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https://github.com/wassname/moral-maps.git
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wvs map: emptiest-slot zone labels + one label per model family
Zone labels now get a dedicated open-space search (_open_slot: scan a ring around the hull centroid, keep the slot whose nearest dot/label is farthest) instead of adjustText's local minimum -- so Latin America/African-Islamic land in the sparse margins with a leader to their hull, not the crowded centre. And with 17 models the names were too many: plot every star but LABEL only the latest per family (highest version), dropping the redundant 'claude-' so the flagship reads 'opus-4.8'. Colour + legend carry the unlabelled siblings. Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
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wassname
+10
-1
@@ -289,10 +289,19 @@ def main() -> None:
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# Drop the " (rated)" readout tag from the on-map labels (the cache/CI-table keep it) -- the map is
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# crowded and every model here is rated, so the tag adds nothing.
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plot_models = {k.replace(" (rated)", ""): v for k, v in models.items()}
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# Too many model names to label them all. Plot every star (colour = family) but LABEL only the
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# latest model per family (highest version number), and drop the redundant "claude-" so the flagship
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# reads "opus-4.8". Colour + legend carry the unlabelled siblings.
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fams: dict[str, list[str]] = {}
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for k in plot_models:
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fams.setdefault(maps.model_family_color(k), []).append(k)
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def _ver(k: str) -> list[float]:
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return [float(n) for n in re.findall(r"\d+(?:\.\d+)?", k)]
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model_labels = {max(ks, key=_ver): max(ks, key=_ver).replace("claude-", "") for ks in fams.values()}
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fig = maps.plot_value_map(
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"WVS Inglehart-Welzel", countries, P,
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("Survival", "Self-expression", "Traditional", "Secular-Rational"),
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models=plot_models, emphasize=emph)
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models=plot_models, model_labels=model_labels, emphasize=emph)
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fig.savefig(args.out, dpi=200, bbox_inches="tight")
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logger.info(f"wrote {args.out}")
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+52
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@@ -190,7 +190,6 @@ def draw_zone_hulls(ax, P: np.ndarray, countries: list[str], zones: dict[str, li
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from matplotlib.patches import Polygon as MplPolygon
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cidx = {c: i for i, c in enumerate(countries)}
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buf = pad * float(np.hypot(*(P.max(0) - P.min(0))))
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center = P.mean(0) # the crowded middle -- push zone labels away from it
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specs: list[tuple[str, tuple[float, float], str]] = []
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for zname, members in zones.items():
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pts = np.array([P[cidx[c]] for c in members if c in cidx])
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@@ -201,14 +200,13 @@ def draw_zone_hulls(ax, P: np.ndarray, countries: list[str], zones: dict[str, li
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zcol = ZONE_COLORS.get(zname, "#888888")
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ax.add_patch(MplPolygon(coords, closed=True, facecolor="none", edgecolor=zcol,
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lw=1.8, alpha=0.9, zorder=1.5))
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# anchor at the hull vertex FARTHEST from the plot centre: seeds the label in the sparse outer
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# region (the allocator then fine-tunes), instead of the top vertex which can face the crowd.
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apex = coords[int(np.argmax(np.hypot(*(coords - center).T)))]
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anchor = pts.mean(0) # zone centroid: the leader ties the label here
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if label:
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ax.text(apex[0], apex[1], zname, fontsize=10, color=zcol, ha="center", va="bottom",
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top = coords[np.argmax(coords[:, 1])] # ipsative maps draw it at the hull top vertex
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ax.text(top[0], top[1], zname, fontsize=10, color=zcol, ha="center", va="bottom",
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style="italic", fontweight="bold", zorder=5,
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path_effects=[pe.withStroke(linewidth=3.0, foreground="white")])
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specs.append((zname, (float(apex[0]), float(apex[1])), zcol))
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specs.append((zname, (float(anchor[0]), float(anchor[1])), zcol))
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return specs
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@@ -260,8 +258,32 @@ def model_family_color(name: str) -> str:
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return MODEL_RED
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def _open_slot(anchor: tuple[float, float], obstacles: list[tuple[float, float]],
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xlim: tuple[float, float], ylim: tuple[float, float], span: np.ndarray,
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radii=(0.08, 0.14, 0.22, 0.32, 0.44)) -> tuple[float, float]:
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"""A label position in the emptiest nearby space: scan a ring of candidate offsets (fractions of
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the data span) around `anchor` and keep the one whose NEAREST obstacle (a dot or an already-placed
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label) is farthest, with a mild penalty for straying from the anchor. Distances are normalised by
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the data span so x/y crowding weigh equally. Used for the few big zone labels, which adjustText's
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local force-relaxation otherwise parks in a crowded local minimum."""
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ax0, ay0 = anchor
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best, best_score = (ax0, ay0), -np.inf
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for r in radii:
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for deg in range(0, 360, 20):
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a = np.radians(deg)
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x, y = ax0 + r * span[0] * np.cos(a), ay0 + r * span[1] * np.sin(a)
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if not (xlim[0] < x < xlim[1] and ylim[0] < y < ylim[1]):
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continue
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dmin = min(np.hypot((x - ox) / span[0], (y - oy) / span[1]) for ox, oy in obstacles)
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score = dmin - 0.35 * r # prefer open space; mild pull toward the anchor
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if score > best_score:
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best_score, best = score, (x, y)
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return best
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def plot_value_map(display: str, countries: list[str], P: np.ndarray,
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poles: tuple[str, str, str, str], *, models: dict[str, tuple[float, float]] | None = None,
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model_labels: dict[str, str] | None = None,
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steer: dict[str, tuple[float, float, str]] | None = None,
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emphasize: set[str] | None = None, title: str | None = None, note: str | None = None):
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"""The interpretable "4-value map": two NAMED axes with four pole signposts through the human
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@@ -294,22 +316,25 @@ def plot_value_map(display: str, countries: list[str], P: np.ndarray,
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zone_specs = draw_zone_hulls(ax, P, countries, zones, label=False) # labels go through the allocator
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ax.scatter(P[:, 0], P[:, 1], s=26, c=dot_cols, alpha=0.85, edgecolors="white", linewidths=0.5, zorder=3)
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# ONE allocator for EVERY label -- country, model star, AND zone name. Each is created at its anchor
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# then MOVED by adjustText off the dots (obs_x/obs_y) and off the other labels into open space, with
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# a leader line. The zone names used to be nailed to their hull's top vertex (which lands in crowded
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# spots); routing them through the same allocator is the fix.
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# Two-stage placement. Point labels (country / model / steer) go through ONE adjustText pass (force
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# repulsion off the dots and each other, leader lines). The few big ZONE labels get a dedicated
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# emptiest-slot search first (adjustText's local relaxation parks them in crowded local minima), and
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# the point labels then avoid those. obs_x/obs_y are the dots every label must dodge.
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obs_x, obs_y = list(P[:, 0]), list(P[:, 1])
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lab_specs = [(P[i, 0], P[i, 1], countries[i], "#111", "normal", "normal", 9)
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for i, c in enumerate(countries) if c in label_set]
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if models:
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# each model is a STAR coloured by lab family (model_family_color); its label takes that colour.
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# The 95% CI is NOT drawn (whiskers overlap into noise with a dozen+ models) -- it lives in the
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# companion table, which also shows the wide ones are item-disagreement, not sampling noise.
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# each model is a STAR coloured by lab family. Every model is plotted, but only `model_labels`
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# get a text label (default: all) -- the WVS panel labels ONE representative per family and lets
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# colour + legend carry the rest. The 95% CI is not drawn (it lives in the companion table).
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mnames = list(models)
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mx = np.array([models[k][0] for k in mnames]); my = np.array([models[k][1] for k in mnames])
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mcols = [model_family_color(k) for k in mnames]
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ax.scatter(mx, my, s=230, marker="*", c=mcols, edgecolors="white", linewidths=0.8, zorder=8)
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lab_specs += [(x, y, k, col, "bold", "normal", 9) for k, x, y, col in zip(mnames, mx, my, mcols)]
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for k, x, y, col in zip(mnames, mx, my, mcols):
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disp = k if model_labels is None else model_labels.get(k)
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if disp:
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lab_specs.append((x, y, disp, col, "bold", "normal", 9))
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obs_x += list(mx); obs_y += list(my)
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if steer:
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bx, by, blab = steer["base"]
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@@ -324,13 +349,24 @@ def plot_value_map(display: str, countries: list[str], P: np.ndarray,
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ax.scatter(bx, by, s=90, c=C_BASE, edgecolors="white", linewidths=1.0, zorder=8)
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lab_specs.append((bx, by, blab, C_BASE, "bold", "normal", 9))
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obs_x.append(bx); obs_y.append(by)
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lab_specs += [(zx, zy, zn, zc, "bold", "italic", 10) for zn, (zx, zy), zc in zone_specs]
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ax.margins(0.13)
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fig.canvas.draw()
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xlim, ylim = ax.get_xlim(), ax.get_ylim()
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span = P.max(0) - P.min(0)
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obs_pts = list(zip(obs_x, obs_y))
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zone_texts, zplaced = [], []
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for zn, (zx, zy), zc in zone_specs: # big zone labels -> emptiest slot, leader to hull
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lx, ly = _open_slot((zx, zy), obs_pts + zplaced, xlim, ylim, span)
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zplaced.append((lx, ly))
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zone_texts.append(ax.annotate(
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zn, xy=(zx, zy), xytext=(lx, ly), color=zc, fontsize=10, fontweight="bold", fontstyle="italic",
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ha="center", va="center", zorder=9, arrowprops=dict(arrowstyle="-", color=zc, lw=0.7, alpha=0.6),
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path_effects=[pe.withStroke(linewidth=2.5, foreground="white")]))
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texts = [ax.text(x, y, t, color=c, fontsize=fs, fontweight=fw, fontstyle=st, ha="center",
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va="center", zorder=9, path_effects=[pe.withStroke(linewidth=2.5, foreground="white")])
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for x, y, t, c, fw, st, fs in lab_specs]
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adjust_text(texts, x=obs_x, y=obs_y, ax=ax, expand=(1.15, 1.4),
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adjust_text(texts, x=obs_x, y=obs_y, ax=ax, objects=zone_texts, expand=(1.15, 1.4),
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arrowprops=dict(arrowstyle="-", color="#aaa", lw=0.6))
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_pole_signposts(ax, med_x, med_y, poles)
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ax.set_xticks([]); ax.set_yticks([]); ax.set_xlabel(""); ax.set_ylabel("")
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