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Replaced `mu`/`sigma` with the more descriptive `mean`/`stdDeviation`

This commit is contained in:
Vincent Esche 2019-11-01 19:45:04 +01:00
parent 844fd175cf
commit da8da3835a
4 changed files with 80 additions and 72 deletions
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42
Sources/Surge/Linear Algebra/Matrix.swift
View File

@ -161,36 +161,37 @@ extension Matrix where Scalar == Float {
}
/// Generates a matrix of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public static func randomNormal(
rows: Int,
columns: Int,
mu: Float = 0.0,
sigma: Float = 1.0
mean: Float = 0.0,
stdDeviation: Float = 1.0
) -> Matrix {
var generator = SystemRandomNumberGenerator()
return self.randomNormal(
rows: rows,
columns: columns,
mu: mu,
sigma: sigma,
mean: mean,
stdDeviation: stdDeviation,
using: &generator
)
}
/// Generates a matrix of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma")
/// based on the provided random-number `generator`.
public static func randomNormal<T>(
rows: Int,
columns: Int,
mu: Float = 0.0,
sigma: Float = 1.0,
mean: Float = 0.0,
stdDeviation: Float = 1.0,
using generator: inout T
) -> Matrix where T: RandomNumberGenerator {
let grid = Surge.randomNormal(
count: rows * columns,
mu: mu,
sigma: sigma,
mean: mean,
stdDeviation: stdDeviation,
using: &generator
)
return Matrix(rows: rows, columns: columns, grid: grid)
@ -230,36 +231,37 @@ extension Matrix where Scalar == Double {
}
/// Generates a matrix of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public static func randomNormal(
rows: Int,
columns: Int,
mu: Double = 0.0,
sigma: Double = 1.0
mean: Double = 0.0,
stdDeviation: Double = 1.0
) -> Matrix {
var generator = SystemRandomNumberGenerator()
return self.randomNormal(
rows: rows,
columns: columns,
mu: mu,
sigma: sigma,
mean: mean,
stdDeviation: stdDeviation,
using: &generator
)
}
/// Generates a matrix of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma")
/// based on the provided random-number `generator`.
public static func randomNormal<T>(
rows: Int,
columns: Int,
mu: Double = 0.0,
sigma: Double = 1.0,
mean: Double = 0.0,
stdDeviation: Double = 1.0,
using generator: inout T
) -> Matrix where T: RandomNumberGenerator {
let grid = Surge.randomNormal(
count: rows * columns,
mu: mu,
sigma: sigma,
mean: mean,
stdDeviation: stdDeviation,
using: &generator
)
return Matrix(rows: rows, columns: columns, grid: grid)

38
Sources/Surge/Linear Algebra/Scalar.swift
View File

@ -86,20 +86,21 @@ public func * (lhs: Double, rhs: Matrix<Double>) -> Matrix<Double> {
extension Float {
/// Generates a normal-distributed random value with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public static func randomNormal(
mu: Float = 0.0,
sigma: Float = 1.0
mean: Float = 0.0,
stdDeviation: Float = 1.0
) -> Float {
var generator = SystemRandomNumberGenerator()
return randomNormal(mu: mu, sigma: sigma, using: &generator)
return randomNormal(mean: mean, stdDeviation: stdDeviation, using: &generator)
}
/// Generates a normal-distributed random value with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma")
/// based on the provided random-number `generator`.
public static func randomNormal<T>(
mu: Float = 0.0,
sigma: Float = 1.0,
mean: Float = 0.0,
stdDeviation: Float = 1.0,
using generator: inout T
) -> Float where T: RandomNumberGenerator {
let lhs = Float.random(in: 0.0...1.0, using: &generator)
@ -107,28 +108,29 @@ extension Float {
let z = sqrt(-2.0 * log(lhs)) * cos(2.0 * .pi * rhs)
// After applying the transform `z` holds values with a sigma of `1.0` and a mu of `0.0`.
// After applying the transform `z` holds values with a stdDeviation of `1.0` and a mean of `0.0`.
return z * sigma + mu
return z * stdDeviation + mean
}
}
extension Double {
/// Generates a normal-distributed random value with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public static func randomNormal(
mu: Double = 0.0,
sigma: Double = 1.0
mean: Double = 0.0,
stdDeviation: Double = 1.0
) -> Double {
var generator = SystemRandomNumberGenerator()
return randomNormal(mu: mu, sigma: sigma, using: &generator)
return randomNormal(mean: mean, stdDeviation: stdDeviation, using: &generator)
}
/// Generates a normal-distributed random value with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma")
/// based on the provided random-number `generator`.
public static func randomNormal<T>(
mu: Double = 0.0,
sigma: Double = 1.0,
mean: Double = 0.0,
stdDeviation: Double = 1.0,
using generator: inout T
) -> Double where T: RandomNumberGenerator {
let lhs = Double.random(in: 0.0...1.0, using: &generator)
@ -136,8 +138,8 @@ extension Double {
let z = sqrt(-2.0 * log(lhs)) * cos(2.0 * .pi * rhs)
// After applying the transform `z` holds values with a sigma of `1.0` and a mu of `0.0`.
// After applying the transform `z` holds values with a stdDeviation of `1.0` and a mean of `0.0`.
return z * sigma + mu
return z * stdDeviation + mean
}
}

34
Sources/Surge/Linear Algebra/Vector.swift
View File

@ -87,25 +87,26 @@ extension Vector where Scalar == Float {
}
/// Generates a vector of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public static func randomNormal(
count: Int,
mu: Float = 0.0,
sigma: Float = 1.0
mean: Float = 0.0,
stdDeviation: Float = 1.0
) -> Vector {
var generator = SystemRandomNumberGenerator()
return self.randomNormal(count: count, mu: mu, sigma: sigma, using: &generator)
return self.randomNormal(count: count, mean: mean, stdDeviation: stdDeviation, using: &generator)
}
/// Generates a vector of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma")
/// based on the provided random-number `generator`.
public static func randomNormal<T>(
count: Int,
mu: Float = 0.0,
sigma: Float = 1.0,
mean: Float = 0.0,
stdDeviation: Float = 1.0,
using generator: inout T
) -> Vector where T: RandomNumberGenerator {
let scalars = Surge.randomNormal(count: count, mu: mu, sigma: sigma, using: &generator)
let scalars = Surge.randomNormal(count: count, mean: mean, stdDeviation: stdDeviation, using: &generator)
return Vector(scalars: scalars)
}
}
@ -132,25 +133,26 @@ extension Vector where Scalar == Double {
}
/// Generates a vector of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public static func randomNormal(
count: Int,
mu: Double = 0.0,
sigma: Double = 1.0
mean: Double = 0.0,
stdDeviation: Double = 1.0
) -> Vector {
var generator = SystemRandomNumberGenerator()
return self.randomNormal(count: count, mu: mu, sigma: sigma, using: &generator)
return self.randomNormal(count: count, mean: mean, stdDeviation: stdDeviation, using: &generator)
}
/// Generates a vector of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma")
/// based on the provided random-number `generator`.
public static func randomNormal<T>(
count: Int,
mu: Double = 0.0,
sigma: Double = 1.0,
mean: Double = 0.0,
stdDeviation: Double = 1.0,
using generator: inout T
) -> Vector where T: RandomNumberGenerator {
let scalars = Surge.randomNormal(count: count, mu: mu, sigma: sigma, using: &generator)
let scalars = Surge.randomNormal(count: count, mean: mean, stdDeviation: stdDeviation, using: &generator)
return Vector(scalars: scalars)
}
}

38
Sources/Surge/Random/Random.swift
View File

@ -61,33 +61,34 @@ public func random<T>(
}
/// Generates an array of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public func randomNormal(
count: Int,
mu: Float = 0.0,
sigma: Float = 1.0
mean: Float = 0.0,
stdDeviation: Float = 1.0
) -> [Float] {
var generator = SystemRandomNumberGenerator()
return randomNormal(count: count, mu: mu, sigma: sigma, using: &generator)
return randomNormal(count: count, mean: mean, stdDeviation: stdDeviation, using: &generator)
}
/// Generates an array of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation).
/// `mean` (aka "mu") and `stdDeviation` (aka "sigma").
public func randomNormal(
count: Int,
mu: Double = 0.0,
sigma: Double = 1.0
mean: Double = 0.0,
stdDeviation: Double = 1.0
) -> [Double] {
var generator = SystemRandomNumberGenerator()
return randomNormal(count: count, mu: mu, sigma: sigma, using: &generator)
return randomNormal(count: count, mean: mean, stdDeviation: stdDeviation, using: &generator)
}
/// Generates an array of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mu` (mean) and `sigma` (std deviation)
/// based on the provided random-number `generator`.
public func randomNormal<T>(
count: Int,
mu: Float = 0.0,
sigma: Float = 1.0,
mean: Float = 0.0,
stdDeviation: Float = 1.0,
using generator: inout T
) -> [Float] where T: RandomNumberGenerator {
var lhs: [Float] = random(count: count, in: 0.0...1.0, using: &generator)
@ -98,18 +99,19 @@ public func randomNormal<T>(
// After applying the transform `lhs` holds values with a sigma of `1.0` and a mu of `0.0`.
// stdNormal * sigma + mu
mulInPlace(&lhs, sigma)
addInPlace(&lhs, mu)
mulInPlace(&lhs, stdDeviation)
addInPlace(&lhs, mean)
return lhs
}
/// Generates an array of normal-distributed random values with given
/// `mu` (mean) and `sigma` (std deviation) based on the provided random-number `generator`.
/// `mu` (mean) and `sigma` (std deviation)
/// based on the provided random-number `generator`.
public func randomNormal<T>(
count: Int,
mu: Double = 0.0,
sigma: Double = 1.0,
mean: Double = 0.0,
stdDeviation: Double = 1.0,
using generator: inout T
) -> [Double] where T: RandomNumberGenerator {
// Box-Muller transform
@ -122,8 +124,8 @@ public func randomNormal<T>(
// After applying the transform `lhs` holds values with a sigma of `1.0` and a mu of `0.0`.
// stdNormal * sigma + mu
mulInPlace(&lhs, sigma)
addInPlace(&lhs, mu)
mulInPlace(&lhs, stdDeviation)
addInPlace(&lhs, mean)
return lhs
}