# LoadError: MethodError: no method matching (::Colon)(::Int64, ::Nothing)

**URL:** <https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052>\
**Category:** General Usage\
**Created:** [April 14, 2025, 8:37am UTC](https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052 "2025-04-14T08:37:41Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![Efstein](https://avatars.discourse-cdn.com/v4/letter/e/c67d28/32.png) [@Efstein](https://discourse.julialang.org/u/Efstein)\
**Post date:** [April 14, 2025, 8:37am UTC](https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052/1 "2025-04-14T08:37:41Z")

</div>

Hi Everbody!

I’m still quite new to Julia, so I hope I am not missing something obvious here…  
My task is to solve numerically a system of equations, my working example looks like this:

```julia
using Optimization, Zygote, Symbolics
using ForwardDiff

function getChemicalPotential(id::Int, T)
    n = ["C(gr)", "H2O", "CH4", "N2", "C2H6", "NH3", "H2", "CO", "CO2", "CH2O2", "C2H4", "C(d)", "HCN"]
    c_vector = [
        [-5214.9, 13.037, 0.0051, -8.4343e-7, 5.5694e-11, -74.387],
        [-9156, 27.216, 0.0091186, -1.2446e-6, 6.847e-11, 28.25],
        [-11271, 25.806, 0.02905, -4.7955e-6, 2.9592e-10, 18.67],
        [-8463.6, 26.815, 0.0037938, -6.0948e-7, 3.751e-11, 36.65],
        [-17885, 42.55, 0.049247, -8.008e-6, 4.7591e-10, -41.251],
        [-9535.2, 26.177, 0.019086, -2.9443e-6, 1.6862e-10, 32.5247],
        [-7865.8, 26.239, 0.0023634, -1.3255e-7, 1.72229e-12, -20.3209],
        [-9086.50436189, 29.0370119629, 0.00245170237304, -2.91117727464e-7, 1.29678792586e-11, 29.8419],
        [-13381, 43.301, 0.005694, -6.7725e-7, 3.0335e-11, -38.8709],
        [-17807, 48.381, 0.024825, -4.561e-6, 3.0382e-10, -40.997],
        [-14897, 37.224, 0.035119, -5.9621e-6, 3.7559e-10, -13.0221],
        [-4832, 10.818, 0.0067481, -1.1898e-6, 7.6844e-11, -66.141],
        [-10962, 33.517, 0.010353, -1.6675e-6, 1.0168e-10, 4.7979],
    ]
    Hf0_vector = [20.1, -241.826, -74.873, 0.0, -84.6576, -45.898, 0.0, -110.529, -393.522, -378.561, 52.467, 28.2, 135.143]
    c = c_vector[id]
    Hf0 = Hf0_vector[id]
    mu = c[1] - c[6]*T - c[2]*T*log(T-1) - c[3]*T^2 - c[4]*T^(3/2) - c[5]*T^(4/3) + Hf0
    return mu
end

function minimizationFunction(x::AbstractVector{Tx}, b::AbstractVector{Tb}) where {Tx, Tb}
    α = 0.5
    β = 0.38
    ε = 1.0
    θ = 4350
    κ = 9.23
    R = 8.314
    p = x[end-2]
    t = x[end-1]
    V = x[end]
    mu_over_RT = [getChemicalPotential(i, t)/ R / t for i in 1:13] 
    xtot = sum(x[1:end-3])
    funcs = [mu_over_RT[i] + log(x[i]/xtot) + 1 - x[i]/xtot for i in 1:13]

    # BKW equation
    kovolumes = [0.0, 246.0, 479.0, 392.0, 832.0, 405.0, 110.0, 390.0, 590.0, 663.0, 700.0, 0.0, 510.0]
    xBKW = κ*sum([x[i]*kovolumes[i] for i in 1:13])/(xtot*V * (t + θ)^α)
    BKW = p*V/R/t - 1 - xBKW * exp(β*xBKW)
    append!(funcs, BKW)
    func = sum(abs.(funcs))	
    return func
end

function solve_equilibrium(b::Vector{Float64})
    x0 = [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1e5, 1000.0, 1.0]
    lower_bounds = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
    upper_bounds = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1e10, 20000.0, 1000.0]
    lower_constr = [0.0, 0.0, 0.0, 0.0]
    upper_constr = [0.0, 0.0, 0.0, 0.0]
    alphas = [1.0 0.0 0.0 0.0
                0.0 2.0 1.0 0.0
                1.0 4.0 0.0 0.0
                0.0 0.0 0.0 2.0
                2.0 6.0 0.0 0.0
                0.0 3.0 0.0 1.0
                0.0 2.0 0.0 0.0
                1.0 0.0 1.0 0.0
                1.0 0.0 2.0 0.0
                1.0 2.0 2.0 0.0
                2.0 4.0 0.0 0.0
                1.0 0.0 0.0 0.0
                1.0 1.0 0.0 1.0
                0.0 0.0 0.0 0.0
                0.0 0.0 0.0 0.0
                0.0 0.0 0.0 0.0]

    constraint(res, x, b) = (res .= (alphas' * x) - b)
    objective = OptimizationFunction(minimizationFunction, Optimization.AutoForwardDiff(), cons=constraint)
    opt_problem = OptimizationProblem(objective, x0, b, lb=lower_bounds, ub=upper_bounds, lcons=lower_constr, ucons=upper_constr)
    result = solve(opt_problem, Optimization.LBFGS())
end

# C, H, O, N
b = [5.972, 9.317, 1.917, 1.862]
solution = solve_equilibrium(b)

println("Solution vector (x):")
println(solution)

```

But now, I get the following error:

```julia
LoadError: MethodError: no method matching (::Colon)(::Int64, ::Nothing)
The function `Colon()` exists, but no method is defined for this combination of argument types.

Closest candidates are:
  (::Colon)(::T, ::Any, ::T) where T<:Real
   @ Base range.jl:50
  (::Colon)(::A, ::Any, ::C) where {A<:Real, C<:Real}
   @ Base range.jl:10
  (::Colon)(::T, ::Any, ::T) where T
   @ Base range.jl:49
  ...

```

I think the problem is my constraint definition, as I don’t get the error if I leave it out, but I can’t figure out why. Can anybody help me?

Thanks in advance!

---

<div class="post-metadata">

**Author:** ![Sukera](https://avatars.discourse-cdn.com/v4/letter/s/ce7236/32.png) [@Sukera](https://discourse.julialang.org/u/Sukera)\
**Post date:** [April 14, 2025, 8:49am UTC](https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052/2 "2025-04-14T08:49:16Z")

</div>

Hi! The error message you posted is not enough to narrow down where the error occurs, could you post the full stacktrace that follows after it?

---

<div class="post-metadata">

**Author:** ![Efstein](https://avatars.discourse-cdn.com/v4/letter/e/c67d28/32.png) [@Efstein](https://discourse.julialang.org/u/Efstein)\
**Post date:** [April 14, 2025, 8:56am UTC](https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052/3 "2025-04-14T08:56:54Z")

</div>

Hi, and thank you for your fast response!  
Sure, the full Stack trace looks like this:

```julia

Stacktrace:
 [1] __solve(cache::OptimizationCache{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), OptimizationBase.var"#grad#16"{Vector{Float64}, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoForwardDiff{nothing, Nothing}}, Nothing, Nothing, Nothing, Nothing, OptimizationBase.var"#9#26"{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}}, OptimizationBase.var"#cons_j!#29"{AutoForwardDiff{nothing, Nothing}, DifferentiationInterfaceForwardDiffExt.ForwardDiffOneArgJacobianPrep{ForwardDiff.JacobianConfig{ForwardDiff.Tag{OptimizationBase.var"#cons_oop#27"{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, Int64}, Float64}, Float64, 8, Vector{ForwardDiff.Dual{ForwardDiff.Tag{OptimizationBase.var"#cons_oop#27"{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, 
Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, Int64}, Float64}, Float64, 8}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OptimizationBase.ReInitCache{Vector{Float64}, Vector{Float64}}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Nothing, Optimization.LBFGS, Bool, OptimizationBase.NullCallback, Nothing})
   @ Optimization C:\Users\flo\.julia\packages\Optimization\PnmC0\src\lbfgsb.jl:176
 [2] solve!(cache::OptimizationCache{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), OptimizationBase.var"#grad#16"{Vector{Float64}, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, 
Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoForwardDiff{nothing, Nothing}}, Nothing, Nothing, Nothing, Nothing, OptimizationBase.var"#9#26"{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}}, OptimizationBase.var"#cons_j!#29"{AutoForwardDiff{nothing, Nothing}, DifferentiationInterfaceForwardDiffExt.ForwardDiffOneArgJacobianPrep{ForwardDiff.JacobianConfig{ForwardDiff.Tag{OptimizationBase.var"#cons_oop#27"{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, Int64}, Float64}, Float64, 8, Vector{ForwardDiff.Dual{ForwardDiff.Tag{OptimizationBase.var"#cons_oop#27"{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, Int64}, Float64}, Float64, 8}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OptimizationBase.ReInitCache{Vector{Float64}, Vector{Float64}}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Nothing, Optimization.LBFGS, Bool, OptimizationBase.NullCallback, Nothing})
   @ SciMLBase C:\Users\flo\.julia\packages\SciMLBase\dJpGC\src\solve.jl:187
 [3] solve(::OptimizationProblem{true, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, typeof(minimizationFunction), Nothing, Nothing, Nothing, Nothing, Nothing, var"#constraint#12"{Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Nothing, Vector{Float64}, Vector{Float64}, Nothing, @Kwargs{}}, ::Optimization.LBFGS; kwargs::@Kwargs{})
   @ SciMLBase C:\Users\flo\.julia\packages\SciMLBase\dJpGC\src\solve.jl:95
 [4] solve
   @ C:\Users\flo\.julia\packages\SciMLBase\dJpGC\src\solve.jl:92 [inlined]
 [5] solve_equilibrium(b::Vector{Float64})
   @ Main C:\Users\flo\Documents\Julia\waveEquation\numericalSolution_NLsolve.jl:76
 [6] top-level scope
   @ C:\Users\flo\Documents\Julia\waveEquation\numericalSolution_NLsolve.jl:81

```

---

<div class="post-metadata">

**Author:** ![eldee](https://avatars.discourse-cdn.com/v4/letter/e/b5a626/32.png) [@eldee](https://discourse.julialang.org/u/eldee)\
**Post date:** [April 14, 2025, 12:26pm UTC](https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052/4 "2025-04-14T12:26:00Z")

</div>

The issue is that in `lbfgsb.jl`’s

```julia
function SciMLBase.__solve(cache::OptimizationCache{...}) where {...}
    ...
    maxiters = Optimization._check_and_convert_maxiters(cache.solver_args.maxiters)
    ...
    for i in 1:maxiters
        ...
    end
end

```

`maxiters` is set to `nothing` (which is also `cache.solver_args.maxiters`). The range in the for loop then becomes `1:nothing` (a.k.a. `Colon()(1, nothing)`), which is not defined.

I’m not familiar enough with Optimization.jl to be certain, but this sounds like a bug to me, so you might want to open an issue on GitHub. In any case, if you explicitly supply the keyword argument `maxiters` to `solve`, the code does run.

```julia-repl
julia> solve(opt_problem, Optimization.LBFGS(), maxiters=1000)
retcode: MaxIters
u: 16-element Vector{Float64}:
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
      0.5
 100000.0
   1000.0
      1.0

```

---

<div class="post-metadata">

**Author:** ![Efstein](https://avatars.discourse-cdn.com/v4/letter/e/c67d28/32.png) [@Efstein](https://discourse.julialang.org/u/Efstein)\
**Post date:** [April 14, 2025, 1:18pm UTC](https://discourse.julialang.org/t/loaderror-methoderror-no-method-matching-colon-int64-nothing/128052/5 "2025-04-14T13:18:22Z")

</div>

Ahh, that makes sense! When using maxiters in my Code, it also works.  
Thank you ver much for your help, guys!