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#ifndef _MULTINOMIAL_SAMPLER_HPP_
#define _MULTINOMIAL_SAMPLER_HPP_
#include <random>
#include <vector>
#include <algorithm>
class MultinomialSampler {
public:
MultinomialSampler(std::random_device& rd) :
gen_(rd()), u01_(0.0, 1.0) {}
void operator()(
std::vector<uint64_t>::iterator sampleBegin,
uint32_t n,
uint32_t k,
std::vector<double>::iterator probsBegin,
bool clearCounts = true) {
uint32_t i, j;
double u, sum;
std::vector<double> z(k+1, 0.0);
if (clearCounts) {
for (i = 0; i < k; i++) {
*(sampleBegin + i) = 0;
}
}
z[0] = 0;
for (i = 1; i <= k; i++) {
sum = 0;
for (j = 0; j < i; j++) sum+= *(probsBegin + j);
z[i] = sum;
}
// If k is small (<= 100), linear search is usually faster
if (k <= 100) {
for (j = 0; j < n; j++) {
u = u01_(gen_);
for (i = 0; i < k; i++) {
if ((z[i] < u) && (u <= z[i+1])) {
(*(sampleBegin + i))++;
break;
}
}
}
} else { // k is large enough to warrant binary search
for (j = 0; j < n; j++) {
u = u01_(gen_);
// Find the offset of the element to increment
auto it = std::lower_bound(z.begin(), z.end()-1, u);
size_t offset = static_cast<size_t>(
std::distance(z.begin(), it));
if (*it > u and offset > 0) {
offset -= 1;
}
(*(sampleBegin + offset))++;
}
}
}
private:
std::mt19937 gen_;
std::uniform_real_distribution<> u01_;
};
#endif //_MULTINOMIAL_SAMPLER_HPP_
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