Spectrum Tools

Introduction

This module contains general tools to process white dwarf spectra.

API

class wdtools.SpecTools(plot_continuum=False, smoothing=1e-15, filter_skylines=True, crop=True)

Spectrum processing tools and functions.

chisquare(residual)

Chi^2 statistics from residual

Unscaled chi^2 statistic from an array of residuals (does not account for uncertainties).

continuum_normalize(wl, fl, ivar=None)

Continuum-normalization with smoothing splines that avoid a pre-made list of absorption lines for DA and DB spectra. To normalize spectra that only have Balmer lines (DA),

we recommend using the normalize_balmer function instead. Also crops the spectrum to the 3700 - 7000 Angstrom range.

Parameters

  • wl (array) – Wavelength array of spectrum

  • fl (array) – Flux array of spectrum

  • ivar (array, optional) – Inverse variance array. If None, will return only the normalized wavelength and flux.

Returns

Tuple of cropped wavelength, cropped and normalized flux, and (if ivar is not None)

cropped and normalized inverse variance array.

Return type

tuple

find_centroid(wl, flux, centroid, half_window=25, window_step=2, n_fit=12, make_plot=False, pltname='', debug=False, normalize=True)

Statistical inference of spectral redshift by iteratively fitting Voigt profiles to cropped windows around the line centroid.

Parameters

  • wl (array) – Wavelength array of spectrum

  • flux (array) – Flux array of spectrum

  • centroid (float) – Theoretical wavelength of line centroid

  • half_window (float, optional) – Distance in Angstroms from the theoretical centroid to include in the fit

  • window_step (float, optional) – Step size in Angstroms to reduce the half-window size after each fitting iteration

  • n_fit (int, optional) – Number of iterated fits to perform

  • make_plot (bool, optional) – Whether to plot the absorption line with all fits overlaid.

  • pltname (str, optional) – If not ‘’, saves the plot to the supplied path with whatever extension you specify.

Returns

Tuple of 3 values: the mean fitted centroid across iterations, the propagated uncertainty reported by the fitting routine, and the standard deviation of the centroid across all iterations. We find the latter is a good estimator of statistical uncertainty in the fitted centroid.

Return type

tuple

linear(wl, p1, p2)

Linear polynomial of degree 1

normalize_balmer(wl, fl, ivar=None, lines=['alpha', 'beta', 'gamma', 'delta'], skylines=False, make_plot=False, make_subplot=False, make_stackedplot=False, centroid_dict={'alpha': 6564.61, 'beta': 4862.68, 'delta': 4102.89, 'eps': 3971.2, 'gamma': 4341.68, 'h8': 3890.12}, distance_dict={'alpha': 300, 'beta': 200, 'delta': 75, 'eps': 50, 'gamma': 120, 'h8': 25}, sky_fill=nan)

Continuum-normalization of any spectrum by fitting each line individually.

Fits every absorption line by fitting a linear model added to a Voigt profile to the spectrum, and dividing out the linear model. All normalized lines are concatenated and returned. For statistical and plotting purposes, two adjacent lines should not have overlapping regions (governed by the distance_dict).

Parameters

  • wl (array) – Wavelength array of spectrum

  • fl (array) – Flux array of spectrum

  • ivar (array, optional) – Inverse variance array. If None, will return only the normalized wavelength and flux.

  • lines (array-like, optional) – Array of which Balmer lines to include in the fit. Can be any combination of [‘alpha’, ‘beta’, ‘gamma’, ‘delta’, ‘eps’, ‘h8’]

  • skylines (bool, optional) – If True, masks out pre-selected telluric features and replace them with np.nan.

  • make_plot (bool, optional) – Whether to plot the continuum-normalized spectrum.

  • make_subplot (bool, optional) – Whether to plot each individual fit of the linear + Voigt profiles. Use for debugging.

  • make_stackedplot (bool, optional) – Plot continuum-normalized lines stacked with a common centroid, vertically displaced for clarity.

  • centroid_dict (dict, optional) – Dictionary of centroid names and theoretical wavelengths. Change this if your wavelength calibration is different from SDSS.

  • distance_dict (dict, optional) – Dictionary of centroid names and distances from the centroid to include in the normalization process. Should include the entire wings of each line and minimal continuum. No two adjacent lines should have overlapping regions.

  • sky_fill (float) – What value to replace the telluric features with on the normalized spectrum. Defaults to np.nan.

Returns

Tuple of cropped wavelength, cropped and normalized flux, and (if ivar is not None) cropped and normalized inverse variance array.

Return type

tuple

normalize_line(wl, fl, ivar, centroid, distance, make_plot=False, return_centre=False)

Continuum-normalization of a single absorption line by fitting a linear model added to a Voigt profile to the spectrum, and dividing out the linear model.

Parameters

  • wl (array) – Wavelength array of spectrum

  • fl (array) – Flux array of spectrum

  • ivar (array, optional) – Inverse variance array. If None, will return only the normalized wavelength and flux.

  • centroid (float) – The theoretical centroid of the absorption line that is being fitted, in wavelength units.

  • distance (float) – Distance in Angstroms away from the line centroid to include in the fit. Should include the entire absorption line wings with minimal continum.

  • make_plot (bool, optional) – Whether to plot the linear + Voigt fit. Use for debugging.

Returns

Tuple of cropped wavelength, cropped and normalized flux, and (if ivar is not None) cropped and normalized inverse variance array.

Return type

tuple