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feat(plotly): implement errorbar-basic (#9518)
## Implementation: `errorbar-basic` - python/plotly Implements the **python/plotly** version of `errorbar-basic`. **File:** `plots/errorbar-basic/implementations/python/plotly.py` **Parent Issue:** #973 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/28473053865)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>
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‎plots/errorbar-basic/implementations/python/plotly.py‎

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""" anyplot.ai
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errorbar-basic: Basic Error Bar Plot
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Library: plotly 6.7.0 | Python 3.14.4
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Quality: 85/100 | Updated: 2026-04-25
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Library: plotly 6.8.0 | Python 3.13.14
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Quality: 91/100 | Updated: 2026-06-30
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"""
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import importlib
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import os
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import sys
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import numpy as np
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import plotly.graph_objects as go
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# Drop script directory from sys.path so the `plotly` package resolves, not this file
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sys.path[:] = [p for p in sys.path if os.path.abspath(p or ".") != os.path.dirname(os.path.abspath(__file__))]
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go = importlib.import_module("plotly.graph_objects")
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np = importlib.import_module("numpy")
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# Theme tokens
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THEME = os.getenv("ANYPLOT_THEME", "light")
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PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
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ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
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INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
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INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
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GRID = "rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)"
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BRAND = "#009E73" # Okabe-Ito position 1
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INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
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GRID = "rgba(26,26,23,0.15)" if THEME == "light" else "rgba(240,239,232,0.15)"
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CTRL_FILL = "rgba(26,26,23,0.05)" if THEME == "light" else "rgba(240,239,232,0.05)"
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# Imprint palette — one hue per group (positions 1–6)
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IMPRINT_PALETTE = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#2ABCCD", "#954477"]
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# Data — clinical trial response (mg/dL) with asymmetric 95% confidence intervals
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np.random.seed(42)
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groups = ["Control", "Treatment A", "Treatment B", "Treatment C", "Treatment D", "Treatment E"]
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x_positions = list(range(len(groups)))
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means = np.array([42.3, 51.7, 63.2, 47.8, 72.4, 58.9])
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err_upper = np.array([5.4, 7.8, 4.1, 9.3, 3.6, 6.5])
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err_lower = np.array([4.1, 6.2, 3.8, 7.9, 4.7, 5.1])
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# Plot
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# Control CI bounds — reference band for comparison
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control_lo = float(means[0] - err_lower[0])
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control_hi = float(means[0] + err_upper[0])
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fig = go.Figure()
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fig.add_trace(
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go.Scatter(
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x=x_positions,
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y=means,
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mode="markers",
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marker=dict(size=28, color=BRAND, line=dict(color=PAGE_BG, width=3)),
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error_y=dict(
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type="data",
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symmetric=False,
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array=err_upper,
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arrayminus=err_lower,
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visible=True,
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thickness=4,
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width=18,
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color=BRAND,
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),
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name="Mean ± 95% CI",
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customdata=np.stack([np.array(groups), means - err_lower, means + err_upper], axis=-1),
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hovertemplate=(
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"<b>%{customdata[0]}</b><br>"
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"Mean: %{y:.1f} mg/dL<br>"
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"95%% CI: [%{customdata[1]:.1f}, %{customdata[2]:.1f}]"
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"<extra></extra>"
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),
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# Subtle control CI reference band (drawn below data)
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fig.add_hrect(y0=control_lo, y1=control_hi, fillcolor=CTRL_FILL, line_width=0, layer="below")
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# Control baseline dashed reference line
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fig.add_hline(y=float(means[0]), line_dash="dot", line_color=INK_MUTED, line_width=1.5)
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# Per-group traces — Imprint palette assigns each group a distinct hue
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for i, (group, x, mean, eu, el) in enumerate(
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zip(groups, x_positions, means.tolist(), err_upper.tolist(), err_lower.tolist(), strict=False)
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):
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color = IMPRINT_PALETTE[i]
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fig.add_trace(
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go.Scatter(
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x=[x],
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y=[mean],
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mode="markers",
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marker={"size": 20, "color": color, "line": {"color": PAGE_BG, "width": 2}},
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error_y={
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"type": "data",
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"symmetric": False,
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"array": [eu],
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"arrayminus": [el],
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"visible": True,
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"thickness": 3,
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"width": 12,
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"color": color,
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},
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name=group,
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customdata=[[group, round(mean - el, 1), round(mean + eu, 1)]],
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hovertemplate=(
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"<b>%{customdata[0]}</b><br>"
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"Mean: %{y:.1f} mg/dL<br>"
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"95%% CI: [%{customdata[1]}, %{customdata[2]}]"
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"<extra></extra>"
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),
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)
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)
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# Annotation: Treatment D (index 4) — highest mean response
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fig.add_annotation(
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x=4,
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y=float(means[4] + err_upper[4]),
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text="Peak response",
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showarrow=True,
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arrowhead=2,
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arrowcolor=INK_SOFT,
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arrowwidth=1.5,
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ax=0,
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ay=-32,
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font={"size": 10, "color": INK_SOFT},
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bgcolor=ELEVATED_BG,
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bordercolor=INK_SOFT,
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borderwidth=1,
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borderpad=3,
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xanchor="center",
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)
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# Annotation: control baseline label
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fig.add_annotation(
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x=5.55,
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y=float(means[0]),
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text="Control<br>baseline",
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showarrow=False,
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font={"size": 10, "color": INK_MUTED},
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xanchor="left",
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yanchor="middle",
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bgcolor=ELEVATED_BG,
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borderpad=2,
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)
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# Style
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fig.update_layout(
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title=dict(
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text="Clinical Response by Group · errorbar-basic · plotly · pyplots.ai",
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font=dict(size=28, color=INK),
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x=0.5,
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xanchor="center",
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y=0.95,
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),
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xaxis=dict(
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title=dict(text="Experimental Group", font=dict(size=22, color=INK)),
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tickfont=dict(size=18, color=INK_SOFT),
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tickmode="array",
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tickvals=x_positions,
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ticktext=groups,
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showgrid=False,
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linecolor=INK_SOFT,
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zeroline=False,
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ticks="",
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),
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yaxis=dict(
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title=dict(text="Response (mg/dL)", font=dict(size=22, color=INK)),
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tickfont=dict(size=18, color=INK_SOFT),
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gridcolor=GRID,
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gridwidth=1,
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linecolor=INK_SOFT,
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zeroline=False,
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range=[0, 90],
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ticks="",
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),
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autosize=False,
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title={
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"text": "Clinical Response by Group · errorbar-basic · python · plotly · anyplot.ai",
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"font": {"size": 16, "color": INK},
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"x": 0.5,
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"xanchor": "center",
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},
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xaxis={
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"title": {"text": "Experimental Group", "font": {"size": 12, "color": INK}},
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"tickfont": {"size": 10, "color": INK_SOFT},
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"tickmode": "array",
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"tickvals": x_positions,
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"ticktext": groups,
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"showgrid": False,
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"linecolor": INK_SOFT,
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"zeroline": False,
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"ticks": "",
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"range": [-0.6, 6.0],
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},
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yaxis={
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"title": {"text": "Response (mg/dL)", "font": {"size": 12, "color": INK}},
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"tickfont": {"size": 10, "color": INK_SOFT},
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"gridcolor": GRID,
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"gridwidth": 1,
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"linecolor": INK_SOFT,
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"zeroline": False,
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"range": [28, 88],
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"ticks": "",
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},
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paper_bgcolor=PAGE_BG,
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plot_bgcolor=PAGE_BG,
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font=dict(color=INK),
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margin=dict(l=140, r=80, t=130, b=120),
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font={"color": INK},
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margin={"l": 80, "r": 80, "t": 80, "b": 60},
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showlegend=True,
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legend=dict(
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font=dict(size=16, color=INK_SOFT),
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bgcolor=ELEVATED_BG,
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bordercolor=INK_SOFT,
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borderwidth=1,
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x=0.98,
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y=0.98,
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xanchor="right",
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yanchor="top",
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),
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hoverlabel=dict(bgcolor=ELEVATED_BG, bordercolor=INK_SOFT, font=dict(color=INK, size=16)),
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legend={
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"font": {"size": 10, "color": INK_SOFT},
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"bgcolor": ELEVATED_BG,
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"bordercolor": INK_SOFT,
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"borderwidth": 1,
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"x": 0.98,
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"y": 0.98,
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"xanchor": "right",
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"yanchor": "top",
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},
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hoverlabel={"bgcolor": ELEVATED_BG, "bordercolor": INK_SOFT, "font": {"color": INK, "size": 10}},
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)
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# Save
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fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
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# Save — landscape 3200 × 1800 (width=800 × scale=4, height=450 × scale=4)
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fig.write_image(f"plot-{THEME}.png", width=800, height=450, scale=4)
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fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")

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