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

Comprehensive quality review of plotnine band-basic implementation.

Author: MarkusNeusinger

plots/band-basic/implementations/plotnine.py

@@ -1,7 +1,7 @@
-""" pyplots.ai
+"""pyplots.ai
 band-basic: Basic Band Plot
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: plotnine 0.15.3 | Python 3.14
+Quality: /100 | Updated: 2026-02-23
 """
 
 import numpy as np
@@ -10,6 +10,7 @@
     aes,
     element_blank,
     element_line,
+    element_rect,
     element_text,
     geom_line,
     geom_ribbon,
@@ -20,34 +21,34 @@
 )
 
 
-# Data - time series with 95% confidence interval (model predictions)
+# Data - sensor readings with 95% confidence interval
 np.random.seed(42)
-n_points = 50
-x = np.linspace(0, 10, n_points)
+n_points = 60
+days = np.linspace(0, 30, n_points)
 
-# Generate central trend with curvature
-y_center = 3 * np.sin(0.5 * x) + 0.3 * x + 5
-
-# Uncertainty grows with x (heteroscedastic - realistic for forecasts)
-uncertainty = 0.5 + 0.15 * x
+# Central trend: temperature rising then stabilizing (realistic sensor pattern)
+temperature = 18 + 4 * (1 - np.exp(-0.15 * days)) + 1.5 * np.sin(0.4 * days)
 noise = np.random.normal(0, 0.3, n_points)
-y_center = y_center + noise
+temperature = temperature + noise
+
+# Uncertainty narrows as model calibrates, then widens for extrapolation
+uncertainty = 1.8 * np.exp(-0.08 * days) + 0.3 + 0.04 * np.maximum(days - 20, 0)
 
-# Confidence band boundaries (95% CI uses 1.96 standard errors)
-y_lower = y_center - 1.96 * uncertainty
-y_upper = y_center + 1.96 * uncertainty
+# Confidence band boundaries (95% CI)
+temp_lower = temperature - 1.96 * uncertainty
+temp_upper = temperature + 1.96 * uncertainty
 
-df = pd.DataFrame({"x": x, "y_center": y_center, "y_lower": y_lower, "y_upper": y_upper})
+df = pd.DataFrame({"days": days, "temperature": temperature, "temp_lower": temp_lower, "temp_upper": temp_upper})
 
 # Plot
 plot = (
-    ggplot(df, aes(x="x"))
-    + geom_ribbon(aes(ymin="y_lower", ymax="y_upper"), fill="#306998", alpha=0.3)
-    + geom_line(aes(y="y_center"), color="#306998", size=2)
+    ggplot(df, aes(x="days"))
+    + geom_ribbon(aes(ymin="temp_lower", ymax="temp_upper"), fill="#306998", alpha=0.25)
+    + geom_line(aes(y="temperature"), color="#306998", size=2.5)
     + labs(
-        x="Time",
-        y="Predicted Value",
-        title="Model Forecast with 95% Confidence Interval · band-basic · plotnine · pyplots.ai",
+        x="Time (days)",
+        y="Temperature (\u00b0C)",
+        title="Sensor Calibration Forecast \u00b7 band-basic \u00b7 plotnine \u00b7 pyplots.ai",
     )
     + theme_minimal()
     + theme(
@@ -56,8 +57,13 @@
         axis_title=element_text(size=20),
         axis_text=element_text(size=16),
         plot_title=element_text(size=24),
-        panel_grid_major=element_line(color="#cccccc", size=0.5, alpha=0.3),
+        panel_grid_major_y=element_line(color="#cccccc", size=0.5, alpha=0.2),
+        panel_grid_major_x=element_blank(),
         panel_grid_minor=element_blank(),
+        panel_border=element_blank(),
+        axis_line_x=element_line(color="#333333", size=0.5),
+        axis_line_y=element_line(color="#333333", size=0.5),
+        plot_background=element_rect(fill="white", color="none"),
     )
 )
 

plots/band-basic/metadata/plotnine.yaml

@@ -1,16 +1,16 @@
 library: plotnine
 specification_id: band-basic
 created: '2025-12-23T09:08:40Z'
-updated: '2025-12-23T09:10:54Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-23T13:41:00Z'
+generated_by: claude-opus-4-6
 workflow_run: 20456385974
 issue: 0
-python_version: 3.13.11
-library_version: 0.15.2
+python_version: '3.14'
+library_version: 0.15.3
 preview_url: https://storage.googleapis.com/pyplots-images/plots/band-basic/plotnine/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/band-basic/plotnine/plot_thumb.png
 preview_html: null
-quality_score: 92
+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