Carte des regroupements LISA (autocorrélation locale)

import geopandas as gpd
import matplotlib.pyplot as plt
import numpy as np
from esda.moran import Moran_Local
from libpysal import examples, weights
from matplotlib.patches import Patch

# Data: literacy of military conscripts in 85 départements, c. 1830 (Guerry, 1833)
g = gpd.read_file(examples.load_example("Guerry").get_path("guerry.shp"))
y = g["Litercy"].to_numpy(dtype=float)

w = weights.Queen.from_dataframe(g, use_index=False)
w.transform = "r"
lisa = Moran_Local(y, w, permutations=999, seed=1)

# Quadrants: 1 high–high, 2 low–high, 3 low–low, 4 high–low; grey if not significant
labels = {1: "High–high cluster", 3: "Low–low cluster", 2: "Low–high outlier", 4: "High–low outlier"}
colors = {1: "#FF3B30", 3: "#007AFF", 2: "#9FCBFF", 4: "#FFA8A2"}
sig = lisa.p_sim < 0.05
g["cluster"] = np.where(sig, lisa.q, 0)
counts = {k: int((g["cluster"] == k).sum()) for k in labels}

fig, ax = plt.subplots(figsize=(8, 7.4))
g.plot(color=[colors.get(c, "#E5E5EA") for c in g["cluster"]], edgecolor="white", linewidth=0.6, ax=ax)
handles = [Patch(color=colors[k], label=f"{labels[k]} ({counts[k]})") for k in labels if counts[k]]
handles.append(Patch(color="#E5E5EA", label=f"Not significant ({int((~sig).sum())})"))
ax.legend(handles=handles, loc="lower left", fontsize=9.5)
ax.set_axis_off()

# Name the strongest cluster cores
for _, r in g.assign(p=lisa.p_sim, Is=lisa.Is)[sig].nlargest(4, "Is").iterrows():
    c = r.geometry.representative_point()
    ax.annotate(r["Dprtmnt"], (c.x, c.y), fontsize=8, ha="center", color="#1D1D1F",
                bbox=dict(boxstyle="round,pad=0.15", fc="white", ec="none", alpha=0.8))

north = g.centroid.y[g["cluster"] == 1].mean() > g.centroid.y[g["cluster"] == 3].mean()
where = "north and east" if north else "south"
ax.set_title(f"A literate {where} ({counts[1]} high–high) against a less literate "
             f"block ({counts[3]} low–low)", pad=26)
ax.text(0, 1.02, f"Local Moran's I, 999 permutations, pseudo p < 0.05, no multiple-testing correction · "
        f"queen weights · n = {w.n} départements, Guerry (1833)",
        transform=ax.transAxes, fontsize=9.5, color="#6E6E73")
plt.show()