Using Filter Parameters after turboSETI Completes

Sometimes, when running turboSETI (or the FindDoppler Python class object), one or more of the 3 filtering parameter values (minimum drift rate, maximum drift rate, and minimum SNR) are guessed, misspecified, or omitted. It is desirable to have a second chance at filtering out dedoppler top hits that are not interesting for analysis (E.g. RFI). Also, this will reduce the number of plots (PNG files) produced which then need to be pruned manually.

This release of turbo_seti adds 2 courses of action that can be taken after the turboSETI execution:

• With a new utility (dat_filter), apply one or more of the 3 above filtering parameters to permanently update the DAT file produced by turboSETI.
• In the plotSETI program or through the use of the find_event_pipeline API, specify values for one or more of the 3 filtering parameters. Note that in this case, the DAT file is not updated.

For example, suppose turboSETI has produced xx.dat from xx.h5 with drift rates varying from -0.5 to 0.5. All of the SNR values are acceptable but we'd like to avoid signals with drift rate absolute values below 0.1 and above 0.4. Then, the following dat_filter execution will permanently purge the signals near 0 drift rates:

dat_filter -m 0.1 -M 0.4 xx.dat

Alternatively, without modifying xx.dat, we could use plotSETI with new parameters instead. Assume that both xx.h5 and xx.dat are in the same directory abc. Then, the following execution will do event analysis and produce plots without permanently purging the signals near 0 drift rates from xx.dat:

plotSETI -m 0.1 -M 0.4 abc

The latter might be a useful tool for experimentation.