# Evaluate multi-variable anonymous function for one variable

**URL:** <https://discourse.julialang.org/t/evaluate-multi-variable-anonymous-function-for-one-variable/11397>\
**Category:** General Usage\
**Created:** [June 3, 2018, 8:35pm UTC](https://discourse.julialang.org/t/evaluate-multi-variable-anonymous-function-for-one-variable/11397 "2018-06-03T20:35:32Z")\
**Posts on this page:** 1\
**Showing post:** 7

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**Author:** ![rdeits](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/rdeits/32/286_2.png) [@rdeits](https://discourse.julialang.org/u/rdeits)\
**Post date:** [June 4, 2018, 7:22pm UTC](https://discourse.julialang.org/t/evaluate-multi-variable-anonymous-function-for-one-variable/11397/7 "2018-06-04T19:22:40Z")

</div>

As @mauro3 suggested, all you need to do is create a new anonymous function for each of your `g_i`, where each anonymous function takes only one argument (`x_i`) and stores the appropriate values of the other arguments to `f`. A function with some of its arguments already bound to values is a [closure](https://en.wikipedia.org/wiki/Closure_(computer_programming)) and we usually write them in Julia with anonymous functions.

For example, given `f(x, y)`, we can make `g1` an anonymous function that only takes `x` and holds a default value for `y`:

```julia
julia> f(x, y) = x + y
f (generic function with 1 method)

julia> g1 = x -> f(x, 2.0) # y = 2.0
(::#1) (generic function with 1 method)

julia> g2 = y -> f(1.5, y) # x = 1.5
(::#3) (generic function with 1 method)

julia> g1(1.5) == g2(2.0) == f(1.5, 2.0)
true

```

To automate this across all the inputs to some function `f`, we just need to build up those anonymous functions in a loop.

Here’s one way to do it. I’m using the helpful `setindex` function from `StaticArrays.jl` to make this a bit more efficient:

```julia
julia> using StaticArrays: setindex

julia> function make_closures(f, default_values...)
         [xi -> f(setindex(default_values, xi, i)...) for i in 1:length(default_values)]
       end
make_closures (generic function with 1 method)

julia> gs = make_closures(f, 0.75, 1.5, 0.8)
3-element Array{##11#13{Int64,#f,Tuple{Float64,Float64,Float64}},1}:
 #11
 #11
 #11

julia> gs[1](1.0) == f(1.0, 1.5, 0.8)
true

julia> gs[2](1.0) == f(0.75, 1.0, 0.8)
true

julia> gs[3](1.0) == f(0.75, 1.5, 1.0)
true

```

A very nice feature of Julia is that you can do this with essentially no performance penalty. Using BenchmarkTools.jl:

```julia
julia> using BenchmarkTools

julia> @btime $(gs[1])(0.75)
  14.931 ns (0 allocations: 0 bytes)

```

Also, as @mauro3 suggested, it will be easier for us to read your code and help you if you [quote it properly](https://discourse.julialang.org/t/psa-how-to-quote-code-with-backticks/7530)

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