# Question: Least square fitting method for non-linear function
**URL:** https://discourse.julialang.org/t/question-least-square-fitting-method-for-non-linear-function/97595
**Category:** General Usage
**Tags:** question, lsqfit
**Created:** [April 18, 2023, 12:46am UTC](https://discourse.julialang.org/t/question-least-square-fitting-method-for-non-linear-function/97595 "2023-04-18T00:46:44Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@manu\_han](https://discourse.julialang.org/u/manu_han)
#### Post date: [April 18, 2023, 12:46am UTC](https://discourse.julialang.org/t/question-least-square-fitting-method-for-non-linear-function/97595/1 "2023-04-18T00:46:44Z")
To fit the non-linear function with other data, I am trying to use the ‘LsqFit.curve\_fit’ which was introduced by the following link: [GitHub - JuliaNLSolvers/LsqFit.jl: Simple curve fitting in Julia](https://github.com/JuliaNLSolvers/LsqFit.jl)
here is toy example:
```julia
using DelimitedFiles, Plots, Serialization, Transducers, Match, LsqFit, Dierckx
#meta=deserialize("meta_SPS.bin");
meta=rand(55,27,150) #same type with real meta
#Fv_NOC=deserialize("Fv_NOC.bin");
Fv_NOC=rand(200,3,55) #same type with real meta
meta_start=395; meta_end=400; meta_div=trunc(Int,((meta_end-meta_start)*100)); #
meta_cal=LinRange(meta_start,meta_end,meta_div);
I_sharp=Array{Float64,2}(undef,150,27);
I_broad=zeros(Float64, meta_div)
obs_metaq=LinRange(394,402,205); obs_Iq=LinRange(100,1000,205);
function OTrans(meta, meta_shift, Holn, Fv_NOC, p)
Translation=p
for brazera=1:27;
for J1=1:150
I_sharp[J1,brazera]=(1/(meta[J1,brazera,numb_v].-meta_shift[numb_v])^4)*Holn[J1,brazera]*exp(-2.2/Translation)
I_broad.+= I_sharp[J1,brazera].*exp.(-2 .*( meta_cal .-(meta[J1,brazera,numb_v])).^2)
end
end
return I_broad
end
interpolation=Spline1D(obs_metaq, obs_Iq, k=1)
Int_Iq=interpolation(meta_cal) #Finding query points
p0=Float64.([300])
fit=LsqFit.curve_fit(OTrans,meta_cal,Int_Iq,p0)
```
I made a code similar to the example introduced, but it didn’t work leaving an error like the following message:
```julia
ERROR: MethodError: no method matching OTrans(::LinRange{Float64, Int64}, ::Vector{Float64})
Closest candidates are:
OTrans(::Any) at Toy_example.jl:48
Stacktrace:
[1] (::LsqFit.var"#18#20"{typeof(OTrans), LinRange{Float64, Int64}, Vector{Float64}})(p::Vector{Float64})
```
How can I get this to work? or any other method?
---
### Author:  [@Sevi](https://discourse.julialang.org/u/Sevi)
#### Post date: [April 18, 2023, 9:39am UTC](https://discourse.julialang.org/t/question-least-square-fitting-method-for-non-linear-function/97595/2 "2023-04-18T09:39:05Z")
It looks like `LsqFit.curve_fit` expects the model function you want to minimize as first argument, but the arguments of this `model` function have to have a specific signature.
In your example, `OTrans` requires five arguments, but the model function has to accept two arguments with a specific meaning. This is documented here
> **[GitHub - JuliaNLSolvers/LsqFit.jl: Simple curve fitting in Julia](https://github.com/JuliaNLSolvers/LsqFit.jl#existing-functionality)**
>
> Simple curve fitting in Julia. Contribute to JuliaNLSolvers/LsqFit.jl development by creating an account on GitHub.
If you want to keep your `OTrans` function as it is, one possibility would be to define another function with the right signature that internally calls `OTrans` in the right way. Something like
```julia
OTrans(#= different arguments here =#) = ...
model(x, p) = OTrans(#= use x, p to compute the right arguments for OTrans =#)
```
Aside: Your code is formatted in a pretty weird way which makes it hard to see what is going on. To make it easier for yourself and others, you might want to format the code a bit (e.g. put statements in the same scope at the same indentation level).
---
### Author:  [@manu\_han](https://discourse.julialang.org/u/manu_han)
#### Post date: [June 6, 2023, 6:47am UTC](https://discourse.julialang.org/t/question-least-square-fitting-method-for-non-linear-function/97595/3 "2023-06-06T06:47:32Z")
As follow your comment, I put an argument as an array having 4 elements.
But it doesn’t work with the error as follows: MethodError: no method matching isinf(::Array{Float64, 3}).
Cite: [How to use the array as the argument for curve-fit?](https://discourse.julialang.org/t/how-to-use-the-array-as-the-argument-for-curve-fit/99802)
Is there a way to solve this problem?
other posts I cited:
> [@Curve fitting with LsqFit](https://discourse.julialang.org/t/curve-fitting-with-lsqfit/27685/5):
>
> Thank you! It is much clearer now. Yet, there is a new problem. Now i am trying to use a complex function with ternary operator: model1(t, p) = @.(p[1] \* exp(-p[2] \* t) + p[3] \* exp(-p[4] \* t) \* cos(p[5] \* t + p[6])+ p[7] \* (t \> p[8] ? 0 : (1 - t / p[8])^2)) The error i get is the following: ERROR: TypeError: non-boolean (BitArray{1}) used in boolean context Stacktrace: [1] model1(::Array{Int64,1}, ::Array{Float64,1}) at .\REPL[184]:1 [2] top-level scope at none:0 Many thanks in advance f…
> [@\[ANN\] JSON3.jl - Yet another JSON package for Julia](https://discourse.julialang.org/t/ann-json3-jl-yet-another-json-package-for-julia/25625/6):
>
> Nice, in that case the only thing I’d have done differently would be to have it fail more for other types.