def PRESTOsp(fil_file, dmlo, dmhi, base_name, snr_cut, mask_file, basename):
print "Running PRESTO with %f to %f DM range" % (lodm, hidm)
if mask_file:
cmd = "prepsubband %s -lodm %f -numdms %d -dmstep 1 -mask %s -o prepsubband" % (
fil_file, dmlo, dmhi - dmlo, mask_file)
else:
cmd = "prepsubband %s -lodm %f -numdms %d -dmstep 1 -o prepsubband" % (
fil_file, dmlo, dmhi - dmlo)
os.system(cmd)
#Run single pulse search on the .dat files
tbin = 0.4 # Seconds. Time window to compare candidates
nhits_max = 500
dm_min = dmlo
dm_max = dmhi
fullfile = '%s_full.txt' % basename
allfile = '%s_all.txt' % basename
tmp_file = '%s_FRBcand.txt' % basename
cmd = "single_pulse_search.py prepsubband*.dat"
os.system(cmd)
cmd = "cat prepsubband*.singlepulse > All_cand.singlepulse"
os.system(cmd)
cand_file = "All_cand.singlepulse"
sys.path.insert(0,
'/home/vgajjar/SP_search_wrapper/PulsarSearch/robert_sp/')
import sp_cand_find as sp
cands = sp.cands_from_file(cand_file, 0)
print("%d total candidates" % len(cands))
cands = sp.find_duplicates(cands, tbin, 1000.0)
sp.write_cands(fullfile, cands)
ndupes = np.array([dd.nhits for dd in cands])
yy = np.where((ndupes > 0) & (ndupes <= nhits_max))[0]
#print len(yy)
all_cands = [cands[ii] for ii in yy]
sp.write_cands(allfile, all_cands)
dms = np.array([dd.dm for dd in cands])
snrs = np.array([dd.sigma for dd in cands])
xx = np.where((ndupes > 0) & (ndupes <= nhits_max) & (dms >= dm_min)
& (dms <= dm_max) & (snrs >= snr_cut))[0]
gcands = [cands[ii] for ii in xx]
print("%d good candidates" % len(gcands))
if (len(gcands)):
sp.write_cands(tmp_file, gcands)
else:
print "Nothing to plot"
sp.make_nhits_plot(ndupes, nhits_max, basename)
return gcands
def PRESTOsp(fil_file, dmlo, dmhi, outdir, snr_cut, zerodm, mask_file,
base_name, nosearch):
print "Running PRESTO with %f to %f DM range" % (lodm, hidm)
#prepsubband can only take 500 DMs to dedisperse
dmr = int(500)
#DM Step
dmstep = 1
if not nosearch:
cmd = "rm *.dat prepsub*.inf *.singlepulse"
os.system(cmd)
if zerodm:
if mask_file:
cmd = "prepsubband %s -lodm 0 -numdms 1 -dmstep 1 -mask %s -o prepsubband" % (
fil_file, mask_file)
else:
cmd = "prepsubband %s -lodm 0 -numdms 1 -dmstep 1 -o prepsubband" % (
fil_file)
#if not nosearch: os.system(cmd)
os.system(cmd)
for d in range(int(dmlo), int(dmhi), dmr):
if (d + dmr > dmhi): dmhi1 = dmhi
else: dmhi1 = d + dmr
if (d > 1000): dmstep = dmstep + 1
if mask_file:
cmd = "prepsubband %s -lodm %f -numdms %d -dmstep %d -mask %s -o prepsubband" % (
fil_file, d, dmhi1 - d, dmstep, mask_file)
else:
cmd = "prepsubband %s -lodm %f -numdms %d -dmstep %d -o prepsubband" % (
fil_file, d, dmhi1 - d, dmstep)
if not nosearch: os.system(cmd)
#Run single pulse search on the .dat files
tint = 1 # Seconds. Time window to compare candidates
nhits_max = 12000
dm_min = 530
dm_max = 630
fullfile = '%s_orig_cand.txt' % base_name
allfile = '%s_clean_cand.txt' % base_name
tmp_file = '%s_FRBcand.txt' % base_name
cmd = "single_pulse_search.py -m 0.01 -b -t %f prepsubband*.dat" % (
snr_cut)
if not nosearch: os.system(cmd)
cmd = "cat prepsubband*.singlepulse > All_cand.singlepulse"
os.system(cmd)
cand_file = "All_cand.singlepulse"
sys.path.insert(0,
'/home/vgajjar/SP_search_wrapper/PulsarSearch/robert_sp/')
import sp_cand_find as sp
cands = sp.cands_from_file(cand_file, 0)
print("%d total candidates" % len(cands))
cands = sp.find_duplicates(cands, tint, 1000.0)
if (len(cands)):
if zerodm:
zdm = []
dupdms = np.array([dd.dupes_dms for dd in cands])
for i, d in enumerate(dupdms):
if (0.0 not in d): zdm.append(i)
cands = [cands[ii] for ii in zdm]
sp.write_cands(fullfile, cands)
ndupes = np.array([dd.nhits for dd in cands])
#print dupes
yy = np.where((ndupes > 0) & (ndupes <= nhits_max))[0]
#print len(yy)
all_cands = [cands[ii] for ii in yy]
if len(all_cands): sp.write_cands(allfile, all_cands)
dms = np.array([dd.dm for dd in cands])
snrs = np.array([dd.sigma for dd in cands])
xx = np.where((ndupes > 0) & (ndupes <= nhits_max) & (dms >= dm_min)
& (dms <= dm_max) & (snrs >= snr_cut))[0]
gcands = [cands[ii] for ii in xx]
print("%d good candidates" % len(gcands))
if (len(gcands)):
sp.write_cands(tmp_file, gcands)
sp.make_nhits_plot(ndupes, nhits_max, base_name)
else:
print "Nothing to plot"
else:
gcands = []
return gcands
