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In most cases, you should only have to modify part of the producer file between two flags:
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##########################################################
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## User Input start -->
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##########################################################
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## <-- User Input end
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This page will describe how to tweak some of the default data:
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This is done mostly in the block in the smallsstasmalldata_producer file below (<...>/smalldata_tools/examplesproducers/smalldatasmd_producer.py).
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########################################################## # run independent parameters ########################################################## #aliases for experiment specific PVs go here epicsPV = ['s1h_w'] #tt calibration parameters (if passing None, init will use values used during recording ttCalibPars = None # (or [] or [p0, p1, p2] #aioParams=[[1],['laser'],[1.],[0.]] aioParams=[] ########################################################## ## ## <-- User Input end ## ########################################################## |
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Should you have user motors e.g. for sample motion for which you would like to save the position or if you are using a lakeshore for temperature control or have other remotely controlled data you would like to save, you will need to add those to the epicsPV line. For the exact names, ask the beam line staff. Please note that 's1h_w' is only an example/placeholder. You can get the list of possible EPICS variables names/aliases by using
"detnames
exp=<expname>:run=<run#>
-e"
This will only work when you have the analysis environment setup by calling:
source
/reg/g/psdm/etc/psconda.sh
Please note that these PVs will appear in event event, but they are NOT time matched. The time values are close, but can differ by up to second, usually it's better than that, but it is not reliable.
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Timetool calibration parameters
If we take a tt calibration run, we obtain a set of parameters for the conversion of the peak position on the timetool in pixel to ps. This should then be used in the DAQ and nothing needs to be done. Should you realize that this steps has been missed for at least some of the data or have you extracted better parameters, you can put the obtained parameters into the ttCalibPars parameter. They will be used for any new productions (e.g. for reprocessing of runs taken before the calibration was in place). If it is set to "None" or an empty list, the calibration saved in the data is used.
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Values read in from our analog inputs are timestamped at 120Hz and saved in the data using the channel name. You can select channels to be saved, give them an alias and possibly apply a (linear) conversion.
aioParams=[[1],['laser'],[1.],[0.]]
First argument (necessary if using): list of channel numbers of interest (from 0-15)
Second: argument (necessary if using): list of channel names
Third: argument (optional, defaults to 1.): conversion factor
Fourth: argument (optional, defaults to 0.): offset
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