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Entry  Fri May 25 19:13:10 2012, Duncan Macleod, Summary, Computer Scripts / Programs, 40m summary webpages 
    Reply  Fri May 25 20:45:25 2012, Duncan Macleod, Summary, Computer Scripts / Programs, 40m summary webpages 
       Reply  Wed Jun 27 15:10:34 2012, Jamie, Update, Computer Scripts / Programs, 40m summary webpages move 
Message ID: 6686     Entry time: Fri May 25 19:13:10 2012     Reply to this: 6687
Author: Duncan Macleod 
Type: Summary 
Category: Computer Scripts / Programs 
Subject: 40m summary webpages 

40m summary webpages

 The aLIGO-style summary webpages are now running on 40m data! They are running on megatron so can be viewed from within the martian network at:

http://192.168.113.209/~controls/summary

At the moment I have configured the 5 seismic BLRMS bands, and a random set of PSL channels taken from a strip tool.

Technical notes

  • The code is in python depending heavily on the LSCSoft PyLAL and GLUE modules.
    • /home/controls/public_html/summary/bin/summary_page.py
  • The HTML is supported by a CSS script and a JS script which are held locally in the run directory, and JQuery linked from the google repo.
    • /home/controls/public_html/summary/summary_page.css
    • /home/controls/public_html/summary/pylaldq.js
  • The configuration is controlled via a single INI format file
    • /home/controls/public_html/summary/share/c1_summary_page.ini

Getting frames

Since there are no segments or triggers for C1, the only data sources are GWF frames. These are mounted from the framebuilder under /frames on megatron. There is a python script that takes in a pair of GPS times and a frame type that will locate the frames for you. This is how you use it to find T type frames (second trends) for May 25 2012:

python /home/controls/public_html/summary/bin/framecache.py --ifo C1 --gps-start-time 1021939215 --gps-end-time 1022025615 --type T -o framecache.lcf

If you don't have GPS times, you can use the tconvert tool to generate them

$ tconvert May 25
1021939215

The available frame types, as far as I'm aware are R (raw), T (seconds trends), and M (minute trends).

Running the code

The code is designed to be fairly easy to use, with most of the options set in the ini file. The code has three modes - day, month, or GPS start-stop pair. The month mode is a little sketchy so don't expect too much from it. To run in day mode:

python /home/controls/public_html/summary/bin/summary_page.py --ifo C1 --config-file /home/controls/public_html/summary/share/c1_summary_page.ini --output-dir . --verbose --data-cache framecache.lcf -SRQDUTAZBVCXH --day 20120525

Please forgive the large apparently arbitrary collection of letters, since the 40m doesn't use segments or triggers, these options disable processing of these elements, and there are quite a few of them. They correspond to --skip-something options in long form. To see all the options, run

python /home/controls/public_html/summary/bin/summary_page.py --help

There is also a convenient shell script that will run over today's data in day mode, doing everything for you. This will run framecache.py to find the frames, then run summary_page.py to generate the results in the correct output directory. To use this, run

bash /home/controls/public_html/summary/bin/c1_summary_page.sh

Configuration

Different data tabs are disabled via command link --skip-this-tab style options, but the content of tabs is controlled via the ini file. I'll try to give an overview of how to use these. The only configuration required for the Seismic BLRMS 0.1-0.3 Hz tab is the following section:

 

[data-Seismic 0.1-0.3 Hz]
channels = C1:PEM-RMS_STS1X_0p1_0p3,C1:PEM-RMS_STS1Y_0p1_0p3,C1:PEM-RMS_STS1Z_0p1_0p3
labels = STS1X,STS1Y,STS1Z
frame-type = R
plot-dataplot1 =
plot-dataplot3 =
amplitude-log = True
amplitude-lim = 1,500
amplitude-label = BLRMS motion ($\mu$m/s)

The entries can be explained as follows:

  1. '[data-Seismic 0.1-0.3 Hz] - This is the section heading. The 'data-' mark identifies this as data, and is a relic of how the code is written, the 'Seismic 0.1-0.3 Hz' part is the name of the tab to be displayed in the output.
  2. 'channels = ...' - This is a comma-separated list of channels as they are named in the frames. These must be exact so the code knows how to find them.
  3. 'labels = STS1X,STS1Y,STS1Z' - This is a comma-separated list of labels mapping channel names to something more readable for the plots, this is optional.
  4. 'frame-type = R' - This tells the code what frame type the channels are, so it can determine from which frames to read them, this is not optional, I think.
  5. 'plot-dataplotX' - This tells the code I want to run dataplotX for this tab. Each 'dataplot' is defined in it's own section, and if none of these options are given, the code tries to use all of them. In this configuration 'plot-dataplot1' tells the code I want to display the time-series of data for this tab.
  6. 'amplitude-XXX = YYY' - This gives the plotter specific information about this tab that overrides the defaults defined in the dataplotX section. The options in this example tell the plotter that when plotting amplitude on any plot, that axis should be log-scale, with a limit of 1-500 and with a specific label. The possible plotting configurations for this style of option are: 'lim', 'log', 'label', I think.

Other compatible options not used in this example are:

 

  • scale = X,Y,Z - a comma-separated list of scale factors to apply to the data. This can either be a single entry for all channels, or one per channel, nothing in between.
  • offset = X,Y,Z - another comma-separate list of DC offsets to apply to the data (before scaling, by default). DAQ noise may mean a channel that should read zero during quick times is offset by some fixed amount, so you can correct that here. Again either one for all channels, or one per channel.
  • transform = lambda x: f(x) - a python format lambda function. This is basically any mathematical function that can be applied to each data sample. By default the code constructs the function 'lambda d: scale * (d-offset)', i.e. it calibrates the data by removing the offset an applying the scale.
  • band = fmin, fmax - a low,high pair of frequencies within which to bandpass the data. Sketchy at best...
  • ripple_db = X - the ripple in the stopband of the bandpass filter
  • width = X - the width in the passband of the bandpass filter
  • rms_average = X - number of seconds in a single RMS average (combine with band to make BLRMS)
  • spectrum-segment-length = X - the length of FFT to use when calculating the spectrum, as a number of samples
  • spectrum-overlap = X - the overlap (samples) between neighbouring FFTs when calculating the spectrum
  • spectrum-time-step = X - the length (seconds) of a single median-mean average for the spectrogram

At the moment a package version issue means the spectrogram doesn't work, but the spectrum should. At the time of writing, to use the spectrum simple add 'plot-dataplot2'.

You can view the configuration file within the webpage via the 'About' link off any page.

Please e-mail any suggestions/complaints/praise to duncan.macleod@ligo.org.

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