Radio Astronomy Gain and Visibility Inspector
Project description
ragavi
Radio Astronomy Gain and Visibility Inspector
Introduction
- This library mainly requires
Nodejs>=8
- Install build dependencies:
** Python casacore comes as a dependency of Daskms ** Nodejs is a requirement for Bokeh and can be installed using the commands
$ sudo apt-get install curl
$ curl -sL https://deb.nodesource.com/setup_8.x | bash -
$ apt-get install -y nodejs
All python requirements are found in requirements.txt
or
To install nodejs in the virtual environment, use: nodeenv, a nodejs virtual environment. More info can be found here
Create nodejs virtual environment with:
$ nodeenv envName
and
$ . envName/bin/activate
to switch to environment.
Installation
Installation from source, working directory where source is checked out
$ pip install .
This package is available on PYPI via
$ pip install ragavi
Usage
- Ragavi currently has two segements:
Gain plotter
Visibility plotter
For the gains plotter, the name-space ragavi-vis
is used. To get help for this
$ ragavi-gains -h
To use ragavi gain plotter
$ ragavi-gains -t /path/to/your/table
Multiple tables can be plotted on the same document simply by adding them in a space separated list to the -t
/ --table
switch e.g
$ ragavi-gains -t delay/table/1/ bandpass/table/2 flux/table/3
For the visibility plotter, the name-space ragavi-vis
is used. Help can be obtained by running
$ ragavi-vis -h
To run ragavi-vis, the arguments --table
, --xaxis
and --yaxis
are basic requirements e.g.
$ ragavi-vis --ms /my/measurement/set --xaxis time --yaxis amplitude
For large datasets, it is advisable to supply at least --ymin
and --ymax
values to avoid an extra pass over the data.
Change the size (resolution) of the output aggregated image – and resulting html file size – by specifying --canvas-width
and --canvas-height
options.
The xova package is required for Averaging. It is not available on PyPi yet and therefore can be installed via:
$ pip install git+git://github.com/ska-sa/xova.git@master
License
This project is licensed under the MIT License - see license for details.
Contribute
Contributions are always welcome! Please ensure that you adhere to our coding standards pep8.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file ragavi-0.3.7.tar.gz
.
File metadata
- Download URL: ragavi-0.3.7.tar.gz
- Upload date:
- Size: 54.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.6.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 812bc7dcf903fb4eed52b41bac6dc42d9491104a79994a414f6bf9df327345d4 |
|
MD5 | cb3249b4a9b236427bb654d53845f7fe |
|
BLAKE2b-256 | 90fa064ae004e3118cbad210b9c77e555809969cdb5232dfce61f6d2dee4035b |