forked from mpusz/mp-units
added STL random number distributions wrappers
This commit is contained in:
Ramzi Sabra
committed by
Mateusz Pusz
Mateusz Pusz
parent
5dd9eaac87
commit
1ce7949cf5
@@ -0,0 +1,587 @@
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#include <numeric>
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#include <units/random.h>
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#include <units/physical/si/length.h>
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#include <catch2/catch.hpp>
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using namespace units;
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using namespace units::physical::si;
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TEST_CASE("uniform_int_distribution")
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{
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using Rep = std::int64_t;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::uniform_int_distribution<Qty>();
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CHECK(dist.a() == Qty::zero());
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CHECK(dist.b() == Qty::max());
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}
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SECTION ("parametrized") {
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constexpr Rep a = 5;
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constexpr Rep b = 2;
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auto stl_dist = std::uniform_int_distribution(a, b);
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auto units_dist = units::uniform_int_distribution(Qty(a), Qty(b));
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CHECK(units_dist.a() == Qty(stl_dist.a()));
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CHECK(units_dist.b() == Qty(stl_dist.b()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("uniform_real_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::uniform_real_distribution<Qty>();
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CHECK(dist.a() == Qty::zero());
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CHECK(dist.b() == Qty::one());
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}
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SECTION ("parametrized") {
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constexpr Rep a = 5.0;
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constexpr Rep b = 2.0;
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auto stl_dist = std::uniform_real_distribution(a, b);
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auto units_dist = units::uniform_real_distribution(Qty(a), Qty(b));
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CHECK(units_dist.a() == Qty(stl_dist.a()));
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CHECK(units_dist.b() == Qty(stl_dist.b()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("binomial_distribution")
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{
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using Rep = std::int64_t;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::binomial_distribution<Qty>();
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CHECK(dist.p() == 0.5);
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CHECK(dist.t() == Qty::one());
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}
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SECTION ("parametrized") {
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constexpr Rep t = 5;
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constexpr double p = 0.25;
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auto stl_dist = std::binomial_distribution(t, p);
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auto units_dist = units::binomial_distribution(Qty(t), p);
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CHECK(units_dist.p() == stl_dist.p());
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CHECK(units_dist.t() == Qty(stl_dist.t()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("negative_binomial_distribution")
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{
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using Rep = std::int64_t;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::negative_binomial_distribution<Qty>();
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CHECK(dist.p() == 0.5);
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CHECK(dist.k() == Qty::one());
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}
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SECTION ("parametrized") {
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constexpr Rep k = 5;
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constexpr double p = 0.25;
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auto stl_dist = std::negative_binomial_distribution(k, p);
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auto units_dist = units::negative_binomial_distribution(Qty(k), p);
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CHECK(units_dist.p() == stl_dist.p());
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CHECK(units_dist.k() == Qty(stl_dist.k()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("geometric_distribution")
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{
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using Rep = std::int64_t;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::geometric_distribution<Qty>();
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CHECK(dist.p() == 0.5);
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}
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SECTION ("parametrized") {
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constexpr double p = 0.25;
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auto stl_dist = std::geometric_distribution<Rep>(p);
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auto units_dist = units::geometric_distribution<Qty>(p);
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CHECK(units_dist.p() == stl_dist.p());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("poisson_distribution")
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{
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using Rep = std::int64_t;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::poisson_distribution<Qty>();
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CHECK(dist.mean() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr double mean = 5.0;
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auto stl_dist = std::poisson_distribution<Rep>(mean);
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auto units_dist = units::poisson_distribution<Qty>(mean);
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CHECK(units_dist.mean() == stl_dist.mean());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("exponential_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::exponential_distribution<Qty>();
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CHECK(dist.lambda() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr double lambda = 2.0;
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auto stl_dist = std::exponential_distribution<Rep>(lambda);
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auto units_dist = units::exponential_distribution<Qty>(lambda);
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CHECK(units_dist.lambda() == stl_dist.lambda());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("gamma_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::gamma_distribution<Qty>();
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CHECK(dist.alpha() == 1.0);
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CHECK(dist.beta() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr double alpha = 5.0;
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constexpr double beta = 2.0;
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auto stl_dist = std::gamma_distribution<Rep>(alpha, beta);
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auto units_dist = units::gamma_distribution<Qty>(alpha, beta);
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CHECK(units_dist.alpha() == stl_dist.alpha());
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CHECK(units_dist.beta() == stl_dist.beta());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("weibull_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::weibull_distribution<Qty>();
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CHECK(dist.a() == 1.0);
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CHECK(dist.b() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr Rep a = 5.0;
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constexpr Rep b = 2.0;
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auto stl_dist = std::weibull_distribution(a, b);
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auto units_dist = units::weibull_distribution<Qty>(a, b);
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CHECK(units_dist.a() == stl_dist.a());
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CHECK(units_dist.b() == stl_dist.b());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("extreme_value_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::extreme_value_distribution<Qty>();
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CHECK(dist.a() == Qty::zero());
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CHECK(dist.b() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr Rep a = 5.0;
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constexpr Rep b = 2.0;
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auto stl_dist = std::extreme_value_distribution(a, b);
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auto units_dist = units::extreme_value_distribution<Qty>(Qty(a), b);
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CHECK(units_dist.a() == Qty(stl_dist.a()));
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CHECK(units_dist.b() == stl_dist.b());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("normal_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::normal_distribution<Qty>();
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CHECK(dist.mean() == Qty::zero());
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CHECK(dist.stddev() == Qty::one());
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}
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SECTION("parametrized")
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{
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constexpr Rep mean = 5.0;
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constexpr Rep stddev = 2.0;
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auto stl_dist = std::normal_distribution(mean, stddev);
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auto units_dist = units::normal_distribution(Qty(mean), Qty(stddev));
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CHECK(units_dist.mean() == Qty(stl_dist.mean()));
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CHECK(units_dist.stddev() == Qty(stl_dist.stddev()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("lognormal_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::lognormal_distribution<Qty>();
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CHECK(dist.m() == Qty::zero());
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CHECK(dist.s() == Qty::one());
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}
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SECTION("parametrized")
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{
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constexpr Rep m = 5.0;
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constexpr Rep s = 2.0;
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auto stl_dist = std::lognormal_distribution(m, s);
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auto units_dist = units::lognormal_distribution(Qty(m), Qty(s));
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CHECK(units_dist.m() == Qty(stl_dist.m()));
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CHECK(units_dist.s() == Qty(stl_dist.s()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("chi_squared_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::chi_squared_distribution<Qty>();
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CHECK(dist.n() == 1.0);
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}
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SECTION("parametrized")
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{
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constexpr Rep n = 5.0;
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auto stl_dist = std::chi_squared_distribution(n);
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auto units_dist = units::chi_squared_distribution<Qty>(n);
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CHECK(units_dist.n() == stl_dist.n());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("cauchy_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::cauchy_distribution<Qty>();
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CHECK(dist.a() == Qty::zero());
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CHECK(dist.b() == Qty::one());
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}
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SECTION ("parametrized") {
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constexpr Rep a = 5.0;
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constexpr Rep b = 2.0;
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auto stl_dist = std::cauchy_distribution(a, b);
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auto units_dist = units::cauchy_distribution(Qty(a), Qty(b));
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CHECK(units_dist.a() == Qty(stl_dist.a()));
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CHECK(units_dist.b() == Qty(stl_dist.b()));
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("fisher_f_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::fisher_f_distribution<Qty>();
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CHECK(dist.m() == 1.0);
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CHECK(dist.n() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr Rep m = 5.0;
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constexpr Rep n = 2.0;
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auto stl_dist = std::fisher_f_distribution<Rep>(m, n);
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auto units_dist = units::fisher_f_distribution<Qty>(m, n);
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CHECK(units_dist.m() == stl_dist.m());
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CHECK(units_dist.n() == stl_dist.n());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("student_t_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto dist = units::student_t_distribution<Qty>();
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CHECK(dist.n() == 1.0);
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}
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SECTION ("parametrized") {
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constexpr Rep n = 2.0;
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auto stl_dist = std::student_t_distribution<Rep>(n);
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auto units_dist = units::student_t_distribution<Qty>(n);
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CHECK(units_dist.n() == stl_dist.n());
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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}
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}
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TEST_CASE("discrete_distribution")
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{
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using Rep = std::int64_t;
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using Qty = length<metre, Rep>;
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SECTION("default")
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{
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auto stl_dist = std::discrete_distribution<Rep>();
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auto units_dist = units::discrete_distribution<Qty>();
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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CHECK(units_dist.probabilities() == stl_dist.probabilities());
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}
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SECTION ("parametrized_input_it") {
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constexpr std::array<double, 3> weights = {1.0, 2.0, 3.0};
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auto stl_dist = std::discrete_distribution<Rep>(weights.cbegin(), weights.cend());
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auto units_dist = units::discrete_distribution<Qty>(weights.cbegin(), weights.cend());
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CHECK(units_dist.probabilities() == stl_dist.probabilities());
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}
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SECTION ("parametrized_initializer_list") {
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std::initializer_list<double> weights = {1.0, 2.0, 3.0};
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auto stl_dist = std::discrete_distribution<Rep>(weights);
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auto units_dist = units::discrete_distribution<Qty>(weights);
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CHECK(units_dist.probabilities() == stl_dist.probabilities());
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}
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SECTION ("parametrized_range") {
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constexpr std::size_t count = 3;
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constexpr double xmin = 1, xmax = 3;
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auto stl_dist = std::discrete_distribution<Rep>(count, xmin, xmax, [](double val) { return val; });
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auto units_dist = units::discrete_distribution<Qty>(count, xmin, xmax, [](double val) { return val; });
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CHECK(units_dist.probabilities() == stl_dist.probabilities());
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}
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}
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TEST_CASE("piecewise_constant_distribution")
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{
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using Rep = long double;
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using Qty = length<metre, Rep>;
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std::vector<Rep> intervals_rep_vec = {1.0, 2.0, 3.0};
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std::vector<Qty> intervals_qty_vec = {1.0q_m, 2.0q_m, 3.0q_m};
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SECTION("default")
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{
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auto stl_dist = std::piecewise_constant_distribution<Rep>();
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auto units_dist = units::piecewise_constant_distribution<Qty>();
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CHECK(units_dist.min() == Qty(stl_dist.min()));
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CHECK(units_dist.max() == Qty(stl_dist.max()));
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CHECK(stl_dist.intervals().size() == 2);
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CHECK(units_dist.intervals().size() == 2);
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CHECK(stl_dist.densities().size() == 1);
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CHECK(units_dist.densities().size() == 1);
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||||
}
|
||||
|
||||
SECTION ("parametrized_input_it") {
|
||||
constexpr std::array<Rep, 3> intervals_rep = {1.0, 2.0, 3.0};
|
||||
constexpr std::array<Qty, 3> intervals_qty = {1.0q_m, 2.0q_m, 3.0q_m};
|
||||
constexpr std::array<Rep, 3> weights = {1.0, 2.0, 3.0};
|
||||
|
||||
auto stl_dist = std::piecewise_constant_distribution<Rep>(intervals_rep.cbegin(), intervals_rep.cend(), weights.cbegin());
|
||||
auto units_dist = units::piecewise_constant_distribution<Qty>(intervals_qty.cbegin(), intervals_qty.cend(), weights.cbegin());
|
||||
|
||||
CHECK(stl_dist.intervals() == intervals_rep_vec);
|
||||
CHECK(units_dist.intervals() == intervals_qty_vec);
|
||||
CHECK(units_dist.densities() == stl_dist.densities());
|
||||
}
|
||||
|
||||
SECTION ("parametrized_initializer_list") {
|
||||
std::initializer_list<Rep> intervals_rep = {1.0, 2.0, 3.0};
|
||||
std::initializer_list<Qty> intervals_qty = {1.0q_m, 2.0q_m, 3.0q_m};
|
||||
|
||||
auto stl_dist = std::piecewise_constant_distribution<Rep>(intervals_rep, [](Rep val) { return val; });
|
||||
auto units_dist = units::piecewise_constant_distribution<Qty>(intervals_qty, [](Qty qty) { return qty.count(); });
|
||||
|
||||
CHECK(units_dist.intervals() == intervals_qty_vec);
|
||||
CHECK(units_dist.densities() == stl_dist.densities());
|
||||
}
|
||||
|
||||
SECTION ("parametrized_range") {
|
||||
constexpr std::size_t nw = 2;
|
||||
constexpr Rep xmin_rep = 1.0, xmax_rep = 3.0;
|
||||
constexpr Qty xmin_qty = 1.0q_m, xmax_qty = 3.0q_m;
|
||||
|
||||
auto stl_dist = std::piecewise_constant_distribution<Rep>(nw, xmin_rep, xmax_rep, [](Rep val) { return val; });
|
||||
auto units_dist = units::piecewise_constant_distribution<Qty>(nw, xmin_qty, xmax_qty, [](Qty qty) { return qty.count(); });
|
||||
|
||||
CHECK(units_dist.intervals() == intervals_qty_vec);
|
||||
CHECK(units_dist.densities() == stl_dist.densities());
|
||||
}
|
||||
}
|
||||
|
||||
TEST_CASE("piecewise_linear_distribution")
|
||||
{
|
||||
using Rep = long double;
|
||||
using Qty = length<metre, Rep>;
|
||||
|
||||
std::vector<Rep> intervals_rep_vec = {1.0, 2.0, 3.0};
|
||||
std::vector<Qty> intervals_qty_vec = {1.0q_m, 2.0q_m, 3.0q_m};
|
||||
|
||||
SECTION("default")
|
||||
{
|
||||
auto stl_dist = std::piecewise_linear_distribution<Rep>();
|
||||
auto units_dist = units::piecewise_linear_distribution<Qty>();
|
||||
|
||||
CHECK(units_dist.min() == Qty(stl_dist.min()));
|
||||
CHECK(units_dist.max() == Qty(stl_dist.max()));
|
||||
CHECK(stl_dist.intervals().size() == 2);
|
||||
CHECK(units_dist.intervals().size() == 2);
|
||||
CHECK(stl_dist.densities().size() == 2);
|
||||
CHECK(units_dist.densities().size() == 2);
|
||||
}
|
||||
|
||||
SECTION ("parametrized_input_it") {
|
||||
constexpr std::array<Rep, 3> intervals_rep = {1.0, 2.0, 3.0};
|
||||
constexpr std::array<Qty, 3> intervals_qty = {1.0q_m, 2.0q_m, 3.0q_m};
|
||||
constexpr std::array<Rep, 3> weights = {1.0, 2.0, 3.0};
|
||||
|
||||
auto stl_dist = std::piecewise_linear_distribution<Rep>(intervals_rep.cbegin(), intervals_rep.cend(), weights.cbegin());
|
||||
auto units_dist = units::piecewise_linear_distribution<Qty>(intervals_qty.cbegin(), intervals_qty.cend(), weights.cbegin());
|
||||
|
||||
CHECK(stl_dist.intervals() == intervals_rep_vec);
|
||||
CHECK(units_dist.intervals() == intervals_qty_vec);
|
||||
CHECK(units_dist.densities() == stl_dist.densities());
|
||||
}
|
||||
|
||||
SECTION ("parametrized_initializer_list") {
|
||||
std::initializer_list<Rep> intervals_rep = {1.0, 2.0, 3.0};
|
||||
std::initializer_list<Qty> intervals_qty = {1.0q_m, 2.0q_m, 3.0q_m};
|
||||
|
||||
auto stl_dist = std::piecewise_linear_distribution<Rep>(intervals_rep, [](Rep val) { return val; });
|
||||
auto units_dist = units::piecewise_linear_distribution<Qty>(intervals_qty, [](Qty qty) { return qty.count(); });
|
||||
|
||||
CHECK(units_dist.intervals() == intervals_qty_vec);
|
||||
CHECK(units_dist.densities() == stl_dist.densities());
|
||||
}
|
||||
|
||||
SECTION ("parametrized_range") {
|
||||
constexpr std::size_t nw = 2;
|
||||
constexpr Rep xmin_rep = 1.0, xmax_rep = 3.0;
|
||||
constexpr Qty xmin_qty = 1.0q_m, xmax_qty = 3.0q_m;
|
||||
|
||||
auto stl_dist = std::piecewise_linear_distribution<Rep>(nw, xmin_rep, xmax_rep, [](Rep val) { return val; });
|
||||
auto units_dist = units::piecewise_linear_distribution<Qty>(nw, xmin_qty, xmax_qty, [](Qty qty) { return qty.count(); });
|
||||
|
||||
CHECK(units_dist.intervals() == intervals_qty_vec);
|
||||
CHECK(units_dist.densities() == stl_dist.densities());
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user