# read the literature value of the period and the dispersion measure
period = pulsar.period
DM = pulsar.DM
# Time resolution of the telescope
dt = (512 * 64) / (70e6)
# Array with the bandwith
frequencyarray = obs.freq
# 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,
import numpy as np
from functools import lru_cache
obsfilelist = [
"./data/obs-10-04-2018/B0125+25-04-2018.fits",
"./data/obs-10-04-2018/B0329+54_10-04-2018.fits",
"./data/obs-10-04-2018/B1946+35_10-04-2018.fits",
"./data/obs-10-04-2018/B2111+46_10-04-2018.fits",
"./data/obs-10-04-2018/B2154+40_10-04-2018.fits",
"./data/obs-10-04-2018/B2217_10-04-2018.fits",
"./data/obs-10-04-2018/B2310+42-04-2018.fits"
]
print("loading data")
obs = Observation("./data/obs-10-04-2018/B2310+42-04-2018.fits.gz")
print("flagging")
obs.flag = flagData(obs.data)
time_fold_bins = 1000
freq_fold_bins = 100
@TaskGenerator
def chisq(period, DM):
folded = timeFolding(obs.data,
time_fold_bins,
period,
flagged=obs.flag,
corrected_times=obs.times)
dedispersed = dedispersion(folded,
obs,
period,