我怎样才能 return 从 Swift 4 中的正态分布得到一个浮点数或双精度数?
How can I return a float or double from normal distribution in Swift 4?
我正在尝试 return 从 Swift4 中均值 = 0 和标准差 = 4 的正态分布中得到浮点数或双精度数。最接近我需要的是使用 GameplayKit -> GKGaussianDistribution,如下面的代码所示:
func generateForecast() {
let gauss = GKGaussianDistribution(randomSource: self.source, mean: 0.0, deviation: 4.0)
self.epsilon = gauss.nextInt()
}
我的问题是我打电话的时候
gauss.nextInt()
我显然得到了一个整数。当我尝试
gauss.nextUniform()
我得到一个介于 -1 和 1 之间的数字。
有没有一种相当简单的方法来 return 来自 Swift4 中正态分布的浮点数或双精度数而不是 Int 或介于 -1 和 1 之间的浮点数?
import AppKit
import PlaygroundSupport
import GameplayKit
let nibFile = NSNib.Name(rawValue:"MyView")
var topLevelObjects : NSArray?
Bundle.main.loadNibNamed(nibFile, owner:nil, topLevelObjects: &topLevelObjects)
let views = (topLevelObjects as! Array<Any>).filter { [=15=] is NSView }
// Present the view in Playground
PlaygroundPage.current.liveView = views[0] as! NSView
let s = 0.001
var auto_corr: [Int] = []
class Market {
var numAgents: Int
var traders: [Agent] = []
var price: Double
var epsilon: Int
var priceHist: [Double] = []
var returnHist: [Double] = []
var returnRealHist: [Double] = []
var logReturn: Double = 0
var realReturn: Double = 0
let source = GKRandomSource()
init(numAgents: Int, price: Double, epsilon: Int) {
self.numAgents = numAgents
self.price = price
self.epsilon = epsilon
for _ in 1...numAgents {
self.traders.append(Agent(phi: 1, theta: 1))
}
}
func generateForecast() {
let gauss = GKGaussianDistribution(randomSource: self.source, mean: 0.0, deviation: 4.0)
self.epsilon = gauss.nextInt()
}
}
GKGaussianDistribution
的文档没有提到它从基数 class 覆盖 nextUniform()
,所以不要假设它会为您 return 正态分布值:
您可以使用 Box-Muller Transformation 滚动您自己的高斯分布:
class MyGaussianDistribution {
private let randomSource: GKRandomSource
let mean: Float
let deviation: Float
init(randomSource: GKRandomSource, mean: Float, deviation: Float) {
precondition(deviation >= 0)
self.randomSource = randomSource
self.mean = mean
self.deviation = deviation
}
func nextFloat() -> Float {
guard deviation > 0 else { return mean }
let x1 = randomSource.nextUniform() // a random number between 0 and 1
let x2 = randomSource.nextUniform() // a random number between 0 and 1
let z1 = sqrt(-2 * log(x1)) * cos(2 * Float.pi * x2) // z1 is normally distributed
// Convert z1 from the Standard Normal Distribution to our Normal Distribution
return z1 * deviation + mean
}
}
我故意没有从 GKRandomDistribution
中继承 class 因为还有其他方法我需要覆盖但与这个问题无关。
我正在尝试 return 从 Swift4 中均值 = 0 和标准差 = 4 的正态分布中得到浮点数或双精度数。最接近我需要的是使用 GameplayKit -> GKGaussianDistribution,如下面的代码所示:
func generateForecast() {
let gauss = GKGaussianDistribution(randomSource: self.source, mean: 0.0, deviation: 4.0)
self.epsilon = gauss.nextInt()
}
我的问题是我打电话的时候
gauss.nextInt()
我显然得到了一个整数。当我尝试
gauss.nextUniform()
我得到一个介于 -1 和 1 之间的数字。
有没有一种相当简单的方法来 return 来自 Swift4 中正态分布的浮点数或双精度数而不是 Int 或介于 -1 和 1 之间的浮点数?
import AppKit
import PlaygroundSupport
import GameplayKit
let nibFile = NSNib.Name(rawValue:"MyView")
var topLevelObjects : NSArray?
Bundle.main.loadNibNamed(nibFile, owner:nil, topLevelObjects: &topLevelObjects)
let views = (topLevelObjects as! Array<Any>).filter { [=15=] is NSView }
// Present the view in Playground
PlaygroundPage.current.liveView = views[0] as! NSView
let s = 0.001
var auto_corr: [Int] = []
class Market {
var numAgents: Int
var traders: [Agent] = []
var price: Double
var epsilon: Int
var priceHist: [Double] = []
var returnHist: [Double] = []
var returnRealHist: [Double] = []
var logReturn: Double = 0
var realReturn: Double = 0
let source = GKRandomSource()
init(numAgents: Int, price: Double, epsilon: Int) {
self.numAgents = numAgents
self.price = price
self.epsilon = epsilon
for _ in 1...numAgents {
self.traders.append(Agent(phi: 1, theta: 1))
}
}
func generateForecast() {
let gauss = GKGaussianDistribution(randomSource: self.source, mean: 0.0, deviation: 4.0)
self.epsilon = gauss.nextInt()
}
}
GKGaussianDistribution
的文档没有提到它从基数 class 覆盖 nextUniform()
,所以不要假设它会为您 return 正态分布值:
您可以使用 Box-Muller Transformation 滚动您自己的高斯分布:
class MyGaussianDistribution {
private let randomSource: GKRandomSource
let mean: Float
let deviation: Float
init(randomSource: GKRandomSource, mean: Float, deviation: Float) {
precondition(deviation >= 0)
self.randomSource = randomSource
self.mean = mean
self.deviation = deviation
}
func nextFloat() -> Float {
guard deviation > 0 else { return mean }
let x1 = randomSource.nextUniform() // a random number between 0 and 1
let x2 = randomSource.nextUniform() // a random number between 0 and 1
let z1 = sqrt(-2 * log(x1)) * cos(2 * Float.pi * x2) // z1 is normally distributed
// Convert z1 from the Standard Normal Distribution to our Normal Distribution
return z1 * deviation + mean
}
}
我故意没有从 GKRandomDistribution
中继承 class 因为还有其他方法我需要覆盖但与这个问题无关。