% Auto-generated benchmark data macros
% Generated by: experiments/benchmarks/analyze_results.py
% Do not edit manually - regenerate with 'make report'

% Overall correctness (all sample sizes)
\newcommand{\cssrOverallCorrectness}{82}
\newcommand{\spectralOverallCorrectness}{85}
\newcommand{\nsdOverallCorrectness}{73}
\newcommand{\csmOverallCorrectness}{39}
\newcommand{\bsiOverallCorrectness}{32}

% Correctness at N >= 1,000
\newcommand{\cssrLargeNCorrectness}{80}
\newcommand{\spectralLargeNCorrectness}{98}
\newcommand{\nsdLargeNCorrectness}{75}
\newcommand{\csmLargeNCorrectness}{45}
\newcommand{\bsiLargeNCorrectness}{25}

% Correctness at N >= 10,000
\newcommand{\cssrTenKCorrectness}{75}
\newcommand{\spectralTenKCorrectness}{100}
\newcommand{\nsdTenKCorrectness}{75}
\newcommand{\csmTenKCorrectness}{50}
\newcommand{\bsiTenKCorrectness}{25}

% Runtime at N=1,000,000 (seconds)
\newcommand{\cssrRuntime}{13.5}
\newcommand{\spectralRuntime}{38.1}
\newcommand{\nsdRuntime}{4.0}
\newcommand{\csmRuntime}{1.2}
\newcommand{\bsiRuntime}{25.8}

% Speedup vs CSSR
\newcommand{\cssrSpeedup}{1}
\newcommand{\spectralSpeedup}{0.4}
\newcommand{\nsdSpeedup}{3.4}
\newcommand{\csmSpeedup}{11.4}
\newcommand{\bsiSpeedup}{0.5}

% Best performing algorithm
\newcommand{\bestAlgorithm}{SPECTRAL}
\newcommand{\bestCorrectness}{98}

% Test statistics (from pytest)
\newcommand{\testCount}{355}
\newcommand{\testCoverage}{90}
