wassname/moral-maps
1
0
Fork 0
mirror of https://github.com/wassname/moral-maps.git synced 2026-09-09 11:27:22 +08:00
Code Issues Packages Projects Releases Wiki Activity

maps: extract shared _map_annotations, fail loud on textalloc

Browse Source 
The zone/dot-colour/label-set policy was duplicated inline in plot_value_map and
plot_ipsative_pca -- subtle plotting policy that would silently diverge between
the two figures. One helper now, so they can't drift. Also drop the broad
except-Exception textalloc fallbacks (textalloc is a hard maps dep; the fallback
hid broken layouts) and a dead textalloc import in plot_ipsative_pca.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
This commit is contained in:
wassname
2026-07-05 08:25:28 +08:00
co-authored by Claudypoo
parent 520cbc04a4
commit 599b8528d3
1 changed files with 30 additions and 57 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/tinymfv/maps.py
+30 -57
View File
@@ -152,6 +152,25 @@ def outlying_countries(P: np.ndarray, countries: list[str], n: int = 4) -> set[s
return {countries[int(np.argmax(Pc[:, 0] * dx + Pc[:, 1] * dy))] for dx, dy in dirs}
def _map_annotations(P: np.ndarray, countries: list[str], zones_all: dict[str, list[str]] | None,
emphasize: set[str] | None, grey: str):
"""Shared map policy for plot_value_map + plot_ipsative_pca -- one copy so the two renderers can't
silently diverge: pick the 4 most-separate zones, colour each dot by its drawn zone (`grey` if
ungrouped), and build label_set = landmarks (emphasize) + 4 corner outliers + one central
representative per drawn zone. Returns (selected_zones, dot_cols, label_set)."""
zones = select_spread_zones(P, countries, zones_all, 4) if zones_all else {}
zone_of_c = {c: z for z, ms in zones.items() for c in ms}
dot_cols = [ZONE_COLORS.get(zone_of_c.get(c), grey) for c in countries]
cidx = {c: i for i, c in enumerate(countries)}
reps = set()
for ms in zones.values():
mem = [c for c in ms if c in cidx]
mp = P[[cidx[c] for c in mem]]
reps.add(mem[int(np.argmin(np.hypot(*(mp - mp.mean(0)).T)))])
label_set = (emphasize or set()) | outlying_countries(P, countries, 4) | reps
return zones, dot_cols, label_set
def draw_zone_hulls(ax, P: np.ndarray, countries: list[str], zones: dict[str, list[str]],
pad: float = 0.022) -> None:
"""Economist-style zone outline: the tight CONVEX HULL of a zone's country-mean points, rounded
@@ -218,16 +237,7 @@ def plot_value_map(display: str, countries: list[str], P: np.ndarray,
import textalloc as ta
zones_all, emph = zones_for(countries)
emph = (emphasize or set()) | emph
zones = select_spread_zones(P, countries, zones_all, 4)
zone_of_c = {c: z for z, ms in zones.items() for c in ms}
dot_cols = [ZONE_COLORS.get(zone_of_c.get(c), "#888888") for c in countries]
cidx = {c: i for i, c in enumerate(countries)}
reps = set()
for ms in zones.values():
mem = [c for c in ms if c in cidx]
mp = P[[cidx[c] for c in mem]]
reps.add(mem[int(np.argmin(np.hypot(*(mp - mp.mean(0)).T)))])
label_set = emph | outlying_countries(P, countries, 4) | reps
zones, dot_cols, label_set = _map_annotations(P, countries, zones_all, emph, "#888888")
med_x, med_y = float(np.median(P[:, 0])), float(np.median(P[:, 1]))
fig, ax = plt.subplots(figsize=(10.5, 8.5))
@@ -372,21 +382,10 @@ def compass(ax_main, L: np.ndarray, labels: list[str], title: str = "compass",
r = np.hypot(x, y)
tx.append(x / r * (r + 0.07)); ty.append(y / r * (r + 0.07)); tips_x.append(x); tips_y.append(y)
cax.set_xlim(-1.5, 1.5); cax.set_ylim(-1.5, 1.5)
placed = False
try: # textalloc spreads colliding tip labels
import textalloc as ta
ta.allocate_text(ax_main.figure, cax, tx, ty, [l.capitalize() for l in labels],
x_scatter=tips_x + [0], y_scatter=tips_y + [0], textsize=7.5,
linecolor=color, linewidth=0.5, textcolor=color, draw_lines=True)
placed = True
except Exception:
placed = False
if not placed:
for j, lab in enumerate(labels):
x, y = L[j]; r = np.hypot(x, y)
cax.text(x / r * (r + 0.07), y / r * (r + 0.07), lab.capitalize(), fontsize=7.5,
fontweight="bold", color=color, ha="left" if x >= 0 else "right",
va="bottom" if y >= 0 else "top", clip_on=False)
import textalloc as ta # textalloc spreads colliding tip labels
ta.allocate_text(ax_main.figure, cax, tx, ty, [l.capitalize() for l in labels],
x_scatter=tips_x + [0], y_scatter=tips_y + [0], textsize=7.5,
linecolor=color, linewidth=0.5, textcolor=color, draw_lines=True)
cax.set_aspect("equal"); cax.axis("off")
cax.set_title(title, fontsize=10, fontweight="bold", color=color, pad=3)
@@ -453,10 +452,6 @@ def plot_ipsative_pca(instr: Instrument, dims: list[str], countries: list[str],
variance dominates). An eigenvalue floor gives a 1- or 2-country zone a visible blob. The PCA is
fit on the country means M; `respondents`/`haze` only scatter + set the crop. Returns the
Figure."""
try:
import textalloc as ta
except ImportError:
ta = None
_, Vt, var, mu, Pc = ipsative_pca(M) # fit on country means: between-country axes
P = (M @ Pc - mu) @ Vt[:2].T
cloud = haze if haze is not None else respondents # what we scatter + crop to (fit is separate)
@@ -473,13 +468,11 @@ def plot_ipsative_pca(instr: Instrument, dims: list[str], countries: list[str],
Pi = (cloud @ Pc - mu) @ Vt[:2].T
ax.scatter(Pi[:, 0], Pi[:, 1], s=4, c="#8f8a7e", alpha=0.14, edgecolors="none",
zorder=1, rasterized=True)
# Same clean treatment as the WVS map: draw only the 4 zones covering the most separate space, as
# edge-only hulls, and colour each dot by its drawn zone (grey if ungrouped).
sel_zones = select_spread_zones(P, countries, zones, 4) if zones else {}
# Same clean treatment as the WVS map (shared policy via _map_annotations): draw only the 4 zones
# covering the most separate space, as edge-only hulls, and colour each dot by its drawn zone.
sel_zones, dot_cols, label_set = _map_annotations(P, countries, zones, emphasize, C_HUM)
if sel_zones:
draw_zone_hulls(ax, P, countries, sel_zones)
zone_of_c = {c: z for z, ms in sel_zones.items() for c in ms}
dot_cols = [ZONE_COLORS.get(zone_of_c.get(c), C_HUM) for c in countries]
ax.scatter(P[:, 0], P[:, 1], s=26, c=dot_cols, alpha=0.75, edgecolors="white", linewidths=0.5, zorder=3)
# Society labels: each name/ISO code is pinned RIGHT NEXT to its dot (small fixed offset, no
# leader line). A label is dropped if its box would collide with an already-placed one -- better an
@@ -491,13 +484,6 @@ def plot_ipsative_pca(instr: Instrument, dims: list[str], countries: list[str],
renderer = fig.canvas.get_renderer()
placed_boxes = []
emph = emphasize or set()
cidx = {c: i for i, c in enumerate(countries)}
reps = set()
for ms in sel_zones.values():
mem = [c for c in ms if c in cidx]
mp = P[[cidx[c] for c in mem]]
reps.add(mem[int(np.argmin(np.hypot(*(mp - mp.mean(0)).T)))])
label_set = emph | outlying_countries(P, countries, 4) | reps
order_lr = [i for i in np.argsort(P[:, 0]) if countries[i] in label_set] # leftmost wins contested space
order = [i for i in order_lr if countries[i] in emph] + [i for i in order_lr if countries[i] not in emph]
for i in order:
@@ -807,10 +793,7 @@ def plot_range_zoom(instr: Instrument, dims: list[str], cs: list[float], prof: d
"""Zoomed companion: one subplot per factor with its OWN y-axis, so the steer (small vs the
human spread) is legible. Societies near the steer named; off-range extremes in the corners.
Returns the Figure."""
try:
import textalloc as ta
except ImportError:
ta = None
import textalloc as ta
n = len(dims)
ncol = min(3, n)
nrow = (n + ncol - 1) // ncol
@@ -849,18 +832,8 @@ def plot_range_zoom(instr: Instrument, dims: list[str], cs: list[float], prof: d
txt = [("c=0" if c == 0 else f"c={c:+g}") for c in cs] + list(named)
dot_x = [xs] * len(cs) + (list(soc_x) if near else [])
dot_y = list(map(float, yv)) + ([v for _, v in near] if near else [])
placed = False
if ta is not None:
try:
ta.allocate_text(fig, ax, tx, ty, txt, x_scatter=dot_x, y_scatter=dot_y,
textsize=6.5, linecolor="#bbbbbb", linewidth=0.4, textcolor="#333333")
placed = True
except Exception:
placed = False
if not placed:
for x, y, t in zip(tx, ty, txt):
ax.annotate(t, (x + (0.12 if x >= 0 else -0.12), y), fontsize=6.5,
ha="left" if x >= 0 else "right", va="center", color="#333333")
ta.allocate_text(fig, ax, tx, ty, txt, x_scatter=dot_x, y_scatter=dot_y,
textsize=6.5, linecolor="#bbbbbb", linewidth=0.4, textcolor="#333333")
mx_name, mx_val = max(soc, key=lambda t: t[1])
mn_name, mn_val = min(soc, key=lambda t: t[1])
if mx_val > yhi: