The Lambert W function, also called the omega function or product logarithm.
lambertw(z,k) # Lambert W function for argument z and branch index k
lambertw(z) # the same as lambertw(z,0)
z
may be Complex or Real. k
must be an integer. For Real
z
, k
must be either 0
or -1
.
Examples:
julia> lambertw(10)
1.7455280027406994
julia> lambertw(e)
1
julia> lambertw(1.0)
0.5671432904097838
julia> lambertw(-pi/2 + 0im) / pi
4.6681174759251105e-18 + 0.5im
Return 1 + W(-1/e + z)
, for z
satisfying 0 <= abs(z) < 1/e
,
on the branch of index k
, where k
must be either 0
or -1
. This
function is designed to minimize loss of precision near the branch point z=-1/e
.
lambertwbp(z,k)
converges to Float64
precision for abs(z) < 0.32
.
If k=-1
and imag(z) < 0
, the value on the branch k=1
is returned.
julia> lambertwbp(1e-3,-1)
-0.07560894118662498
julia> lambertwbp(0)
-0.0
lambertwbp
uses a series expansion about the branch point z=-1/e
.
The loss of precision in lambertw
is analogous to the loss of precision
in computing the sqrt(1-x)
for x
close to 1
.
The functional inverse of the Lambert W function.
julia> finv(lambertw)(lambertw(1.0))
1.0
julia> finv(lambertw)(lambertw(1+im/2,3))
1.0 + 0.49999999999999944im
The omega constant
julia> ω
ω = 0.5671432904097...
julia> omega
ω = 0.5671432904097...
julia> ω * exp(ω)
1.0
julia> big(ω)
5.67143290409783872999968662210355549753815787186512508135131079223045793086683e-01 with 256 bits of precision
julia> lambertw(1) == float(ω)
true