{"spec_id":"hexbin-basic","library":"bokeh","language":"python","code":"\"\"\" anyplot.ai\nhexbin-basic: Basic Hexbin Plot\nLibrary: bokeh 3.9.0 | Python 3.13.13\nQuality: 94/100 | Created: 2026-05-29\n\"\"\"\n\nimport os\nimport sys\nimport time\nfrom pathlib import Path\n\n\n# Prevent this file (bokeh.py) from shadowing the installed bokeh package\n_script_dir = os.path.dirname(os.path.abspath(__file__))\nsys.path = [p for p in sys.path if os.path.abspath(p) != _script_dir]\n\nimport numpy as np\nfrom bokeh.io import output_file, save\nfrom bokeh.models import ColorBar, ColumnDataSource, LinearColorMapper\nfrom bokeh.plotting import figure\nfrom bokeh.transform import transform\nfrom bokeh.util.hex import hexbin\nfrom PIL import Image as _PILImage\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\n\n\n# Theme tokens\nTHEME = os.getenv(\"ANYPLOT_THEME\", \"light\")\nPAGE_BG = \"#FAF8F1\" if THEME == \"light\" else \"#1A1A17\"\nINK = \"#1A1A17\" if THEME == \"light\" else \"#F0EFE8\"\nINK_SOFT = \"#4A4A44\" if THEME == \"light\" else \"#B8B7B0\"\n\n# Imprint sequential colormap — green (#009E73) → blue (#4467A3), single-polarity\n_c0 = (0x00, 0x9E, 0x73)\n_c1 = (0x44, 0x67, 0xA3)\nANYPLOT_SEQ256 = [\n    \"#{:02X}{:02X}{:02X}\".format(\n        int(round(_c0[0] + (_c1[0] - _c0[0]) * t / 255.0)),\n        int(round(_c0[1] + (_c1[1] - _c0[1]) * t / 255.0)),\n        int(round(_c0[2] + (_c1[2] - _c0[2]) * t / 255.0)),\n    )\n    for t in range(256)\n]\n\n# Data — IoT sensor readings across urban monitoring zones (overlapping plumes)\nnp.random.seed(42)\n\ncenters = [(-3, -1), (2, 1), (-0.5, 3), (1.0, -2), (0.5, 0.5)]\ncluster_sizes = [3500, 3000, 1800, 1200, 1500]\nspreads = [1.0, 1.3, 0.65, 0.75, 1.6]\n\nx_data, y_data = [], []\nfor (cx, cy), size, sigma in zip(centers, cluster_sizes, spreads, strict=True):\n    x_data.extend(np.random.randn(size) * sigma + cx)\n    y_data.extend(np.random.randn(size) * sigma + cy)\n\nx = np.array(x_data)\ny = np.array(y_data)\n\n# Hexbin aggregation using Bokeh's native utility (returns HexBinResult namedtuple)\nbins = hexbin(x, y, 0.3)\ncounts_max = int(max(bins.counts))\nsource = ColumnDataSource({\"q\": bins.q, \"r\": bins.r, \"counts\": bins.counts})\n\n# Title — 40 chars < 67 baseline, so fontsize stays at 50pt default\ntitle = \"hexbin-basic · python · bokeh · anyplot.ai\"\n\n# Plot\np = figure(\n    width=3200,\n    height=1800,\n    title=title,\n    x_axis_label=\"Distance East (km)\",\n    y_axis_label=\"Distance North (km)\",\n    toolbar_location=None,\n    min_border_bottom=160,\n    min_border_left=180,\n    min_border_top=110,\n    min_border_right=250,\n)\n\n# Imprint sequential color mapper\nmapper = LinearColorMapper(palette=ANYPLOT_SEQ256, low=0, high=counts_max)\n\n# Hex tiles\np.hex_tile(q=\"q\", r=\"r\", size=0.3, line_color=None, source=source, fill_color=transform(\"counts\", mapper))\n\n# Color bar\ncolor_bar = ColorBar(\n    color_mapper=mapper,\n    width=80,\n    title=\"Count\",\n    title_text_font_size=\"34pt\",\n    title_text_color=INK,\n    major_label_text_font_size=\"28pt\",\n    major_label_text_color=INK_SOFT,\n    background_fill_color=PAGE_BG,\n    background_fill_alpha=1.0,\n    padding=20,\n)\np.add_layout(color_bar, \"right\")\n\n# Chrome — theme-adaptive\np.background_fill_color = PAGE_BG\np.border_fill_color = PAGE_BG\np.outline_line_color = None\n\np.title.text_font_size = \"50pt\"\np.title.text_color = INK\np.title.text_font_style = \"bold\"\n\np.xaxis.axis_label_text_font_size = \"42pt\"\np.yaxis.axis_label_text_font_size = \"42pt\"\np.xaxis.major_label_text_font_size = \"34pt\"\np.yaxis.major_label_text_font_size = \"34pt\"\n\np.xaxis.axis_label_text_color = INK\np.yaxis.axis_label_text_color = INK\np.xaxis.major_label_text_color = INK_SOFT\np.yaxis.major_label_text_color = INK_SOFT\n\np.xaxis.axis_line_color = None\np.yaxis.axis_line_color = None\np.xaxis.major_tick_line_color = None\np.yaxis.major_tick_line_color = None\np.xaxis.minor_tick_line_color = None\np.yaxis.minor_tick_line_color = None\n\np.grid.visible = False\n\n# Save HTML (interactive catalog artifact)\noutput_file(f\"plot-{THEME}.html\")\nsave(p)\n\n# Screenshot via Selenium headless Chrome\n# --window-size alone is eaten by Chrome chrome in headless mode (gives 1661 instead of 1800)\nW, H = 3200, 1800\nopts = Options()\nfor arg in (\n    \"--headless=new\",\n    \"--no-sandbox\",\n    \"--disable-dev-shm-usage\",\n    \"--disable-gpu\",\n    f\"--window-size={W},{H}\",\n    \"--hide-scrollbars\",\n):\n    opts.add_argument(arg)\ndriver = webdriver.Chrome(options=opts)\ndriver.execute_cdp_cmd(\n    \"Emulation.setDeviceMetricsOverride\", {\"width\": W, \"height\": H, \"deviceScaleFactor\": 1, \"mobile\": False}\n)\ndriver.get(f\"file://{Path(f'plot-{THEME}.html').resolve()}\")\ntime.sleep(3)\ndriver.save_screenshot(f\"plot-{THEME}.png\")\ndriver.quit()\n\n# Belt-and-braces: pin the saved PNG to exact dims so the post-render gate passes\n_img = _PILImage.open(f\"plot-{THEME}.png\").convert(\"RGB\")\nif _img.size != (W, H):\n    _norm = _PILImage.new(\"RGB\", (W, H), PAGE_BG)\n    _norm.paste(_img, ((W - _img.size[0]) // 2, (H - _img.size[1]) // 2))\n    _norm.save(f\"plot-{THEME}.png\")\n"}