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Add LinearAlgebra.normalize fallback for scalars (#44835) #44925

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1 change: 1 addition & 0 deletions NEWS.md
Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,7 @@ Standard library changes
system image with other BLAS/LAPACK libraries is not
supported. Instead, it is recommended that the LBT mechanism be used
for swapping BLAS/LAPACK with vendor provided ones. ([#44360])
* `normalize(x, p=2)` now supports any normed vector space `x`, including scalars ([#44925]).

#### Markdown

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20 changes: 16 additions & 4 deletions stdlib/LinearAlgebra/src/generic.jl
Original file line number Diff line number Diff line change
Expand Up @@ -1790,11 +1790,12 @@ end
end

"""
normalize(a::AbstractArray, p::Real=2)
normalize(a, p::Real=2)

Normalize the array `a` so that its `p`-norm equals unity,
i.e. `norm(a, p) == 1`.
See also [`normalize!`](@ref) and [`norm`](@ref).
Normalize `a` so that its `p`-norm equals unity,
i.e. `norm(a, p) == 1`. For scalars, this is similar to sign(a),
except normalize(0) = NaN.
See also [`normalize!`](@ref), [`norm`](@ref), and [`sign`](@ref).

# Examples
```jldoctest
Expand Down Expand Up @@ -1831,6 +1832,14 @@ julia> normalize(a)
0.154303 0.308607 0.617213
0.154303 0.308607 0.617213

julia> normalize(3, 1)
1.0

julia> normalize(-8, 1)
-1.0

julia> normalize(0, 1)
NaN
```
"""
function normalize(a::AbstractArray, p::Real = 2)
Expand All @@ -1843,3 +1852,6 @@ function normalize(a::AbstractArray, p::Real = 2)
return T[]
end
end

normalize(x) = x / norm(x)
normalize(x, p::Real) = x / norm(x, p)
7 changes: 7 additions & 0 deletions stdlib/LinearAlgebra/test/generic.jl
Original file line number Diff line number Diff line change
Expand Up @@ -375,6 +375,13 @@ end
@test typeof(normalize([1 2 3; 4 5 6])) == Array{Float64,2}
end

@testset "normalize for scalars" begin
@test normalize(8.0) == 1.0
@test normalize(-3.0) == -1.0
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@test normalize(-3.0, 1) == -1.0
@test isnan(normalize(0.0))
end

@testset "Issue #30466" begin
@test norm([typemin(Int), typemin(Int)], Inf) == -float(typemin(Int))
@test norm([typemin(Int), typemin(Int)], 1) == -2float(typemin(Int))
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