- Design goals
- Supported compilers
- Integration
- Five-minute tutorial
- Number range
- Common type number range
- Character range
- Bool
- Random value from std::initializer_list
- Random iterator
- Random element from array
- Container of random values
- Weighted random values
- Shuffle
- Custom distribution
- Custom Seeder
- Thread local random
- Local random
- engine
- Get engine
- Seeding
- min-value
- max-value
- 'get' without arguments
- Discard
- Is equal
- Serialize
- Deserialize
There are few ways to get working with random in C++:
- C style
srand( time(NULL) ); // seed with time since epoch
auto random_number = (rand() % 9) + 1; // get a pseudo-random integer between 1 and 9
- Problems
- should specify seed
- should write your own distribution algorithm
- There are no guarantees as to the quality of the random sequence produced.
- C++11 style
std::random_device random_device; // create object for seeding
std::mt19937 engine{random_device()}; // create engine and seed it
std::uniform_int_distribution<> dist(1,9); // create distribution for integers with [1; 9] range
auto random_number = dist(engine); // finally get a pseudo-random integer number
- Problems
- should specify seed
- should choose, create and use a chain of various objects like engines and distributions
- mt19937 uses 5000 bytes of memory for each creation (which is bad for performance if we create it too frequently)
- uncomfortable and not intuitively clear usage
- effolkronium random style
// auto seeded
auto random_number = Random::get(1, 9); // invoke 'get' method to generate a pseudo-random integer in [1; 9] range
// yep, that's all.
- Advantages
- Intuitive syntax. You can do almost everything with random by simple 'get' method, like getting simple numbers, bools, random object from given set or using custom distribution.
- Trivial integration. All code consists of a single header file
random.hpp
. That's it. No library, no subproject, no dependencies, no complex build system. The class is written in vanilla C++11. All in all, everything should require no adjustment of your compiler flags or project settings. - Usability. There are 3 versions of random:
- random_static which has static methods and static internal state. It's not thread safe but more efficient
- random_thread_local which has static methods and thread_local internal state. It's thread safe but less efficient
- random_local which has non static methods and local internal state. It can be created on the stack at local scope
- GCC 4.9 - 10.0 (and possibly later)
- Clang 3.7 - 10.0 (and possibly later)
- Microsoft Visual C++ 2015 - 2022 (and possibly later)
- As subproject
add_subdirectory(random) # path to the 'random' library root
... # create target
target_link_libraries(${TARGET} effolkronium_random) # add include path to a compiler
- As external project
First of all, build or|and install this project:
cd "path_to_root_of_the_library"
mkdir build
cd build
cmake -G"Visual Studio 15 2017" ..
cmake --build . --target install --config Release
ctest -C Release
Then, find the package by a cmake
find_package(effolkronium_random REQUIRED)
... # create target
target_link_libraries(${TARGET} effolkronium_random)
The single required source, file random.hpp
is in the include/effolkronium
directory.
All you need to do is add
#include "effolkronium/random.hpp"
// get base random alias which is auto seeded and has static API and internal state
using Random = effolkronium::random_static;
to the files you want to use effolkronium random class. That's it. Do not forget to set the necessary switches to enable C++11 (e.g., -std=c++11
for GCC and Clang).
Returns a pseudo-random number in a [first; second] range.
auto val = Random::get(-1, 1) // decltype(val) is int
// specify explicit type
auto val = Random::get<uint8_t>(-1, 1) // decltype(val) is uint8_t
// you able to use range from greater to lower
auto val = Random::get(1.l, -1.l) // decltype(val) is long double
auto val = Random::get(1.f, -1) // Error: implicit conversions are not allowed here.
Choose common type of two range arguments by std::common_type.
auto val = Random::get<Random::common>(1, 0.f) // decltype(val) is float
auto val = Random::get<Random::common>(0ul, 1ull) // decltype(val) is unsigned long long
auto val = Random::get<Random::common>(1.2l, 1.5f) // decltype(val) is long double
auto val = Random::get<Random::common>(1u, -1) // Error: prevent conversion from signed to unsigned.
Returns a pseudo-random character in a [first; second] range.
auto val = Random::get('a', 'z')
auto val = Random::get(L'㋐', L'㋾')
auto val = Random::get<wchar_t>()
Generate true with [0; 1] probability
auto val = Random::get<bool>(0.7) // true with 70% probability
auto val = Random::get<bool>() // true with 50% probability by default
auto val = Random::get<bool>(-1) // Error: assert occurred! Out of [0; 1] range
Return random value from values in a std::initializer_list
auto val = Random::get({1, 2, 3}) // val = 1 or 2 or 3
Return random iterator from iterator range or container. Iterator must be at least Input iterator. If a std::distance(first, last) == 0, return the 'last' iterator. If container is empty, return std::end(container) iterator.
std::array<int, 3> array{ {1, 2, 3} };
- Iterator range
auto randomIt = Random::get( array.begin(), array.end() );
- Container
auto randomIt = Random::get( array );
Return pointer to random element in built-in array
int array [] = {1, 2, 3};
auto randomPtr = Random::get( array );
Return container filled with random numbers. Any containers with "begin", "end" and "insert" methods are applicable
auto vec = Random::get<std::vector>(1, 9, 5); // decltype(vec) is std::vector<int> with size = 5
// Note: "reserve" method invokes automatically for performance
auto mset = Random::get<std::multiset>(1.0, 9.9, 10); // decltype(mset) is std::multiset<double> with size = 10
auto arr = Random::get<std::array, 5>('0', '9'); // decltype(arr) is std::array<char, 5>
// Warning: Returning arrays with large size could be ineficcient
auto vec = Random::get<std::vector>(1l, 9ll, 5); // decltype(vec) is std::vector<long long> with size = 5
template<typename T>
class MyContainer
{
iterator begin() {...}
iterator end() {...}
void insert(iterator after, T value) {...}
};
auto vec = Random::get<MyContainer>(1, 9, 5); // decltype(vec) is std::MyContainer<int> with size = 5
Return random iterator from map-like containers
std::unordered_map<std::string, unsigned long> nonzero_ulong_umap = {{"Orange", 1ul}, {"Apple", 2ul}, {"Banana", 3ul}};
std::unordered_map<std::string, unsigned> nonzero_uint_umap = {{"Orange", 1u}, {"Apple", 2u}, {"Banana", 3u}};
std::map<std::string, float> nonzero_float_map = {{"Orange", 1.0f}, {"Apple", 2.0f}, {"Banana", 3.0f}};
std::map<std::string, double> nonzero_double_map = {{"Orange", 1.0}, {"Apple", 2.0}, {"Banana", 3.0}};
Random::get<Random_t::weight>(nonzero_ulong_umap);
Random::get<Random_t::weight>(nonzero_uint_umap);
Random::get<Random_t::weight>(nonzero_float_map);
Random::get<Random_t::weight>(nonzero_double_map);
Reorders the elements in a given range or in all container ref
std::array<int, 3> array{ {1, 2, 3} };
- Iterator range
Random::shuffle( array.begin( ), array.end( ) )
- Container
Random::shuffle( array )
Return result from operator() of a distribution with internal random engine argument
- Template argument
// 1.f and 2.f will be forwarded to std::gamma_distribution constructor
auto result = Random::get<std::gamma_distribution<>>( 1.f, 2.f );
- Argument by reference
std::gamma_distribution<> gamma{ 1.f, 2.f };
auto result = Random::get( gamma ); // return result of gamma.operator()( engine_ )
Specify seed by which random engine will be seeded at construction time:
- Number
struct MySeeder {
unsigned operator() () {
return 42u;
}
};
// Seeded by 42
using Random = effolkronium::basic_random_static<std::mt19937, MySeeder>;
- Seed sequence
Because we can't copy std::seed_seq, the 'random' library destroy seeder instance after engine seeding. So it's safe to return seed by reference.
struct MySeeder {
// std::seed_seq isn't copyable
std::seed_seq& operator() () {
return seed_seq_;
}
std::seed_seq seed_seq_{ { 1, 2, 3, 4, 5 } };
};
// Seeded by seed_seq_ from MySeeder
using Random = effolkronium::basic_random_static<std::mt19937, MySeeder>;
- Reseed
Seed an internal random engine by a newly created Seeder instance
Random::reseed( );
It uses static methods API and data with thread_local storage which is fully thread safe (but less performance)
using Random = effolkronium::random_thread_local
// use in the same way as random_static. Thread safe
std::thread first{ [ ] { Random::get( ); } };
std::thread second{ [ ] { Random::get( ); } };
It uses non static methods API and data with auto storage which can be created on the stack at local scope
#include "effolkronium/random.hpp"
using Random_t = effolkronium::random_local
int main( ) {
Random_t localRandom{ }; // Construct on the stack
// access throughout dot
auto val = localRandom.get(-10, 10);
} // Destroy localRandom and free stack memory
Set new seed for an internal random engine.
Random::seed( 10 ); // 10 is new seed number
std::seed_seq sseq{ 1, 2, 3 };
Random::seed( sseq ); // use seed sequence here
Returns the minimum value potentially generated by the internal random-number engine
auto minVal = Random::min( );
Returns the maximum value potentially generated by the internal random-number engine
auto maxVal = Random::max( );
Returns the random number in [ Random::min( ), Random::max ] range
auto val = Random::get( );
// val is random number in [ Random::min( ), Random::max ] range
Returns reference to the internal engine.
auto& engine = Random::engine( );
std::sample(itBeg, itEnd, std::back_inserter(out), 5, Random::engine( ));
Returns copy of internal engine.
auto engine = Random::get_engine( );
Advances the internal engine's state by a specified amount. Equivalent to calling Random::get() N times and discarding the result.
Random::discard( 500 );
Compares internal pseudo-random number engine with other pseudo-random number engine.
Random::Engine otherEngine;
bool isSame = Random::is_equal( otherEngine );
Serializes the internal state of the internal pseudo-random number engine as a sequence of decimal numbers separated by one or more spaces, and inserts it to the output stream. The fill character and the formatting flags of the stream are ignored and unaffected.
std::stringstream strStream;
Random::serialize( strStream ); // the strStream now contain internal state of the Random internal engine
Restores the internal state of the internal pseudo-random number engine from the serialized representation, which was created by an earlier call to 'serialize' using a stream with the same imbued locale and the same CharT and Traits. If the input cannot be deserialized, internal engine is left unchanged and failbit is raised on input stream.
std::stringstream strStream;
Random::serialize( strStream );
// ...
Random::deserialize( strStream ); // Restore internal state of internal Random engine