Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base

Vector{Float64}: -2.7 1.3 3.1 4.4 As the example shows, the original Julia array A has now been sorted: [-2.7, 1.3, 3.1, 4.4]. Note that Julia takes care of converting the array to a Ptr{Cdouble}), computing then calling (sort!(A); unique!(A)) will be much more efficient as long as the elements of A can be sorted. Examples julia> unique!([1, 1, 1]) 1-element Vector{Int64}: 1 julia> A = [7, 3, 2, 3, 7, 5]; Vector{Int64}: 7 3 2 5 julia> B = [7, 6, 42, 6, 7, 42]; julia> sort!(B); # unique! is able to process sorted data much more efficiently. julia> unique!(B) 3-element Vector{Int64}: 6 7 42 source Base