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example.cpp
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55 lines (46 loc) · 1.9 KB
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// The OpenHiP package is licensed under the MIT "Expat" License:
//
// Copyright (c) 2022: Nico Curti.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
//
// the software is provided "as is", without warranty of any kind, express or
// implied, including but not limited to the warranties of merchantability,
// fitness for a particular purpose and noninfringement. in no event shall the
// authors or copyright holders be liable for any claim, damages or other
// liability, whether in an action of contract, tort or otherwise, arising from,
// out of or in connection with the software or the use or other dealings in the
// software.
//
//M*/
#include <array> // std :: array
#include <scorer.h> // scorer object
int main ()
{
const int32_t n_labels = 12;
std :: array < int32_t, n_labels > y_true = { {2, 0, 2, 2, 0, 1, 1, 2, 2, 0, 1, 2} };
std :: array < int32_t, n_labels > y_pred = { {0, 0, 2, 1, 0, 2, 1, 0, 2, 0, 2, 2} };
scorer score;
#ifdef _OPENMP
#pragma omp parallel shared (score)
{
#endif
score.compute_score(y_true.data(), y_pred.data(), n_labels, n_labels);
#ifdef _OPENMP
}
#endif
score.print();
return 0;
}