{"spec_id":"curve-oc","library":"pygal","language":"python","code":"\"\"\" anyplot.ai\ncurve-oc: Operating Characteristic (OC) Curve\nLibrary: pygal 3.1.3 | Python 3.13.14\nQuality: 88/100 | Updated: 2026-06-20\n\"\"\"\n\nimport os\nimport sys\n\n\n# This file is named pygal.py — remove its own directory from sys.path so that\n# `import pygal` resolves to the installed package, not this script itself.\n_thisdir = os.path.dirname(os.path.abspath(__file__))\nif _thisdir in sys.path:\n sys.path.remove(_thisdir)\n\nfrom math import comb\n\nimport cairosvg\nimport numpy as np\nimport pygal\nfrom pygal.style import Style\n\n\nTHEME = os.getenv(\"ANYPLOT_THEME\", \"light\")\n\n# Theme-adaptive chrome tokens\nPAGE_BG = \"#FAF8F1\" if THEME == \"light\" else \"#1A1A17\"\nINK = \"#1A1A17\" if THEME == \"light\" else \"#F0EFE8\"\nINK_MUTED = \"#6B6A63\" if THEME == \"light\" else \"#A8A79F\"\n\n# Imprint categorical palette — first series always #009E73\nIMPRINT_PALETTE = (\n \"#009E73\", # green — n=50, c=1\n \"#C475FD\", # lavender — n=50, c=2\n \"#4467A3\", # blue — n=100, c=2 (reference plan)\n \"#BD8233\", # ochre — n=100, c=3\n INK_MUTED, # muted neutral — AQL reference line\n INK_MUTED, # muted neutral — LTPD reference line\n \"#AE3030\", # matte red — producer's risk (alpha)\n \"#AE3030\", # matte red — consumer's risk (beta)\n)\n\n# Data — tighter x-range for practical readability\nfraction_defective = np.linspace(0, 0.15, 200)\n\n# Sampling plans: (sample_size, acceptance_number, label)\nplans = [(50, 1, \"n=50, c=1\"), (50, 2, \"n=50, c=2\"), (100, 2, \"n=100, c=2\"), (100, 3, \"n=100, c=3\")]\n\n# Compute OC curves — P(accept) = sum C(n,k) * p^k * (1-p)^(n-k) for k=0..c\noc_curves = {}\nfor n, c, label in plans:\n p = fraction_defective\n oc_curves[label] = sum(comb(n, k) * p**k * (1 - p) ** (n - k) for k in range(c + 1))\n\n# Quality levels\naql = 0.01 # Acceptable Quality Level (1%)\nltpd = 0.08 # Lot Tolerance Percent Defective (8%)\n\n# Risks for reference plan n=100, c=2\npa_at_aql = float(sum(comb(100, k) * aql**k * (1 - aql) ** (100 - k) for k in range(3)))\nalpha = 1 - pa_at_aql\nbeta = float(sum(comb(100, k) * ltpd**k * (1 - ltpd) ** (100 - k) for k in range(3)))\n\ncustom_style = Style(\n background=PAGE_BG,\n plot_background=PAGE_BG,\n foreground=INK,\n foreground_strong=INK,\n foreground_subtle=INK_MUTED,\n colors=IMPRINT_PALETTE,\n title_font_size=66,\n label_font_size=56,\n major_label_font_size=44,\n legend_font_size=44,\n value_font_size=36,\n stroke_width=2.5,\n font_family=\"sans-serif\",\n tooltip_font_size=36,\n opacity=0.9,\n opacity_hover=1.0,\n)\n\nchart = pygal.XY(\n width=3200,\n height=1800,\n style=custom_style,\n title=\"curve-oc · python · pygal · anyplot.ai\",\n x_title=\"Fraction Defective (p)\",\n y_title=\"P(accept)\",\n show_dots=False,\n stroke=True,\n fill=False,\n show_x_guides=False,\n show_y_guides=True,\n legend_at_bottom=True,\n legend_at_bottom_columns=4,\n legend_box_size=28,\n truncate_legend=-1,\n interpolate=\"hermite\",\n interpolation_parameters={\"type\": \"cardinal\", \"c\": 0.75},\n range=(0, 1.05),\n xrange=(0, 0.15),\n x_value_formatter=lambda x: f\"{x:.0%}\",\n value_formatter=lambda y: f\"{y:.2f}\",\n allow_interruptions=True,\n x_labels=[0, 0.01, 0.02, 0.04, 0.06, 0.08, 0.10, 0.12, 0.15],\n y_labels=[0, 0.2, 0.4, 0.6, 0.8, 1.0],\n show_minor_y_labels=True,\n js=[],\n print_values=False,\n margin_top=40,\n margin_bottom=80,\n margin_left=60,\n spacing=20,\n)\n\n# Linestyle map: solid for n=100 plans, dashed for n=50 to aid distinction near p=0\nlinestyles = {\n \"n=50, c=1\": {\"width\": 6, \"dasharray\": \"16, 10\", \"linecap\": \"round\"},\n \"n=50, c=2\": {\"width\": 6, \"dasharray\": \"4, 8\", \"linecap\": \"round\"},\n \"n=100, c=2\": {\"width\": 12, \"linecap\": \"round\", \"linejoin\": \"round\"},\n \"n=100, c=3\": {\"width\": 6, \"linecap\": \"round\", \"linejoin\": \"round\"},\n}\n\nfor _n, _c, label in plans:\n curve_data = list(zip(fraction_defective.tolist(), oc_curves[label].tolist(), strict=True))\n chart.add(\n label,\n curve_data,\n show_dots=False,\n stroke_style=linestyles[label],\n formatter=lambda v: f\"P(accept)={v[1]:.3f}\" if isinstance(v, (list, tuple)) else f\"{v:.3f}\",\n )\n\n# AQL vertical reference line — thin dashed, subordinate to curves\nchart.add(\n f\"AQL ({aql:.0%})\",\n [(aql, 0), (aql, 1.05)],\n show_dots=False,\n stroke_style={\"width\": 3, \"dasharray\": \"14, 8\", \"linecap\": \"round\"},\n)\n\n# LTPD vertical reference line\nchart.add(\n f\"LTPD ({ltpd:.0%})\",\n [(ltpd, 0), (ltpd, 1.05)],\n show_dots=False,\n stroke_style={\"width\": 3, \"dasharray\": \"14, 8\", \"linecap\": \"round\"},\n)\n\n# Producer's risk point (alpha at AQL for n=100, c=2)\nchart.add(\n f\"α={alpha:.1%} (producer risk)\",\n [(aql, pa_at_aql)],\n stroke=False,\n show_dots=True,\n dots_size=22,\n formatter=lambda v: f\"α={1 - v[1]:.1%}\" if isinstance(v, (list, tuple)) else f\"{v:.3f}\",\n)\n\n# Consumer's risk point (beta at LTPD for n=100, c=2)\nchart.add(\n f\"β={beta:.1%} (consumer risk)\",\n [(ltpd, beta)],\n stroke=False,\n show_dots=True,\n dots_size=22,\n formatter=lambda v: f\"β={v[1]:.1%}\" if isinstance(v, (list, tuple)) else f\"{v:.3f}\",\n)\n\n# Post-process SVG: inject CSS to remove the 4-sided box frame (top/right spines).\n# Pygal draws a full border rect around the plot area; there is no built-in option\n# to suppress individual sides, so we hide the rect stroke via CSS.\n_svg = chart.render()\n_frame_css = (\n b'\"\n)\n_svg_patched = (\n _svg.replace(b\"\", _frame_css + b\"\", 1)\n if b\"\" in _svg\n else _svg.replace(b\"\", _frame_css + b\"\", 1)\n)\n\ncairosvg.svg2png(bytestring=_svg_patched, write_to=f\"plot-{THEME}.png\")\nwith open(f\"plot-{THEME}.html\", \"wb\") as f:\n f.write(_svg_patched)\n"}