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Avoid asking for a discrete_distribution when all weights are zero #22

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Avoid asking for a discrete_distribution when all weights are zero #22

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7 changes: 7 additions & 0 deletions include/dkm.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,13 @@ std::vector<std::array<T, N>> random_plusplus(const std::vector<std::array<T, N>
// Calculate the distance to the closest mean for each data point
auto distances = details::closest_distance(means, data);
// Pick a random point weighted by the distance from existing means
// If all distances are 0, the normalization step in std::discrete_distribution can cause a floating point
// exception, thus we check that:
double distance_sum = std::accumulate(distances.begin(), distances.end(), 0.0);
if (FP_ZERO == std::fpclassify(distance_sum)) {
// all distances zero, thus we want just a distribution with equal probability for everything
std::fill(distances.begin(), distances.end(), 1.0);
}
// TODO: This might convert floating point weights to ints, distorting the distribution for small weights
#if !defined(_MSC_VER) || _MSC_VER >= 1900
std::discrete_distribution<input_size_t> generator(distances.begin(), distances.end());
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