if True, normalize astronomical data to Tsky of WVR 3 if False, normalize to Tsky of the astronomical spw
- scaleAstronomicalSignal: if True, then magnify the black trace to occupy half the vertical scale (in order to better view small time variations)
- The maximum correlation value of the 4 WVR channels.
- If more than one antenna, then return the median of the antenna maxima.
CASA <11>: au.wvrCorrelation('uid___A002_X8358e4_X917.ms',spw=2,plotfile=True,antenna='PM04')
Working on antenna PM04 (1/1)
Scan 1,2,3,4,5,6,7,8,9,10,11,12,13 (field=0,1,2,3,4,5,6): azim = -17.04, elev = 59.86 (degrees)
Plot left in uid___A002_X8358e4_X917.ms.wvrCorrelation.PM04.spw02.png