//===----------------------------------------------------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // REQUIRES: long_tests // // template // class discrete_distribution // template result_type operator()(_URNG& g); #include #include #include #include "test_macros.h" int main(int, char**) { { typedef std::discrete_distribution<> D; typedef std::minstd_rand G; G g; D d; const int N = 100; std::vector 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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); } return 0; }