feat(letsplot): implement streamgraph-basic

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

@@ -1,81 +1,100 @@
-""" pyplots.ai
+""" anyplot.ai
 streamgraph-basic: Basic Stream Graph
-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: 2026-05-06
 """
 
+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.export import ggsave
+from scipy.interpolate import make_interp_spline
 
 
 LetsPlot.setup_html()  # noqa: F405
 
-# Data - monthly streaming hours by music genre over two years
+# 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 — first series always #009E73
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00"]
+
+# Data — monthly streaming hours by music genre over two years
 np.random.seed(42)
 n_months = 24
 genres = ["Pop", "Rock", "Hip-Hop", "Electronic", "Jazz"]
-n_genres = len(genres)
 
-# Generate smooth trends for each genre with distinct patterns
 raw_values = {}
+months_orig = np.arange(n_months, dtype=float)
 for i, genre in enumerate(genres):
     base = 100 + 50 * np.sin(np.linspace(0, 4 * np.pi, n_months) + i * 0.7)
     trend = np.linspace(0, 25, n_months) * (1 if i % 2 == 0 else -0.6)
     noise = np.random.randn(n_months) * 8
     raw_values[genre] = np.clip(base + trend + noise, 25, None)
 
-# Compute streamgraph positions (centered around baseline)
-values_matrix = np.array([raw_values[g] for g in genres])
-total_per_month = values_matrix.sum(axis=0)
-baseline_offset = -total_per_month / 2
+# Smooth each series with a cubic spline for flowing curves
+n_interp = n_months * 8
+months_smooth = np.linspace(0, n_months - 1, n_interp)
+values_smooth = {}
+for genre in genres:
+    spline = make_interp_spline(months_orig, raw_values[genre], k=3)
+    values_smooth[genre] = np.clip(spline(months_smooth), 10, None)
+
+# Compute streamgraph positions (symmetric baseline around zero)
+values_matrix = np.array([values_smooth[g] for g in genres])
+total_per_point = values_matrix.sum(axis=0)
+baseline_offset = -total_per_point / 2
 
-# Build dataframe with ymin/ymax for ribbon geometry
 data = []
-for month_idx in range(n_months):
-    cumulative = baseline_offset[month_idx]
+for t_idx, t in enumerate(months_smooth):
+    cumulative = baseline_offset[t_idx]
     for genre_idx, genre in enumerate(genres):
         ymin = cumulative
-        ymax = cumulative + values_matrix[genre_idx, month_idx]
-        data.append({"month": month_idx, "genre": genre, "ymin": ymin, "ymax": ymax})
+        ymax = cumulative + values_matrix[genre_idx, t_idx]
+        data.append({"month": t, "genre": genre, "ymin": ymin, "ymax": ymax})
         cumulative = ymax
 
 df = pd.DataFrame(data)
 
-# Create streamgraph using geom_ribbon for precise ymin/ymax control
+# Plot
+anyplot_theme = theme(  # noqa: F405
+    plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),  # noqa: F405
+    panel_background=element_rect(fill=PAGE_BG),  # noqa: F405
+    panel_grid_major_x=element_line(color=INK_SOFT, size=0.3, linetype="dashed"),  # noqa: F405
+    panel_grid_major_y=element_blank(),  # noqa: F405
+    panel_grid_minor=element_blank(),  # noqa: F405
+    axis_title=element_text(color=INK, size=20),  # noqa: F405
+    axis_text=element_text(color=INK_SOFT, size=16),  # noqa: F405
+    axis_text_y=element_blank(),  # noqa: F405
+    axis_ticks_y=element_blank(),  # noqa: F405
+    axis_line=element_line(color=INK_SOFT),  # noqa: F405
+    plot_title=element_text(color=INK, size=24),  # noqa: F405
+    legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),  # noqa: F405
+    legend_text=element_text(color=INK_SOFT, size=16),  # noqa: F405
+    legend_title=element_text(color=INK, size=18),  # noqa: F405
+)
+
 plot = (
     ggplot(df, aes(x="month", fill="genre"))  # noqa: F405
     + geom_ribbon(aes(ymin="ymin", ymax="ymax"), alpha=0.9)  # noqa: F405
-    + scale_fill_manual(  # noqa: F405
-        values=["#306998", "#FFD43B", "#38BDF8", "#A78BFA", "#FB923C"]
-    )
+    + scale_fill_manual(values=OKABE_ITO)  # noqa: F405
     + scale_x_continuous(  # noqa: F405
         breaks=[0, 6, 12, 18, 23], labels=["Jan '23", "Jul '23", "Jan '24", "Jul '24", "Dec '24"]
     )
     + labs(  # noqa: F405
-        x="Month", y="Streaming Hours", fill="Genre", title="streamgraph-basic · lets-plot · pyplots.ai"
+        x="Month", y="", fill="Genre", title="streamgraph-basic · letsplot · anyplot.ai"
     )
     + 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
-        legend_text=element_text(size=16),  # noqa: F405
-        legend_title=element_text(size=18),  # noqa: F405
-        axis_text_y=element_blank(),  # noqa: F405
-        axis_ticks_y=element_blank(),  # noqa: F405
-        panel_grid_major_y=element_blank(),  # noqa: F405
-        panel_grid_minor_y=element_blank(),  # noqa: F405
-        panel_grid_major_x=element_line(  # noqa: F405
-            color="#CCCCCC", size=0.5, linetype="dashed"
-        ),
-    )
+    + anyplot_theme
 )
 
-# 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=".")