Skip to main content

Python script for interpolating FITS model images over frequency

Project description

https://img.shields.io/pypi/v/smops.svg

smops (aka Smooth Operator) is a python package for interpolating channelised FITS model images onto user-specified higher resolution frequency grid. For example, you can give smops a set of 4 per-subband model FITS images, and ask it to return 16 model images, which can then be fed back into e.g. wsclean for a predict operation. Usage:

smops --ms /ms/used/togen/images.ms -ip prefix-used-for-those-images -co 16 -order 4

Its options are:

usage: smops [-h] [-v] [-op] [-j] [-s] [-mem] -ms  -ip  -co  [-order]

Refine model images in frequency

optional arguments:
-h, --help            show this help message and exit
-v, --version         show program's version number and exit
-op , --output-prefix
                        What to prefix the new interpolated model name with.
-j , --num-threads    Number of threads to use while writing out output images
-s , --stokes         Which stokes model to extrapolate. Write as single string e.g IQUV. Required when there are multiple Stokes
                        images in a directory. Default 'I'.
-mem , --max-mem      Approximate memory cap in GB

Required arguments:
-ms , --ms            Input MS. Used for getting reference frequency
-ip , --input-prefix
                        The input image prefix. The same as the one used for wsclean
-co , --channels-out
                        Number of channels to generate out
-order , --polynomial-order
                        Order of the spectral polynomial
  • Free software: MIT license

Credits

This package is a brain child of @o-smirnov x @landmanbester and is under @ratt-ru.

It was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

smops-0.1.2.tar.gz (10.0 kB view details)

Uploaded Source

Built Distribution

smops-0.1.2-py2.py3-none-any.whl (7.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file smops-0.1.2.tar.gz.

File metadata

  • Download URL: smops-0.1.2.tar.gz
  • Upload date:
  • Size: 10.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for smops-0.1.2.tar.gz
Algorithm Hash digest
SHA256 91d30fb392d057d606aa64769cfd1081ff7053b88664b866b871c6bb6bd42b85
MD5 1894a90797ef773c341daa015eb546cd
BLAKE2b-256 13d86e733690483a84789e9a7c739f3b01f95600347df829a17a31f3967a9f72

See more details on using hashes here.

File details

Details for the file smops-0.1.2-py2.py3-none-any.whl.

File metadata

  • Download URL: smops-0.1.2-py2.py3-none-any.whl
  • Upload date:
  • Size: 7.7 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for smops-0.1.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 a24694efefb2464ea7e9ac860a1419affa33460fa4a16a97a1373bba78d3c201
MD5 2a8682d5bd22830f0b34a4d27c069c6a
BLAKE2b-256 94b9193b57eea73bbf83660b11d2ea66777960858a2456974c0b212749050100

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page