def test_fits_to_fil():
# from fits
file = os.path.join(_install_dir, "data/small.fits")
f = Your(file)
w = Writer(f,
nstart=0,
nsamp=1,
outname="temp",
outdir="./",
c_min=0,
c_max=200)
# test with outname
w.to_fil()
assert os.path.isfile("temp.fil")
y = Your("temp.fil")
assert y.your_header.nspectra == 1
assert y.your_header.nchans == 200
assert (y.get_data(0, 1) - f.get_data(0, 1)[:, 0:200]).sum() == 0
os.remove("temp.fil")
# test without outname
w = Writer(f, outdir="./")
w.to_fil()
assert os.path.isfile("small_converted.fil")
y = Your("small_converted.fil")
assert y.your_header.nspectra == f.your_header.nspectra
ns = y.your_header.nspectra
assert y.your_header.nchans == f.your_header.nchans
assert (y.get_data(0, ns) - f.get_data(0, ns)).sum() == 0
os.remove("small_converted.fil")
def test_fil_to_fits():
file = os.path.join(_install_dir, "data/small.fil")
f = Your(file)
w = Writer(
f,
outname="temp",
outdir="./",
flag_rfi=False,
zero_dm_subt=False,
nstart=1,
nsamp=2,
c_min=40,
c_max=200,
)
# test with outname
w.to_fits()
assert os.path.isfile("temp.fits")
y = Your("temp.fits")
assert y.your_header.nspectra == 2
assert y.your_header.nchans == 160
assert (y.get_data(0, 2) - f.get_data(1, 2)[:, 40:200]).sum() == 0
os.remove("temp.fits")
# test without outname
w = Writer(f, outdir="./", flag_rfi=True, zero_dm_subt=True)
w.to_fits()
assert os.path.isfile("small_converted.fits")
y = Your("small_converted.fits")
assert y.your_header.nchans == f.your_header.nchans
ns = y.your_header.nspectra
os.remove("small_converted.fits")
def test_gulps(your_object):
w = Writer(
your_object,
nstart=1,
nsamp=2,
gulp=2,
outname="temp",
c_min=10,
c_max=200,
outdir="./",
)
w.to_fil()
assert os.path.isfile("temp.fil")
w = Writer(
your_object,
nstart=1,
nsamp=5,
gulp=20,
outname="temp",
c_min=10,
c_max=200,
outdir="./",
)
w.to_fil()
assert os.path.isfile("temp.fil")
os.remove("temp.fil")
def test_fil_to_fil(your_object):
# from fil
w = Writer(
your_object,
nstart=1,
nsamp=2,
outname="temp",
c_min=10,
c_max=200,
outdir="./",
flag_rfi=False,
zero_dm_subt=False,
)
# test with outname
w.to_fil()
assert os.path.isfile("temp.fil")
y = Your("temp.fil")
assert y.your_header.nspectra == 2
assert y.your_header.nchans == 190
assert (y.get_data(0, 2) -
your_object.get_data(1, 2)[:, 10:200]).sum() == 0
os.remove("temp.fil")
# test without outname
w = Writer(your_object, nstart=0, nsamp=10, outdir="./", flag_rfi=True)
w.to_fil()
assert os.path.isfile("small_converted.fil")
y = Your("small_converted.fil")
assert y.your_header.nspectra == 10
assert y.your_header.nchans == your_object.your_header.nchans
os.remove("small_converted.fil")
def test_4pol_fits_to_fits():
file = os.path.join(_install_dir, "data/test_4pol.fits")
your_obj = Your(file)
w = Writer(your_obj,
nstart=1,
nsamp=20,
gulp=20,
outname="temp_4pol",
outdir="./",
npoln=4)
w.to_fits()
y = Your("temp_4pol.fits")
assert y.your_header.nspectra == 20
assert y.your_header.nchans == your_obj.your_header.nchans
assert (y.get_data(0, 5, npoln=4) -
your_obj.get_data(1, 5, npoln=4)).sum() == 0
os.remove("temp_4pol.fits")
def test_failing_replacement_policy(your_object):
with pytest.raises(ValueError):
w = Writer(
your_object,
outname="temp",
outdir="./",
flag_rfi=True,
zero_dm_subt=False,
replacement_policy="blah",
)
def test_frequency_decimatation(your_object):
with pytest.raises(NotImplementedError):
w = Writer(
your_object,
outname="temp",
outdir="./",
flag_rfi=False,
zero_dm_subt=False,
frequency_decimation_factor=2,
)
def test_pol(your_object):
w = Writer(
your_object,
outname="temp",
outdir="./",
flag_rfi=True,
zero_dm_subt=False,
npoln=1,
)
assert w.poln_order == "AA+BB"
with pytest.raises(ValueError):
w = Writer(
your_object,
outname="temp",
outdir="./",
flag_rfi=True,
zero_dm_subt=False,
npoln=3,
)
w.poln_order
def test_fil_to_fil():
# from fil
file = os.path.join(_install_dir, 'data/small.fil')
f = Your(file)
w = Writer(f)
# test with outname
w.to_fil(nstart=0,
nsamp=2,
outname='temp.fil',
c=[0, 200],
outdir='./',
flag_rfi=True,
zero_dm_subt=True)
assert os.path.isfile('temp.fil')
y = Your('temp.fil')
assert y.your_header.nspectra == 2
assert y.your_header.nchans == 200
os.remove('temp.fil')
# test without outname
w.to_fil(nstart=0, nsamp=1, outdir='./')
assert os.path.isfile('small_converted.fil')
y = Your('small_converted.fil')
assert y.your_header.nspectra == 1
assert y.your_header.nchans == f.your_header.nchans
os.remove('small_converted.fil')
def test_fits_to_fits():
file = os.path.join(_install_dir, 'data/small.fits')
f = Your(file)
w = Writer(f)
# test with outname
w.to_fits(outname='temp.fits', outdir='./', nstart=0, nsamp=2)
assert os.path.isfile('temp.fits')
y = Your('temp.fits')
assert y.your_header.nspectra == 2
assert y.your_header.nchans == f.your_header.nchans
os.remove('temp.fits')
# test without outname
w.to_fits(outdir='./', c=[0, 10])
assert os.path.isfile('small_converted.fits')
y = Your('small_converted.fits')
assert y.your_header.nchans == 10
os.remove('small_converted.fits')
if your_object.your_header.nspectra < 2**18:
nsamps_gulp = your_object.your_header.nspectra
else:
nsamps_gulp = int(
np.max([(2**np.ceil(np.log2(dispersion_delay_samples))), 2**18]))
if values.channel_end > 0:
c_max = values.channel_end
else:
c_max = None
your_dada_writer = Writer(
your_object=your_object,
progress=~values.no_progress,
c_min=values.channel_start,
c_max=c_max,
savgol_sigma=values.savgol_sigma,
spectral_kurtosis_sigma=values.spectral_kurtosis_sigma,
savgol_frequency_window=values.savgol_frequency_window,
flag_rfi=values.flag_rfi,
)
your_dada_writer.setup_dada(
) # need to run the set up inorder to get the dada key
if values.mask:
logging.info(f"Reading RFI mask from {values.mask}")
mask = np.loadtxt(values.mask)
if len(mask.shape) == 1:
bad_chans = list(mask)
else:
logging.warning(
"RFI mask not understood, can only be 1D. Not using RFI flagging."
'writer_%Y_%m_%d_%H_%M_%S_%f.log')
if values.verbose:
logging.basicConfig(filename=log_filename,
level=logging.DEBUG,
format=logging_format)
else:
logging.basicConfig(filename=log_filename,
level=logging.INFO,
format=logging_format)
logging.info("Input Arguments:-")
for arg, value in sorted(vars(values).items()):
logging.info("Argument %s: %r", arg, value)
y = Your(values.files)
w = Writer(y)
if values.type == 'fits':
w.to_fits(c=values.chans,
nstart=values.nstart,
nsamp=values.nsamp,
outdir=values.outdir,
outname=values.out_name,
progress=values.no_progress,
flag_rfi=values.flag_rfi,
sk_sig=values.sk_sig,
sg_fw=values.sg_fw,
sg_sig=values.sg_sig,
zero_dm_subt=values.zero_dm_subt)
elif values.type == 'fil':
w.to_fil(c=values.chans,
handlers=[RichHandler(rich_tracebacks=True)],
)
logging.info("Input Arguments:-")
for arg, value in sorted(vars(values).items()):
logging.info("Argument %s: %r", arg, value)
y = Your(values.files)
w = Writer(
y,
c_min=values.chans[0],
c_max=values.chans[1],
nstart=values.nstart,
nsamp=values.nsamp,
outdir=values.outdir,
outname=values.out_name,
progress=values.no_progress,
flag_rfi=values.flag_rfi,
spectral_kurtosis_sigma=values.spectral_kurtosis_sigma,
savgol_frequency_window=values.savgol_frequency_window,
savgol_sigma=values.savgol_sigma,
zero_dm_subt=values.zero_dm_subt,
time_decimation_factor=values.time_decimation_factor,
frequency_decimation_factor=values.frequency_decimation_factor,
)
if values.type == "fits":
w.to_fits()
elif values.type == "fil":
w.to_fil()
else:
raise ValueError("Type can either be 'fits' or 'fil'")
logging.info("Input Arguments:-")
for arg, value in sorted(vars(values).items()):
logging.info("Argument %s: %r", arg, value)
y = Your(values.files)
w = Writer(
y,
c_min=values.chans[0],
c_max=values.chans[1],
nstart=values.nstart,
nsamp=values.nsamp,
outdir=values.outdir,
outname=values.out_name,
progress=values.no_progress,
flag_rfi=values.flag_rfi,
spectral_kurtosis_sigma=values.spectral_kurtosis_sigma,
savgol_frequency_window=values.savgol_frequency_window,
savgol_sigma=values.savgol_sigma,
gulp=values.gulp_size,
zero_dm_subt=values.zero_dm_subt,
time_decimation_factor=values.time_decimation_factor,
frequency_decimation_factor=values.frequency_decimation_factor,
replacement_policy=values.replacement_policy,
npoln=values.num_polarisation,
highest_frequency_first=values.highest_frequency_first,
)
if values.type == "fits":
w.to_fits(npsub=values.npsub)
elif values.type == "fil":
w.to_fil()