For many experiment, the analysis of the smalldata h5 files is not too computing intensive and the analysis team can benefit from the quick and iterative nature of the Jupyter notebooks framework over the more involved cube production.

In this section, a few template notebook for common experiments are discussed.

Common features

All templates will start with a section where the experiment and run can be defined. The large commented block should be uncommented whenever actual data are being analyzed.

Sets of alias to better find the relevant quantities in the h5 files are also defined in the following cell, together with the quantity to be used for filtering (typically i0, timing tool fit, ...).

# helper dict to find data in file
dataDict = {'alias': 'path/in/the/h5',
			...
           }

filters =  {}
filters['alias_filt1'] = [low,high]
filters['alias_filt2'] = [low,high]
	...

print('Filter selection:')
for key,value in filters.items():
	print('\t{} : {}'.format(key, value))
hist_bins = {key: 35 for key in filters.keys()}

Make sure to adapt the alias to the detectors names in your actual data.

The goodness of the filters be be evaluated in the next cell.