Current version: 1.2.1 Updated on: 2014-03-29
pyrmsynth performs RM synthesis, either simply by Fourier transformation
(to produce a dirty image) or using the RMCLEAN method as described by
Heald, et al. (2009). It uses FFTs for the Fourier inversion and, as far as
known to the authors, this is the only RM synthesis software around that does
this. The Numpy FFTs are themselves quite fast, but in order to use them, the
data first need to be placed on a regularly spaced lambda^2 grid. For this, the
data are "gridded" by convolution with a Kaiser-Bessel Window function and
sampling at regular intervals, as described in e.g. Beatty, Nishimura, and
Pauly (IEEE Transactions in Med. Imaging, Vol 24, No. 6, 2005). This procedure
also naturally allows for the handling of non-regularly spaced frequencies.
The gridding procedure, which requires a convolution, is quite slow when implemented in pure Python, so I was re-implemented the gridding routines using Cython, which converts python-eque code into C code that can be compiled and imported into Python.
The result is a package that performs fast RM Synthesis and RM CLEAN imaging while still providing the flexibility of a Python interface.
pyrmsynth contains an application rmsynthesis.py for processing the lines of
sight in a "stack" of sky images, i.e. many polarized sky images at different
frequencies. This application was written with LOFAR
processing in mind, but should be generally useful as long as your images are
provided as a set of FITS files generaged by CASA (or something compatible).
pyrmsynth also can be used as a more generic library for writing your own
RM synthesis applications. The rm_tools sub-package contains efficient
classes for RM synthesis and RM CLEAN. You can easily write your own scripts
to do file I/O and use this package to do the actual RM synthesis computations
in an efficient manner.
Code usage:
python rmsynthesis.py
The rmsynthesis.py software, for the moment, works on sets of FITS files. Each FITS file contains images from a single sub-band, or some other subset of the observed frequencies. As a default, the code assumes all Stokes parameters to be saved in one FITS file. There is an additional option that allows for the handling of separately save Q and U FITS files. Simply put all FITS files in a single directory and the software will read them all in, stack them into a single data cube, and perform RM synthesis along each line of sight. If user defined frequency weights should be included, you have to provide a text file that gives a weight to be applied to each frequency. The name of this file MUST be "weight.txt".
The software reads in a parameter file. An example can be found in the file rmsynth.par. Copy this file elsewhere and edit to your heart's content. All of the parameters listed in the sample file must be included. A description of the various options is included in the comments in the .par file.
In addition to the parameter file, there are a couple of options that you can set when running the code. Type rmsynthesis.py -h if you need help. Right now, the options are
Options:
--version show program's version number and exit
-h, --help show this help message and exit
-p, --plot_rmsf Plot the RMSF as soon as it is computed.
-V, --stokes_v Produce a Stokes V cube after reading the fits files.
-s, --separate_stokes Indicate that the Stokes Q and U input images are stored in separate FITS files.
-f, --freq_last Indicate that NAXIS4 is the frequency axis.
-r, --rest_freq Indicate that the frequency for an image is given in the RESTFREQ header keyword
For more detailed information, please refer to the pyrmsynth wiki (https://github.com/mrbell/pyrmsynth/wiki/Using-rmsynthesis.py). Any bugs and issues can be reported to the developers via the github issue tracker.
pyrmsynth is licensed under the GPLv3.