A comprehensive method to periodically check suspension anomalies in various OSEMs

spectrums.py - is a collection of functions that can be used to study fluctuations of various OSEM suspensions over time.

git link: https://git.ligo.org/hanford_osem/hanford_OSEM/-/blob/main/spectrums.py?ref_type=heads

How to use it:

We can git pull from the link above. In any LIGO cluster terminal or Jupyter we can use igwn-py kernel and import just the following dependency:

from spectrums Import *

# define a time segment object:
time_seg = time_segment()

In the prompt this will ask to enter a ref_time (reference time), this would be gps time when OSEMs were known to have no anomalies. Once pressed enter, it will ask for check_time, this would be another gps time which is being checked against ref_time. Finally it will ask to enter duration. For a long duration this might take a long time to execute. Keeping duration =180 (in seconds) is a reasonable choice.
This will create a time segment object as a dictionary.

Now, we can either check the OSEM fluctuations directly by running the following command:

host = 'nds.ligo-wa.caltech.edu'
osem_fluctuations(time_segments = time_seg, host=host)

This will show us available OSEMs and we can enter at least one or a list of OSEMs that we wish to investigate. It may take a few minutes to get all the plots. Checking individual OSEMs might be time consuming, a quick alternative is to check their BLRM values first:

check_blrms(time_segments = time_seg, 
            host=host, 
            fs = 256, 
            lowcut = 15, 
            highcut = 20,
            threshold = None)

Runing this function allows us to enter either one or a list of OSEMs like before to have their BLRM values printed. We can apply a threshold of choice to see which OSEM(s) look problematic. Then only check plots of those OSEMs in osem_fluctuations() function.