Resources for IPTA DR2 "lite" analysis. Started during the IPTA Hack Week, New York 2017.
Use gen_partim.ipynb
to produce cleaned and filtered .par
and .tim
files.
These can then be used with any GW or noise analysis.
gwb_FoM.ipynb
and bwm_FoM.ipynb
demonstrate data selection using a figure of merit.
Some enterprise
tools are provided here,
but you are better off using the most up to date enterprise extensions.
If you update any jupyter notebooks, PLEASE run a Restart & Clear Output under the Kernel menu. This helps keep change-logs cleaner.