NVIDIA/nvbench
1
0
Fork 0
mirror of https://github.com/NVIDIA/nvbench.git synced 2026-04-19 22:38:52 +00:00
Code Issues Packages Projects Releases Wiki Activity

Handle empty input in mean

Browse Source
This commit is contained in:
Georgy Evtushenko
2024-01-10 09:52:14 -08:00
parent f5db89cc2b
commit 42c6bdea70
2 changed files with 30 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
nvbench/detail/statistics.cuh
View File

@@ -62,11 +62,22 @@ ValueType standard_deviation(Iter first, Iter last, ValueType mean)
return std::sqrt(variance);
}
/**
* Computes and returns the mean.
*
* If the input has fewer than 1 sample, infinity is returned.
*/
template <class It>
nvbench::float64_t compute_mean(It first, It last)
{
const auto n = std::distance(first, last);
return std::accumulate(first, last, 0.0) / static_cast<nvbench::float64_t>(n);
const auto num = std::distance(first, last);
if (num < 1)
{
return std::numeric_limits<nvbench::float64_t>::infinity();
}
return std::accumulate(first, last, 0.0) / static_cast<nvbench::float64_t>(num);
}
/**

17
testing/statistics.cu
View File

@@ -25,6 +25,22 @@
namespace statistics = nvbench::detail::statistics;
void test_mean()
{
{
std::vector<nvbench::float64_t> data{1.0, 2.0, 3.0, 4.0, 5.0};
const nvbench::float64_t actual = statistics::compute_mean(std::begin(data), std::end(data));
const nvbench::float64_t expected = 3.0;
ASSERT(std::abs(actual - expected) < 0.001);
}
{
std::vector<nvbench::float64_t> data;
const bool finite = std::isfinite(statistics::compute_mean(std::begin(data), std::end(data)));
ASSERT(!finite);
}
}
void test_std()
{
std::vector<nvbench::float64_t> data{1.0, 2.0, 3.0, 4.0, 5.0};
@@ -104,6 +120,7 @@ void test_slope_conversion()
int main()
{
test_mean();
test_std();
test_lin_regression();
test_r2();