SpectrumSampler¶

class msaexp.spectrum.SpectrumSampler(spec_input, oversample_kwargs={'factor': 5, 'pad': 12}, with_sensitivity=True, **kwargs)[source]¶

Bases: object

Helper functions for sampling templates onto the wavelength grid of an observed spectrum

Parameters

spec_inputstr, HDUList

str : spectrum filename, usually [root].spec.fits
HDUList : FITS data

with_sensitivitybool

Initialize sensitivity curves for including multiple spectral orders in the model generation.

Attributes

specTable: 1D spectrum table from the SPEC1D HDU of ``file`
metadict: Metadata of spec table
spec_wobsarray-like: Observed wavelengths, microns
spec_R_fwhmarray-like: Tabulated spectral resolution R = lambda / dlambda, assumed to be defined as FWHM
validarray-like: Boolean array of valid 1D data

Attributes Summary

`meta`	Metadata of `spec` table
`spec`
`spec_R_fwhm`
`spec_wobs`
`valid`
`wave_step`

Methods Summary

`bspline_array`([nspline, step_size, ...])	Initialize bspline templates for continuum fits
`drizzled_hdu_figure`(**kwargs)	Run `drizzled_hdu_figure` on array data
`emission_line`(line_um[, line_flux, ...])	Make an emission line template - deprecated in favor of `fast_emission_line`
`fast_emission_line`(line_um[, line_flux, ...])	Make an emission line template with numerically correct pixel integration function
`fit_single_template`(template[, z, spl, ...])	Resample and fit a template to the spectrum
`igm_absorption`(z[, scale_tau, scale_disp])	Inoue+ (2014) IGM absorption
`initialize_emission_line`([nsamp])	Initialize emission line
`initialize_spec`(spec_input, **kwargs)	Read spectrum data from file and initialize attributes
`load_sensitivity_curve`([sens_file, prefix, ...])
`multiplot`([sx, sy, z, ny, xpad, ...])	Make a plot of the spectrum split into wavelength intervals
`oversampled_wavelengths`([factor, pad])	Generate a wavelength grid that oversamples the spectrum wavelengths
`redo_1d_extraction`(**kwargs)	Redo 1D extraction from 2D arrays with `make_optimal_extraction`
`resample_bagpipes_model`(model_galaxy[, ...])	Resample a `bagpipes` model to the wavelength grid of the spectrum.
`resample_eazy_template`(template[, z, ...])	Smooth and resample an `eazy.templates.Template` object onto the observed wavelength grid of a spectrum

Attributes Documentation

meta¶: Metadata of spec table

spec = {}¶

spec_R_fwhm = None¶

spec_wobs = None¶

valid = None¶

wave_step = None¶

Methods Documentation

bspline_array(nspline=13, step_size=None, remap_arrays=None, minmax=None, log=False, by_wavelength=False, get_matrix=True, orders=[1, 2, 3, 4])[source]¶

Initialize bspline templates for continuum fits

Parameters

nsplineint: Number of spline functions to sample across the wavelength range
logbool: Sample in log(wavelength)
by_wavelengthbool: If True, sample bspline functions across the wavelength range. If False, sample bspline functions across the index range.
get_matrixbool: If True, return array data. Otherwise, return template objects.

Returns

bsplarray-like: bspline data, depending on get_matrix

drizzled_hdu_figure(**kwargs)[source]¶

Run drizzled_hdu_figure on array data

Parameters

kwargsdict: Keyword arguments passed to drizzled_hdu_figure

Returns

figFigure: Spectrum figure

emission_line(line_um, line_flux=1, scale_disp=1.0, velocity_sigma=100.0, nsig=4, **kwargs)[source]¶

Make an emission line template - deprecated in favor of fast_emission_line

Parameters

line_umfloat: Line center, microns
line_fluxfloat: Line normalization
scale_dispfloat: Factor by which to scale the tabulated resolution FWHM curve
velocity_sigmafloat: Velocity sigma width in km/s
nsigint: Number of sigmas of the convolution kernel to sample

Returns

resarray-like: Gaussian emission line sampled at the spectrum wavelengths

fast_emission_line(line_um, line_flux=1, scale_disp=1.0, velocity_sigma=100.0, orders=[1, 2, 3, 4], lorentz=False, verbose=False, **kwargs)[source]¶

Make an emission line template with numerically correct pixel integration function

Parameters

line_umfloat: Line center, microns
line_fluxfloat: Line normalization
scale_dispfloat: Factor by which to scale the tabulated resolution FWHM curve
velocity_sigmafloat: Velocity sigma width in km/s
orderslist: List of spectral orders to include if the sensitivity curves have been read along with the spectrum.
lorentzbool: Generate a Lorentzian function instead of a Gaussian

Returns

resarray-like: Gaussian emission line sampled at the spectrum wavelengths

fit_single_template(template, z=0.0, spl=None, spline_type='multiply', lsq=<function lstsq>, lsq_kwargs={'rcond': None}, loss=None, **kwargs)[source]¶

Resample and fit a template to the spectrum

Parameters

templateeazy.templates.Template: High-resolution, rest-frame template
zfloat: Redshift
spl(N, M) array: Optional spline array
lsq, lsq_kwargsfunc, dict: Least-squares optimization function, keyword args
lossfunc: Loss function, e.g, scip.stats.norm(scale=spec['full_err'][spec.valid])
kwargsdict: keyword arguments passed to resample_eazy_template, e.g., “scale_disp”, “velocity_sigma”

Returns

resultdict: Fit results - model: best-fit model, (M,) array - A: design matrix, (N, M) array - coeffs: least-squares coefficients, (N,) array - lnp : loss.logpdf(residual) (M,) array

igm_absorption(z, scale_tau=1.0, scale_disp=1.3)[source]¶

Inoue+ (2014) IGM absorption

Parameters

zfloat: Redshift
scale_taufloat: Factor to scale $tau_mathrm{IGM}$
scale_dispfloat: Dispersion R rescaling

Returns

igmarray-like: IGM model transmission at observed-frame wavelengths

initialize_emission_line(nsamp=64)[source]¶

Initialize emission line

Parameters

nsampint: Number of samples for the emission line. Default = 64

initialize_spec(spec_input, **kwargs)[source]¶

Read spectrum data from file and initialize attributes

Parameters

spec_inputstr: Filename, usually [root].spec.fits
kwargsdict: Keyword arguments passed to read_spectrum

load_sensitivity_curve(sens_file=None, prefix='msaexp_sensitivity', version='001', file_template='{prefix}_{grating}_{filter}_{version}.fits', verbose=False, **kwargs)[source]¶

multiplot(sx=10, sy=2.5, z=0, ny=5, xpad=0.05, wave_limits=None, xgrid=None, fig=None, ymax=None, sharey=False, flam=0, okws=None, bkg=0.0, data=None, show_bkg=True, verbose=True, show_sn=False, **kwargs)[source]¶

Make a plot of the spectrum split into wavelength intervals

Parameters

sx, syfloat: x and y size of the separate figure axes
zfloat: If provided, plot in rest-frame intervals
nyint: Number of wavelength intervals
xpadfloat: Fractional overlap of wavelength intervals
wave_limits[float, float], None: Override limits from min / max wavelength of the spectrum
xgridlist: Explicit list of wavelength steps. If not provided, will split the spectrum wavelength array into ny intervals
figfigure: If not provided, initialize a new figure

Returns

figfigure: Figure object
axeslist: List of axis objects

Examples

from msaexp import spectrum
import msaexp.utils

sp = spectrum.SpectrumSampler("https://s3.amazonaws.com/msaexp-nirspec/extractions/smacs0723-ero-v4/smacs0723-ero-v4_g395m-f290lp_2736_6355.spec.fits")

z = 7.665

fig, axes = sp.multiplot(
    ny=4,
    sx=8, sy=2,
    z=z,
    color='k', alpha=0.5
)

# Overplot line list
li = msaexp.utils.lines.LineList()
for ax in axes:
    li.add_to_axis(ax, alpha=0.5)

axes[-1].set_xlabel(f'rest wavelength, z={z:.3f}')
fig.tight_layout(pad=1)

(Source code, png, hires.png, pdf)

../_images/msaexp-spectrum-SpectrumSampler-1.png

oversampled_wavelengths(factor=5, pad=12)[source]¶

Generate a wavelength grid that oversamples the spectrum wavelengths

Parameters

factorint: Oversampling factor

Returns

wavesarray-like: Oversampled wavelengths

redo_1d_extraction(**kwargs)[source]¶

Redo 1D extraction from 2D arrays with make_optimal_extraction

Parameters

kwargsdict: Keyword arguments passed to make_optimal_extraction

Returns

outputSpectrumSampler: A new SpectrumSampler object

Examples

# Compare 1D extractions
from msaexp import spectrum
import matplotlib.pyplot as plt

sp = spectrum.SpectrumSampler('https://s3.amazonaws.com/msaexp-nirspec/extractions/ceers-ddt-v3/ceers-ddt-v3_prism-clear_2750_1598.spec.fits')

fig, axes = plt.subplots(2, 1, figsize=(8, 5),
                         sharex=True, sharey=True)

# Boxcar extraction, center pixel +/- 2 pix
ax = axes[0]
new = sp.redo_1d_extraction(ap_radius=2, bkg_offset=-6)

ax.plot(sp['wave'], sp['flux'], alpha=0.5,
        label='Original optimal extraction')
ax.plot(new['wave'], new['aper_flux'], alpha=0.5,
        label='Boxcar, y = 23 ± 2')

ax.grid()
ax.legend()

# Extractions above and below the center
ax = axes[1]
low = sp.redo_1d_extraction(ap_center=21, ap_radius=1)
hi = sp.redo_1d_extraction(ap_center=25, ap_radius=1)

ax.plot(low['wave'], low['aper_flux']*1.5, alpha=0.5,
        label='Below, y = 21 ± 1', color='b')
ax.plot(hi['wave'], hi['aper_flux']*3, alpha=0.5,
        label='Above, y = 25 ± 1', color='r')

ax.set_xlim(0.9, 5.3)
ax.grid()
ax.legend()

ax.set_xlabel(r'$\lambda$')
for ax in axes:
    ax.set_ylabel(r'$\mu\mathrm{Jy}$')

fig.tight_layout(pad=1)

(Source code, png, hires.png, pdf)

../_images/msaexp-spectrum-SpectrumSampler-2.png

resample_bagpipes_model(model_galaxy, model_comp=None, nsig=5, scale_disp=1.3, orders=[1, 2, 3, 4], **kwargs)[source]¶

Resample a bagpipes model to the wavelength grid of the spectrum.

See msaexp.spectrum.resample_bagpipes_model.

resample_eazy_template(template, z=0, scale_disp=1.0, velocity_sigma=100.0, fnu=True, nsig=4, with_igm=False, orders=[1, 2, 3, 4], verbose=False, **kwargs)[source]¶

Smooth and resample an eazy.templates.Template object onto the observed wavelength grid of a spectrum

Parameters

templateeazy.templates.Template: Template object
zfloat: Redshift
scale_dispfloat: Factor multiplied to the tabulated spectral resolution before sampling
velocity_sigmafloat: Gaussian velocity broadening factor, km/s
fnubool: Return resampled template in f-nu flux densities
nsigint: Number of standard deviations to sample for the convolution
orderslist: List of spectral orders to include if the sensitivity curves have been read along with the spectrum.

Returns

resarray-like: Template flux density smoothed and resampled at the spectrum wavelengths

Navigation

SpectrumSampler¶