Normalize¶
Description¶
For a given histogram or an array divide each bin/element by a sum of all the elements.
In 1d case the Normalize may also normalize by a sum of a range (subhistogram).
Inputs¶
normalize.inp— \(A\) input array or histogram. Should be 1-dimensional in case of a subrange.
Outputs¶
normalize.out— \(B\) output array of the same shape as \(A\).
Arguments¶
In case no arguments passed the input array or histogram is normalized to the hole sum.
size_t start— \(s\) first bin of the integral.size_t length— \(n\) number of bins to integrate starting from \(s\).
Tests¶
Use the following commands for the usage example and testing:
./tests/detector/test_normalize.py
Implementation¶
The result is an array/histogram, normalized by a sum:
\[B_{j,\dotsc} = \frac{A_{j,\dotsc}}{\sum\limits_{i,\dotsc}A_{i,\dotsc}}.\]
When the integration range is specified the formula is the following:
\[B_j = \frac{A_j}{\sum\limits_{i=s}^{s+n-1}A_{i}}.\]