Justin Visser
45fdf7ffa4
Config is the single source of truth for parameters (TS types will be generated from these structs in milestone 2); all randomness flows from its three seeds, so identical configs give identical results. Golden test pins the default world: none=99/120 (82%), random=70/120 (58%), most-connected=7/120 (6%). Same story as the prototype's 85/64/8 with different dice; the ordering and the collapse are asserted explicitly, exact Python numbers are out of scope by design. 'go run ./cmd/spreadlab' prints the three-scenario comparison. This completes milestone 1 (engine ported, parameterised, tested).
35 lines
1 KiB
Go
35 lines
1 KiB
Go
// Command spreadlab will serve the spreadlab dashboard. Until the HTTP
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// server lands (milestone 2), it runs the prototype's three scenarios in
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// the default world and prints the comparison.
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package main
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import (
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"fmt"
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"os"
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"github.com/JustinZeus/spreadlab/internal/engine"
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)
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func main() {
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config := engine.DefaultConfig()
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fmt.Printf("spreadlab: %d students, educate %d, forwarding probability %.2f\n",
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config.NumStudents, config.NumEducated, config.ForwardProb)
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fmt.Println("(illustrative, not validated)")
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fmt.Println()
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strategies := []engine.Strategy{
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engine.StrategyNone,
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engine.StrategyRandom,
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engine.StrategyMostConnected,
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}
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for _, strategy := range strategies {
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result, err := engine.RunScenario(config, strategy)
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if err != nil {
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fmt.Fprintln(os.Stderr, "spreadlab:", err)
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os.Exit(1)
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}
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fmt.Printf("%-15s educated=%3d reached=%3d/%d (%2.0f%%) in %d rounds\n",
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result.Strategy, len(result.Educated), result.NumReached,
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config.NumStudents, result.ReachedPct, result.NumRounds)
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}
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}
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