def plotSensorSeeingPC (which):
days = seeing [which]
allDays = allSeeing [which]
siteRange = args.indirs [which]
yTicks = []
correlationsArray = []
for p in ambient.parameterBasenames [1:]:
otherDays = ambient.Days (os.path.join (siteRange.path, p + ".orig"), args.start_date, args.stop_date)
otherDays.setGoodness (allDays)
yTicks.append (p)
dayList = ambient.dayListFromRange (otherDays, siteRange.startDate, siteRange.stopDate)
correlations = ambient.goodCorrelate (days, dayList, args.min_points)
correlationsArray.append (correlations)
ambient.plotSensorSeeingPC (os.path.join (args.outdir, "pc-seeing+all-{}.pdf").format (siteRange.name),
correlationsArray, yTicks, days,
args.indirs [which].name)
leapYear = False
for i in range (2):
allSeeing.append (getSeeingDays (i))
if allSeeing [-1].isLeapYear ():
leapYear = True
for i in range (2):
dayList = ambient.dayListFromRange (allSeeing [i], args.indirs [i].startDate, args.indirs [i].stopDate, leapYear=leapYear)
seeing.append (dayList)
# 1e. calculate PC for each day. Sort from highest to lowest PC
#make a list of (day0, day1, pc)
#day0 is never None but day1 can be None whenever it's lacking a day that site0 has
#pc values > 1.0 mean nonsense, including not enough matching points
correlations = ambient.goodCorrelate (seeing [0], seeing [1], args.min_points)
#sort on pc
correlations = sorted (correlations, key=lambda x: x[2], reverse=not args.worst)
def writeCorr (out, c):
day0 = c [0]
day1 = c [1]
if not day0:
return
if not day1 or not day0.good:
out.write ("{:%m/%d/%y}\n".format (day0.datetime))
else:
out.write ("{:%m/%d/%y} {:%m/%d/%y} {:.5f} \
({} {}) ({} {}))\n".format (day0.datetime,
day1.datetime,
