def test_flex_shift():
# Dummy slf
# Read spectra
obj_spec = readspec(data_path('obj_lrisb_600_sky.fits'))
arx_file = os.path.join(data.Paths.sky_spec, 'sky_LRISb_600.fits')
arx_spec = readspec(arx_file)
arx_lines = arc.detect_lines(arx_spec.flux.value)
# Call
flex_dict = flexure.spec_flex_shift(obj_spec,
arx_spec,
arx_lines,
mxshft=60)
# # Apply
# from scipy import interpolate
# print(flex_dict['shift'])
# npix = len(obj_spec.wavelength)
# x = np.linspace(0., 1., npix)
# f = interpolate.interp1d(x, obj_spec.wavelength.value, bounds_error=False,
# fill_value="extrapolate")
# new_wave = f(x+flex_dict['shift']/(npix-1))
#
# from matplotlib import pyplot
# pyplot.plot(arx_spec.wavelength, arx_spec.flux)
# pyplot.plot(obj_spec.wavelength, obj_spec.flux)
# pyplot.plot(new_wave, obj_spec.flux)
# pyplot.show()
assert np.abs(flex_dict['shift'] - 43.7) < 0.1
def plot_spec_and_models(spec_filename, models_filenames='all'):
"""Plots several models in on top of a single spectrum.
Parameters
----------
"""
if models_filenames == 'all':
models = glob.glob("*_inspect.fits")
else:
models = models_filenames
spec = readspec(spec_filename)
models_specs = [readspec(model) for model in models]
plt.figure()
if spec.co_is_set:
spec.normalize(co=spec.co)
plt.plot(spec.wavelength, spec.flux, 'k', drawstyle='steps-mid')
plt.plot(spec.wavelength, spec.sig, 'g', drawstyle='steps-mid')
for model_s in models_specs:
plt.plot(model_s.wavelength,
model_s.flux,
label=model_s.filename.split('_inspect')[0])
plt.legend(ncol=5)
plt.ylim(-0.2, 2.1)
def test_read_table():
t = Table([(1, 2, 3), (1, 2, 3), (1, 2, 3)], names=['WAVE', 'FLUX', 'ERR'])
spec = io.readspec(t)
np.testing.assert_allclose(spec.wavelength[0].value, 1)
np.testing.assert_allclose(spec.flux[0], 1)
# Read table with non standard tags
t = Table([(1, 2, 3), (1, 2, 3), (1, 2, 3)],
names=['dumb_wave', 'dumb_flux', 'dumb_sig'])
spec = io.readspec(t,
wave_tag='dumb_wave',
flux_tag='dumb_flux',
sig_tag='dumb_sig')
np.testing.assert_allclose(spec.wavelength[0].value, 1)
np.testing.assert_allclose(spec.flux[0], 1)
# More..
t = Table([(1, 2, 3), (1, 2, 3), (1, 2, 3)],
names=['dumb_wave', 'dumb_flux', 'dumb_ivar'])
spec = io.readspec(t,
wave_tag='dumb_wave',
flux_tag='dumb_flux',
ivar_tag='dumb_ivar')
t = Table([(1, 2, 3), (1, 2, 3), (1, 2, 3)],
names=['dumb_wave', 'dumb_flux', 'dumb_var'])
spec = io.readspec(t,
wave_tag='dumb_wave',
flux_tag='dumb_flux',
var_tag='dumb_var')
def test_write_fits():
spec = io.readspec(data_path('UM184_nF.fits'))
# Write. Should be replaced with tempfile.TemporaryFile
spec.write_to_fits(data_path('tmp.fits'))
spec2 = io.readspec(data_path('tmp.fits'))
# check a round trip works
np.testing.assert_allclose(spec.dispersion, spec2.dispersion)
def abslines_from_VPfile(parfile,specfile=None,ra=None,dec=None):
'''
Takes a joebvp parameter file and builds a list of linetools AbsLines from the measurements therein.
Parameters
----------
parfile : str
Name of the parameter file in the joebvp format
ra : float, optional
Right Ascension of the QSO in decimal degrees
dec : float, optional
Declination of the QSO in decimal degress
Returns
-------
abslinelist: list
List of AbsLine objects
'''
from linetools.spectralline import AbsLine
from linetools.lists.linelist import LineList
import astropy.units as u
llist = LineList('ISM')
if specfile!=None:
spec=readspec(specfile) # Allow spectrum file to be declared in call
linetab = ascii.read(parfile) # Read parameters from file
linetab['restwave']=linetab['restwave']*u.AA
abslinelist = [] # Initiate list to populate
for i,row in enumerate(linetab):
### Check to see if errors for this line are defined
colerr,berr,velerr=get_errors(linetab,i)
### Adjust velocity limits according to centroid errors and limits from file
vcentmin = row['vel']-velerr
vcentmax = row['vel']+velerr
v1 = vcentmin + row['vlim1']
v2 = vcentmax + row['vlim2']
line=AbsLine(row['restwave']*u.AA, z=row['zsys'],closest=True, linelist=llist)
vlims=[v1,v2]*u.km/u.s
line.limits.set(vlims)
### Set other parameters
line.attrib['logN'] = row['col']
line.attrib['sig_logN'] = colerr
line.attrib['b'] = row['bval'] * u.km/u.s
line.attrib['sig_b'] = berr * u.km/u.s
line.attrib['vel'] = row['vel'] * u.km/u.s
### Attach the spectrum to this AbsLine but check first to see if this one is same as previous
if specfile==None:
if i==0:
spec=readspec(row['specfile'])
elif row['specfile']!=linetab['specfile'][i-1]:
spec=readspec(row['specfile'])
else:
pass
line.analy['spec']=spec
### Add it to the list and go on
abslinelist.append(line)
return abslinelist
def main(*args, **kwargs):
""" Runs the XSpecGui on an input file
"""
import argparse
parser = argparse.ArgumentParser(description='Parse')
parser.add_argument("file", type=str, help="Spectral file")
parser.add_argument("skyfile",
type=str,
help="Archived PYPIT sky file (e.g. paranal_sky.fits")
parser.add_argument("--exten", type=int, help="FITS extension")
parser.add_argument("--optimal",
default=False,
help="Show Optimal? Default is boxcar",
action="store_true")
parser.add_argument("--scale_user",
default=1.,
type=float,
help="Scale user spectrum by a factor")
pargs = parser.parse_args()
from matplotlib import pyplot as plt
# Extension
exten = (pargs.exten if hasattr(pargs, 'exten') else 0)
#scale = (pargs.scale_user if hasattr(pargs, 'scale_user') else 1.)
# Read spec keywords
ikwargs = {}
if pargs.optimal:
ikwargs['wave_tag'] = 'opt_wave'
ikwargs['flux_tag'] = 'opt_sky'
else:
ikwargs['wave_tag'] = 'box_wave'
ikwargs['flux_tag'] = 'box_sky'
# Load user file
user_sky = readspec(pargs.file, exten=exten, **ikwargs)
# Load sky spec
arx_sky = readspec(sky_path + pargs.skyfile)
# Plot
plt.clf()
plt.plot(user_sky.wavelength,
user_sky.flux * pargs.scale_user,
'k-',
label='user')
plt.plot(arx_sky.wavelength, arx_sky.flux, 'b-', label='archive')
legend = plt.legend(loc='upper left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='small',
numpoints=1)
plt.show()
def test_write_fits(spec, spec2):
# Write. Should be replaced with tempfile.TemporaryFile
spec.write_to_fits(data_path("tmp.fits"))
specin = io.readspec(data_path("tmp.fits"))
# check a round trip works
np.testing.assert_allclose(spec.dispersion, specin.dispersion)
# ESI
spec2.write_to_fits(data_path("tmp2.fits"))
specin2 = io.readspec(data_path("tmp2.fits"))
# check a round trip works
np.testing.assert_allclose(spec2.dispersion, specin2.dispersion)
def test_write_fits(spec, spec2):
# Write. Should be replaced with tempfile.TemporaryFile
spec.write_to_fits(data_path('tmp.fits'))
specin = io.readspec(data_path('tmp.fits'))
# check a round trip works
np.testing.assert_allclose(spec.wavelength, specin.wavelength)
# ESI
spec2.write_to_fits(data_path('tmp2.fits'))
specin2 = io.readspec(data_path('tmp2.fits'))
# check a round trip works
np.testing.assert_allclose(spec2.wavelength, specin2.wavelength)
def test_readwrite_metadata():
spec = io.readspec(data_path('UM184_nF.fits'))
d = {'a':1, 'b':'abc', 'c':3.2, 'd':np.array([1,2,3]),
'e':dict(a=1,b=2)}
spec.meta.update(d)
spec.write_to_fits(data_path('tmp.fits'))
spec2 = io.readspec(data_path('tmp.fits'))
assert spec2.meta['a'] == d['a']
assert spec2.meta['b'] == d['b']
np.testing.assert_allclose(spec2.meta['c'], d['c'])
np.testing.assert_allclose(spec2.meta['d'], d['d'])
assert spec2.meta['e'] == d['e']
def test_readwrite_meta_as_dicts(spec):
sp = XSpectrum1D.from_tuple((np.array([5,6,7]), np.ones(3), np.ones(3)*0.1))
sp.meta['headers'][0] = dict(a=1, b='abc')
sp2 = XSpectrum1D.from_tuple((np.array([8,9,10]), np.ones(3), np.ones(3)*0.1))
sp2.meta['headers'][0] = dict(c=2, d='efg')
spec = ltsu.collate([sp,sp2])
# Write
spec.write_to_fits(data_path('tmp.fits'))
spec.write_to_hdf5(data_path('tmp.hdf5'))
# Read and test
newspec = io.readspec(data_path('tmp.hdf5'))
assert newspec.meta['headers'][0]['a'] == 1
assert newspec.meta['headers'][0]['b'] == 'abc'
newspec2 = io.readspec(data_path('tmp.fits'))
assert 'METADATA' in newspec2.meta['headers'][0].keys()
def test_hdf5(specm):
import h5py
# Write. Should be replaced with tempfile.TemporaryFile
specm.write_to_hdf5(data_path('tmp.hdf5'))
#
specread = io.readspec(data_path('tmp.hdf5'))
# check a round trip works
np.testing.assert_allclose(specm.wavelength, specread.wavelength)
# Add to existing file
tmp2 = h5py.File(data_path('tmp2.hdf5'), 'w')
foo = tmp2.create_group('boxcar')
specm.add_to_hdf5(tmp2, path='/boxcar/')
tmp2.close()
# check a round trip works
spec3 = io.readspec(data_path('tmp2.hdf5'), path='/boxcar/')
np.testing.assert_allclose(specm.wavelength, spec3.wavelength)
def spec_plot(spec_fil,
ID_path=None,
ambig_fil=None,
dwv=25.,
outfil='tmp.pdf'):
mpl.rcParams['font.family'] = 'stixgeneral'
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.gridspec as gridspec
'''
spec_fil: string
Filename of spectrum
outfil: string ('tmp.pdf')
Filename for output
dwv: float (25.)
Ang per window
'''
npx = 1
npy = 4
# Read spectrum
spec = lsio.readspec(spec_file)
# Start plot
pp = PdfPages(outfil)
def test_flex_shift():
if not os.getenv('PYPIT'):
pass
else:
# Dummy slf
arut.dummy_settings()
settings.argflag['reduce']['flexure']['maxshift'] = 50
slf = arut.dummy_self()
# Read spectra
obj_spec = lsio.readspec(data_path('obj_lrisb_600_sky.fits'))
arx_file = pypit.__path__[0]+'/data/sky_spec/sky_LRISb_600.fits'
arx_spec = lsio.readspec(arx_file)
# Call
#msgs._debug['flexure'] = True
flex_dict = arwave.flex_shift(slf, 1, obj_spec, arx_spec)
assert np.abs(flex_dict['shift'] - 43.7) < 0.1
def coadd_cos_from_x1dfiles(filenames, wv_array=None, A_pix=0.01 * u.AA):
spec_list = []
#TODO: mask out x1d spectral regions with bad values.
for filename in filenames:
sp = readspec(filename)
import pdb
pdb.set_trace()
# mask =
spec_list += [sp]
# spec_list contains all individual spectra
specs = collate(spec_list) # now all in a single XSpectrum1D object
#rebin
if wv_array is None:
# bring them to a unique native wavelength grid using PYPIT
A_pix = A_pix.to("AA").value
cat_wave = arco.new_wave_grid(specs.data['wave'],
wave_method='pixel',
A_pix=A_pix)
else:
cat_wave = wv_array.to('AA').value
specs = specs.rebin(cat_wave * u.AA,
all=True,
do_sig=True,
masking='none',
grow_bad_sig=True)
# estimate weights for coaddition (PYPYT)
sn2, weights = arco.sn_weight(specs)
# coaddition
spec1d = arco.one_d_coadd(specs, weights)
return spec1d
def model_profile(spec,
fitpars,
instr=None,
gratings=None,
lsfranges=None,
cen_wave=None,
lps=None,
slits=None):
'''Produce Voigt profile model from parameters and instrumental setup for
convolving proper line spread function. Note
Parameters
----------
spec : string or XSpectrum1D
The spectrum to be fitted with the input lines
fitpars : list of lists
The joebvp parameter array that includes line measurements
instr : list of str, optional
Instruments used to observe the spectral regions defined in lsfranges
gratings : list of str, optional
Gratings used for each spectral region defined in lsfranges
lsfranges : array of size len(instr)x2
Beginning and ending wavelengths of spectral ranges for each setup
cen_wave : list of str, optional
Central wavelength setting for each spectral region defined in lsfranges
lps : list of str, optional
Lifetime positions of detector (particularly for COS)
slits : list of str, optional
Slit setting for each spectral region defined in lsfranges
Returns
-------
wavelength : Quantity
Wavelength array from spec
profile : array
Voigt profile model
'''
### Setup LSF parameters if provided
if instr is not None:
cfg.instr = instr
cfg.lsfranges = lsfranges
cfg.gratings = gratings
cfg.cen_wave = cen_wave
cfg.lps = lps
cfg.slits = slits
### Deal with alternate input types
if isinstance(spec, str):
specobj = readspec(spec)
else:
specobj = spec
makevoigt.get_lsfs()
#import pdb; pdb.set_trace()
cfg.wave = specobj.wavelength.value
cfg.spectrum = specobj
profile = makevoigt.cosvoigt(cfg.wave, fitpars)
return specobj.wavelength, profile
def test_sep_files():
spec = io.readspec(data_path('UM184_nF.fits'))
idl = ascii.read(data_path('UM184.dat.gz'), names=['wave', 'flux', 'sig'])
np.testing.assert_allclose(spec.wavelength.value, idl['wave'])
np.testing.assert_allclose(spec.sig, idl['sig'], atol=2e-3, rtol=0)
assert spec.wavelength.unit == u.Unit('AA')
def test_attrib():
spec = io.readspec(data_path('UM184_nF.fits'))
#
np.testing.assert_allclose(spec.wvmin.value, 3056.6673905210096)
np.testing.assert_allclose(spec.wvmax.value, 9205.255609841855)
#assert spec.npix == 15024 -- With masking on
assert spec.npix == 16582
def test_write_ascii(spec):
# Write. Should be replaced with tempfile.TemporaryFile
spec.write_to_ascii(data_path('tmp.ascii'))
#
specb = io.readspec(data_path('tmp.ascii'))
# check a round trip works
np.testing.assert_allclose(spec.wavelength, specb.wavelength)
def test_attrib():
spec = io.readspec(data_path('UM184_nF.fits'))
#
np.testing.assert_allclose(spec.wvmin.value, 3056.6673905210096)
np.testing.assert_allclose(spec.wvmax.value, 9205.255609841855)
#assert spec.npix == 15024 -- With masking on
assert spec.npix == 16582
def test_write_ascii(spec):
# Write. Should be replaced with tempfile.TemporaryFile
spec.write_to_ascii(data_path("tmp.ascii"))
#
spec2 = io.readspec(data_path("tmp.ascii"))
# check a round trip works
np.testing.assert_allclose(spec.dispersion, spec2.dispersion)
def test_aodm_absline():
# Init CIV 1548
abslin = AbsLine('CIV 1548', z=2.9304)
# Set spectrum
abslin.analy['spec'] = lsio.readspec(
data_path('UM184_nF.fits')) # Fumagalli+13 MagE spectrum
abslin.limits.set([6080.78, 6087.82] * u.AA)
#abslin.analy['wvlim'] = [6080.78, 6087.82]*u.AA
#
abslin.measure_aodm()
N, sig_N, flgN = [abslin.attrib[key] for key in ['N', 'sig_N', 'flag_N']]
np.testing.assert_allclose(N.value, 76369981945649.38)
assert N.unit == 1 / u.cm**2
assert flgN == 1
# Now velocity limits
abslin.setz(2.92929)
abslin.limits.set((-150., 150.) * u.km / u.s)
#
abslin.measure_aodm()
N, sig_N, flgN = [abslin.attrib[key] for key in ['N', 'sig_N', 'flag_N']]
np.testing.assert_allclose(N.value, 80410608889125.64)
return
def compare_s2n(pp,lrdx_sciobj,pypit_boxfile, iso):
'''Compare boxcar S/N
'''
# Read/Load
pypit_boxspec = lsio.readspec(pypit_boxfile)
# Read LowRedux
sig = np.sqrt(lrdx_sciobj['MASK_BOX']/(lrdx_sciobj['SIVAR_BOX'] + (lrdx_sciobj['MASK_BOX']==0)))
lwrdx_boxspec = XSpectrum1D.from_tuple( (lrdx_sciobj['WAVE_BOX'], lrdx_sciobj['FLUX_BOX'], sig) )
# Plot
plt.clf()
fig = plt.figure(figsize=(16,7))
fig.suptitle("Instr={:s}, Setup={:s} :: Boxcar S/N for {:s} :: PYPIT ({:s})".format(iso[0], iso[1], iso[2], pypit.version), fontsize=18.)
ax = plt.gca()
ymax = np.median(pypit_boxspec.flux)*2.
# PYPIT
gdpy = pypit_boxspec.sig > 0.
pys2n = pypit_boxspec.flux[gdpy]/pypit_boxspec.sig[gdpy]
ax.plot(pypit_boxspec.dispersion[gdpy],pys2n, 'k-', drawstyle='steps', label='PYPIT')
# LowRedux
gdlx = lwrdx_boxspec.sig > 0.
ax.plot(lwrdx_boxspec.dispersion[gdlx], lwrdx_boxspec.flux[gdlx]/lwrdx_boxspec.sig[gdlx],
'-', color='blue', label='LowRedux')
# Axes
ax.set_xlim(np.min(pypit_boxspec.dispersion.value), np.max(pypit_boxspec.dispersion.value))
ax.set_ylim(0.,np.median(pys2n)*2.)
ax.set_xlabel('Wavelength',fontsize=17.)
ax.set_ylabel('S/N per pixel',fontsize=17.)
# Legend
legend = plt.legend(loc='upper right', borderpad=0.3,
handletextpad=0.3, fontsize='x-large')
# Finish
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1,rect=[0, 0.03, 1, 0.95])
pp.savefig(bbox_inches='tight')
plt.close()
def init_conti_full(self):
print("Initializing the continuum")
spec = self.spec_widg.orig_spec
spec.select = self.model_spec # Just in case, but this should already be the case
# Full Model (LLS+continuum)
self.full_model = XSpectrum1D.from_tuple(
(spec.wavelength, np.ones(len(spec.wavelength))))
self.conti_dict = pycc.init_conti_dict(
Norm=float(np.median(spec.flux.value)),
piv_wv=1215. * (1 + self.zqso),
#piv_wv2=915.*(1+zqso),
igm='True')
# Read Telfer and apply IGM
if self.template is not None:
tspec = lsi.readspec(self.template)
# assume wavelengths
tspec = XSpectrum1D.from_tuple(
(tspec.wavelength.value * (1 + self.zqso), tspec.flux.value))
else:
tspec = pycq.get_telfer_spec(
zqso=self.zqso, igm=(self.conti_dict['igm'] == 'True'))
# Rebin
self.continuum = tspec.rebin(spec.wavelength)
# Reset pivot wave
self.conti_dict['piv_wv'] = 915. * (1 + self.zqso)
#self.conti_dict['piv_wv'] = 1215.*(1+zqso)
#self.conti_dict['piv_wv2'] = 915.*(1+zqso)
self.base_continuum = self.continuum.flux
self.update_conti()
self.spec_widg.continuum = self.continuum
def test_hi_lya():
# Simple system (without an absline)
dla1 = DLASystem.from_json(
data_path('J010311.38+131616.7_z2.309_ESI.json'))
dla1.zabs = 4.
dla1.NHI = 21.
dla2 = DLASystem.from_json(
data_path('J010311.38+131616.7_z2.309_ESI.json'))
dla2.zabs = 3.5
dla2.NHI = 20.5
spec_fil = linetools.__path__[0] + '/spectra/tests/files/PH957_f.fits'
spec = lsio.readspec(spec_fil)
# Just lya
model, lya_lines = pyasu.hi_model([dla1, dla2], spec, lya_only=True)
ipx = np.argmin(np.abs(spec.wavelength.value - (1 + dla1.zabs) * 1215.67))
assert model.flux[ipx].value < 1e-4
ipx2 = np.argmin(
np.abs(spec.wavelength.value - (1 + dla1.zabs) * 1025.7222))
assert model.flux[ipx2].value > 0.99
# Lyman series
model2, lyman_lines = pyasu.hi_model([dla1, dla2], spec)
assert len(lyman_lines) > 10
assert model2.flux[ipx2].value < 1e-4
# LLS
model3, lyman_lines = pyasu.hi_model([dla1, dla2], spec, add_lls=True)
assert model3.flux[0].value < 1e-4
def coadd_cos_from_x1dfiles(filenames, wv_array=None, A_pix=0.01*u.AA):
spec_list = []
#TODO: mask out x1d spectral regions with bad values.
for filename in filenames:
sp = readspec(filename)
import pdb; pdb.set_trace()
# mask =
spec_list += [sp]
# spec_list contains all individual spectra
specs = collate(spec_list) # now all in a single XSpectrum1D object
#rebin
if wv_array is None:
# bring them to a unique native wavelength grid using PYPIT
A_pix = A_pix.to("AA").value
cat_wave = arco.new_wave_grid(specs.data['wave'], wave_method='pixel', A_pix=A_pix)
else:
cat_wave = wv_array.to('AA').value
specs = specs.rebin(cat_wave*u.AA, all=True, do_sig=True, masking='none',grow_bad_sig=True)
# estimate weights for coaddition (PYPYT)
sn2, weights = arco.sn_weight(specs)
# coaddition
spec1d = arco.one_d_coadd(specs, weights)
return spec1d
def test_coadd_stis_from_x1dfiles(plot=False):
spec_old = readspec("./data/m5zng1_stis/m5zng1_stis.fits")
# co-add independently of old
filenames = glob.glob("./data/m5zng1_stis/o6n*_x1d.fits")
spec_new = coadd.coadd_stis_from_x1dfiles(filenames, wv_array=None)
spec_new_rebinned = spec_new.rebin(spec_old.wavelength,
do_sig=True,
grow_bad_sig=True)
if plot:
plt.plot(spec_old.wavelength,
spec_old.flux,
drawstyle='steps-mid',
color='k')
plt.plot(spec_old.wavelength,
spec_old.sig,
drawstyle='steps-mid',
color='g')
plt.plot(spec_new.wavelength,
spec_new.flux,
drawstyle='steps-mid',
color='b')
plt.plot(spec_new.wavelength,
spec_new.sig,
drawstyle='steps-mid',
color='y')
spec_new.write_to_fits("new.fits")
def mk_comp(ctype,vlim=[-300.,300]*u.km/u.s,add_spec=False, use_rand=True,
add_trans=False, zcomp=2.92939, b=20*u.km/u.s):
# Read a spectrum Spec
if add_spec:
xspec = lsio.readspec(lt_path+'/spectra/tests/files/UM184_nF.fits')
else:
xspec = None
# AbsLines
if ctype == 'HI':
all_trans = ['HI 1215', 'HI 1025']
elif ctype == 'SiII':
all_trans = ['SiII 1260', 'SiII 1304', 'SiII 1526', 'SiII 1808']
if add_trans:
all_trans += ['SiII 1193']
abslines = []
for trans in all_trans:
iline = AbsLine(trans, z=zcomp)
if use_rand:
rnd = np.random.rand()
else:
rnd = 0.
iline.attrib['logN'] = 13.3 + rnd
iline.attrib['sig_logN'] = 0.15
iline.attrib['flag_N'] = 1
iline.attrib['b'] = b
iline.analy['spec'] = xspec
iline.limits.set(vlim)
_,_ = ltaa.linear_clm(iline.attrib) # Loads N, sig_N
abslines.append(iline)
# Component
abscomp = AbsComponent.from_abslines(abslines)
return abscomp, abslines
def test_write_ascii(spec):
# Write. Should be replaced with tempfile.TemporaryFile
spec.write_to_ascii(data_path('tmp.ascii'))
#
specb = io.readspec(data_path('tmp.ascii'))
# check a round trip works
np.testing.assert_allclose(spec.wavelength, specb.wavelength)
def test_hdf5(specm):
import h5py
# Write. Should be replaced with tempfile.TemporaryFile
specm.write_to_hdf5(data_path('tmp.hdf5'))
#
specread = io.readspec(data_path('tmp.hdf5'))
# check a round trip works
np.testing.assert_allclose(specm.wavelength, specread.wavelength)
# Add to existing file
tmp2 = h5py.File(data_path('tmp2.hdf5'), 'w')
foo = tmp2.create_group('boxcar')
specm.add_to_hdf5(tmp2, path='/boxcar/')
tmp2.close()
# check a round trip works
spec3 = io.readspec(data_path('tmp2.hdf5'), path='/boxcar/')
np.testing.assert_allclose(specm.wavelength, spec3.wavelength)
def test_slice():
spec = io.readspec(data_path('UM184_nF.fits'))
spec2 = io.readspec(data_path('PH957_f.fits'))
spec3 = spec2.copy()
# Collate to make a multispec spectrum
mspec = lsu.collate([spec, spec2, spec3])
# Array
newspec = mspec[np.array([0, 1])]
# Test
assert newspec.nspec == 2
assert not newspec.co_is_set
# Int
newspec2 = mspec[1]
assert newspec2.nspec == 1
# Slice
newspec3 = mspec[0:2]
assert newspec3.nspec == 2
def test_gauss_smooth():
spec = io.readspec(data_path('UM184_nF.fits'))
# Smooth
smth_spec = spec.gauss_smooth(4.)
# Test
np.testing.assert_allclose(smth_spec.flux[3000].value, 0.8288110494613)
assert smth_spec.flux.unit == spec.flux.unit
def test_relvel():
spec = io.readspec(data_path('UM184_nF.fits'))
# Velocity
velo = spec.relative_vel(5000.*u.AA)
# Test
np.testing.assert_allclose(velo[6600].value, -3716.441360213781)
assert velo.unit == (u.km/u.s)
def specr():
# Replace bad pixels (for rebinning)
data = io.readspec(data_path('UM184_nF.fits'), masking='edges')
sig = data.sig.value
bad_pix = sig <= 0.
sig[bad_pix] = 1.
data.sig = sig
return data
def test_readwrite_meta_as_dicts(spec):
sp = XSpectrum1D.from_tuple((np.array([5, 6,
7]), np.ones(3), np.ones(3) * 0.1))
sp.meta['headers'][0] = dict(a=1, b='abc')
sp2 = XSpectrum1D.from_tuple(
(np.array([8, 9, 10]), np.ones(3), np.ones(3) * 0.1))
sp2.meta['headers'][0] = dict(c=2, d='efg')
spec = ltsu.collate([sp, sp2])
# Write
spec.write_to_fits(data_path('tmp.fits'))
spec.write_to_hdf5(data_path('tmp.hdf5'))
# Read and test
newspec = io.readspec(data_path('tmp.hdf5'))
assert newspec.meta['headers'][0]['a'] == 1
assert newspec.meta['headers'][0]['b'] == 'abc'
newspec2 = io.readspec(data_path('tmp.fits'))
assert 'METADATA' in newspec2.meta['headers'][0].keys()
def specr():
# Replace bad pixels (for rebinning)
data = io.readspec(data_path('UM184_nF.fits'), masking='edges')
sig = data.sig.value
bad_pix = sig <= 0.
sig[bad_pix] = 1.
data.sig = sig
return data
def test_slice():
spec = io.readspec(data_path('UM184_nF.fits'))
spec2 = io.readspec(data_path('PH957_f.fits'))
spec3 = spec2.copy()
# Collate to make a multispec spectrum
mspec = lsu.collate([spec,spec2,spec3])
# Array
newspec = mspec[np.array([0,1])]
# Test
assert newspec.nspec == 2
assert not newspec.co_is_set
# Int
newspec2 = mspec[1]
assert newspec2.nspec == 1
# Slice
newspec3 = mspec[0:2]
assert newspec3.nspec == 2
def __init__(self,specfilename,parfilename=None,wave1=None,wave2=None,numchunks=8,parent=None):
QtWidgets.QMainWindow.__init__(self, parent)
#super(Main,self).__init__()
self.setupUi(self)
### Initialize stuff
self.line_dict = {}
self.fitpars = None
self.parinfo = None
self.linecmts = None
self.wave1 = wave1
self.wave2 = wave2
self.numchunks = numchunks
self.spls = []
self.labeltog = 1
self.pixtog = 0
self.restog = 1
self.fitconvtog = 0
self.lastclick=1334.
### Read in spectrum and list of lines to fit
self.specfilename=specfilename
self.spectrum = readspec(specfilename)
self.wave=self.spectrum.wavelength.value
self.normflux=self.spectrum.flux/self.spectrum.co
self.normsig=self.spectrum.sig/self.spectrum.co
cfg.spectrum = self.spectrum
cfg.wave=self.wave
cfg.normflux=self.normflux
cfg.filename=self.specfilename
if not parfilename==None:
self.initialpars(parfilename)
### Connect signals to slots
self.fitButton.clicked.connect(self.fitlines)
self.fitConvBox.clicked.connect(self.togfitconv)
self.boxLineLabel.clicked.connect(self.toglabels)
self.boxFitpix.clicked.connect(self.togfitpix)
self.boxResiduals.clicked.connect(self.togresiduals)
self.loadParsButton.clicked.connect(self.openParFileDialog)
self.addLineButton.clicked.connect(self.addLineDialog)
self.writeParsButton.clicked.connect(self.writeParFileDialog)
self.writeModelButton.clicked.connect(self.writeModelFileDialog)
self.writeModelCompButton.clicked.connect(self.writeModelCompFileDialog)
self.quitButton.clicked.connect(self.quitGui)
### Initialize spectral plots
fig=Figure(figsize=(5,3))
self.fig=fig
self.initplot(fig)
### Initialize side plot
sidefig=Figure(figsize=(5.85,3.75))
self.sidefig = sidefig
self.addsidempl(self.sidefig)
self.sideplot(self.lastclick) #Dummy initial cenwave setting
def __init__(self,specfilename,parfilename=None,wave1=None,wave2=None,numchunks=8,parent=None):
QtWidgets.QMainWindow.__init__(self, parent)
#super(Main,self).__init__()
self.setupUi(self)
### Initialize stuff
self.line_dict = {}
self.fitpars = None
self.parinfo = None
self.linecmts = None
self.wave1 = wave1
self.wave2 = wave2
self.numchunks = numchunks
self.spls = []
self.labeltog = 1
self.pixtog = 0
self.restog = 1
self.fitconvtog = 0
self.lastclick=1334.
### Read in spectrum and list of lines to fit
self.specfilename=specfilename
self.spectrum = readspec(specfilename)
self.wave=self.spectrum.wavelength.value
self.normflux=self.spectrum.flux/self.spectrum.co
self.normsig=self.spectrum.sig/self.spectrum.co
cfg.spectrum = self.spectrum
cfg.wave=self.wave
cfg.normflux=self.normflux
cfg.filename=self.specfilename
if not parfilename==None:
self.initialpars(parfilename)
### Connect signals to slots
self.fitButton.clicked.connect(self.fitlines)
self.fitConvBox.clicked.connect(self.togfitconv)
self.boxLineLabel.clicked.connect(self.toglabels)
self.boxFitpix.clicked.connect(self.togfitpix)
self.boxResiduals.clicked.connect(self.togresiduals)
self.loadParsButton.clicked.connect(self.openParFileDialog)
self.addLineButton.clicked.connect(self.addLineDialog)
self.writeParsButton.clicked.connect(self.writeParFileDialog)
self.writeModelButton.clicked.connect(self.writeModelFileDialog)
self.writeModelCompButton.clicked.connect(self.writeModelCompFileDialog)
self.quitButton.clicked.connect(self.quitGui)
### Initialize spectral plots
fig=Figure()
self.fig=fig
self.initplot(fig)
### Initialize side plot
sidefig=Figure(figsize=(5.25,2))
self.sidefig = sidefig
self.addsidempl(self.sidefig)
self.sideplot(self.lastclick) #Dummy initial cenwave setting
def read_spec(row):
# Filename
coord = SkyCoord(ra=row['RA_GROUP'], dec=row['DEC_GROUP'], unit='deg')
filename = 'J{:s}{:s}.txt'.format(coord.ra.to_string(unit=u.hour,sep='',pad=True)[0:4],
coord.dec.to_string(sep='',pad=True,alwayssign=True)[0:5])
# Read
spec = lsio.readspec(path+filename)
# Return
return filename, spec
def test_addnoise():
spec = io.readspec(data_path('UM184_nF.fits'))
#
spec.add_noise(seed=12)
np.testing.assert_allclose(spec.flux[1000], 0.44806158542633057)
# With S/N input
spec.add_noise(seed=19,s2n=10.)
np.testing.assert_allclose(spec.flux[1000], 0.24104823059199412)
def test_rebin():
spec = io.readspec(data_path('UM184_nF.fits'))
# Rebin
new_wv = np.arange(3000., 9000., 5) * u.AA
newspec = spec.rebin(new_wv)
# Test
np.testing.assert_allclose(newspec.flux[1000], 0.9999280967617779)
assert newspec.flux.unit == u.dimensionless_unscaled
def json_eqw(json_file, fits_file, outfile, overwrite=False):
ion_name = []
restwave = []
col = []
col_err = []
flag = []
zcomp = []
if not os.path.isfile(json_file):
return np.array(ion_name), np.array(restwave), np.array(col), \
np.array(col_err), np.array(flag), np.array(zcomp)
if not os.path.isfile(outfile) or overwrite == True:
out = open(outfile, 'w')
out.write('#ion_name, restwave, logN, logN_err, flag_N, zcomp\n')
with open(json_file) as data_file:
igmg_dict = json.load(data_file)
comp_list = []
for ii, key in enumerate(igmg_dict['cmps'].keys()):
comp = AbsComponent.from_dict(igmg_dict['cmps'][key],
chk_sep=False,
chk_data=False,
chk_vel=False)
comp_list += [comp]
spec = readspec(fits_file)
for i, cc in enumerate(comp_list):
for j, al in enumerate(cc._abslines):
al.analy['spec'] = spec
al.measure_ew()
al.measure_aodm()
ion_name.append(al.ion_name)
restwave.append(al.wrest.value)
col.append(al.attrib['logN'])
sig_logN = al.attrib['sig_logN']
if np.isnan(sig_logN):
sig_logN = 0.0
col_err.append(sig_logN)
flag.append(al.attrib['flag_N'])
zcomp.append(al.z)
out.write('%s\t%f\t%e\t%e\t%d\t%0.6f\n'%(al.ion_name, al.wrest.value, \
al.attrib['logN'], sig_logN, al.attrib['flag_N'], al.z))
out.close()
if os.path.isfile(outfile) and len(open(outfile).readlines()) > 1:
ion_name = np.loadtxt(outfile,
unpack=True,
skiprows=1,
usecols=0,
dtype='str')
restwave, col, col_err, flag, zcomp = \
np.loadtxt(outfile, unpack = True, skiprows = 1, usecols = (1, 2, 3, 4, 5))
return np.array(ion_name), np.array(restwave), np.array(col), np.array(
col_err), np.array(flag), np.array(zcomp)
def compare_skyspec(pp,sciobj,pypit_skyboxfile, iso):
'''Compare traces
Parameters:
----------
pp: Pdf obj
sciobj: Table
LowRedux sciobj table
iso: tuple
instr, setup, obj strings
'''
# Load
pypit_skyspec = lsio.readspec(pypit_skyboxfile)
#
lwrdx_skywv = sciobj['WAVE_BOX']
lwrdx_skyfx = sciobj['SKY_BOX']
lwrdx_skywv = arwv.vactoair(lwrdx_skywv*u.AA)
#
plt.clf()
plt.figure(figsize=(16,8))
gs = gridspec.GridSpec(2, 1)
# Full
ax = plt.subplot(gs[0])
# PYPIT
ax.plot(pypit_skyspec.dispersion, pypit_skyspec.flux, 'k-', label='PYPIT', drawstyle='steps')
# LowRedux
ax.plot(lwrdx_skywv, lwrdx_skyfx/(2.*sciobj['BOX_RAD']), '-', color='blue', label='LowRedux')
# Axes
ax.set_xlim(np.min(pypit_skyspec.dispersion.value),np.max(pypit_skyspec.dispersion.value))
ax.set_ylim(0.,np.max(pypit_skyspec.flux))
ax.set_xlabel('Wavelength',fontsize=17.)
ax.set_ylabel('Sky (Counts/pix)',fontsize=17.)
# Legend
legend = plt.legend(loc='upper left', borderpad=0.3,
handletextpad=0.3, fontsize='x-large')
# ZOOM
axz = plt.subplot(gs[1])
# PYPIT
axz.plot(pypit_skyspec.dispersion, pypit_skyspec.flux, 'k-', label='PYPIT', drawstyle='steps-mid')
# LowRedux
axz.plot(lwrdx_skywv, lwrdx_skyfx/(2.*sciobj['BOX_RAD']), '-', color='blue', label='LowRedux')
# Axes
zlim = np.array([7200., 7700.])*u.AA
axz.set_xlim(zlim.value)
ymx = np.max( pypit_skyspec.flux[np.where((pypit_skyspec.dispersion>zlim[0])&(pypit_skyspec.dispersion<zlim[1]))])
axz.set_ylim(0.,ymx)
axz.set_xlabel('Wavelength',fontsize=17.)
axz.set_ylabel('Sky (Counts/pix)',fontsize=17.)
# Legend
legend = plt.legend(loc='upper right', borderpad=0.3,
handletextpad=0.3, fontsize='x-large')
ax.set_title("Instr={:s}, Setup={:s} :: Sky Spectra for {:s} :: PYPIT ({:s})".format(iso[0], iso[1], iso[2], pypit.version), fontsize=18.)
# Finish
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig(bbox_inches='tight')
plt.close()
def main(*args, **kwargs):
""" Runs the continuum fitter
"""
import argparse
parser = argparse.ArgumentParser(description='GUI to fit a continuum to a spectrum')
parser.add_argument("file", type=str, help="Input spectral file (FITS, ASCII, etc.)")
parser.add_argument("outfil", type=str, help="Output, normalized spectrum filename; FITS [can be the same]")
parser.add_argument("--redshift", type=float, help="Redshift of the Source")
parser.add_argument("--wchunk", type=float, help="Width of a 'chunk' (Ang)")
parser.add_argument("--native", default=True, action='store_true', help="Do not mask input spectrum")
parser.add_argument("--specdb", type=str, help="Input file is specdb. Input (ra,dec,group) in this order without spaces")
#parser.add_argument("-exten", type=int, help="FITS extension")
pargs = parser.parse_args()
from linetools.guis import specdbutils
from linetools.spectra import io as lsio
# Read spectrum
if pargs.native:
masking = 'none'
else:
masking = 'edges'
# Load from simple file
if pargs.specdb is None:
xspec = lsio.readspec(pargs.file, masking=masking)
else:
# Load specdb
spdb = specdbutils.load_specb(pargs.file)
if spdb is None:
print("You have not yet installed specdb!!")
print("Exiting..")
return
# Parse
ra,dec,group = pargs.specdb.split(',')
# Load
xspec = specdbutils.load_xspec(spdb, float(ra), float(dec), group=group, masking=masking)
kwrds = {}
if pargs.wchunk is not None:
kwrds['dw'] = pargs.wchunk
# Redshift
if pargs.redshift is not None:
kwrds['kind'] = 'QSO'
kwrds['redshift'] = pargs.redshift
# Run
print("WARNING: QUIT with q keystroke, not by clicking to kill.")
xspec.fit_continuum(**kwrds)
# Output
xspec.write_to_fits(pargs.outfil)
def test_readwrite_metadata(spec):
d = {"a": 1, "b": "abc", "c": 3.2, "d": np.array([1, 2, 3]), "e": dict(a=1, b=2)}
spec.meta.update(d)
spec.write_to_fits(data_path("tmp.fits"))
spec2 = io.readspec(data_path("tmp.fits"))
assert spec2.meta["a"] == d["a"]
assert spec2.meta["b"] == d["b"]
np.testing.assert_allclose(spec2.meta["c"], d["c"])
np.testing.assert_allclose(spec2.meta["d"], d["d"])
assert spec2.meta["e"] == d["e"]
def test_box_smooth():
spec = io.readspec(data_path('UM184_nF.fits'))
# Smooth
newspec3 = spec.box_smooth(3)
np.testing.assert_allclose(newspec3.flux[4000], 0.9967582821846008)
assert newspec3.flux.unit == u.dimensionless_unscaled
newspec5 = spec.box_smooth(5)
np.testing.assert_allclose(newspec5.flux[3000], 1.086308240890503)
def from_file(self, ifile):
''' From file
Parameters
----------
ifile : str
Filename
'''
slf = lsio.readspec(ifile)
return slf
def from_file(self, ifile, **kwargs):
""" From file
Parameters
----------
ifile : str
Filename
"""
slf = lsio.readspec(ifile, **kwargs)
return slf
def main(args):
import os
from pkg_resources import resource_filename
from matplotlib import pyplot as plt
from linetools.spectra.io import readspec
# Path to archived sky spectra
sky_path = os.path.join(resource_filename('pypeit', 'data'), 'sky_spec')
# Extension
exten = args.exten if hasattr(args, 'exten') else 0
# Read spec keywords
ikwargs = {}
if args.optimal:
ikwargs['wave_tag'] = 'opt_wave'
ikwargs['flux_tag'] = 'opt_sky'
else:
ikwargs['wave_tag'] = 'box_wave'
ikwargs['flux_tag'] = 'box_sky'
# Load user file
user_sky = readspec(args.file, exten=exten, **ikwargs)
# Load sky spec
arx_sky = readspec(sky_path + args.skyfile)
# Plot
plt.clf()
plt.plot(user_sky.wavelength,
user_sky.flux * args.scale_user,
'k-',
label='user')
plt.plot(arx_sky.wavelength, arx_sky.flux, 'b-', label='archive')
legend = plt.legend(loc='upper left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='small',
numpoints=1)
plt.show()
def read_spec(row):
# Filename
coord = SkyCoord(ra=row['RA_GROUP'], dec=row['DEC_GROUP'], unit='deg')
filename = 'J{:s}{:s}.txt'.format(
coord.ra.to_string(unit=u.hour, sep='', pad=True)[0:4],
coord.dec.to_string(sep='', pad=True, alwayssign=True)[0:5])
# Read
spec = lsio.readspec(path + filename)
# Return
return filename, spec
def test_model_abs():
# Simple system (without an absline)
dla = DLASystem.from_json(data_path('J010311.38+131616.7_z2.309_ESI.json'))
spec_fil = linetools.__path__[0]+'/spectra/tests/files/PH957_f.fits'
spec = lsio.readspec(spec_fil)
model, lya_lines = dla.model_abs(spec)
# import pdb; pdb.set_trace()
# Check core
ipx = np.argmin(np.abs(spec.wavelength.value-(1+dla.zabs)*1215.67))
assert model.flux[ipx].value < 1e-4
def plotspec(args):
"""Plot spectrum files
Parameters
----------
filenames : list of str
Spectrum filenames
"""
from linetools.spectra.io import readspec
import warnings
import matplotlib.pyplot as plt
import matplotlib as mpl
warnings.simplefilter('ignore', mpl.mplDeprecation)
spec_cache = {}
fig = plt.figure(figsize=(10,5))
fig.subplots_adjust(left=0.07, right=0.95, bottom=0.11)
ax = fig.add_subplot(111)
i = 0
quit = False
print("#### Use left and right arrow keys to navigate, 'Q' to quit ####")
while quit is False:
filename = args.filenames[i]
if filename not in spec_cache:
spec_cache[filename] = readspec(filename)
sp = spec_cache[filename]
ax.cla()
sp.plot(show=False)
ax.set_xlabel(str(sp.wavelength.unit))
ax.set_title(filename)
if args.redshift is not None:
from linetools.lists.linelist import LineList
ll = LineList('Strong')
#import pdb ;pdb.set_trace()
wlines = ll._data['wrest'] * (1 + args.redshift)
y0, y1 = ax.get_ylim()
ax.vlines(wlines.to(sp.wavelength.unit).value, y0, y1,
linestyle='dotted')
while True:
plt.waitforbuttonpress()
if sp._plotter.last_keypress == 'right':
i += 1
i = min(i, len(args.filenames) - 1)
# Note this only breaks out of the inner while loop
break
elif sp._plotter.last_keypress == 'left':
i -= 1
i = max(i, 0)
break
elif sp._plotter.last_keypress == 'Q':
quit = True
break
def test_sep_files():
""" Separate flux/error files"""
spec = io.readspec(data_path('UM184_nF.fits'))
idl = ascii.read(data_path('UM184.dat.gz'), names=['wave', 'flux', 'sig'])
#np.testing.assert_allclose(spec.wavelength.value, idl['wave'])
np.testing.assert_allclose(spec.data['wave'][spec.select], idl['wave'])
np.testing.assert_allclose(spec.data['sig'][spec.select],
idl['sig'],
atol=2e-3,
rtol=0)
assert spec.wavelength.unit == u.Unit('AA')
def test_dla_XY():
spec_fil = linetools.__path__[0]+'/spectra/tests/files/PH957_f.fits'
spec = lsio.readspec(spec_fil)
dla = DLASystem.from_json(data_path('J010311.38+131616.7_z2.309_ESI.json'))
#
dla.measure_aodm(spec=spec)
dla.update_component_colm()
dla.fill_ionN()
dla.XY = RelAbund.from_ionclm_table((1,21.37,0.08), dla._ionN)
tbl = dla.XY.table()
assert len(tbl) == 8
def test_dla_XY():
spec_fil = linetools.__path__[0]+'/spectra/tests/files/PH957_f.fits'
spec = lsio.readspec(spec_fil)
dla = DLASystem.from_json(data_path('J010311.38+131616.7_z2.309_ESI.json'))
#
dla.measure_aodm(spec=spec)
dla.update_component_colm()
dla.fill_ionN()
dla.XY = RelAbund.from_ionclm_table((1,21.37,0.08), dla._ionN)
tbl = dla.XY.table()
assert len(tbl) == 8
def main(*args, **kwargs):
""" Runs the XSpecGui on an input file
"""
import argparse
parser = argparse.ArgumentParser(description='Parse')
parser.add_argument("file", type=str, help="Spectral file")
parser.add_argument("skyfile", type=str, help="Archived PYPIT sky file (e.g. paranal_sky.fits")
parser.add_argument("--exten", type=int, help="FITS extension")
parser.add_argument("--optimal", default=False,
help="Show Optimal? Default is boxcar", action="store_true")
parser.add_argument("--scale_user", default=1., type=float, help="Scale user spectrum by a factor")
pargs = parser.parse_args()
from matplotlib import pyplot as plt
# Extension
exten = (pargs.exten if hasattr(pargs, 'exten') else 0)
#scale = (pargs.scale_user if hasattr(pargs, 'scale_user') else 1.)
# Read spec keywords
ikwargs = {}
if pargs.optimal:
ikwargs['wave_tag'] = 'opt_wave'
ikwargs['flux_tag'] = 'opt_sky'
else:
ikwargs['wave_tag'] = 'box_wave'
ikwargs['flux_tag'] = 'box_sky'
# Load user file
user_sky = readspec(pargs.file, exten=exten, **ikwargs)
# Load sky spec
arx_sky = readspec(sky_path+pargs.skyfile)
# Plot
plt.clf()
plt.plot(user_sky.wavelength, user_sky.flux*pargs.scale_user, 'k-', label='user')
plt.plot(arx_sky.wavelength, arx_sky.flux, 'b-', label='archive')
legend = plt.legend(loc='upper left', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='small', numpoints=1)
plt.show()
def combinespectfiles(spfile_a, spfile_b, file_ab):
""" Coadd two spectra, and write output in a file
Parameters
----------
spfile_a : str
spfile_b : str
.fits files with spectra
file_ab : str
output .fits file with combined spectra
Returns
-------
"""
from linetools.spectra import io as tio
from linetools.spectra import utils as spltu
file_a = tio.readspec(spfile_a)
file_b = tio.readspec(spfile_b)
spliced_sp = spltu.splice_two(file_b, file_a, chk_units=False)
spliced_sp.write(file_ab)
def test_measurekin_absline():
# Test Simple kinematics
abslin = AbsLine('NiII 1741',z=2.307922)
# Set spectrum
abslin.analy['spec'] = lsio.readspec(data_path('PH957_f.fits'))
abslin.limits.set([-70., 70.]*u.km/u.s)
# Measure Kin
abslin.measure_kin()
np.testing.assert_allclose(abslin.attrib['kin']['Dv'].value, 75.)
np.testing.assert_allclose(abslin.attrib['kin']['fedg'], 0.20005782376000183)
def main(*args, **kwargs):
""" Runs the continuum fitter
"""
import argparse
parser = argparse.ArgumentParser(
description='GUI to fit a continuum to a spectrum')
parser.add_argument("file",
type=str,
help="Input spectral file (FITS, ASCII, etc.)")
parser.add_argument(
"outfil",
type=str,
help="Output, normalized spectrum filename; FITS [can be the same]")
parser.add_argument("--redshift",
type=float,
help="Redshift of the Source")
parser.add_argument("--wchunk",
type=float,
help="Width of a 'chunk' (Ang)")
parser.add_argument("--native",
default=True,
action='store_true',
help="Do not mask input spectrum")
#parser.add_argument("-exten", type=int, help="FITS extension")
pargs = parser.parse_args()
from linetools.guis.xspecgui import XSpecGui
from linetools.spectra import io as lsio
# Read spectrum
if pargs.native:
masking = 'none'
else:
masking = 'edges'
xspec = lsio.readspec(pargs.file, masking=masking)
kwrds = {}
if pargs.wchunk is not None:
kwrds['dw'] = pargs.wchunk
# Redshift
if pargs.redshift is not None:
kwrds['kind'] = 'QSO'
kwrds['redshift'] = pargs.redshift
# Run
print("WARNING: QUIT with q keystroke, not by clicking to kill.")
xspec.fit_continuum(**kwrds)
# Output
xspec.write_to_fits(pargs.outfil)