def plot_spectrum(ax, spec, complist=None, plot_res=True, fwhm=3):
""" Plots a spectrum in a given axis
Parameters
----------
ax : axis
matplotlib axis
spec: XSpectrum1D
Spectrum to plot
complist : list of AbsComponents, optional
If given, a model is computed and plotted
plot_res : bool, optional
Whether to plot residuals, only works if components
is not None.
fwhm : int, optional
FWHM in pixels
Returns
-------
ax : axis
Axis with the plot.
"""
# checks
if not isinstance(spec, XSpectrum1D):
raise IOError('Input spec must be XSpectrum1D object.')
if complist is not None:
if not isinstance(complist[0], AbsComponent):
raise IOError('components must be a list of AbsComponent objects.')
plot_model = True
else:
plot_model = False
if plot_model:
# create a model
model = lav.voigt_from_components(spec.wavelength, complist, fwhm=fwhm)
if spec.co_is_set:
spec.normalize(co=spec.co)
ax.plot(model.wavelength, spec.flux, '-', color=COLOR_FLUX, lw=1)
if spec.sig_is_set:
ax.plot(model.wavelength, spec.sig, '-', color=COLOR_SIG, lw=0.5)
if plot_model:
ax.plot(model.wavelength, model.flux, '-', color=COLOR_MODEL, lw=0.5)
if plot_res:
residual = spec.flux - model.flux
ax.plot(spec.wavelength, residual, '.', color=COLOR_RESIDUAL, ms=2)
ax.plot(spec.wavelength,
-1 * spec.sig,
'-',
drawstyle='steps-mid',
color=COLOR_SIG,
lw=0.5)
def plot_spectrum(ax, spec, complist=None, plot_res=True, fwhm=3):
""" Plots a spectrum in a given axis
Parameters
----------
ax : axis
matplotlib axis
spec: XSpectrum1D
Spectrum to plot
complist : list of AbsComponents, optional
If given, a model is computed and plotted
plot_res : bool, optional
Whether to plot residuals, only works if components
is not None.
fwhm : int, optional
FWHM in pixels
Returns
-------
ax : axis
Axis with the plot.
"""
# checks
if not isinstance(spec, XSpectrum1D):
raise IOError('Input spec must be XSpectrum1D object.')
if complist is not None:
if not isinstance(complist[0], AbsComponent):
raise IOError('components must be a list of AbsComponent objects.')
plot_model = True
else:
plot_model = False
if plot_model:
# create a model
model = lav.voigt_from_components(spec.wavelength, complist, fwhm=fwhm)
if spec.co_is_set:
spec.normalize(co=spec.co)
ax.plot(model.wavelength, spec.flux, '-', color=COLOR_FLUX, lw=1)
if spec.sig_is_set:
ax.plot(model.wavelength, spec.sig, '-', color=COLOR_SIG, lw=0.5)
if plot_model:
ax.plot(model.wavelength, model.flux, '-', color=COLOR_MODEL, lw=0.5)
if plot_res:
residual = spec.flux - model.flux
ax.plot(spec.wavelength, residual, '.', color=COLOR_RESIDUAL, ms=2)
ax.plot(spec.wavelength, -1*spec.sig, '-', drawstyle='steps-mid', color=COLOR_SIG, lw=0.5)
def plot_vel(ax, spec, iline, z, dvlims, complist=None, fwhm=3, min_ew_blends=0.01*u.AA):
# first normalize
if not spec.normed:
spec.normalize(co=spec.co)
# first identify good components
good_comps = []
good_comps_aux = ltiu.get_components_at_z(complist, z, dvlims)
for comp in good_comps_aux:
for aline in comp._abslines:
if aline.name == iline['name']:
good_comps += [comp]
break
# bad comps will be those unrelated to the given redshift/transition
bad_comps = []
for comp in complist:
if comp not in good_comps:
bad_comps += [comp]
# only good comps will have a model
if len(good_comps) > 0:
# import pdb; pdb.set_trace()
model_spec = lav.voigt_from_components(spec.wavelength, good_comps, fwhm=fwhm)
else:
model_spec = XSpectrum1D.from_tuple((spec.wavelength, np.ones(spec.npix)))
# main plot
velo = ltu.dv_from_z(spec.wavelength/iline['wrest'] - 1. , z)
ax.plot(velo, spec.flux, drawstyle='steps-mid', color=COLOR_FLUX)
plot_spec_complist(ax, velo, spec, bad_comps, min_ew = min_ew_blends, color=COLOR_BLEND, lw=2, drawstyle='steps-mid')
plot_spec_complist(ax, velo, model_spec, good_comps, min_ew = None, color=COLOR_MODEL, lw=1, ls='-')
if spec.sig_is_set:
ax.plot(velo, spec.sig, drawstyle='steps-mid', color=COLOR_SIG, lw=0.5)
# Zero velocity line
ax.plot([0., 0.], [-1e9, 1e9], ':', color='gray')
# Unity flux level line
ax.plot([-1e9, 1e9], [1, 1], ':', color='b', lw=0.5)
# Zero flux level line
ax.plot([-1e9, 1e9], [0, 0], '--', color='k', lw=1)
def test_voigt_from_components():
from linetools.isgm.tests.test_use_abscomp import mk_comp
wv_array = np.arange(900, 1250, 0.01) * u.AA
comp1, HIlines = mk_comp('HI', zcomp=0.01, vlim=[-10, 10] * u.km / u.s)
comp2, HIlines = mk_comp('HI', zcomp=0.05, vlim=[-10, 10] * u.km / u.s)
model = lav.voigt_from_components(wv_array, [comp1, comp2])
def plot_vel(ax,
spec,
iline,
z,
dvlims,
complist=None,
fwhm=3,
min_ew_blends=0.01 * u.AA):
# first normalize
if not spec.normed:
spec.normalize(co=spec.co)
# first identify good components
good_comps = []
good_comps_aux = ltiu.get_components_at_z(complist, z, dvlims)
for comp in good_comps_aux:
for aline in comp._abslines:
if aline.name == iline['name']:
good_comps += [comp]
break
# bad comps will be those unrelated to the given redshift/transition
bad_comps = []
for comp in complist:
if comp not in good_comps:
bad_comps += [comp]
# only good comps will have a model
if len(good_comps) > 0:
# import pdb; pdb.set_trace()
model_spec = lav.voigt_from_components(spec.wavelength,
good_comps,
fwhm=fwhm)
else:
model_spec = XSpectrum1D.from_tuple(
(spec.wavelength, np.ones(spec.npix)))
# main plot
velo = ltu.dv_from_z(spec.wavelength / iline['wrest'] - 1., z)
ax.plot(velo, spec.flux, drawstyle='steps-mid', color=COLOR_FLUX)
plot_spec_complist(ax,
velo,
spec,
bad_comps,
min_ew=min_ew_blends,
color=COLOR_BLEND,
lw=2,
drawstyle='steps-mid')
plot_spec_complist(ax,
velo,
model_spec,
good_comps,
min_ew=None,
color=COLOR_MODEL,
lw=1,
ls='-')
if spec.sig_is_set:
ax.plot(velo, spec.sig, drawstyle='steps-mid', color=COLOR_SIG, lw=0.5)
# Zero velocity line
ax.plot([0., 0.], [-1e9, 1e9], ':', color='gray')
# Unity flux level line
ax.plot([-1e9, 1e9], [1, 1], ':', color='b', lw=0.5)
# Zero flux level line
ax.plot([-1e9, 1e9], [0, 0], '--', color='k', lw=1)
def test_voigt_from_components():
from linetools.isgm.tests.test_use_abscomp import mk_comp
wv_array = np.arange(900, 1250, 0.01) * u.AA
comp1, HIlines = mk_comp('HI', zcomp=0.01, vlim=[-10,10]*u.km/u.s)
comp2, HIlines = mk_comp('HI', zcomp=0.05, vlim=[-10,10]*u.km/u.s)
model = lav.voigt_from_components(wv_array, [comp1,comp2])