/IPTA_DR2_analysis

Primary LanguageJupyter Notebook

IPTA DR2 analysis

Resources for IPTA DR2 "lite" analysis. Started during the IPTA Hack Week, New York 2017.

How to use

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.

contributing

If you update any jupyter notebooks, PLEASE run a Restart & Clear Output under the Kernel menu. This helps keep change-logs cleaner.