| //===----------------------------------------------------------------------===// |
| // |
| // The LLVM Compiler Infrastructure |
| // |
| // This file is distributed under the University of Illinois Open Source |
| // License. See LICENSE.TXT for details. |
| // |
| //===----------------------------------------------------------------------===// |
| |
| // <random> |
| |
| // template<class IntType = int> |
| // class discrete_distribution |
| |
| // template<class _URNG> result_type operator()(_URNG& g); |
| |
| #include <random> |
| #include <vector> |
| #include <cassert> |
| |
| int main() |
| { |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| D d; |
| const int N = 100; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| assert((double)u[i]/N == prob[i]); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {.3}; |
| D d(p0, p0+1); |
| const int N = 100; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| assert((double)u[i]/N == prob[i]); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {.75, .25}; |
| D d(p0, p0+2); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {0, 1}; |
| D d(p0, p0+2); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| assert((double)u[0]/N == prob[0]); |
| assert((double)u[1]/N == prob[1]); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {1, 0}; |
| D d(p0, p0+2); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| assert((double)u[0]/N == prob[0]); |
| assert((double)u[1]/N == prob[1]); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {.3, .1, .6}; |
| D d(p0, p0+3); |
| const int N = 10000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {0, 25, 75}; |
| D d(p0, p0+3); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {25, 0, 75}; |
| D d(p0, p0+3); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {25, 75, 0}; |
| D d(p0, p0+3); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {0, 0, 1}; |
| D d(p0, p0+3); |
| const int N = 100; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {0, 1, 0}; |
| D d(p0, p0+3); |
| const int N = 100; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {1, 0, 0}; |
| D d(p0, p0+3); |
| const int N = 100; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| { |
| typedef std::discrete_distribution<> D; |
| typedef std::minstd_rand G; |
| G g; |
| double p0[] = {33, 0, 0, 67}; |
| D d(p0, p0+3); |
| const int N = 1000000; |
| std::vector<D::result_type> u(d.max()+1); |
| for (int i = 0; i < N; ++i) |
| { |
| D::result_type v = d(g); |
| assert(d.min() <= v && v <= d.max()); |
| u[v]++; |
| } |
| std::vector<double> prob = d.probabilities(); |
| for (int i = 0; i <= d.max(); ++i) |
| if (prob[i] != 0) |
| assert(std::abs((double)u[i]/N - prob[i]) / prob[i] < 0.001); |
| else |
| assert(u[i] == 0); |
| } |
| } |