update(band-basic): bokeh — comprehensive quality review

Comprehensive quality review of bokeh band-basic implementation.

Author: MarkusNeusinger

plots/band-basic/implementations/bokeh.py

@@ -1,7 +1,7 @@
-""" pyplots.ai
+"""pyplots.ai
 band-basic: Basic Band Plot
-Library: bokeh 3.8.1 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: bokeh 3.8.2 | Python 3.14
+Quality: /100 | Updated: 2026-02-23
 """
 
 import numpy as np
@@ -18,49 +18,68 @@
 y_upper = y_center + 1.96 * uncertainty  # 95% CI upper bound
 y_lower = y_center - 1.96 * uncertainty  # 95% CI lower bound
 
-# Create ColumnDataSource for band (patch requires closed polygon)
-x_band = np.concatenate([x, x[::-1]])
-y_band = np.concatenate([y_upper, y_lower[::-1]])
-band_source = ColumnDataSource(data={"x": x_band, "y": y_band})
+# Create ColumnDataSource
+source = ColumnDataSource(data={"x": x, "y_center": y_center, "y_upper": y_upper, "y_lower": y_lower})
 
-# Create ColumnDataSource for center line
-line_source = ColumnDataSource(data={"x": x, "y": y_center})
-
-# Create figure (4800 × 2700 px)
-p = figure(width=4800, height=2700, title="band-basic · bokeh · pyplots.ai", x_axis_label="Time", y_axis_label="Value")
+# Create figure (4800 x 2700 px)
+p = figure(
+    width=4800,
+    height=2700,
+    title="band-basic \u00b7 bokeh \u00b7 pyplots.ai",
+    x_axis_label="Time (s)",
+    y_axis_label="Value",
+    toolbar_location=None,
+)
 
-# Plot band (semi-transparent fill)
-p.patch(
+# Plot band using varea (idiomatic Bokeh band glyph)
+p.varea(
     x="x",
-    y="y",
-    source=band_source,
+    y1="y_lower",
+    y2="y_upper",
+    source=source,
     fill_color="#306998",
     fill_alpha=0.3,
-    line_color="#306998",
-    line_alpha=0.5,
-    line_width=2,
     legend_label="95% Confidence Interval",
 )
 
 # Plot center line
-p.line(x="x", y="y", source=line_source, line_color="#FFD43B", line_width=4, legend_label="Mean Trend")
+p.line(x="x", y="y_center", source=source, line_color="#FFD43B", line_width=6, legend_label="Mean Trend")
+
+# Styling for 4800x2700 px — Bokeh pt renders at CSS scale, need large values
+p.title.text_font_size = "96pt"
+p.title.text_font_style = "normal"
+p.xaxis.axis_label_text_font_size = "72pt"
+p.yaxis.axis_label_text_font_size = "72pt"
+p.xaxis.major_label_text_font_size = "56pt"
+p.yaxis.major_label_text_font_size = "56pt"
+
+# Remove top and right spines
+p.outline_line_color = None
+p.xaxis.axis_line_color = "#333333"
+p.yaxis.axis_line_color = "#333333"
 
-# Styling for 4800×2700 px
-p.title.text_font_size = "28pt"
-p.xaxis.axis_label_text_font_size = "22pt"
-p.yaxis.axis_label_text_font_size = "22pt"
-p.xaxis.major_label_text_font_size = "18pt"
-p.yaxis.major_label_text_font_size = "18pt"
+# Grid styling - subtle solid lines
+p.xgrid.grid_line_alpha = 0.15
+p.ygrid.grid_line_alpha = 0.15
+p.xgrid.grid_line_dash = "solid"
+p.ygrid.grid_line_dash = "solid"
 
-# Grid styling
-p.grid.grid_line_alpha = 0.3
-p.grid.grid_line_dash = [6, 4]
+# Remove tick marks, keep labels
+p.xaxis.major_tick_line_color = None
+p.yaxis.major_tick_line_color = None
+p.xaxis.minor_tick_line_color = None
+p.yaxis.minor_tick_line_color = None
 
 # Legend styling
-p.legend.label_text_font_size = "18pt"
+p.legend.label_text_font_size = "56pt"
 p.legend.location = "top_left"
 p.legend.background_fill_alpha = 0.7
+p.legend.border_line_color = None
+p.legend.glyph_width = 60
+p.legend.glyph_height = 40
+p.legend.padding = 20
+p.legend.spacing = 12
 
 # Save as PNG and HTML
 export_png(p, filename="plot.png")
-save(p, filename="plot.html", title="band-basic · bokeh · pyplots.ai")
+save(p, filename="plot.html", title="band-basic \u00b7 bokeh \u00b7 pyplots.ai")

plots/band-basic/metadata/bokeh.yaml

@@ -1,16 +1,16 @@
 library: bokeh
 specification_id: band-basic
 created: '2025-12-23T09:09:02Z'
-updated: '2025-12-23T09:11:03Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-23T13:43:00Z'
+generated_by: claude-opus-4-6
 workflow_run: 20456384474
 issue: 0
-python_version: 3.13.11
-library_version: 3.8.1
+python_version: '3.14'
+library_version: 3.8.2
 preview_url: https://storage.googleapis.com/pyplots-images/plots/band-basic/bokeh/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/band-basic/bokeh/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/band-basic/bokeh/plot.html
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies: []
   techniques:

plots/band-basic/specification.md

@@ -16,7 +16,7 @@ A band plot displays a filled region between two boundary lines, commonly used t
 - `x` (numeric) - Independent variable, often representing time or sequence
 - `y_lower` (numeric) - Lower boundary values defining the bottom of the band
 - `y_upper` (numeric) - Upper boundary values defining the top of the band
-- `y_center` (numeric, optional) - Central trend line values (mean/median)
+- `y_center` (numeric) - Central trend line values (mean/median), shown as a contrasting line
 - Size: 20-200 data points
 - Example: Time series with 95% confidence interval bounds
 

plots/band-basic/specification.yaml

@@ -6,7 +6,7 @@ title: Basic Band Plot
 
 # Specification tracking
 created: 2025-12-15T20:42:54Z
-updated: 2025-12-15T20:42:54Z
+updated: 2026-02-23T12:00:00Z
 issue: 979
 suggested: MarkusNeusinger
 
@@ -18,10 +18,14 @@ tags:
   data_type:
     - numeric
     - continuous
+    - timeseries
   domain:
     - statistics
     - science
+    - general
+    - engineering
   features:
     - basic
     - confidence-interval
     - uncertainty
+    - 2d