{"spec_id":"histogram-basic","library":"bokeh","language":"python","code":"\"\"\" anyplot.ai\nhistogram-basic: Basic Histogram\nLibrary: bokeh 3.9.0 | Python 3.13.13\nQuality: 93/100 | Updated: 2026-05-28\n\"\"\"\n\nimport io\nimport os\nimport sys\nimport time\nfrom pathlib import Path\n\nfrom PIL import Image\n\n\n# Prevent this file's directory from shadowing the installed bokeh package\nsys.path = [p for p in sys.path if os.path.abspath(p) != os.path.dirname(os.path.abspath(__file__))]\n\nimport numpy as np\nfrom bokeh.io import output_file, save\nfrom bokeh.models import ColumnDataSource, HoverTool, Label, Legend, LegendItem, NumeralTickFormatter\nfrom bokeh.plotting import figure\nfrom bokeh.transform import linear_cmap\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\"\nELEVATED_BG = \"#FFFDF6\" if THEME == \"light\" else \"#242420\"\nINK = \"#1A1A17\" if THEME == \"light\" else \"#F0EFE8\"\nINK_SOFT = \"#4A4A44\" if THEME == \"light\" else \"#B8B7B0\"\nINK_MUTED = \"#6B6A63\" if THEME == \"light\" else \"#A8A79F\"\n\n# imprint_seq colormap: brand green (#009E73) → blue (#4467A3), 256 stops\nANYPLOT_SEQ256 = [\n    \"#{:02X}{:02X}{:02X}\".format(\n        int(round(68 * t / 255)), int(round(158 - 55 * t / 255)), int(round(115 + 48 * t / 255))\n    )\n    for t in range(256)\n]\n\n# Data — Marathon finish times (bimodal: main recreational group + slower group)\nnp.random.seed(42)\nmain_group = np.random.normal(loc=240, scale=30, size=380)\nslower_group = np.random.normal(loc=305, scale=18, size=100)\noutliers = np.random.normal(loc=370, scale=12, size=20)\nvalues = np.concatenate([main_group, slower_group, outliers])\nvalues = values[(values > 120) & (values < 420)]\n\n# Statistics\nmedian_val = np.median(values)\nmean_val = np.mean(values)\n\n# Histogram bins\ncounts, edges = np.histogram(values, bins=28)\nleft_edges = edges[:-1]\nright_edges = edges[1:]\nmax_count = int(counts.max())\n\nsource = ColumnDataSource(\n    data={\n        \"left\": left_edges,\n        \"right\": right_edges,\n        \"top\": counts,\n        \"bottom\": [0] * len(counts),\n        \"count\": counts,\n        \"bin_start\": [f\"{e:.0f}\" for e in left_edges],\n        \"bin_end\": [f\"{e:.0f}\" for e in right_edges],\n    }\n)\n\n# imprint_seq color mapper: low count → green, high count → blue\nfill_mapper = linear_cmap(field_name=\"top\", palette=ANYPLOT_SEQ256, low=0, high=max_count)\n\n# Figure — 3200 × 1800 px landscape\nTITLE = \"histogram-basic · python · bokeh · anyplot.ai\"\nn = len(TITLE)\ntitle_pt = max(34, round(50 * (67 / n if n > 67 else 1.0)))\np = figure(\n    width=3200,\n    height=1800,\n    title=TITLE,\n    x_axis_label=\"Finish Time (min)\",\n    y_axis_label=\"Number of Runners\",\n    toolbar_location=None,\n    x_range=(118, 410),\n    min_border_bottom=160,\n    min_border_left=180,\n    min_border_top=110,\n    min_border_right=50,\n)\n\n# Histogram bars\nbars = p.quad(\n    left=\"left\",\n    right=\"right\",\n    top=\"top\",\n    bottom=\"bottom\",\n    source=source,\n    fill_color=fill_mapper,\n    line_color=PAGE_BG,\n    line_width=1.5,\n    fill_alpha=0.85,\n    hover_fill_color=\"#DDCC77\",\n    hover_fill_alpha=0.95,\n    hover_line_color=PAGE_BG,\n)\n\n# HoverTool\nhover = HoverTool(\n    renderers=[bars], tooltips=[(\"Range\", \"@bin_start–@bin_end min\"), (\"Runners\", \"@count\")], mode=\"mouse\"\n)\np.add_tools(hover)\n\n# Median reference line (matte red)\nmedian_line = p.line(\n    x=[median_val, median_val], y=[0, max_count * 1.05], line_color=\"#AE3030\", line_width=5, line_alpha=0.9\n)\n\n# Mean reference line (ochre, dashed)\nmean_line = p.line(\n    x=[mean_val, mean_val],\n    y=[0, max_count * 1.05],\n    line_color=\"#BD8233\",\n    line_width=5,\n    line_dash=[14, 7],\n    line_alpha=0.9,\n)\n\n# Legend — top-left, closer to the data's left shoulder\nlegend = Legend(\n    items=[\n        LegendItem(label=f\"Median: {median_val:.0f} min\", renderers=[median_line]),\n        LegendItem(label=f\"Mean: {mean_val:.0f} min\", renderers=[mean_line]),\n    ],\n    location=\"top_left\",\n    label_text_font_size=\"34pt\",\n    label_text_color=INK_SOFT,\n    glyph_width=60,\n    glyph_height=6,\n    spacing=16,\n    padding=24,\n    background_fill_color=ELEVATED_BG,\n    background_fill_alpha=0.85,\n    border_line_color=INK_SOFT,\n    border_line_alpha=0.5,\n)\np.add_layout(legend, \"center\")\n\n# Annotations — main distribution peak\npeak_label = Label(\n    x=190,\n    y=max_count * 1.02,\n    text=\"▼ Main group (~4 hr pace)\",\n    text_font_size=\"28pt\",\n    text_color=INK_SOFT,\n    text_font_style=\"bold\",\n)\np.add_layout(peak_label)\n\n# Annotation — slower group shoulder\nslower_peak = int(counts[np.abs(left_edges - 295) < 15].max())\nshoulder_label = Label(\n    x=278,\n    y=slower_peak + max_count * 0.08,\n    text=\"▼ Slower group (~5 hr pace)\",\n    text_font_size=\"28pt\",\n    text_color=INK_SOFT,\n    text_font_style=\"bold\",\n)\np.add_layout(shoulder_label)\n\n# Subtitle — x=215 starts right of the legend box\nsubtitle = Label(\n    x=215,\n    y=max_count * 1.14,\n    text=f\"N = {len(values)} runners  │  Right-skewed bimodal distribution\",\n    text_font_size=\"28pt\",\n    text_color=INK_MUTED,\n)\np.add_layout(subtitle)\n\n# Typography\np.title.text_font_size = f\"{title_pt}pt\"\np.title.text_color = INK\np.title.text_font_style = \"bold\"\np.xaxis.axis_label_text_font_size = \"42pt\"\np.yaxis.axis_label_text_font_size = \"42pt\"\np.xaxis.axis_label_text_color = INK\np.yaxis.axis_label_text_color = INK\np.xaxis.major_label_text_font_size = \"34pt\"\np.yaxis.major_label_text_font_size = \"34pt\"\np.xaxis.major_label_text_color = INK_SOFT\np.yaxis.major_label_text_color = INK_SOFT\np.yaxis.formatter = NumeralTickFormatter(format=\"0,0\")\n\n# Grid — y-axis only, very subtle\np.xgrid.visible = False\np.ygrid.grid_line_alpha = 0.15\np.ygrid.grid_line_color = INK\np.ygrid.grid_line_width = 1\n\n# Chrome\np.outline_line_color = INK_SOFT\np.background_fill_color = PAGE_BG\np.border_fill_color = PAGE_BG\np.xaxis.axis_line_width = 2\np.yaxis.axis_line_width = 2\np.xaxis.axis_line_color = INK_SOFT\np.yaxis.axis_line_color = INK_SOFT\np.xaxis.minor_tick_line_color = None\np.yaxis.minor_tick_line_color = None\np.xaxis.major_tick_line_color = INK_SOFT\np.yaxis.major_tick_line_color = INK_SOFT\np.y_range.start = 0\np.y_range.end = max_count * 1.22\n\n# Save HTML (interactive artifact)\noutput_file(f\"plot-{THEME}.html\")\nsave(p)\n\n# Screenshot with headless Chrome — window is H+200 tall so bokeh canvas fills\n# exactly W×H; PIL crops to the target rect before saving.\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 + 200}\",\n    \"--hide-scrollbars\",\n    \"--force-device-scale-factor=1\",\n):\n    opts.add_argument(arg)\ndriver = webdriver.Chrome(options=opts)\ndriver.set_window_size(W, H + 200)\ndriver.get(f\"file://{Path(f'plot-{THEME}.html').resolve()}\")\ntime.sleep(3)\nraw = driver.get_screenshot_as_png()\ndriver.quit()\nImage.open(io.BytesIO(raw)).crop((0, 0, W, H)).save(f\"plot-{THEME}.png\")\n"}