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feat(pygal): implement sequence-logo-basic (#4610)
## Implementation: `sequence-logo-basic` - pygal Implements the **pygal** version of `sequence-logo-basic`. **File:** `plots/sequence-logo-basic/implementations/pygal.py` **Parent Issue:** #4421 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/22780525053)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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‎plots/sequence-logo-basic/implementations/pygal.py‎

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""" pyplots.ai
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sequence-logo-basic: Sequence Logo for Motif Visualization
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Library: pygal 3.1.0 | Python 3.14.3
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Quality: 81/100 | Created: 2026-03-06
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"""
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import numpy as np
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import pygal
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from pygal.style import Style
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# Data — ETS transcription factor binding site motif (10 positions)
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# Positions 2-7 form the conserved GGAATT core
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frequencies = {
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1: {"A": 0.40, "C": 0.20, "G": 0.25, "T": 0.15},
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2: {"A": 0.10, "C": 0.05, "G": 0.80, "T": 0.05},
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3: {"A": 0.05, "C": 0.05, "G": 0.85, "T": 0.05},
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4: {"A": 0.90, "C": 0.03, "G": 0.04, "T": 0.03},
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5: {"A": 0.85, "C": 0.05, "G": 0.05, "T": 0.05},
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6: {"A": 0.05, "C": 0.05, "G": 0.05, "T": 0.85},
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7: {"A": 0.05, "C": 0.05, "G": 0.05, "T": 0.85},
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8: {"A": 0.25, "C": 0.30, "G": 0.20, "T": 0.25},
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9: {"A": 0.15, "C": 0.35, "G": 0.35, "T": 0.15},
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10: {"A": 0.30, "C": 0.20, "G": 0.30, "T": 0.20},
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}
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nucleotides = ["A", "C", "G", "T"]
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max_entropy = 2.0 # bits for DNA
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# Calculate information content at each position
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info_content = {}
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for pos, freqs in frequencies.items():
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entropy = 0
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for nt in nucleotides:
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f = freqs[nt]
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if f > 0:
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entropy -= f * np.log2(f)
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info_content[pos] = max_entropy - entropy
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# Identify conserved core (IC > 0.5 bits) for visual emphasis
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core_positions = {pos for pos, ic in info_content.items() if ic > 0.5}
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# Scale each nucleotide height by frequency * information content
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# Build per-nucleotide series with letter labels inside bars
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stacked_data = {nt: [] for nt in nucleotides}
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for pos in sorted(frequencies.keys()):
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ic = info_content[pos]
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for nt in nucleotides:
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height = round(frequencies[pos][nt] * ic, 4)
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show_letter = height >= 0.10
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is_core = pos in core_positions
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stacked_data[nt].append(
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{
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"value": height,
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"label": (
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f"{'[core] ' if is_core else ''}Pos {pos}: {nt} = {frequencies[pos][nt]:.0%} x {ic:.2f} bits"
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),
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"formatter": (lambda x, letter=nt, show=show_letter: letter if show else ""),
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}
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)
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# Colorblind-safe DNA palette: teal A, blue C, amber G, purple T
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# Avoids red-green confusion while maintaining visual distinctiveness
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custom_style = Style(
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background="white",
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plot_background="#f8f9fa",
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foreground="#2d2d2d",
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foreground_strong="#111111",
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foreground_subtle="#e0e0e0",
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colors=("#0f766e", "#1d4ed8", "#d97706", "#7c3aed"),
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opacity=0.92,
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opacity_hover=1.0,
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title_font_size=36,
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label_font_size=22,
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major_label_font_size=20,
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legend_font_size=22,
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value_font_size=24,
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title_font_family="sans-serif",
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label_font_family="sans-serif",
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major_label_font_family="sans-serif",
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legend_font_family="sans-serif",
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value_font_family="monospace",
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tooltip_font_size=18,
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tooltip_font_family="monospace",
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)
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# X-labels: mark conserved core positions for emphasis
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x_labels = []
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for pos in sorted(frequencies.keys()):
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if pos in core_positions:
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label = f"*{pos}*"
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else:
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label = str(pos)
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x_labels.append(label)
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# Plot
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chart = pygal.StackedBar(
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width=4800,
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height=2700,
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style=custom_style,
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title="sequence-logo-basic · pygal · pyplots.ai",
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x_title="Position (* = conserved core, IC > 0.5 bits)",
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y_title="Information content (bits)",
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show_x_guides=False,
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show_y_guides=True,
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show_minor_y_labels=False,
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margin=60,
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margin_bottom=120,
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spacing=6,
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legend_at_bottom=True,
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legend_at_bottom_columns=4,
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legend_box_size=28,
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print_values=True,
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print_values_position="center",
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rounded_bars=3,
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y_labels_major_count=6,
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truncate_legend=-1,
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tooltip_border_radius=10,
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tooltip_fancy_mode=True,
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min_scale=0,
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range=(0, 1.6),
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x_label_rotation=0,
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secondary_style=custom_style,
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inner_radius=0,
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js=[],
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)
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chart.x_labels = x_labels
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for nt in nucleotides:
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chart.add(nt, stacked_data[nt])
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# Save
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chart.render_to_png("plot.png")
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chart.render_to_file("plot.html")

‎plots/sequence-logo-basic/metadata/pygal.yaml‎

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library: pygal
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specification_id: sequence-logo-basic
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created: '2026-03-06T20:25:16Z'
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updated: '2026-03-06T20:51:27Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 22780525053
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issue: 4421
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python_version: 3.14.3
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library_version: 3.1.0
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preview_url: https://storage.googleapis.com/pyplots-images/plots/sequence-logo-basic/pygal/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/sequence-logo-basic/pygal/plot_thumb.png
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preview_html: https://storage.googleapis.com/pyplots-images/plots/sequence-logo-basic/pygal/plot.html
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quality_score: 81
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review:
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strengths:
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- 'Excellent data quality: real ETS transcription factor binding site with biologically
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accurate frequencies'
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- Colorblind-safe palette (teal/blue/amber/purple) with deliberate avoidance of
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red-green confusion
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- Clean, well-structured code with appropriate complexity
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- Good use of pygal-specific features (formatters, tooltips, rounded bars, dual
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output)
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- Core position marking on x-axis adds context to the visualization
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weaknesses:
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- 'Not a true sequence logo: letters are small text labels inside bars rather than
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scaled glyphs filling the bar height'
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- Fixed stacking order (A, C, G, T) rather than frequency-sorted per position as
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spec requires
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- Y-axis range (0-1.6) creates wasted vertical space above the tallest bar (~1.35)
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image_description: 'The plot is a stacked bar chart with 10 positions along the
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x-axis and "Information content (bits)" on the y-axis (ranging from 0 to ~1.5).
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Four nucleotide series are displayed: A (teal/green), C (blue), G (amber/orange),
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T (red/purple). Positions 2-7 feature tall stacked bars representing a conserved
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GGAATT core — position 4 is the tallest (~1.35 bits, dominated by green A). Positions
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1, 8, 9, 10 have very short bars indicating low information content. Letters (G,
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A, T) are printed as text labels inside the larger bar segments. The title reads
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"sequence-logo-basic · pygal · pyplots.ai" at the top. A legend at the bottom
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shows all four nucleotides in a 4-column layout. The plot background is light
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gray (#f8f9fa) on a white canvas, with rounded bar corners and subtle styling.'
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criteria_checklist:
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visual_quality:
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score: 27
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max: 30
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items:
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- id: VQ-01
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name: Text Legibility
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score: 7
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max: 8
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passed: true
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comment: Font sizes explicitly set (title=36, labels=22, major_labels=20,
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value=24). All text readable. Title slightly compact relative to canvas.
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- id: VQ-02
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name: No Overlap
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score: 6
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max: 6
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passed: true
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comment: No overlapping text or elements. X-labels well-spaced, legend at
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bottom in 4 columns.
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- id: VQ-03
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name: Element Visibility
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score: 5
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max: 6
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passed: true
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comment: Conserved positions prominent. Positions 8-10 have very short bars
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where segments are hard to distinguish.
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- id: VQ-04
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name: Color Accessibility
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score: 4
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max: 4
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passed: true
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comment: Teal/blue/amber/purple palette avoids red-green confusion with good
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contrast.
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- id: VQ-05
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name: Layout & Canvas
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score: 3
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max: 4
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passed: true
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comment: Plot fills ~50-60% of canvas. Some wasted vertical space above tallest
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bar.
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- id: VQ-06
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name: Axis Labels & Title
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score: 2
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max: 2
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passed: true
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comment: Y-axis with units (bits), X-axis descriptive with core position context.
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design_excellence:
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score: 12
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max: 20
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items:
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- id: DE-01
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name: Aesthetic Sophistication
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score: 5
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max: 8
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passed: true
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comment: Custom palette, light gray background, rounded bars, custom opacity.
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Above defaults but not publication-ready.
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- id: DE-02
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name: Visual Refinement
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score: 4
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max: 6
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passed: true
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comment: No x-guides, subtle foreground colors, custom margins and spacing,
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organized legend.
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- id: DE-03
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name: Data Storytelling
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score: 3
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max: 6
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passed: true
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comment: Conserved core visually stands out. Core positions marked on x-axis.
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Letters identify dominant nucleotides.
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spec_compliance:
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score: 11
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max: 15
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items:
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- id: SC-01
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name: Plot Type
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score: 3
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max: 5
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passed: false
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comment: Stacked bar chart approximation rather than true sequence logo with
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scaled letter glyphs.
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- id: SC-02
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name: Required Features
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score: 2
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max: 4
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passed: false
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comment: Missing frequency-based stacking order and scaled letter glyphs.
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IC-scaled heights and DNA colors present.
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- id: SC-03
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name: Data Mapping
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score: 3
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max: 3
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passed: true
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comment: X-axis positions 1-10, Y-axis information content in bits. Stack
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heights correctly reflect IC.
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- id: SC-04
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name: Title & Legend
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score: 3
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max: 3
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passed: true
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comment: Title follows exact format. Legend correctly labels all four nucleotides.
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data_quality:
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score: 14
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max: 15
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 5
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max: 6
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passed: true
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comment: '10-position motif with good variation: highly conserved, mixed,
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and near-uniform positions.'
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- id: DQ-02
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name: Realistic Context
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score: 5
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max: 5
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passed: true
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comment: ETS transcription factor binding site with GGAATT core — real, well-known
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biological motif.
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- id: DQ-03
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name: Appropriate Scale
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score: 4
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max: 4
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passed: true
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comment: Frequencies sum to 1.0 per position. IC ranges 0.02-1.35 bits, within
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0-2 bits for DNA.
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: 'Linear flow: imports, data, IC calculation, style, chart config,
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save. No functions or classes.'
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- id: CQ-02
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name: Reproducibility
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score: 2
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max: 2
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passed: true
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comment: Fully deterministic data, no random generation.
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: numpy, pygal, pygal.style.Style — all used.
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- id: CQ-04
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name: Code Elegance
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score: 2
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max: 2
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passed: true
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comment: Clean, well-organized. Lambda with default arguments for formatters
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is appropriate.
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- id: CQ-05
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name: Output & API
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score: 1
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max: 1
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passed: true
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comment: Saves as plot.png via render_to_png. Current API.
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library_mastery:
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score: 7
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max: 10
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items:
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- id: LM-01
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name: Idiomatic Usage
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score: 4
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max: 5
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passed: true
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comment: StackedBar, Style class, structured data dicts with value/label/formatter,
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idiomatic pygal patterns.
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- id: LM-02
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name: Distinctive Features
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score: 3
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max: 5
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passed: true
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comment: print_values with custom formatters, tooltip config, rounded_bars,
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legend_at_bottom_columns, dual PNG+HTML render.
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verdict: REJECTED
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impl_tags:
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dependencies: []
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techniques:
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- html-export
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patterns:
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- data-generation
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- iteration-over-groups
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dataprep:
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- normalization
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styling:
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- alpha-blending

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