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

Comprehensive quality review improving rendering, band styling, and library features.

Author: MarkusNeusinger

plots/bullet-basic/implementations/bokeh.py

@@ -1,51 +1,51 @@
-""" pyplots.ai
+"""pyplots.ai
 bullet-basic: Basic Bullet Chart
-Library: bokeh 3.8.1 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: bokeh 3.8.2 | Python 3.14.3
+Quality: /100 | Updated: 2026-02-22
 """
 
 from bokeh.io import export_png, output_file, save
-from bokeh.models import Label
+from bokeh.models import Label, Range1d
 from bokeh.plotting import figure
 
 
 # Data - Sales performance metrics with targets
 metrics = [
-    {"label": "Revenue", "actual": 275, "target": 250, "ranges": [150, 225, 300]},
-    {"label": "Profit", "actual": 85, "target": 100, "ranges": [50, 75, 100]},
-    {"label": "Orders", "actual": 320, "target": 350, "ranges": [200, 300, 400]},
-    {"label": "Customers", "actual": 1450, "target": 1200, "ranges": [800, 1100, 1500]},
-    {"label": "Satisfaction", "actual": 4.2, "target": 4.5, "ranges": [3.0, 4.0, 5.0]},
+    {"label": "Revenue", "unit": "$K", "actual": 275, "target": 250, "ranges": [150, 225, 300]},
+    {"label": "Profit", "unit": "$K", "actual": 85, "target": 100, "ranges": [50, 75, 100]},
+    {"label": "Orders", "unit": "", "actual": 320, "target": 350, "ranges": [200, 300, 400]},
+    {"label": "Customers", "unit": "", "actual": 1450, "target": 1200, "ranges": [800, 1100, 1500]},
+    {"label": "Satisfaction", "unit": "/5", "actual": 4.2, "target": 4.5, "ranges": [3.0, 4.0, 5.0]},
 ]
 
 # Configuration
 num_metrics = len(metrics)
-bar_spacing = 1.5  # Space between each bullet row
-bar_height = 0.8  # Maximum height of range bars
+bar_spacing = 1.5
+bar_height = 0.8
 
-# Qualitative range colors (grayscale: poor, satisfactory, good - light to dark)
-range_colors = ["#dddddd", "#aaaaaa", "#777777"]
+# Qualitative range colors: lightest (widest, good) to darkest (narrowest, poor)
+range_colors = ["#d4d4d4", "#a8a8a8", "#737373"]
 
 # Create figure
 p = figure(
     width=4800,
     height=2700,
-    x_range=(0, 110),
-    y_range=(-0.5, num_metrics * bar_spacing),
+    x_range=Range1d(-38, 118),
+    y_range=Range1d(-0.8, num_metrics * bar_spacing + 0.2),
     title="bullet-basic · bokeh · pyplots.ai",
-    x_axis_label="% of Target Range",
+    x_axis_label="% of Maximum Range",
     toolbar_location=None,
 )
 
 # Remove y-axis ticks and gridlines
 p.yaxis.visible = False
 p.ygrid.grid_line_color = None
-p.xgrid.grid_line_alpha = 0.3
-p.xgrid.grid_line_dash = "dashed"
+p.xgrid.grid_line_alpha = 0.15
+p.xgrid.grid_line_dash = [6, 4]
 
 # Draw bullets for each metric
 for i, metric in enumerate(metrics):
-    y_pos = (num_metrics - 1 - i) * bar_spacing  # Reverse so first is at top
+    y_pos = (num_metrics - 1 - i) * bar_spacing
     actual = metric["actual"]
     target = metric["target"]
     ranges = metric["ranges"]
@@ -56,26 +56,27 @@
     norm_target = (target / max_range) * 100
     norm_ranges = [(r / max_range) * 100 for r in ranges]
 
-    # Draw qualitative ranges (background bands) - from outer to inner
+    # Draw qualitative ranges (background bands) - widest first (lightest = good)
     for j in range(len(norm_ranges) - 1, -1, -1):
         range_width = norm_ranges[j]
-        height_factor = 1 - j * 0.25  # Decrease height for inner ranges
+        height_factor = 1 - j * 0.2
         h = bar_height * height_factor
         p.rect(x=range_width / 2, y=y_pos, width=range_width, height=h, color=range_colors[j], line_color=None)
 
-    # Draw actual value bar (primary measure)
-    actual_bar_height = bar_height * 0.35
+    # Draw actual value bar
+    actual_bar_height = bar_height * 0.3
     p.rect(x=norm_actual / 2, y=y_pos, width=norm_actual, height=actual_bar_height, color="#306998", line_color=None)
 
-    # Draw target marker (thin black vertical line)
-    target_marker_height = bar_height * 0.6
-    p.rect(x=norm_target, y=y_pos, width=0.8, height=target_marker_height, color="#1a1a1a", line_color=None)
+    # Draw target marker (thin vertical line)
+    target_marker_height = bar_height * 0.55
+    p.rect(x=norm_target, y=y_pos, width=0.7, height=target_marker_height, color="#1a1a1a", line_color=None)
 
-    # Add metric label on the left
+    # Add metric label with unit
+    unit_text = f" ({metric['unit']})" if metric["unit"] else ""
     label = Label(
         x=-2,
         y=y_pos,
-        text=metric["label"],
+        text=f"{metric['label']}{unit_text}",
         text_font_size="28pt",
         text_color="#333333",
         text_align="right",
@@ -84,40 +85,71 @@
     )
     p.add_layout(label)
 
-    # Add actual value text label on the right
+    # Add actual value as text
+    value_text = str(int(actual)) if actual == int(actual) else str(actual)
     value_label = Label(
-        x=norm_actual + 3,
+        x=norm_actual + 2,
         y=y_pos,
-        text=str(metric["actual"]),
-        text_font_size="24pt",
+        text=value_text,
+        text_font_size="22pt",
         text_color="#306998",
         text_align="left",
         text_baseline="middle",
         text_font_style="bold",
     )
     p.add_layout(value_label)
 
-# Extend x_range to accommodate labels (but clip axis display)
-p.x_range.start = -35
-p.x_range.end = 115
+# Legend - positioned below the chart
+legend_y = -0.5
+legend_start_x = 10
+legend_spacing = 22
+range_labels = ["Poor", "Satisfactory", "Good"]
+box_w = 4
+box_h = 0.2
+
+for k, (color, lbl) in enumerate(zip(range_colors[::-1], range_labels, strict=True)):
+    lx = legend_start_x + k * legend_spacing
+    p.rect(x=lx, y=legend_y, width=box_w, height=box_h, color=color, line_color="#999999", line_width=1)
+    p.add_layout(
+        Label(
+            x=lx + box_w / 2 + 1,
+            y=legend_y,
+            text=lbl,
+            text_font_size="20pt",
+            text_color="#555555",
+            text_align="left",
+            text_baseline="middle",
+        )
+    )
+
+# Target marker legend entry
+target_lx = legend_start_x + len(range_labels) * legend_spacing
+p.rect(x=target_lx, y=legend_y, width=1.0, height=box_h, color="#1a1a1a", line_color=None)
+p.add_layout(
+    Label(
+        x=target_lx + box_w / 2 + 1,
+        y=legend_y,
+        text="Target",
+        text_font_size="20pt",
+        text_color="#555555",
+        text_align="left",
+        text_baseline="middle",
+    )
+)
 
-# Styling - scaled for 4800x2700 canvas
-p.title.text_font_size = "42pt"
+# Style - scaled for 4800x2700 canvas
+p.title.text_font_size = "36pt"
 p.title.text_color = "#333333"
 p.title.align = "center"
-p.xaxis.axis_label_text_font_size = "28pt"
-p.xaxis.major_label_text_font_size = "22pt"
-
-# Only show positive tick marks on x-axis
+p.xaxis.axis_label_text_font_size = "24pt"
+p.xaxis.major_label_text_font_size = "20pt"
 p.xaxis.ticker = [0, 20, 40, 60, 80, 100]
-
-# Axis styling
 p.xaxis.axis_line_color = "#666666"
 p.outline_line_color = None
 
 # Save as PNG
 export_png(p, filename="plot.png")
 
-# Save as HTML for interactivity
+# Save as HTML
 output_file("plot.html")
 save(p)

plots/bullet-basic/metadata/bokeh.yaml

@@ -1,16 +1,16 @@
 library: bokeh
 specification_id: bullet-basic
 created: '2025-12-23T09:18:59Z'
-updated: '2025-12-23T09:23:32Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-22T12:00:00+00:00'
+generated_by: claude-opus-4-6
 workflow_run: 20456605377
 issue: 0
-python_version: 3.13.11
-library_version: 3.8.1
+python_version: 3.14.3
+library_version: 3.8.2
 preview_url: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/bokeh/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/bokeh/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/bokeh/plot.html
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies: []
   techniques: