josiest/simulacrum

A framework for procedural content generation with C++20

simulacrum

A modern library for procedural content generation

Example usage

// math and algorithms
#include <simulacrum/random_walks.hpp>
#include <random>
#include <algorithm>

// data types and type constraints
#include <glm/glm.hpp>
#include <cstdint>
#include <spatula/geometry.hpp>

// i/o
#include <iostream>

namespace ranges = std::ranges;
namespace sim = simulacrum;

void print_point(glm::ivec2 const & p)
{
    std::cout << "(" << p.x << ", " << p.y << ")" << std::endl;
}

int main()
{
    // -- create resources for the walk --

    // we'll need to make our own random engine
    std::random_device seed;
    std::mt19937 rng(seed());
    glm::ivec2 const origin(0, 0);

    // reserve enough space for all the points
    std::uint32_t const N = 5;
    std::vector<glm::ivec2> points;
    points.reserve(N);
    auto into_points = std::back_inserter(points);

    // -- perform the simulation --
    using cardinal = sp::direction::cardinal;
    ranges::generate_n(into_points, N, sim::uniform_walk<cardinal>(rng, origin));
    ranges::for_each(points, print_point);
}

Possible output:

(0, 1)
(1, 1)
(0, 1)
(0, 0)
(0, -1)

Requirements

• A compiler for C++20 or newer
• spatula library

Installation

Since this is a header-only library, all you really need to do is to make sure that the compiler can see the include path that has the source code. Alternatively, you can build it with cmake:

mkdir build
cd build
cmake ..
sudo cmake --install .

If you're on windows, you'll need to run cmake --install . as adminsitrator instead of using sudo.

At this point, if you're using cmake, you can add this to your CMakeLists.txt

find_package(simulacrum REQUIRED)
...
target_link_libraries(<target> INTERFACE sim::simulacrom)

Documentation

Overview

• random_walk(rng, start, distribution
• uniform_walk(rng, start)

simulation

random_walk(rng, start, sample_space)

Simulate a random walk.

Signature

template<sp::ranged_enum Direction,
         std::uniform_random_bit_generator Engine,
         sp::vector2 Vector,
         class Distribution>

class random_walk {
public:
    random_walk(Engine & rng, Vector const & start,
                Distribution const & sample_space);
    Vector operator()();
};

Return

A function object that takes no arguments and advances the walk's position, returning the previous position.

Parameters

• rng the random number generator
• start the starting position of the walk
• sample_space the direction distribution to use when walking

Examples

#include <random>
#include <SFML/System.hpp>
#include <spatula/geometry.hpp>
#include <simulacrum/random_walks.hpp>
// ...

std::random_device seed;
std::mt19937 rng(seed());
sf::Vector2i const start(100, 100);

using direction_distribution = std::discrete_distribution<std::uint32_t>;
direction_distribution sample_direction{3, 2, 1, 1};

std::uint32_t const N = 100;
std::vector<sf::Vector2i> points;
points.reserve(N);

auto into_points = std::back_inserter(points);
using cardinal = sp::direction::cardinal;
ranges::generate_n(into_points, N,
                   sim::random_walk<cardinal>(rng, start, sample_direction));

uniform_walk(rng, start)

Simulate a uniform random walk

Signature

template<std::uniform_random_bit_generator Engine, sp::vector2 Vector>
auto uniform_walk(Engine & rng, Vector const & start);

Return

A random_walk function object with a std::uniform_int_distribution as its sample space.

Parameters

• rng the random number generator to sample from
• start where the random walk should start from

Examples

#include <glm/glm.hpp>
#include <spatula/geometry.hpp>
#include <simulacrum/random_walks.hpp>

namespace sim = simulacrum;

// ...

std::random_device seed;
std::mt19937 rng(seed());
glm::ivec2 const origin(0, 0);

std::array<glm::ivec2, 10> points;
using cardinal = sp::direction::cardinal;
ranges::generate(points, sim::uniform_walk<cardinal>(rng, origin));