Bar (Advanced)

Vertical bar chart — advanced template (real data + narrative).

Source: dartwork_mpl/asset/prompt/05-templates/advanced/bar.py · MCP dartwork-mpl://template/advanced/bar.

[VISUAL] ⚠️  TEXT_CONTRAST: Text contrast 1.68:1 is below the 4.5:1 AA threshold for normal text (sample: 'EU 2030 target ≈ 55%')
[VISUAL] 💡 TEXT_CONTRAST: Text contrast 3.32:1 is below the 4.5:1 AA threshold for normal text (sample: 'Top-5 markets, 2024 — only Norway has...')
[VISUAL] ⚠️  TEXT_CONTRAST: Text contrast 2.07:1 is below the 4.5:1 AA threshold for normal text (sample: 'Source: IEA Global EV Outlook 2024 (i...')
[VISUAL] 💡 GRAYSCALE_SAFETY: Data colors have near-identical grayscale luminance: #ffbb50/#54d3aa, #ffbb50/#7dddbd, #00c897/#54d3aa, #54d3aa/#7dddbd, #7dddbd/#a0e7cf

=== FIX SUGGESTIONS ===
[VISUAL] ⚠️  TEXT_CONTRAST: Text contrast 1.68:1 is below the 4.5:1 AA threshold for normal text (sample: 'EU 2030 target ≈ 55%')
[VISUAL] 💡 TEXT_CONTRAST: Text contrast 3.32:1 is below the 4.5:1 AA threshold for normal text (sample: 'Top-5 markets, 2024 — only Norway has...')
[VISUAL] ⚠️  TEXT_CONTRAST: Text contrast 2.07:1 is below the 4.5:1 AA threshold for normal text (sample: 'Source: IEA Global EV Outlook 2024 (i...')
[VISUAL] 💡 GRAYSCALE_SAFETY: Data colors have near-identical grayscale luminance: #ffbb50/#54d3aa, #ffbb50/#7dddbd, #00c897/#54d3aa, #54d3aa/#7dddbd, #7dddbd/#a0e7cf

# ai-template-meta-start
# tier: advanced
# basic_counterpart: bar
# use_case: Rank a small categorical set with a reference threshold and per-bar value labels
# difficulty: intermediate
# data_shape: categories: list[str], values: list[float], threshold: float
# tags: bar, ranking, reference-line, annotated, narrative
# narrative: 2024 BEV market share, top-5 leaders vs. EU 2030 mandate (55%)
# advanced_apis: dm.cspace, dm.format_axis_si (for non-percent), PercentFormatter, axhline, ax.text per bar, dm.check_figure_quality
# ai-template-meta-end

import matplotlib.pyplot as plt
from matplotlib.ticker import PercentFormatter

import dartwork_mpl as dm

# 1. Style preset — switch to "report" / "presentation" / "*-kr" freely.
dm.style.use("scientific")

# 2. Real-world data with a story.
# Source (illustrative, near-2024 figures): IEA Global EV Outlook 2024
# https://www.iea.org/reports/global-ev-outlook-2024
countries = ["Norway", "Iceland", "Sweden", "China", "Germany"]
bev_share = [
    88.9,
    71.0,
    38.7,
    25.0,
    18.4,
]  # battery EV share of new car sales, %
eu_2030_target = 55.0  # EU CO2 fleet target implies ~55% BEV share by 2030

# 3. OKLCH gradient — color encodes magnitude (perceptually uniform).
#    dm.cspace(start, end, n) returns Color objects across OKLCH space.
#    Higher value → deeper hue (sequential convention).
gradient = dm.cspace("dc.teal5", "dc.teal1", n=len(countries))
bar_colors = [c.to_hex() for c in gradient]

# 4. Figure — col1 width keeps the layout dense and reviewer-friendly.
fig, ax = plt.subplots(figsize=dm.figsize(dm.col1, "standard"))

# 5. Bars + per-bar value labels (annotation density carries the story).
bars = ax.bar(
    countries, bev_share, color=bar_colors, edgecolor="white", linewidth=0.3
)
for bar_, v in zip(bars, bev_share, strict=False):
    ax.text(
        bar_.get_x() + bar_.get_width() / 2,
        v + 1.5,
        f"{v:.1f}%",
        ha="center",
        va="bottom",
        fontsize=dm.fs(-1),
        fontweight=dm.fw(1),
    )

# 6. Reference threshold — EU 2030 mandate as a horizontal context line.
ax.axhline(
    eu_2030_target, linestyle="--", linewidth=0.5, color="dc.amber4", zorder=1
)
ax.text(
    len(countries) - 0.5,
    eu_2030_target + 1.5,
    f"EU 2030 target ≈ {eu_2030_target:.0f}%",
    ha="right",
    va="bottom",
    fontsize=dm.fs(-1),
    color="dc.amber4",
    fontstyle="italic",
)

# 7. Axes formatting — domain-aware (percent), no chart-junk.
ax.yaxis.set_major_formatter(PercentFormatter(decimals=0))
ax.set_ylim(0, 105)
ax.set_ylabel("BEV share of new car sales")
ax.set_xlabel("Market")

# 8. Title + takeaway subtitle (narrative-led). Pad the title up so the
#    subtitle line gets clear vertical separation.
ax.set_title(
    "Norway leads global BEV adoption by a wide margin",
    fontsize=dm.fs(1),
    fontweight=dm.fw(1),
    loc="left",
    pad=18,
)
ax.text(
    0.0,
    1.02,
    "Top-5 markets, 2024 — only Norway has cleared the EU 2030 trajectory.",
    transform=ax.transAxes,
    ha="left",
    va="bottom",
    fontsize=dm.fs(-1),
    color="oc.gray6",
)

# 9. Source footnote — non-negotiable for real-data plots.
fig.text(
    0.01,
    0.005,
    "Source: IEA Global EV Outlook 2024 (illustrative).",
    fontsize=dm.fs(-2),
    color="oc.gray5",
    ha="left",
    va="bottom",
)

# 10. Layout — simple_layout is flush (margin=0); a small inch margin
#     gives subtitle / source footnote / x-label room to breathe.
#     Pair with validate_with_fixes to catch anything left.
dm.simple_layout(fig, margin=dm.inch(0.08))
dm.validate_with_fixes(fig)

# 11. Self-check — surfaces remaining clipping / overlap / contrast
#     issues before the agent reports "done". Returns [] when clean.
issues = dm.check_figure_quality(fig)
if issues:
    print(f"[bar-advanced] quality issues: {issues}")

dm.save_formats(fig, "bar_advanced")