feat(altair): implement venn-labeled-items

plots/venn-labeled-items/implementations/python/altair.py

@@ -1,7 +1,7 @@
 """ anyplot.ai
 venn-labeled-items: Chartgeist-Style Venn Diagram with Labeled Items
-Library: altair 6.1.0 | Python 3.14.4
-Quality: 86/100 | Created: 2026-04-25
+Library: altair 6.2.2 | Python 3.13.14
+Quality: 85/100 | Updated: 2026-06-25
 """
 
 import importlib
@@ -11,35 +11,38 @@
 from collections import defaultdict
 
 
-# Drop script directory from sys.path so the `altair` package resolves, not this file
+# Drop script dir from sys.path so `altair` package resolves, not this file
 sys.path[:] = [p for p in sys.path if os.path.abspath(p or ".") != os.path.dirname(os.path.abspath(__file__))]
 alt = importlib.import_module("altair")
 pd = importlib.import_module("pandas")
 
-
-# Theme tokens
 THEME = os.getenv("ANYPLOT_THEME", "light")
 PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
 INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
 INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
 
-# Okabe-Ito categorical palette: brand green, vermillion, blue
+# Imprint palette — first series is always #009E73
 COLOR_A = "#009E73"
 COLOR_B = "#C475FD"
 COLOR_C = "#4467A3"
 
-# Symmetric three-circle Venn layout on a 1200x1200 square canvas
-CANVAS = 1200
-center_x, center_y = CANVAS / 2, CANVAS / 2
-RADIUS = 240
-OFFSET = RADIUS / math.sqrt(3)
+# Canvas: square 2400×2400 target (inner view 500×460, scale_factor=4.0)
+CANVAS_W = 500
+CANVAS_H = 460
+TARGET_W, TARGET_H = 2400, 2400
+
+# Symmetric three-circle Venn layout in a 500×460 coordinate space.
+# center_y=240 (below midpoint) shifts diagram toward canvas bottom, reducing empty lower space.
+center_x, center_y = 250.0, 240.0
+RADIUS = 90.0
+OFFSET = RADIUS / math.sqrt(3)  # ≈ 51.96
 
-cx_a = center_x - OFFSET * math.sin(math.radians(60))
-cy_a = center_y + OFFSET * math.cos(math.radians(60))
-cx_b = center_x + OFFSET * math.sin(math.radians(60))
-cy_b = center_y + OFFSET * math.cos(math.radians(60))
-cx_c = center_x
-cy_c = center_y - OFFSET
+cx_a = center_x - OFFSET * math.sin(math.radians(60))  # ≈ 205
+cy_a = center_y + OFFSET * math.cos(math.radians(60))  # ≈ 266
+cx_b = center_x + OFFSET * math.sin(math.radians(60))  # ≈ 295
+cy_b = cy_a
+cx_c = center_x  # 250
+cy_c = center_y - OFFSET  # ≈ 188
 
 df_circles = pd.DataFrame(
     [
@@ -49,15 +52,14 @@
     ]
 )
 
-# Category labels: outside each circle, on the side away from the diagram centroid
-label_a_x = cx_a + math.cos(math.radians(150)) * (RADIUS + 30)
-label_a_y = cy_a + math.sin(math.radians(150)) * (RADIUS + 30)
-label_b_x = cx_b + math.cos(math.radians(30)) * (RADIUS + 30)
-label_b_y = cy_b + math.sin(math.radians(30)) * (RADIUS + 30)
+# Category labels — placed outside each circle on the side away from the diagram centre
+label_a_x = cx_a + math.cos(math.radians(150)) * (RADIUS + 12)
+label_a_y = cy_a + math.sin(math.radians(150)) * (RADIUS + 12)
+label_b_x = cx_b + math.cos(math.radians(30)) * (RADIUS + 12)
+label_b_y = cy_b + math.sin(math.radians(30)) * (RADIUS + 12)
 label_c_x = cx_c
-label_c_y = cy_c - (RADIUS + 30)
+label_c_y = cy_c - (RADIUS + 12)
 
-# Items distributed across the seven Venn zones
 items_raw = [
     ("NFTs", "A"),
     ("Metaverse", "A"),
@@ -75,22 +77,24 @@
     ("Coffee", "ABC"),
 ]
 
-# Geometric centroids of each Venn region (chosen for clear in-zone placement)
+# Geometric centroids of each Venn region, verified to lie in the correct zone.
+# AC/BC pushed outward (x±50) and downward (y-41) from original to separate from
+# the ABC centroid, eliminating the collision in the densely-packed centre cluster.
 zone_centers = {
-    "A": (390, 715),
-    "B": (810, 715),
-    "C": (600, 357),
-    "AB": (600, 745),
-    "AC": (480, 540),
-    "BC": (720, 540),
-    "ABC": (600, 600),
+    "A": (155.0, 252.0),
+    "B": (345.0, 252.0),
+    "C": (250.0, 135.0),
+    "AB": (250.0, 290.0),
+    "AC": (200.0, 213.0),
+    "BC": (300.0, 213.0),
+    "ABC": (250.0, 254.0),
 }
 
+LINE_HEIGHT = 14.0
 zone_to_items = defaultdict(list)
-for label, zone in items_raw:
-    zone_to_items[zone].append(label)
+for lbl, zone in items_raw:
+    zone_to_items[zone].append(lbl)
 
-LINE_HEIGHT = 30
 records = []
 for zone, labels in zone_to_items.items():
     cx_zone, cy_zone = zone_centers[zone]
@@ -100,14 +104,14 @@
         records.append({"label": label, "zone": zone, "x": cx_zone, "y": start_y - idx * LINE_HEIGHT})
 df_items = pd.DataFrame(records)
 
-# Plot
-domain_x = [0, CANVAS]
-domain_y = [0, CANVAS]
+domain_x = [0, CANVAS_W]
+domain_y = [0, CANVAS_H]
+# circle_size: mark_point size is area in px² at view scale; radius = RADIUS px (1 data unit = 1 px here)
 circle_size = math.pi * RADIUS * RADIUS
 
 filled_circles = (
     alt.Chart(df_circles)
-    .mark_point(shape="circle", filled=True, opacity=0.22, strokeWidth=0)
+    .mark_point(shape="circle", filled=True, opacity=0.30, strokeWidth=0)
     .encode(
         x=alt.X("x:Q", scale=alt.Scale(domain=domain_x), axis=None),
         y=alt.Y("y:Q", scale=alt.Scale(domain=domain_y), axis=None),
@@ -131,7 +135,7 @@
     alt.Chart(pd.DataFrame([{"x": label_a_x, "y": label_a_y}]))
     .mark_text(
         text="Overhyped",
-        fontSize=30,
+        fontSize=14,
         fontWeight="bold",
         fontStyle="italic",
         font="serif",
@@ -149,7 +153,7 @@
     alt.Chart(pd.DataFrame([{"x": label_b_x, "y": label_b_y}]))
     .mark_text(
         text="Actually Useful",
-        fontSize=30,
+        fontSize=14,
         fontWeight="bold",
         fontStyle="italic",
         font="serif",
@@ -167,7 +171,7 @@
     alt.Chart(pd.DataFrame([{"x": label_c_x, "y": label_c_y}]))
     .mark_text(
         text="Secretly Loved",
-        fontSize=30,
+        fontSize=14,
         fontWeight="bold",
         fontStyle="italic",
         font="serif",
@@ -183,7 +187,7 @@
 
 item_labels = (
     alt.Chart(df_items)
-    .mark_text(fontSize=20, color=INK, fontWeight="normal")
+    .mark_text(fontSize=10, color=INK, fontWeight="normal")
     .encode(
         x=alt.X("x:Q", scale=alt.Scale(domain=domain_x), axis=None),
         y=alt.Y("y:Q", scale=alt.Scale(domain=domain_y), axis=None),
@@ -194,26 +198,42 @@
 chart = (
     alt.layer(filled_circles, outline_circles, label_a, label_b, label_c, item_labels)
     .properties(
-        width=CANVAS,
-        height=CANVAS,
+        width=CANVAS_W,
+        height=CANVAS_H,
         background=PAGE_BG,
         title=alt.Title(
-            text="Pop Culture Vibes · venn-labeled-items · altair · anyplot.ai",
+            text="Pop Culture Vibes · venn-labeled-items · python · altair · anyplot.ai",
             subtitle="An opinionated three-circle taxonomy",
-            fontSize=28,
-            subtitleFontSize=18,
+            fontSize=16,
+            subtitleFontSize=11,
             color=INK,
             subtitleColor=INK_SOFT,
             anchor="middle",
             font="serif",
             subtitleFont="serif",
             subtitleFontStyle="italic",
-            offset=24,
+            offset=16,
         ),
-        padding={"left": 30, "right": 30, "top": 20, "bottom": 20},
+        padding={"left": 20, "right": 20, "top": 10, "bottom": 10},
     )
     .configure_view(fill=PAGE_BG, stroke=None)
 )
 
-chart.save(f"plot-{THEME}.png", scale_factor=3.0)
+chart.save(f"plot-{THEME}.png", scale_factor=4.0)
+
+# Pad to exact 2400×2400 — vl-convert may land slightly short; never crop
+from PIL import Image as PILImage  # noqa: E402
+
+
+_img = PILImage.open(f"plot-{THEME}.png").convert("RGB")
+_w, _h = _img.size
+if _w > TARGET_W or _h > TARGET_H:
+    raise SystemExit(
+        f"vl-convert produced {_w}×{_h}, exceeds target {TARGET_W}×{TARGET_H}. Shrink chart width/height and re-render."
+    )
+if _w < TARGET_W or _h < TARGET_H:
+    _canvas = PILImage.new("RGB", (TARGET_W, TARGET_H), PAGE_BG)
+    _canvas.paste(_img, ((TARGET_W - _w) // 2, (TARGET_H - _h) // 2))
+    _canvas.save(f"plot-{THEME}.png")
+
 chart.save(f"plot-{THEME}.html")