feat(letsplot): implement rug-basic (#5589)

## Implementation: `rug-basic` - python/letsplot

Implements the **python/letsplot** version of `rug-basic`.

**File:** `plots/rug-basic/implementations/python/letsplot.py`

**Parent Issue:** #978

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25148880653)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>

Author: github-actions[bot]

plots/rug-basic/implementations/python/letsplot.py

@@ -1,9 +1,11 @@
-""" pyplots.ai
+""" anyplot.ai
 rug-basic: Basic Rug Plot
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: letsplot 4.9.0 | Python 3.13.13
+Quality: 87/100 | Updated: 2026-04-30
 """
 
+import os
+
 import numpy as np
 import pandas as pd
 from lets_plot import *  # noqa: F403
@@ -12,6 +14,13 @@
 
 LetsPlot.setup_html()  # noqa: F405
 
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+BRAND = "#009E73"  # Okabe-Ito position 1
+
 # Data - Simulated response times with clusters and gaps (realistic scenario)
 np.random.seed(42)
 cluster1 = np.random.normal(120, 15, 45)  # Fast responses ~120ms
@@ -22,37 +31,39 @@
 
 df = pd.DataFrame({"response_time": values})
 
-# Rug data - create short segments at bottom of plot
-# Height scaled to be visible but small relative to plot (spec requirement)
-rug_y_max = 0.0004  # Small tick height, ~10% of density peak
+rug_y_max = 0.0005
 df_rug = pd.DataFrame(
     {"x": values, "xend": values, "y": np.zeros(len(values)), "yend": np.full(len(values), rug_y_max)}
 )
 
 # Plot - Density curve with rug marks along x-axis
 plot = (
     ggplot(df, aes(x="response_time"))  # noqa: F405
-    + geom_density(fill="#306998", alpha=0.3, size=1.5, color="#306998")  # noqa: F405
+    + geom_density(fill=BRAND, alpha=0.25, size=1.5, color=BRAND)  # noqa: F405
     + geom_segment(  # noqa: F405
         aes(x="x", xend="xend", y="y", yend="yend"),  # noqa: F405
         data=df_rug,
-        color="#306998",
-        alpha=0.8,
-        size=1.2,
+        color=BRAND,
+        alpha=0.7,
+        size=1.5,
+    )
+    + labs(  # noqa: F405
+        x="Response Time (ms)", y="Density", title="rug-basic · letsplot · anyplot.ai"
     )
-    + labs(x="Response Time (ms)", y="Density", title="rug-basic · letsplot · pyplots.ai")  # noqa: F405
     + theme_minimal()  # noqa: F405
     + theme(  # noqa: F405
-        axis_title=element_text(size=20),  # noqa: F405
-        axis_text=element_text(size=16),  # noqa: F405
-        plot_title=element_text(size=24),  # noqa: F405
-        panel_grid=element_line(color="#cccccc", size=0.5),  # noqa: F405
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),  # noqa: F405
+        panel_background=element_rect(fill=PAGE_BG),  # noqa: F405
+        axis_title=element_text(size=20, color=INK),  # noqa: F405
+        axis_text=element_text(size=16, color=INK_SOFT),  # noqa: F405
+        plot_title=element_text(size=24, color=INK),  # noqa: F405
+        panel_grid_major=element_line(color=INK_SOFT, size=0.2),  # noqa: F405
+        panel_grid_minor=element_blank(),  # noqa: F405
+        axis_line=element_line(color=INK_SOFT),  # noqa: F405
     )
     + ggsize(1600, 900)  # noqa: F405
 )
 
-# Save PNG (scale 3x to get 4800 x 2700 px)
-export_ggsave(plot, filename="plot.png", path=".", scale=3)
-
-# Save HTML for interactive version
-export_ggsave(plot, filename="plot.html", path=".")
+# Save PNG (scale 3x for 4800x2700) and HTML
+export_ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)
+export_ggsave(plot, f"plot-{THEME}.html", path=".")