fit_SN3

sitelle.fit.fit_SN3(source, cube, v_guess=None, lines=None, return_fit_params=False, kwargs_spec={}, kwargs_bkg={}, debug=False)

Function specialized to fit sources found in the SN3 cube. The background spectrum is not fitted, due to the presence of sky lines that would bias the estimation of the velocity. | It looks very similar to fit_SN2() and the code should be refactored. It differs however in the philosophy behind the velocity estimation : this method has been designed to be performed after a SN2 fit, from which we already estimated the velocity of the source. Thus no guess is performed here.

The method can be used in a parallel process. The SNR of the spec is estimated using the stats_without_lines() method.

Parameters:
  • source (Series) – A row from a DataFrame containing detected sources. Should have columns xpos, ypos, assumed to correspond to the SN2 pixel coordinates.
  • cube (SpectralCube) – The cube taken in SN3 filter.
  • v_guess (float) – (Optional) If None, looking for the element source['v_guess']
  • lines (list of str) – (Optinal) Names of the lines to fit. If None, SN3_LINES are used, except if no v_guess has been found; then we assume it’s only a Hbeta line at very fast velocity.
  • return_fit_params (bool, Default = False) – (Optional) If True, returns the full parameters of the fit.
  • kwargs_spec (dict) – (Optional) Additional keyword arguments to be used by fit_spectrum() when fitting the source spectrum.
  • kwargs_bkg (dict) – (Optional) Additional keyword arguments to be used by fit_spectrum() when fitting the background spectrum.
  • debug (bool, Default = False) – (Optional) If True, the velocity guess is verbose.
Returns:

fit_res – A dict containg a lot of information about the fit.

Parameter Description
err estimated noise value on the spectra
guess_snr SNR guess
exit_status code to identify cause of crash
v_guess guessed velocity in km/s
chi2 chi2 computed on the residual
rchi2 reduced chi2 computed on the residual
ks_pvalue ks test computed on the residuals
logGBF log Gaussian Bayes Factor on the residuals
rchi2 reduced chi2 computed on the residual
broadening broadening estimation of the lines
broadening_err error on the brodeaning estimation
velocity estimated velocity
velocity_err error on the fitted velocity
flux_* flux estimation for * line, where * is the line name
flux_*_err error on the flux estimation for * line, where * is the line name
snr_* Estimated SNR of the * line

Return type:

dict

See also

fit_SN2()