Giorgio Gilestro
6f8cef1ac5
Removed from main (all preserved on the dev branch): the arXiv build and
its sources, design documents (blueprint, results summary, review responses,
essay drafts), tasks/ and CLAUDE.md, the cover letter and reference tooling,
two unused manuscript figures, and every experiment that feeds no figure or
number in the paper: the collapse null, the sexual-vs-asexual lineage, the
NK speciation variant, the 0.5B single-seed LLM prototypes, the compose and
society experiments with their calibration and pilot runs, and their
configs, runners, tests, figure scripts and PBS jobs. Their result bundles
are moved to results/_archive/ (ignored) so the parquets stay on disk.
Also: plot_llm_speciation reads the s{seed}/ layout; the mating-breadth
plot writes under its bundle name; Makefile targets reduced to the kept
experiments; REPRODUCING.md and README point to dev for the rest.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
67 lines
3.1 KiB
Python
67 lines
3.1 KiB
Python
"""E14 figure — mating systems: monogamy vs promiscuity (mate-pool breadth) across ruggedness.
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Three panels, each vs mate-pool breadth (log x: 0.03 = monogamous/structured -> 1.0 = promiscuous/
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panmictic), one line per landscape ruggedness K:
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(A) best fitness / global optimum — the *champion*. On smooth landscapes (low K) it is maximised by
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wide breadth; as ruggedness rises the peak shifts to an INTERMEDIATE breadth (full promiscuity
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prematurely converges below it) — the mating-system image of E9's "optimal recombination rate
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shrinks with ruggedness".
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(B) mean fitness / global optimum — the *typical* individual. Monotonically favoured by breadth at
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every K: panmixia lifts the whole population toward a good consensus.
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(C) diversity (mean normalised pairwise Hamming) — monotonically DESTROYED by breadth at every K
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(promiscuity homogenises), the reservoir largest under monogamy and on rugged landscapes.
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The tension between (A)/(C) is the result: promiscuity maximises the typical model and kills diversity;
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on rugged landscapes the best model needs preserved diversity, so an intermediate breadth wins.
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Usage: python figures/plot_figS13_mating_breadth.py
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import matplotlib.pyplot as plt
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sys.path.insert(0, str(Path(__file__).parent))
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from _figlib import load_bundle, savefig, letter_axes # noqa: E402
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def main() -> None:
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df, _ = load_bundle("results/figS13_mating_breadth")
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last = df[df["generation"] == df["generation"].max()].copy()
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last["best_n"] = last["best_fitness"] / last["global_opt"]
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last["mean_n"] = last["mean_fitness"] / last["global_opt"]
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Ks = sorted(last["K"].unique())
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cmap = plt.get_cmap("viridis")
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colors = {K: cmap(i / max(1, len(Ks) - 1)) for i, K in enumerate(Ks)}
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fig, axes = plt.subplots(1, 3, figsize=(16, 5))
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panels = [
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("best_n", "best fitness / global optimum",
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"Best model peaks at intermediate breadth on rugged\nlandscapes (the peak shifts left as $K$ rises)"),
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("mean_n", "mean fitness / global optimum",
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"Population mean rises monotonically with breadth\n(panmixia lifts the whole population)"),
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("diversity", "diversity (mean pairwise Hamming)",
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"Standing diversity falls monotonically with breadth\n(promiscuity homogenises; monogamy preserves)"),
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]
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for ax, (col, ylab, title) in zip(axes, panels):
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for K in Ks:
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g = (last[last["K"] == K].groupby("breadth")[col]
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.agg(["mean", "sem"]).reset_index())
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ax.errorbar(g["breadth"], g["mean"], yerr=1.96 * g["sem"].fillna(0.0),
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marker="o", lw=1.8, capsize=2, color=colors[K], label=f"K={K}")
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ax.set_xscale("log")
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ax.set(xlabel="mate-pool breadth (monogamous ← → promiscuous)", ylabel=ylab)
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ax.set_title(title, fontsize=9)
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ax.legend(title="ruggedness", frameon=False, fontsize=8)
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fig.tight_layout()
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letter_axes(fig)
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savefig(fig, "results/figS13_mating_breadth", "figS13_mating_breadth")
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if __name__ == "__main__":
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main()
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