Analyses examples#
Bool and category axes#
Taken together, the flexibility in axes and the tools to easily sum over axes can be applied to transform the way you approach analysis with histograms. For example, let’s say you are presented with the following data in a 3xN table:
Data 
Details 




True or False 

A collection of integers 
In a traditional analysis, you might bin over value
where
is_valid
is True, and then make a collection of histograms, one for
each run number. With boosthistogram, you can make a single histogram,
and use an axis for each:
value_ax = bh.axis.Regular(100, 5, 5)
bool_ax = bh.axis.Integer(0, 2, underflow=False, overflow=False)
run_number_ax = bh.axis.IntCategory([], growth=True)
Now, you can use these axes to create a single histogram that you can
fill. If you want to get a histogram of all run numbers and just the
True is_valid
selection, you can use a sum
:
h1 = hist[:, True, sum]
You can expand this example to any number of dimensions, boolean flags, and categories.