feat(plotnine): implement venn-labeled-items

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

@@ -1,14 +1,13 @@
 """ anyplot.ai
 venn-labeled-items: Chartgeist-Style Venn Diagram with Labeled Items
-Library: plotnine 0.15.3 | Python 3.14.4
-Quality: 85/100 | Created: 2026-04-25
+Library: plotnine 0.15.7 | Python 3.13.14
+Quality: 88/100 | Updated: 2026-06-25
 """
 
 import os
 import sys
 
 
-# Avoid name collision so `from plotnine import ...` resolves to the package
 _HERE = os.path.dirname(os.path.abspath(__file__))
 sys.path = [p for p in sys.path if os.path.abspath(p) != _HERE]
 
@@ -19,6 +18,7 @@
     coord_fixed,
     element_blank,
     element_rect,
+    geom_label,
     geom_polygon,
     geom_text,
     ggplot,
@@ -33,119 +33,120 @@
 # Theme tokens
 THEME = os.getenv("ANYPLOT_THEME", "light")
 PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
 INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
 INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
 INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
 
-# Okabe-Ito categorical (positions 1, 2, 3)
-COLOR_A = "#009E73"  # brand green — ALWAYS first series
-COLOR_B = "#C475FD"  # vermillion
-COLOR_C = "#4467A3"  # blue
+# Imprint palette positions 1–3
+COLOR_A = "#009E73"
+COLOR_B = "#C475FD"
+COLOR_C = "#4467A3"
 
 # Symmetric three-circle Venn geometry
 RADIUS = 1.5
 circle_meta = [
-    ("Overhyped", -0.85, 0.50, COLOR_A),
-    ("Actually Useful", 0.85, 0.50, COLOR_B),
-    ("Secretly Loved", 0.00, -1.00, COLOR_C),
+    ("Peak Instagram", -0.85, 0.50, COLOR_A),
+    ("Actually Nutritious", 0.85, 0.50, COLOR_B),
+    ("Surprisingly Addictive", 0.00, -1.00, COLOR_C),
 ]
 
-# Polygon ring per circle (semi-transparent fills, colored outline)
 theta = np.linspace(0, 2 * np.pi, 240)
 circle_rows = []
 for name, cx, cy, color in circle_meta:
     for t in theta:
         circle_rows.append({"name": name, "x": cx + RADIUS * np.cos(t), "y": cy + RADIUS * np.sin(t), "fill": color})
 circles_df = pd.DataFrame(circle_rows)
 
-# Items placed in their assigned zones
+# Items placed in their assigned Venn zones
 items_df = pd.DataFrame(
     [
-        # A only — Overhyped
-        ("NFTs", -2.05, 1.05),
-        ("Metaverse", -2.10, 0.55),
-        ("Smart Fridges", -2.00, 0.05),
-        # B only — Actually Useful
-        ("Google Maps", 2.05, 1.05),
-        ("Spreadsheets", 2.10, 0.55),
-        ("Calendar Apps", 2.00, 0.05),
-        # C only — Secretly Loved
-        ("Roller Skating", -0.70, -2.10),
-        ("Soap Operas", 0.70, -2.10),
-        # A ∩ B
-        ("ChatGPT", 0.00, 1.20),
-        ("Smartwatches", 0.00, 0.85),
-        # A ∩ C
-        ("Crocs", -1.10, -0.20),
-        ("Vinyl Records", -1.05, -0.60),
-        # B ∩ C
-        ("Dolly Parton", 1.10, -0.20),
-        ("Spotify", 1.05, -0.60),
-        # A ∩ B ∩ C
-        ("Sourdough", 0.00, 0.12),
-        ("TikTok", 0.00, -0.32),
+        # A only — Peak Instagram (upper-left)
+        ("Cloud Bread", -2.00, 1.30),
+        ("Charcoal Ice Cream", -2.30, 0.52),
+        ("Butterfly Pea Tea", -2.20, -0.05),
+        # B only — Actually Nutritious (upper-right)
+        ("Sardines", 2.00, 1.30),
+        ("Kimchi", 2.30, 0.52),
+        ("Lentil Soup", 2.20, -0.05),
+        # C only — Surprisingly Addictive (bottom)
+        ("Takis", -0.95, -2.25),
+        ("Boba Tea", 0.00, -2.58),
+        ("Funyuns", 0.95, -2.25),
+        # A ∩ B — photogenic and nutritious (top center)
+        ("Avocado Toast", 0.00, 1.35),
+        ("Overnight Oats", 0.00, 0.82),
+        # A ∩ C — photogenic and addictive (lower left, centered in zone)
+        ("Cronuts", -0.90, -0.55),
+        ("Dirty Soda", -0.90, -1.05),
+        # B ∩ C — nutritious and addictive (lower right, centered in zone)
+        ("Greek Yogurt", 0.90, -0.55),
+        ("Edamame", 0.90, -1.05),
+        # A ∩ B ∩ C (center)
+        ("Sourdough", 0.00, 0.28),
+        ("Matcha", 0.00, -0.22),
     ],
     columns=["label", "x", "y"],
 )
 
-# Category labels rendered outside each circle, on its outer side
-cat_left_df = pd.DataFrame({"label": ["Overhyped"], "x": [-1.95], "y": [2.30], "color": [COLOR_A]})
-cat_right_df = pd.DataFrame({"label": ["Actually Useful"], "x": [1.95], "y": [2.30], "color": [COLOR_B]})
-cat_bottom_df = pd.DataFrame({"label": ["Secretly Loved"], "x": [0.00], "y": [-2.85], "color": [COLOR_C]})
+# Consolidated category labels — one DataFrame, one geom_text layer
+cat_df = pd.DataFrame(
+    {
+        "label": ["Peak Instagram", "Actually Nutritious", "Surprisingly Addictive"],
+        "x": [-1.80, 1.80, 0.00],
+        "y": [2.32, 2.32, -2.85],
+        "color": [COLOR_A, COLOR_B, COLOR_C],
+    }
+)
 
-# Editorial-style title text inside the canvas
-title_df = pd.DataFrame({"label": ["Chartgeist 2026"], "x": [0.0], "y": [3.25], "color": [INK]})
+# Editorial title and spec subtitle
+title_df = pd.DataFrame({"label": ["Food Trend Taxonomy"], "x": [0.0], "y": [3.22], "color": [INK]})
 subtitle_df = pd.DataFrame(
-    {"label": ["venn-labeled-items · plotnine · anyplot.ai"], "x": [0.0], "y": [2.85], "color": [INK_MUTED]}
+    {"label": ["venn-labeled-items · python · plotnine · anyplot.ai"], "x": [0.0], "y": [2.82], "color": [INK_MUTED]}
 )
 
 # Plot
 plot = (
     ggplot()
     + geom_polygon(
-        data=circles_df, mapping=aes(x="x", y="y", group="name", fill="fill", color="fill"), alpha=0.22, size=1.4
+        data=circles_df, mapping=aes(x="x", y="y", group="name", fill="fill"), color=INK_SOFT, alpha=0.22, size=0.6
     )
-    + geom_text(data=items_df, mapping=aes(x="x", y="y", label="label"), size=13, color=INK, family="serif")
-    + geom_text(
-        data=cat_left_df,
-        mapping=aes(x="x", y="y", label="label", color="color"),
-        size=22,
-        fontweight="bold",
+    # geom_label gives each item a clean background box — more readable in overlapping zones
+    + geom_label(
+        data=items_df,
+        mapping=aes(x="x", y="y", label="label"),
+        size=11,
+        color=INK,
+        fill=ELEVATED_BG,
+        label_size=0,
+        label_padding=0.12,
         family="serif",
-        ha="center",
-    )
-    + geom_text(
-        data=cat_right_df,
-        mapping=aes(x="x", y="y", label="label", color="color"),
-        size=22,
-        fontweight="bold",
-        family="serif",
-        ha="center",
     )
+    # Consolidated category label layer (was three separate geom_text calls)
     + geom_text(
-        data=cat_bottom_df,
+        data=cat_df,
         mapping=aes(x="x", y="y", label="label", color="color"),
-        size=22,
+        size=18,
         fontweight="bold",
         family="serif",
         ha="center",
     )
     + geom_text(
         data=title_df,
         mapping=aes(x="x", y="y", label="label", color="color"),
-        size=30,
+        size=26,
         fontweight="bold",
         fontstyle="italic",
         family="serif",
     )
-    + geom_text(data=subtitle_df, mapping=aes(x="x", y="y", label="label", color="color"), size=12, family="serif")
+    + geom_text(data=subtitle_df, mapping=aes(x="x", y="y", label="label", color="color"), size=14, family="serif")
     + scale_fill_identity()
     + scale_color_identity()
     + scale_x_continuous(limits=(-3.5, 3.5), expand=(0, 0))
     + scale_y_continuous(limits=(-3.5, 3.5), expand=(0, 0))
     + coord_fixed(ratio=1)
     + theme(
-        figure_size=(12, 12),
+        figure_size=(6, 6),
         plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
         panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
         axis_title=element_blank(),
@@ -158,4 +159,4 @@
     )
 )
 
-plot.save(f"plot-{THEME}.png", dpi=300, verbose=False)
+plot.save(f"plot-{THEME}.png", dpi=400, width=6, height=6, units="in", verbose=False)