Energy test with optimised permutations

The energy test is a method for determining if two samples orginate from the same underlying distribution. This implimention can efficiently make use of multiple CPUs, with support for using scaled permutations as described in JINST 13 (2018) no.04, P04011.

For an implimentation that can be used with NVIDIA GPUs, which may be faster for unscaled calculations with large samples (> 10⁷ points), see Manet.

Compiling

macOS with gcc

This assumes gcc has been installed using homebrew.

g++-7 -o energy_test -std=c++1z -O3 -march=native -Wall -I. energy_test.cpp -fopenmp

Manchester machines

source /cvmfs/sft.cern.ch/lcg/external/gcc/6.2.0/x86_64-slc6-gcc62-opt/setup.sh
g++ -o energy_test -std=c++1z -O3 -march=native -Wall -I. energy_test.cpp -fopenmp

lxplus

source /cvmfs/sft.cern.ch/lcg/external/gcc/6.2.0/x86_64-slc6-gcc62-opt/setup.sh
g++ -o energy_test -std=c++1z -O3 -Wall -I. energy_test.cpp -fopenmp

Input data

The data is assumed to be in space separated text files and a script is included can create a suitable file (assuming root_pandas in installed):

./prepare_data.py  --input-fn=data/raw/sample0.root --output-fn-D0=data/csv/sample0-d0.csv --output-fn-D0bar=data/csv/sample0-d0bar.csv

Running

Run the energy test for the input data only:

time ./energy_test sample1.csv sample2.csv

Run the energy test for the input data only, limiting the input files to 10000 events:

time ./energy_test --max-events=10000 sample1.csv sample2.csv

Run the energy test with permutations for 10000 points from sample 1 and 11000 points from sample 2:

time ./energy_test --max-events-1=10000 --max-events-2=11000 --n-permutations=100 sample1.csv sample2.csv