1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
|
from astroquery.alma import Alma
from astroquery.splatalogue import Splatalogue
from astroquery.simbad import Simbad
from astropy import units as u
from astropy import constants
from spectral_cube import SpectralCube
m83table = Alma.query_object('M83', public=True)
m83urls = Alma.stage_data(m83table['Member ous id'])
# Sometimes there can be duplicates: avoid them with
# list(set())
# also, to save time, we just download the first one
m83files = Alma.download_and_extract_files(list(set(m83urls['URL']))[0])
m83files = m83files
Simbad.add_votable_fields('rv_value')
m83simbad = Simbad.query_object('M83')
rvel = m83simbad['RV_VALUE'][0]*u.Unit(m83simbad['RV_VALUE'].unit)
for fn in m83files:
if 'line' in fn:
cube = SpectralCube.read(fn)
# Convert frequencies to their rest frequencies
frange = u.Quantity([cube.spectral_axis.min(),
cube.spectral_axis.max()]) * (1+rvel/constants.c)
# Query the top 20 most common species in the frequency range of the
# cube with an upper energy state <= 50K
lines = Splatalogue.query_lines(frange[0], frange[1], top20='top20',
energy_max=50, energy_type='eu_k',
only_NRAO_recommended=True)
lines.pprint()
# Change the cube coordinate system to be in velocity with respect
# to the rest frequency (in the M83 rest frame)
rest_frequency = lines['Freq-GHz'][0]*u.GHz / (1+rvel/constants.c)
vcube = cube.with_spectral_unit(u.km/u.s,
rest_value=rest_frequency,
velocity_convention='radio')
# Write the cube with the specified line name
fmt = "{Species}{Resolved QNs}"
row = lines[0]
linename = fmt.format(**dict(zip(row.colnames, row.data)))
vcube.write('M83_ALMA_{linename}.fits'.format(linename=linename))
|
