feat(seaborn): implement line-timeseries

plots/line-timeseries/implementations/python/seaborn.py

@@ -1,49 +1,82 @@
-""" pyplots.ai
+""" anyplot.ai
 line-timeseries: Time Series Line Plot
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-26
+Library: seaborn 0.13.2 | Python 3.13.13
+Quality: 88/100 | Updated: 2026-05-09
 """
 
+import os
+
 import matplotlib.dates as mdates
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import seaborn as sns
 
 
+# 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"
+BRAND = "#009E73"  # Okabe-Ito position 1
+
+# Theme-adaptive seaborn configuration
+sns.set_theme(
+    style="ticks",
+    rc={
+        "figure.facecolor": PAGE_BG,
+        "axes.facecolor": PAGE_BG,
+        "axes.edgecolor": INK_SOFT,
+        "axes.labelcolor": INK,
+        "text.color": INK,
+        "xtick.color": INK_SOFT,
+        "ytick.color": INK_SOFT,
+        "grid.color": INK,
+        "grid.alpha": 0.15,
+        "legend.facecolor": ELEVATED_BG,
+        "legend.edgecolor": INK_SOFT,
+    },
+)
+
 # Data: Daily temperature readings over 3 months
 np.random.seed(42)
 dates = pd.date_range(start="2024-01-01", periods=90, freq="D")
 
-# Create realistic temperature pattern with seasonal variation and noise
 day_of_year = np.arange(90)
-base_temp = 5 + 10 * np.sin(2 * np.pi * (day_of_year + 10) / 365)  # Seasonal trend
+base_temp = 5 + 10 * np.sin(2 * np.pi * (day_of_year + 10) / 365)
 noise = np.random.randn(90) * 3
 temperature = base_temp + noise
 
 df = pd.DataFrame({"Date": dates, "Temperature (°C)": temperature})
 
-# Create plot
-fig, ax = plt.subplots(figsize=(16, 9))
+# Plot
+fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
 
-sns.lineplot(data=df, x="Date", y="Temperature (°C)", color="#306998", linewidth=3, ax=ax)
+sns.lineplot(data=df, x="Date", y="Temperature (°C)", color=BRAND, linewidth=3, ax=ax, errorbar=("ci", 95))
 
-# Style adjustments for large canvas
-ax.set_xlabel("Date", fontsize=20)
-ax.set_ylabel("Temperature (°C)", fontsize=20)
-ax.set_title("line-timeseries · seaborn · pyplots.ai", fontsize=24)
-ax.tick_params(axis="both", labelsize=16)
+# Style
+ax.set_xlabel("Date", fontsize=20, color=INK)
+ax.set_ylabel("Temperature (°C)", fontsize=20, color=INK)
+ax.set_title("line-timeseries · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK)
+ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
 
-# Smart date formatting for months
+# Smart date formatting
 ax.xaxis.set_major_locator(mdates.MonthLocator())
 ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %Y"))
 ax.xaxis.set_minor_locator(mdates.WeekdayLocator(byweekday=mdates.MO))
 
 # Rotate labels to prevent overlap
 plt.setp(ax.get_xticklabels(), rotation=45, ha="right")
 
-# Grid for readability
-ax.grid(True, alpha=0.3, linestyle="--")
+# Grid on both axes for readability
+ax.grid(True, alpha=0.15, linewidth=0.8, color=INK)
+
+# Remove top and right spines
+ax.spines["top"].set_visible(False)
+ax.spines["right"].set_visible(False)
+for spine in ["left", "bottom"]:
+    ax.spines[spine].set_color(INK_SOFT)
 
 plt.tight_layout()
-plt.savefig("plot.png", dpi=300, bbox_inches="tight")
+plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)