feat(letsplot): implement ecdf-basic

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

@@ -1,53 +1,74 @@
-""" pyplots.ai
+""" anyplot.ai
 ecdf-basic: Basic ECDF Plot
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 96/100 | Created: 2025-12-23
+Library: letsplot 4.9.0 | Python 3.14.4
+Quality: 87/100 | Updated: 2026-04-24
 """
 
+import os
+
 import numpy as np
 import pandas as pd
-from lets_plot import *  # noqa: F403
-from lets_plot.export import ggsave as export_ggsave
+from lets_plot import (
+    LetsPlot,
+    aes,
+    element_blank,
+    element_line,
+    element_rect,
+    element_text,
+    ggplot,
+    ggsize,
+    labs,
+    scale_y_continuous,
+    stat_ecdf,
+    theme,
+    theme_minimal,
+)
+from lets_plot.export import ggsave
+
 
+LetsPlot.setup_html()
 
-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"
+GRID = "#C9C7C1" if THEME == "light" else "#565551"
+BRAND = "#009E73"
 
-# Data - Response times (ms) from a web service
+# Data — Web service response times (ms) with mixed distribution
 np.random.seed(42)
 response_times = np.concatenate(
-    [
-        np.random.exponential(scale=50, size=150),  # Fast responses
-        np.random.normal(loc=200, scale=30, size=50),  # Slower responses
-    ]
+    [np.random.exponential(scale=50, size=150), np.random.normal(loc=200, scale=30, size=50)]
 )
+df = pd.DataFrame({"response_time": response_times})
 
-# Sort data and calculate ECDF values
-sorted_values = np.sort(response_times)
-ecdf_values = np.arange(1, len(sorted_values) + 1) / len(sorted_values)
-
-df = pd.DataFrame({"response_time": sorted_values, "ecdf": ecdf_values})
-
-# Plot - ECDF as step function
+# Plot — ECDF using stat_ecdf with step geometry
 plot = (
-    ggplot(df, aes(x="response_time", y="ecdf"))  # noqa: F405
-    + geom_step(color="#306998", size=2)  # noqa: F405
-    + labs(  # noqa: F405
-        x="Response Time (ms)", y="Cumulative Proportion", title="ecdf-basic · letsplot · pyplots.ai"
+    ggplot(df, aes(x="response_time"))
+    + stat_ecdf(geom="step", color=BRAND, size=2)
+    + labs(
+        x="Response Time (ms)",
+        y="Cumulative Proportion",
+        title="Web Service Response Times · ecdf-basic · letsplot · anyplot.ai",
     )
-    + scale_y_continuous(limits=[0, 1], breaks=[0, 0.25, 0.5, 0.75, 1.0])  # noqa: F405
-    + ggsize(1600, 900)  # noqa: F405
-    + theme_minimal()  # noqa: F405
-    + theme(  # noqa: F405
-        axis_text=element_text(size=16),  # noqa: F405
-        axis_title=element_text(size=20),  # noqa: F405
-        plot_title=element_text(size=24),  # noqa: F405
-        panel_grid_major=element_line(color="#CCCCCC", size=0.5, linetype="dashed"),  # noqa: F405
-        panel_grid_minor=element_blank(),  # noqa: F405
+    + scale_y_continuous(limits=[0, 1], breaks=[0, 0.25, 0.5, 0.75, 1.0])
+    + ggsize(1600, 900)
+    + theme_minimal()
+    + theme(
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        legend_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_grid_major=element_line(color=GRID, size=0.6),
+        panel_grid_minor=element_blank(),
+        axis_line=element_line(color=INK_SOFT, size=0.6),
+        axis_ticks=element_line(color=INK_SOFT, size=0.5),
+        axis_text=element_text(size=16, color=INK_SOFT),
+        axis_title=element_text(size=20, color=INK),
+        plot_title=element_text(size=24, color=INK),
     )
 )
 
-# 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
+ggsave(plot, filename=f"plot-{THEME}.png", path=".", scale=3)
+ggsave(plot, filename=f"plot-{THEME}.html", path=".")