feat(letsplot): implement sequence-logo-basic

plots/sequence-logo-basic/implementations/letsplot.py

@@ -0,0 +1,137 @@
+""" pyplots.ai
+sequence-logo-basic: Sequence Logo for Motif Visualization
+Library: letsplot 4.8.2 | Python 3.14.3
+Quality: 79/100 | Created: 2026-03-06
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import *
+
+
+LetsPlot.setup_html()
+
+# Data — 10-position DNA transcription factor binding site motif
+positions = list(range(1, 11))
+
+# Realistic motif frequencies (resembling a TATA-box-like binding site)
+frequencies = {
+    1: {"A": 0.25, "C": 0.25, "G": 0.25, "T": 0.25},
+    2: {"A": 0.10, "C": 0.05, "G": 0.05, "T": 0.80},
+    3: {"A": 0.85, "C": 0.05, "G": 0.05, "T": 0.05},
+    4: {"A": 0.05, "C": 0.05, "G": 0.05, "T": 0.85},
+    5: {"A": 0.90, "C": 0.02, "G": 0.02, "T": 0.06},
+    6: {"A": 0.60, "C": 0.05, "G": 0.05, "T": 0.30},
+    7: {"A": 0.15, "C": 0.05, "G": 0.70, "T": 0.10},
+    8: {"A": 0.05, "C": 0.80, "G": 0.10, "T": 0.05},
+    9: {"A": 0.30, "C": 0.30, "G": 0.20, "T": 0.20},
+    10: {"A": 0.25, "C": 0.25, "G": 0.25, "T": 0.25},
+}
+
+# Color scheme: A=green, C=blue, G=orange, T=red
+color_map = {"A": "#2CA02C", "C": "#1F77B4", "G": "#FF7F0E", "T": "#D62728"}
+
+# Calculate information content and build letter data
+rows = []
+max_info = 0.0
+for pos in positions:
+    freqs = frequencies[pos]
+    entropy = -sum(f * np.log2(f) for f in freqs.values() if f > 0)
+    info_content = 2.0 - entropy
+
+    # Sort by frequency (least frequent at bottom, most frequent on top)
+    sorted_letters = sorted(freqs.items(), key=lambda x: x[1])
+
+    y_bottom = 0.0
+    for letter, freq in sorted_letters:
+        height = freq * info_content
+        if height < 0.04:
+            y_bottom += height
+            continue
+        rows.append(
+            {
+                "position": pos,
+                "xmin": pos - 0.45,
+                "xmax": pos + 0.45,
+                "ymin": y_bottom,
+                "ymax": y_bottom + height,
+                "ymid": y_bottom + height / 2,
+                "height": height,
+                "letter": letter,
+                "frequency": freq,
+                "info_bits": round(info_content, 3),
+            }
+        )
+        y_bottom += height
+    if info_content > max_info:
+        max_info = info_content
+
+df = pd.DataFrame(rows)
+
+# Legend data — invisible points to create a proper legend with square symbols
+legend_df = pd.DataFrame({"x": [0] * 4, "y": [0] * 4, "letter": ["A", "C", "G", "T"]})
+
+# Y-axis upper limit: round up to nearest 0.2 with small padding
+y_max = np.ceil(max_info * 5) / 5 + 0.05
+
+# Build plot with colored letters as the primary visual element
+plot = (
+    ggplot()
+    # Subtle background rectangles for structure
+    + geom_rect(
+        aes(xmin="xmin", xmax="xmax", ymin="ymin", ymax="ymax", fill="letter"),
+        data=df,
+        alpha=0.15,
+        color="rgba(0,0,0,0)",
+        size=0,
+        show_legend=False,
+    )
+    # Colored letter glyphs — the primary visual element
+    + geom_text(
+        aes(x="position", y="ymid", label="letter", color="letter", size="height"),
+        data=df,
+        fontface="bold",
+        show_legend=False,
+        tooltips=layer_tooltips()
+        .format("@frequency", ".0%")
+        .format("@info_bits", ".3f")
+        .line("@letter")
+        .line("Frequency: @frequency")
+        .line("Info content: @info_bits bits"),
+    )
+    # Invisible points for proper legend (square shape shows color blocks)
+    + geom_point(
+        aes(x="x", y="y", fill="letter"),
+        data=legend_df,
+        size=6,
+        shape=22,
+        color="rgba(0,0,0,0)",
+        alpha=0,
+        tooltips="none",
+    )
+    # Manual color scales
+    + scale_fill_manual(values=color_map, name="Nucleotide", breaks=["A", "C", "G", "T"])
+    + scale_color_manual(values=color_map)
+    + scale_size(range=[6, 36], guide="none")
+    + scale_x_continuous(breaks=positions, limits=[0.3, 10.7])
+    + scale_y_continuous(limits=[0, y_max], breaks=[0.0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4])
+    + guides(fill=guide_legend(override_aes={"size": 12, "alpha": 1.0}))
+    + labs(x="Position", y="Information content (bits)", title="sequence-logo-basic \u00b7 letsplot \u00b7 pyplots.ai")
+    + theme_minimal()
+    + theme(
+        plot_title=element_text(size=28, face="bold"),
+        axis_title=element_text(size=22),
+        axis_text=element_text(size=18),
+        legend_title=element_text(size=20, face="bold"),
+        legend_text=element_text(size=18),
+        panel_grid_major_x=element_blank(),
+        panel_grid_minor=element_blank(),
+        panel_grid_major_y=element_line(color="#E0E0E0", size=0.5),
+        plot_background=element_rect(color="white", fill="white"),
+    )
+    + ggsize(1600, 900)
+)
+
+# Save
+ggsave(plot, "plot.png", scale=3, path=".")
+ggsave(plot, "plot.html", path=".")

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

@@ -0,0 +1,237 @@
+library: letsplot
+specification_id: sequence-logo-basic
+created: '2026-03-06T20:26:04Z'
+updated: '2026-03-06T20:56:37Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 22780525013
+issue: 4421
+python_version: 3.14.3
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/sequence-logo-basic/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/sequence-logo-basic/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/sequence-logo-basic/letsplot/plot.html
+quality_score: 79
+review:
+  strengths:
+  - Excellent realistic data choice (TATA-box motif) that immediately communicates
+    biological meaning
+  - Semi-transparent background rectangles are a creative solution that adds structure
+    and helps visualize letter boundaries
+  - Clean well-organized code with proper information content calculation
+  - Good use of lets-plot-specific features (layer_tooltips with formatted biological
+    data, HTML export)
+  - 'Strong visual refinement: subtle grid, removed x-grid lines, explicit font sizing'
+  weaknesses:
+  - Letters are not stretched to fill their allocated height as true sequence logos
+    require — fundamental lets-plot limitation with text rendering
+  - Small-frequency letters at the base of stacks are very small and hard to read
+  - Color scheme uses green+red which is challenging for colorblind users (though
+    spec-mandated for DNA)
+  image_description: 'The plot displays a sequence logo for a 10-position DNA transcription
+    factor binding site (TATA-box-like motif). At each position, nucleotide letters
+    (A, C, G, T) are stacked vertically with heights proportional to information content
+    in bits. Standard DNA colors are used: A=green, C=blue, G=orange, T=red. Semi-transparent
+    background rectangles behind each letter stack add visual depth. Positions 2-5
+    show the conserved TATA core with large dominant letters (T, A, T, A). Positions
+    1, 9, and 10 have no visible letters (uniform distribution = 0 bits). Positions
+    7 (G) and 8 (C) show moderate conservation. The y-axis ranges from 0 to 1.4 bits
+    with subtle horizontal gridlines. A "Nucleotide" legend with colored squares appears
+    on the right. The title reads "sequence-logo-basic · letsplot · pyplots.ai". Overall
+    layout is clean with good canvas utilization.'
+  criteria_checklist:
+    visual_quality:
+      score: 23
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 6
+        max: 8
+        passed: true
+        comment: Font sizes explicitly set. Main letters readable; small-frequency
+          letters at stack bases are very small due to size scaling.
+      - id: VQ-02
+        name: No Overlap
+        score: 5
+        max: 6
+        passed: true
+        comment: Small letters at bottom of stacks slightly crowded at positions 2-4,
+          but no significant overlap.
+      - id: VQ-03
+        name: Element Visibility
+        score: 4
+        max: 6
+        passed: true
+        comment: Dominant letters clearly visible. Background rectangles aid visibility.
+          Small-frequency letters at base are quite tiny.
+      - id: VQ-04
+        name: Color Accessibility
+        score: 3
+        max: 4
+        passed: true
+        comment: Standard DNA colors (green/blue/orange/red) as spec-mandated. Green+red
+          can challenge colorblind users.
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 3
+        max: 4
+        passed: true
+        comment: Good canvas utilization (~60%). Empty positions 1, 9, 10 create some
+          whitespace reflecting the data.
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: Position and Information content (bits) — descriptive with units.
+    design_excellence:
+      score: 13
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 5
+        max: 8
+        passed: true
+        comment: Custom DNA palette, semi-transparent background rectangles, bold
+          letters, minimal theme. Above defaults but not publication-level.
+      - id: DE-02
+        name: Visual Refinement
+        score: 4
+        max: 6
+        passed: true
+        comment: theme_minimal(), x-grid removed, subtle y-grid only, white background,
+          generous spacing.
+      - id: DE-03
+        name: Data Storytelling
+        score: 4
+        max: 6
+        passed: true
+        comment: TATA-box motif creates natural visual hierarchy. Conserved core dominates
+          visually.
+    spec_compliance:
+      score: 12
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 3
+        max: 5
+        passed: false
+        comment: Sequence logo with stacked letters scaled by info content, but letters
+          not stretched to fill rectangles as spec requires — lets-plot limitation.
+      - id: SC-02
+        name: Required Features
+        score: 3
+        max: 4
+        passed: true
+        comment: Vertical stacking, info content scaling, standard colors, frequency
+          ordering, axis labels all present. Missing stretched glyph rendering.
+      - id: SC-03
+        name: Data Mapping
+        score: 3
+        max: 3
+        passed: true
+        comment: X=position, Y=information content. Correct mapping with proper calculation.
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: Title format correct. Legend shows all four nucleotides with correct
+          color-coded squares.
+    data_quality:
+      score: 14
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 5
+        max: 6
+        passed: true
+        comment: Shows high conservation (pos 2-5, 7-8), low conservation (pos 1,
+          9-10), and mixed (pos 6).
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: TATA-box-like transcription factor binding site — a real, well-known
+          biological motif.
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: Information content 0 to ~1.4 bits, realistic for 4-letter DNA alphabet
+          (max 2 bits).
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Linear flow: imports, data, calculation, plot, save. No functions
+          or classes.'
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: Deterministic hardcoded frequency data.
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: All imports (numpy, pandas, lets_plot) are used.
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean, well-organized code. Invisible legend points technique is
+          a reasonable workaround.
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot.png with scale=3 for 4800x2700. Current API.
+    library_mastery:
+      score: 7
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 4
+        max: 5
+        passed: true
+        comment: 'Good ggplot grammar: aes(), multiple geom layers, scale_*_manual(),
+          theme customization, guides().'
+      - id: LM-02
+        name: Distinctive Features
+        score: 3
+        max: 5
+        passed: true
+        comment: Uses layer_tooltips() with custom formatting — a distinctive lets-plot
+          interactive feature. Also exports HTML.
+  verdict: REJECTED
+impl_tags:
+  dependencies: []
+  techniques:
+  - layer-composition
+  - custom-legend
+  - hover-tooltips
+  - html-export
+  patterns:
+  - data-generation
+  - iteration-over-groups
+  dataprep:
+  - normalization
+  styling:
+  - grid-styling
+  - alpha-blending