diff --git a/scripts/wvs_map.py b/scripts/wvs_map.py index 07979e7..2dd191e 100644 --- a/scripts/wvs_map.py +++ b/scripts/wvs_map.py @@ -223,17 +223,22 @@ def main() -> None: ax.axvline(med_x, color="#c9c4b4", lw=1.0, zorder=1) maps.draw_zone_hulls(ax, P, countries, zones) ax.scatter(P[:, 0], P[:, 1], s=28, c=dot_cols, alpha=0.85, edgecolors="white", linewidths=0.5, zorder=3) - for i, c in enumerate(countries): - if c in label_set: - ax.annotate(c, (P[i, 0], P[i, 1]), fontsize=9, xytext=(4, 3), - textcoords="offset points", color="#111", fontweight="bold", zorder=6) - # LLM stars cluster in one corner (that IS the result), so their inline labels collide -- use a - # legend in the empty lower-right instead; the distinct colours tie each star to its name. + mnames = list(models) + mpts = np.array([models[k] for k in mnames]) for (name, pt), col in zip(models.items(), MODEL_COLORS): - ax.scatter(*pt, s=190, marker="*", c=col, edgecolors="white", linewidths=1.0, zorder=8, - label=name) - ax.legend(loc="lower right", fontsize=9, framealpha=0.92, title="LLMs (sampled)", - title_fontproperties={"weight": "bold"}, borderpad=0.7, labelspacing=0.5).set_zorder(11) + ax.scatter(*pt, s=190, marker="*", c=col, edgecolors="white", linewidths=1.0, zorder=8) + # All labels (country + LLM) placed by textalloc: non-overlapping, with leader lines back to the + # dot/star. LLM labels ON the map (not a legend), coloured to their star; country labels dark. The + # scatter set it avoids is every dot + star, so no label lands on a point. + import textalloc as ta + lab_i = [i for i, c in enumerate(countries) if c in label_set] + tx = [P[i, 0] for i in lab_i] + list(mpts[:, 0]) + ty = [P[i, 1] for i in lab_i] + list(mpts[:, 1]) + txt = [countries[i] for i in lab_i] + mnames + tcol = ["#111"] * len(lab_i) + list(MODEL_COLORS[:len(mnames)]) + ta.allocate_text(fig, ax, tx, ty, txt, + x_scatter=list(P[:, 0]) + list(mpts[:, 0]), y_scatter=list(P[:, 1]) + list(mpts[:, 1]), + textsize=9, textcolor=tcol, linecolor="#aaa", linewidth=0.6, draw_lines=True) # Four pole signposts, each arrow sitting ON its neutral crosshair (x=0.5 for the vertical axis, # y=0.5 for the horizontal one -- these lines are NOT at the plot centre) and pointing out to its # pole, in the padded inner margin. All labels horizontal so they stay readable. diff --git a/src/tinymfv/maps.py b/src/tinymfv/maps.py index f214e95..9d3fdc6 100644 --- a/src/tinymfv/maps.py +++ b/src/tinymfv/maps.py @@ -142,11 +142,14 @@ def select_spread_zones(P: np.ndarray, countries: list[str], zones: dict[str, li def outlying_countries(P: np.ndarray, countries: list[str], n: int = 4) -> set[str]: - """The `n` countries farthest from the data centroid -- the automatic extreme labels for ANY map, - unioned with a named-major set (US/Japan/China...) so every map labels the same few landmarks plus - whatever its own extremes are.""" - d = np.hypot(*(P - P.mean(0)).T) - return {countries[i] for i in np.argsort(d)[::-1][:n]} + """The corner-most country in each direction: the society that projects farthest along each of n + compass directions from the centroid (n=4 -> the four diagonal CORNERS top-right/bottom-left/ + top-left/bottom-right; n=8 adds the axis extremes). Unlike 'n farthest from the centroid' (which + can bunch all on one side and miss a corner), this guarantees the top-right-most, bottom-left-most + etc. are each labelled -- the extremes a reader's eye goes to, on ANY map.""" + Pc = P - P.mean(0) + dirs = [(1, 1), (-1, -1), (-1, 1), (1, -1), (1, 0), (-1, 0), (0, 1), (0, -1)][:n] + return {countries[int(np.argmax(Pc[:, 0] * dx + Pc[:, 1] * dy))] for dx, dy in dirs} def draw_zone_hulls(ax, P: np.ndarray, countries: list[str], zones: dict[str, list[str]],