feat(bokeh): implement pdp-basic

plots/pdp-basic/implementations/python/bokeh.py

@@ -1,18 +1,51 @@
-""" pyplots.ai
+""" anyplot.ai
 pdp-basic: Partial Dependence Plot
-Library: bokeh 3.8.1 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-31
+Library: bokeh 3.9.0 | Python 3.13.13
+Quality: 90/100 | Updated: 2026-05-15
 """
 
-import numpy as np
-from bokeh.io import export_png
-from bokeh.models import Band, ColumnDataSource, Span
-from bokeh.plotting import figure
-from sklearn.datasets import make_friedman1
-from sklearn.ensemble import GradientBoostingRegressor
-from sklearn.inspection import partial_dependence
+import importlib
+import sys
+from pathlib import Path
 
 
+# Remove current directory from sys.path to avoid shadowing bokeh package
+sys.path = [p for p in sys.path if Path(p).resolve() != Path(__file__).resolve().parent]
+
+# Import bokeh module and its submodules
+bokeh_io = importlib.import_module("bokeh.io")  # noqa: E402
+bokeh_models = importlib.import_module("bokeh.models")  # noqa: E402
+bokeh_plotting = importlib.import_module("bokeh.plotting")  # noqa: E402
+
+import os  # noqa: E402
+import time  # noqa: E402
+
+import numpy as np  # noqa: E402
+from selenium import webdriver  # noqa: E402
+from selenium.webdriver.chrome.options import Options  # noqa: E402
+from sklearn.datasets import make_friedman1  # noqa: E402
+from sklearn.ensemble import GradientBoostingRegressor  # noqa: E402
+from sklearn.inspection import partial_dependence  # noqa: E402
+
+
+# Use imported modules
+output_file = bokeh_io.output_file
+save = bokeh_io.save
+Band = bokeh_models.Band
+ColumnDataSource = bokeh_models.ColumnDataSource
+Span = bokeh_models.Span
+figure = bokeh_plotting.figure
+
+# 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
+ACCENT = "#D55E00"  # Okabe-Ito position 2
+
 # Data - Train a model and compute partial dependence
 np.random.seed(42)
 
@@ -55,11 +88,11 @@
 y_min = lower_centered.min() - 1.5
 rug_source = ColumnDataSource(data={"x": rug_x, "y": np.full_like(rug_x, y_min + 0.3)})
 
-# Create figure with proper sizing
+# Plot
 p = figure(
     width=4800,
     height=2700,
-    title="pdp-basic · bokeh · pyplots.ai",
+    title="pdp-basic · bokeh · anyplot.ai",
     x_axis_label="Feature X₀ Value",
     y_axis_label="Partial Dependence (centered)",
 )
@@ -70,63 +103,78 @@
     lower="lower",
     upper="upper",
     source=source,
-    fill_color="#306998",
+    fill_color=BRAND,
     fill_alpha=0.25,
-    line_color="#306998",
+    line_color=BRAND,
     line_alpha=0.4,
 )
 p.add_layout(band)
 
 # Add horizontal line at y=0 for reference
-zero_line = Span(location=0, dimension="width", line_color="#555555", line_width=3, line_dash="dashed", line_alpha=0.6)
+zero_line = Span(location=0, dimension="width", line_color=INK_SOFT, line_width=3, line_dash="dashed", line_alpha=0.6)
 p.add_layout(zero_line)
 
 # Add invisible patch for confidence band legend entry
-p.patch([], [], fill_color="#306998", fill_alpha=0.25, line_color="#306998", line_alpha=0.4, legend_label="80% CI")
+p.patch([], [], fill_color=BRAND, fill_alpha=0.25, line_color=BRAND, line_alpha=0.4, legend_label="80% CI")
 
 # Add main PDP line
-p.line("x", "y", source=source, line_width=5, line_color="#306998", legend_label="Average PD")
+p.line("x", "y", source=source, line_width=5, line_color=BRAND, legend_label="Average PD")
 
 # Add rug plot for data distribution
 p.scatter(
     "x",
     "y",
     source=rug_source,
     size=25,
-    color="#FFD43B",
+    color=ACCENT,
     alpha=0.6,
     line_width=3,
     angle=1.5708,
     marker="dash",
     legend_label="Data Distribution",
 )
 
-# Text styling - scaled for 4800x2700 px canvas
-p.title.text_font_size = "56pt"
-p.title.text_font_style = "bold"
-p.xaxis.axis_label_text_font_size = "42pt"
-p.yaxis.axis_label_text_font_size = "42pt"
-p.xaxis.major_label_text_font_size = "32pt"
-p.yaxis.major_label_text_font_size = "32pt"
+# Style - Text sizing
+p.title.text_font_size = "28pt"
+p.title.text_color = INK
+p.xaxis.axis_label_text_font_size = "22pt"
+p.yaxis.axis_label_text_font_size = "22pt"
+p.xaxis.axis_label_text_color = INK
+p.yaxis.axis_label_text_color = INK
+p.xaxis.major_label_text_font_size = "18pt"
+p.yaxis.major_label_text_font_size = "18pt"
+p.xaxis.major_label_text_color = INK_SOFT
+p.yaxis.major_label_text_color = INK_SOFT
 
 # Axis styling
 p.xaxis.axis_line_width = 3
 p.yaxis.axis_line_width = 3
+p.xaxis.axis_line_color = INK_SOFT
+p.yaxis.axis_line_color = INK_SOFT
 p.xaxis.major_tick_line_width = 3
 p.yaxis.major_tick_line_width = 3
+p.xaxis.major_tick_line_color = INK_SOFT
+p.yaxis.major_tick_line_color = INK_SOFT
 p.xaxis.minor_tick_line_width = 2
 p.yaxis.minor_tick_line_width = 2
+p.xaxis.minor_tick_line_color = INK_SOFT
+p.yaxis.minor_tick_line_color = INK_SOFT
 
 # Grid styling
-p.xgrid.grid_line_alpha = 0.3
-p.ygrid.grid_line_alpha = 0.3
+p.xgrid.grid_line_color = INK
+p.ygrid.grid_line_color = INK
+p.xgrid.grid_line_alpha = 0.10
+p.ygrid.grid_line_alpha = 0.10
 p.xgrid.grid_line_dash = "dashed"
 p.ygrid.grid_line_dash = "dashed"
 
 # Legend styling
 p.legend.location = "bottom_right"
-p.legend.label_text_font_size = "32pt"
+p.legend.label_text_font_size = "18pt"
+p.legend.label_text_color = INK_SOFT
+p.legend.background_fill_color = ELEVATED_BG
 p.legend.background_fill_alpha = 0.9
+p.legend.border_line_color = INK_SOFT
 p.legend.border_line_alpha = 0.5
 p.legend.border_line_width = 2
 p.legend.glyph_height = 50
@@ -135,9 +183,31 @@
 p.legend.padding = 25
 p.legend.margin = 40
 
-# Background
-p.background_fill_color = "#fafafa"
-p.border_fill_color = "white"
-
-# Save
-export_png(p, filename="plot.png")
+# Background and border
+p.background_fill_color = PAGE_BG
+p.border_fill_color = PAGE_BG
+p.outline_line_color = INK_SOFT
+
+# Save HTML
+output_file(f"plot-{THEME}.html")
+save(p)
+
+# Screenshot with headless Chrome
+W, H = 4800, 2700
+opts = Options()
+for arg in (
+    "--headless=new",
+    "--no-sandbox",
+    "--disable-dev-shm-usage",
+    "--disable-gpu",
+    f"--window-size={W},{H}",
+    "--hide-scrollbars",
+):
+    opts.add_argument(arg)
+
+driver = webdriver.Chrome(options=opts)
+driver.set_window_size(W, H)
+driver.get(f"file://{Path(f'plot-{THEME}.html').resolve()}")
+time.sleep(3)  # let bokeh's JS render the canvas
+driver.save_screenshot(f"plot-{THEME}.png")
+driver.quit()