Question

在Julia中返回数组中唯一元素数量的函数是什么？

在R中，您有length(unique(x))。我可以在Julia中做同样的事情，但是我认为应该有一种更有效的方法。

Answer 1

如果您想要一个准确的答案，length(unique(x))与普通对象一样有效。如果您的值具有有限的域，例如UInt8，则使用固定大小的表可能会更有效。如果您可以接受近似值，则可以使用HyperLogLog数据结构/算法，该数据结构/算法在OnlineStats包中实现：

https://joshday.github.io/OnlineStats.jl/latest/api/#OnlineStats.HyperLogLog

Answer 2

如果之后不需要x数组，则length(unique!(x))会稍微快一些。对于Floats和Integers，如果数组已经排序，则可以使用map reduce。

function count_unique_sorted(x)
    f(a) = (a,0)
    function op(a,b)
    if a[1] == b[1]
        return (b[1],a[2])
    else
        return (b[1],a[2]+1)
    end
    end
    return mapreduce(f,op,x)[2]+1 
end

如果您不关心数组x的顺序，则可以对一个函数进行排序和计数：

count_unique_sorted!(x)=count_unique_sorted(sort!(x))

一些基准：

using Random,StatsBase, BenchmarkTools
x  = sample(1:100,200)
length(unique(x)) == count_unique_sorted(sort(x)) #true

使用length(unique(x))：

@benchmark length(unique(x))
BenchmarkTools.Trial:
  memory estimate:  6.08 KiB
  allocs estimate:  17
  --------------
  minimum time:     3.350 μs (0.00% GC)
  median time:      3.688 μs (0.00% GC)
  mean time:        5.352 μs (24.35% GC)
  maximum time:     6.691 ms (99.90% GC)
  --------------
  samples:          10000
  evals/sample:     8

使用Set：

@benchmark length(Set(x))
BenchmarkTools.Trial:
  memory estimate:  2.82 KiB
  allocs estimate:  8
  --------------
  minimum time:     2.256 μs (0.00% GC)
  median time:      2.467 μs (0.00% GC)
  mean time:        3.654 μs (26.04% GC)
  maximum time:     5.297 ms (99.91% GC)
  --------------
  samples:          10000
  evals/sample:     9

使用count_unique_sorted!：

x2 = copy(x)
@benchmark count_unique_sorted!(x2)
BenchmarkTools.Trial:
  memory estimate:  0 bytes
  allocs estimate:  0
  --------------
  minimum time:     948.387 ns (0.00% GC)
  median time:      990.323 ns (0.00% GC)
  mean time:        1.038 μs (0.00% GC)
  maximum time:     2.481 μs (0.00% GC)
  --------------
  samples:          10000
  evals/sample:     31

将count_unique_sorted与已排序的数组一起使用

x3 = sort(x)
@benchmark count_unique_sorted(x3)
BenchmarkTools.Trial:
  memory estimate:  0 bytes
  allocs estimate:  0
  --------------
  minimum time:     140.962 ns (0.00% GC)
  median time:      146.831 ns (0.00% GC)
  mean time:        154.121 ns (0.00% GC)
  maximum time:     381.806 ns (0.00% GC)
  --------------
  samples:          10000
  evals/sample:     852

使用count_unique_sorted并对数组进行排序

@benchmark count_unique_sorted(sort(x))
BenchmarkTools.Trial:
  memory estimate:  1.77 KiB
  allocs estimate:  1
  --------------
  minimum time:     1.470 μs (0.00% GC)
  median time:      1.630 μs (0.00% GC)
  mean time:        2.367 μs (21.82% GC)
  maximum time:     4.880 ms (99.94% GC)
  --------------
  samples:          10000
  evals/sample:     10

对于字符串，排序和计数比创建Set慢。

Answer 3

看来length(Set(x))比length(unique(x))快一些。

julia> using StatsBase, BenchmarkTools

julia> num_unique(x) = length(Set(x));

julia> a = sample(1:100, 200);

julia> num_unique(x) == length(unique(x))
true

julia> @benchmark length(unique(x)) setup=(x = sample(1:10000, 20000))
BenchmarkTools.Trial: 
  memory estimate:  450.50 KiB
  allocs estimate:  36
  --------------
  minimum time:     498.130 μs (0.00% GC)
  median time:      570.588 μs (0.00% GC)
  mean time:        579.011 μs (2.41% GC)
  maximum time:     2.321 ms (63.03% GC)
  --------------
  samples:          5264
  evals/sample:     1

julia> @benchmark num_unique(x) setup=(x = sample(1:10000, 20000))
BenchmarkTools.Trial: 
  memory estimate:  288.68 KiB
  allocs estimate:  8
  --------------
  minimum time:     283.031 μs (0.00% GC)
  median time:      393.317 μs (0.00% GC)
  mean time:        397.878 μs (4.24% GC)
  maximum time:     33.499 ms (98.80% GC)
  --------------
  samples:          6704
  evals/sample:     1

另一个测试字符串数组的基准：

julia> using Random

julia> @benchmark length(unique(x)) setup=(x = [randstring(3) for _ in 1:10000])
BenchmarkTools.Trial: 
  memory estimate:  450.50 KiB
  allocs estimate:  36
  --------------
  minimum time:     818.024 μs (0.00% GC)
  median time:      895.944 μs (0.00% GC)
  mean time:        906.568 μs (1.61% GC)
  maximum time:     1.964 ms (51.19% GC)
  --------------
  samples:          3049
  evals/sample:     1

julia> @benchmark num_unique(x) setup=(x = [randstring(3) for _ in 1:10000])
BenchmarkTools.Trial: 
  memory estimate:  144.68 KiB
  allocs estimate:  8
  --------------
  minimum time:     367.018 μs (0.00% GC)
  median time:      378.666 μs (0.00% GC)
  mean time:        384.486 μs (1.07% GC)
  maximum time:     1.314 ms (70.80% GC)
  --------------
  samples:          4527
  evals/sample:     1

朱莉娅：如何返回数组中唯一元素的数量

3 个答案: