Supporting code and data for M. Pietka et al. 2017 (https://arxiv.org/abs/1707.04265). The scripts select individual flaring events from light-curves, measure exponential rise/decline rates and create a set of diagnostic plots, including luminosity vs time-scale and time-scale probability distribution.
Individual class directories contain radio light-curves collected from the literature. The column headings in the files are as follows:
- col. 1 - Time (days)
- col. 2 - Flux density (Jy)
- col. 3 - Flux density error (Jy)
Additionally, within some of the individual class directories, the 'GBI' directories contain light-curves downloaded from the GBI database and have the following column headings:
- col. 1 - Mod. Julian Date of observation (JD-2400000.5).
- col. 2 - Local Hour Angle of observation (hours).
- col. 3 - Flux Density in Janskys at 2.25 GHz
- col. 4 - Flux Density in Janskys at 8.3 GHz.
- col. 5 - Spectral index.
- col. 6 - Estimated 1-sigma error of col. 3.
- col. 7 - Estimated 1-sigma error of col. 4.
target-distances-and-class.txt
gives a list of sources together with distances, observing frequencies and type of the light-curve. In the available sample there are four light-curve types (specified in the 'LC-type' column), each of them processed differently by the flare finder:
- Papers-s -- Pre-selected individual flares, with no information about the background emission.
- GBI-m -- Well sampled light-curves with good background emission information.
- Papers-m -- Light-curves consisting of single or multiple flares with very limited background information.
- GBI-s -- Light-curves with long time-scale flares (mostly AGN), very limited background information, and, some noisy datapoints which required smoothing.
A detailed description of the light-curve types, example plots and details of the processing can be found in Pietka et al. 2017.
To add a new source to a sample copy the light-curve data into a corresponding class directory and add the source to the 'target-distances-and-class.txt' file with the appropriate 'LC-type' label.
In the scripts
directory run run_flare_fits.py
. This script automatically selects flares from the light-curves and fits exponential function to rise/decline of each flare.
Parameters of the fits and diagnostic plots are placed in the results
directory.
combine_flares_output.py
processes individual *.json
parameters files into 'complete_rise' and 'complete_decline' files containing information about the rise/decline rates, errors and peak radio luminosity for each flare.
optional arguments:
-h, --help show this help message and exit
-j JSONFILESPATH, --jsonfilespath JSONFILESPATH
Directory in which output files (*_flares.json) from
flare finder are stored.
-t TARGETSFILEPATH, --targetsfilepath TARGETSFILEPATH
Directory in which target-distances-and-class.txt file
is stored.
Luminosity-timescale.py
- luminosity vs rise/decline time of the event figure, based on the 'complete_rise/decline' files.
optional arguments:
-h, --help show this help message and exit
-p COMPLETE_MEASUREMENTS, --complete_measurements COMPLETE_MEASUREMENTS
Directory in which *complete_rise/decline* files are
stored.
Probability-distribution.py
- probability distribution of rise/decline time-scale figure, corrected for the estimated areal densities.
Estimated areal densities, calculated to 0.1 mJy flux density limit, are stored in the sky-densities.txt
file.
Output files prob_distribution_table_averaged_X_rise/decline
contain probability distribution tables averaged over a chosen logarithmic time-step X
(default 0.5)
optional arguments:
-h, --help show this help message and exit
-p COMPLETE_MEASUREMENTS, --complete_measurements COMPLETE_MEASUREMENTS
Directory in which *complete_rise/decline* files are
stored.
-r SKY_DENSITIES, --sky_densities SKY_DENSITIES
Directory in which sky-densities.txt file is stored.
-s STEP, --step STEP Logarithmic timestep over which to average the
probability tables.