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

plots/band-basic/implementations/letsplot.py

@@ -1,57 +1,105 @@
 """ pyplots.ai
 band-basic: Basic Band Plot
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 93/100 | Created: 2025-12-23
+Library: letsplot 4.8.2 | Python 3.14
+Quality: 91/100 | Updated: 2026-02-23
 """
 
 import numpy as np
 import pandas as pd
 from lets_plot import (
     LetsPlot,
     aes,
+    arrow,
+    element_blank,
     element_line,
+    element_rect,
     element_text,
+    geom_hline,
     geom_line,
     geom_ribbon,
+    geom_segment,
+    geom_text,
     ggplot,
     ggsave,
     ggsize,
     labs,
+    layer_tooltips,
+    scale_x_continuous,
+    scale_y_continuous,
     theme,
     theme_minimal,
 )
 
 
 LetsPlot.setup_html()
 
-# Data - time series with 95% confidence interval
+# Data - sensor temperature readings with 95% confidence interval
 np.random.seed(42)
-x = np.linspace(0, 10, 100)
-y_center = 2 * np.sin(x) + 0.5 * x  # Central trend (sinusoidal + linear growth)
-noise_scale = 0.3 + 0.15 * x  # Increasing uncertainty over time
-y_lower = y_center - 1.96 * noise_scale  # 95% CI lower bound
-y_upper = y_center + 1.96 * noise_scale  # 95% CI upper bound
+time_seconds = np.linspace(0, 10, 100)
+temp_mean = 2 * np.sin(time_seconds) + 0.5 * time_seconds  # Central trend
+uncertainty = 0.3 + 0.15 * time_seconds  # Growing uncertainty over time
+temp_lower = temp_mean - 1.96 * uncertainty  # 95% CI lower bound
+temp_upper = temp_mean + 1.96 * uncertainty  # 95% CI upper bound
 
-df = pd.DataFrame({"x": x, "y_center": y_center, "y_lower": y_lower, "y_upper": y_upper})
+df = pd.DataFrame({"time": time_seconds, "mean": temp_mean, "lower": temp_lower, "upper": temp_upper})
+
+# Annotation with arrow connector pointing to the widening band region
+annot_df = pd.DataFrame({"x": [7.0], "y": [9.2], "label": ["Growing uncertainty"]})
+target_idx = np.argmin(np.abs(time_seconds - 9.5))
+arrow_df = pd.DataFrame({"x": [8.7], "y": [9.0], "xend": [9.5], "yend": [temp_upper[target_idx] + 0.15]})
 
 # 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=1.5)
-    + labs(x="Time (s)", y="Value (units)", title="band-basic · letsplot · pyplots.ai")
+    ggplot(df, aes(x="time"))
+    # Baseline reference at 0°C
+    + geom_hline(yintercept=0, color="#BBBBBB", size=0.7, linetype="dashed", tooltips="none")
+    + geom_ribbon(
+        aes(ymin="lower", ymax="upper"),
+        fill="#306998",
+        size=0,
+        alpha=0.2,
+        tooltips=layer_tooltips()
+        .format("lower", "{.2f}")
+        .format("upper", "{.2f}")
+        .line("95% CI")
+        .line("Upper|@upper")
+        .line("Lower|@lower"),
+    )
+    + geom_line(
+        aes(y="mean"),
+        color="#C75B2E",
+        size=2.0,
+        tooltips=layer_tooltips()
+        .format("mean", "{.2f}")
+        .format("time", "{.1f}")
+        .line("Time|@time s")
+        .line("Mean|@mean"),
+    )
+    # Arrow connector from annotation to widening band
+    + geom_segment(
+        aes(x="x", y="y", xend="xend", yend="yend"),
+        data=arrow_df,
+        color="#555555",
+        size=0.7,
+        arrow=arrow(length=8, type="open"),
+        tooltips="none",
+    )
+    + geom_text(aes(x="x", y="y", label="label"), data=annot_df, size=12, color="#444444")
+    + labs(x="Time (s)", y="Temperature (\u00b0C)", title="band-basic \u00b7 letsplot \u00b7 pyplots.ai")
+    + scale_x_continuous(limits=[-0.3, 10.8])
+    + scale_y_continuous(limits=[-2.2, 9.5], expand=[0, 0.02])
     + theme_minimal()
     + theme(
-        axis_title=element_text(size=20),
-        axis_text=element_text(size=16),
-        plot_title=element_text(size=24),
-        panel_grid=element_line(color="#cccccc", size=0.5),
+        axis_title=element_text(size=20, color="#333333"),
+        axis_text=element_text(size=16, color="#555555"),
+        plot_title=element_text(size=24, color="#222222"),
+        panel_grid_major=element_line(size=0.3, color="#E8E8E8"),
+        panel_grid_minor=element_blank(),
+        plot_background=element_rect(color="white", fill="white", size=0),
     )
     + ggsize(1600, 900)
 )
 
-# Save PNG (scale=3 gives 4800x2700)
+# Save
 ggsave(plot, "plot.png", path=".", scale=3)
-
-# Save HTML for interactive version
-ggsave(plot, "plot.html", path=".")
+plot.to_html("plot.html")