https://github.com/josephwkania/radio_transients

Singularity containers with common radio transient search software.
https://github.com/josephwkania/radio_transients

fast-radio-bursts psrdada pulsars radio-astronomy

Last synced: 2 months ago
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Singularity containers with common radio transient search software.

• Host: GitHub
• URL: https://github.com/josephwkania/radio_transients
• Owner: josephwkania
• License: gpl-3.0
• Created: 2021-03-06T05:27:00.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2024-03-14T21:39:58.000Z (10 months ago)
• Last Synced: 2024-08-02T06:12:24.566Z (5 months ago)
• Topics: fast-radio-bursts, psrdada, pulsars, radio-astronomy
• Language: Singularity
• Homepage:
• Size: 115 KB
• Stars: 7
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• frbsoft - GitHub

README

        
# radio_transients

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[![License](https://img.shields.io/github/license/josephwkania/radio_transients?style=flat-square)]()

[![Sylabs](https://img.shields.io/badge/Hosted-Sylabs-Green.svg)](https://cloud.sylabs.io/library/josephwkania/radio_transients/radio_transients)

## Overview

These are my Singularity Recipes for common radio transient software.

There are three containers

### radio_transients

Contains everything (CPU+GPU)

 

    CUDA 10.2

    FETCH          https://github.com/devanshkv/fetch  -- In Conda environment `FE`

    heimdall       https://sourceforge.net/p/heimdall-astro/wiki/Use/

    - dedisp       https://github.com/ajameson/dedisp

    htop           https://htop.dev/

    iqrm_apollo    https://gitlab.com/kmrajwade/iqrm_apollo

    jupyterlab     https://jupyter.org/

    PRESTO         https://www.cv.nrao.edu/~sransom/presto/

    psrdada        http://psrdada.sourceforge.net/

    psrdada-python https://github.com/TRASAL/psrdada-python

    psrcat         https://www.atnf.csiro.au/people/pulsar/psrcat/download.html

    pysigproc      https://github.com/devanshkv/pysigproc

    riptide        https://github.com/v-morello/riptide

    sigproc        https://github.com/SixByNine/sigproc

    Tempo          http://tempo.sourceforge.net/

    RFIClean       https://github.com/ymaan4/RFIClean

    YAPP           https://github.com/jayanthc/yapp

    your           https://github.com/thepetabyteproject/your

Get with

`singularity pull --arch amd64 library://josephwkania/radio_transients/radio_transients:latest`

*One of FETCH's dependencies causes PRESTO's Python scripts to fail. 

This necessitated putting them in different environments. 

Everything except for PRESTO is in `RT`, which is loaded by default.

PRESTO is in `PE`, in the shell you can activate this 

with `conda activate PE`. If you need access outside the container,

you should use radio_transients:cpu, which has PRESTO in the default environment. 

### radio_transients_cpu

Contains CPU based programs

    htop

    iqrm_apollo

    jupyterlab   

    PRESTO

    psrcat

    pysigproc

    riptide

    sigproc

    Tempo 

    RFIClean

    YAPP  

    your

Get with

`singularity pull --arch amd64 library://josephwkania/radio_transients/radio_transients:cpu`  

There is an arm version `Singularity.arm`,

`singularity pull --arch arm library://josephwkania/radio_transients/radio_transients:arm`

### radio_transients_gpu

Contains gpu based programs

    CUDA 10.2

    FETCH      

    jupyterlab

    heimdall

    - dedisp

    htop 

    psrdada 

    psrdada-python

    your

Get with

`singularity pull --arch amd64 library://josephwkania/radio_transients/radio_transients:gpu`

### How to use

Your `$HOME` automatically gets mounted.

You can mount a directory with `-B /dir/on/host:/mnt`, which will mount `/dir/on/host` to `/mnt` in the container. 

For the gpu processes, you must pass `--nv` when running singularity.

`singularity shell --nv -B /data:/mnt radio_transients_gpu.sif` 

will mount `/data` to `/mnt`, give you GPU access, and drop you into the interactive shell. 

`singularity exec --nv -B /data:/mnt radio_transients_gpu.sif your_heimdall.py -f /mnt/data.fil` 

will mount `/data` to `/mnt`, give you GPU access, and run your_heimdall.py without entering the container.

All the Python scripts are installed in a Conda environment `RT`, this environment is automatically loaded.

You can see the commits and corresponding dates by running `singularity inspect radio_transients.sif`

### Sylabs Cloud

These are built on a E5 v3 family machine and uploaded to Sylabs Cloud at 

https://cloud.sylabs.io/library/josephwkania/radio_transients/radio_transients

They where last built on 27-Nov-2021

If your processor your processor is significantly older than this, you may run into problems with 

the older processor not having the whole instruction set needed. In this case, you should build

use singularity to build the image locally. 

An archival version of these (built 25-April-2021) are on Singularity Hub at: 

https://singularity-hub.org/collections/5231

[![https://www.singularity-hub.org/static/img/hosted-singularity--hub-%23e32929.svg](https://www.singularity-hub.org/static/img/hosted-singularity--hub-%23e32929.svg)](https://singularity-hub.org/collections/5231)

### Improvements

If you come across bug or have suggestions for improvements, let me know or submit a pull request.

### Thanks

To Kshitij Aggarwal for bug reports and suggestions.