The goal of this page is to help the on-boarding of new students who are interesting in single pulse searches.

The tutorial uses PRESTO. Although PRESTO may not be the best for a computationally intensive pipelines, it is pedagogically useful by allowing the user to manually run each pipeline step.

Link to PRESTO tutorial in PRESTO's github repo

Note, I providing the commands outside of singularity. Run them with singularity as you prefer.

1. Data: short observation of a test pulsar (MY_DATA.fil)
2. Software: singularity image containing PRESTO

Become familiar with the structure and contents of the data using waterfaller.py.

Example command:

waterfaller.py --show-ts --show-spec --colour-map='viridis' -d 57 -T 100 -t 5 --downsamp=8 --scaleindep MY_DATA.fil

Parameters to play around with:

• Turn on and off dedispersion
• Go to a different time in the file
• Change the downsample factor
• Look at data with and without independently scaling each frequency channel

PRESTOs removes RFI by calculating a mask. The mask informtion is saved in a number of files, one of which can be passed to the following steps. Therefore, a new, cleaned copy of the original data file is not produced.

Example command:

rfifind -o mask_file_name -time 1.0 -zapchan N:N MY_DATA.fil

Parameters to play around with:

• Duration of processing time (-time)
• In the case of PSRFITS data: -noscales -nooffsetts
• Change thresholding parameters (-timesig, -freqsig, -chanfrac, -intfrac)
• Add channels to manually zap (-zapchan)

Note, rfifind can be quite slow to run, but it is possible under some circumstances to recalculate the mask from the mask itself rather than rerunning the entire code.

Data file: MY_DATA.fil
Original mask: mask_file_name_rfifind.mask

rfifind -o mask_file_name -nocompute -freqsig 8 -mask mask_file_name_rfifind.mask MY_DATA.fil