# Sampling from custom distribution: "No method matching iterate..."

**URL:** <https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925>\
**Category:** Probabilistic Programming\
**Tags:** turing, distributions\
**Created:** [October 29, 2024, 3:33pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925 "2024-10-29T15:33:18Z")\
**Posts on this page:** 6\
**Page:** 1

<div class="post-metadata">

**Author:** ![alexdmeyer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alexdmeyer/32/29605_2.png) [@alexdmeyer](https://discourse.julialang.org/u/alexdmeyer)\
**Post date:** [October 29, 2024, 3:33pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925/1 "2024-10-29T15:33:18Z")

</div>

Hello fellow Julians,

I’m trying to use a custom distribution/sampleable for inference in Turing.jl, and I’ve encountered a problem I can’t solve. Following the [instructions on the Turing docs](https://turinglang.org/docs/tutorials/usage-custom-distribution/), I made the following minimal working example – a uniform distribution on [0,L]:

```julia
    struct MyUniformDist <: ContinuousUnivariateDistribution
        L::Real
    end
    Distributions.logpdf(d::MyUniformDist, x::Real) = 0 ≤ x ≤ d.L ? log(1/d.L) : -Inf
    Distributions.rand(rng::AbstractRNG, d::MyUniformDist) = rand(rng) * d.L
    Distributions.minimum(d::MyUniformDist) = 0.
    Distributions.maximum(d::MyUniformDist) = d.L

```

I try to sample from it,

```julia
foo = MyUniformDist(3)
rand(foo)

```

and get the following error:

```julia
ERROR: MethodError: no method matching iterate(::MyUniformDist)

Closest candidates are:
  iterate(::LLVM.StructTypeElementSet)
   @ LLVM ~/.julia/packages/LLVM/bzSzE/src/core/type.jl:246
  iterate(::LLVM.StructTypeElementSet, ::Any)
   @ LLVM ~/.julia/packages/LLVM/bzSzE/src/core/type.jl:246
  iterate(::CSV.Chunks)
   @ CSV ~/.julia/packages/CSV/XLcqT/src/chunks.jl:91
  ...

Stacktrace:
 [1] copyto!(dest::Vector{Float64}, src::MyUniformDist)
   @ Base ./abstractarray.jl:943
 [2] _collect(cont::UnitRange{Int64}, itr::MyUniformDist, ::Base.HasEltype, isz::Base.HasLength)
   @ Base ./array.jl:765
 [3] collect(itr::MyUniformDist)
   @ Base ./array.jl:759
 [4] quantile(itr::MyUniformDist, p::Float64; sorted::Bool, alpha::Float64, beta::Float64)
   @ Statistics /Applications/Julia-1.10.app/Contents/Resources/julia/share/julia/stdlib/v1.10/Statistics/src/Statistics.jl:1086
 [5] rand(rng::Random.TaskLocalRNG, d::MyUniformDist)
   @ Distributions ~/.julia/packages/Distributions/uuqsE/src/univariates.jl:157
 [6] rand(::MyUniformDist)
   @ Distributions ~/.julia/packages/Distributions/uuqsE/src/genericrand.jl:22
 [7] top-level scope
   @ ~/path/to/my/file.jl:268

```

Can anyone give me some insight into what’s going on?

Thanks so much,

Alex M

Edit: fixed some remnants of my actual use-case in the MWE, but the problem remains the same.

---

<div class="post-metadata">

**Author:** ![alexdmeyer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alexdmeyer/32/29605_2.png) [@alexdmeyer](https://discourse.julialang.org/u/alexdmeyer)\
**Post date:** [October 29, 2024, 3:35pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925/2 "2024-10-29T15:35:33Z")

</div>

P.S. Here’s the output of `]st` (I have a lot of packages that I don’t use anymore):

```julia
[cbdf2221] AlgebraOfGraphics v0.8.13
  [c9ce4bd3] ArchGDAL v0.10.4
  [6e4b80f9] BenchmarkTools v1.5.0
  [024491cd] BetaML v0.12.1
  [e2ed5e7c] Bijections v0.1.9
  [a134a8b2] BlackBoxOptim v0.6.3
  [336ed68f] CSV v0.10.15
  [13f3f980] CairoMakie v0.12.15
  [e2e10f9a] CatBoost v0.3.5
  [aaaa29a8] Clustering v0.15.7
  [35d6a980] ColorSchemes v3.27.0
⌅ [5ae59095] Colors v0.12.11
  [861a8166] Combinatorics v1.0.2
  [7d11a335] ConcaveHull v1.1.0
⌅ [ae264745] Copulas v0.1.13
⌃ [a93c6f00] DataFrames v1.6.1
  [864edb3b] DataStructures v0.18.20
  [7806a523] DecisionTree v0.12.4
  [8bb1440f] DelimitedFiles v1.9.1
  [39dd38d3] Dierckx v0.5.3
⌃ [c894b116] DiffEqJump v8.6.2
⌃ [0c46a032] DifferentialEquations v7.11.0
  [b4f34e82] Distances v0.10.12
  [31c24e10] Distributions v0.25.112
  [ab853011] EvoLinear v0.4.3
  [f6006082] EvoTrees v0.16.7
⌃ [587475ba] Flux v0.14.21
  [f6369f11] ForwardDiff v0.10.36
  [38e38edf] GLM v1.9.0
  [2fb1d81b] GeoArrays v0.9.0
  [61d90e0f] GeoJSON v0.8.1
  [523d8e89] Gillespie v0.1.0 `https://github.com/sdwfrost/Gillespie.jl#master`
⌃ [af5da776] GlobalSensitivity v2.4.0
  [7073ff75] IJulia v1.25.0
  [a98d9a8b] Interpolations v0.15.1
  [3587e190] InverseFunctions v0.1.17
  [c3a54625] JET v0.9.12
⌅ [033835bb] JLD2 v0.4.53
  [9da8a3cd] JLSO v2.7.0
⌃ [ccbc3e58] JumpProcesses v9.10.1
  [5ab0869b] KernelDensity v0.6.9
  [23b0397c] KissSmoothing v1.0.8
  [b1bec4e5] LIBSVM v0.8.1
  [984bce1d] LambertW v1.0.0
  [a5e1c1ea] LatinHypercubeSampling v1.9.0
  [b4f0291d] LazySets v2.14.2
  [d3d80556] LineSearches v7.3.0
  [bdcacae8] LoopVectorization v0.12.171
  [f0e99cf1] MLBase v0.9.2
  [add582a8] MLJ v0.20.7
  [a7f614a8] MLJBase v1.7.0
  [c6f25543] MLJDecisionTreeInterface v0.4.2
  [094fc8d1] MLJFlux v0.6.0
  [caf8df21] MLJGLMInterface v0.3.7
  [61c7150f] MLJLIBSVMInterface v0.2.1
  [6ee0df7b] MLJLinearModels v0.10.0
  [1b6a4a23] MLJMultivariateStatsInterface v0.5.3
  [5ae90465] MLJScikitLearnInterface v0.7.0
  [54119dfa] MLJXGBoostInterface v0.3.11
  [ff71e718] MixedModels v4.26.1
  [af6c499f] MutableNamedTuples v0.1.3
  [2774e3e8] NLsolve v4.5.1
  [77ba4419] NaNMath v1.0.2
  [636a865e] NearestNeighborModels v0.2.3
  [b8a86587] NearestNeighbors v0.4.20
  [429524aa] Optim v1.9.4
  [90014a1f] PDMats v0.11.31
  [2c7acb1b] PDMatsExtras v2.8.0
  [9b87118b] PackageCompiler v2.1.21
  [c3e4b0f8] Pluto v0.20.1
  [7f904dfe] PlutoUI v0.7.60
  [e409e4f3] PoissonRandom v0.4.4
  [647866c9] PolygonOps v0.1.2
  [67491407] Polyhedra v0.7.8
  [27ebfcd6] Primes v0.5.6
  [92933f4c] ProgressMeter v1.10.2
  [1fd47b50] QuadGK v2.11.1
  [8a4e6c94] QuasiMonteCarlo v0.3.3
  [6f49c342] RCall v0.14.6
  [e6cf234a] RandomNumbers v1.6.0
  [a3a2b9e3] Rasters v0.12.0
  [f2b01f46] Roots v2.2.1
  [cdeec39e] SIRUS v2.0.1
  [8e980c4a] Shapefile v0.13.1
  [05bca326] SimpleDiffEq v1.11.1
  [276daf66] SpecialFunctions v2.4.0
  [860ef19b] StableRNGs v1.0.2
  [90137ffa] StaticArrays v1.9.8
  [2913bbd2] StatsBase v0.34.3
  [f3b207a7] StatsPlots v0.15.7
  [fd094767] Suppressor v0.2.8
  [bd369af6] Tables v1.12.0
⌃ [fce5fe82] Turing v0.34.1
  [009559a3] XGBoost v2.5.1
  [37e2e46d] LinearAlgebra
  [9a3f8284] Random
  [2f01184e] SparseArrays v1.10.0

```

---

<div class="post-metadata">

**Author:** ![alexdmeyer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alexdmeyer/32/29605_2.png) [@alexdmeyer](https://discourse.julialang.org/u/alexdmeyer)\
**Post date:** [October 29, 2024, 7:25pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925/3 "2024-10-29T19:25:08Z")

</div>

I fixed it. The problem was something to do with conflicting methods for `rand` in the Random and RandomNumbers packages.

I guess that’s a real reason to clean up my package environment after all.

---

<div class="post-metadata">

**Author:** ![Christopher\_Fisher](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/christopher_fisher/32/26132_2.png) [@Christopher\_Fisher](https://discourse.julialang.org/u/Christopher_Fisher)\
**Post date:** [October 29, 2024, 7:25pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925/4 "2024-10-29T19:25:23Z")

</div>

> [@alexdmeyer](#):
>
> `rand(rng::AbstractRNG, d::MyUniformDist) = rand(rng) * d.L`

The main problem is that you need to import the methods, including `rand` in order to extend them. Try the following:

```julia
using Distributions 
import Distributions: logpdf, rand, maximum, minimum
using Random 

struct MyUniformDist <: ContinuousUnivariateDistribution
    L::Real
end
logpdf(d::MyUniformDist, x::Real) = 0 ≤ x ≤ d.L ? log(1/d.L) : -Inf
rand(rng::AbstractRNG, d::MyUniformDist) = rand(rng) * d.L
minimum(d::MyUniformDist) = 0.
maximum(d::MyUniformDist) = d.L

foo = MyUniformDist(3)
rand(foo)

```

---

<div class="post-metadata">

**Author:** ![Christopher\_Fisher](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/christopher_fisher/32/26132_2.png) [@Christopher\_Fisher](https://discourse.julialang.org/u/Christopher_Fisher)\
**Post date:** [October 29, 2024, 7:28pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925/5 "2024-10-29T19:28:16Z")

</div>

And you are right about `using Random`. That must be available for `AbstractRNG`. You do not need to import `rand` if you use `Distributions.rand`.

---

<div class="post-metadata">

**Author:** ![alexdmeyer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alexdmeyer/32/29605_2.png) [@alexdmeyer](https://discourse.julialang.org/u/alexdmeyer)\
**Post date:** [October 29, 2024, 10:24pm UTC](https://discourse.julialang.org/t/sampling-from-custom-distribution-no-method-matching-iterate/121925/6 "2024-10-29T22:24:10Z")

</div>

Thanks so much @Christopher_Fisher for clarifying that & making it useful to future readers! I appreciate it.