| //===--- MonteCarloE.swift ------------------------------------------------===// |
| // |
| // This source file is part of the Swift.org open source project |
| // |
| // Copyright (c) 2014 - 2017 Apple Inc. and the Swift project authors |
| // Licensed under Apache License v2.0 with Runtime Library Exception |
| // |
| // See https://swift.org/LICENSE.txt for license information |
| // See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors |
| // |
| //===----------------------------------------------------------------------===// |
| |
| // This test measures performance of Monte Carlo estimation of the e constant. |
| // |
| // We use 'dart' method: we split an interval into N pieces and drop N darts |
| // to this interval. |
| // After that we count number of empty intervals. The probability of being |
| // empty is (1 - 1/N)^N which estimates to e^-1 for large N. |
| // Thus, e = N / Nempty. |
| import TestsUtils |
| |
| public let MonteCarloE = BenchmarkInfo( |
| name: "MonteCarloE", |
| runFunction: run_MonteCarloE, |
| tags: [.validation, .algorithm]) |
| |
| public func run_MonteCarloE(scale: Int) { |
| let N = 200000*scale |
| var intervals = [Bool](repeating: false, count: N) |
| for _ in 1...N { |
| let pos = Int(UInt(truncatingBitPattern: Random())%UInt(N)) |
| intervals[pos] = true |
| } |
| let numEmptyIntervals = intervals.filter{!$0}.count |
| // If there are no empty intervals, then obviously the random generator is |
| // not 'random' enough. |
| CheckResults(numEmptyIntervals != N) |
| let e_estimate = Double(N)/Double(numEmptyIntervals) |
| let e = 2.71828 |
| CheckResults(abs(e_estimate - e) < 0.1) |
| } |
