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TimeTool results can be computed by the DAQ while data is being recorded and written directly into the .xtc files, or after data has been recorded. In AMO/XPP the time tool analysis is done by the DAQ while data is being recorded. Results can be accessed using the following epics-variables names: TTSPEC:AMPL , TTSPEC:AMPLNXT, TTSPEC:FLTPOS, TTSPEC:FLTPOSFWHM, TTSPEC:FLTPOS_PS, TTSPEC:REFAMPL or by getting the appropriate Psana.TimeTool.DataV* object from the event (either V1 or V2) from the opal camera source.

Tip
titleFiltering TT Data

If you make a plot of the measured timetool delay it is quite noisy (e.g. the laser delay vs. the measured filter position, TTSPEC:FLTPOS, while keeping the TT stage stationary). There are many outliers. This can be greatly cleaned up by filtering based on the TT peak.

I (TJ, <tjlane@slac.stanford.edu>) have found the following "vetos" on the data to work well, though they are quite conservative (throw away a decent amount of data). That said they should greatly clean up the TT response and has let me proceed in a "blind" fashion:

Require:

tt_amp(evt) > 0.05 AND

50.0 < tt_fwhm < 300.0

This was selected based on one experiment (cxii2415, run 65) and cross-validated against the current experiment (cxij8816, run 69).

 

This document covers how to run the TimeTool after data has been recorded. Starting with ana-0.16.9, a Python wrapper to the TimeTool is provided which is the preferred way to run the TimeTool algorithms. Previous to ana-0.16.9 one would use Psana modules. One would loadi the C++ TimeTool.Analyze module via a psana config file.

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