Eri*_*icP 6 performance f# idiomatic imperative
我正在使用Exercism来学习F#.Nth Prime的挑战是建立一个Eratosthenes筛子.单元测试让你搜索第1,001个素数,即104,743.
我修改了一个代码片段,我记得从F#For Fun和Profit批量工作(需要10k素数,而不是25)并将它与我自己的命令式版本进行比较.性能差异显着:
有没有一种有效的方法来这样做?我喜欢F#.我喜欢使用F#库保存多少时间.但有时我看不到有效的惯用路线.
这是惯用的代码:
// we only need to check numbers ending in 1, 3, 7, 9 for prime
let getCandidates seed =
let nextTen seed ten =
let x = (seed) + (ten * 10)
[x + 1; x + 3; x + 7; x + 9]
let candidates = [for x in 0..9 do yield! nextTen seed x ]
match candidates with
| 1::xs -> xs //skip 1 for candidates
| _ -> candidates
let filterCandidates (primes:int list) (candidates:int list): int list =
let isComposite candidate =
primes |> List.exists (fun p -> candidate % p = 0 )
candidates |> List.filter (fun c -> not (isComposite c))
let prime nth : int option =
match nth with
| 0 -> None
| 1 -> Some 2
| _ ->
let rec sieve seed primes candidates =
match candidates with
| [] -> getCandidates seed |> filterCandidates primes |> sieve (seed + 100) primes //get candidates from next hunderd
| p::_ when primes.Length = nth - 2 -> p //value found; nth - 2 because p and 2 are not in primes list
| p::xs when (p * p) < (seed + 100) -> //any composite of this prime will not be found until after p^2
sieve seed (p::primes) [for x in xs do if (x % p) > 0 then yield x]
| p::xs ->
sieve seed (p::primes) xs
Some (sieve 0 [3; 5] [])
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这是当务之急:
type prime =
struct
val BaseNumber: int
val mutable NextMultiple: int
new (baseNumber) = {BaseNumber = baseNumber; NextMultiple = (baseNumber * baseNumber)}
//next multiple that is odd; (odd plus odd) is even plus odd is odd
member this.incrMultiple() = this.NextMultiple <- (this.BaseNumber * 2) + this.NextMultiple; this
end
let prime nth : int option =
match nth with
| 0 -> None
| 1 -> Some 2
| _ ->
let nth' = nth - 1 //not including 2, the first prime
let primes = Array.zeroCreate<prime>(nth')
let mutable primeCount = 0
let mutable candidate = 3
let mutable isComposite = false
while primeCount < nth' do
for i = 0 to primeCount - 1 do
if primes.[i].NextMultiple = candidate then
isComposite <- true
primes.[i] <- primes.[i].incrMultiple()
if isComposite = false then
primes.[primeCount] <- new prime(candidate)
primeCount <- primeCount + 1
isComposite <- false
candidate <- candidate + 2
Some primes.[nth' - 1].BaseNumber
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因此,一般来说,在使用函数式习惯用法时,您可能会期望比使用命令式模型时慢一些,因为您必须创建新对象,这比修改现有对象要花费更长的时间。
对于这个问题,特别是当使用 F# 列表时,与使用数组相比,每次都需要迭代素数列表,这是一种性能损失。您还应该注意,您不需要单独生成候选列表,您只需循环并动态添加 2 即可。也就是说,最大的性能优势可能是使用突变来存储您的nextNumber.
type prime = {BaseNumber: int; mutable NextNumber: int}
let isComposite (primes:prime list) candidate =
let rec inner primes candidate =
match primes with
| [] -> false
| p::ps ->
match p.NextNumber = candidate with
| true -> p.NextNumber <- p.NextNumber + p.BaseNumber*2
inner ps candidate |> ignore
true
| false -> inner ps candidate
inner primes candidate
let prime nth: int option =
match nth with
| 0 -> None
| 1 -> Some 2
| _ ->
let rec findPrime (primes: prime list) (candidate: int) (n: int) =
match nth - n with
| 1 -> primes
| _ -> let isC = isComposite primes candidate
if (not isC) then
findPrime ({BaseNumber = candidate; NextNumber = candidate*candidate}::primes) (candidate + 2) (n+1)
else
findPrime primes (candidate + 2) n
let p = findPrime [{BaseNumber = 3; NextNumber = 9};{BaseNumber = 5; NextNumber = 25}] 7 2
|> List.head
Some(p.BaseNumber)
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运行完这个#time,我得到了大约 500 毫秒的运行时间prime 10001。相比之下,“命令式”代码大约需要 250 毫秒,“idomatic”代码大约需要 1300 毫秒。