/lofar_helpers

Primary LanguagePython

LOFAR helper scripts

These scripts are helper script for LOFAR data reduction.
Most scripts were used for imaging and recalibrating of A399-401, which are two pre-merging galaxy clusters.

Clone this full repo with: git clone https://github.com/jurjen93/lofar_helpers.git

Two standalone scripts are briefly discussed below:

Make boxes for LOFAR self-calibration

With make_boxes.py it is possible to make boxes around sources that can be extracted and self-calibrated.
Note that this script only works with Python 3.

Usage

Use make_boxes.py as a standalone script with Python 3, by running on the command line:
python make_boxes.py <FLAGS>
You can use the following flags: \

  • --file --> followed by the fits file name (and path)
  • --location --> followed by the location (path) to store the data \
  • --no_images --> don't save the images locally \
  • --ds9 --> interactive mode to validate the box selection in ds9
  • --max_boxes --> max number of boxes

The script returns the following:

  • directory with .reg region boxes.
  • directory with box images, to check the quality of the boxes.

Details

The following steps are taken in the algorithm:

  • Determine (surface brightness) pixels that go over the threshold >0.07.
  • Loop through all peak fluxes (sources) and check if these are already included in other images. If so, we stop here.
  • Check if the source is 'interesting' by comparing the outlier fluxes in the images with the outliers in a gaussian filtered version. If not, we stop here.
  • Reposition the image by taking into account the borders where we don't want to have high flux peaks or other sources. This is done by moving the center of the image and resizing.
  • We also look for islands of flux, which we find by binning 100x100 pixels and summing over these pixels. When the flux exceeds 30, we extract a box from this position.
  • If there are multiple peak fluxes (sources) we flag these as done from our list.
  • Now we save the image of the box and the .reg.

Merge solutions

With h5_merger.py it is possible to merge h5 solutions, which are a result from self-calibrating the different directions that are extracted with the boxes.
This script is compatible with both Python 2 and Python 3.

Special requirements

h5_mergers.py relies heavily on losoto: https://github.com/revoltek/losoto which works really well to work with .h5 files.

Usage

There are two ways to use this script. To use it within your script, you can just import the most important function with: from h5_merger import merge_h5

And use the following parameters:

  • h5_out --> output file name
  • h5_tables --> h5 tables to merge in list form or string (with/without wildcard)
  • ms_files --> ms files to use in list form or string (with/without wildcard)
  • convert_tec --> convert tec to phase (boolean)
  • merge_all_in_one --> choose to merge al directions into one direction
  • lin2circ --> linear to circular polarization transformation
  • circ2lin --> circular to linear polarization transformation
  • add_direction --> add default direction (phase 0 and amplitude 1)

Or you can run the script on the command line with python h5_merger.py <FLAGS>

  • -out --> output file name
  • -in --> h5 tables to merge in list form or string (with/without wildcard)
  • -ms --> ms files to use in list form or string (with/without wildcard)
  • -ct --> convert tec to phase
  • -merge_all_in_one --> choose to merge al directions into one direction
  • --lin2circ --> linear to circular polarization transformation
  • --circ2lin --> circular to linear polarization transformation
  • --add_direction --> add default direction (phase 0 and amplitude 1)

More functionalities have been added recently, which can be all listed with the help function.

Contact

Let me know if you are using this script and have any issues or suggestions for improvements. You can contact me on: jurjendejong(AT)strw.leidenuniv.nl