julia_help outputs the documentation of a julia function.

julia_help(fname)

## Arguments

fname the name of julia function you want to get help with.

## Examples


## julia_setup is quite time consuming
julia_help("sqrt")#> 
#> sqrt(x)
#> 
#>
#> Return $\sqrt{x}$. Throws [DomainError](@ref) for negative [Real](@ref) arguments. Use complex negative arguments instead. The prefix operator √ is equivalent to sqrt.
#>
#> # Examples
#>
#> jldoctest; filter = r"Stacktrace:(\n $[0-9]+$.*)*"
#> julia> sqrt(big(81))
#> 9.0
#>
#> julia> sqrt(big(-81))
#> ERROR: DomainError with -8.1e+01:
#> NaN result for non-NaN input.
#> Stacktrace:
#>  [1] sqrt(::BigFloat) at ./mpfr.jl:501
#> [...]
#>
#> julia> sqrt(big(complex(-81)))
#> 0.0 + 9.0im
#> 
#>
#> 
#> sqrt(A::AbstractMatrix)
#> 
#>
#> If A has no negative real eigenvalues, compute the principal matrix square root of A, that is the unique matrix $X$ with eigenvalues having positive real part such that $X^2 = A$. Otherwise, a nonprincipal square root is returned.
#>
#> If A is symmetric or Hermitian, its eigendecomposition ([eigen](@ref)) is used to compute the square root. Otherwise, the square root is determined by means of the Björck-Hammarling method [^BH83], which computes the complex Schur form ([schur](@ref)) and then the complex square root of the triangular factor.
#>
#> [^BH83]: Åke Björck and Sven Hammarling, "A Schur method for the square root of a matrix", Linear Algebra and its Applications, 52-53, 1983, 127-140. [doi:10.1016/0024-3795(83)80010-X](https://doi.org/10.1016/0024-3795(83)80010-X)
#>
#> # Examples
#>
#> jldoctest
#> julia> A = [4 0; 0 4]
#> 2×2 Array{Int64,2}:
#>  4  0
#>  0  4
#>
#> julia> sqrt(A)
#> 2×2 Array{Float64,2}:
#>  2.0  0.0
#>  0.0  2.0
#>