feat(letsplot): implement sankey-basic (#5608)

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

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

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

**Parent Issue:** #810

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25156796686)*

---------

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/sankey-basic/implementations/python/letsplot.py

@@ -1,14 +1,17 @@
-""" pyplots.ai
+""" anyplot.ai
 sankey-basic: Basic Sankey Diagram
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: letsplot 4.9.0 | Python 3.13.13
+Quality: 85/100 | Updated: 2026-04-30
 """
 
+import os
+
 import pandas as pd
 from lets_plot import (
     LetsPlot,
     aes,
     element_blank,
+    element_rect,
     element_text,
     geom_polygon,
     geom_rect,
@@ -27,6 +30,16 @@
 
 LetsPlot.setup_html()
 
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+
+# Okabe-Ito palette for source categories (canonical order, first = #009E73)
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7"]
+
 # Energy flow data: sources -> sectors (realistic energy distribution)
 flows = [
     ("Coal", "Industrial", 28),
@@ -41,9 +54,9 @@
     ("Renewable", "Industrial", 6),
 ]
 
-# Define node ordering
 sources = ["Coal", "Natural Gas", "Nuclear", "Renewable"]
 targets = ["Industrial", "Residential", "Commercial"]
+source_color_map = dict(zip(sources, OKABE_ITO, strict=True))
 
 # Calculate totals for each node
 source_totals = {}
@@ -54,7 +67,7 @@
 for _, tgt, val in flows:
     target_totals[tgt] = target_totals.get(tgt, 0) + val
 
-# Normalize positions
+# Layout parameters
 total_flow = sum(v for _, _, v in flows)
 node_gap = 0.04
 x_left = 0.18
@@ -80,43 +93,33 @@
 source_offsets = dict.fromkeys(sources, 0)
 target_offsets = dict.fromkeys(targets, 0)
 
-# Build flow polygons with smooth bezier curves
+# Build flow polygons with smooth cubic bezier curves
 flow_data = []
 
 for src, tgt, val in flows:
     flow_height = val / total_flow * 0.85
 
-    # Source connection points
     src_y0 = source_positions[src]["y0"] + source_offsets[src]
     src_y1 = src_y0 + flow_height
     source_offsets[src] += flow_height
 
-    # Target connection points
     tgt_y0 = target_positions[tgt]["y0"] + target_offsets[tgt]
     tgt_y1 = tgt_y0 + flow_height
     target_offsets[tgt] += flow_height
 
-    # Create smooth bezier polygon for flow
     n_points = 40
-    x_vals_top = []
-    y_vals_top = []
-    x_vals_bottom = []
-    y_vals_bottom = []
+    x_vals_top, y_vals_top = [], []
+    x_vals_bottom, y_vals_bottom = [], []
 
     for i in range(n_points + 1):
         t = i / n_points
         x = x_left + t * (x_right - x_left)
-        # Smooth cubic bezier easing
         ease = t * t * (3 - 2 * t)
-        y_top = src_y1 + ease * (tgt_y1 - src_y1)
-        y_bottom = src_y0 + ease * (tgt_y0 - src_y0)
-
         x_vals_top.append(x)
-        y_vals_top.append(y_top)
+        y_vals_top.append(src_y1 + ease * (tgt_y1 - src_y1))
         x_vals_bottom.append(x)
-        y_vals_bottom.append(y_bottom)
+        y_vals_bottom.append(src_y0 + ease * (tgt_y0 - src_y0))
 
-    # Combine into closed polygon
     x_polygon = x_vals_top + x_vals_bottom[::-1]
     y_polygon = y_vals_top + y_vals_bottom[::-1]
 
@@ -132,32 +135,18 @@
 for src in sources:
     pos = source_positions[src]
     node_rects.append(
-        {
-            "xmin": pos["x"] - node_width / 2,
-            "xmax": pos["x"] + node_width / 2,
-            "ymin": pos["y0"],
-            "ymax": pos["y1"],
-            "label": src,
-            "side": "source",
-        }
+        {"xmin": pos["x"] - node_width / 2, "xmax": pos["x"] + node_width / 2, "ymin": pos["y0"], "ymax": pos["y1"]}
     )
 
 for tgt in targets:
     pos = target_positions[tgt]
     node_rects.append(
-        {
-            "xmin": pos["x"] - node_width / 2,
-            "xmax": pos["x"] + node_width / 2,
-            "ymin": pos["y0"],
-            "ymax": pos["y1"],
-            "label": tgt,
-            "side": "target",
-        }
+        {"xmin": pos["x"] - node_width / 2, "xmax": pos["x"] + node_width / 2, "ymin": pos["y0"], "ymax": pos["y1"]}
     )
 
 df_nodes = pd.DataFrame(node_rects)
 
-# Build labels with flow values
+# Build labels with flow totals
 labels = []
 for src in sources:
     pos = source_positions[src]
@@ -183,56 +172,50 @@
 
 df_labels = pd.DataFrame(labels)
 
-# Colors for each energy source
-source_colors = {"Coal": "#4A4A4A", "Natural Gas": "#306998", "Nuclear": "#9B59B6", "Renewable": "#27AE60"}
-
-# Create the plot
+# Plot
 plot = (
     ggplot()
     + geom_polygon(
-        aes(x="x", y="y", group="flow_id", fill="source"), data=df_flows, alpha=0.65, color="white", size=0.2
-    )
-    + geom_rect(
-        aes(xmin="xmin", xmax="xmax", ymin="ymin", ymax="ymax"),
-        data=df_nodes,
-        fill="#2C3E50",
-        color="#1A252F",
-        size=1.5,
+        aes(x="x", y="y", group="flow_id", fill="source"), data=df_flows, alpha=0.65, color=PAGE_BG, size=0.2
     )
+    + geom_rect(aes(xmin="xmin", xmax="xmax", ymin="ymin", ymax="ymax"), data=df_nodes, fill=INK, color=INK, size=1.5)
     + geom_text(
         aes(x="x", y="y", label="label"),
         data=df_labels[df_labels["side"] == "left"],
         size=14,
         hjust=1,
+        color=INK_SOFT,
         family="sans-serif",
     )
     + geom_text(
         aes(x="x", y="y", label="label"),
         data=df_labels[df_labels["side"] == "right"],
         size=14,
         hjust=0,
+        color=INK_SOFT,
         family="sans-serif",
     )
-    + scale_fill_manual(values=[source_colors[s] for s in sources], name="Energy Source")
-    + labs(title="Energy Flow · sankey-basic · letsplot · pyplots.ai")
+    + scale_fill_manual(values=[source_color_map[s] for s in sources], name="Energy Source")
+    + labs(title="Energy Flow · sankey-basic · letsplot · anyplot.ai")
     + theme_minimal()
     + theme(
-        plot_title=element_text(size=30, face="bold"),
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_background=element_rect(fill=PAGE_BG),
+        plot_title=element_text(size=30, face="bold", color=INK),
         axis_title=element_blank(),
         axis_text=element_blank(),
         axis_ticks=element_blank(),
         panel_grid=element_blank(),
-        legend_text=element_text(size=18),
-        legend_title=element_text(size=20, face="bold"),
+        legend_text=element_text(size=18, color=INK_SOFT),
+        legend_title=element_text(size=20, face="bold", color=INK),
         legend_position="bottom",
+        legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
     )
     + scale_x_continuous(limits=[-0.02, 1.02])
     + scale_y_continuous(limits=[-0.02, 1.02])
     + ggsize(1600, 900)
 )
 
-# Save as PNG (scale 3x for 4800 × 2700 px)
-ggsave(plot, "plot.png", path=".", scale=3)
-
-# Save as HTML for interactivity
-ggsave(plot, "plot.html", path=".")
+# Save PNG (scale 3x for 4800 × 2700 px) and HTML
+ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)
+ggsave(plot, f"plot-{THEME}.html", path=".")