devmotion

# This file is machine-generated - editing it directly is not advised

julia_version = "1.9.1"
manifest_format = "2.0"
project_hash = "65efc28519b1ed70299db030b3148e218b921e6a"

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git-tree-sha1 = "dcfdf328328f2645531c4ddebf841228aef74130"
uuid = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
version = "0.1.3"

devmotion

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devmotion

/*
* One-pass algorithm of `log_sum_exp`.
*/
function log_sum_exp_onepass(x:Real[_]) -> Real {
  if length(x) > 0 {
    let (mx, r) <- transform_reduce(x, (-inf, 0.0), 
        \(x:(Real, Real), y:(Real, Real)) -> {
          let (xa, xb) <- x;
          let (ya, yb) <- y;
          if xa > ya {

devmotion

┌ Warning: dt(2.220446049250313e-16) <= dtmin(2.220446049250313e-16) at t=4.2228999661198057e-16. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /home/david/.julia/packages/SciMLBase/koNdH/src/integrator_interface.jl:366
Sampling 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| Time: 0:00:09
ERROR: DimensionMismatch("arrays could not be broadcast to a common size; got a dimension with lengths 120 and 6120")
Stacktrace:
  [1] _bcs1
    @ ./broadcast.jl:516 [inlined]
  [2] _bcs
    @ ./broadcast.jl:510 [inlined]
  [3] broadcast_shape

devmotion

using AdvancedMH
using ArraysOfArrays
using CairoMakie
using DiffEqNoiseProcess
using Distributions
using StochasticDiffEq
using Turing
using Random

struct CrankNicolsonProposal{P,T} <: AdvancedMH.Proposal{P}

devmotion

julia> using DynamicPPL

julia> @model function demo4(n, ::Type{TV}=Vector{Float64}) where {TV}
           m ~ Normal()
           x = TV(undef, n)
           @show __varinfo__
           for i in eachindex(x)
               x[i] ~ Normal(m, 1.0)
           end
       end

devmotion

using BenchmarkTools
using Distances
using Distributions
using StatsBase

using LinearAlgebra
using SparseArrays

function f(
    c, μ::DiscreteNonParametric, ν::DiscreteNonParametric, plan::SparseMatrixCSC

devmotion

using Distributions
using SparseArrays
using LinearAlgebra
using StatsBase

function _ot_cost_plan(c, μ::DiscreteNonParametric, ν::DiscreteNonParametric; get=:plan)
    len_μ = length(μ.p)
    len_ν = length(ν.p)
    wi = μ.p[1]
    wj = ν.p[1]

devmotion

devmotion

using Turing
using Turing.RandomMeasures

using Random

function stickbreaking(rpm = DirichletProcess(0.25))
    # Data
    data = [-2,2,-1.5,1.5]

    # Base distribution