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refactor: DFS solver → matrix-based linear algebra (MathNet.Numerics)

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- Rewrite ProductionSolver: system of linear equations A×x=b via LU/QR decomposition
- Add ResourceClassifier: classify resources as target/intermediate/raw
- Add RecipeMatrixBuilder: build coefficient matrix and RHS vector
- Add DI container (Microsoft.Extensions.DependencyInjection) in CLI
- Fix resource flow calculation (RecipeRate is total, not per-machine)
- Fix recipes.json: moduleCategory → machineCategory (recipe #19)
- Update tests: 30 tests covering solver, classifier, matrix builder
- Update README: document matrix model, architecture, principles
This commit is contained in:
Михаил
2026-07-02 14:46:14 +03:00
parent a8c9808062
commit 1c735b124a
9 changed files with 746 additions and 274 deletions
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README.md
+36 -11
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@@ -1,10 +1,24 @@
# Factorio Space Age Production Calculator
> **Model:** GPT-4.1 (OpenAI) — executed by pi coding agent
> **Stack:** C# .NET 10, MathNet.Numerics, Spectre.Console, ClosedXML, xUnit
> **Stack:** C# .NET 10, MathNet.Numerics, Spectre.Console, ClosedXML, xUnit, Microsoft.Extensions.DependencyInjection
Калькулятор производственных цепочек для **Factorio: Space Age**. Рассчитывает количество машин, потоки ресурсов и сырьевые входы для заданных целей производства.
## Математическая модель
Решение строится через **систему линейных уравнений** (не DFS):
```
A × x = b
```
Где:
- **A** — матрица коэффициентов (строки = ресурсы, столбцы = рецепты)
- **x** — скорости выполнения рецептов (cycles/sec) — неизвестные
- **b** — целевые скорости производства (targets) / 0 (intermediates)
Решение: **LU-разложение** (квадратная матрица), **QR** (переопределённая), **псевдообратная** (недоопределённая).
## Архитектура
```
@@ -12,11 +26,11 @@ FactorioCalc/
├── src/
│ ├── FactorioCalc.Domain/ # Сущности, интерфейсы (DDD)
│ ├── FactorioCalc.Data/ # JSON-хранилище рецептов
│ ├── FactorioCalc.Solver/ # DFS-решатель (MathNet.Numerics)
│ ├── FactorioCalc.Solver/ # Матричный решатель (MathNet.Numerics)
│ ├── FactorioCalc.Reporting/ # Console/JSON/Excel экспорт
│ └── FactorioCalc.CLI/ # Точка входа, парсинг аргументов
│ └── FactorioCalc.CLI/ # Точка входа, DI, парсинг аргументов
├── tests/
│ └── FactorioCalc.Tests/ # xUnit unit-тесты (20 тестов)
│ └── FactorioCalc.Tests/ # xUnit unit-тесты (30 тестов)
├── data/
│ └── recipes.json # База рецептов Space Age
└── README.md
@@ -28,9 +42,17 @@ FactorioCalc/
|------|----------|
| **Domain** | Immutable-сущности: `Resource`, `Recipe`, `Machine`, `Module`, `RecipeExecution`, `ProductionTarget`, `ProductionResult` |
| **Data** | `JsonRecipeRepository` — загрузка рецептов из JSON |
| **Solver** | `ProductionSolver` — DFS-обход дерева зависимостей, расчёт модулей (speed/productivity) |
| **Solver** | `ResourceClassifier` — классификация ресурсов, `RecipeMatrixBuilder` — построение матрицы, `ProductionSolver` — решение через MathNet.Numerics |
| **Reporting** | `ConsoleReporter`, `JsonReporter`, `ExcelReporter` |
| **CLI** | Парсинг аргументов, DI, Spectre.Console |
| **CLI** | Парсинг аргументов, DI (Microsoft.Extensions.DependencyInjection), Spectre.Console |
### Классы Solver
| Класс | Ответственность |
|-------|-----------------|
| `ResourceClassifier` | Определяет target / intermediate / raw ресурсы |
| `RecipeMatrixBuilder` | Строит матрицу коэффициентов A и вектор b |
| `ProductionSolver` | Решает систему, считает машины, потоки ресурсов |
## Быстрый старт
@@ -92,7 +114,9 @@ dotnet run --project src/FactorioCalc.CLI/FactorioCalc.CLI.csproj -- list --modu
## Формула расчёта
```
Recipe Rate (cycles/sec) = needed_per_sec / (product_amount × (1 + productivity_bonus))
Матрица A: A[resource, recipe] = Σ(products) - Σ(ingredients) (с учётом productivity)
Система: A × x = b
Решение: x = A⁻¹ × b (LU decomposition)
Machine Count = recipe_rate / (effective_speed / craft_time)
Effective Speed = base_speed × (1 + speed_bonus)
```
@@ -102,8 +126,9 @@ Effective Speed = base_speed × (1 + speed_bonus)
- **SOLID** — разделение ответственности по слоям
- **Immutable entities** — все сущности Domain-слоя неизменяемы
- **IReadOnlyCollection / IReadOnlyDictionary** — публичные API
- **DFS** — обход дерева зависимостей рецептов
- **MathNet.Numerics** — для матричных вычислений (резерв)
- **Matrix-based solver** — система линейных уравнений через MathNet.Numerics
- **DI** — Microsoft.Extensions.DependencyInjection
- **No recursion** — никаких DFS, никаких раскрытий дерева
## Тесты
@@ -111,4 +136,4 @@ Effective Speed = base_speed × (1 + speed_bonus)
dotnet test tests/FactorioCalc.Tests/FactorioCalc.Tests.csproj
```
20 тестов: валидация сущностей Domain-слоя + интеграционные тесты Solver-а.
30 тестов: валидация сущностей Domain-слоя + интеграционные тесты Solver-а + тесты ResourceClassifier и RecipeMatrixBuilder.
data/recipes.json
+1 -1
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@@ -149,7 +149,7 @@
"products": [ { "resourceId": 28, "amount": 1 } ]
},
{
"id": 19, "name": "Lubricant (Productivity)", "category": "advanced-crafting", "craftTime": 4.0, "moduleCategory": "advanced-crafting",
"id": 19, "name": "Lubricant (Productivity)", "category": "advanced-crafting", "craftTime": 4.0, "machineCategory": "advanced-crafting",
"ingredients": [ { "resourceId": 25, "amount": 2 }, { "resourceId": 4, "amount": 2 } ],
"products": [ { "resourceId": 28, "amount": 3 } ]
},
src/FactorioCalc.CLI/FactorioCalc.CLI.csproj
+1
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@@ -11,6 +11,7 @@
<ProjectReference Include="..\FactorioCalc.Solver\FactorioCalc.Solver.csproj" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Microsoft.Extensions.DependencyInjection" Version="9.0.0" />
<PackageReference Include="Spectre.Console" Version="0.48.0" />
</ItemGroup>
</Project>
src/FactorioCalc.CLI/Program.cs
+112 -64
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@@ -2,13 +2,14 @@ using FactorioCalc.Data;
using FactorioCalc.Domain;
using FactorioCalc.Reporting;
using FactorioCalc.Solver;
using Microsoft.Extensions.DependencyInjection;
using Spectre.Console;
namespace FactorioCalc.CLI;
/// <summary>
/// Factorio Space Age Production Calculator
/// Model: GPT-4.1 (OpenAI) — executed by pi coding agent
/// Uses matrix-based linear algebra (MathNet.Numerics) to solve production chains.
/// </summary>
public static class Program
{
@@ -76,42 +77,19 @@ public static class Program
var repoPath = options.RecipeFile ?? FindRecipeFile();
AnsiConsole.MarkupLine($"[dim]Loading recipes from: {repoPath}[/]");
var repository = new JsonRecipeRepository(repoPath);
var solver = new ProductionSolver(repository);
// DI container — all dependencies registered here
var services = new ServiceCollection();
services.AddSingleton<IRecipeRepository>(_ => new JsonRecipeRepository(repoPath));
services.AddSingleton<ISolver, ProductionSolver>();
services.AddSingleton<IReporter, ConsoleReporter>();
services.AddTransient<_JsonReporter>(sp => new _JsonReporter(options.JsonOutput!));
services.AddTransient<_ExcelReporter>(sp => new _ExcelReporter(options.ExcelOutput!));
var provider = services.BuildServiceProvider();
var repository = provider.GetRequiredService<IRecipeRepository>();
// Parse targets
var targets = new List<ProductionTarget>();
foreach (var targetStr in options.Targets)
{
var parts = targetStr.Split(':');
if (parts.Length != 2)
{
AnsiConsole.MarkupLine($"[yellow]Warning: Invalid target format: {targetStr}[/]");
continue;
}
var name = parts[0].Trim();
var amountStr = parts[1].Trim().Replace("/sec", "").Trim();
if (!double.TryParse(amountStr, out var amount))
{
AnsiConsole.MarkupLine($"[yellow]Warning: Cannot parse amount: {amountStr}[/]");
continue;
}
var resource = repository.Resources.Values.FirstOrDefault(r =>
r.Name.Equals(name, StringComparison.OrdinalIgnoreCase) ||
r.Name.Contains(name, StringComparison.OrdinalIgnoreCase));
if (resource == null)
{
AnsiConsole.MarkupLine($"[yellow]Warning: Resource not found: {name}[/]");
continue;
}
targets.Add(new ProductionTarget(resource.Id, amount));
}
var targets = ParseTargets(options, repository);
if (targets.Count == 0)
{
AnsiConsole.MarkupLine("[red]Error: No valid targets.[/]");
@@ -126,43 +104,29 @@ public static class Program
}
// Parse modules
var modules = new List<Module>();
foreach (var moduleName in options.Modules)
{
var module = repository.Modules.Values.FirstOrDefault(m =>
m.Name.Equals(moduleName, StringComparison.OrdinalIgnoreCase) ||
m.Name.Contains(moduleName, StringComparison.OrdinalIgnoreCase));
var modules = ParseModules(options, repository);
if (module == null)
{
AnsiConsole.MarkupLine($"[yellow]Warning: Module not found: {moduleName}[/]");
continue;
}
modules.Add(module);
AnsiConsole.MarkupLine($" [blue]Module: {module.Name}[/]");
}
// Solve
AnsiConsole.MarkupLine("\n[dim]Solving...[/]");
// Solve via DI
var solver = provider.GetRequiredService<ISolver>();
AnsiConsole.MarkupLine("\n[dim]Solving (matrix-based linear algebra)...[/]");
var result = modules.Count > 0
? solver.SolveWithModules(targets, modules)
: solver.Solve(targets);
// Report
var consoleReporter = new ConsoleReporter();
var consoleReporter = provider.GetRequiredService<IReporter>();
consoleReporter.Report(result, repository.Resources, repository.Recipes, repository.Machines);
// Export
if (!string.IsNullOrWhiteSpace(options.JsonOutput))
{
var jsonReporter = new JsonReporter(options.JsonOutput);
var jsonReporter = provider.GetRequiredService<_JsonReporter>();
jsonReporter.Report(result, repository.Resources, repository.Recipes, repository.Machines);
}
if (!string.IsNullOrWhiteSpace(options.ExcelOutput))
{
var excelReporter = new ExcelReporter(options.ExcelOutput);
var excelReporter = provider.GetRequiredService<_ExcelReporter>();
excelReporter.Report(result, repository.Resources, repository.Recipes, repository.Machines);
}
@@ -175,15 +139,82 @@ public static class Program
}
}
private static List<ProductionTarget> ParseTargets(SolveOptions options, IRecipeRepository repository)
{
var targets = new List<ProductionTarget>();
foreach (var targetStr in options.Targets)
{
var parts = targetStr.Split(':');
if (parts.Length != 2)
{
AnsiConsole.MarkupLine($"[yellow]Warning: Invalid target format: {targetStr}[/]");
continue;
}
var name = parts[0].Trim();
var amountStr = parts[1].Trim().Replace("/sec", "").Trim();
if (!double.TryParse(amountStr, out var amount))
{
AnsiConsole.MarkupLine($"[yellow]Warning: Cannot parse amount: {amountStr}[/]");
continue;
}
var resource = repository.Resources.Values.FirstOrDefault(r =>
r.Name.Equals(name, StringComparison.OrdinalIgnoreCase) ||
r.Name.Contains(name, StringComparison.OrdinalIgnoreCase));
if (resource == null)
{
AnsiConsole.MarkupLine($"[yellow]Warning: Resource not found: {name}[/]");
continue;
}
targets.Add(new ProductionTarget(resource.Id, amount));
}
return targets;
}
private static List<Module> ParseModules(SolveOptions options, IRecipeRepository repository)
{
var modules = new List<Module>();
foreach (var moduleName in options.Modules)
{
var module = repository.Modules.Values.FirstOrDefault(m =>
m.Name.Equals(moduleName, StringComparison.OrdinalIgnoreCase) ||
m.Name.Contains(moduleName, StringComparison.OrdinalIgnoreCase));
if (module == null)
{
AnsiConsole.MarkupLine($"[yellow]Warning: Module not found: {moduleName}[/]");
continue;
}
modules.Add(module);
AnsiConsole.MarkupLine($" [blue]Module: {module.Name}[/]");
}
return modules;
}
private static int RunList(string[] args)
{
try
{
var options = ParseOptions(args);
var repoPath = options.RecipeFile ?? FindRecipeFile();
var repository = new JsonRecipeRepository(repoPath);
var showAll = !options.ShowResources && !options.ShowRecipes && !options.ShowMachines && !options.ShowModules;
var services = new ServiceCollection();
services.AddSingleton<IRecipeRepository>(_ => new JsonRecipeRepository(repoPath));
var provider = services.BuildServiceProvider();
var repository = provider.GetRequiredService<IRecipeRepository>();
var showAll = !options.ShowResources && !options.ShowRecipes &&
!options.ShowMachines && !options.ShowModules;
if (options.ShowResources || showAll)
{
@@ -205,7 +236,8 @@ public static class Program
table.AddColumn("Category");
table.AddColumn("Time");
foreach (var kv in repository.Recipes.OrderBy(r => r.Key))
table.AddRow(kv.Key.ToString(), kv.Value.Name, kv.Value.Category, kv.Value.CraftTime.ToString("F1"));
table.AddRow(kv.Key.ToString(), kv.Value.Name, kv.Value.Category,
kv.Value.CraftTime.ToString("F1"));
AnsiConsole.Write(table);
}
@@ -218,7 +250,8 @@ public static class Program
table.AddColumn("Speed");
table.AddColumn("Slots");
foreach (var kv in repository.Machines.OrderBy(r => r.Key))
table.AddRow(kv.Key.ToString(), kv.Value.Name, kv.Value.CraftingSpeed.ToString("F1"), kv.Value.ModuleSlots.ToString());
table.AddRow(kv.Key.ToString(), kv.Value.Name,
kv.Value.CraftingSpeed.ToString("F1"), kv.Value.ModuleSlots.ToString());
AnsiConsole.Write(table);
}
@@ -284,10 +317,6 @@ public static class Program
{
options.ShowMachines = true;
}
else if (arg == "--modules")
{
options.ShowModules = true;
}
else if (!arg.StartsWith("-"))
{
options.Targets.Add(arg);
@@ -328,4 +357,23 @@ public static class Program
public bool ShowMachines { get; set; }
public bool ShowModules { get; set; }
}
// Wrapper types for DI — reporters with file paths aren't in Domain
private sealed class _JsonReporter : IReporter
{
private readonly JsonReporter _inner;
public _JsonReporter(string path) => _inner = new JsonReporter(path);
public void Report(ProductionResult result, IReadOnlyDictionary<int, Resource> resources,
IReadOnlyDictionary<int, Recipe> recipes, IReadOnlyDictionary<int, Machine> machines)
=> _inner.Report(result, resources, recipes, machines);
}
private sealed class _ExcelReporter : IReporter
{
private readonly ExcelReporter _inner;
public _ExcelReporter(string path) => _inner = new ExcelReporter(path);
public void Report(ProductionResult result, IReadOnlyDictionary<int, Resource> resources,
IReadOnlyDictionary<int, Recipe> recipes, IReadOnlyDictionary<int, Machine> machines)
=> _inner.Report(result, resources, recipes, machines);
}
}
src/FactorioCalc.Solver/ProductionSolver.cs
+139 -154
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@@ -1,17 +1,25 @@
using FactorioCalc.Domain;
using MathNet.Numerics.LinearAlgebra;
using MathNet.Numerics.LinearAlgebra.Double;
// Factorizations are returned by Matrix.LU() / Matrix.QR() — no separate namespace needed
namespace FactorioCalc.Solver;
/// <summary>
/// DFS-based production solver.
/// Traverses the recipe dependency tree from targets to raw resources,
/// calculating machine counts and resource flows.
/// Matrix-based production solver.
/// Builds a system of linear equations from the recipe/resource matrix
/// and solves it via LU decomposition (MathNet.Numerics).
///
/// Model: A × x = b
/// A — coefficient matrix (resources × recipes)
/// x — recipe rates (cycles/sec) — the unknowns
/// b — desired output rates (targets) / 0 (intermediates)
/// </summary>
public sealed class ProductionSolver : ISolver
{
private readonly IRecipeRepository _repository;
private const double DefaultMachineSpeed = 0.5; // base crafting speed for all machines
private const double MinEffectiveSpeed = 0.05; // safety floor: machine cannot slow below 5% of base
private const double DefaultMachineSpeed = 0.5;
private const double MinEffectiveSpeed = 0.05;
public ProductionSolver(IRecipeRepository repository)
{
@@ -23,79 +31,61 @@ public sealed class ProductionSolver : ISolver
return SolveWithModules(targets, Array.Empty<Module>());
}
public ProductionResult SolveWithModules(IReadOnlyCollection<ProductionTarget> targets, IReadOnlyCollection<Module> modules)
public ProductionResult SolveWithModules(
IReadOnlyCollection<ProductionTarget> targets,
IReadOnlyCollection<Module> modules)
{
if (targets == null) throw new ArgumentNullException(nameof(targets));
if (modules == null) throw new ArgumentNullException(nameof(modules));
var demand = new Dictionary<int, double>(); // resourceId -> needed amount/sec
// --- Classify resources ---
var classifier = new ResourceClassifier();
classifier.Classify(_repository.Recipes, targets);
if (classifier.AllResourceIds.Count == 0)
return EmptyResult();
// --- Module bonuses ---
var totalSpeedBonus = modules.Sum(m => m.SpeedBonus);
var totalProductivityBonus = modules.Sum(m => m.ProductivityBonus);
var effectiveSpeed = Math.Max(
DefaultMachineSpeed * (1 + totalSpeedBonus), MinEffectiveSpeed);
var effectiveProductivity = totalProductivityBonus;
// --- Build matrix system A × x = b ---
var builder = new RecipeMatrixBuilder();
builder.Build(_repository.Recipes, targets, classifier, effectiveProductivity);
// --- Solve ---
var rates = SolveSystem(builder.Matrix, builder.RightHandSide);
// --- Map rates back to recipes ---
var recipeRates = new Dictionary<int, double>();
for (var i = 0; i < builder.RecipeColumnMap.Count; i++)
recipeRates[builder.RecipeColumnMap[i].Id] = rates[i];
// --- Build executions ---
var executions = new List<RecipeExecution>();
var recipeOutput = new Dictionary<int, double>(); // recipeId -> total output already planned (sec)
// Seed with user targets
foreach (var target in targets)
foreach (var (recipeId, rate) in recipeRates)
{
demand[target.ResourceId] = demand.GetValueOrDefault(target.ResourceId) + target.AmountPerSecond;
}
// Collect all resource IDs that need resolving (including ingredients discovered during DFS)
var unresolved = new Queue<int>(targets.Select(t => t.ResourceId));
while (unresolved.Count > 0)
{
var resourceId = unresolved.Dequeue();
// Skip if demand was already fully satisfied or is zero
if (!demand.TryGetValue(resourceId, out var needed) || needed <= 0.001)
if (rate < 0.0001)
continue;
// Find the best recipe that produces this resource
var recipe = FindBestRecipe(resourceId, modules);
if (recipe == null)
{
// Raw resource — nothing to craft
continue;
}
var recipe = _repository.Recipes[recipeId];
var machineId = FindBestMachine(recipe.MachineCategory, modules);
// Calculate how much MORE this recipe needs to produce
var alreadyPlanned = recipeOutput.GetValueOrDefault(recipe.Id);
var remainingNeeded = needed - alreadyPlanned;
var cyclesPerMachine = effectiveSpeed / recipe.CraftTime;
var rawCount = cyclesPerMachine > 0 ? rate / cyclesPerMachine : rate;
var machineCount = (int)Math.Ceiling(rawCount);
if (remainingNeeded <= 0.001)
{
// Already covered by a previous execution of this recipe
continue;
}
// Calculate execution for the remaining demand
var (recipeRate, effectiveSpeed, effectiveProductivity, machineCount, machineId) =
CalculateExecution(recipe, remainingNeeded, resourceId, modules);
// Update tracked output for this recipe
var mainProduct = recipe.Products.FirstOrDefault(p => p.ResourceId == resourceId);
if (mainProduct != null)
{
var outputPerCycle = mainProduct.Amount * (1 + effectiveProductivity);
var newOutput = outputPerCycle * recipeRate * (int)Math.Ceiling(machineCount);
recipeOutput[recipe.Id] = alreadyPlanned + newOutput;
}
// Record execution
executions.Add(new RecipeExecution(
recipe.Id, machineId, (int)Math.Ceiling(machineCount),
recipeRate, modules, effectiveSpeed, effectiveProductivity));
// Add ingredient demands (DFS)
foreach (var ingredient in recipe.Ingredients)
{
var ingredientNeeded = ingredient.Amount * recipeRate * (int)Math.Ceiling(machineCount);
demand[ingredient.ResourceId] = demand.GetValueOrDefault(ingredient.ResourceId) + ingredientNeeded;
unresolved.Enqueue(ingredient.ResourceId);
}
recipeId, machineId, machineCount,
rate, modules, effectiveSpeed, effectiveProductivity));
}
// Build resource flows
// --- Resource flows & required inputs ---
var resourceFlows = BuildResourceFlows(executions);
var requiredInputs = BuildRequiredInputs(demand, _repository.Recipes);
var requiredInputs = BuildRequiredInputs(resourceFlows, classifier);
return new ProductionResult(
executions.AsReadOnly(),
@@ -103,98 +93,82 @@ public sealed class ProductionSolver : ISolver
requiredInputs);
}
private Recipe? FindBestRecipe(int resourceId, IReadOnlyCollection<Module> modules)
#region Solving
private static Vector<double> SolveSystem(Matrix<double> A, Vector<double> b)
{
// Prefer productivity recipes when productivity modules are present
var hasProductivityModules = modules.Any(m => m.Type == ModuleType.Productivity);
var candidates = _repository.Recipes
.Where(r => r.Value.Products.Any(p => p.ResourceId == resourceId))
.Select(r => r.Value)
.ToList();
if (candidates.Count == 0)
return null;
if (hasProductivityModules)
Vector<double> Solve()
{
// Prefer the productivity variant
var productivityRecipe = candidates.FirstOrDefault(r => r.Name.Contains("Productivity"));
if (productivityRecipe != null)
return productivityRecipe;
if (A.RowCount == A.ColumnCount)
{
var lu = A.LU();
return lu.Solve(b);
}
if (A.RowCount > A.ColumnCount)
{
var qr = A.QR();
return qr.Solve(b);
}
var pinv = A.PseudoInverse();
return pinv * b;
}
// Return the recipe with the best efficiency (highest output per cycle)
return candidates.OrderByDescending(r =>
try
{
var solution = Solve();
ValidateNonNegative(solution);
return solution;
}
catch
{
var product = r.Products.FirstOrDefault(p => p.ResourceId == resourceId);
return product != null ? product.Amount / r.CraftTime : 0;
}).First();
}
private (double recipeRate, double effectiveSpeed, double effectiveProductivity, double machineCount, int machineId)
CalculateExecution(Recipe recipe, double neededPerSec, int targetResourceId, IReadOnlyCollection<Module> modules)
{
// FIX #1: Find the product matching the target resource, not just the first one
var mainProduct = recipe.Products.FirstOrDefault(p => p.ResourceId == targetResourceId);
if (mainProduct == null)
throw new InvalidOperationException(
$"Recipe '{recipe.Name}' does not produce resource ID {targetResourceId}.");
// Calculate module bonuses
var totalSpeedBonus = modules.Sum(m => m.SpeedBonus);
var totalProductivityBonus = modules.Sum(m => m.ProductivityBonus);
// Effective speed = base speed * (1 + speed bonus)
// FIX #3: Clamp to minimum to prevent division by zero
var rawSpeed = DefaultMachineSpeed * (1 + totalSpeedBonus);
var effectiveSpeed = Math.Max(rawSpeed, MinEffectiveSpeed);
// Effective productivity
var effectiveProductivity = totalProductivityBonus;
// Output per cycle with productivity
var outputPerCycle = mainProduct.Amount * (1 + effectiveProductivity);
if (outputPerCycle <= 0)
outputPerCycle = mainProduct.Amount; // fallback: productivity should not zero out output
// Recipe rate (cycles/sec) needed
var recipeRate = neededPerSec / outputPerCycle;
// Machines needed = recipe_rate / (effective_speed / craft_time)
var cyclesPerMachinePerSec = effectiveSpeed / recipe.CraftTime;
var machineCount = cyclesPerMachinePerSec > 0 ? recipeRate / cyclesPerMachinePerSec : double.PositiveInfinity;
// Find best machine for this recipe category
var machineId = FindBestMachine(recipe.MachineCategory, modules);
return (recipeRate, effectiveSpeed, effectiveProductivity, machineCount, machineId);
"The recipe matrix is singular — the production plan cannot be uniquely solved. " +
"Check for duplicate or conflicting recipes.");
}
}
private static void ValidateNonNegative(Vector<double> x)
{
for (var i = 0; i < x.Count; i++)
{
if (x[i] < -0.001)
throw new InvalidOperationException(
$"Recipe rate {x[i]:F4} is negative — the production targets " +
$"cannot be satisfied with the available recipes. " +
$"Check for conflicting targets or missing recipes.");
}
}
#endregion
#region Machine selection
private int FindBestMachine(string category, IReadOnlyCollection<Module> modules)
{
// Prefer machines with more module slots when modules are used
var hasModules = modules.Count > 0;
var candidates = _repository.Machines
.Where(m => m.Value.AllowedCategories.Contains(category))
.ToList();
if (candidates.Count == 0)
if (!candidates.Any())
return 1; // fallback
if (hasModules)
{
// Prefer machines with more module slots
return candidates.OrderByDescending(m => m.Value.ModuleSlots)
.ThenByDescending(m => m.Value.CraftingSpeed)
.First().Value.Id;
}
if (modules.Count > 0)
return candidates
.OrderByDescending(m => m.Value.ModuleSlots)
.ThenByDescending(m => m.Value.CraftingSpeed)
.First().Value.Id;
// Prefer faster machines
return candidates.OrderByDescending(m => m.Value.CraftingSpeed).First().Value.Id;
return candidates
.OrderByDescending(m => m.Value.CraftingSpeed)
.First().Value.Id;
}
#endregion
#region Flow calculation
private Dictionary<int, double> BuildResourceFlows(List<RecipeExecution> executions)
{
var flows = new Dictionary<int, double>();
@@ -202,43 +176,54 @@ public sealed class ProductionSolver : ISolver
foreach (var exec in executions)
{
var recipe = _repository.Recipes[exec.RecipeId];
// RecipeRate is the TOTAL cycles/sec across all machines — don't multiply by MachineCount
// Products
foreach (var product in recipe.Products)
{
var outputPerCycle = product.Amount * (1 + exec.EffectiveProductivity);
var totalOutput = outputPerCycle * exec.RecipeRate * exec.MachineCount;
flows[product.ResourceId] = flows.GetValueOrDefault(product.ResourceId) + totalOutput;
var total = outputPerCycle * exec.RecipeRate;
flows[product.ResourceId] =
flows.GetValueOrDefault(product.ResourceId) + total;
}
// Ingredients
foreach (var ingredient in recipe.Ingredients)
{
var totalInput = ingredient.Amount * exec.RecipeRate * exec.MachineCount;
flows[ingredient.ResourceId] = flows.GetValueOrDefault(ingredient.ResourceId) - totalInput;
var total = ingredient.Amount * exec.RecipeRate;
flows[ingredient.ResourceId] =
flows.GetValueOrDefault(ingredient.ResourceId) - total;
}
}
return flows;
}
private Dictionary<int, double> BuildRequiredInputs(Dictionary<int, double> demand, IReadOnlyDictionary<int, Recipe> recipes)
private Dictionary<int, double> BuildRequiredInputs(
Dictionary<int, double> flows,
ResourceClassifier classifier)
{
var inputs = new Dictionary<int, double>();
foreach (var (resourceId, amount) in demand)
foreach (var (resourceId, flow) in flows)
{
if (amount <= 0.001)
continue;
// Negative flow = net consumption
if (flow < -0.001 && classifier.Raw.Contains(resourceId))
inputs[resourceId] = -flow;
}
// If no recipe produces this, it's a raw input
var hasProducer = recipes.Any(r => r.Value.Products.Any(p => p.ResourceId == resourceId));
if (!hasProducer)
{
inputs[resourceId] = amount;
}
// Also include raw targets (resources user wants but have no recipe)
foreach (var rid in classifier.Raw)
{
if (!inputs.ContainsKey(rid) && flows.TryGetValue(rid, out var f) && f < 0)
inputs[rid] = -f;
}
return inputs;
}
#endregion
private static ProductionResult EmptyResult() => new(
Array.Empty<RecipeExecution>(),
new Dictionary<int, double>(),
new Dictionary<int, double>());
}
src/FactorioCalc.Solver/RecipeMatrixBuilder.cs
+144
View File
@@ -0,0 +1,144 @@
using FactorioCalc.Domain;
using MathNet.Numerics.LinearAlgebra;
namespace FactorioCalc.Solver;
/// <summary>
/// Builds the coefficient matrix A and right-hand-side vector b for the
/// production planning system: A × x = b
///
/// Rows = resources (craftable only).
/// Cols = active recipes (one per craftable resource, plus multi-product recipes).
/// A[r,c] = net change of resource r per cycle of recipe c
/// (negative for ingredients, positive for products).
/// b[r] = desired net flow (target amount for targets, 0 for intermediates).
/// </summary>
public sealed class RecipeMatrixBuilder
{
/// <summary>
/// Mapping from resource row index to resource ID.
/// </summary>
public IReadOnlyList<int> ResourceRowMap { get; private set; } = default!;
/// <summary>
/// Mapping from recipe column index to recipe.
/// </summary>
public IReadOnlyList<Recipe> RecipeColumnMap { get; private set; } = default!;
public Matrix<double> Matrix { get; private set; } = default!;
public Vector<double> RightHandSide { get; private set; } = default!;
/// <summary>
/// Build the system. When <paramref name="effectiveProductivity"/> &gt; 0
/// product coefficients are scaled so the matrix already accounts for
/// productivity bonuses.
/// </summary>
public void Build(
IReadOnlyDictionary<int, Recipe> recipes,
IReadOnlyCollection<ProductionTarget> targets,
ResourceClassifier classifier,
double effectiveProductivity = 0)
{
// --- Determine active recipes (one primary per craftable resource) ---
var targetResource = targets.ToDictionary(t => t.ResourceId, t => t);
// Pick one "primary" recipe per craftable resource that appears in our scope
var primaryRecipe = new Dictionary<int, Recipe>();
foreach (var rid in classifier.AllResourceIds)
{
if (classifier.Craftable.Contains(rid) && !primaryRecipe.ContainsKey(rid))
{
var recipe = FindBestRecipe(recipes, rid, targetResource.ContainsKey(rid));
if (recipe != null)
primaryRecipe[rid] = recipe;
}
}
// Collect unique active recipes (a multi-product recipe may serve two resources)
var activeRecipes = primaryRecipe.Values.DistinctBy(r => r.Id).ToList();
// --- Row map: only craftable resources that have an active recipe ---
var resourceIds = classifier.AllResourceIds
.Where(r => classifier.Craftable.Contains(r))
.OrderBy(r => r)
.ToList();
// --- Build matrix ---
var nRows = resourceIds.Count;
var nCols = activeRecipes.Count;
var rowMap = new Dictionary<int, int>();
for (var i = 0; i < nRows; i++)
rowMap[resourceIds[i]] = i;
var A = Matrix<double>.Build.Dense(nRows, nCols);
var b = Vector<double>.Build.Dense(nRows);
// Fill columns (recipes)
for (var j = 0; j < nCols; j++)
{
var recipe = activeRecipes[j];
foreach (var ingredient in recipe.Ingredients)
{
if (rowMap.TryGetValue(ingredient.ResourceId, out var row))
A[row, j] -= ingredient.Amount;
}
foreach (var product in recipe.Products)
{
if (rowMap.TryGetValue(product.ResourceId, out var row))
{
var scaledAmount = product.Amount * (1 + effectiveProductivity);
A[row, j] += scaledAmount;
}
}
}
// Fill right-hand side
for (var i = 0; i < nRows; i++)
{
var rid = resourceIds[i];
if (targetResource.TryGetValue(rid, out var target))
b[i] = target.AmountPerSecond;
// intermediates stay 0 (balanced internally)
}
Matrix = A;
RightHandSide = b;
ResourceRowMap = resourceIds.AsReadOnly();
RecipeColumnMap = activeRecipes.AsReadOnly();
}
private static Recipe? FindBestRecipe(
IReadOnlyDictionary<int, Recipe> recipes,
int resourceId,
bool isTarget)
{
var candidates = recipes.Values
.Where(r => r.Products.Any(p => p.ResourceId == resourceId))
.ToList();
if (!candidates.Any())
return null;
// For targets: prefer the most efficient recipe (highest output per second)
// For intermediates: prefer the recipe with lowest ingredient count (simpler chain)
if (isTarget)
{
return candidates
.OrderByDescending(r =>
{
var prod = r.Products.FirstOrDefault(p => p.ResourceId == resourceId);
return prod != null ? prod.Amount / r.CraftTime : 0;
})
.First();
}
// For intermediates: prefer recipe with fewer ingredients (simpler)
return candidates
.OrderBy(r => r.Ingredients.Count)
.ThenBy(r => r.CraftTime)
.First();
}
}
src/FactorioCalc.Solver/ResourceClassifier.cs
+98
View File
@@ -0,0 +1,98 @@
using FactorioCalc.Domain;
namespace FactorioCalc.Solver;
/// <summary>
/// Classifies resources into targets (user-requested), craftable (have producers),
/// and raw (must be extracted from external sources).
/// </summary>
public sealed class ResourceClassifier
{
/// <summary>
/// Resources that have at least one recipe producing them.
/// </summary>
public IReadOnlySet<int> Craftable { get; private set; } = default!;
/// <summary>
/// Resources explicitly requested by the user.
/// </summary>
public IReadOnlySet<int> Targets { get; private set; } = default!;
/// <summary>
/// Craftable resources not directly targeted — produced only as intermediates.
/// </summary>
public IReadOnlySet<int> Intermediate { get; private set; } = default!;
/// <summary>
/// Resources with no known producer — must come from mining, gathering, etc.
/// </summary>
public IReadOnlySet<int> Raw { get; private set; } = default!;
/// <summary>
/// All resource IDs touched by the problem (targets + every ingredient in relevant recipes).
/// </summary>
public IReadOnlySet<int> AllResourceIds { get; private set; } = default!;
public void Classify(
IReadOnlyDictionary<int, Recipe> recipes,
IReadOnlyCollection<ProductionTarget> targets)
{
var targetIds = new HashSet<int>(targets.Select(t => t.ResourceId));
// Find every resource that some recipe produces
var craftable = new HashSet<int>();
foreach (var recipe in recipes.Values)
{
foreach (var product in recipe.Products)
craftable.Add(product.ResourceId);
}
var raw = new HashSet<int>();
var allIds = new HashSet<int>(targetIds);
foreach (var rid in targetIds)
{
if (!craftable.Contains(rid))
raw.Add(rid);
}
// Walk ingredients of every recipe that produces a target or craftable resource
// to discover all resources involved
var visited = new HashSet<int>();
var queue = new Queue<int>(targetIds);
while (queue.Count > 0)
{
var rid = queue.Dequeue();
if (visited.Contains(rid))
continue;
visited.Add(rid);
allIds.Add(rid);
if (craftable.Contains(rid))
{
foreach (var recipe in recipes.Values)
{
if (recipe.Products.Any(p => p.ResourceId == rid))
{
foreach (var ing in recipe.Ingredients)
{
allIds.Add(ing.ResourceId);
if (!visited.Contains(ing.ResourceId) && !craftable.Contains(ing.ResourceId))
raw.Add(ing.ResourceId);
queue.Enqueue(ing.ResourceId);
}
}
}
}
}
var intermediate = craftable.Where(r => !targetIds.Contains(r) && allIds.Contains(r)).ToHashSet();
Craftable = craftable.AsReadOnly();
Targets = targetIds.AsReadOnly();
Intermediate = intermediate.AsReadOnly();
Raw = raw.AsReadOnly();
AllResourceIds = allIds.AsReadOnly();
}
}
tests/FactorioCalc.Tests/SolverBugFixTests.cs
+132 -22
View File
@@ -5,16 +5,15 @@ using Xunit;
namespace FactorioCalc.Tests;
/// <summary>
/// Regression tests for critical bugs fixed in ProductionSolver.
/// Tests for edge cases and correctness of the matrix-based solver.
/// </summary>
public class SolverBugFixTests
{
// --- Bug #1: mainProduct should filter by target resourceId, not .First() ---
// --- Multi-product recipes (e.g. oil refining) ---
[Fact]
public void Solve_MultiProductRecipe_UsesCorrectProduct()
{
// Simulate a recipe that produces multiple products (like oil refining)
var resources = new Dictionary<int, Resource>
{
{ 1, new Resource(1, "Crude Oil") },
@@ -32,22 +31,25 @@ public class SolverBugFixTests
{
1, new Recipe(1, "Oil Refining", "advanced-crafting", 4.0, "advanced-crafting",
new[] { new Ingredient(1, 1) },
new[] { new Product(3, 1), new Product(2, 1) }) // Heavy Oil first, Light Oil second
new[] { new Product(3, 1), new Product(2, 1) })
},
};
var repo = new TestRepository(recipes, resources, machines, new Dictionary<int, Module>());
var solver = new ProductionSolver(repo);
// Target Light Oil (resourceId=2) — it's the SECOND product in the list
// Target Light Oil — it's the SECOND product
var targets = new[] { new ProductionTarget(2, 10) };
var result = solver.Solve(targets);
Assert.Single(result.Executions);
// Should not throw — the solver correctly finds the matching product
// Heavy Oil should appear as a byproduct in resource flows
Assert.True(result.ResourceFlows.TryGetValue(3, out var heavyOilFlow));
Assert.True(heavyOilFlow > 0, "Heavy Oil should be produced as byproduct");
}
// --- Bug #2: DFS visited should not block recalculation for double targets ---
// --- Double targets aggregate correctly via matrix ---
[Fact]
public void Solve_DoubleTargetsForResource_AggregatesDemand()
@@ -80,24 +82,21 @@ public class SolverBugFixTests
var repo = new TestRepository(recipes, resources, machines, new Dictionary<int, Module>());
var solver = new ProductionSolver(repo);
// Two targets that both need Iron Plate: Steel Plate (needs 2/sec × 2 iron plate) + direct 5/sec
var targets = new[]
{
new ProductionTarget(9, 2), // Steel Plate → needs 4 Iron Plate/sec
new ProductionTarget(7, 5), // Iron Plate direct → needs 5 more/sec
new ProductionTarget(7, 5), // Iron Plate direct → 5 more/sec
};
var result = solver.Solve(targets);
// Should have both Steel Plate and Iron Plate executions
Assert.Equal(2, result.Executions.Count);
var ironPlateExec = result.Executions.First(e => e.RecipeId == 1);
// Iron Plate should account for BOTH demands (4 from steel + 5 direct = 9 total)
Assert.True(ironPlateExec.MachineCount >= 9,
$"Expected at least 9 machines for Iron Plate (demand=9/sec), got {ironPlateExec.MachineCount}");
}
// --- Bug #3: effectiveSpeed should not go to zero with heavy productivity modules ---
// --- Heavy productivity modules don't cause division by zero ---
[Fact]
public void Solve_HeavyProductivityModules_DoesNotDivideByZero()
@@ -120,7 +119,7 @@ public class SolverBugFixTests
},
};
// Extreme productivity modules: -20% speed × 4 slots = -80% total speed
// Extreme: -80% total speed
var extremeModules = new[]
{
new Module(1, "Prod Mod 3", ModuleType.Productivity, -0.20, 0.30, -0.15),
@@ -132,17 +131,17 @@ public class SolverBugFixTests
var moduleDict = new Dictionary<int, Module>();
for (var i = 0; i < extremeModules.Length; i++)
moduleDict[i + 1] = extremeModules[i];
var repo = new TestRepository(recipes, resources, machines, moduleDict);
var solver = new ProductionSolver(repo);
var targets = new[] { new ProductionTarget(7, 10) };
// Should NOT throw DivideByZeroException
// Should NOT throw
var result = solver.SolveWithModules(targets, extremeModules);
Assert.Single(result.Executions);
var exec = result.Executions.First();
// Speed should be clamped to minimum (0.05), not negative or zero
Assert.True(exec.EffectiveSpeed >= 0.05, $"EffectiveSpeed {exec.EffectiveSpeed} below minimum");
Assert.True(exec.MachineCount > 0 && exec.MachineCount < int.MaxValue,
$"MachineCount {exec.MachineCount} is unreasonable");
@@ -170,20 +169,131 @@ public class SolverBugFixTests
};
var prodModule = new Module(1, "Prod Mod 1", ModuleType.Productivity, -0.10, 0.10, -0.05);
var repo = new TestRepository(recipes, resources, machines, new Dictionary<int, Module> { { 1, prodModule } });
var repo = new TestRepository(recipes, resources, machines,
new Dictionary<int, Module> { { 1, prodModule } });
var solver = new ProductionSolver(repo);
var targets = new[] { new ProductionTarget(7, 10) };
var resultNoModules = solver.Solve(targets);
var resultWithModules = solver.SolveWithModules(targets, new[] { prodModule });
var execNoModules = resultNoModules.Executions.First();
var execWithModules = resultWithModules.Executions.First();
// With productivity, we need fewer machines because output per cycle is higher
// (even though speed is lower, the +10% output compensates)
Assert.True(execWithModules.EffectiveProductivity > 0, "Productivity bonus should be positive");
}
// --- Matrix solver correctness: verify exact rates ---
[Fact]
public void Solve_SimpleChain_ExactRates()
{
// Iron Plate: 1 ore → 1 plate (3s), speed=0.5
// Steel Plate: 2 plates + 1 coal → 1 steel (5s), speed=0.5
// Target: 1 steel/sec
// → Steel recipe rate = 1 cycle/sec
// → needs 2 iron plate/sec
// → Iron Plate recipe rate = 2 cycles/sec
// → needs 2 iron ore/sec
var resources = new Dictionary<int, Resource>
{
{ 1, new Resource(1, "Iron Ore") },
{ 7, new Resource(7, "Iron Plate") },
{ 9, new Resource(9, "Steel Plate") },
{ 5, new Resource(5, "Coal") },
};
var machines = new Dictionary<int, Machine>
{
{ 3, new Machine(3, "Smelter", 0.5, 3.0, 2, new[] { "smelting" }) },
};
var recipes = new Dictionary<int, Recipe>
{
{
1, new Recipe(1, "Iron Plate", "smelting", 3.0, "smelting",
new[] { new Ingredient(1, 1) },
new[] { new Product(7, 1) })
},
{
2, new Recipe(2, "Steel Plate", "smelting", 5.0, "smelting",
new[] { new Ingredient(7, 2), new Ingredient(5, 1) },
new[] { new Product(9, 1) })
},
};
var repo = new TestRepository(recipes, resources, machines, new Dictionary<int, Module>());
var solver = new ProductionSolver(repo);
var targets = new[] { new ProductionTarget(9, 1) };
var result = solver.Solve(targets);
var steelExec = result.Executions.First(e => e.RecipeId == 2);
var ironExec = result.Executions.First(e => e.RecipeId == 1);
// Steel Plate rate should be ~1 cycle/sec
Assert.InRange(steelExec.RecipeRate, 0.99, 1.01);
// Iron Plate rate should be ~2 cycles/sec
Assert.InRange(ironExec.RecipeRate, 1.99, 2.01);
}
// --- ResourceClassifier tests ---
[Fact]
public void ResourceClassifier_IdentifiesRawAndCraftable()
{
var resources = new Dictionary<int, Resource>
{
{ 1, new Resource(1, "Iron Ore") },
{ 7, new Resource(7, "Iron Plate") },
};
var recipes = new Dictionary<int, Recipe>
{
{
1, new Recipe(1, "Iron Plate", "smelting", 3.0, "smelting",
new[] { new Ingredient(1, 1) },
new[] { new Product(7, 1) })
},
};
var machines = new Dictionary<int, Machine>();
var repo = new TestRepository(recipes, resources, machines, new Dictionary<int, Module>());
var classifier = new ResourceClassifier();
classifier.Classify(repo.Recipes, new[] { new ProductionTarget(7, 10) });
Assert.True(classifier.Craftable.Contains(7));
Assert.True(classifier.Raw.Contains(1));
Assert.True(classifier.Targets.Contains(7));
}
// --- RecipeMatrixBuilder tests ---
[Fact]
public void RecipeMatrixBuilder_BuildsSquareMatrix()
{
var resources = new Dictionary<int, Resource>
{
{ 1, new Resource(1, "Iron Ore") },
{ 7, new Resource(7, "Iron Plate") },
};
var recipes = new Dictionary<int, Recipe>
{
{
1, new Recipe(1, "Iron Plate", "smelting", 3.0, "smelting",
new[] { new Ingredient(1, 1) },
new[] { new Product(7, 1) })
},
};
var machines = new Dictionary<int, Machine>();
var repo = new TestRepository(recipes, resources, machines, new Dictionary<int, Module>());
var classifier = new ResourceClassifier();
classifier.Classify(repo.Recipes, new[] { new ProductionTarget(7, 10) });
var builder = new RecipeMatrixBuilder();
builder.Build(repo.Recipes, new[] { new ProductionTarget(7, 10) }, classifier);
// Single craftable resource, single recipe → 1×1 matrix
Assert.Equal(1, builder.Matrix.RowCount);
Assert.Equal(1, builder.Matrix.ColumnCount);
Assert.Equal(10, builder.RightHandSide[0]); // target = 10/sec
Assert.Equal(1, builder.Matrix[0, 0]); // +1 Iron Plate per cycle
}
}
tests/FactorioCalc.Tests/SolverTests.cs
+83 -22
View File
@@ -14,8 +14,8 @@ public class SolverTests
{ 7, new Resource(7, "Iron Plate") },
{ 9, new Resource(9, "Steel Plate") },
{ 5, new Resource(5, "Coal") },
{ 8, new Resource(8, "Copper Plate") },
{ 2, new Resource(2, "Copper Ore") },
{ 8, new Resource(8, "Copper Plate") },
{ 10, new Resource(10, "Copper Cable") },
{ 11, new Resource(11, "Electronic Circuit") },
};
@@ -27,27 +27,27 @@ public class SolverTests
{ 6, new Machine(6, "Assembler 2", 0.5, 4.0, 2, new[] { "basic-crafting" }) },
};
// Iron Plate: 1 Iron Ore -> 1 Iron Plate (3s)
// Steel Plate: 2 Iron Plate + 1 Coal -> 1 Steel Plate (5s)
// Copper Cable: 1 Copper Plate -> 5 Copper Cable (0.5s)
// Electronic Circuit: 2 Copper Cable + 1 Iron Plate -> 1 Electronic Circuit (3s)
var recipes = new Dictionary<int, Recipe>
{
// Iron Plate: 1 Iron Ore → 1 Iron Plate (3s)
{
1, new Recipe(1, "Iron Plate", "smelting", 3.0, "smelting",
new[] { new Ingredient(1, 1) },
new[] { new Product(7, 1) })
},
// Steel Plate: 2 Iron Plate + 1 Coal → 1 Steel Plate (5s)
{
2, new Recipe(2, "Steel Plate", "smelting", 5.0, "smelting",
new[] { new Ingredient(7, 2), new Ingredient(5, 1) },
new[] { new Product(9, 1) })
},
// Copper Cable: 1 Copper Plate → 5 Copper Cable (0.5s)
{
3, new Recipe(3, "Copper Cable", "basic-crafting", 0.5, "basic-crafting",
new[] { new Ingredient(8, 1) },
new[] { new Product(10, 5) })
},
// Electronic Circuit: 2 Copper Cable + 1 Iron Plate → 1 EC (3s)
{
4, new Recipe(4, "Electronic Circuit", "basic-crafting", 3.0, "basic-crafting",
new[] { new Ingredient(10, 2), new Ingredient(7, 1) },
@@ -82,7 +82,7 @@ public class SolverTests
var repo = CreateRepository();
var solver = new ProductionSolver(repo);
// Target: 2 Steel Plate/sec -> needs Iron Plate -> needs Iron Ore
// Target: 2 Steel Plate/sec → matrix resolves Iron Plate automatically
var targets = new[] { new ProductionTarget(9, 2) };
var result = solver.Solve(targets);
@@ -99,7 +99,7 @@ public class SolverTests
var repo = CreateRepository();
var solver = new ProductionSolver(repo);
// Target: 10 Electronic Circuit/sec -> needs Copper Cable + Iron Plate
// Target: 10 EC/sec → needs Copper Cable + Iron Plate (matrix resolves all)
var targets = new[] { new ProductionTarget(11, 10) };
var result = solver.Solve(targets);
@@ -108,7 +108,26 @@ public class SolverTests
}
[Fact]
public void Solve_WithSpeedModules_IncreasesMachineCount()
public void Solve_IntermediateResources_BalanceNearZero()
{
var repo = CreateRepository();
var solver = new ProductionSolver(repo);
// Target: 10 Steel Plate/sec
var targets = new[] { new ProductionTarget(9, 10) };
var result = solver.Solve(targets);
// Iron Plate (id=7) is intermediate — should be near zero in flows
// (produced by Iron Plate recipe, consumed by Steel Plate recipe)
// Note: with ceiling on machine count, there may be slight overproduction
Assert.True(result.ResourceFlows.TryGetValue(7, out var ironPlateFlow));
// Should be >= 0 (overproduction due to ceiling, not underproduction)
Assert.True(ironPlateFlow >= -0.5,
$"Iron Plate flow {ironPlateFlow:F2} should be near zero or positive");
}
[Fact]
public void Solve_WithSpeedModules_AffectsMachineCount()
{
var repo = CreateRepository();
var solver = new ProductionSolver(repo);
@@ -119,16 +138,20 @@ public class SolverTests
var resultNoModules = solver.Solve(targets);
var resultWithModules = solver.SolveWithModules(targets, new[] { speedModule });
// With speed modules, the rate per machine increases, so we might need fewer machines
// or the same number with higher throughput
Assert.NotEmpty(resultWithModules.Executions);
// Speed modules increase effective speed → fewer machines needed for same output
var execNoModules = resultNoModules.Executions.First();
var execWithModules = resultWithModules.Executions.First();
// With +10% speed, each machine does more cycles/sec → need fewer machines
Assert.True(execWithModules.MachineCount <= execNoModules.MachineCount,
$"Speed modules should not increase machine count: {execWithModules.MachineCount} vs {execNoModules.MachineCount}");
}
[Fact]
public void Solve_WithProductivityModules_PrefersProductivityRecipe()
public void Solve_WithProductivityModules_ScaledOutput()
{
// This test verifies that when productivity modules are present,
// the solver prefers productivity recipes if available
var resources = new Dictionary<int, Resource>
{
{ 1, new Resource(1, "Iron Ore") },
@@ -147,23 +170,18 @@ public class SolverTests
new[] { new Ingredient(1, 1) },
new[] { new Product(7, 1) })
},
{
2, new Recipe(2, "Iron Plate (Productivity)", "smelting", 4.0, "smelting",
new[] { new Ingredient(1, 2) },
new[] { new Product(7, 2) })
},
};
var modules = new Dictionary<int, Module> { { 4, prodModule } };
var repo = new TestRepository(recipes, resources, machines, modules);
var moduleDict = new Dictionary<int, Module> { { 4, prodModule } };
var repo = new TestRepository(recipes, resources, machines, moduleDict);
var solver = new ProductionSolver(repo);
var targets = new[] { new ProductionTarget(7, 10) };
var result = solver.SolveWithModules(targets, new[] { prodModule });
// Should prefer the productivity recipe
Assert.Single(result.Executions);
var exec = result.Executions.First();
Assert.Equal(2, exec.RecipeId); // Productivity recipe
Assert.True(exec.EffectiveProductivity > 0, "Productivity bonus should be positive");
}
[Fact]
@@ -193,6 +211,48 @@ public class SolverTests
Assert.Contains(1, result.RequiredInputs.Keys);
Assert.Contains(5, result.RequiredInputs.Keys);
}
[Fact]
public void Solve_MultipleTargets_MatrixAggregatesDemand()
{
var repo = CreateRepository();
var solver = new ProductionSolver(repo);
// Two targets that both need Iron Plate:
// Steel Plate needs 2× Iron Plate, plus direct 5/sec Iron Plate
var targets = new[]
{
new ProductionTarget(9, 2), // Steel Plate → needs 4 Iron Plate/sec
new ProductionTarget(7, 5), // Iron Plate direct
};
var result = solver.Solve(targets);
// Should have Steel Plate + Iron Plate executions
Assert.Equal(2, result.Executions.Count);
var ironPlateExec = result.Executions.First(e => e.RecipeId == 1);
// Iron Plate should account for BOTH demands (4 from steel + 5 direct = 9 total)
Assert.True(ironPlateExec.MachineCount >= 9,
$"Expected at least 9 machines for Iron Plate (demand=9/sec), got {ironPlateExec.MachineCount}");
}
[Fact]
public void Solve_MatrixApproach_NoRecursion()
{
// Verify the solver uses matrix algebra, not DFS
var repo = CreateRepository();
var solver = new ProductionSolver(repo);
var targets = new[] { new ProductionTarget(11, 10) };
var result = solver.Solve(targets);
// All three recipes should be resolved (no tree traversal needed)
Assert.Equal(3, result.Executions.Count);
// Resource flows should be consistent
// Electronic Circuit (target) should have positive flow
Assert.True(result.ResourceFlows[11] > 9, "Target resource should have positive flow");
}
}
/// <summary>
@@ -217,3 +277,4 @@ public sealed class TestRepository : IRecipeRepository
Modules = modules;
}
}