Merge commit 'd581e9b58dbd841707deb2469c649b423358b657' into prompt/random-selector
This commit is contained in:
73
README.md
73
README.md
@@ -10,6 +10,7 @@ A templated C++20 Wave Function Collapse engine that can work with 2D grids, 3D
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- **Multiple World Types**: Built-in support for 2D/3D arrays, graphs, and Sudoku grids
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- **Coordinate Agnostic**: Works without coordinate systems using only cell IDs
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- **C++20**: Uses modern C++ features like concepts, ranges, and smart pointers
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- **Custom Random Selectors**: Pluggable random selection strategies for cell collapse, including compile-time compatible options
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## Project Structure
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@@ -31,6 +32,78 @@ nd-wfc/
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└── build/ # Build directory (generated)
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```
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## Custom Random Selectors
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The WFC library now supports customizable random selection strategies for choosing cell values during the collapse process. This allows users to implement different randomization algorithms while maintaining compile-time compatibility.
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### Features
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- **Default Random Selector**: A constexpr-compatible seed-based randomizer using linear congruential generator
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- **Advanced Random Selector**: High-quality randomization using `std::mt19937` and `std::uniform_int_distribution`
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- **Custom Selectors**: Support for user-defined selector classes that can capture state and maintain behavior between calls
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- **Lambda Support**: Selectors can be implemented as lambdas with captured variables for flexible behavior
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### Usage
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#### Basic Usage with Default Selector
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```cpp
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using MyWFC = WFC::Builder<MyWorld, int, VariableMap>
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::SetRandomSelector<WFC::DefaultRandomSelector<int>>
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::Build;
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MyWorld world(size);
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MyWFC::Run(world, seed);
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```
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#### Advanced Random Selector
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```cpp
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using MyWFC = WFC::Builder<MyWorld, int, VariableMap>
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::SetRandomSelector<WFC::AdvancedRandomSelector<int>>
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::Build;
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MyWorld world(size);
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MyWFC::Run(world, seed);
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```
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#### Custom Selector Implementation
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```cpp
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class CustomSelector {
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private:
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mutable int callCount = 0;
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public:
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size_t operator()(std::span<const int> possibleValues) const {
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// Round-robin selection
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return callCount++ % possibleValues.size();
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}
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};
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using MyWFC = WFC::Builder<MyWorld, int, VariableMap>
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::SetRandomSelector<CustomSelector>
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::Build;
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```
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#### Stateful Lambda Selector
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```cpp
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int counter = 0;
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auto selector = [&counter](std::span<const int> values) mutable -> size_t {
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return counter++ % values.size();
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};
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// Use with WFC (would need to wrap in a class for template parameter)
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```
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### Key Benefits
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1. **Compile-time Compatible**: The default selector works in constexpr contexts for compile-time WFC solving
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2. **Stateful Selection**: Selectors can maintain state between calls for deterministic or custom behaviors
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3. **Flexible Interface**: Simple function signature `(std::span<const VarT>) -> size_t` makes implementation easy
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4. **Performance**: Custom selectors can optimize for specific use cases (e.g., always pick first, weighted selection)
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## Building the Project
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### Prerequisites
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191
demos/random_selector_example.cpp
Normal file
191
demos/random_selector_example.cpp
Normal file
@@ -0,0 +1,191 @@
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/**
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* @brief Example demonstrating custom random selectors in WFC
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*
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* This example shows how to use different random selection strategies
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* in the Wave Function Collapse algorithm, including:
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* - Default constexpr random selector
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* - Advanced random selector with std::mt19937
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* - Custom lambda-based selectors
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*/
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#include <iostream>
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#include <vector>
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#include <array>
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#include <random>
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#include "../include/nd-wfc/wfc.hpp"
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// Simple test world for demonstration
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struct SimpleWorld {
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using ValueType = int;
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std::vector<int> data;
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size_t grid_size;
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SimpleWorld(size_t size) : data(size * size, 0), grid_size(size) {}
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size_t size() const { return data.size(); }
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void setValue(size_t id, int value) { data[id] = value; }
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int getValue(size_t id) const { return data[id]; }
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void print() const {
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for (size_t i = 0; i < grid_size; ++i) {
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for (size_t j = 0; j < grid_size; ++j) {
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std::cout << data[i * grid_size + j] << " ";
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}
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std::cout << std::endl;
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}
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}
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};
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int main() {
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std::cout << "=== WFC Random Selector Examples ===\n\n";
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// Example 1: Using the default constexpr random selector
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std::cout << "1. Default Random Selector (constexpr-friendly):\n";
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{
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WFC::DefaultRandomSelector<int> selector(0x12345678);
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// Test with some sample values
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std::array<int, 4> values = {1, 2, 3, 4};
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std::span<const int> span(values.data(), values.size());
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std::cout << "Possible values: ";
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for (int v : values) std::cout << v << " ";
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std::cout << "\nSelected indices: ";
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for (int i = 0; i < 8; ++i) {
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size_t index = selector(span);
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std::cout << index << "(" << values[index] << ") ";
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}
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std::cout << "\n\n";
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}
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// Example 2: Using the advanced random selector
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std::cout << "2. Advanced Random Selector (std::mt19937):\n";
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{
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std::mt19937 rng(54321);
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WFC::AdvancedRandomSelector<int> selector(rng);
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std::array<int, 5> values = {10, 20, 30, 40, 50};
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std::span<const int> span(values.data(), values.size());
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std::cout << "Possible values: ";
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for (int v : values) std::cout << v << " ";
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std::cout << "\nSelected values: ";
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for (int i = 0; i < 10; ++i) {
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size_t index = selector(span);
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std::cout << values[index] << " ";
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}
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std::cout << "\n\n";
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}
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// Example 3: Custom lambda selector that always picks the first element
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std::cout << "3. Custom Lambda Selector (always first):\n";
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{
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auto firstSelector = [](std::span<const int> values) -> size_t {
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return 0; // Always pick first
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};
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std::array<int, 3> values = {100, 200, 300};
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std::span<const int> span(values.data(), values.size());
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std::cout << "Possible values: ";
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for (int v : values) std::cout << v << " ";
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std::cout << "\nSelected values: ";
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for (int i = 0; i < 5; ++i) {
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size_t index = firstSelector(span);
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std::cout << values[index] << " ";
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}
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std::cout << "\n\n";
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}
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// Example 4: Stateful lambda selector with captured variables
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std::cout << "4. Stateful Lambda Selector (round-robin):\n";
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{
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int callCount = 0;
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auto roundRobinSelector = [&callCount](std::span<const int> values) mutable -> size_t {
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return callCount++ % values.size();
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};
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std::array<int, 3> values = {1, 2, 3};
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std::span<const int> span(values.data(), values.size());
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std::cout << "Possible values: ";
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for (int v : values) std::cout << v << " ";
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std::cout << "\nRound-robin selection: ";
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for (int i = 0; i < 9; ++i) {
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size_t index = roundRobinSelector(span);
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std::cout << values[index] << " ";
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}
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std::cout << "\n\n";
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}
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// Example 5: Custom selector with probability weighting
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std::cout << "5. Weighted Random Selector:\n";
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{
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std::mt19937 rng(99999);
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auto weightedSelector = [&rng](std::span<const int> values) -> size_t {
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// Simple weighted selection - favor earlier indices
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std::vector<double> weights;
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for (size_t i = 0; i < values.size(); ++i) {
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weights.push_back(1.0 / (i + 1.0)); // Higher weight for lower indices
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}
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std::discrete_distribution<size_t> dist(weights.begin(), weights.end());
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return dist(rng);
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};
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std::array<int, 4> values = {1, 2, 3, 4};
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std::span<const int> span(values.data(), values.size());
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std::cout << "Possible values: ";
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for (int v : values) std::cout << v << " ";
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std::cout << "\nWeighted selection ( favors lower values): ";
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for (int i = 0; i < 12; ++i) {
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size_t index = weightedSelector(span);
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std::cout << values[index] << " ";
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}
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std::cout << "\n\n";
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}
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// Example 6: Integration with WFC Builder
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std::cout << "6. WFC Builder Integration:\n";
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{
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// Define a simple WFC setup with custom random selector
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using VariableMap = WFC::VariableIDMap<int, 0, 1, 2, 3>;
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// Using default random selector
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using DefaultWFC = WFC::Builder<SimpleWorld, int, VariableMap>
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::SetRandomSelector<WFC::DefaultRandomSelector<int>>
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::Build;
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// Using advanced random selector
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using AdvancedWFC = WFC::Builder<SimpleWorld, int, VariableMap>
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::SetRandomSelector<WFC::AdvancedRandomSelector<int>>
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::Build;
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// Note: Lambda types cannot be used directly as template parameters
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// Instead, you would create a custom selector class:
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// class CustomSelector {
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// public:
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// size_t operator()(std::span<const int> values) const {
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// return values.size() > 1 ? 1 : 0;
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// }
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// };
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// using CustomWFC = WFC::Builder<SimpleWorld, int, VariableMap>
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// ::SetRandomSelector<CustomSelector>
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// ::Build;
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std::cout << "Successfully created WFC types with different random selectors:\n";
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std::cout << "- DefaultWFC with DefaultRandomSelector\n";
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std::cout << "- AdvancedWFC with AdvancedRandomSelector\n";
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std::cout << "- Custom selector classes can be created for lambda-like behavior\n";
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}
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std::cout << "\n=== Examples completed successfully! ===\n";
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return 0;
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}
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@@ -345,7 +345,8 @@ struct Callbacks
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template<typename WorldT, typename VarT,
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typename VariableIDMapT = VariableIDMap<VarT>,
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typename ConstrainerFunctionMapT = ConstrainerFunctionMap<void*>,
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typename CallbacksT = Callbacks<WorldT>>
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typename CallbacksT = Callbacks<WorldT>,
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typename RandomSelectorT = DefaultRandomSelector<VarT>>
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class WFC {
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public:
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static_assert(WorldType<WorldT>, "WorldT must satisfy World type requirements");
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@@ -359,14 +360,16 @@ public:
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WFCQueue<size_t> propagationQueue;
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Wave<MaskType> wave;
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std::mt19937& rng;
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RandomSelectorT& randomSelector;
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WFCStackAllocator& allocator;
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size_t& iterations;
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SolverState(WorldT& world, size_t variableAmount, std::mt19937& rng, WFCStackAllocator& allocator, size_t& iterations)
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SolverState(WorldT& world, size_t variableAmount, std::mt19937& rng, RandomSelectorT& randomSelector, WFCStackAllocator& allocator, size_t& iterations)
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: world(world)
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, propagationQueue{ WFCStackAllocatorAdapter<size_t>(allocator) }
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, wave{ world.size(), variableAmount, allocator }
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, rng(rng)
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, randomSelector(randomSelector)
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, allocator(allocator)
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, iterations(iterations)
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{}
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@@ -391,11 +394,13 @@ public:
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size_t iterations = 0;
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auto random = std::mt19937{ seed };
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RandomSelectorT randomSelector{ seed };
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SolverState state
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{
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world,
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ConstrainerFunctionMapT::size(),
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random,
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randomSelector,
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allocator,
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iterations
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};
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@@ -532,8 +537,13 @@ private:
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// randomly select a value from possible values
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while (availableValues)
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{
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std::uniform_int_distribution<size_t> dist(0, availableValues - 1);
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size_t randomIndex = dist(state.rng);
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// Create a span of the actual variable values for the random selector
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std::array<VarT, VariableIDMapT::ValuesRegisteredAmount> valueArray;
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for (size_t i = 0; i < availableValues; ++i) {
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valueArray[i] = VariableIDMapT::GetValue(possibleValues[i]);
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}
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std::span<const VarT> currentPossibleValues(valueArray.data(), availableValues);
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size_t randomIndex = state.randomSelector(currentPossibleValues);
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size_t selectedValue = possibleValues[randomIndex];
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{
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@@ -621,15 +631,65 @@ concept ConstrainerFunction = requires(T func, WorldT& world, size_t index, Worl
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func(world, index, value, constrainer);
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};
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/**
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* @brief Concept to validate random selector function signature
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* The function must be callable with parameters: (std::span<const VarT>) and return size_t
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*/
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template <typename T, typename VarT>
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concept RandomSelectorFunction = requires(T func, std::span<const VarT> possibleValues) {
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{ func(possibleValues) } -> std::convertible_to<size_t>;
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};
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/**
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* @brief Default constexpr random selector using a simple seed-based algorithm
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* This provides a compile-time random selection that maintains state between calls
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*/
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template <typename VarT>
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class DefaultRandomSelector {
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private:
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mutable uint32_t m_seed;
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public:
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constexpr explicit DefaultRandomSelector(uint32_t seed = 0x12345678) : m_seed(seed) {}
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constexpr size_t operator()(std::span<const VarT> possibleValues) const {
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if (possibleValues.empty()) return 0;
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// Simple linear congruential generator for constexpr compatibility
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m_seed = m_seed * 1103515245 + 12345;
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return static_cast<size_t>(m_seed) % possibleValues.size();
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}
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};
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/**
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* @brief Advanced random selector using std::mt19937 and std::uniform_int_distribution
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* This provides high-quality randomization for runtime use
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*/
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template <typename VarT>
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class AdvancedRandomSelector {
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private:
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std::mt19937& m_rng;
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public:
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explicit AdvancedRandomSelector(std::mt19937& rng) : m_rng(rng) {}
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size_t operator()(std::span<const VarT> possibleValues) const {
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if (possibleValues.empty()) return 0;
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std::uniform_int_distribution<size_t> dist(0, possibleValues.size() - 1);
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return dist(m_rng);
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}
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};
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||||
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/**
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* @brief Builder class for creating WFC instances
|
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*/
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template<typename WorldT, typename VarT = typename WorldT::ValueType, typename VariableIDMapT = VariableIDMap<VarT>, typename ConstrainerFunctionMapT = ConstrainerFunctionMap<void*>, typename CallbacksT = Callbacks<WorldT>>
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template<typename WorldT, typename VarT = typename WorldT::ValueType, typename VariableIDMapT = VariableIDMap<VarT>, typename ConstrainerFunctionMapT = ConstrainerFunctionMap<void*>, typename CallbacksT = Callbacks<WorldT>, typename RandomSelectorT = DefaultRandomSelector<VarT>>
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class Builder {
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public:
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||||
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template <VarT ... Values>
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using DefineIDs = Builder<WorldT, VarT, typename VariableIDMapT::template Merge<Values...>, ConstrainerFunctionMapT, CallbacksT>;
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using DefineIDs = Builder<WorldT, VarT, typename VariableIDMapT::template Merge<Values...>, ConstrainerFunctionMapT, CallbacksT, RandomSelectorT>;
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||||
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template <typename ConstrainerFunctionT, VarT ... CorrespondingValues>
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||||
requires ConstrainerFunction<ConstrainerFunctionT, WorldT, VarT, VariableIDMapT>
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||||
@@ -640,17 +700,21 @@ public:
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||||
ConstrainerFunctionT,
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VariableIDMap<VarT, CorrespondingValues...>,
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decltype([](WorldT&, size_t, WorldValue<VarT>, Constrainer<VariableIDMapT>&) {})
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>, CallbacksT
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||||
>, CallbacksT, RandomSelectorT
|
||||
>;
|
||||
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||||
template <typename NewCellCollapsedCallbackT>
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using SetCellCollapsedCallback = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, typename CallbacksT::template SetCellCollapsedCallbackT<NewCellCollapsedCallbackT>>;
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using SetCellCollapsedCallback = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, typename CallbacksT::template SetCellCollapsedCallbackT<NewCellCollapsedCallbackT>, RandomSelectorT>;
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template <typename NewContradictionCallbackT>
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using SetContradictionCallback = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, typename CallbacksT::template SetContradictionCallbackT<NewContradictionCallbackT>>;
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using SetContradictionCallback = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, typename CallbacksT::template SetContradictionCallbackT<NewContradictionCallbackT>, RandomSelectorT>;
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||||
template <typename NewBranchCallbackT>
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using SetBranchCallback = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, typename CallbacksT::template SetBranchCallbackT<NewBranchCallbackT>>;
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using SetBranchCallback = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, typename CallbacksT::template SetBranchCallbackT<NewBranchCallbackT>, RandomSelectorT>;
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||||
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||||
using Build = WFC<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, CallbacksT>;
|
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template <typename NewRandomSelectorT>
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requires RandomSelectorFunction<NewRandomSelectorT, VarT>
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using SetRandomSelector = Builder<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, CallbacksT, NewRandomSelectorT>;
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||||
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||||
using Build = WFC<WorldT, VarT, VariableIDMapT, ConstrainerFunctionMapT, CallbacksT, RandomSelectorT>;
|
||||
};
|
||||
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||||
} // namespace WFC
|
||||
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||||
@@ -1,4 +1,125 @@
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||||
#include <gtest/gtest.h>
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||||
#include <array>
|
||||
#include <vector>
|
||||
#include <algorithm>
|
||||
#include "nd-wfc/wfc.hpp"
|
||||
#include "nd-wfc/worlds.hpp"
|
||||
|
||||
// Test world for demonstration
|
||||
struct TestWorld {
|
||||
using ValueType = int;
|
||||
std::vector<int> data;
|
||||
|
||||
TestWorld(size_t size) : data(size, 0) {}
|
||||
size_t size() const { return data.size(); }
|
||||
void setValue(size_t id, int value) { data[id] = value; }
|
||||
int getValue(size_t id) const { return data[id]; }
|
||||
};
|
||||
|
||||
// Test random selectors
|
||||
TEST(RandomSelectorTest, DefaultRandomSelector) {
|
||||
using namespace WFC;
|
||||
|
||||
// Test default random selector with constexpr capabilities
|
||||
DefaultRandomSelector<int> selector(12345);
|
||||
|
||||
std::array<int, 3> testValues = {1, 2, 3};
|
||||
std::span<const int> span(testValues.data(), testValues.size());
|
||||
|
||||
// Test that selector returns valid indices
|
||||
size_t index1 = selector(span);
|
||||
size_t index2 = selector(span);
|
||||
|
||||
EXPECT_LT(index1, testValues.size());
|
||||
EXPECT_LT(index2, testValues.size());
|
||||
EXPECT_GE(index1, 0);
|
||||
EXPECT_GE(index2, 0);
|
||||
}
|
||||
|
||||
TEST(RandomSelectorTest, AdvancedRandomSelector) {
|
||||
using namespace WFC;
|
||||
|
||||
std::mt19937 rng(54321);
|
||||
AdvancedRandomSelector<int> selector(rng);
|
||||
|
||||
std::array<int, 4> testValues = {10, 20, 30, 40};
|
||||
std::span<const int> span(testValues.data(), testValues.size());
|
||||
|
||||
// Test that selector returns valid indices
|
||||
size_t index = selector(span);
|
||||
EXPECT_LT(index, testValues.size());
|
||||
EXPECT_GE(index, 0);
|
||||
|
||||
// Verify the selected value matches
|
||||
EXPECT_EQ(testValues[index], span[index]);
|
||||
}
|
||||
|
||||
TEST(RandomSelectorTest, CustomLambdaSelector) {
|
||||
using namespace WFC;
|
||||
|
||||
// Custom selector that always picks the first element
|
||||
auto firstSelector = [](std::span<const int> values) -> size_t {
|
||||
return 0;
|
||||
};
|
||||
|
||||
std::array<int, 3> testValues = {100, 200, 300};
|
||||
std::span<const int> span(testValues.data(), testValues.size());
|
||||
|
||||
size_t index = firstSelector(span);
|
||||
EXPECT_EQ(index, 0);
|
||||
EXPECT_EQ(span[index], 100);
|
||||
}
|
||||
|
||||
TEST(RandomSelectorTest, StatefulLambdaSelector) {
|
||||
using namespace WFC;
|
||||
|
||||
// Stateful selector that cycles through options
|
||||
uint32_t callCount = 0;
|
||||
auto cyclingSelector = [&callCount](std::span<const int> values) mutable -> size_t {
|
||||
return callCount++ % values.size();
|
||||
};
|
||||
|
||||
std::array<int, 3> testValues = {1, 2, 3};
|
||||
std::span<const int> span(testValues.data(), testValues.size());
|
||||
|
||||
// Test multiple calls
|
||||
EXPECT_EQ(cyclingSelector(span), 0);
|
||||
EXPECT_EQ(cyclingSelector(span), 1);
|
||||
EXPECT_EQ(cyclingSelector(span), 2);
|
||||
EXPECT_EQ(cyclingSelector(span), 0); // Should cycle back
|
||||
}
|
||||
|
||||
TEST(RandomSelectorTest, WFCIntegration) {
|
||||
using namespace WFC;
|
||||
|
||||
// Create a simple WFC setup with custom random selector
|
||||
using VariableMap = VariableIDMap<int, 0, 1, 2>;
|
||||
using CustomWFC = Builder<TestWorld, int, VariableMap>
|
||||
::SetRandomSelector<DefaultRandomSelector<int>>
|
||||
::Build;
|
||||
|
||||
TestWorld world(4);
|
||||
uint32_t seed = 12345;
|
||||
|
||||
// This should compile and run without errors
|
||||
// (Note: This is a basic integration test - full WFC solving would require proper constraints)
|
||||
SUCCEED();
|
||||
}
|
||||
|
||||
TEST(RandomSelectorTest, ConstexprDefaultSelector) {
|
||||
using namespace WFC;
|
||||
|
||||
// Test that default selector can be used in constexpr context
|
||||
constexpr DefaultRandomSelector<int> selector(0xDEADBEEF);
|
||||
|
||||
constexpr std::array<int, 2> testValues = {42, 84};
|
||||
constexpr auto span = std::span<const int>(testValues.data(), testValues.size());
|
||||
|
||||
// This should compile in constexpr context
|
||||
constexpr size_t index = selector(span);
|
||||
EXPECT_LT(index, testValues.size());
|
||||
EXPECT_GE(index, 0);
|
||||
}
|
||||
|
||||
int main(int argc, char **argv) {
|
||||
::testing::InitGoogleTest(&argc, argv);
|
||||
|
||||
Reference in New Issue
Block a user