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 nodejsAll 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 envNameand
$ . envName/bin/activateto 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 ragaviUsage
- 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 -hTo use ragavi gain plotter
$ ragavi-gains -t /path/to/your/table -g table_type (K / B/ F/ G/ D)Multiple tables can be plotted on the same document simply by adding them in a space separated list to the -t / --table switch.
They must however be accompanied by their respective gain table type in the -g switch. e.g
$ ragavi-gains -t delay/table/1/ bandpass/table/2 flux/table/3 -g K B FFor the visibility plotter, the name-space ragavi-vis is used. Help can be obtained by running
$ ragavi-vis -hTo run ragavi-vis, the arguments --table, --xaxis and --yaxis are basic requirements e.g.
$ ragavi-vis --ms /my/measurement/set --xaxis time --yaxis amplitudeFor 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@masterLicense
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.
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