def fb_avg(fname, tgoal=1000, fgoal=128, fscr=None):
""" Downsample a filterbank file to appropriate resolution for plotting.
"""
fr = FilReader(fname)
if fscr is None:
fscr = int(fr.header['nchans'] / fgoal)
tscr = 2**int(np.log2(fr.header['nsamples'] / tgoal))
gulp = tscr
nchan = fr.header['nchans']
nblock = fr.header['nsamples'] / tscr
nsub = nchan / fscr
output = np.empty((nsub, nblock))
for nsamps, i, data in fr.readPlan(gulp, verbose=False):
if nsamps != gulp:
#print 'breaking at %d'%i
break
t = data.reshape(
(gulp, nchan)).transpose().astype(np.float32).mean(axis=1)
output[:, i] = np.average(t.reshape(nchan / fscr, fscr), axis=1)
freqs = np.arange(
fr.header['nchans']) * fr.header['foff'] + fr.header['fch1']
freqs = freqs.reshape(len(freqs) / fscr, fscr).mean(axis=1)
times = np.arange(nblock) * fr.header['tsamp'] * gulp
return output, freqs, times
def fil_splitter(fil_fns, outfn, nsub, tqdm_desc=None, verbose=True):
"""
Split filterbank data to different subband files
"""
start_time = timeit.default_timer()
if isinstance(fil_fns, str):
fil_fns = [fil_fns]
if len(fil_fns) > 1:
raise TypeError(f'Input files: "{len(fil_fns)}". Not supported yet!.')
if nsub == 1:
raise TypeError(f'Nsub: {nsub}. No need for conversion!.')
myFil = FilReader(fil_fns[0])
out_files = []
hdr_changes = {}
chanpersub = myFil.header.nchans // nsub
for isub in range(nsub):
hdr_changes["nchans"] = chanpersub
hdr_changes[
"fch1"] = myFil.header.fch1 + isub * chanpersub * myFil.header.foff
outfil = f'{outfn.split(".fil")[0]}_sub{str(isub).zfill(2)}.fil'
out_files.append(
myFil.header.prepOutfile(outfil,
hdr_changes,
nbits=myFil.header.nbits))
if verbose:
print("Splitting Filterbank:")
print("---------------------------------")
gulpsize = 32768
for nsamps, ii, data in tqdm(myFil.readPlan(gulp=gulpsize, verbose=False),
total=np.ceil(myFil.header.nsamples /
gulpsize).astype('int'),
desc=tqdm_desc):
for isub, out_file in enumerate(out_files):
data = data.reshape(nsamps, myFil.header.nchans)
subint_tofil = data[:, chanpersub * isub:chanpersub * (isub + 1)]
out_file.cwrite(subint_tofil.ravel())
# Now close each of the filterbank file.
for out_file in out_files:
out_file.close()
end_time = timeit.default_timer()
if verbose:
print(f'Done')
print(f'Execution time: {(end_time-start_time):.3f} seconds\n')
def fb_avg(fname,tbingoal=1000,fgoal=128,fscr=None,last_minute=False):
""" Downsample a filterbank file to appropriate resolution for plotting.
"""
fr = FilReader(fname)
if fscr is None:
fscr = int(fr.header['nchans']/fgoal)
nsamp = fr.header['nsamples']
if (nsamp*fr.header['tsamp']) < 60:
last_minute = False
if last_minute:
nsamp = int(60./fr.header['tsamp'])+1
try:
tscr = 2**int(np.log2(nsamp/tbingoal))
except OverflowError:
tscr = 1
gulp = tscr
nchan = fr.header['nchans']
nblock = nsamp/tscr
nsub = nchan/fscr
output = np.empty( (nsub, nblock) )
start = 0
if last_minute:
start = max(0,int(fr.header['nsamples']-nsamp)-1)
for nsamps,i,data in fr.readPlan(gulp,start=start,verbose=False):
if nsamps != gulp:
#print 'breaking at %d'%i
break
t = data.reshape((gulp,nchan)).transpose().astype(np.float32).mean(axis=1)
output[:,i] = np.average(t.reshape(nchan/fscr,fscr),axis=1)
freqs = np.arange(fr.header['nchans'])*fr.header['foff']+fr.header['fch1']
freqs = freqs.reshape(len(freqs)/fscr,fscr).mean(axis=1)
times = (start + np.arange(nblock)*gulp)*fr.header['tsamp']
return output,freqs,times
