BigO.jl

Complexity estimation library
Author endremborza
Popularity
4 Stars
Updated Last
10 Months Ago
Started In
March 2021

BigO

Stable Dev Build Status Coverage

Julia library for complexity plotting and estimation

Quickstart

using Random
using BigO



function lamesort!(a)
    for i in axes(a,1)
        for j in 1:i
            if a[i] < a[j]
                 a[j], a[i] = a[i], a[j]
            end
        end
    end
end

function _merge(a1::AbstractArray{T, 1}, a2::AbstractArray{T, 1}) where {T}
    n1, n2 = size(a1,1), size(a2,1)
    n = n1 + n2
    out = Array{T,1}(undef, n)
    i, j = 1, 1
    while i + j <= n + 1
        if (i > n1) e = a2[j]; j += 1
        elseif (j > n2) e = a1[i]; i += 1
        elseif (a1[i] > a2[j]) e = a2[j]; j += 1
        else e = a1[i]; i += 1 end
        out[i+j - 2 ] = e
    end
    return out
end

function mergesort(a)
    n = size(a, 1)
    n == 1 && return a
    h = n ÷ 2
    return _merge(mergesort(a[1:h]), mergesort(a[h+1:n]))
end


report = RunReport([mergesort, lamesort!], randperm, 100:1000:10100, seconds=0.2; samples=200)
report |> bigos

Dict{String,String} with 2 entries: "mergesort" => "O(n log n)" "lamesort!" => "O(n^p)"

using Plots
report |> plot

plot

Used By Packages

No packages found.