def refine_cand(candsfile,
candloc=[],
candnum=-1,
threshold=0,
scaledm=2.1,
scalepix=2,
scaleuv=1.0,
chans=[],
returndata=False):
""" Helper function to interact with merged cands file and refine analysis
candsfile is merged pkl file
candloc (scan, segment, candint, dmind, dtind, beamnum) is as above.
if no candloc, then it prints out cands above threshold.
"""
if candnum >= 0:
candlocs, candprops, d0 = pc.read_candidates(candsfile,
snrmin=threshold,
returnstate=True)
candloc = candlocs[candnum]
candprop = candprops[candnum]
logger.info('Refining cand {0} with features {1}'.format(
candloc, candprop))
values = rt.pipeline_refine(d0,
candloc,
scaledm=scaledm,
scalepix=scalepix,
scaleuv=scaleuv,
chans=chans,
returndata=returndata)
return values
elif candloc:
logger.info('Refining cand {0}'.format(candloc))
d0 = pickle.load(open(candsfile, 'r'))
values = rt.pipeline_refine(d0,
candloc,
scaledm=scaledm,
scalepix=scalepix,
scaleuv=scaleuv,
chans=chans,
returndata=returndata)
return d, cands
else:
return None
def refine_cand(candsfile, candloc=[], threshold=0):
""" Helper function to interact with merged cands file and refine analysis
candsfile is merged pkl file
candloc (scan, segment, candint, dmind, dtind, beamnum) is as above.
if no candloc, then it prints out cands above threshold.
"""
if not candloc:
plot_cand(candsfile, candloc=[], candnum=-1, threshold=threshold,
savefile=False, returndata=False)
else:
d = pickle.load(open(candsfile, 'r'))
cands = rt.pipeline_refine(d, candloc)
return cands
def refine_cand(candsfile, candloc=[], threshold=0):
""" Helper function to interact with merged cands file and refine analysis
candsfile is merged pkl file
candloc (scan, segment, candint, dmind, dtind, beamnum) is as above.
if no candloc, then it prints out cands above threshold.
"""
if not candloc:
plot_cand(candsfile,
candloc=[],
candnum=-1,
threshold=threshold,
savefile=False,
returndata=False)
else:
d = pickle.load(open(candsfile, 'r'))
cands = rt.pipeline_refine(d, candloc)
return cands