vidavis 0.0.4

Radio astronomy visibility data visualization

This is a pre-alpha package. All applications are in various phases of prototyping.

Introduction

This package currently requires the visibility data to conform to the XRADIO MeasurementSet v4.0.0 schema, input as a Zarr file path which is read into an Xarray-based XRADIO ProcessingSet. Input MSv2 file paths will be automatically converted to MSv4 zarr files with default partitioning if the necessary packages are found (see Requirements).

The Bokeh plots are created with hvPlot and optionally shown in a Panel-based GUI.

The first application added to vidavis is MsRaster, which creates raster plots of visibility data. See example below.

Installation

vidavis is available from PyPI.

Requirements

• Python 3.11 or greater

• Optionally python-casacore or casatools for MSv2 conversion

• Optionally Selenium along with a web driver to export to file using save()

Install

• pip install vidavis

MSv2 Conversion

To enable conversion from MSv2 to MSv4 with python-casacore use (this only works for Linux):

• pip install "xradio[python-casacore]"

On macOS it is required to pre-install python-casacore using:

• conda install -c conda-forge python-casacore

Exporting Plots

To enable exporting plots to file without showing the plot, using preferred web driver:

Selenium with geckodriver and Firefox (to ensure compatible versions):

• conda install -c conda-forge selenium firefox geckodriver

Selenium with ChromeDriver (Chrome), with the executable chromedriver in your PATH:

• conda install -c conda-forge selenium python-chromedriver-binary

or:

• pip install selenium chromedriver-binary

Simple MsRaster Usage Example

A simple example using the MsRaster application to create visibility raster plots:

>>> from vidavis.apps import MsRaster
>>> msr = MsRaster(ms=myms)
>>> msr.plot() # default time vs. baseline plot
>>> msr.show() # open plot in default browser tab