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ana.addCut('lightStatus/xray',0.5,1.5,'on')

ana.addCut('lightStatus/laser',0.5,1.5,'on')

We are defining an event selection called "on". At this point we only require there to be both laser and X-rays. Typically one would add requirement on the incoming intensity and, if interested in the timetool, some quality requirement on the time tool signal.

ana.addCube('cube','delay',np.arange(13.,15.,0.05),'on')

Here we are defining a cube called "cube": we give it a name (here "cube"), a variable we want to bin in (here "delay"), the bins we would like to use for the binning and lastly the name of the filter/event selection we defined previously (here "on").

cs140Dict = {'source':'cs140_rob','full':1}

ana.addToCube('cube',['ipm2/sum','ipm3/sum','diodeU/channels',cs140Dict])

Now we tell what data we would like to bin. You can either pass the names of variables in the littleData or the name of detectors in the "big" data. This is not being passed as a dictionary with the source name (the alias) and then information of what information you would like to add to the cube (main use case of the full data, passed as above asking 'full':1 as value pair - the 1 is unimportant, the code only checks the presence of the "full" key).

anaps.makeCubeData('cube')

At least we will now make the cube. Note that we are calling this on "anaps" (!). "ana" has the same function: this will only bin the data present in the smallData file (or the derived fields attached to the xarray), it will quietly ignore the variables only to be gotten from the xtc. Because this will get data from the xtc file, you will want to run this using mpi using the driver script, but checking the cube definition (correct definition of bins,....) can be done using "ana" interactively.

The cube name will be used to name the hdf5 file that will get written by the function. The "ana" function by default will NOT write a file and only return a dictionary with the binned data. It has a parameter that will make it write an hdf5 file. The "anaps" function will always write the hdf5 file as this is integral to how the events are distributed among cores and how the data is reassembled in the end.

The primary binning variable is defined in the cube definition. It either needs to be a variable in the smallData originally or an added variable. Using "delay" will create a derived variable for the X-ray-laser delay using the scan variable (if applicable), the timetool and the fast delay stage encoder value. If the bins are not passed, the code will try to use the np.unique(scanValue) which will only work for "step" scans.

In addition to the primary binning variables, you can now add more binning variables to make a higher dimensional "cube". This can be done like this:

You can pass either a list like [varname, bins] or a dict with variables names as keys and bin boundaries as values.

You can add lists of variables in the smallData, wether they were present "originally or if they were added to the data. Now there are two ways to also bin droplet data: You can either save an image based on droplets/bin or make square arrays in x/y/adu for each bin. This is specified like this:

 Data from the xtc file are added as dictionaries as described above. Option for the dictionary include:

thresAdu: require pixels in to be added image to be above threshold

thresRms: -"-