Swiftプログラムの実行時間の計測 平均や標準偏差の計算

TimeProfiler.swift

import Accelerate

class TimeProfiler {
    private var results: [Float] = []
    private var samples: Int = 0
    private let ignores: Int

    /// 現在の試行回数
    var trials: Int {
        results.count
    }

    /// 平均
    var mean: Float {
        vDSP.mean(results)
    }

    /// 標準偏差
    var standardDeviation: Float {
        let mean = vDSP.mean(results)
        let meanSquare = vDSP.meanSquare(results)
        let count = results.count
        return sqrt(meanSquare - mean * mean) * sqrt(Float(count) / Float(count - 1))
    }

    /// 最初の ignores 回分の測定を無視する場合は値を指定してください
    init(ignores: Int = 0) {
        self.ignores = ignores
    }

    /// 試行
    func trial<U>(procedure: () -> (U)) -> U {
        let start = mach_absolute_time()
        let result = procedure()
        let end = mach_absolute_time()
        if samples >= ignores {
            results.append(nanoElapsed(start: start, end: end))
        }
        samples += 1
        return result
    }

    /// 試行
    func trial<T, U>(input: T, procedure: ((T) -> (U))) -> U {
        let start = mach_absolute_time()
        let result = procedure(input)
        let end = mach_absolute_time()
        if samples >= ignores {
            results.append(nanoElapsed(start: start, end: end))
        }
        samples += 1
        return result
    }

    /// 測定のリセット
    func reset() {
        results = []
        samples = 0
    }

    private func nanoElapsed(start: UInt64, end: UInt64) -> Float {
        var timebaseInfo = mach_timebase_info_data_t()
        mach_timebase_info(&timebaseInfo)
        return Float((end - start) * UInt64(timebaseInfo.numer) / UInt64(timebaseInfo.denom))
    }
}