MapLines.tools.line_fit

Main emission-line fitting routines used by MapLines.

MapLines.tools.line_fit

Core routines for emission-line fitting in astronomical spectra.

This module implements the main spectral fitting routines used by MapLines to model emission lines in both single spectra and IFU datacubes. The fitting procedure uses Bayesian parameter estimation based on Markov Chain Monte Carlo (MCMC) sampling.

Two main interfaces are provided:

line_fit_single

Fits emission lines in a single spectrum.

line_fit

Fits emission lines in each spaxel of an IFU datacube.

The models can include:

  • Gaussian emission-line components

  • skewed line profiles

  • Voigt or Lorentzian profiles

  • outflow components

  • power-law continuum

  • Fe II templates

The fitting procedure relies on:

  • prior definitions from YAML configuration files

  • spectral models defined in MapLines.tools.models

  • likelihood functions in MapLines.tools.priors

  • MCMC sampling implemented in MapLines.tools.mcmc

Outputs include model spectra, individual line components, and best-fit parameters saved in FITS format.

MapLines.tools.line_fit.line_fit_single(file1, file_out, file_out2, name_out2, dir_out='', colors=['blue', 'red', 'purple', 'brown', 'pink'], smoth=False, ker=2, config_lines='line_prop.yml', labplot=True, input_format='TableFits', z=0.05536, lA1=6450.0, lA2=6850.0, verbose=True, outflow=False, powlaw=False, feii=False, res_norm=True, voigt=False, lorentz=False, skew=False, error_c=True, ncpu=10, flux_f=1.0, erft=0.75, cont=False)[source]

Fit emission lines in a single astronomical spectrum.

This function performs a Bayesian fit of emission lines in a one-dimensional spectrum using an MCMC sampler. The line model and parameter priors are defined through a YAML configuration file.

Parameters:

  • file1 (str) – Input spectrum file.

  • file_out (str) – Output file name for the fitted spectral model.

  • file_out2 (str) – Output file name for the parameter results.

  • name_out2 (str) – Name used for output plots.

  • dir_out (str, optional) – Output directory for plots and results.

  • colors (list of str, optional) – Colors used for plotting individual line components.

  • smoth (bool, optional) – If True, apply smoothing to the input spectrum.

  • ker (int, optional) – Kernel size used for smoothing.

  • config_lines (str, optional) – YAML file defining emission lines and priors.

  • z (float, optional) – Redshift used to shift wavelengths to rest frame.

  • lA1 (float) – Wavelength range used for fitting.

  • lA2 (float) – Wavelength range used for fitting.

  • verbose (bool, optional) – Print best-fit parameters.

  • outflow (bool, optional) – Include an outflow component in the model.

  • powlaw (bool, optional) – Include a power-law continuum component.

  • feii (bool, optional) – Include FeII emission templates.

  • voigt (bool, optional) – Use Voigt profiles instead of Gaussian profiles.

  • lorentz (bool, optional) – Use Lorentzian profiles.

  • skew (bool, optional) – Use skewed Gaussian profiles.

  • ncpu (int, optional) – Number of CPUs used by the MCMC sampler.

Return type:

None

Notes

The fitting procedure consists of the following steps:

  1. Load the spectrum and associated uncertainties.

  2. Select the wavelength range used for fitting.

  3. Define the spectral model and parameter priors.

  4. Run an MCMC sampler to estimate the posterior distribution.

  5. Compute the best-fit model parameters.

  6. Save model spectra and parameters in FITS files.

The output FITS files include:

  • total model spectrum

  • individual emission-line components

  • input spectrum

  • error spectrum

  • derived parameters

Examples

>>> from MapLines.tools.line_fit import line_fit_single
>>> line_fit_single(
...     "spectrum.fits",
...     "fit_output",
...     "params_output",
...     "Ha_fit"
... )
MapLines.tools.line_fit.line_fit(file1, file2, file3, file_out, file_out2, name_out2, notebook=False, dir_out='', colors=['blue', 'red', 'purple', 'brown', 'pink'], z=0.05536, j_t=0, i_t=0, powlaw=False, feii=False, labplot=True, config_lines='line_prop.yml', lA1=6450.0, lA2=6850.0, outflow=False, voigt=False, lorentz=False, skew=False, error_c=True, test=False, plot_f=True, ncpu=10, pgr_bar=True, flux_f=1.0, erft=0, cont=False, res_norm=True, spe=50, scl='-16')[source]

Fit emission lines in an IFU datacube.

This routine performs emission-line fitting for each spatial pixel (spaxel) in a spectral cube. Each spectrum is fitted independently using an MCMC sampler.

Parameters:

  • file1 (str) – Input spectral cube.

  • file2 (str) – Auxiliary input file.

  • file3 (str) – Mask or error cube.

  • file_out (str) – Output FITS cube containing the fitted models.

  • file_out2 (str) – Output FITS cube containing fitted parameters.

  • name_out2 (str) – Base name used for plots.

  • notebook (bool, optional) – If True, use tqdm notebook progress bars.

  • dir_out (str, optional) – Output directory for plots.

  • z (float, optional) – Redshift of the object.

  • config_lines (str) – YAML file defining line models and priors.

  • outflow (bool, optional) – Include outflow emission components.

  • powlaw (bool, optional) – Include power-law continuum component.

  • feii (bool, optional) – Include FeII emission templates.

  • skew (bool, optional) – Use skewed Gaussian line profiles.

  • voigt (bool, optional) – Use Voigt line profiles.

  • lorentz (bool, optional) – Use Lorentzian profiles.

  • ncpu (int, optional) – Number of CPUs used for MCMC sampling.

Return type:

None

Notes

The routine iterates over all spatial pixels in the datacube, fitting emission lines independently.

The outputs are:

  • a cube containing the best-fit spectral model

  • cubes containing individual line components

  • cubes with fitted parameters

  • diagnostic plots for each spaxel (optional)

The results are stored in FITS format with extensions corresponding to each model component.