def chisq(period, DM):
folded = timeFolding(obs.data,
time_fold_bins,
period,
flagged=obs.flag,
corrected_times=obs.times)
dedispersed = dedispersion(folded,
obs,
period,
DM,
freq_fold_bins=freq_fold_bins)
chisq = ((dedispersed - dedispersed.mean())**2).sum()
return chisq
# this part should be RFI flagging something like:
# noflag = flagging(twodarray)
print("Flagging bad data")
flag = obs.data == 0 if args.skiprfi else flagData(twodarray)
obs.flag = flag
print("Folding")
# calculate the folded array
foldedarray = timeFolding(twodarray,
args.nbins,
period,
flagged=flag,
corrected_times=obs.times)
# make a waterfall plot of the result
waterfall(foldedarray)
print("Dedispersing")
# do the dedispersion
pulse_profile = dedispersion(foldedarray,
obs,
period,
obs.pulsar.DM,
freq_fold_bins=args.nbinsdedisp)
# plot the final pulse profile
plt.plot(pulse_profile)
plt.show()
corrected_times=obs.times)
foldedarray60 = timeFolding(twodarray60,
args.nbins,
period,
corrected_times=obs.times)
foldedarray = timeFolding(twodarray,
args.nbins,
period,
corrected_times=obs.times)
#show the rainfall plot and allow for fiddling with the DM
DM = 8.5
print(DM)
waterfall(dedispersion(foldedarray, DM, frequencyarray))
if DMplay:
DM2 = DM
while True:
disp = foldedarray[:]
DM1 = input("Input new DM:")
if DM1 == "":
DM = float(DM2)
break
waterfall(dedispersion(disp, float(DM1), frequencyarray))
DM2 = float(DM1)
fin10 = pulseProfile(foldedarray10, DM, frequencyarray)
fin30 = pulseProfile(foldedarray30, DM, frequencyarray)
fin60 = pulseProfile(foldedarray60, DM, frequencyarray)