build_lightcurves¶

This script allows you to quickly build lightcurves of sources you have extracted using find_sources.py. As of v2.0.0 find_sources.py can now output lightcurve plots directly, this script can be helpful to run the lightcurve plotting again on a complete find_sources.py output.

Peak fluxes are used by default, integrated fluxes can be used by using the --use-int-flux flag.

Running the script¶

Prior to running this script you should query the survey data using find_sources.py with the --vast-pilot flag set to your desired epochs. Then run build_lightcurves FOLDER where FOLDER is the output folder of the previous query.

Usage¶

Most options should be self explanatory. The lightcurve plots are saved in the same directory as the input.

usage: build_lightcurves [-h] [--use-int-flux] [--quiet] [--debug] [--min-points MIN_POINTS]
                            [--min-detections MIN_DETECTIONS] [--mjd] [--grid]
                            [--yaxis-start {auto,0}] [--use-forced-for-limits] [--use-forced-for-all]
                            [--hide-legend] [--plot-dpi PLOT_DPI] [--nice NICE]
                            folder

positional arguments:
  folder

optional arguments:
  -h, --help            show this help message and exit
  --use-int-flux        Use the integrated flux, rather than peak flux (default: False)
  --quiet               Turn off non-essential terminal output. (default: False)
  --debug               Turn on debug output. (default: False)
  --min-points MIN_POINTS
                        Minimum number of epochs a source must be covered by (default: 2)
  --min-detections MIN_DETECTIONS
                        Minimum number of times a source must be detected (default: 1)
  --mjd                 Plot lightcurve in MJD rather than datetime. (default: False)
  --grid                Turn on the 'grid' in the lightcurve plot. (default: False)
  --yaxis-start {auto,0}
                        Define where the y axis on the lightcurve plot starts from. 'auto' will let
                        matplotlib decide the best range and '0' will start from 0. (default: 0)
  --use-forced-for-limits
                        Use the forced fits values instead of upper limits. (default: False)
  --use-forced-for-all  Use the forced fits for all datapoints. (default: False)
  --hide-legend         Don't show the legend on the final plot. (default: False)
  --plot-dpi PLOT_DPI   Specify the DPI of all saved figures. (default: 150)
  --nice NICE           Set nice level. (default: 5)

Last update: July 18, 2023
Created: May 6, 2021