Leonid PershinandClaude Opus 4.8
ead22517ee
CI / build-test (push) Successful in 1m17s
Adds the species/organism layer on top of the gene foundation. GenomeTemplate carries which GeneDefs an individual has plus the per-organism base value and spread its alleles are drawn around (and an optional discrete-variant override), so the same shared GeneDef expresses different centres for different species — Generate() draws an individual, Registry() feeds breeding and trait computation. Genome.Breed gains an optional mutationChance that overrides every gene's fixed MutationChance, so a caller can drive mutation from an evolvable trait. Allele sampling (numeric spread+clamp, weighted discrete pick) is factored into a shared GeneSampling used by both Generate paths. Covered by GenomeTemplateTests (per-species centres, registry-driven breeding, mutation override on/off). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
57 lines
1.8 KiB
C#
57 lines
1.8 KiB
C#
namespace MrGameEng.Genetics;
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/// <summary>
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/// Shared, deterministic allele sampling used by both <see cref="Genome.Generate"/> (gene defaults)
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/// and <see cref="GenomeTemplate"/> (per-individual base overrides). Centralizes the numeric
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/// spread+clamp and the weighted discrete pick so the two paths stay consistent.
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/// </summary>
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internal static class GeneSampling
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{
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/// <summary>A numeric allele drawn as <c>baseValue ± spread·|baseValue|</c>, clamped to the gene's range.</summary>
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public static float Numeric(GeneDef gene, float baseValue, float spread, Random random)
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{
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var value = baseValue + (random.NextSingle() * 2f - 1f) * spread * MathF.Abs(baseValue);
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return Math.Clamp(value, gene.Min, gene.Max);
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}
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/// <summary>
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/// A discrete variant index in <c>[0, Variants)</c>, picked from <paramref name="weights"/> when
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/// they match the variant count, otherwise the gene's own weights, otherwise uniformly.
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/// </summary>
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public static float Variant(GeneDef gene, float[]? weights, Random random)
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{
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var variants = Math.Max(1, gene.Variants);
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var w =
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weights is { Length: > 0 } && weights.Length == variants
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? weights
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: gene.VariantWeights;
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if (w.Length != variants)
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{
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return random.Next(variants);
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}
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var total = 0f;
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foreach (var value in w)
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{
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total += MathF.Max(0f, value);
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}
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if (total <= 0f)
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{
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return random.Next(variants);
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}
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var roll = random.NextSingle() * total;
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for (var i = 0; i < variants; i++)
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{
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roll -= MathF.Max(0f, w[i]);
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if (roll < 0f)
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{
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return i;
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}
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}
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return variants - 1;
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}
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}
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