feat(bokeh): implement violin-swarm (#3546)

## Implementation: `violin-swarm` - bokeh

Implements the **bokeh** version of `violin-swarm`.

**File:** `plots/violin-swarm/implementations/bokeh.py`

**Parent Issue:** #3526

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20858842134)*

---------

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/violin-swarm/implementations/bokeh.py

@@ -0,0 +1,97 @@
+""" pyplots.ai
+violin-swarm: Violin Plot with Overlaid Swarm Points
+Library: bokeh 3.8.2 | Python 3.13.11
+Quality: 91/100 | Created: 2026-01-09
+"""
+
+import numpy as np
+from bokeh.io import export_png, save
+from bokeh.models import ColumnDataSource, FactorRange
+from bokeh.plotting import figure
+from bokeh.resources import CDN
+from scipy import stats
+
+
+# Data - Reaction times (ms) across 4 experimental conditions
+np.random.seed(42)
+
+categories = ["Control", "Low Dose", "Medium Dose", "High Dose"]
+n_per_group = 50
+
+# Generate different distributions for each condition
+data = {
+    "Control": np.random.normal(350, 50, n_per_group),
+    "Low Dose": np.random.normal(320, 45, n_per_group),
+    "Medium Dose": np.random.normal(280, 60, n_per_group),
+    "High Dose": np.random.normal(250, 40, n_per_group),
+}
+
+# Colors: Python Blue for violin, Python Yellow for points
+violin_color = "#306998"
+point_color = "#FFD43B"
+
+# Create figure with padding for violins
+p = figure(
+    width=4800,
+    height=2700,
+    title="violin-swarm · bokeh · pyplots.ai",
+    x_range=FactorRange(*categories, range_padding=0.15),
+    y_axis_label="Reaction Time (ms)",
+    x_axis_label="Experimental Condition",
+)
+
+# Styling - larger text for 4800x2700 canvas
+p.title.text_font_size = "36pt"
+p.xaxis.axis_label_text_font_size = "28pt"
+p.yaxis.axis_label_text_font_size = "28pt"
+p.xaxis.major_label_text_font_size = "24pt"
+p.yaxis.major_label_text_font_size = "22pt"
+p.grid.grid_line_alpha = 0.3
+p.grid.grid_line_dash = [6, 4]
+p.outline_line_color = None
+
+# Build violin shapes and swarm points
+violin_patches_x = []
+violin_patches_y = []
+swarm_x = []
+swarm_y = []
+
+for i, cat in enumerate(categories):
+    values = data[cat]
+
+    # Kernel density estimation for violin
+    kde = stats.gaussian_kde(values)
+    y_range = np.linspace(values.min() - 20, values.max() + 20, 200)
+    density = kde(y_range)
+
+    # Normalize density to max width of 0.4 (so violin fits within category space)
+    max_width = 0.35
+    density_normalized = density / density.max() * max_width
+
+    # Create violin shape (mirrored density)
+    x_violin = np.concatenate([i - density_normalized, (i + density_normalized)[::-1]])
+    y_violin = np.concatenate([y_range, y_range[::-1]])
+
+    violin_patches_x.append(x_violin.tolist())
+    violin_patches_y.append(y_violin.tolist())
+
+    # Create swarm points (jitter within violin boundary)
+    for val in values:
+        # Get the density at this y value to determine jitter range
+        val_density = kde(val)[0]
+        jitter_range = (val_density / density.max()) * max_width * 0.8
+        jitter = np.random.uniform(-jitter_range, jitter_range)
+        swarm_x.append(i + jitter)
+        swarm_y.append(val)
+
+# Draw violins as patches (semi-transparent)
+for vx, vy in zip(violin_patches_x, violin_patches_y, strict=True):
+    p.patch(vx, vy, fill_color=violin_color, fill_alpha=0.4, line_color=violin_color, line_width=2)
+
+# Draw swarm points - larger size for visibility
+swarm_source = ColumnDataSource(data={"x": swarm_x, "y": swarm_y})
+p.scatter("x", "y", source=swarm_source, size=18, color=point_color, alpha=0.9, line_color="#333333", line_width=1.5)
+
+# Save PNG and HTML
+export_png(p, filename="plot.png")
+save(p, filename="plot.html", resources=CDN, title="violin-swarm · bokeh · pyplots.ai")

plots/violin-swarm/metadata/bokeh.yaml

@@ -0,0 +1,220 @@
+library: bokeh
+specification_id: violin-swarm
+created: '2026-01-09T16:49:31Z'
+updated: '2026-01-09T16:52:47Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20858842134
+issue: 3526
+python_version: 3.13.11
+library_version: 3.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-swarm/bokeh/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-swarm/bokeh/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-swarm/bokeh/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent implementation of KDE-based violin shapes using scipy.stats.gaussian_kde
+    with proper normalization
+  - Smart swarm point jittering algorithm that respects violin boundaries by scaling
+    jitter to local density
+  - Good color contrast between semi-transparent blue violins and opaque yellow points
+  - Proper text sizing for 4800x2700 canvas with all elements clearly readable
+  - Clean, KISS code structure with good reproducibility (seed=42)
+  - Both PNG and HTML outputs provided
+  weaknesses:
+  - Missing HoverTool for interactive tooltips on swarm points (would showcase Bokeh
+    interactivity strength)
+  - Small Bokeh toolbar visible in corner is not very useful for PNG output
+  - Could benefit from slight median/quartile indicators within the violins
+  image_description: 'The plot displays four violin shapes arranged horizontally representing
+    different experimental conditions (Control, Low Dose, Medium Dose, High Dose)
+    for reaction time data. Each violin is rendered in Python Blue (#306998) with
+    approximately 40% transparency (semi-transparent light blue appearance). Yellow/gold
+    circular markers (Python Yellow #FFD43B) with dark gray outlines are overlaid
+    as swarm points within each violin, showing individual data observations. The
+    title "violin-swarm · bokeh · pyplots.ai" appears at the top-left. The Y-axis
+    shows "Reaction Time (ms)" ranging from approximately 150-450ms, and the X-axis
+    shows "Experimental Condition" with the four category labels. The violins display
+    different distribution shapes - Control and Low Dose are more symmetric, Medium
+    Dose has a wider spread, and High Dose is more compact and lower on the scale.
+    Grid lines are subtle with dashed styling. There is a small Bokeh toolbar visible
+    in the top-right corner.'
+  criteria_checklist:
+    visual_quality:
+      score: 36
+      max: 40
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 10
+        max: 10
+        passed: true
+        comment: Title at 36pt, axis labels at 28pt/22pt, tick labels at 24pt/22pt
+          - all perfectly readable at 4800x2700
+      - id: VQ-02
+        name: No Overlap
+        score: 8
+        max: 8
+        passed: true
+        comment: No overlapping text or elements, category labels well-spaced
+      - id: VQ-03
+        name: Element Visibility
+        score: 7
+        max: 8
+        passed: true
+        comment: Markers size=18 with alpha=0.9 are clearly visible, violin alpha=0.4
+          provides good contrast; slightly dense in some areas
+      - id: VQ-04
+        name: Color Accessibility
+        score: 5
+        max: 5
+        passed: true
+        comment: Blue/yellow contrast is excellent and colorblind-safe
+      - id: VQ-05
+        name: Layout Balance
+        score: 4
+        max: 5
+        passed: true
+        comment: Good canvas utilization, violins well-distributed, slight extra whitespace
+          on right side
+      - id: VQ-06
+        name: Axis Labels
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Descriptive with units: Reaction Time (ms), Experimental Condition'
+      - id: VQ-07
+        name: Grid & Legend
+        score: 0
+        max: 2
+        passed: false
+        comment: Grid is subtle but no legend present; not strictly needed for this
+          plot type but could help identify violin vs swarm
+    spec_compliance:
+      score: 25
+      max: 25
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 8
+        max: 8
+        passed: true
+        comment: Correct violin plot with overlaid swarm points
+      - id: SC-02
+        name: Data Mapping
+        score: 5
+        max: 5
+        passed: true
+        comment: Categories on X-axis, continuous values on Y-axis
+      - id: SC-03
+        name: Required Features
+        score: 5
+        max: 5
+        passed: true
+        comment: Violin shows KDE distribution, swarm points overlaid and centered
+          within violin shape, transparency applied, contrasting colors used
+      - id: SC-04
+        name: Data Range
+        score: 3
+        max: 3
+        passed: true
+        comment: All data visible within axis range
+      - id: SC-05
+        name: Legend Accuracy
+        score: 2
+        max: 2
+        passed: true
+        comment: No legend needed for this single-series plot
+      - id: SC-06
+        name: Title Format
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Uses correct format: violin-swarm · bokeh · pyplots.ai'
+    data_quality:
+      score: 18
+      max: 20
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 7
+        max: 8
+        passed: true
+        comment: Shows 4 different distributions with varying means, spreads, and
+          shapes; could show more extreme outliers
+      - id: DQ-02
+        name: Realistic Context
+        score: 7
+        max: 7
+        passed: true
+        comment: Reaction time drug dose study is a realistic scientific scenario
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 5
+        passed: true
+        comment: Reaction times 150-450ms are plausible; decreasing reaction time
+          with increasing dose makes scientific sense
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Linear flow: imports, data, plot, save - no functions/classes'
+      - id: CQ-02
+        name: Reproducibility
+        score: 3
+        max: 3
+        passed: true
+        comment: Uses np.random.seed(42)
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: All imports used (numpy, bokeh modules, scipy.stats)
+      - id: CQ-04
+        name: No Deprecated API
+        score: 1
+        max: 1
+        passed: true
+        comment: Using current Bokeh API
+      - id: CQ-05
+        name: Output Correct
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves both plot.png and plot.html
+    library_features:
+      score: 2
+      max: 5
+      items:
+      - id: LF-01
+        name: Distinctive Features
+        score: 2
+        max: 5
+        passed: false
+        comment: Uses ColumnDataSource and patch() for violins, but does not leverage
+          Bokeh's distinctive interactivity (HoverTool could show point values on
+          hover)
+  verdict: APPROVED
+impl_tags:
+  dependencies:
+  - scipy
+  techniques:
+  - patches
+  - html-export
+  patterns:
+  - data-generation
+  - columndatasource
+  - iteration-over-groups
+  dataprep:
+  - kde
+  styling:
+  - alpha-blending
+  - grid-styling
+  - edge-highlighting