This repository contains the optical fluxes and spectra discussed in the paper The Long-term broad-line responsivity in MKN 110. In addition to these data-sets, the script make_mkn110_figures.py produces the figures included in the paper (as well as a few additional ones).
The fluxes are included in the tab-separated file mkn110_flux_data_mr.tsv. The columns represent the MJD of the observation (except for the stacked data), the relevant emission line, the data-set to which the epoch belongs (data-sets as defined in the paper). The flux data are comprised of fluxes first published by Bischoff & Kollatschny (1999)1 and Kollatschny et al. (2001)2, fluxes derived from the available spectra (listed below), and fluxes first published here.
The spectral data are stored in the spectra directory. The spectra are in ASCII format containing two columns: wavelength (Angstrom) and flux density (erg/cm^-2/s^-1/AA). The spectra are labelled by provenance and date:
- The spectra labelled fast_YYYYMMDD were dowloaded from the FAST public archive and flux calibrated as detailed in the paper.
- The spectrum labelled sdss_mkn110_20011209 was downloaded from the SDSS public data archive.
- The spectra labelled fast_landt_YYYYMMDD were first published in Landt et al. (2008)3 and Landt et al. (2011)4.
The results of the spectral fitting are included in the tab-separated files mkn110_profile_data.tsv and mkn110_profile_data_stacked.tsv. The columns represent the data of the spectral observation (this does not apply to the stacked data), and for He II 4686 and Hbeta the normalised line flux, narrow-to-broad line component offset in km/s, and the broad line width in km/s. The files mkn110_profile_data_original.tsv and mkn110_profile_data_original_stacked.tsv contain the same information, however the flux is not normalised (erg/cm^-2/s^-1) and the offsets and line widths are in units of Angstrom.
Further details on the data-sets provided here can be found in the paper.
To run the Python script, open a terminal, navigate to the directory containing the contents of this repository, and simply enter
python make_mkn110_figures.py
When run, the script makes use of the convenience function generate_plots, which will produce each of the figures in turn. The code is structured around the classes FluxData, SpecData, ProfileFittingData, and PlotCreator, all of which are documented through docstrings. The template provided by generate_plots can also be followed as an example for the use of these classes, for any interested user.
Comments, questions, and suggestions are of course always welcome.
The script has been tested using Python 3.8.5 and requires the following packages to be installed (version numbers are those with which this script was tested):
- numpy (1.20.2)
- scipy (1.8.0)
- pandas (1.2.3)
- astropy (5.0.3)
- extinction (0.4.6)