'Nhires': {
'bottomleft':
coordinates.SkyCoord("17:47:20.072",
"-28:22:22.0",
unit=(u.h, u.deg),
frame='icrs'),
'topright':
coordinates.SkyCoord("17:47:19.706",
"-28:22:15.6",
unit=(u.h, u.deg),
frame='icrs'),
'inregion':
'fullN',
'fitsfile':
paths.lbpath(
'sgr_b2m.N.B6.allspw.continuum.r0.5.clean1000.image.tt0.pbcor.fits'
),
'bbox': [-0.15, 0.95],
'loc':
2,
'l1':
1,
'l2':
4,
'min':
-1, # mJy
'max':
25,
'width':
2.5,
'height':
frame='fk5')
diskycoorddict[source] = diskycoords
diskycoorddict['e2'] = diskycoorddict['e2e']
for name, cutoutname, source, vrange in (
('lacy', 'northwest', lacy, (50,75)),
('north', 'north', north, (45,75)),
('e8', 'e8', e8, (45,75)),
('e2', 'e2', e2e, (45,70)),
):
diskycoords = diskycoorddict[name]
for fn in glob.glob(paths.lbpath("W51{0}cax*ALL_medsub_cutout.fits".format(cutoutname))):
print(fn)
try:
cube = SpectralCube.read(fn).with_spectral_unit(u.GHz)
except TypeError as ex:
print(ex)
continue
extraction_path = pvextractor.Path(diskycoords, 0.05*u.arcsec)
for line, restfreq, velocity_res, spw in line_to_image_list:
basename = line
frq = float(restfreq.strip('GHz')) * u.GHz
vmax_b=1.5,
vmax_r=1.5,
vmin_g=0.0001,
embed_avm_tags=True)
fig1.clf()
F = aplpy.FITSFigure(lacy_rgb_cube_png, figure=fig1)
F.recenter(lacy.ra.deg, lacy.dec.deg, radius=0.001)
F.show_rgb(lacy_rgb_cube_png)
F.add_scalebar((5000*u.au / (5400*u.pc)).to(u.deg,u.dimensionless_angles()))
F.scalebar.set_label('5000 au / 0.025 pc')
F.scalebar.set_color('w')
F.save(paths.fpath("outflows/rgb_SO_continuum_outflows_aplpy_wideLacy.png"))
F.recenter(lacy.ra.deg, lacy.dec.deg, radius=0.0005)
F.save(paths.fpath("outflows/rgb_SO_continuum_outflows_aplpy_zoomLacy.png"))
F.show_contour(paths.lbpath('W51ncax.cont.image.pbcor.fits'), levels=[0.001,
0.0020,
0.004,
0.008,
0.012],
colors=['w']*6, layer='alma_cont_cycle3hires')
F.recenter(lacy.ra.deg, lacy.dec.deg, radius=0.0005)
F.save(paths.fpath("outflows/rgb_SO_continuum_outflows_aplpy_zoomLacy_cycle3hires.png"))
F.save(paths.fpath("outflows/rgb_SO_continuum_outflows_aplpy_zoomLacy_cycle3hires.pdf"))
red_fits_cutout_lacy_fn = paths.dpath('12m/moments/LacyJet_12CO2m1_red70_95.fits')
blue_fits_cutout_lacy_fn = paths.dpath('12m/moments/LacyJet_12CO2m1_blue30_50.fits')
'radius': 0.10*u.arcsec,
'filename': 'W51n_cont_uniform.image.tt0.pbcor.fits'},
'e2e': {'center': coordinates.SkyCoord('19:23:43.969', '14:30:34.525', unit=(u.hour, u.deg), frame='fk5'),
'radius': 0.25*u.arcsec,
'filename': 'W51e2_cont_uniform.image.tt0.pbcor.fits'},
'e8': {'center': coordinates.SkyCoord('19:23:43.906', '14:30:28.269', unit=(u.hour, u.deg), frame='fk5'),
'radius': 0.16*u.arcsec,
'filename': 'W51e2_cont_uniform.image.tt0.pbcor.fits'},
}
for key in objects:
obj = objects[key]
objects[key]['aperture'] = regions.CircleSkyRegion(center=obj['center'],
radius=obj['radius'])
for objname in objects:
obj = objects[objname]
fh = fits.open(paths.lbpath(obj['filename']))[0]
datawcs = wcs.WCS(fh.header)
data = fh.data
beam = radio_beam.Beam.from_fits_header(fh.header)
pixreg = obj['aperture'].to_pixel(datawcs)
mask = pixreg.to_mask()
cutout = mask.cutout(data) * mask.data
pkflux = cutout.max() * u.Unit(fh.header['BUNIT'])
#pkbright = pkflux.to(u.K, beam.jtok_equiv(fh.header['CRVAL3']*u.Unit(fh.header['CUNIT3'])))
pkbright = pkflux.to(u.K, beam.jtok_equiv(225*u.GHz))
print("%{2:10s} Peak flux: {0:8.2f} Peak brightness: {1:8.1f} Beam major: {3:0.3f}"
.format(pkflux.to(u.mJy/u.beam), pkbright, objname, beam.major.to(u.arcsec)))