feat(letsplot): implement bland-altman-basic

plots/bland-altman-basic/implementations/python/letsplot.py

@@ -1,16 +1,30 @@
-""" pyplots.ai
+""" anyplot.ai
 bland-altman-basic: Bland-Altman Agreement Plot
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-25
+Library: letsplot 4.9.0 | Python 3.13.13
+Quality: 92/100 | Updated: 2026-05-07
 """
 
+import os
+
 import numpy as np
 import pandas as pd
 from lets_plot import *
 
 
 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
+BRAND = "#009E73"  # Position 1 - first categorical series
+SECONDARY = "#D55E00"  # Position 2
+ACCENT = "#0072B2"  # Position 3
+
 # Data: Simulated blood pressure readings from two sphygmomanometers
 np.random.seed(42)
 n = 80
@@ -38,7 +52,7 @@
 
 # Annotation data - position labels at the left side with offset from line
 annot_x = df["mean"].min() + 2
-y_offset = 0.8  # Offset so labels don't overlap lines
+y_offset = 0.8
 annot_df = pd.DataFrame(
     {
         "x": [annot_x, annot_x, annot_x],
@@ -48,60 +62,54 @@
             f"+1.96 SD: {upper_loa:.2f} mmHg",
             f"-1.96 SD: {lower_loa:.2f} mmHg",
         ],
-        "color": ["bias", "loa", "loa"],
+        "line_type": ["bias", "loa", "loa"],
     }
 )
 
-# Build plot
+# Build plot with theme-adaptive styling
 plot = (
     ggplot()
-    # Scatter points
-    + geom_point(aes(x="mean", y="diff"), data=df, color="#306998", size=5, alpha=0.7)
-    # Mean difference line (bias)
-    + geom_hline(yintercept=mean_diff, color="#16a34a", size=1.5)
-    # Upper limit of agreement
-    + geom_hline(yintercept=upper_loa, color="#dc2626", size=1.2, linetype="dashed")
-    # Lower limit of agreement
-    + geom_hline(yintercept=lower_loa, color="#dc2626", size=1.2, linetype="dashed")
-    # Annotations using geom_label for better visibility
+    + geom_point(aes(x="mean", y="diff"), data=df, color=BRAND, size=6, alpha=0.7, stroke=0.5)
+    + geom_hline(yintercept=mean_diff, color=BRAND, size=1.5)
+    + geom_hline(yintercept=upper_loa, color=SECONDARY, size=1.2, linetype="dashed")
+    + geom_hline(yintercept=lower_loa, color=SECONDARY, size=1.2, linetype="dashed")
     + geom_label(
         aes(x="x", y="y", label="label"),
-        data=annot_df[annot_df["color"] == "bias"],
+        data=annot_df[annot_df["line_type"] == "bias"],
         size=12,
-        color="#16a34a",
-        fill="white",
+        color=BRAND,
+        fill=ELEVATED_BG,
         hjust=0,
         label_padding=0.3,
     )
     + geom_label(
         aes(x="x", y="y", label="label"),
-        data=annot_df[annot_df["color"] == "loa"],
+        data=annot_df[annot_df["line_type"] == "loa"],
         size=12,
-        color="#dc2626",
-        fill="white",
+        color=SECONDARY,
+        fill=ELEVATED_BG,
         hjust=0,
         label_padding=0.3,
     )
-    # Labels and title
     + labs(
         x="Mean of Two Methods (mmHg)",
         y="Difference (Method 1 - Method 2) (mmHg)",
-        title="bland-altman-basic · letsplot · pyplots.ai",
+        title="bland-altman-basic · letsplot · anyplot.ai",
     )
-    # Size and theme
     + ggsize(1600, 900)
     + theme_minimal()
     + theme(
-        plot_title=element_text(size=24),
-        axis_title=element_text(size=20),
-        axis_text=element_text(size=16),
-        panel_grid_major=element_line(color="#e5e5e5", size=0.5),
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_grid_major=element_line(color=INK, size=0.3, linetype="solid"),
         panel_grid_minor=element_blank(),
+        plot_title=element_text(size=24, color=INK),
+        axis_title=element_text(size=20, color=INK),
+        axis_text=element_text(size=16, color=INK_SOFT),
+        axis_line=element_line(color=INK_SOFT, size=0.5),
     )
 )
 
-# Save PNG (scale 3x for 4800x2700)
-ggsave(plot, "plot.png", scale=3, path=".")
-
-# Save HTML for interactive version
-ggsave(plot, "plot.html", path=".")
+# Save PNG and HTML with theme-suffixed filenames
+ggsave(plot, f"plot-{THEME}.png", scale=3, path=".")
+ggsave(plot, f"plot-{THEME}.html", path=".")