feat(pygal): implement errorbar-basic

plots/errorbar-basic/implementations/python/pygal.py

@@ -1,10 +1,16 @@
 """ anyplot.ai
 errorbar-basic: Basic Error Bar Plot
-Library: pygal 3.1.0 | Python 3.14.4
-Quality: 88/100 | Updated: 2026-04-25
+Library: pygal 3.1.3 | Python 3.13.14
+Quality: 84/100 | Updated: 2026-06-30
 """
 
 import os
+import sys
+
+
+# Remove script's own directory from sys.path so 'import pygal' resolves the
+# installed package rather than this file.
+sys.path[:] = [p for p in sys.path if os.path.abspath(p or ".") != os.path.dirname(os.path.abspath(__file__))]
 
 import pygal
 from pygal.style import Style
@@ -14,54 +20,57 @@
 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"
 INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
 
-BRAND = "#009E73"  # Okabe-Ito position 1 — primary data color
+IMPRINT_PALETTE = ("#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477", "#99B314")
+BRAND = IMPRINT_PALETTE[0]  # #009E73 — Imprint palette position 1, always first series
+ANYPLOT_AMBER = "#DDCC77"  # warning / caution annotation (outside categorical pool, per pygal.md)
 
 # Data — dose-response study: vehicle control + escalating doses (mg/kg)
 categories = ["Vehicle", "1 mg/kg", "3 mg/kg", "10 mg/kg", "30 mg/kg", "100 mg/kg"]
 means = [25.3, 28.4, 33.1, 38.7, 47.5, 42.0]
-# Asymmetric errors: 10 and 30 mg/kg show notable lower-tail variability
+# Asymmetric errors: 10 mg/kg shows notable lower-tail variability
 err_lower = [2.1, 2.5, 3.0, 6.2, 4.8, 3.4]
 err_upper = [2.1, 2.5, 3.0, 2.8, 2.2, 3.4]
 
 n = len(categories)
 baseline = means[0]  # Vehicle/control mean — visual reference for treatment effects
 
-# Style — first series (baseline reference) uses muted ink, all data series use brand green
+# Colors: series ordering determines color assignment
+# 1: Mean ± error → BRAND; 2: asymmetry callout → ANYPLOT_AMBER; 3: baseline → INK_MUTED; 4+: error bars → BRAND
+colors_tuple = (BRAND, ANYPLOT_AMBER, INK_MUTED) + (BRAND,) * 62
+
 custom_style = Style(
     background=PAGE_BG,
     plot_background=PAGE_BG,
     foreground=INK,
     foreground_strong=INK,
     foreground_subtle=INK_MUTED,
-    colors=(INK_MUTED,) + (BRAND,) * 64,
-    title_font_size=56,
-    label_font_size=40,
-    major_label_font_size=40,
-    legend_font_size=36,
-    value_font_size=28,
-    tooltip_font_size=32,
-    stroke_width=6,
+    colors=colors_tuple,
+    title_font_size=66,
+    label_font_size=56,
+    major_label_font_size=44,
+    legend_font_size=44,
+    value_font_size=36,
+    tooltip_font_size=36,
+    stroke_width=4,
     opacity=1.0,
     opacity_hover=0.85,
 )
 
-# Y-axis zoomed to the data band with breathing room above and below
+# Y-axis range with breathing room
 data_min = min(m - e for m, e in zip(means, err_lower, strict=True))
 data_max = max(m + e for m, e in zip(means, err_upper, strict=True))
 pad = (data_max - data_min) * 0.15
 y_min = max(0.0, data_min - pad)
 y_max = data_max + pad
 
-# x positions shifted to 1..n so pygal's implicit x=0 line stays off-canvas
 chart = pygal.XY(
     style=custom_style,
-    width=4800,
-    height=2700,
+    width=3200,
+    height=1800,
     dots_size=24,
-    title="errorbar-basic · pygal · anyplot.ai",
+    title="errorbar-basic · python · pygal · anyplot.ai",
     x_title="Dose",
     y_title="Response Value (units)",
     show_legend=True,
@@ -77,8 +86,32 @@
 
 chart.x_labels = [{"label": categories[i], "value": i + 1} for i in range(n)]
 chart.x_labels_major = [{"label": categories[i], "value": i + 1} for i in range(n)]
+chart.y_labels = [20, 25, 30, 35, 40, 45, 50]
+
+# Mean points — first series (BRAND #009E73) so brand green is assigned as palette position 1
+mean_points = [
+    {"value": (i + 1, means[i]), "label": f"{categories[i]}: {means[i]:.1f} (−{err_lower[i]:.1f}/+{err_upper[i]:.1f})"}
+    for i in range(n)
+]
+chart.add("Mean ± error", mean_points, stroke=False, dots_size=28)
+
+# Asymmetric variability callout — second series (ANYPLOT_AMBER warning color)
+# Amber marker overlaid at 10 mg/kg creates a visual focal point for the chart's key insight:
+# lower-tail variability (6.2) substantially exceeds upper (2.8), indicating non-Gaussian spread
+asym_idx = 3  # 10 mg/kg
+chart.add(
+    "↓ Asymmetric at 10 mg/kg (−6.2 / +2.8)",
+    [
+        {
+            "value": (asym_idx + 1, means[asym_idx]),
+            "label": "10 mg/kg: lower-tail variability (6.2) ≫ upper (2.8) — floor-effect compression near peak response",
+        }
+    ],
+    stroke=False,
+    dots_size=38,
+)
 
-# Vehicle baseline reference line — visual hierarchy anchor at control mean
+# Vehicle baseline reference line — third series (INK_MUTED) for control comparison
 chart.add(
     "Vehicle baseline",
     [(0.5, baseline), (n + 0.5, baseline)],
@@ -87,21 +120,12 @@
     stroke_style={"width": 3, "dasharray": "18, 14"},
 )
 
-cap_width = 0.16  # Width of error bar caps in x-axis units
-
-# Mean points with rich tooltip labels (pygal interactive feature)
-mean_points = [
-    {"value": (i + 1, means[i]), "label": f"{categories[i]}: {means[i]:.1f} (-{err_lower[i]:.1f}/+{err_upper[i]:.1f})"}
-    for i in range(n)
-]
-chart.add("Mean ± error", mean_points, stroke=False, dots_size=28)
-
-# Error bars: separate series per segment for clean line breaks (no legend entry)
+# Error bars: vertical stem + upper and lower caps per data point
+cap_width = 0.16
 for i in range(n):
     x = i + 1
     low = means[i] - err_lower[i]
     high = means[i] + err_upper[i]
-
     chart.add(None, [(x, low), (x, high)], stroke=True, show_dots=False)
     chart.add(None, [(x - cap_width, low), (x + cap_width, low)], stroke=True, show_dots=False)
     chart.add(None, [(x - cap_width, high), (x + cap_width, high)], stroke=True, show_dots=False)