In most cases, you should only have to modify part of the producer file between two flags:
########################################################## ## ## User Input start --> ## ########################################################## ... ########################################################## ## ## <-- User Input end ## ##########################################################
This user section is split in two parts, one for run-dependent parameters, usually mainly involving the more complex area detector analysis, which is likely to vary from run to run, and a run-independent part, which allows for the addition of EPICS PVs or analog inputs/outputs for example.
Run-independant variables
This will describe how to tweak some of the default data:
This is done mostly in the block in the smalldata_producer file below (<...>/smalldata_tools/producers/smd_producer.py).
########################################################## # 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=[]
EPICS PVs
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-by-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.
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.
Analog Input
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
Addition of the time tool or Wave8 traces
If you have been told you might have to reanalyze the time tool data or you have past experience and feel you can gain by doing so, you can add the event-by-event trace of the OPAL camera used for the time tool like this:
##########################################################
## User Input start -->
##########################################################
<UserData inputs described elsewhere>
##adding raw timetool traces:
#defaultDets.append(ttRawDetector(env=ds.env()))
##adding wave8 traces:
#defaultDets.append(wave8Detector('Wave8WF'))
##########################################################
## <-- User Input end
##########################################################
Time tool analysis
XTCAV values
Run-dependent variables
Area detectors analysis
In order to keep the filesizes small to avoid issue when analysis the smallData files, we try to extract the important information gleaned from areaDetectors at an event-by-event basis and only save these pieces of data. Implementation examples of each of the analysis functions that are readily available can be found in <smalldata_tools>/producers/smalldata_producer_template.py.
In general, reach out to your data and controls POC to discuss analysis needs for your experiments. The POC will make sure the functions you need are prepared in the main producer file, and you should only have to change the parameters, such as region of interest or thresholds.
Generally speaking, the parameters for each analysis functions are set from a run-dependent logic like this:
Anallysis function parameters
def getFuncParam(run):
"""
"""
if isinstance(run,str):
run=int(run)
ret_dict = {}
if run>0:
func_dict = {}
func_dict['param1'] = param1
func_dict['param2'] = param2
func_dict['param3'] = param3
ret_dict['detname'] = func_dict
return ret_dict
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