"""Figures for the expansion_analogs study (static PNG, light surface)."""
import json
import os

import numpy as np
import pandas as pd

from common import C, DATA, FIG, jeffreys, style

STATUS_COL = {"persisted": C["blue"], "abandoned": C["orange"]}


def _lon(x):
    return np.mod(np.asarray(x, float), 360.0)


def fig_map(u, pac):
    plt = style()
    fig = plt.figure(figsize=(11.8, 5.9))
    ax = fig.add_axes([0.05, 0.17, 0.60, 0.74])
    ix = {k: i for i, k in enumerate(u.unit)}
    # evidence-based parent links
    for _, r in u.iterrows():
        if isinstance(r.parent, str) and r.region == "E":
            p = u.iloc[ix[r.parent]]
            ax.plot(_lon([p.lon, r.lon]), [p.lat, r.lat], color=C["ink2"], lw=0.9, alpha=0.75, zorder=1)
    # the long corner hops that only exist through abandoned stepping stones (dashed)
    for a, b in (("Teraina", "Hawaiian Islands"), ("Henderson", "Rapa Nui")):
        pa, pb = u.iloc[ix[a]], u.iloc[ix[b]]
        ax.plot(_lon([pa.lon, pb.lon]), [pa.lat, pb.lat], color=C["orange"], lw=1.1, ls=(0, (4, 3)), zorder=1)
    size = 18 + 26 * np.log10(np.maximum(u.land_km2.values, 1))
    for st, lab in (("none", "No settlement found"), ("traces", "Traces only")):
        m = (u.status == st).values
        ax.scatter(_lon(u.lon[m]), u.lat[m], s=size[m] * 0.7, facecolors="none", edgecolors=C["muted"], lw=1.0 if st == "none" else 1.6,
                   marker="o" if st == "none" else "D", label=lab, zorder=2)
    doubt = (u.evidence == "doubtful").values
    for st, lab in (("persisted", "Inhabited at European contact"), ("abandoned", "Settled, then abandoned")):
        m = (u.status == st).values & ~doubt
        ax.scatter(_lon(u.lon[m]), u.lat[m], s=size[m], color=STATUS_COL[st], edgecolors=C["surface"], lw=1.2, label=lab, zorder=3)
    ax.scatter(_lon(u.lon[doubt]), u.lat[doubt], s=size[doubt], facecolors="none", edgecolors=C["orange"], lw=1.8,
               label="Abandoned, settlement doubtful", zorder=3)
    labels = {"Samoa": (-2, 10), "Tonga": (-6, -15), "Fiji": (-9, 3, "right"), "Southern Cooks": (-34, -15), "Society Islands": (3, -15),
              "Tuamotus": (9, 4), "Marquesas": (9, 4), "Hawaiian Islands": (11, 2), "Rapa Nui": (-22, 11), "New Zealand": (-12, -8, "right"),
              "Chatham Islands": (10, -8), "Mangareva (Gambier)": (-30, -15), "Kiritimati": (10, -1), "Norfolk": (-8, 7, "right"),
              "Raoul (Kermadec)": (9, 3), "Lord Howe": (8, -3), "Auckland Islands": (-9, -3, "right"), "Galapagos": (-30, 11),
              "Juan Fernandez": (-58, -15), "Nihoa": (-14, 9), "Henderson": (5, 9), "Rapa Iti": (7, -12), "Howland": (-8, 8, "right")}
    short = {"Mangareva (Gambier)": "Mangareva", "Raoul (Kermadec)": "Raoul", "Society Islands": "Societies"}
    for k, off in labels.items():
        r = u.iloc[ix[k]]
        ax.annotate(short.get(k, k), (float(_lon(r.lon)), r.lat), xytext=off[:2], textcoords="offset points",
                    fontsize=7.6, color=C["ink2"], zorder=4, ha=off[2] if len(off) > 2 else "left")
    sa = pac["hops"]["rapa_nui_to_south_america_km"]
    ax.annotate(f"South America: {sa:,.0f} km from Rapa Nui", (289.5, -21.5), fontsize=7.6, color=C["ink2"], ha="right", va="center")
    ax.annotate("", xy=(290.5, -23.6), xytext=(256, -23.6), arrowprops=dict(arrowstyle="->", color=C["muted"], lw=0.8))
    ax.set_xlim(147, 291); ax.set_ylim(-58, 31)
    ax.set_xticks([160, 180, 200, 220, 240, 260, 280]); ax.set_xticklabels(["160°E", "180°", "160°W", "140°W", "120°W", "100°W", "80°W"])
    ax.set_yticks([-40, -20, 0, 20]); ax.set_yticklabels(["40°S", "20°S", "0°", "20°N"])
    ax.set_title("Polynesian settlement units: what was reached, what lasted")
    ax.legend(loc="upper left", bbox_to_anchor=(-0.01, -0.07), ncol=5, fontsize=7.6, handletextpad=0.2, columnspacing=1.0)
    ax.text(0.99, 0.975, "Grey lines: source-to-daughter links supported by genetics or archaeology.\n"
            "Dashed: longest hops needed, via islands later abandoned. Marker size: land area.",
            transform=ax.transAxes, fontsize=7.2, color=C["ink2"], ha="right", va="top")
    # panel b: hop distances
    bx = fig.add_axes([0.72, 0.17, 0.265, 0.74])
    Es = ((u.region == "E") & u.settled).values
    nn = u.nearest_settled_km[Es].values
    ev = u.parent_km[Es & u.parent.notna().values].values
    bins = np.arange(0, 2801, 200)
    bx.hist(nn, bins=bins, color=C["blue"], alpha=0.9, rwidth=0.86, label=f"Nearest settled neighbour ({len(nn)} units)")
    bx.hist(ev, bins=bins, histtype="step", color=C["ink"], lw=1.6, label=f"Documented source-to-daughter hop ({len(ev)})")
    D = pac["hops"]["network_bottleneck_km"]
    bx.axvline(D, color=C["orange"], lw=1.4, ls=(0, (4, 3)))
    bx.set_ylim(0, 13.5)
    bx.text(D - 50, 7.2, f"Longest hop the\nsettled network\nneeds: {D:,.0f} km\n(defined from\nthe outcome)", fontsize=7.4, color=C["ink2"], ha="right")
    bx.set_xlabel("Open-sea hop distance (km)"); bx.set_ylabel("Number of settlement units")
    bx.set_yticks([0, 2, 4, 6, 8, 10])
    bx.set_xticks([0, 1000, 2000]); bx.set_xticklabels(["0", "1,000", "2,000"])
    bx.set_title("Most hops were short")
    bx.legend(loc="upper right", fontsize=7.4)
    fig.savefig(os.path.join(FIG, "fig1_pacific_map_and_hops.png"))
    plt.close(fig)


def fig_timeline(u, pac, norse):
    plt = style()
    cur = pd.read_csv(os.path.join(DATA, "pacific_cumulative_settlement_curves.csv"))
    fig, (ax, bx) = plt.subplots(1, 2, figsize=(11.8, 4.7), gridspec_kw=dict(width_ratios=[1.35, 1], wspace=0.36))
    west = 3  # Fiji, Tonga, Samoa: the dated Lapita-period units in the table
    for chron, col, lab in (("S", C["blue"], "Short radiocarbon chronology"), ("A", C["orange"], "Alternative (genetic and model-based) chronology")):
        c = cur[cur.year >= 700]
        c = c[c.chronology == chron]
        ax.fill_between(c.year, c.lo + west, c.hi + west, color=col, alpha=0.18, lw=0)
        ax.plot(c.year, c.med + west, color=col, label=lab)
    # Lapita steps (Fiji about 1050 BC, Tonga about 850 BC, Samoa about 800 BC), then no new dated unit until the eastern pulse
    ax.plot([-1200, -1050, -1050, -850, -850, -800, -800, 700], [0, 0, 1, 1, 2, 2, 3, 3], color=C["ink"], lw=1.6, zorder=3)
    ax.text(-1180, 4.3, "Lapita reaches\nFiji, Tonga, Samoa", fontsize=8, color=C["ink2"])
    pS, pA = pac["timing"]["S"]["pause_years"][2], pac["timing"]["A"]["pause_years"][2]
    ax.annotate("", xy=(840, 1.7), xytext=(-800, 1.7), arrowprops=dict(arrowstyle="<->", color=C["muted"], lw=0.9))
    ax.text(20, 0.45, f"Pause in West Polynesia: about {pA:,.0f} to {pS:,.0f} years", fontsize=8, color=C["ink2"], ha="center")
    dS, dA = pac["timing"]["S"]["pulse_10_90_years"][2], pac["timing"]["A"]["pulse_10_90_years"][2]
    ax.text(760, 17.3, f"Eastern pulse:\n10% to 90% of dated\nunits in {dS:.0f} to {dA:.0f} years", fontsize=8, color=C["ink2"], ha="right")
    ax.text(-1180, 8.6, "20 of 29 settled units have date windows;\n5 of those windows are generic.\nBands: 16% to 84% over the windows.",
            fontsize=7.2, color=C["ink2"], ha="left", va="bottom")
    ax.set_xlim(-1200, 1800); ax.set_ylim(0, 26.5)
    ax.set_xticks([-1000, -500, 0, 500, 1000, 1500]); ax.set_xticklabels(["1000 BC", "500 BC", "AD 1", "500", "1000", "1500"])
    ax.set_ylabel("Dated settlement units occupied (cumulative)")
    ax.set_title("A long pause, then a pulse of a few centuries")
    ax.legend(loc="upper left", fontsize=7.8)
    # panel b: lifetimes of settlements that failed
    rows = []
    for k, v in pac["abandonment"]["lifetime_years_p16_p50_p84"].items():
        rows.append((k.replace(" (Kermadec)", ""), v[0], v[1], v[2], "Pacific"))
    short = {"Greenland Eastern Settlement": "Greenland (East)", "Greenland Western Settlement": "Greenland (West)",
             "Vinland (L'Anse aux Meadows)": "Vinland"}
    for k, v in norse["lifetimes_years"].items():
        rows.append((short.get(k, k), v[0], v[1], v[2], "Norse"))
    rows.sort(key=lambda r: r[2])
    y = np.arange(len(rows))
    generic = set(pac["abandonment"]["lifetime_usable_dates"]["dropped_generic_window"])
    rows = [(r[0] + (" *" if any(r[0].startswith(g.split(" ")[0]) for g in generic) else ""),) + r[1:] for r in rows]
    for i, r in enumerate(rows):
        col = C["blue"] if r[4] == "Pacific" else C["aqua"]
        bx.barh(i, r[2], height=0.56, color=col, zorder=2, alpha=0.45 if r[0].endswith("*") else 1.0)
        bx.plot([r[1], r[3]], [i, i], color=C["ink"], lw=1.0, zorder=3)
        bx.text(max(r[3], r[2]) + 12, i, f"{r[2]:.0f}", va="center", fontsize=7.8, color=C["ink2"])
    bx.set_yticks(y); bx.set_yticklabels([r[0] for r in rows], fontsize=8)
    bx.set_xlabel("Years from first settlement to last dated occupation")
    bx.set_xlim(0, 580)
    bx.grid(axis="y", visible=False)
    from matplotlib.patches import Patch
    bx.legend(handles=[Patch(color=C["blue"], label="Pacific"), Patch(color=C["aqua"], label="Norse North Atlantic")], loc="lower right", fontsize=7.8)
    bx.set_title("Failed settlements: indicative lifetimes")
    bx.text(0.98, 0.30, "* first-settlement window is generic,\nnot specific to the island.\nLines: 16% to 84% range over\nthe first-settlement window.",
            transform=bx.transAxes, fontsize=7.2, color=C["ink2"], ha="right", va="top")
    fig.savefig(os.path.join(FIG, "fig2_timeline_and_lifetimes.png"))
    plt.close(fig)


def fig_abandonment(u, pac, isl):
    """Abandonment at island grain: small AND alone. Replaces the first-pass figure, whose 'size, not isolation' reading was
    an artefact of merging persisted islands into archipelago units."""
    plt = style()
    from matplotlib.ticker import NullFormatter
    fig, (ax, bx, cx) = plt.subplots(1, 3, figsize=(12.6, 4.7), gridspec_kw=dict(width_ratios=[1.45, 0.95, 0.95], wspace=0.33))
    il = pac["abandonment"]["island_level"]
    cols = {"inhabited": C["blue"], "abandoned": C["orange"]}
    for st, lab in (("inhabited", "Inhabited at European contact"), ("abandoned", "Abandoned before contact")):
        m = (isl.contact == st).values
        ax.scatter(isl.land_km2[m], isl.nn_settled_km[m], s=40, color=cols[st], edgecolors=C["surface"], lw=1.1, label=lab, zorder=3)
    m = (isl.contact == "doubtful").values
    ax.scatter(isl.land_km2[m], isl.nn_settled_km[m], s=34, facecolors="none", edgecolors=C["muted"], lw=1.2,
               label="In a persisting group, contact status doubtful", zorder=2)
    lab = {"Rapa Nui": (7, -3), "Rapa Iti": (7, -3), "Penrhyn": (7, -10), "Kiritimati": (7, -3), "Necker": (7, -3), "Suwarrow": (0, 7, "center"),
           "Howland": (7, 2), "Raoul": (7, 2), "Norfolk": (7, -8), "Malden": (-7, 5, "right"), "North Island": (-6, 7, "right"),
           "Chatham Island": (7, 3), "Nihoa": (7, -3), "Henderson": (-7, -11, "right"), "Enderby": (7, -1)}
    for k, off in lab.items():
        r = isl[isl.island == k].iloc[0]
        ax.annotate(k, (r.land_km2, r.nn_settled_km), xytext=off[:2], textcoords="offset points", fontsize=7.2, color=C["ink2"],
                    ha=off[2] if len(off) > 2 else "left")
    ax.set_xscale("log"); ax.set_yscale("log")
    ax.set_xlim(0.1, 4e5); ax.set_ylim(25, 3200)
    ax.set_yticks([30, 100, 300, 1000, 3000]); ax.set_yticklabels(["30", "100", "300", "1,000", "3,000"])
    ax.yaxis.set_minor_formatter(NullFormatter())
    ax.set_xticks([0.1, 1, 10, 100, 1000, 1e4, 1e5]); ax.set_xticklabels(["0.1", "1", "10", "100", "1,000", "10,000", "100,000"], fontsize=7.6)
    ax.set_xlabel("Land area of the island (km², log scale)")
    ax.set_ylabel("Distance to the nearest other settled island (km)")
    ax.set_title("Abandoned islands were small\nand had no near neighbour")
    ax.legend(loc="upper left", bbox_to_anchor=(-0.02, -0.16), ncol=1, fontsize=7.6)
    # panel b: the unit artefact - share abandoned by area class, unit grain against island grain
    classes = [(0, 10, "under\n10"), (10, 100, "10 to\n100"), (100, 1000, "100 to\n1,000"), (1000, 1e9, "over\n1,000")]
    Es = ((u.region == "E") & u.settled).values
    d = u[Es]
    w = 0.36
    for i, (lo, hi, name) in enumerate(classes):
        mu = (d.land_km2 >= lo) & (d.land_km2 < hi)
        k, n = int((d.status[mu] == "abandoned").sum()), int(mu.sum())
        row = il["by_area_class"][i]
        k2, n2 = row["abandoned"], row["islands"]
        bx.bar(i - w / 2 - 0.02, k / n, width=w, color=C["gray"], zorder=2, label="Archipelagos as one unit (first pass)" if i == 0 else None)
        bx.bar(i + w / 2 + 0.02, k2 / n2, width=w, color=C["orange"], zorder=2, label="Island by island" if i == 0 else None)
        bx.text(i - w / 2 - 0.02, k / n + 0.02, f"{k}/{n}", ha="center", fontsize=7.4, color=C["ink2"])
        bx.text(i + w / 2 + 0.02, k2 / n2 + 0.02, f"{k2}/{n2}", ha="center", fontsize=7.4, color=C["ink2"])
    bx.set_xticks(range(len(classes))); bx.set_xticklabels([c[2] for c in classes], fontsize=8)
    bx.set_ylim(0, 1.05); bx.set_yticks([0, 0.25, 0.5, 0.75, 1.0]); bx.set_yticklabels(["0%", "25%", "50%", "75%", "100%"])
    bx.set_xlabel("Land area (km²)"); bx.set_ylabel("Share abandoned before contact")
    bx.grid(axis="x", visible=False)
    bx.legend(loc="upper right", fontsize=7.6)
    bx.set_title("The size effect shrinks\nat island grain")
    # panel c: aggregation-radius profile
    prof = il["aggregation_radius_profile"]
    xs = np.arange(len(prof))
    auc = [p["leave_one_unit_out_auc"] for p in prof]
    cx.plot(xs, auc, color=C["blue"], lw=2, marker="o", ms=6, mec=C["surface"], mew=1.2, zorder=3)
    for x_, a_ in zip(xs, auc):
        end = x_ in (xs[0], xs[-1])   # end labels go below the point, clear of the line
        cx.text(x_, a_ - 0.026 if end else a_ + 0.012, f"{a_:.2f}", ha="center", fontsize=7.4, color=C["ink2"])
    cx.axhline(0.5, color=C["muted"], lw=1.0, ls=(0, (4, 3)))
    cx.text(xs[-1], 0.508, "no skill", fontsize=7.4, color=C["ink2"], ha="right")
    cx.set_xticks(xs); cx.set_xticklabels(["island\nonly"] + [f"{p['radius_km']:,}" for p in prof[1:]], fontsize=7.8)
    cx.set_ylim(0.45, 0.85)
    cx.set_xlabel("Land counted within this distance (km)")
    cx.set_ylabel("Out-of-sample skill (AUC, whole groups held out)")
    cx.set_title("Land within 50 to 300 km\npredicts persistence best")
    fig.savefig(os.path.join(FIG, "fig3_abandonment_vs_size.png"))
    plt.close(fig)


def fig_percolation(u, pac):
    plt = style()
    fig, (ax, bx) = plt.subplots(1, 2, figsize=(12.2, 4.7), gridspec_kw=dict(width_ratios=[1.0, 1.15], wspace=0.5))
    ramp = {2100: "#86b6ef", 2600: "#2a78d6", 3500: "#104281"}   # one hue, light to dark = shorter to longer assumed range
    ends = {}
    for R, col in ramp.items():
        prof = pac["percolation"][str(R)]["all_land_units_with_habitability"]["profile"]
        ps = np.array([float(k) for k in prof]); vs = np.array(list(prof.values()))
        ax.plot(ps, vs, color=col, lw=2, marker="o", ms=3.5, label=f"{R:,} km")
        ends[R] = vs[2]
    ax.axhline(np.exp(-2), color=C["muted"], lw=0.9, ls=(0, (1, 2)))
    ax.text(0.99, np.exp(-2) + 0.02, "support limit (likelihood ratio e⁻²)", fontsize=7.2, color=C["ink2"], ha="right")
    ax.axvline(1 / 3, color=C["muted"], lw=1.0, ls=(0, (4, 3)))
    ax.text(1 / 3 + 0.015, 1.12, "Landis's illustrative p = 1/3", fontsize=7.6, color=C["ink2"], ha="left", va="top")
    ax.set_xlim(0, 1.0); ax.set_ylim(0, 1.15)
    ax.set_xlabel("Probability that a settlement goes on to found others (p)")
    ax.set_ylabel("Profile likelihood relative to its maximum")
    ax.set_title("The Pacific bounds p only from below,\nand only if voyaging range was short")
    ax.legend(loc="upper left", bbox_to_anchor=(-0.02, -0.15), ncol=3, fontsize=7.8, title="Assumed voyaging range", title_fontsize=7.8, columnspacing=1.2)
    ax.text(0.99, 0.02, "All 50 land units of East Polynesia;\nhabitability fitted from land area.", fontsize=7.2, color=C["ink2"], ha="right", va="bottom")
    # panel b: share of targets settled, by definition of 'target'
    defs = pac["reach"]["by_definition"]
    names = ["Every land unit in reach", "Excluding rocks and\nsubantarctic islands", "10 km² or more, excluding\nrocks and subantarctic",
             "Held a civilian settlement for\n20 years or more after contact", "Carries a self-supporting\ncommunity since contact",
             "Settled, or self-supporting later\n(first-pass definition: circular)"]
    y = np.arange(len(defs))[::-1]
    for yi, d_, nm in zip(y, defs, names):
        circ = d_["denominator_depends_on_outcome"]
        bx.barh(yi, d_["fraction"], height=0.56, color=C["gray"] if circ else C["blue"], zorder=2)
        bx.barh(yi, d_["inhabited_at_contact"] / d_["targets"], height=0.56, color=C["ink2"] if circ else "#104281", zorder=3)
        bx.text(d_["fraction"] + 0.015, yi, f"{d_['settled']} of {d_['targets']}", va="center", fontsize=8, color=C["ink2"])
    bx.set_yticks(y); bx.set_yticklabels(names, fontsize=7.8)
    bx.set_xlim(0, 1.18); bx.set_xticks([0, 0.25, 0.5, 0.75, 1.0]); bx.set_xticklabels(["0%", "25%", "50%", "75%", "100%"])
    bx.set_xlabel("Share of targets settled before European contact")
    bx.grid(axis="y", visible=False)
    from matplotlib.patches import Patch
    bx.legend(handles=[Patch(color=C["blue"], label="Settled at some time"), Patch(color="#104281", label="Still inhabited at contact")],
              loc="upper left", bbox_to_anchor=(-0.02, -0.15), ncol=2, fontsize=7.8)
    bx.set_title("How full the Pacific was depends on what counts as a target")
    fig.savefig(os.path.join(FIG, "fig4_percolation_fit_and_reach.png"))
    plt.close(fig)


def fig_invasions_prior(inv, tab, coefs, syn):
    plt = style()
    fig, (ax, bx) = plt.subplots(1, 2, figsize=(11.8, 4.6), gridspec_kw=dict(width_ratios=[1, 1.15], wspace=0.27))
    x = tab.geo_mid.values
    ax.errorbar(x, tab.fraction, yerr=[tab.fraction - tab.ci_lo, tab.ci_hi - tab.fraction], fmt="o", color=C["blue"], ecolor=C["ink"],
                elinewidth=1.0, ms=6.5, mec=C["surface"], mew=1.2, zorder=3)
    for _, r in tab.iterrows():
        ax.text(r.geo_mid, r.ci_hi + 0.02, f"n={int(r.n)}", fontsize=7.4, color=C["ink2"], ha="center")
    xs = np.logspace(np.log10(2), 3, 100)
    b3 = coefs[1]
    ax.plot(xs, 1 / (1 + np.exp(-(b3[0] + b3[1] * np.log10(xs)))), color=C["blue"], lw=1.6, alpha=0.8)
    ax.axhline(0.10, color=C["muted"], lw=1.0, ls=(0, (4, 3)))
    ax.text(28000, 0.115, "'Tens rule': 10%", fontsize=7.8, color=C["ink2"], ha="right")
    ax.set_xscale("log"); ax.set_xlim(2, 30000); ax.set_ylim(0, 0.8)
    ax.set_xticks([10, 100, 1000, 10000]); ax.set_xticklabels(["10", "100", "1,000", "10,000"])
    ax.set_yticks([0, 0.2, 0.4, 0.6, 0.8]); ax.set_yticklabels(["0%", "20%", "40%", "60%", "80%"])
    ax.set_xlabel("Birds released per introduction event (log scale)")
    ax.set_ylabel("Share of introductions that established")
    p = inv["propagule"]
    ax.set_title(f"{p['n_events']} bird introductions: {100 * p['overall_fraction']:.0f}% established")
    ax.text(0.98, 0.30, "Points: binned events, 95% intervals.\nCurve: logistic fit, releases up to 1,000.",
            transform=ax.transAxes, fontsize=7.4, color=C["ink2"], va="top", ha="right")
    # panel b: the low tail of the first-pass 'prior' is set by the assumed feasibility floor
    s = np.load(os.path.join(DATA, "prior_samples.npz"))
    grid = np.linspace(-12, 0, 400)
    cdf = lambda v: np.searchsorted(np.sort(v), grid) / len(v)
    bx.plot(grid, cdf(s["log10_p_base"]), color=C["ink"], lw=2.0, label="Project model's current prior")
    ramp = {"1e_2": ("#f5b99b", "10⁻²"), "1e_4": (C["orange"], "10⁻⁴"), "1e_6": ("#9c3a12", "10⁻⁶")}
    for k, (col, lab) in ramp.items():
        v = cdf(s["log10_floor_" + k])
        bx.plot(grid, v, color=col, lw=2.0, label=f"Illustrative product × discount, floor {lab}")
    bx.plot(grid, cdf(s["log10_product_mixture"]), color=C["blue"], lw=2.0, label="Illustrative product alone (given feasibility)")
    bx.axvline(-3, color=C["muted"], lw=1.0, ls=(0, (4, 3)))
    fl = syn["feasibility_floor_sensitivity"]
    bx.text(-3.15, 0.99, "share below 10⁻³:\n" + "\n".join(f"floor {lab}: {100 * fl[k.replace('_', '-')]['share_below_1e_3']:.0f}%"
                                                         for k, (_, lab) in ramp.items())
            + f"\nmodel prior: {100 * syn['model_priors']['base W=(1,30)']['share_below_1e_3']:.0f}%",
            fontsize=7.4, color=C["ink2"], ha="right", va="top")
    bx.set_xlim(-12, 0); bx.set_ylim(0, 1.02)
    bx.set_xticks([-12, -10, -8, -6, -4, -2, 0]); bx.set_xticklabels(["10⁻¹²", "10⁻¹⁰", "10⁻⁸", "10⁻⁶", "10⁻⁴", "10⁻²", "1"])
    bx.set_yticks([0, 0.25, 0.5, 0.75, 1.0]); bx.set_yticklabels(["0%", "25%", "50%", "75%", "100%"])
    bx.set_xlabel("Probability that a civilisation becomes a sustained expander")
    bx.set_ylabel("Probability of being below this value")
    bx.set_title("The low tail is set by an assumed floor, not by data")
    bx.legend(loc="upper left", bbox_to_anchor=(-0.02, -0.15), ncol=2, fontsize=7.4, columnspacing=1.0)
    fig.savefig(os.path.join(FIG, "fig5_invasion_base_rates_and_prior.png"))
    plt.close(fig)


def run(u, pac, norse, inv, tab, coefs, syn, isl):
    os.makedirs(FIG, exist_ok=True)
    fig_map(u, pac)
    fig_timeline(u, pac, norse)
    fig_abandonment(u, pac, isl)
    fig_percolation(u, pac)
    fig_invasions_prior(inv, tab, coefs, syn)