I want to convert a multivariate function into a single variable function. Aka to perform partial differentiation. While my attempt works but it is such an ugly kludge. Is there a better way of doing this? func1(x,y) = 3.0*x + 7.0*y^2.0 function create1Dfunction(func::Function,vector::Vector,varnu…

How about just this: julia> func1(x, y) = 3.0*x + 7.0*y^2.0 func1 (generic function with 1 method) julia> g(x) = func1(3.1, x) g (generic function with 1 method) julia> func1(3.1, 7.8) 435.18 julia> g(7.8) 435.18

What if my function have 26 variables and I want to convert it to a single variable function on variable number 21? And fill the rest with the value [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26] and I don’t want to do it by hand. And I don’t know the value of the vector of n…

Ah, I see. Here’s an option without dynamic code generation: oned(f, args, pos) = x -> f(ntuple(i -> i == pos ? x : args[i], length(args))...) f(x, y) = 3.0*x + 7.0*y^2 g = oned(f, [3.1, 7.8], 2) And now: julia> f(3.1, 7.8) 435.18 julia> g(7.8) 435.18

[image] bennedich: oned(f, args, pos) = x -> f(ntuple(i -> i == pos ? x : args[i], length(args))…) Thank you very much. That worked and is a lot shorter function oned(f::Function, args::Vector, pos::Int64) return x -> f(ntuple(i -> i == pos ? x : args[i], length(args))...) end h = oned(f…

Please check my final version of the program func1(x,y) = 3.0 * x + 7.0 * y ^ 2.0 func2(X) = 3.0 * X[1] + 7.0 * X[2] ^ 2.0 function create1Dfunction(func::Function,args::Vector,pos::Int64;FuncType::String="MultiParameters") if 1 <= pos <= length(args) if FuncType == "MultiParam…

you could also splat the vector f(a,b,c,d,e,f,g) = a+b+c+d+e+f+g g(a) = f(a,[1,2,3,4,5,6]...) g(3) #24

Another option could be to add a method to the function foo using keyword arguments with the same names: foo(a,b,c,d,e,f,g) = a + b + c + d + e + f + g foo(;a=1.0, b=2.0, c=3.0, d=4.0, e=5.0, f=6.0, g=7.0) = foo(a,b,c,d,e,f,g) # Examples: foo(c=-25) # 0.0 foo(d=0) # 24.0

My package CallableExpressions.jl supports constructing evaluatable expression, and partial evaluation of these expressions. Several other packages offer different approaches to solving similar problems. A PR by @MilesCranmer , solving this problem, was also recently merged, to be released with Julia…

This thread is ancient, but this should be done using tuples instead: create1arg(f, args::Tuple, pos::Integer) = x -> f(Base.setindex(args, x, pos)...) And then distinguish the vector-arg version like this create1arg(f, args::Vector, pos::Integer) = x -> f(setindex!(args, x, pos)) Or some non-…

[image] DNF: This thread is ancient Our grannies too. Can we continue to visit them, please.

Converting a multivariate function to a single variate function

New to Julia

nilshg August 13, 2024, 12:21pm 14

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Converting a multivariate function to a single variate function

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