verification.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SHGF Forney-Style Factor Graph\n",
    "<img src=\"figures/SHGF-FFG.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Retrieve research results (verification)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To inspect the reported research results you must install the following julia packages:\n",
    "**JLD**, **PGFPlotsX**, **Plots**, **LaTeXStrings**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notational conventions: prefixes **m** and **v** denote mean and variance of the random variables respectively.\n",
    "\n",
    "For a sake of brevity, throughout the code we use $x$ and $z$ instead of $x^{(1)}$ and $x^{(2)}$ respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "using JLD\n",
    "using SparseArrays\n",
    "\n",
    "rfilename = \"dump/results_verification_analytic_mixture.jld\"\n",
    "resultsJLD = JLD.load(rfilename)\n",
    "results = resultsJLD[\"results\"];\n",
    "datasetJLD = JLD.load(\"dump/dataset_test.jld\")\n",
    "dataset = datasetJLD[\"dataset\"];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_datasets = length(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = 4\n",
    "\n",
    "mz, vz, mx, vx, ms, mω, vω,fe = results[index][\"mz\"], results[index][\"vz\"], results[index][\"mx\"], results[index][\"vx\"], results[index][\"ms\"], results[index][\"mω\"], results[index][\"vω\"], results[index][\"fe\"]\n",
    "reals = dataset[index][\"reals\"]\n",
    "obs = dataset[index][\"obs\"]\n",
    "upper_rw = dataset[index][\"rw\"]\n",
    "switches = dataset[index][\"switches\"]\n",
    "omegas = dataset[index][\"ωs\"]\n",
    "n_samples = length(obs);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "using PGFPlotsX, Plots\n",
    "using LaTeXStrings\n",
    "\n",
    "pgfplotsx()\n",
    "push!(PGFPlotsX.CUSTOM_PREAMBLE, raw\"\\usepgfplotslibrary{fillbetween}\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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       "\n"
      ],
      "text/plain": [
       "Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(\"xlabel\" => L\"$t$\", \"ylabel\" => L\"$x_t^{(1)}$\", \"legend_pos\" => \"south east\", \"grid\" => \"major\", \"title\" => \"Dataset 4\"), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(\"only_marks\" => nothing, \"scatter\" => nothing, \"scatter_src\" => \"explicit\"), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(\"x\" => \"x\", \"y\" => \"y\", \"meta\" => \"col\"), true), TableData([1.0 -219.26842087962962 1.0; 2.0 -219.26842087962962 1.0; … ; 99.0 -219.26842087962962 2.0; 100.0 -219.26842087962962 2.0], [\"x\", \"y\", \"col\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(\"only_marks\" => nothing, \"scatter\" => nothing, \"scatter_src\" => \"explicit\"), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(\"x\" => \"x\", \"y\" => \"y\", \"meta\" => \"col\"), true), TableData([1.0 0.061047864237217433 1.0; 2.0 0.07147757906201893 1.0; … ; 99.0 -164.25339741371744 2.0; 100.0 -169.26842087962962 2.0], [\"x\", \"y\", \"col\"], Int64[], true)), Any[])])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categories = [x[2] for x in findmax.(ms)]\n",
    "maxup = maximum(obs) + 3.0\n",
    "mindown = minimum(obs) - 50.0\n",
    "\n",
    "axis1 = @pgf Axis({xlabel=L\"t\",\n",
    "           ylabel=L\"x_t^{(1)}\",\n",
    "        legend_pos = \"south east\",\n",
    "        grid = \"major\",\n",
    "        title=\"Dataset $(index)\",\n",
    "    },\n",
    "    Plot(\n",
    "        {only_marks, scatter, scatter_src = \"explicit\"},\n",
    "        Table(\n",
    "            {x = \"x\", y = \"y\", meta = \"col\"},\n",
    "             x = collect(1:n_samples), y = mindown*ones(n_samples), col = categories\n",
    "        ),\n",
    "    ),\n",
    "    Plot(\n",
    "        {only_marks,scatter,scatter_src = \"explicit\"},\n",
    "        Table(\n",
    "            {x = \"x\", y = \"y\", meta = \"col\"},\n",
    "             x = collect(1:n_samples), y = obs, col = switches\n",
    "        ),\n",
    "    ),\n",
    ")\n",
    "\n",
    "# pgfsave(\"figures/verification_results_mixture_recovered_switches.pdf\", axis1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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       "</g>\n",
       "</g>\n",
       "</svg>\n",
       "\n"
      ],
      "text/plain": [
       "Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(\"xlabel\" => \"iteration\", \"ylabel\" => \"free-enery [nats]\", \"legend_pos\" => \"north east\", \"grid\" => \"major\"), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any, Any}(), false), Coordinates{2}(Union{Nothing, Coordinate{2}}[Coordinate{2}((1, 0.960441598963926), nothing, nothing, nothing, nothing), Coordinate{2}((2, 0.8818453526584044), nothing, nothing, nothing, nothing), Coordinate{2}((3, 0.846260586921977), nothing, nothing, nothing, nothing), Coordinate{2}((4, 0.823802883193902), nothing, nothing, nothing, nothing), Coordinate{2}((5, 0.8090020703446062), nothing, nothing, nothing, nothing), Coordinate{2}((6, 0.7987441465527069), nothing, nothing, nothing, nothing), Coordinate{2}((7, 0.791333273998431), nothing, nothing, nothing, nothing), Coordinate{2}((8, 0.7857225640757014), nothing, nothing, nothing, nothing), Coordinate{2}((9, 0.7807115523685245), nothing, nothing, nothing, nothing), Coordinate{2}((10, 0.7766651507865088), nothing, nothing, nothing, nothing)  …  Coordinate{2}((50, 0.7604884150869567), nothing, nothing, nothing, nothing), Coordinate{2}((51, 0.7604680943414002), nothing, nothing, nothing, nothing), Coordinate{2}((52, 0.7604465250869634), nothing, nothing, nothing, nothing), Coordinate{2}((53, 0.7604196148461054), nothing, nothing, nothing, nothing), Coordinate{2}((54, 0.760388766574164), nothing, nothing, nothing, nothing), Coordinate{2}((55, 0.7603686402463683), nothing, nothing, nothing, nothing), Coordinate{2}((56, 0.7603454322870021), nothing, nothing, nothing, nothing), Coordinate{2}((57, 0.7603286812690009), nothing, nothing, nothing, nothing), Coordinate{2}((58, 0.7603024203640537), nothing, nothing, nothing, nothing), Coordinate{2}((59, 0.7602857299577667), nothing, nothing, nothing, nothing)]), Any[])])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FE = zeros(100)\n",
    "for i in 1:n_datasets\n",
    "    fe = results[i][\"fe\"] ./ n_samples\n",
    "    FE += fe\n",
    "end\n",
    "FE ./= (n_datasets)\n",
    "\n",
    "\n",
    "axis2 = @pgf Axis({xlabel=L\"t\",\n",
    "           ylabel=L\"x_t^{(2)}\",\n",
    "        legend_pos = \"north east\",\n",
    "    },\n",
    "    Plot({no_marks,color=\"blue\"},Coordinates(collect(1:n_samples), mz)),\n",
    "    LegendEntry(\"estimate\"),\n",
    "    Plot({ \"name path=f\", no_marks,color=\"blue\",opacity=0.2 }, Coordinates(collect(1:n_samples), mz .+  sqrt.(vz))),\n",
    "    Plot({ \"name path=g\", no_marks, color=\"blue\",opacity=0.2}, Coordinates(collect(1:n_samples), mz .-  sqrt.(vz))),\n",
    "    Plot({ thick, color = \"blue\", fill = \"blue\", opacity = 0.2 },\n",
    "               raw\"fill between [of=f and g]\"),\n",
    "\n",
    "    Plot({no_marks,color=\"green\"},Coordinates(collect(1:n_samples), upper_rw)),\n",
    "    LegendEntry(\"ground truth\"),\n",
    ")\n",
    "pgfsave(\"figures/verification_results_mixture_recovered_upper_layer.tikz\", axis2)\n",
    "\n",
    "axis3 = @pgf Axis({xlabel=\"iteration\",\n",
    "           ylabel=\"free-enery [nats]\",\n",
    "        legend_pos = \"north east\",\n",
    "        grid = \"major\",\n",
    "    },\n",
    "    Plot(Coordinates(collect(1:59),FE[2:60]))\n",
    ")\n",
    "# pgfsave(\"figures/verification_results_mixture_free_energy.pdf\", axis3)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Root Mean Squared Error "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.08565819645617266"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using StatsBase\n",
    "sum([rmsd(results[i][\"mω\"], Float64.(dataset[i][\"ωs\"]), normalize=true) for i in 1:n_datasets])/n_datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Implemetation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run the inference, the following packages must be installed:\n",
    "**ForneyLab**, **GCV**, **ProgressMeter**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Revise\n",
    "using ForneyLab\n",
    "include(\"sgcv/SGCV.jl\")\n",
    "using Main.SGCV\n",
    "include(\"gcv/GCV.jl\")\n",
    "using Main.GCV\n",
    "include(\"compatibility.jl\") # resolves compatibility issues with ForneyLab\n",
    "using SparseArrays\n",
    "using ProgressMeter;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pad (generic function with 1 method)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Auxialry function for graph initializtion\n",
    "pad(sym::Symbol, t::Int) = sym*:_*Symbol(lpad(t,3,'0')) # Left-pads a number with zeros, converts it to symbol and appends to sym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "generate_mp (generic function with 1 method)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Function for generating graph and message-passing (MP) algorithm\n",
    "function generate_mp(ndim, n_samples)\n",
    "    # Initialize FFG\n",
    "    fg = FactorGraph()\n",
    "    z = Vector{Variable}(undef, n_samples)\n",
    "    x = Vector{Variable}(undef, n_samples)\n",
    "    y = Vector{Variable}(undef, n_samples)\n",
    "    s = Vector{Variable}(undef, n_samples)\n",
    "    @RV A ~ Dirichlet(ones(ndim, ndim))\n",
    "    @RV ω ~ GaussianMeanPrecision(placeholder(:mω, dims=(ndim, )), placeholder(:wω, dims=(ndim, ndim)))\n",
    "    @RV [id=pad(:z,1)] z[1] ~ GaussianMeanPrecision(placeholder(:mz_prior1), placeholder(:wz_prior1))\n",
    "    @RV [id=pad(:x,1)] x[1] ~ GaussianMeanPrecision(placeholder(:mx_prior1), placeholder(:wx_prior1))\n",
    "    @RV [id=pad(:y,1)] y[1] ~ GaussianMeanPrecision(x[1], placeholder(:wy_prior1))\n",
    "    @RV [id=pad(:s,1)] s[1] ~ ForneyLab.Categorical(ones(ndim) ./ ndim)\n",
    "    placeholder(y[1], :y, index = 1)\n",
    "    for t in 2:n_samples\n",
    "        @RV [id=pad(:s,t)] s[t] ~ Transition(s[t-1], A)\n",
    "        @RV [id=pad(:z,t)] z[t] ~ GaussianMeanPrecision(z[t - 1], placeholder(pad(:wz_transition, t)))\n",
    "        @RV [id=pad(:x,t)] x[t] ~ SwitchingGaussianControlledVariance(x[t - 1], z[t],ones(ndim),ω,s[t])\n",
    "        @RV [id=pad(:y,t)] y[t] ~ GaussianMeanPrecision(x[t], placeholder(pad(:wy_transition, t)))\n",
    "        placeholder(y[t], :y, index = t)\n",
    "    end\n",
    "    # Initialize recognition distribution\n",
    "    q = PosteriorFactorization(x, z ,s, A, ω, ids=[:X :Z :S :A :Ω])\n",
    "    # Create algorithm\n",
    "    algo = messagePassingAlgorithm(free_energy=true)\n",
    "    src_code = algorithmSourceCode(algo, free_energy=true);\n",
    "    return src_code\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mp (generic function with 1 method)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Function for running MP-based inference\n",
    "function mp(obs;\n",
    "    ndims,\n",
    "    n_its = 100,\n",
    "    wy_prior1 = 1.0,\n",
    "    κ_m_prior = ones(ndims),\n",
    "    ω_m_prior = omegas,\n",
    "    κ_w_prior =  huge .* diageye(ndims),\n",
    "    ω_w_prior = 1.0 .* diageye(ndims),\n",
    "    z_m_prior = 0.0,\n",
    "    z_w_prior = 10.0,\n",
    "    x_m_prior = 0.0,\n",
    "    x_w_prior = 1.0,\n",
    "    x_x_m_prior = zeros(ndims),\n",
    "    x_x_w_prior = 1.0*diageye(ndims),\n",
    "    z_z_m_prior = zeros(ndims),\n",
    "    z_z_w_prior = 10.0*diageye(ndims),\n",
    "    z_w_transition_prior = 1000.0,\n",
    "    y_w_transition_prior =  1/mnv,\n",
    ")\n",
    "\n",
    "    # Initialize dictionary to store marginal distributions\n",
    "    marginals = Dict()\n",
    "    marginals[:A] = ProbabilityDistribution(ForneyLab.MatrixVariate, Dirichlet, a=ones(ndims, ndims))\n",
    "    marginals[:κ] = ProbabilityDistribution(ForneyLab.Multivariate, GaussianMeanPrecision, m = κ_m_prior, w = κ_w_prior)\n",
    "    marginals[:ω] = ProbabilityDistribution(ForneyLab.Multivariate, GaussianMeanPrecision, m = ω_m_prior, w = ω_w_prior)\n",
    "    marginals[pad(:z,1)] = vague(GaussianMeanPrecision)\n",
    "    marginals[pad(:x,1)] = vague(GaussianMeanPrecision)\n",
    "    marginals[pad(:s,1)] = vague(Categorical, ndims)\n",
    "    for t = 2:n_samples\n",
    "        marginals[pad(:z,t)] = ProbabilityDistribution(ForneyLab.Univariate, GaussianMeanPrecision, m = z_m_prior, w = z_w_prior)\n",
    "        marginals[pad(:x,t)] = ProbabilityDistribution(ForneyLab.Univariate, GaussianMeanPrecision, m = x_m_prior, w = x_w_prior)\n",
    "        marginals[pad(:s,t)] = ProbabilityDistribution(Categorical, p = ones(ndims) ./ ndims)\n",
    "        marginals[pad(:s,t)*:_*pad(:s,t-1)] = ProbabilityDistribution(Contingency,p=ones(ndims, ndims) ./ ndims)\n",
    "        marginals[pad(:z,t)*:_*pad(:z,t-1)] = ProbabilityDistribution(ForneyLab.Multivariate,GaussianMeanPrecision, m = z_z_m_prior, w = z_z_w_prior)\n",
    "        marginals[pad(:x,t)*:_*pad(:x,t-1)] = ProbabilityDistribution(ForneyLab.Multivariate,GaussianMeanPrecision, m = x_x_m_prior, w = x_x_w_prior)\n",
    "    end\n",
    "    \n",
    "    # Initialize dicitionary to store observations and priors\n",
    "    data = Dict()\n",
    "    data[:y] = obs\n",
    "    data[:mz_prior1] = z_m_prior\n",
    "    data[:wz_prior1] = z_w_prior\n",
    "    data[:mx_prior1] = x_m_prior\n",
    "    data[:wx_prior1] = x_w_prior\n",
    "    data[:wy_prior1] = wy_prior1\n",
    "\n",
    "    data[:mω] = ω_m_prior\n",
    "    data[:wω] = ω_w_prior\n",
    "    for t = 1:n_samples\n",
    "        data[pad(:wz_transition, t)] = z_w_transition_prior\n",
    "        data[pad(:wy_transition, t)] = y_w_transition_prior\n",
    "    end\n",
    "\n",
    "    # Initialize array to store free-energy values\n",
    "    fe = Vector{Float64}(undef, n_its)\n",
    "    \n",
    "    # MP loop\n",
    "    for i = 1:n_its\n",
    "\n",
    "        stepX!(data, marginals)\n",
    "        stepS!(data, marginals)\n",
    "        stepA!(data, marginals)\n",
    "        stepZ!(data, marginals)\n",
    "        stepΩ!(data, marginals)\n",
    "\n",
    "        fe[i] = freeEnergy(data, marginals)\n",
    "    end\n",
    "\n",
    "    # Extract inferred marginals\n",
    "    mz = [ForneyLab.unsafeMean(marginals[pad(:z,t)]) for t=1:n_samples]\n",
    "    vz = [ForneyLab.unsafeVar(marginals[pad(:z,t)]) for t=1:n_samples]\n",
    "    mx = [ForneyLab.unsafeMean(marginals[pad(:x,t)]) for t=1:n_samples]\n",
    "    vx = [ForneyLab.unsafeVar(marginals[pad(:x,t)]) for t=1:n_samples]\n",
    "    ms = [ForneyLab.unsafeMean(marginals[pad(:s,t)]) for t=1:n_samples]\n",
    "    mω = ForneyLab.unsafeMean(marginals[:ω])\n",
    "    vω = ForneyLab.unsafeCov(marginals[:ω])\n",
    "    return mz,vz,mx,vx,ms, mω, vω, fe\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate data (we used 42 as a Random seed)\n",
    "include(\"generator.jl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "begin\n",
      "\n",
      "function stepZ!(data::Dict, marginals::Dict=Dict(), messages::Vector{Message}=Array{Message}(undef, 494); dump::Union{GraphDump, Nothing} = nothing)\n",
      "\n",
      "messages[1] = ruleVBGaussianMeanPrecisionOut(nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:mz_prior1]), ProbabilityDistribution(Univariate, PointMass, m=data[:wz_prior1]))\n",
      "messages[2] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[1], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_002]))\n",
      "messages[3] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_002_x_001], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_002])\n",
      "messages[4] = ruleSPEqualityGaussianGCV(messages[2], messages[3], nothing)\n",
      "messages[5] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[4], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_003]))\n",
      "messages[6] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_003_x_002], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_003])\n",
      "messages[7] = ruleSPEqualityGaussianGCV(messages[5], messages[6], nothing)\n",
      "messages[8] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[7], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_004]))\n",
      "messages[9] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_004_x_003], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_004])\n",
      "messages[10] = ruleSPEqualityGaussianGCV(messages[8], messages[9], nothing)\n",
      "messages[11] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[10], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_005]))\n",
      "messages[12] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_005_x_004], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_005])\n",
      "messages[13] = ruleSPEqualityGaussianGCV(messages[11], messages[12], nothing)\n",
      "messages[14] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[13], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_006]))\n",
      "messages[15] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_006_x_005], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_006])\n",
      "messages[16] = ruleSPEqualityGaussianGCV(messages[14], messages[15], nothing)\n",
      "messages[17] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[16], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_007]))\n",
      "messages[18] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_007_x_006], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_007])\n",
      "messages[19] = ruleSPEqualityGaussianGCV(messages[17], messages[18], nothing)\n",
      "messages[20] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[19], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_008]))\n",
      "messages[21] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_008_x_007], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_008])\n",
      "messages[22] = ruleSPEqualityGaussianGCV(messages[20], messages[21], nothing)\n",
      "messages[23] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[22], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_009]))\n",
      "messages[24] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_009_x_008], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_009])\n",
      "messages[25] = ruleSPEqualityGaussianGCV(messages[23], messages[24], nothing)\n",
      "messages[26] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[25], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_010]))\n",
      "messages[27] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_010_x_009], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_010])\n",
      "messages[28] = ruleSPEqualityGaussianGCV(messages[26], messages[27], nothing)\n",
      "messages[29] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[28], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_011]))\n",
      "messages[30] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_011_x_010], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_011])\n",
      "messages[31] = ruleSPEqualityGaussianGCV(messages[29], messages[30], nothing)\n",
      "messages[32] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[31], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_012]))\n",
      "messages[33] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_012_x_011], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_012])\n",
      "messages[34] = ruleSPEqualityGaussianGCV(messages[32], messages[33], nothing)\n",
      "messages[35] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[34], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_013]))\n",
      "messages[36] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_013_x_012], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_013])\n",
      "messages[37] = ruleSPEqualityGaussianGCV(messages[35], messages[36], nothing)\n",
      "messages[38] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[37], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_014]))\n",
      "messages[39] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_014_x_013], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_014])\n",
      "messages[40] = ruleSPEqualityGaussianGCV(messages[38], messages[39], nothing)\n",
      "messages[41] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[40], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_015]))\n",
      "messages[42] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_015_x_014], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_015])\n",
      "messages[43] = ruleSPEqualityGaussianGCV(messages[41], messages[42], nothing)\n",
      "messages[44] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[43], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_016]))\n",
      "messages[45] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_016_x_015], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_016])\n",
      "messages[46] = ruleSPEqualityGaussianGCV(messages[44], messages[45], nothing)\n",
      "messages[47] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[46], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_017]))\n",
      "messages[48] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_017_x_016], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_017])\n",
      "messages[49] = ruleSPEqualityGaussianGCV(messages[47], messages[48], nothing)\n",
      "messages[50] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[49], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_018]))\n",
      "messages[51] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_018_x_017], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_018])\n",
      "messages[52] = ruleSPEqualityGaussianGCV(messages[50], messages[51], nothing)\n",
      "messages[53] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[52], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_019]))\n",
      "messages[54] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_019_x_018], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_019])\n",
      "messages[55] = ruleSPEqualityGaussianGCV(messages[53], messages[54], nothing)\n",
      "messages[56] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[55], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_020]))\n",
      "messages[57] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_020_x_019], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_020])\n",
      "messages[58] = ruleSPEqualityGaussianGCV(messages[56], messages[57], nothing)\n",
      "messages[59] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[58], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_021]))\n",
      "messages[60] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_021_x_020], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_021])\n",
      "messages[61] = ruleSPEqualityGaussianGCV(messages[59], messages[60], nothing)\n",
      "messages[62] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[61], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_022]))\n",
      "messages[63] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_022_x_021], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_022])\n",
      "messages[64] = ruleSPEqualityGaussianGCV(messages[62], messages[63], nothing)\n",
      "messages[65] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[64], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_023]))\n",
      "messages[66] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_023_x_022], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_023])\n",
      "messages[67] = ruleSPEqualityGaussianGCV(messages[65], messages[66], nothing)\n",
      "messages[68] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[67], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_024]))\n",
      "messages[69] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_024_x_023], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_024])\n",
      "messages[70] = ruleSPEqualityGaussianGCV(messages[68], messages[69], nothing)\n",
      "messages[71] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[70], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_025]))\n",
      "messages[72] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_025_x_024], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_025])\n",
      "messages[73] = ruleSPEqualityGaussianGCV(messages[71], messages[72], nothing)\n",
      "messages[74] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[73], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_026]))\n",
      "messages[75] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_026_x_025], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_026])\n",
      "messages[76] = ruleSPEqualityGaussianGCV(messages[74], messages[75], nothing)\n",
      "messages[77] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[76], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_027]))\n",
      "messages[78] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_027_x_026], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_027])\n",
      "messages[79] = ruleSPEqualityGaussianGCV(messages[77], messages[78], nothing)\n",
      "messages[80] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[79], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_028]))\n",
      "messages[81] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_028_x_027], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_028])\n",
      "messages[82] = ruleSPEqualityGaussianGCV(messages[80], messages[81], nothing)\n",
      "messages[83] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[82], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_029]))\n",
      "messages[84] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_029_x_028], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_029])\n",
      "messages[85] = ruleSPEqualityGaussianGCV(messages[83], messages[84], nothing)\n",
      "messages[86] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[85], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_030]))\n",
      "messages[87] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_030_x_029], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_030])\n",
      "messages[88] = ruleSPEqualityGaussianGCV(messages[86], messages[87], nothing)\n",
      "messages[89] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[88], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_031]))\n",
      "messages[90] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_031_x_030], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_031])\n",
      "messages[91] = ruleSPEqualityGaussianGCV(messages[89], messages[90], nothing)\n",
      "messages[92] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[91], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_032]))\n",
      "messages[93] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_032_x_031], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_032])\n",
      "messages[94] = ruleSPEqualityGaussianGCV(messages[92], messages[93], nothing)\n",
      "messages[95] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[94], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_033]))\n",
      "messages[96] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_033_x_032], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_033])\n",
      "messages[97] = ruleSPEqualityGaussianGCV(messages[95], messages[96], nothing)\n",
      "messages[98] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[97], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_034]))\n",
      "messages[99] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_034_x_033], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_034])\n",
      "messages[100] = ruleSPEqualityGaussianGCV(messages[98], messages[99], nothing)\n",
      "messages[101] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[100], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_035]))\n",
      "messages[102] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_035_x_034], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_035])\n",
      "messages[103] = ruleSPEqualityGaussianGCV(messages[101], messages[102], nothing)\n",
      "messages[104] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[103], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_036]))\n",
      "messages[105] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_036_x_035], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_036])\n",
      "messages[106] = ruleSPEqualityGaussianGCV(messages[104], messages[105], nothing)\n",
      "messages[107] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[106], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_037]))\n",
      "messages[108] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_037_x_036], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_037])\n",
      "messages[109] = ruleSPEqualityGaussianGCV(messages[107], messages[108], nothing)\n",
      "messages[110] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[109], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_038]))\n",
      "messages[111] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_038_x_037], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_038])\n",
      "messages[112] = ruleSPEqualityGaussianGCV(messages[110], messages[111], nothing)\n",
      "messages[113] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[112], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_039]))\n",
      "messages[114] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_039_x_038], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_039])\n",
      "messages[115] = ruleSPEqualityGaussianGCV(messages[113], messages[114], nothing)\n",
      "messages[116] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[115], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_040]))\n",
      "messages[117] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_040_x_039], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_040])\n",
      "messages[118] = ruleSPEqualityGaussianGCV(messages[116], messages[117], nothing)\n",
      "messages[119] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[118], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_041]))\n",
      "messages[120] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_041_x_040], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_041])\n",
      "messages[121] = ruleSPEqualityGaussianGCV(messages[119], messages[120], nothing)\n",
      "messages[122] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[121], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_042]))\n",
      "messages[123] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_042_x_041], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_042])\n",
      "messages[124] = ruleSPEqualityGaussianGCV(messages[122], messages[123], nothing)\n",
      "messages[125] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[124], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_043]))\n",
      "messages[126] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_043_x_042], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_043])\n",
      "messages[127] = ruleSPEqualityGaussianGCV(messages[125], messages[126], nothing)\n",
      "messages[128] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[127], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_044]))\n",
      "messages[129] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_044_x_043], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_044])\n",
      "messages[130] = ruleSPEqualityGaussianGCV(messages[128], messages[129], nothing)\n",
      "messages[131] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[130], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_045]))\n",
      "messages[132] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_045_x_044], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_045])\n",
      "messages[133] = ruleSPEqualityGaussianGCV(messages[131], messages[132], nothing)\n",
      "messages[134] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[133], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_046]))\n",
      "messages[135] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_046_x_045], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_046])\n",
      "messages[136] = ruleSPEqualityGaussianGCV(messages[134], messages[135], nothing)\n",
      "messages[137] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[136], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_047]))\n",
      "messages[138] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_047_x_046], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_047])\n",
      "messages[139] = ruleSPEqualityGaussianGCV(messages[137], messages[138], nothing)\n",
      "messages[140] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[139], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_048]))\n",
      "messages[141] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_048_x_047], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_048])\n",
      "messages[142] = ruleSPEqualityGaussianGCV(messages[140], messages[141], nothing)\n",
      "messages[143] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[142], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_049]))\n",
      "messages[144] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_049_x_048], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_049])\n",
      "messages[145] = ruleSPEqualityGaussianGCV(messages[143], messages[144], nothing)\n",
      "messages[146] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[145], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_050]))\n",
      "messages[147] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_050_x_049], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_050])\n",
      "messages[148] = ruleSPEqualityGaussianGCV(messages[146], messages[147], nothing)\n",
      "messages[149] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[148], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_051]))\n",
      "messages[150] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_051_x_050], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_051])\n",
      "messages[151] = ruleSPEqualityGaussianGCV(messages[149], messages[150], nothing)\n",
      "messages[152] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[151], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_052]))\n",
      "messages[153] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_052_x_051], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_052])\n",
      "messages[154] = ruleSPEqualityGaussianGCV(messages[152], messages[153], nothing)\n",
      "messages[155] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[154], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_053]))\n",
      "messages[156] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_053_x_052], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_053])\n",
      "messages[157] = ruleSPEqualityGaussianGCV(messages[155], messages[156], nothing)\n",
      "messages[158] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[157], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_054]))\n",
      "messages[159] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_054_x_053], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_054])\n",
      "messages[160] = ruleSPEqualityGaussianGCV(messages[158], messages[159], nothing)\n",
      "messages[161] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[160], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_055]))\n",
      "messages[162] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_055_x_054], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_055])\n",
      "messages[163] = ruleSPEqualityGaussianGCV(messages[161], messages[162], nothing)\n",
      "messages[164] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[163], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_056]))\n",
      "messages[165] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_056_x_055], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_056])\n",
      "messages[166] = ruleSPEqualityGaussianGCV(messages[164], messages[165], nothing)\n",
      "messages[167] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[166], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_057]))\n",
      "messages[168] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_057_x_056], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_057])\n",
      "messages[169] = ruleSPEqualityGaussianGCV(messages[167], messages[168], nothing)\n",
      "messages[170] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[169], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_058]))\n",
      "messages[171] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_058_x_057], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_058])\n",
      "messages[172] = ruleSPEqualityGaussianGCV(messages[170], messages[171], nothing)\n",
      "messages[173] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[172], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_059]))\n",
      "messages[174] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_059_x_058], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_059])\n",
      "messages[175] = ruleSPEqualityGaussianGCV(messages[173], messages[174], nothing)\n",
      "messages[176] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[175], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_060]))\n",
      "messages[177] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_060_x_059], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_060])\n",
      "messages[178] = ruleSPEqualityGaussianGCV(messages[176], messages[177], nothing)\n",
      "messages[179] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[178], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_061]))\n",
      "messages[180] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_061_x_060], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_061])\n",
      "messages[181] = ruleSPEqualityGaussianGCV(messages[179], messages[180], nothing)\n",
      "messages[182] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[181], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_062]))\n",
      "messages[183] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_062_x_061], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_062])\n",
      "messages[184] = ruleSPEqualityGaussianGCV(messages[182], messages[183], nothing)\n",
      "messages[185] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[184], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_063]))\n",
      "messages[186] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_063_x_062], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_063])\n",
      "messages[187] = ruleSPEqualityGaussianGCV(messages[185], messages[186], nothing)\n",
      "messages[188] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[187], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_064]))\n",
      "messages[189] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_064_x_063], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_064])\n",
      "messages[190] = ruleSPEqualityGaussianGCV(messages[188], messages[189], nothing)\n",
      "messages[191] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[190], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_065]))\n",
      "messages[192] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_065_x_064], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_065])\n",
      "messages[193] = ruleSPEqualityGaussianGCV(messages[191], messages[192], nothing)\n",
      "messages[194] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[193], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_066]))\n",
      "messages[195] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_066_x_065], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_066])\n",
      "messages[196] = ruleSPEqualityGaussianGCV(messages[194], messages[195], nothing)\n",
      "messages[197] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[196], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_067]))\n",
      "messages[198] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_067_x_066], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_067])\n",
      "messages[199] = ruleSPEqualityGaussianGCV(messages[197], messages[198], nothing)\n",
      "messages[200] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[199], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_068]))\n",
      "messages[201] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_068_x_067], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_068])\n",
      "messages[202] = ruleSPEqualityGaussianGCV(messages[200], messages[201], nothing)\n",
      "messages[203] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[202], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_069]))\n",
      "messages[204] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_069_x_068], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_069])\n",
      "messages[205] = ruleSPEqualityGaussianGCV(messages[203], messages[204], nothing)\n",
      "messages[206] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[205], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_070]))\n",
      "messages[207] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_070_x_069], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_070])\n",
      "messages[208] = ruleSPEqualityGaussianGCV(messages[206], messages[207], nothing)\n",
      "messages[209] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[208], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_071]))\n",
      "messages[210] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_071_x_070], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_071])\n",
      "messages[211] = ruleSPEqualityGaussianGCV(messages[209], messages[210], nothing)\n",
      "messages[212] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[211], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_072]))\n",
      "messages[213] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_072_x_071], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_072])\n",
      "messages[214] = ruleSPEqualityGaussianGCV(messages[212], messages[213], nothing)\n",
      "messages[215] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[214], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_073]))\n",
      "messages[216] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_073_x_072], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_073])\n",
      "messages[217] = ruleSPEqualityGaussianGCV(messages[215], messages[216], nothing)\n",
      "messages[218] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[217], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_074]))\n",
      "messages[219] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_074_x_073], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_074])\n",
      "messages[220] = ruleSPEqualityGaussianGCV(messages[218], messages[219], nothing)\n",
      "messages[221] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[220], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_075]))\n",
      "messages[222] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_075_x_074], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_075])\n",
      "messages[223] = ruleSPEqualityGaussianGCV(messages[221], messages[222], nothing)\n",
      "messages[224] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[223], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_076]))\n",
      "messages[225] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_076_x_075], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_076])\n",
      "messages[226] = ruleSPEqualityGaussianGCV(messages[224], messages[225], nothing)\n",
      "messages[227] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[226], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_077]))\n",
      "messages[228] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_077_x_076], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_077])\n",
      "messages[229] = ruleSPEqualityGaussianGCV(messages[227], messages[228], nothing)\n",
      "messages[230] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[229], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_078]))\n",
      "messages[231] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_078_x_077], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_078])\n",
      "messages[232] = ruleSPEqualityGaussianGCV(messages[230], messages[231], nothing)\n",
      "messages[233] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[232], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_079]))\n",
      "messages[234] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_079_x_078], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_079])\n",
      "messages[235] = ruleSPEqualityGaussianGCV(messages[233], messages[234], nothing)\n",
      "messages[236] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[235], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_080]))\n",
      "messages[237] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_080_x_079], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_080])\n",
      "messages[238] = ruleSPEqualityGaussianGCV(messages[236], messages[237], nothing)\n",
      "messages[239] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[238], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_081]))\n",
      "messages[240] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_081_x_080], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_081])\n",
      "messages[241] = ruleSPEqualityGaussianGCV(messages[239], messages[240], nothing)\n",
      "messages[242] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[241], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_082]))\n",
      "messages[243] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_082_x_081], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_082])\n",
      "messages[244] = ruleSPEqualityGaussianGCV(messages[242], messages[243], nothing)\n",
      "messages[245] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[244], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_083]))\n",
      "messages[246] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_083_x_082], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_083])\n",
      "messages[247] = ruleSPEqualityGaussianGCV(messages[245], messages[246], nothing)\n",
      "messages[248] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[247], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_084]))\n",
      "messages[249] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_084_x_083], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_084])\n",
      "messages[250] = ruleSPEqualityGaussianGCV(messages[248], messages[249], nothing)\n",
      "messages[251] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[250], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_085]))\n",
      "messages[252] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_085_x_084], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_085])\n",
      "messages[253] = ruleSPEqualityGaussianGCV(messages[251], messages[252], nothing)\n",
      "messages[254] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[253], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_086]))\n",
      "messages[255] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_086_x_085], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_086])\n",
      "messages[256] = ruleSPEqualityGaussianGCV(messages[254], messages[255], nothing)\n",
      "messages[257] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[256], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_087]))\n",
      "messages[258] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_087_x_086], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_087])\n",
      "messages[259] = ruleSPEqualityGaussianGCV(messages[257], messages[258], nothing)\n",
      "messages[260] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[259], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_088]))\n",
      "messages[261] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_088_x_087], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_088])\n",
      "messages[262] = ruleSPEqualityGaussianGCV(messages[260], messages[261], nothing)\n",
      "messages[263] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[262], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_089]))\n",
      "messages[264] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_089_x_088], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_089])\n",
      "messages[265] = ruleSPEqualityGaussianGCV(messages[263], messages[264], nothing)\n",
      "messages[266] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[265], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_090]))\n",
      "messages[267] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_090_x_089], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_090])\n",
      "messages[268] = ruleSPEqualityGaussianGCV(messages[266], messages[267], nothing)\n",
      "messages[269] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[268], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_091]))\n",
      "messages[270] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_091_x_090], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_091])\n",
      "messages[271] = ruleSPEqualityGaussianGCV(messages[269], messages[270], nothing)\n",
      "messages[272] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[271], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_092]))\n",
      "messages[273] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_092_x_091], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_092])\n",
      "messages[274] = ruleSPEqualityGaussianGCV(messages[272], messages[273], nothing)\n",
      "messages[275] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[274], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_093]))\n",
      "messages[276] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_093_x_092], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_093])\n",
      "messages[277] = ruleSPEqualityGaussianGCV(messages[275], messages[276], nothing)\n",
      "messages[278] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[277], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_094]))\n",
      "messages[279] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_094_x_093], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_094])\n",
      "messages[280] = ruleSPEqualityGaussianGCV(messages[278], messages[279], nothing)\n",
      "messages[281] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[280], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_095]))\n",
      "messages[282] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_095_x_094], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_095])\n",
      "messages[283] = ruleSPEqualityGaussianGCV(messages[281], messages[282], nothing)\n",
      "messages[284] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[283], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_096]))\n",
      "messages[285] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_096_x_095], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_096])\n",
      "messages[286] = ruleSPEqualityGaussianGCV(messages[284], messages[285], nothing)\n",
      "messages[287] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[286], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_097]))\n",
      "messages[288] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_097_x_096], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_097])\n",
      "messages[289] = ruleSPEqualityGaussianGCV(messages[287], messages[288], nothing)\n",
      "messages[290] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[289], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_098]))\n",
      "messages[291] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_098_x_097], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_098])\n",
      "messages[292] = ruleSPEqualityGaussianGCV(messages[290], messages[291], nothing)\n",
      "messages[293] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[292], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_099]))\n",
      "messages[294] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_099_x_098], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_099])\n",
      "messages[295] = ruleSPEqualityGaussianGCV(messages[293], messages[294], nothing)\n",
      "messages[296] = ruleSVBGaussianMeanPrecisionOutVGD(nothing, messages[295], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_100]))\n",
      "messages[297] = ruleSVBSwitchingGaussianControlledVariancePIn3PPP(marginals[:x_100_x_099], nothing, ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_100])\n",
      "messages[298] = ruleSVBGaussianMeanPrecisionMEND(messages[297], messages[295], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_100]))\n",
      "messages[299] = ruleSPEqualityGaussianGCV(nothing, messages[294], messages[298])\n",
      "messages[300] = ruleSVBGaussianMeanPrecisionMGVD(messages[299], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_099]))\n",
      "messages[301] = ruleSPEqualityGaussianGCV(nothing, messages[291], messages[300])\n",
      "messages[302] = ruleSVBGaussianMeanPrecisionMGVD(messages[301], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_098]))\n",
      "messages[303] = ruleSPEqualityGaussianGCV(nothing, messages[288], messages[302])\n",
      "messages[304] = ruleSVBGaussianMeanPrecisionMGVD(messages[303], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_097]))\n",
      "messages[305] = ruleSPEqualityGaussianGCV(nothing, messages[285], messages[304])\n",
      "messages[306] = ruleSVBGaussianMeanPrecisionMGVD(messages[305], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_096]))\n",
      "messages[307] = ruleSPEqualityGaussianGCV(nothing, messages[282], messages[306])\n",
      "messages[308] = ruleSVBGaussianMeanPrecisionMGVD(messages[307], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_095]))\n",
      "messages[309] = ruleSPEqualityGaussianGCV(nothing, messages[279], messages[308])\n",
      "messages[310] = ruleSVBGaussianMeanPrecisionMGVD(messages[309], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_094]))\n",
      "messages[311] = ruleSPEqualityGaussianGCV(nothing, messages[276], messages[310])\n",
      "messages[312] = ruleSVBGaussianMeanPrecisionMGVD(messages[311], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_093]))\n",
      "messages[313] = ruleSPEqualityGaussianGCV(nothing, messages[273], messages[312])\n",
      "messages[314] = ruleSVBGaussianMeanPrecisionMGVD(messages[313], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_092]))\n",
      "messages[315] = ruleSPEqualityGaussianGCV(nothing, messages[270], messages[314])\n",
      "messages[316] = ruleSVBGaussianMeanPrecisionMGVD(messages[315], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_091]))\n",
      "messages[317] = ruleSPEqualityGaussianGCV(nothing, messages[267], messages[316])\n",
      "messages[318] = ruleSVBGaussianMeanPrecisionMGVD(messages[317], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_090]))\n",
      "messages[319] = ruleSPEqualityGaussianGCV(nothing, messages[264], messages[318])\n",
      "messages[320] = ruleSVBGaussianMeanPrecisionMGVD(messages[319], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_089]))\n",
      "messages[321] = ruleSPEqualityGaussianGCV(nothing, messages[261], messages[320])\n",
      "messages[322] = ruleSVBGaussianMeanPrecisionMGVD(messages[321], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_088]))\n",
      "messages[323] = ruleSPEqualityGaussianGCV(nothing, messages[258], messages[322])\n",
      "messages[324] = ruleSVBGaussianMeanPrecisionMGVD(messages[323], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_087]))\n",
      "messages[325] = ruleSPEqualityGaussianGCV(nothing, messages[255], messages[324])\n",
      "messages[326] = ruleSVBGaussianMeanPrecisionMGVD(messages[325], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_086]))\n",
      "messages[327] = ruleSPEqualityGaussianGCV(nothing, messages[252], messages[326])\n",
      "messages[328] = ruleSVBGaussianMeanPrecisionMGVD(messages[327], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_085]))\n",
      "messages[329] = ruleSPEqualityGaussianGCV(nothing, messages[249], messages[328])\n",
      "messages[330] = ruleSVBGaussianMeanPrecisionMGVD(messages[329], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_084]))\n",
      "messages[331] = ruleSPEqualityGaussianGCV(nothing, messages[246], messages[330])\n",
      "messages[332] = ruleSVBGaussianMeanPrecisionMGVD(messages[331], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_083]))\n",
      "messages[333] = ruleSPEqualityGaussianGCV(nothing, messages[243], messages[332])\n",
      "messages[334] = ruleSVBGaussianMeanPrecisionMGVD(messages[333], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_082]))\n",
      "messages[335] = ruleSPEqualityGaussianGCV(nothing, messages[240], messages[334])\n",
      "messages[336] = ruleSVBGaussianMeanPrecisionMGVD(messages[335], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_081]))\n",
      "messages[337] = ruleSPEqualityGaussianGCV(nothing, messages[237], messages[336])\n",
      "messages[338] = ruleSVBGaussianMeanPrecisionMGVD(messages[337], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_080]))\n",
      "messages[339] = ruleSPEqualityGaussianGCV(nothing, messages[234], messages[338])\n",
      "messages[340] = ruleSVBGaussianMeanPrecisionMGVD(messages[339], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_079]))\n",
      "messages[341] = ruleSPEqualityGaussianGCV(nothing, messages[231], messages[340])\n",
      "messages[342] = ruleSVBGaussianMeanPrecisionMGVD(messages[341], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_078]))\n",
      "messages[343] = ruleSPEqualityGaussianGCV(nothing, messages[228], messages[342])\n",
      "messages[344] = ruleSVBGaussianMeanPrecisionMGVD(messages[343], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_077]))\n",
      "messages[345] = ruleSPEqualityGaussianGCV(nothing, messages[225], messages[344])\n",
      "messages[346] = ruleSVBGaussianMeanPrecisionMGVD(messages[345], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_076]))\n",
      "messages[347] = ruleSPEqualityGaussianGCV(nothing, messages[222], messages[346])\n",
      "messages[348] = ruleSVBGaussianMeanPrecisionMGVD(messages[347], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_075]))\n",
      "messages[349] = ruleSPEqualityGaussianGCV(nothing, messages[219], messages[348])\n",
      "messages[350] = ruleSVBGaussianMeanPrecisionMGVD(messages[349], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_074]))\n",
      "messages[351] = ruleSPEqualityGaussianGCV(nothing, messages[216], messages[350])\n",
      "messages[352] = ruleSVBGaussianMeanPrecisionMGVD(messages[351], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_073]))\n",
      "messages[353] = ruleSPEqualityGaussianGCV(nothing, messages[213], messages[352])\n",
      "messages[354] = ruleSVBGaussianMeanPrecisionMGVD(messages[353], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_072]))\n",
      "messages[355] = ruleSPEqualityGaussianGCV(nothing, messages[210], messages[354])\n",
      "messages[356] = ruleSVBGaussianMeanPrecisionMGVD(messages[355], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_071]))\n",
      "messages[357] = ruleSPEqualityGaussianGCV(nothing, messages[207], messages[356])\n",
      "messages[358] = ruleSVBGaussianMeanPrecisionMGVD(messages[357], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_070]))\n",
      "messages[359] = ruleSPEqualityGaussianGCV(nothing, messages[204], messages[358])\n",
      "messages[360] = ruleSVBGaussianMeanPrecisionMGVD(messages[359], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_069]))\n",
      "messages[361] = ruleSPEqualityGaussianGCV(nothing, messages[201], messages[360])\n",
      "messages[362] = ruleSVBGaussianMeanPrecisionMGVD(messages[361], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_068]))\n",
      "messages[363] = ruleSPEqualityGaussianGCV(nothing, messages[198], messages[362])\n",
      "messages[364] = ruleSVBGaussianMeanPrecisionMGVD(messages[363], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_067]))\n",
      "messages[365] = ruleSPEqualityGaussianGCV(nothing, messages[195], messages[364])\n",
      "messages[366] = ruleSVBGaussianMeanPrecisionMGVD(messages[365], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_066]))\n",
      "messages[367] = ruleSPEqualityGaussianGCV(nothing, messages[192], messages[366])\n",
      "messages[368] = ruleSVBGaussianMeanPrecisionMGVD(messages[367], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_065]))\n",
      "messages[369] = ruleSPEqualityGaussianGCV(nothing, messages[189], messages[368])\n",
      "messages[370] = ruleSVBGaussianMeanPrecisionMGVD(messages[369], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_064]))\n",
      "messages[371] = ruleSPEqualityGaussianGCV(nothing, messages[186], messages[370])\n",
      "messages[372] = ruleSVBGaussianMeanPrecisionMGVD(messages[371], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_063]))\n",
      "messages[373] = ruleSPEqualityGaussianGCV(nothing, messages[183], messages[372])\n",
      "messages[374] = ruleSVBGaussianMeanPrecisionMGVD(messages[373], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_062]))\n",
      "messages[375] = ruleSPEqualityGaussianGCV(nothing, messages[180], messages[374])\n",
      "messages[376] = ruleSVBGaussianMeanPrecisionMGVD(messages[375], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_061]))\n",
      "messages[377] = ruleSPEqualityGaussianGCV(nothing, messages[177], messages[376])\n",
      "messages[378] = ruleSVBGaussianMeanPrecisionMGVD(messages[377], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_060]))\n",
      "messages[379] = ruleSPEqualityGaussianGCV(nothing, messages[174], messages[378])\n",
      "messages[380] = ruleSVBGaussianMeanPrecisionMGVD(messages[379], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_059]))\n",
      "messages[381] = ruleSPEqualityGaussianGCV(nothing, messages[171], messages[380])\n",
      "messages[382] = ruleSVBGaussianMeanPrecisionMGVD(messages[381], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_058]))\n",
      "messages[383] = ruleSPEqualityGaussianGCV(nothing, messages[168], messages[382])\n",
      "messages[384] = ruleSVBGaussianMeanPrecisionMGVD(messages[383], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_057]))\n",
      "messages[385] = ruleSPEqualityGaussianGCV(nothing, messages[165], messages[384])\n",
      "messages[386] = ruleSVBGaussianMeanPrecisionMGVD(messages[385], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_056]))\n",
      "messages[387] = ruleSPEqualityGaussianGCV(nothing, messages[162], messages[386])\n",
      "messages[388] = ruleSVBGaussianMeanPrecisionMGVD(messages[387], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_055]))\n",
      "messages[389] = ruleSPEqualityGaussianGCV(nothing, messages[159], messages[388])\n",
      "messages[390] = ruleSVBGaussianMeanPrecisionMGVD(messages[389], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_054]))\n",
      "messages[391] = ruleSPEqualityGaussianGCV(nothing, messages[156], messages[390])\n",
      "messages[392] = ruleSVBGaussianMeanPrecisionMGVD(messages[391], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_053]))\n",
      "messages[393] = ruleSPEqualityGaussianGCV(nothing, messages[153], messages[392])\n",
      "messages[394] = ruleSVBGaussianMeanPrecisionMGVD(messages[393], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_052]))\n",
      "messages[395] = ruleSPEqualityGaussianGCV(nothing, messages[150], messages[394])\n",
      "messages[396] = ruleSVBGaussianMeanPrecisionMGVD(messages[395], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_051]))\n",
      "messages[397] = ruleSPEqualityGaussianGCV(nothing, messages[147], messages[396])\n",
      "messages[398] = ruleSVBGaussianMeanPrecisionMGVD(messages[397], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_050]))\n",
      "messages[399] = ruleSPEqualityGaussianGCV(nothing, messages[144], messages[398])\n",
      "messages[400] = ruleSVBGaussianMeanPrecisionMGVD(messages[399], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_049]))\n",
      "messages[401] = ruleSPEqualityGaussianGCV(nothing, messages[141], messages[400])\n",
      "messages[402] = ruleSVBGaussianMeanPrecisionMGVD(messages[401], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_048]))\n",
      "messages[403] = ruleSPEqualityGaussianGCV(nothing, messages[138], messages[402])\n",
      "messages[404] = ruleSVBGaussianMeanPrecisionMGVD(messages[403], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_047]))\n",
      "messages[405] = ruleSPEqualityGaussianGCV(nothing, messages[135], messages[404])\n",
      "messages[406] = ruleSVBGaussianMeanPrecisionMGVD(messages[405], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_046]))\n",
      "messages[407] = ruleSPEqualityGaussianGCV(nothing, messages[132], messages[406])\n",
      "messages[408] = ruleSVBGaussianMeanPrecisionMGVD(messages[407], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_045]))\n",
      "messages[409] = ruleSPEqualityGaussianGCV(nothing, messages[129], messages[408])\n",
      "messages[410] = ruleSVBGaussianMeanPrecisionMGVD(messages[409], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_044]))\n",
      "messages[411] = ruleSPEqualityGaussianGCV(nothing, messages[126], messages[410])\n",
      "messages[412] = ruleSVBGaussianMeanPrecisionMGVD(messages[411], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_043]))\n",
      "messages[413] = ruleSPEqualityGaussianGCV(nothing, messages[123], messages[412])\n",
      "messages[414] = ruleSVBGaussianMeanPrecisionMGVD(messages[413], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_042]))\n",
      "messages[415] = ruleSPEqualityGaussianGCV(nothing, messages[120], messages[414])\n",
      "messages[416] = ruleSVBGaussianMeanPrecisionMGVD(messages[415], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_041]))\n",
      "messages[417] = ruleSPEqualityGaussianGCV(nothing, messages[117], messages[416])\n",
      "messages[418] = ruleSVBGaussianMeanPrecisionMGVD(messages[417], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_040]))\n",
      "messages[419] = ruleSPEqualityGaussianGCV(nothing, messages[114], messages[418])\n",
      "messages[420] = ruleSVBGaussianMeanPrecisionMGVD(messages[419], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_039]))\n",
      "messages[421] = ruleSPEqualityGaussianGCV(nothing, messages[111], messages[420])\n",
      "messages[422] = ruleSVBGaussianMeanPrecisionMGVD(messages[421], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_038]))\n",
      "messages[423] = ruleSPEqualityGaussianGCV(nothing, messages[108], messages[422])\n",
      "messages[424] = ruleSVBGaussianMeanPrecisionMGVD(messages[423], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_037]))\n",
      "messages[425] = ruleSPEqualityGaussianGCV(nothing, messages[105], messages[424])\n",
      "messages[426] = ruleSVBGaussianMeanPrecisionMGVD(messages[425], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_036]))\n",
      "messages[427] = ruleSPEqualityGaussianGCV(nothing, messages[102], messages[426])\n",
      "messages[428] = ruleSVBGaussianMeanPrecisionMGVD(messages[427], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_035]))\n",
      "messages[429] = ruleSPEqualityGaussianGCV(nothing, messages[99], messages[428])\n",
      "messages[430] = ruleSVBGaussianMeanPrecisionMGVD(messages[429], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_034]))\n",
      "messages[431] = ruleSPEqualityGaussianGCV(nothing, messages[96], messages[430])\n",
      "messages[432] = ruleSVBGaussianMeanPrecisionMGVD(messages[431], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_033]))\n",
      "messages[433] = ruleSPEqualityGaussianGCV(nothing, messages[93], messages[432])\n",
      "messages[434] = ruleSVBGaussianMeanPrecisionMGVD(messages[433], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_032]))\n",
      "messages[435] = ruleSPEqualityGaussianGCV(nothing, messages[90], messages[434])\n",
      "messages[436] = ruleSVBGaussianMeanPrecisionMGVD(messages[435], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_031]))\n",
      "messages[437] = ruleSPEqualityGaussianGCV(nothing, messages[87], messages[436])\n",
      "messages[438] = ruleSVBGaussianMeanPrecisionMGVD(messages[437], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_030]))\n",
      "messages[439] = ruleSPEqualityGaussianGCV(nothing, messages[84], messages[438])\n",
      "messages[440] = ruleSVBGaussianMeanPrecisionMGVD(messages[439], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_029]))\n",
      "messages[441] = ruleSPEqualityGaussianGCV(nothing, messages[81], messages[440])\n",
      "messages[442] = ruleSVBGaussianMeanPrecisionMGVD(messages[441], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_028]))\n",
      "messages[443] = ruleSPEqualityGaussianGCV(nothing, messages[78], messages[442])\n",
      "messages[444] = ruleSVBGaussianMeanPrecisionMGVD(messages[443], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_027]))\n",
      "messages[445] = ruleSPEqualityGaussianGCV(nothing, messages[75], messages[444])\n",
      "messages[446] = ruleSVBGaussianMeanPrecisionMGVD(messages[445], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_026]))\n",
      "messages[447] = ruleSPEqualityGaussianGCV(nothing, messages[72], messages[446])\n",
      "messages[448] = ruleSVBGaussianMeanPrecisionMGVD(messages[447], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_025]))\n",
      "messages[449] = ruleSPEqualityGaussianGCV(nothing, messages[69], messages[448])\n",
      "messages[450] = ruleSVBGaussianMeanPrecisionMGVD(messages[449], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_024]))\n",
      "messages[451] = ruleSPEqualityGaussianGCV(nothing, messages[66], messages[450])\n",
      "messages[452] = ruleSVBGaussianMeanPrecisionMGVD(messages[451], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_023]))\n",
      "messages[453] = ruleSPEqualityGaussianGCV(nothing, messages[63], messages[452])\n",
      "messages[454] = ruleSVBGaussianMeanPrecisionMGVD(messages[453], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_022]))\n",
      "messages[455] = ruleSPEqualityGaussianGCV(nothing, messages[60], messages[454])\n",
      "messages[456] = ruleSVBGaussianMeanPrecisionMGVD(messages[455], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_021]))\n",
      "messages[457] = ruleSPEqualityGaussianGCV(nothing, messages[57], messages[456])\n",
      "messages[458] = ruleSVBGaussianMeanPrecisionMGVD(messages[457], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_020]))\n",
      "messages[459] = ruleSPEqualityGaussianGCV(nothing, messages[54], messages[458])\n",
      "messages[460] = ruleSVBGaussianMeanPrecisionMGVD(messages[459], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_019]))\n",
      "messages[461] = ruleSPEqualityGaussianGCV(nothing, messages[51], messages[460])\n",
      "messages[462] = ruleSVBGaussianMeanPrecisionMGVD(messages[461], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_018]))\n",
      "messages[463] = ruleSPEqualityGaussianGCV(nothing, messages[48], messages[462])\n",
      "messages[464] = ruleSVBGaussianMeanPrecisionMGVD(messages[463], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_017]))\n",
      "messages[465] = ruleSPEqualityGaussianGCV(nothing, messages[45], messages[464])\n",
      "messages[466] = ruleSVBGaussianMeanPrecisionMGVD(messages[465], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_016]))\n",
      "messages[467] = ruleSPEqualityGaussianGCV(nothing, messages[42], messages[466])\n",
      "messages[468] = ruleSVBGaussianMeanPrecisionMGVD(messages[467], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_015]))\n",
      "messages[469] = ruleSPEqualityGaussianGCV(nothing, messages[39], messages[468])\n",
      "messages[470] = ruleSVBGaussianMeanPrecisionMGVD(messages[469], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_014]))\n",
      "messages[471] = ruleSPEqualityGaussianGCV(nothing, messages[36], messages[470])\n",
      "messages[472] = ruleSVBGaussianMeanPrecisionMGVD(messages[471], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_013]))\n",
      "messages[473] = ruleSPEqualityGaussianGCV(nothing, messages[33], messages[472])\n",
      "messages[474] = ruleSVBGaussianMeanPrecisionMGVD(messages[473], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_012]))\n",
      "messages[475] = ruleSPEqualityGaussianGCV(nothing, messages[30], messages[474])\n",
      "messages[476] = ruleSVBGaussianMeanPrecisionMGVD(messages[475], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_011]))\n",
      "messages[477] = ruleSPEqualityGaussianGCV(nothing, messages[27], messages[476])\n",
      "messages[478] = ruleSVBGaussianMeanPrecisionMGVD(messages[477], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_010]))\n",
      "messages[479] = ruleSPEqualityGaussianGCV(nothing, messages[24], messages[478])\n",
      "messages[480] = ruleSVBGaussianMeanPrecisionMGVD(messages[479], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_009]))\n",
      "messages[481] = ruleSPEqualityGaussianGCV(nothing, messages[21], messages[480])\n",
      "messages[482] = ruleSVBGaussianMeanPrecisionMGVD(messages[481], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_008]))\n",
      "messages[483] = ruleSPEqualityGaussianGCV(nothing, messages[18], messages[482])\n",
      "messages[484] = ruleSVBGaussianMeanPrecisionMGVD(messages[483], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_007]))\n",
      "messages[485] = ruleSPEqualityGaussianGCV(nothing, messages[15], messages[484])\n",
      "messages[486] = ruleSVBGaussianMeanPrecisionMGVD(messages[485], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_006]))\n",
      "messages[487] = ruleSPEqualityGaussianGCV(nothing, messages[12], messages[486])\n",
      "messages[488] = ruleSVBGaussianMeanPrecisionMGVD(messages[487], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_005]))\n",
      "messages[489] = ruleSPEqualityGaussianGCV(nothing, messages[9], messages[488])\n",
      "messages[490] = ruleSVBGaussianMeanPrecisionMGVD(messages[489], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_004]))\n",
      "messages[491] = ruleSPEqualityGaussianGCV(nothing, messages[6], messages[490])\n",
      "messages[492] = ruleSVBGaussianMeanPrecisionMGVD(messages[491], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_003]))\n",
      "messages[493] = ruleSPEqualityGaussianGCV(nothing, messages[3], messages[492])\n",
      "messages[494] = ruleSVBGaussianMeanPrecisionMGVD(messages[493], nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_002]))\n",
      "\n",
      "marginals[:z_001] = messages[1].dist * messages[494].dist\n",
      "marginals[:z_002] = messages[2].dist * messages[493].dist\n",
      "marginals[:z_003] = messages[5].dist * messages[491].dist\n",
      "marginals[:z_004] = messages[8].dist * messages[489].dist\n",
      "marginals[:z_005] = messages[11].dist * messages[487].dist\n",
      "marginals[:z_006] = messages[14].dist * messages[485].dist\n",
      "marginals[:z_007] = messages[17].dist * messages[483].dist\n",
      "marginals[:z_008] = messages[20].dist * messages[481].dist\n",
      "marginals[:z_009] = messages[23].dist * messages[479].dist\n",
      "marginals[:z_010] = messages[26].dist * messages[477].dist\n",
      "marginals[:z_011] = messages[29].dist * messages[475].dist\n",
      "marginals[:z_012] = messages[32].dist * messages[473].dist\n",
      "marginals[:z_013] = messages[35].dist * messages[471].dist\n",
      "marginals[:z_014] = messages[38].dist * messages[469].dist\n",
      "marginals[:z_015] = messages[41].dist * messages[467].dist\n",
      "marginals[:z_016] = messages[44].dist * messages[465].dist\n",
      "marginals[:z_017] = messages[47].dist * messages[463].dist\n",
      "marginals[:z_018] = messages[50].dist * messages[461].dist\n",
      "marginals[:z_019] = messages[53].dist * messages[459].dist\n",
      "marginals[:z_020] = messages[56].dist * messages[457].dist\n",
      "marginals[:z_021] = messages[59].dist * messages[455].dist\n",
      "marginals[:z_022] = messages[62].dist * messages[453].dist\n",
      "marginals[:z_023] = messages[65].dist * messages[451].dist\n",
      "marginals[:z_024] = messages[68].dist * messages[449].dist\n",
      "marginals[:z_025] = messages[71].dist * messages[447].dist\n",
      "marginals[:z_026] = messages[74].dist * messages[445].dist\n",
      "marginals[:z_027] = messages[77].dist * messages[443].dist\n",
      "marginals[:z_028] = messages[80].dist * messages[441].dist\n",
      "marginals[:z_029] = messages[83].dist * messages[439].dist\n",
      "marginals[:z_030] = messages[86].dist * messages[437].dist\n",
      "marginals[:z_031] = messages[89].dist * messages[435].dist\n",
      "marginals[:z_032] = messages[92].dist * messages[433].dist\n",
      "marginals[:z_033] = messages[95].dist * messages[431].dist\n",
      "marginals[:z_034] = messages[98].dist * messages[429].dist\n",
      "marginals[:z_035] = messages[101].dist * messages[427].dist\n",
      "marginals[:z_036] = messages[104].dist * messages[425].dist\n",
      "marginals[:z_037] = messages[107].dist * messages[423].dist\n",
      "marginals[:z_038] = messages[110].dist * messages[421].dist\n",
      "marginals[:z_039] = messages[113].dist * messages[419].dist\n",
      "marginals[:z_040] = messages[116].dist * messages[417].dist\n",
      "marginals[:z_041] = messages[119].dist * messages[415].dist\n",
      "marginals[:z_042] = messages[122].dist * messages[413].dist\n",
      "marginals[:z_043] = messages[125].dist * messages[411].dist\n",
      "marginals[:z_044] = messages[128].dist * messages[409].dist\n",
      "marginals[:z_045] = messages[131].dist * messages[407].dist\n",
      "marginals[:z_046] = messages[134].dist * messages[405].dist\n",
      "marginals[:z_047] = messages[137].dist * messages[403].dist\n",
      "marginals[:z_048] = messages[140].dist * messages[401].dist\n",
      "marginals[:z_049] = messages[143].dist * messages[399].dist\n",
      "marginals[:z_050] = messages[146].dist * messages[397].dist\n",
      "marginals[:z_051] = messages[149].dist * messages[395].dist\n",
      "marginals[:z_052] = messages[152].dist * messages[393].dist\n",
      "marginals[:z_053] = messages[155].dist * messages[391].dist\n",
      "marginals[:z_054] = messages[158].dist * messages[389].dist\n",
      "marginals[:z_055] = messages[161].dist * messages[387].dist\n",
      "marginals[:z_056] = messages[164].dist * messages[385].dist\n",
      "marginals[:z_057] = messages[167].dist * messages[383].dist\n",
      "marginals[:z_058] = messages[170].dist * messages[381].dist\n",
      "marginals[:z_059] = messages[173].dist * messages[379].dist\n",
      "marginals[:z_060] = messages[176].dist * messages[377].dist\n",
      "marginals[:z_061] = messages[179].dist * messages[375].dist\n",
      "marginals[:z_062] = messages[182].dist * messages[373].dist\n",
      "marginals[:z_063] = messages[185].dist * messages[371].dist\n",
      "marginals[:z_064] = messages[188].dist * messages[369].dist\n",
      "marginals[:z_065] = messages[191].dist * messages[367].dist\n",
      "marginals[:z_066] = messages[194].dist * messages[365].dist\n",
      "marginals[:z_067] = messages[197].dist * messages[363].dist\n",
      "marginals[:z_068] = messages[200].dist * messages[361].dist\n",
      "marginals[:z_069] = messages[203].dist * messages[359].dist\n",
      "marginals[:z_070] = messages[206].dist * messages[357].dist\n",
      "marginals[:z_071] = messages[209].dist * messages[355].dist\n",
      "marginals[:z_072] = messages[212].dist * messages[353].dist\n",
      "marginals[:z_073] = messages[215].dist * messages[351].dist\n",
      "marginals[:z_074] = messages[218].dist * messages[349].dist\n",
      "marginals[:z_075] = messages[221].dist * messages[347].dist\n",
      "marginals[:z_076] = messages[224].dist * messages[345].dist\n",
      "marginals[:z_077] = messages[227].dist * messages[343].dist\n",
      "marginals[:z_078] = messages[230].dist * messages[341].dist\n",
      "marginals[:z_079] = messages[233].dist * messages[339].dist\n",
      "marginals[:z_080] = messages[236].dist * messages[337].dist\n",
      "marginals[:z_081] = messages[239].dist * messages[335].dist\n",
      "marginals[:z_082] = messages[242].dist * messages[333].dist\n",
      "marginals[:z_083] = messages[245].dist * messages[331].dist\n",
      "marginals[:z_084] = messages[248].dist * messages[329].dist\n",
      "marginals[:z_085] = messages[251].dist * messages[327].dist\n",
      "marginals[:z_086] = messages[254].dist * messages[325].dist\n",
      "marginals[:z_087] = messages[257].dist * messages[323].dist\n",
      "marginals[:z_088] = messages[260].dist * messages[321].dist\n",
      "marginals[:z_089] = messages[263].dist * messages[319].dist\n",
      "marginals[:z_090] = messages[266].dist * messages[317].dist\n",
      "marginals[:z_091] = messages[269].dist * messages[315].dist\n",
      "marginals[:z_092] = messages[272].dist * messages[313].dist\n",
      "marginals[:z_093] = messages[275].dist * messages[311].dist\n",
      "marginals[:z_094] = messages[278].dist * messages[309].dist\n",
      "marginals[:z_095] = messages[281].dist * messages[307].dist\n",
      "marginals[:z_096] = messages[284].dist * messages[305].dist\n",
      "marginals[:z_097] = messages[287].dist * messages[303].dist\n",
      "marginals[:z_098] = messages[290].dist * messages[301].dist\n",
      "marginals[:z_099] = messages[293].dist * messages[299].dist\n",
      "marginals[:z_100] = messages[296].dist * messages[297].dist\n",
      "marginals[:z_002_z_001] = ruleMGaussianMeanPrecisionGGD(messages[493], messages[1], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_002]))\n",
      "marginals[:z_003_z_002] = ruleMGaussianMeanPrecisionGGD(messages[491], messages[4], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_003]))\n",
      "marginals[:z_004_z_003] = ruleMGaussianMeanPrecisionGGD(messages[489], messages[7], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_004]))\n",
      "marginals[:z_005_z_004] = ruleMGaussianMeanPrecisionGGD(messages[487], messages[10], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_005]))\n",
      "marginals[:z_006_z_005] = ruleMGaussianMeanPrecisionGGD(messages[485], messages[13], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_006]))\n",
      "marginals[:z_007_z_006] = ruleMGaussianMeanPrecisionGGD(messages[483], messages[16], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_007]))\n",
      "marginals[:z_008_z_007] = ruleMGaussianMeanPrecisionGGD(messages[481], messages[19], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_008]))\n",
      "marginals[:z_009_z_008] = ruleMGaussianMeanPrecisionGGD(messages[479], messages[22], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_009]))\n",
      "marginals[:z_010_z_009] = ruleMGaussianMeanPrecisionGGD(messages[477], messages[25], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_010]))\n",
      "marginals[:z_011_z_010] = ruleMGaussianMeanPrecisionGGD(messages[475], messages[28], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_011]))\n",
      "marginals[:z_012_z_011] = ruleMGaussianMeanPrecisionGGD(messages[473], messages[31], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_012]))\n",
      "marginals[:z_013_z_012] = ruleMGaussianMeanPrecisionGGD(messages[471], messages[34], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_013]))\n",
      "marginals[:z_014_z_013] = ruleMGaussianMeanPrecisionGGD(messages[469], messages[37], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_014]))\n",
      "marginals[:z_015_z_014] = ruleMGaussianMeanPrecisionGGD(messages[467], messages[40], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_015]))\n",
      "marginals[:z_016_z_015] = ruleMGaussianMeanPrecisionGGD(messages[465], messages[43], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_016]))\n",
      "marginals[:z_017_z_016] = ruleMGaussianMeanPrecisionGGD(messages[463], messages[46], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_017]))\n",
      "marginals[:z_018_z_017] = ruleMGaussianMeanPrecisionGGD(messages[461], messages[49], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_018]))\n",
      "marginals[:z_019_z_018] = ruleMGaussianMeanPrecisionGGD(messages[459], messages[52], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_019]))\n",
      "marginals[:z_020_z_019] = ruleMGaussianMeanPrecisionGGD(messages[457], messages[55], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_020]))\n",
      "marginals[:z_021_z_020] = ruleMGaussianMeanPrecisionGGD(messages[455], messages[58], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_021]))\n",
      "marginals[:z_022_z_021] = ruleMGaussianMeanPrecisionGGD(messages[453], messages[61], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_022]))\n",
      "marginals[:z_023_z_022] = ruleMGaussianMeanPrecisionGGD(messages[451], messages[64], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_023]))\n",
      "marginals[:z_024_z_023] = ruleMGaussianMeanPrecisionGGD(messages[449], messages[67], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_024]))\n",
      "marginals[:z_025_z_024] = ruleMGaussianMeanPrecisionGGD(messages[447], messages[70], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_025]))\n",
      "marginals[:z_026_z_025] = ruleMGaussianMeanPrecisionGGD(messages[445], messages[73], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_026]))\n",
      "marginals[:z_027_z_026] = ruleMGaussianMeanPrecisionGGD(messages[443], messages[76], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_027]))\n",
      "marginals[:z_028_z_027] = ruleMGaussianMeanPrecisionGGD(messages[441], messages[79], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_028]))\n",
      "marginals[:z_029_z_028] = ruleMGaussianMeanPrecisionGGD(messages[439], messages[82], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_029]))\n",
      "marginals[:z_030_z_029] = ruleMGaussianMeanPrecisionGGD(messages[437], messages[85], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_030]))\n",
      "marginals[:z_031_z_030] = ruleMGaussianMeanPrecisionGGD(messages[435], messages[88], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_031]))\n",
      "marginals[:z_032_z_031] = ruleMGaussianMeanPrecisionGGD(messages[433], messages[91], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_032]))\n",
      "marginals[:z_033_z_032] = ruleMGaussianMeanPrecisionGGD(messages[431], messages[94], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_033]))\n",
      "marginals[:z_034_z_033] = ruleMGaussianMeanPrecisionGGD(messages[429], messages[97], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_034]))\n",
      "marginals[:z_035_z_034] = ruleMGaussianMeanPrecisionGGD(messages[427], messages[100], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_035]))\n",
      "marginals[:z_036_z_035] = ruleMGaussianMeanPrecisionGGD(messages[425], messages[103], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_036]))\n",
      "marginals[:z_037_z_036] = ruleMGaussianMeanPrecisionGGD(messages[423], messages[106], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_037]))\n",
      "marginals[:z_038_z_037] = ruleMGaussianMeanPrecisionGGD(messages[421], messages[109], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_038]))\n",
      "marginals[:z_039_z_038] = ruleMGaussianMeanPrecisionGGD(messages[419], messages[112], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_039]))\n",
      "marginals[:z_040_z_039] = ruleMGaussianMeanPrecisionGGD(messages[417], messages[115], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_040]))\n",
      "marginals[:z_041_z_040] = ruleMGaussianMeanPrecisionGGD(messages[415], messages[118], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_041]))\n",
      "marginals[:z_042_z_041] = ruleMGaussianMeanPrecisionGGD(messages[413], messages[121], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_042]))\n",
      "marginals[:z_043_z_042] = ruleMGaussianMeanPrecisionGGD(messages[411], messages[124], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_043]))\n",
      "marginals[:z_044_z_043] = ruleMGaussianMeanPrecisionGGD(messages[409], messages[127], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_044]))\n",
      "marginals[:z_045_z_044] = ruleMGaussianMeanPrecisionGGD(messages[407], messages[130], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_045]))\n",
      "marginals[:z_046_z_045] = ruleMGaussianMeanPrecisionGGD(messages[405], messages[133], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_046]))\n",
      "marginals[:z_047_z_046] = ruleMGaussianMeanPrecisionGGD(messages[403], messages[136], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_047]))\n",
      "marginals[:z_048_z_047] = ruleMGaussianMeanPrecisionGGD(messages[401], messages[139], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_048]))\n",
      "marginals[:z_049_z_048] = ruleMGaussianMeanPrecisionGGD(messages[399], messages[142], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_049]))\n",
      "marginals[:z_050_z_049] = ruleMGaussianMeanPrecisionGGD(messages[397], messages[145], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_050]))\n",
      "marginals[:z_051_z_050] = ruleMGaussianMeanPrecisionGGD(messages[395], messages[148], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_051]))\n",
      "marginals[:z_052_z_051] = ruleMGaussianMeanPrecisionGGD(messages[393], messages[151], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_052]))\n",
      "marginals[:z_053_z_052] = ruleMGaussianMeanPrecisionGGD(messages[391], messages[154], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_053]))\n",
      "marginals[:z_054_z_053] = ruleMGaussianMeanPrecisionGGD(messages[389], messages[157], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_054]))\n",
      "marginals[:z_055_z_054] = ruleMGaussianMeanPrecisionGGD(messages[387], messages[160], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_055]))\n",
      "marginals[:z_056_z_055] = ruleMGaussianMeanPrecisionGGD(messages[385], messages[163], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_056]))\n",
      "marginals[:z_057_z_056] = ruleMGaussianMeanPrecisionGGD(messages[383], messages[166], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_057]))\n",
      "marginals[:z_058_z_057] = ruleMGaussianMeanPrecisionGGD(messages[381], messages[169], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_058]))\n",
      "marginals[:z_059_z_058] = ruleMGaussianMeanPrecisionGGD(messages[379], messages[172], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_059]))\n",
      "marginals[:z_060_z_059] = ruleMGaussianMeanPrecisionGGD(messages[377], messages[175], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_060]))\n",
      "marginals[:z_061_z_060] = ruleMGaussianMeanPrecisionGGD(messages[375], messages[178], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_061]))\n",
      "marginals[:z_062_z_061] = ruleMGaussianMeanPrecisionGGD(messages[373], messages[181], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_062]))\n",
      "marginals[:z_063_z_062] = ruleMGaussianMeanPrecisionGGD(messages[371], messages[184], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_063]))\n",
      "marginals[:z_064_z_063] = ruleMGaussianMeanPrecisionGGD(messages[369], messages[187], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_064]))\n",
      "marginals[:z_065_z_064] = ruleMGaussianMeanPrecisionGGD(messages[367], messages[190], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_065]))\n",
      "marginals[:z_066_z_065] = ruleMGaussianMeanPrecisionGGD(messages[365], messages[193], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_066]))\n",
      "marginals[:z_067_z_066] = ruleMGaussianMeanPrecisionGGD(messages[363], messages[196], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_067]))\n",
      "marginals[:z_068_z_067] = ruleMGaussianMeanPrecisionGGD(messages[361], messages[199], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_068]))\n",
      "marginals[:z_069_z_068] = ruleMGaussianMeanPrecisionGGD(messages[359], messages[202], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_069]))\n",
      "marginals[:z_070_z_069] = ruleMGaussianMeanPrecisionGGD(messages[357], messages[205], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_070]))\n",
      "marginals[:z_071_z_070] = ruleMGaussianMeanPrecisionGGD(messages[355], messages[208], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_071]))\n",
      "marginals[:z_072_z_071] = ruleMGaussianMeanPrecisionGGD(messages[353], messages[211], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_072]))\n",
      "marginals[:z_073_z_072] = ruleMGaussianMeanPrecisionGGD(messages[351], messages[214], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_073]))\n",
      "marginals[:z_074_z_073] = ruleMGaussianMeanPrecisionGGD(messages[349], messages[217], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_074]))\n",
      "marginals[:z_075_z_074] = ruleMGaussianMeanPrecisionGGD(messages[347], messages[220], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_075]))\n",
      "marginals[:z_076_z_075] = ruleMGaussianMeanPrecisionGGD(messages[345], messages[223], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_076]))\n",
      "marginals[:z_077_z_076] = ruleMGaussianMeanPrecisionGGD(messages[343], messages[226], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_077]))\n",
      "marginals[:z_078_z_077] = ruleMGaussianMeanPrecisionGGD(messages[341], messages[229], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_078]))\n",
      "marginals[:z_079_z_078] = ruleMGaussianMeanPrecisionGGD(messages[339], messages[232], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_079]))\n",
      "marginals[:z_080_z_079] = ruleMGaussianMeanPrecisionGGD(messages[337], messages[235], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_080]))\n",
      "marginals[:z_081_z_080] = ruleMGaussianMeanPrecisionGGD(messages[335], messages[238], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_081]))\n",
      "marginals[:z_082_z_081] = ruleMGaussianMeanPrecisionGGD(messages[333], messages[241], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_082]))\n",
      "marginals[:z_083_z_082] = ruleMGaussianMeanPrecisionGGD(messages[331], messages[244], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_083]))\n",
      "marginals[:z_084_z_083] = ruleMGaussianMeanPrecisionGGD(messages[329], messages[247], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_084]))\n",
      "marginals[:z_085_z_084] = ruleMGaussianMeanPrecisionGGD(messages[327], messages[250], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_085]))\n",
      "marginals[:z_086_z_085] = ruleMGaussianMeanPrecisionGGD(messages[325], messages[253], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_086]))\n",
      "marginals[:z_087_z_086] = ruleMGaussianMeanPrecisionGGD(messages[323], messages[256], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_087]))\n",
      "marginals[:z_088_z_087] = ruleMGaussianMeanPrecisionGGD(messages[321], messages[259], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_088]))\n",
      "marginals[:z_089_z_088] = ruleMGaussianMeanPrecisionGGD(messages[319], messages[262], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_089]))\n",
      "marginals[:z_090_z_089] = ruleMGaussianMeanPrecisionGGD(messages[317], messages[265], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_090]))\n",
      "marginals[:z_091_z_090] = ruleMGaussianMeanPrecisionGGD(messages[315], messages[268], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_091]))\n",
      "marginals[:z_092_z_091] = ruleMGaussianMeanPrecisionGGD(messages[313], messages[271], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_092]))\n",
      "marginals[:z_093_z_092] = ruleMGaussianMeanPrecisionGGD(messages[311], messages[274], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_093]))\n",
      "marginals[:z_094_z_093] = ruleMGaussianMeanPrecisionGGD(messages[309], messages[277], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_094]))\n",
      "marginals[:z_095_z_094] = ruleMGaussianMeanPrecisionGGD(messages[307], messages[280], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_095]))\n",
      "marginals[:z_096_z_095] = ruleMGaussianMeanPrecisionGGD(messages[305], messages[283], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_096]))\n",
      "marginals[:z_097_z_096] = ruleMGaussianMeanPrecisionGGD(messages[303], messages[286], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_097]))\n",
      "marginals[:z_098_z_097] = ruleMGaussianMeanPrecisionGGD(messages[301], messages[289], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_098]))\n",
      "marginals[:z_099_z_098] = ruleMGaussianMeanPrecisionGGD(messages[299], messages[292], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_099]))\n",
      "marginals[:z_100_z_099] = ruleMGaussianMeanPrecisionFGD(messages[297], messages[295], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_100]))\n",
      "\n",
      "return marginals\n",
      "\n",
      "end\n",
      "\n",
      "function stepA!(data::Dict, marginals::Dict=Dict(), messages::Vector{Message}=Array{Message}(undef, 198); dump::Union{GraphDump, Nothing} = nothing)\n",
      "\n",
      "messages[1] = ruleVBDirichletOut(nothing, ProbabilityDistribution(MatrixVariate, PointMass, m=[1.0 1.0 1.0; 1.0 1.0 1.0; 1.0 1.0 1.0]))\n",
      "messages[2] = ruleSVBTransitionADV(marginals[:s_099_s_098], nothing)\n",
      "messages[3] = ruleSVBTransitionADV(marginals[:s_100_s_099], nothing)\n",
      "messages[4] = ruleSPEqualityDirichlet(messages[2], nothing, messages[3])\n",
      "messages[5] = ruleSVBTransitionADV(marginals[:s_098_s_097], nothing)\n",
      "messages[6] = ruleSPEqualityDirichlet(messages[5], nothing, messages[4])\n",
      "messages[7] = ruleSVBTransitionADV(marginals[:s_097_s_096], nothing)\n",
      "messages[8] = ruleSPEqualityDirichlet(messages[7], nothing, messages[6])\n",
      "messages[9] = ruleSVBTransitionADV(marginals[:s_096_s_095], nothing)\n",
      "messages[10] = ruleSPEqualityDirichlet(messages[9], nothing, messages[8])\n",
      "messages[11] = ruleSVBTransitionADV(marginals[:s_095_s_094], nothing)\n",
      "messages[12] = ruleSPEqualityDirichlet(messages[11], nothing, messages[10])\n",
      "messages[13] = ruleSVBTransitionADV(marginals[:s_094_s_093], nothing)\n",
      "messages[14] = ruleSPEqualityDirichlet(messages[13], nothing, messages[12])\n",
      "messages[15] = ruleSVBTransitionADV(marginals[:s_093_s_092], nothing)\n",
      "messages[16] = ruleSPEqualityDirichlet(messages[15], nothing, messages[14])\n",
      "messages[17] = ruleSVBTransitionADV(marginals[:s_092_s_091], nothing)\n",
      "messages[18] = ruleSPEqualityDirichlet(messages[17], nothing, messages[16])\n",
      "messages[19] = ruleSVBTransitionADV(marginals[:s_091_s_090], nothing)\n",
      "messages[20] = ruleSPEqualityDirichlet(messages[19], nothing, messages[18])\n",
      "messages[21] = ruleSVBTransitionADV(marginals[:s_090_s_089], nothing)\n",
      "messages[22] = ruleSPEqualityDirichlet(messages[21], nothing, messages[20])\n",
      "messages[23] = ruleSVBTransitionADV(marginals[:s_089_s_088], nothing)\n",
      "messages[24] = ruleSPEqualityDirichlet(messages[23], nothing, messages[22])\n",
      "messages[25] = ruleSVBTransitionADV(marginals[:s_088_s_087], nothing)\n",
      "messages[26] = ruleSPEqualityDirichlet(messages[25], nothing, messages[24])\n",
      "messages[27] = ruleSVBTransitionADV(marginals[:s_087_s_086], nothing)\n",
      "messages[28] = ruleSPEqualityDirichlet(messages[27], nothing, messages[26])\n",
      "messages[29] = ruleSVBTransitionADV(marginals[:s_086_s_085], nothing)\n",
      "messages[30] = ruleSPEqualityDirichlet(messages[29], nothing, messages[28])\n",
      "messages[31] = ruleSVBTransitionADV(marginals[:s_085_s_084], nothing)\n",
      "messages[32] = ruleSPEqualityDirichlet(messages[31], nothing, messages[30])\n",
      "messages[33] = ruleSVBTransitionADV(marginals[:s_084_s_083], nothing)\n",
      "messages[34] = ruleSPEqualityDirichlet(messages[33], nothing, messages[32])\n",
      "messages[35] = ruleSVBTransitionADV(marginals[:s_083_s_082], nothing)\n",
      "messages[36] = ruleSPEqualityDirichlet(messages[35], nothing, messages[34])\n",
      "messages[37] = ruleSVBTransitionADV(marginals[:s_082_s_081], nothing)\n",
      "messages[38] = ruleSPEqualityDirichlet(messages[37], nothing, messages[36])\n",
      "messages[39] = ruleSVBTransitionADV(marginals[:s_081_s_080], nothing)\n",
      "messages[40] = ruleSPEqualityDirichlet(messages[39], nothing, messages[38])\n",
      "messages[41] = ruleSVBTransitionADV(marginals[:s_080_s_079], nothing)\n",
      "messages[42] = ruleSPEqualityDirichlet(messages[41], nothing, messages[40])\n",
      "messages[43] = ruleSVBTransitionADV(marginals[:s_079_s_078], nothing)\n",
      "messages[44] = ruleSPEqualityDirichlet(messages[43], nothing, messages[42])\n",
      "messages[45] = ruleSVBTransitionADV(marginals[:s_078_s_077], nothing)\n",
      "messages[46] = ruleSPEqualityDirichlet(messages[45], nothing, messages[44])\n",
      "messages[47] = ruleSVBTransitionADV(marginals[:s_077_s_076], nothing)\n",
      "messages[48] = ruleSPEqualityDirichlet(messages[47], nothing, messages[46])\n",
      "messages[49] = ruleSVBTransitionADV(marginals[:s_076_s_075], nothing)\n",
      "messages[50] = ruleSPEqualityDirichlet(messages[49], nothing, messages[48])\n",
      "messages[51] = ruleSVBTransitionADV(marginals[:s_075_s_074], nothing)\n",
      "messages[52] = ruleSPEqualityDirichlet(messages[51], nothing, messages[50])\n",
      "messages[53] = ruleSVBTransitionADV(marginals[:s_074_s_073], nothing)\n",
      "messages[54] = ruleSPEqualityDirichlet(messages[53], nothing, messages[52])\n",
      "messages[55] = ruleSVBTransitionADV(marginals[:s_073_s_072], nothing)\n",
      "messages[56] = ruleSPEqualityDirichlet(messages[55], nothing, messages[54])\n",
      "messages[57] = ruleSVBTransitionADV(marginals[:s_072_s_071], nothing)\n",
      "messages[58] = ruleSPEqualityDirichlet(messages[57], nothing, messages[56])\n",
      "messages[59] = ruleSVBTransitionADV(marginals[:s_071_s_070], nothing)\n",
      "messages[60] = ruleSPEqualityDirichlet(messages[59], nothing, messages[58])\n",
      "messages[61] = ruleSVBTransitionADV(marginals[:s_070_s_069], nothing)\n",
      "messages[62] = ruleSPEqualityDirichlet(messages[61], nothing, messages[60])\n",
      "messages[63] = ruleSVBTransitionADV(marginals[:s_069_s_068], nothing)\n",
      "messages[64] = ruleSPEqualityDirichlet(messages[63], nothing, messages[62])\n",
      "messages[65] = ruleSVBTransitionADV(marginals[:s_068_s_067], nothing)\n",
      "messages[66] = ruleSPEqualityDirichlet(messages[65], nothing, messages[64])\n",
      "messages[67] = ruleSVBTransitionADV(marginals[:s_067_s_066], nothing)\n",
      "messages[68] = ruleSPEqualityDirichlet(messages[67], nothing, messages[66])\n",
      "messages[69] = ruleSVBTransitionADV(marginals[:s_066_s_065], nothing)\n",
      "messages[70] = ruleSPEqualityDirichlet(messages[69], nothing, messages[68])\n",
      "messages[71] = ruleSVBTransitionADV(marginals[:s_065_s_064], nothing)\n",
      "messages[72] = ruleSPEqualityDirichlet(messages[71], nothing, messages[70])\n",
      "messages[73] = ruleSVBTransitionADV(marginals[:s_064_s_063], nothing)\n",
      "messages[74] = ruleSPEqualityDirichlet(messages[73], nothing, messages[72])\n",
      "messages[75] = ruleSVBTransitionADV(marginals[:s_063_s_062], nothing)\n",
      "messages[76] = ruleSPEqualityDirichlet(messages[75], nothing, messages[74])\n",
      "messages[77] = ruleSVBTransitionADV(marginals[:s_062_s_061], nothing)\n",
      "messages[78] = ruleSPEqualityDirichlet(messages[77], nothing, messages[76])\n",
      "messages[79] = ruleSVBTransitionADV(marginals[:s_061_s_060], nothing)\n",
      "messages[80] = ruleSPEqualityDirichlet(messages[79], nothing, messages[78])\n",
      "messages[81] = ruleSVBTransitionADV(marginals[:s_060_s_059], nothing)\n",
      "messages[82] = ruleSPEqualityDirichlet(messages[81], nothing, messages[80])\n",
      "messages[83] = ruleSVBTransitionADV(marginals[:s_059_s_058], nothing)\n",
      "messages[84] = ruleSPEqualityDirichlet(messages[83], nothing, messages[82])\n",
      "messages[85] = ruleSVBTransitionADV(marginals[:s_058_s_057], nothing)\n",
      "messages[86] = ruleSPEqualityDirichlet(messages[85], nothing, messages[84])\n",
      "messages[87] = ruleSVBTransitionADV(marginals[:s_057_s_056], nothing)\n",
      "messages[88] = ruleSPEqualityDirichlet(messages[87], nothing, messages[86])\n",
      "messages[89] = ruleSVBTransitionADV(marginals[:s_056_s_055], nothing)\n",
      "messages[90] = ruleSPEqualityDirichlet(messages[89], nothing, messages[88])\n",
      "messages[91] = ruleSVBTransitionADV(marginals[:s_055_s_054], nothing)\n",
      "messages[92] = ruleSPEqualityDirichlet(messages[91], nothing, messages[90])\n",
      "messages[93] = ruleSVBTransitionADV(marginals[:s_054_s_053], nothing)\n",
      "messages[94] = ruleSPEqualityDirichlet(messages[93], nothing, messages[92])\n",
      "messages[95] = ruleSVBTransitionADV(marginals[:s_053_s_052], nothing)\n",
      "messages[96] = ruleSPEqualityDirichlet(messages[95], nothing, messages[94])\n",
      "messages[97] = ruleSVBTransitionADV(marginals[:s_052_s_051], nothing)\n",
      "messages[98] = ruleSPEqualityDirichlet(messages[97], nothing, messages[96])\n",
      "messages[99] = ruleSVBTransitionADV(marginals[:s_051_s_050], nothing)\n",
      "messages[100] = ruleSPEqualityDirichlet(messages[99], nothing, messages[98])\n",
      "messages[101] = ruleSVBTransitionADV(marginals[:s_050_s_049], nothing)\n",
      "messages[102] = ruleSPEqualityDirichlet(messages[101], nothing, messages[100])\n",
      "messages[103] = ruleSVBTransitionADV(marginals[:s_049_s_048], nothing)\n",
      "messages[104] = ruleSPEqualityDirichlet(messages[103], nothing, messages[102])\n",
      "messages[105] = ruleSVBTransitionADV(marginals[:s_048_s_047], nothing)\n",
      "messages[106] = ruleSPEqualityDirichlet(messages[105], nothing, messages[104])\n",
      "messages[107] = ruleSVBTransitionADV(marginals[:s_047_s_046], nothing)\n",
      "messages[108] = ruleSPEqualityDirichlet(messages[107], nothing, messages[106])\n",
      "messages[109] = ruleSVBTransitionADV(marginals[:s_046_s_045], nothing)\n",
      "messages[110] = ruleSPEqualityDirichlet(messages[109], nothing, messages[108])\n",
      "messages[111] = ruleSVBTransitionADV(marginals[:s_045_s_044], nothing)\n",
      "messages[112] = ruleSPEqualityDirichlet(messages[111], nothing, messages[110])\n",
      "messages[113] = ruleSVBTransitionADV(marginals[:s_044_s_043], nothing)\n",
      "messages[114] = ruleSPEqualityDirichlet(messages[113], nothing, messages[112])\n",
      "messages[115] = ruleSVBTransitionADV(marginals[:s_043_s_042], nothing)\n",
      "messages[116] = ruleSPEqualityDirichlet(messages[115], nothing, messages[114])\n",
      "messages[117] = ruleSVBTransitionADV(marginals[:s_042_s_041], nothing)\n",
      "messages[118] = ruleSPEqualityDirichlet(messages[117], nothing, messages[116])\n",
      "messages[119] = ruleSVBTransitionADV(marginals[:s_041_s_040], nothing)\n",
      "messages[120] = ruleSPEqualityDirichlet(messages[119], nothing, messages[118])\n",
      "messages[121] = ruleSVBTransitionADV(marginals[:s_040_s_039], nothing)\n",
      "messages[122] = ruleSPEqualityDirichlet(messages[121], nothing, messages[120])\n",
      "messages[123] = ruleSVBTransitionADV(marginals[:s_039_s_038], nothing)\n",
      "messages[124] = ruleSPEqualityDirichlet(messages[123], nothing, messages[122])\n",
      "messages[125] = ruleSVBTransitionADV(marginals[:s_038_s_037], nothing)\n",
      "messages[126] = ruleSPEqualityDirichlet(messages[125], nothing, messages[124])\n",
      "messages[127] = ruleSVBTransitionADV(marginals[:s_037_s_036], nothing)\n",
      "messages[128] = ruleSPEqualityDirichlet(messages[127], nothing, messages[126])\n",
      "messages[129] = ruleSVBTransitionADV(marginals[:s_036_s_035], nothing)\n",
      "messages[130] = ruleSPEqualityDirichlet(messages[129], nothing, messages[128])\n",
      "messages[131] = ruleSVBTransitionADV(marginals[:s_035_s_034], nothing)\n",
      "messages[132] = ruleSPEqualityDirichlet(messages[131], nothing, messages[130])\n",
      "messages[133] = ruleSVBTransitionADV(marginals[:s_034_s_033], nothing)\n",
      "messages[134] = ruleSPEqualityDirichlet(messages[133], nothing, messages[132])\n",
      "messages[135] = ruleSVBTransitionADV(marginals[:s_033_s_032], nothing)\n",
      "messages[136] = ruleSPEqualityDirichlet(messages[135], nothing, messages[134])\n",
      "messages[137] = ruleSVBTransitionADV(marginals[:s_032_s_031], nothing)\n",
      "messages[138] = ruleSPEqualityDirichlet(messages[137], nothing, messages[136])\n",
      "messages[139] = ruleSVBTransitionADV(marginals[:s_031_s_030], nothing)\n",
      "messages[140] = ruleSPEqualityDirichlet(messages[139], nothing, messages[138])\n",
      "messages[141] = ruleSVBTransitionADV(marginals[:s_030_s_029], nothing)\n",
      "messages[142] = ruleSPEqualityDirichlet(messages[141], nothing, messages[140])\n",
      "messages[143] = ruleSVBTransitionADV(marginals[:s_029_s_028], nothing)\n",
      "messages[144] = ruleSPEqualityDirichlet(messages[143], nothing, messages[142])\n",
      "messages[145] = ruleSVBTransitionADV(marginals[:s_028_s_027], nothing)\n",
      "messages[146] = ruleSPEqualityDirichlet(messages[145], nothing, messages[144])\n",
      "messages[147] = ruleSVBTransitionADV(marginals[:s_027_s_026], nothing)\n",
      "messages[148] = ruleSPEqualityDirichlet(messages[147], nothing, messages[146])\n",
      "messages[149] = ruleSVBTransitionADV(marginals[:s_026_s_025], nothing)\n",
      "messages[150] = ruleSPEqualityDirichlet(messages[149], nothing, messages[148])\n",
      "messages[151] = ruleSVBTransitionADV(marginals[:s_025_s_024], nothing)\n",
      "messages[152] = ruleSPEqualityDirichlet(messages[151], nothing, messages[150])\n",
      "messages[153] = ruleSVBTransitionADV(marginals[:s_024_s_023], nothing)\n",
      "messages[154] = ruleSPEqualityDirichlet(messages[153], nothing, messages[152])\n",
      "messages[155] = ruleSVBTransitionADV(marginals[:s_023_s_022], nothing)\n",
      "messages[156] = ruleSPEqualityDirichlet(messages[155], nothing, messages[154])\n",
      "messages[157] = ruleSVBTransitionADV(marginals[:s_022_s_021], nothing)\n",
      "messages[158] = ruleSPEqualityDirichlet(messages[157], nothing, messages[156])\n",
      "messages[159] = ruleSVBTransitionADV(marginals[:s_021_s_020], nothing)\n",
      "messages[160] = ruleSPEqualityDirichlet(messages[159], nothing, messages[158])\n",
      "messages[161] = ruleSVBTransitionADV(marginals[:s_020_s_019], nothing)\n",
      "messages[162] = ruleSPEqualityDirichlet(messages[161], nothing, messages[160])\n",
      "messages[163] = ruleSVBTransitionADV(marginals[:s_019_s_018], nothing)\n",
      "messages[164] = ruleSPEqualityDirichlet(messages[163], nothing, messages[162])\n",
      "messages[165] = ruleSVBTransitionADV(marginals[:s_018_s_017], nothing)\n",
      "messages[166] = ruleSPEqualityDirichlet(messages[165], nothing, messages[164])\n",
      "messages[167] = ruleSVBTransitionADV(marginals[:s_017_s_016], nothing)\n",
      "messages[168] = ruleSPEqualityDirichlet(messages[167], nothing, messages[166])\n",
      "messages[169] = ruleSVBTransitionADV(marginals[:s_016_s_015], nothing)\n",
      "messages[170] = ruleSPEqualityDirichlet(messages[169], nothing, messages[168])\n",
      "messages[171] = ruleSVBTransitionADV(marginals[:s_015_s_014], nothing)\n",
      "messages[172] = ruleSPEqualityDirichlet(messages[171], nothing, messages[170])\n",
      "messages[173] = ruleSVBTransitionADV(marginals[:s_014_s_013], nothing)\n",
      "messages[174] = ruleSPEqualityDirichlet(messages[173], nothing, messages[172])\n",
      "messages[175] = ruleSVBTransitionADV(marginals[:s_013_s_012], nothing)\n",
      "messages[176] = ruleSPEqualityDirichlet(messages[175], nothing, messages[174])\n",
      "messages[177] = ruleSVBTransitionADV(marginals[:s_012_s_011], nothing)\n",
      "messages[178] = ruleSPEqualityDirichlet(messages[177], nothing, messages[176])\n",
      "messages[179] = ruleSVBTransitionADV(marginals[:s_011_s_010], nothing)\n",
      "messages[180] = ruleSPEqualityDirichlet(messages[179], nothing, messages[178])\n",
      "messages[181] = ruleSVBTransitionADV(marginals[:s_010_s_009], nothing)\n",
      "messages[182] = ruleSPEqualityDirichlet(messages[181], nothing, messages[180])\n",
      "messages[183] = ruleSVBTransitionADV(marginals[:s_009_s_008], nothing)\n",
      "messages[184] = ruleSPEqualityDirichlet(messages[183], nothing, messages[182])\n",
      "messages[185] = ruleSVBTransitionADV(marginals[:s_008_s_007], nothing)\n",
      "messages[186] = ruleSPEqualityDirichlet(messages[185], nothing, messages[184])\n",
      "messages[187] = ruleSVBTransitionADV(marginals[:s_007_s_006], nothing)\n",
      "messages[188] = ruleSPEqualityDirichlet(messages[187], nothing, messages[186])\n",
      "messages[189] = ruleSVBTransitionADV(marginals[:s_006_s_005], nothing)\n",
      "messages[190] = ruleSPEqualityDirichlet(messages[189], nothing, messages[188])\n",
      "messages[191] = ruleSVBTransitionADV(marginals[:s_005_s_004], nothing)\n",
      "messages[192] = ruleSPEqualityDirichlet(messages[191], nothing, messages[190])\n",
      "messages[193] = ruleSVBTransitionADV(marginals[:s_004_s_003], nothing)\n",
      "messages[194] = ruleSPEqualityDirichlet(messages[193], nothing, messages[192])\n",
      "messages[195] = ruleSVBTransitionADV(marginals[:s_003_s_002], nothing)\n",
      "messages[196] = ruleSPEqualityDirichlet(messages[195], nothing, messages[194])\n",
      "messages[197] = ruleSVBTransitionADV(marginals[:s_002_s_001], nothing)\n",
      "messages[198] = ruleSPEqualityDirichlet(nothing, messages[197], messages[196])\n",
      "\n",
      "marginals[:A] = messages[1].dist * messages[198].dist\n",
      "\n",
      "return marginals\n",
      "\n",
      "end\n",
      "\n",
      "function stepΩ!(data::Dict, marginals::Dict=Dict(), messages::Vector{Message}=Array{Message}(undef, 198); dump::Union{GraphDump, Nothing} = nothing)\n",
      "\n",
      "messages[1] = ruleVBGaussianMeanPrecisionOut(nothing, ProbabilityDistribution(Multivariate, PointMass, m=data[:mω]), ProbabilityDistribution(MatrixVariate, PointMass, m=data[:wω]))\n",
      "messages[2] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_099_x_098], marginals[:z_099], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_099])\n",
      "messages[3] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_100_x_099], marginals[:z_100], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_100])\n",
      "messages[4] = ruleSPEqualityFn(messages[2], nothing, messages[3])\n",
      "messages[5] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_098_x_097], marginals[:z_098], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_098])\n",
      "messages[6] = ruleSPEqualityFn(messages[5], nothing, messages[4])\n",
      "messages[7] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_097_x_096], marginals[:z_097], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_097])\n",
      "messages[8] = ruleSPEqualityFn(messages[7], nothing, messages[6])\n",
      "messages[9] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_096_x_095], marginals[:z_096], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_096])\n",
      "messages[10] = ruleSPEqualityFn(messages[9], nothing, messages[8])\n",
      "messages[11] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_095_x_094], marginals[:z_095], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_095])\n",
      "messages[12] = ruleSPEqualityFn(messages[11], nothing, messages[10])\n",
      "messages[13] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_094_x_093], marginals[:z_094], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_094])\n",
      "messages[14] = ruleSPEqualityFn(messages[13], nothing, messages[12])\n",
      "messages[15] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_093_x_092], marginals[:z_093], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_093])\n",
      "messages[16] = ruleSPEqualityFn(messages[15], nothing, messages[14])\n",
      "messages[17] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_092_x_091], marginals[:z_092], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_092])\n",
      "messages[18] = ruleSPEqualityFn(messages[17], nothing, messages[16])\n",
      "messages[19] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_091_x_090], marginals[:z_091], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_091])\n",
      "messages[20] = ruleSPEqualityFn(messages[19], nothing, messages[18])\n",
      "messages[21] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_090_x_089], marginals[:z_090], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_090])\n",
      "messages[22] = ruleSPEqualityFn(messages[21], nothing, messages[20])\n",
      "messages[23] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_089_x_088], marginals[:z_089], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_089])\n",
      "messages[24] = ruleSPEqualityFn(messages[23], nothing, messages[22])\n",
      "messages[25] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_088_x_087], marginals[:z_088], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_088])\n",
      "messages[26] = ruleSPEqualityFn(messages[25], nothing, messages[24])\n",
      "messages[27] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_087_x_086], marginals[:z_087], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_087])\n",
      "messages[28] = ruleSPEqualityFn(messages[27], nothing, messages[26])\n",
      "messages[29] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_086_x_085], marginals[:z_086], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_086])\n",
      "messages[30] = ruleSPEqualityFn(messages[29], nothing, messages[28])\n",
      "messages[31] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_085_x_084], marginals[:z_085], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_085])\n",
      "messages[32] = ruleSPEqualityFn(messages[31], nothing, messages[30])\n",
      "messages[33] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_084_x_083], marginals[:z_084], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_084])\n",
      "messages[34] = ruleSPEqualityFn(messages[33], nothing, messages[32])\n",
      "messages[35] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_083_x_082], marginals[:z_083], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_083])\n",
      "messages[36] = ruleSPEqualityFn(messages[35], nothing, messages[34])\n",
      "messages[37] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_082_x_081], marginals[:z_082], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_082])\n",
      "messages[38] = ruleSPEqualityFn(messages[37], nothing, messages[36])\n",
      "messages[39] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_081_x_080], marginals[:z_081], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_081])\n",
      "messages[40] = ruleSPEqualityFn(messages[39], nothing, messages[38])\n",
      "messages[41] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_080_x_079], marginals[:z_080], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_080])\n",
      "messages[42] = ruleSPEqualityFn(messages[41], nothing, messages[40])\n",
      "messages[43] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_079_x_078], marginals[:z_079], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_079])\n",
      "messages[44] = ruleSPEqualityFn(messages[43], nothing, messages[42])\n",
      "messages[45] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_078_x_077], marginals[:z_078], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_078])\n",
      "messages[46] = ruleSPEqualityFn(messages[45], nothing, messages[44])\n",
      "messages[47] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_077_x_076], marginals[:z_077], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_077])\n",
      "messages[48] = ruleSPEqualityFn(messages[47], nothing, messages[46])\n",
      "messages[49] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_076_x_075], marginals[:z_076], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_076])\n",
      "messages[50] = ruleSPEqualityFn(messages[49], nothing, messages[48])\n",
      "messages[51] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_075_x_074], marginals[:z_075], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_075])\n",
      "messages[52] = ruleSPEqualityFn(messages[51], nothing, messages[50])\n",
      "messages[53] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_074_x_073], marginals[:z_074], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_074])\n",
      "messages[54] = ruleSPEqualityFn(messages[53], nothing, messages[52])\n",
      "messages[55] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_073_x_072], marginals[:z_073], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_073])\n",
      "messages[56] = ruleSPEqualityFn(messages[55], nothing, messages[54])\n",
      "messages[57] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_072_x_071], marginals[:z_072], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_072])\n",
      "messages[58] = ruleSPEqualityFn(messages[57], nothing, messages[56])\n",
      "messages[59] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_071_x_070], marginals[:z_071], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_071])\n",
      "messages[60] = ruleSPEqualityFn(messages[59], nothing, messages[58])\n",
      "messages[61] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_070_x_069], marginals[:z_070], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_070])\n",
      "messages[62] = ruleSPEqualityFn(messages[61], nothing, messages[60])\n",
      "messages[63] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_069_x_068], marginals[:z_069], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_069])\n",
      "messages[64] = ruleSPEqualityFn(messages[63], nothing, messages[62])\n",
      "messages[65] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_068_x_067], marginals[:z_068], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_068])\n",
      "messages[66] = ruleSPEqualityFn(messages[65], nothing, messages[64])\n",
      "messages[67] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_067_x_066], marginals[:z_067], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_067])\n",
      "messages[68] = ruleSPEqualityFn(messages[67], nothing, messages[66])\n",
      "messages[69] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_066_x_065], marginals[:z_066], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_066])\n",
      "messages[70] = ruleSPEqualityFn(messages[69], nothing, messages[68])\n",
      "messages[71] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_065_x_064], marginals[:z_065], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_065])\n",
      "messages[72] = ruleSPEqualityFn(messages[71], nothing, messages[70])\n",
      "messages[73] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_064_x_063], marginals[:z_064], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_064])\n",
      "messages[74] = ruleSPEqualityFn(messages[73], nothing, messages[72])\n",
      "messages[75] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_063_x_062], marginals[:z_063], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_063])\n",
      "messages[76] = ruleSPEqualityFn(messages[75], nothing, messages[74])\n",
      "messages[77] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_062_x_061], marginals[:z_062], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_062])\n",
      "messages[78] = ruleSPEqualityFn(messages[77], nothing, messages[76])\n",
      "messages[79] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_061_x_060], marginals[:z_061], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_061])\n",
      "messages[80] = ruleSPEqualityFn(messages[79], nothing, messages[78])\n",
      "messages[81] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_060_x_059], marginals[:z_060], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_060])\n",
      "messages[82] = ruleSPEqualityFn(messages[81], nothing, messages[80])\n",
      "messages[83] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_059_x_058], marginals[:z_059], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_059])\n",
      "messages[84] = ruleSPEqualityFn(messages[83], nothing, messages[82])\n",
      "messages[85] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_058_x_057], marginals[:z_058], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_058])\n",
      "messages[86] = ruleSPEqualityFn(messages[85], nothing, messages[84])\n",
      "messages[87] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_057_x_056], marginals[:z_057], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_057])\n",
      "messages[88] = ruleSPEqualityFn(messages[87], nothing, messages[86])\n",
      "messages[89] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_056_x_055], marginals[:z_056], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_056])\n",
      "messages[90] = ruleSPEqualityFn(messages[89], nothing, messages[88])\n",
      "messages[91] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_055_x_054], marginals[:z_055], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_055])\n",
      "messages[92] = ruleSPEqualityFn(messages[91], nothing, messages[90])\n",
      "messages[93] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_054_x_053], marginals[:z_054], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_054])\n",
      "messages[94] = ruleSPEqualityFn(messages[93], nothing, messages[92])\n",
      "messages[95] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_053_x_052], marginals[:z_053], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_053])\n",
      "messages[96] = ruleSPEqualityFn(messages[95], nothing, messages[94])\n",
      "messages[97] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_052_x_051], marginals[:z_052], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_052])\n",
      "messages[98] = ruleSPEqualityFn(messages[97], nothing, messages[96])\n",
      "messages[99] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_051_x_050], marginals[:z_051], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_051])\n",
      "messages[100] = ruleSPEqualityFn(messages[99], nothing, messages[98])\n",
      "messages[101] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_050_x_049], marginals[:z_050], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_050])\n",
      "messages[102] = ruleSPEqualityFn(messages[101], nothing, messages[100])\n",
      "messages[103] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_049_x_048], marginals[:z_049], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_049])\n",
      "messages[104] = ruleSPEqualityFn(messages[103], nothing, messages[102])\n",
      "messages[105] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_048_x_047], marginals[:z_048], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_048])\n",
      "messages[106] = ruleSPEqualityFn(messages[105], nothing, messages[104])\n",
      "messages[107] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_047_x_046], marginals[:z_047], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_047])\n",
      "messages[108] = ruleSPEqualityFn(messages[107], nothing, messages[106])\n",
      "messages[109] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_046_x_045], marginals[:z_046], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_046])\n",
      "messages[110] = ruleSPEqualityFn(messages[109], nothing, messages[108])\n",
      "messages[111] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_045_x_044], marginals[:z_045], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_045])\n",
      "messages[112] = ruleSPEqualityFn(messages[111], nothing, messages[110])\n",
      "messages[113] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_044_x_043], marginals[:z_044], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_044])\n",
      "messages[114] = ruleSPEqualityFn(messages[113], nothing, messages[112])\n",
      "messages[115] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_043_x_042], marginals[:z_043], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_043])\n",
      "messages[116] = ruleSPEqualityFn(messages[115], nothing, messages[114])\n",
      "messages[117] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_042_x_041], marginals[:z_042], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_042])\n",
      "messages[118] = ruleSPEqualityFn(messages[117], nothing, messages[116])\n",
      "messages[119] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_041_x_040], marginals[:z_041], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_041])\n",
      "messages[120] = ruleSPEqualityFn(messages[119], nothing, messages[118])\n",
      "messages[121] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_040_x_039], marginals[:z_040], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_040])\n",
      "messages[122] = ruleSPEqualityFn(messages[121], nothing, messages[120])\n",
      "messages[123] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_039_x_038], marginals[:z_039], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_039])\n",
      "messages[124] = ruleSPEqualityFn(messages[123], nothing, messages[122])\n",
      "messages[125] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_038_x_037], marginals[:z_038], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_038])\n",
      "messages[126] = ruleSPEqualityFn(messages[125], nothing, messages[124])\n",
      "messages[127] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_037_x_036], marginals[:z_037], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_037])\n",
      "messages[128] = ruleSPEqualityFn(messages[127], nothing, messages[126])\n",
      "messages[129] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_036_x_035], marginals[:z_036], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_036])\n",
      "messages[130] = ruleSPEqualityFn(messages[129], nothing, messages[128])\n",
      "messages[131] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_035_x_034], marginals[:z_035], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_035])\n",
      "messages[132] = ruleSPEqualityFn(messages[131], nothing, messages[130])\n",
      "messages[133] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_034_x_033], marginals[:z_034], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_034])\n",
      "messages[134] = ruleSPEqualityFn(messages[133], nothing, messages[132])\n",
      "messages[135] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_033_x_032], marginals[:z_033], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_033])\n",
      "messages[136] = ruleSPEqualityFn(messages[135], nothing, messages[134])\n",
      "messages[137] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_032_x_031], marginals[:z_032], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_032])\n",
      "messages[138] = ruleSPEqualityFn(messages[137], nothing, messages[136])\n",
      "messages[139] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_031_x_030], marginals[:z_031], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_031])\n",
      "messages[140] = ruleSPEqualityFn(messages[139], nothing, messages[138])\n",
      "messages[141] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_030_x_029], marginals[:z_030], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_030])\n",
      "messages[142] = ruleSPEqualityFn(messages[141], nothing, messages[140])\n",
      "messages[143] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_029_x_028], marginals[:z_029], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_029])\n",
      "messages[144] = ruleSPEqualityFn(messages[143], nothing, messages[142])\n",
      "messages[145] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_028_x_027], marginals[:z_028], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_028])\n",
      "messages[146] = ruleSPEqualityFn(messages[145], nothing, messages[144])\n",
      "messages[147] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_027_x_026], marginals[:z_027], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_027])\n",
      "messages[148] = ruleSPEqualityFn(messages[147], nothing, messages[146])\n",
      "messages[149] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_026_x_025], marginals[:z_026], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_026])\n",
      "messages[150] = ruleSPEqualityFn(messages[149], nothing, messages[148])\n",
      "messages[151] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_025_x_024], marginals[:z_025], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_025])\n",
      "messages[152] = ruleSPEqualityFn(messages[151], nothing, messages[150])\n",
      "messages[153] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_024_x_023], marginals[:z_024], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_024])\n",
      "messages[154] = ruleSPEqualityFn(messages[153], nothing, messages[152])\n",
      "messages[155] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_023_x_022], marginals[:z_023], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_023])\n",
      "messages[156] = ruleSPEqualityFn(messages[155], nothing, messages[154])\n",
      "messages[157] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_022_x_021], marginals[:z_022], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_022])\n",
      "messages[158] = ruleSPEqualityFn(messages[157], nothing, messages[156])\n",
      "messages[159] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_021_x_020], marginals[:z_021], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_021])\n",
      "messages[160] = ruleSPEqualityFn(messages[159], nothing, messages[158])\n",
      "messages[161] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_020_x_019], marginals[:z_020], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_020])\n",
      "messages[162] = ruleSPEqualityFn(messages[161], nothing, messages[160])\n",
      "messages[163] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_019_x_018], marginals[:z_019], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_019])\n",
      "messages[164] = ruleSPEqualityFn(messages[163], nothing, messages[162])\n",
      "messages[165] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_018_x_017], marginals[:z_018], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_018])\n",
      "messages[166] = ruleSPEqualityFn(messages[165], nothing, messages[164])\n",
      "messages[167] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_017_x_016], marginals[:z_017], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_017])\n",
      "messages[168] = ruleSPEqualityFn(messages[167], nothing, messages[166])\n",
      "messages[169] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_016_x_015], marginals[:z_016], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_016])\n",
      "messages[170] = ruleSPEqualityFn(messages[169], nothing, messages[168])\n",
      "messages[171] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_015_x_014], marginals[:z_015], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_015])\n",
      "messages[172] = ruleSPEqualityFn(messages[171], nothing, messages[170])\n",
      "messages[173] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_014_x_013], marginals[:z_014], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_014])\n",
      "messages[174] = ruleSPEqualityFn(messages[173], nothing, messages[172])\n",
      "messages[175] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_013_x_012], marginals[:z_013], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_013])\n",
      "messages[176] = ruleSPEqualityFn(messages[175], nothing, messages[174])\n",
      "messages[177] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_012_x_011], marginals[:z_012], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_012])\n",
      "messages[178] = ruleSPEqualityFn(messages[177], nothing, messages[176])\n",
      "messages[179] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_011_x_010], marginals[:z_011], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_011])\n",
      "messages[180] = ruleSPEqualityFn(messages[179], nothing, messages[178])\n",
      "messages[181] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_010_x_009], marginals[:z_010], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_010])\n",
      "messages[182] = ruleSPEqualityFn(messages[181], nothing, messages[180])\n",
      "messages[183] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_009_x_008], marginals[:z_009], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_009])\n",
      "messages[184] = ruleSPEqualityFn(messages[183], nothing, messages[182])\n",
      "messages[185] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_008_x_007], marginals[:z_008], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_008])\n",
      "messages[186] = ruleSPEqualityFn(messages[185], nothing, messages[184])\n",
      "messages[187] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_007_x_006], marginals[:z_007], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_007])\n",
      "messages[188] = ruleSPEqualityFn(messages[187], nothing, messages[186])\n",
      "messages[189] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_006_x_005], marginals[:z_006], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_006])\n",
      "messages[190] = ruleSPEqualityFn(messages[189], nothing, messages[188])\n",
      "messages[191] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_005_x_004], marginals[:z_005], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_005])\n",
      "messages[192] = ruleSPEqualityFn(messages[191], nothing, messages[190])\n",
      "messages[193] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_004_x_003], marginals[:z_004], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_004])\n",
      "messages[194] = ruleSPEqualityFn(messages[193], nothing, messages[192])\n",
      "messages[195] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_003_x_002], marginals[:z_003], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_003])\n",
      "messages[196] = ruleSPEqualityFn(messages[195], nothing, messages[194])\n",
      "messages[197] = ruleSVBSwitchingGaussianControlledVariancePPPIn5P(marginals[:x_002_x_001], marginals[:z_002], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), nothing, marginals[:s_002])\n",
      "messages[198] = ruleSPEqualityFn(nothing, messages[197], messages[196])\n",
      "\n",
      "marginals[:ω] = messages[1].dist * messages[198].dist\n",
      "\n",
      "return marginals\n",
      "\n",
      "end\n",
      "\n",
      "function stepS!(data::Dict, marginals::Dict=Dict(), messages::Vector{Message}=Array{Message}(undef, 494); dump::Union{GraphDump, Nothing} = nothing)\n",
      "\n",
      "messages[1] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_099_x_098], marginals[:z_099], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[2] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_098_x_097], marginals[:z_098], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[3] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_097_x_096], marginals[:z_097], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[4] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_096_x_095], marginals[:z_096], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[5] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_095_x_094], marginals[:z_095], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[6] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_094_x_093], marginals[:z_094], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[7] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_093_x_092], marginals[:z_093], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[8] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_092_x_091], marginals[:z_092], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[9] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_091_x_090], marginals[:z_091], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[10] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_090_x_089], marginals[:z_090], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[11] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_089_x_088], marginals[:z_089], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[12] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_088_x_087], marginals[:z_088], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[13] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_087_x_086], marginals[:z_087], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[14] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_086_x_085], marginals[:z_086], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[15] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_085_x_084], marginals[:z_085], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[16] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_084_x_083], marginals[:z_084], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[17] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_083_x_082], marginals[:z_083], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[18] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_082_x_081], marginals[:z_082], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[19] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_081_x_080], marginals[:z_081], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[20] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_080_x_079], marginals[:z_080], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[21] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_079_x_078], marginals[:z_079], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[22] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_078_x_077], marginals[:z_078], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[23] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_077_x_076], marginals[:z_077], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[24] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_076_x_075], marginals[:z_076], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[25] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_075_x_074], marginals[:z_075], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[26] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_074_x_073], marginals[:z_074], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[27] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_073_x_072], marginals[:z_073], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[28] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_072_x_071], marginals[:z_072], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[29] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_071_x_070], marginals[:z_071], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[30] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_070_x_069], marginals[:z_070], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[31] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_069_x_068], marginals[:z_069], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[32] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_068_x_067], marginals[:z_068], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[33] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_067_x_066], marginals[:z_067], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[34] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_066_x_065], marginals[:z_066], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[35] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_065_x_064], marginals[:z_065], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[36] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_064_x_063], marginals[:z_064], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[37] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_063_x_062], marginals[:z_063], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[38] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_062_x_061], marginals[:z_062], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[39] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_061_x_060], marginals[:z_061], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[40] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_060_x_059], marginals[:z_060], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[41] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_059_x_058], marginals[:z_059], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[42] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_058_x_057], marginals[:z_058], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[43] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_057_x_056], marginals[:z_057], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[44] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_056_x_055], marginals[:z_056], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[45] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_055_x_054], marginals[:z_055], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[46] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_054_x_053], marginals[:z_054], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[47] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_053_x_052], marginals[:z_053], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[48] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_052_x_051], marginals[:z_052], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[49] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_051_x_050], marginals[:z_051], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[50] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_050_x_049], marginals[:z_050], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[51] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_049_x_048], marginals[:z_049], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[52] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_048_x_047], marginals[:z_048], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[53] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_047_x_046], marginals[:z_047], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[54] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_046_x_045], marginals[:z_046], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[55] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_045_x_044], marginals[:z_045], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[56] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_044_x_043], marginals[:z_044], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[57] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_043_x_042], marginals[:z_043], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[58] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_042_x_041], marginals[:z_042], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[59] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_041_x_040], marginals[:z_041], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[60] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_040_x_039], marginals[:z_040], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[61] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_039_x_038], marginals[:z_039], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[62] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_038_x_037], marginals[:z_038], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[63] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_037_x_036], marginals[:z_037], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[64] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_036_x_035], marginals[:z_036], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[65] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_035_x_034], marginals[:z_035], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[66] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_034_x_033], marginals[:z_034], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[67] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_033_x_032], marginals[:z_033], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[68] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_032_x_031], marginals[:z_032], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[69] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_031_x_030], marginals[:z_031], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[70] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_030_x_029], marginals[:z_030], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[71] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_029_x_028], marginals[:z_029], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[72] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_028_x_027], marginals[:z_028], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[73] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_027_x_026], marginals[:z_027], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[74] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_026_x_025], marginals[:z_026], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[75] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_025_x_024], marginals[:z_025], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[76] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_024_x_023], marginals[:z_024], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[77] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_023_x_022], marginals[:z_023], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[78] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_022_x_021], marginals[:z_022], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[79] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_021_x_020], marginals[:z_021], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[80] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_020_x_019], marginals[:z_020], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[81] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_019_x_018], marginals[:z_019], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[82] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_018_x_017], marginals[:z_018], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[83] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_017_x_016], marginals[:z_017], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[84] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_016_x_015], marginals[:z_016], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[85] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_015_x_014], marginals[:z_015], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[86] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_014_x_013], marginals[:z_014], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[87] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_013_x_012], marginals[:z_013], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[88] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_012_x_011], marginals[:z_012], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[89] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_011_x_010], marginals[:z_011], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[90] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_010_x_009], marginals[:z_010], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[91] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_009_x_008], marginals[:z_009], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[92] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_008_x_007], marginals[:z_008], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[93] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_007_x_006], marginals[:z_007], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[94] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_006_x_005], marginals[:z_006], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[95] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_005_x_004], marginals[:z_005], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[96] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_004_x_003], marginals[:z_004], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[97] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_003_x_002], marginals[:z_003], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[98] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_002_x_001], marginals[:z_002], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[99] = ruleVBCategoricalOut(nothing, ProbabilityDistribution(Multivariate, PointMass, m=[0.3333333333333333, 0.3333333333333333, 0.3333333333333333]))\n",
      "messages[100] = ruleSVBTransitionOutVCD(nothing, messages[99], marginals[:A])\n",
      "messages[101] = ruleSPEqualityCategorical(messages[100], messages[98], nothing)\n",
      "messages[102] = ruleSVBTransitionOutVCD(nothing, messages[101], marginals[:A])\n",
      "messages[103] = ruleSPEqualityCategorical(messages[102], messages[97], nothing)\n",
      "messages[104] = ruleSVBTransitionOutVCD(nothing, messages[103], marginals[:A])\n",
      "messages[105] = ruleSPEqualityCategorical(messages[104], messages[96], nothing)\n",
      "messages[106] = ruleSVBTransitionOutVCD(nothing, messages[105], marginals[:A])\n",
      "messages[107] = ruleSPEqualityCategorical(messages[106], messages[95], nothing)\n",
      "messages[108] = ruleSVBTransitionOutVCD(nothing, messages[107], marginals[:A])\n",
      "messages[109] = ruleSPEqualityCategorical(messages[108], messages[94], nothing)\n",
      "messages[110] = ruleSVBTransitionOutVCD(nothing, messages[109], marginals[:A])\n",
      "messages[111] = ruleSPEqualityCategorical(messages[110], messages[93], nothing)\n",
      "messages[112] = ruleSVBTransitionOutVCD(nothing, messages[111], marginals[:A])\n",
      "messages[113] = ruleSPEqualityCategorical(messages[112], messages[92], nothing)\n",
      "messages[114] = ruleSVBTransitionOutVCD(nothing, messages[113], marginals[:A])\n",
      "messages[115] = ruleSPEqualityCategorical(messages[114], messages[91], nothing)\n",
      "messages[116] = ruleSVBTransitionOutVCD(nothing, messages[115], marginals[:A])\n",
      "messages[117] = ruleSPEqualityCategorical(messages[116], messages[90], nothing)\n",
      "messages[118] = ruleSVBTransitionOutVCD(nothing, messages[117], marginals[:A])\n",
      "messages[119] = ruleSPEqualityCategorical(messages[118], messages[89], nothing)\n",
      "messages[120] = ruleSVBTransitionOutVCD(nothing, messages[119], marginals[:A])\n",
      "messages[121] = ruleSPEqualityCategorical(messages[120], messages[88], nothing)\n",
      "messages[122] = ruleSVBTransitionOutVCD(nothing, messages[121], marginals[:A])\n",
      "messages[123] = ruleSPEqualityCategorical(messages[122], messages[87], nothing)\n",
      "messages[124] = ruleSVBTransitionOutVCD(nothing, messages[123], marginals[:A])\n",
      "messages[125] = ruleSPEqualityCategorical(messages[124], messages[86], nothing)\n",
      "messages[126] = ruleSVBTransitionOutVCD(nothing, messages[125], marginals[:A])\n",
      "messages[127] = ruleSPEqualityCategorical(messages[126], messages[85], nothing)\n",
      "messages[128] = ruleSVBTransitionOutVCD(nothing, messages[127], marginals[:A])\n",
      "messages[129] = ruleSPEqualityCategorical(messages[128], messages[84], nothing)\n",
      "messages[130] = ruleSVBTransitionOutVCD(nothing, messages[129], marginals[:A])\n",
      "messages[131] = ruleSPEqualityCategorical(messages[130], messages[83], nothing)\n",
      "messages[132] = ruleSVBTransitionOutVCD(nothing, messages[131], marginals[:A])\n",
      "messages[133] = ruleSPEqualityCategorical(messages[132], messages[82], nothing)\n",
      "messages[134] = ruleSVBTransitionOutVCD(nothing, messages[133], marginals[:A])\n",
      "messages[135] = ruleSPEqualityCategorical(messages[134], messages[81], nothing)\n",
      "messages[136] = ruleSVBTransitionOutVCD(nothing, messages[135], marginals[:A])\n",
      "messages[137] = ruleSPEqualityCategorical(messages[136], messages[80], nothing)\n",
      "messages[138] = ruleSVBTransitionOutVCD(nothing, messages[137], marginals[:A])\n",
      "messages[139] = ruleSPEqualityCategorical(messages[138], messages[79], nothing)\n",
      "messages[140] = ruleSVBTransitionOutVCD(nothing, messages[139], marginals[:A])\n",
      "messages[141] = ruleSPEqualityCategorical(messages[140], messages[78], nothing)\n",
      "messages[142] = ruleSVBTransitionOutVCD(nothing, messages[141], marginals[:A])\n",
      "messages[143] = ruleSPEqualityCategorical(messages[142], messages[77], nothing)\n",
      "messages[144] = ruleSVBTransitionOutVCD(nothing, messages[143], marginals[:A])\n",
      "messages[145] = ruleSPEqualityCategorical(messages[144], messages[76], nothing)\n",
      "messages[146] = ruleSVBTransitionOutVCD(nothing, messages[145], marginals[:A])\n",
      "messages[147] = ruleSPEqualityCategorical(messages[146], messages[75], nothing)\n",
      "messages[148] = ruleSVBTransitionOutVCD(nothing, messages[147], marginals[:A])\n",
      "messages[149] = ruleSPEqualityCategorical(messages[148], messages[74], nothing)\n",
      "messages[150] = ruleSVBTransitionOutVCD(nothing, messages[149], marginals[:A])\n",
      "messages[151] = ruleSPEqualityCategorical(messages[150], messages[73], nothing)\n",
      "messages[152] = ruleSVBTransitionOutVCD(nothing, messages[151], marginals[:A])\n",
      "messages[153] = ruleSPEqualityCategorical(messages[152], messages[72], nothing)\n",
      "messages[154] = ruleSVBTransitionOutVCD(nothing, messages[153], marginals[:A])\n",
      "messages[155] = ruleSPEqualityCategorical(messages[154], messages[71], nothing)\n",
      "messages[156] = ruleSVBTransitionOutVCD(nothing, messages[155], marginals[:A])\n",
      "messages[157] = ruleSPEqualityCategorical(messages[156], messages[70], nothing)\n",
      "messages[158] = ruleSVBTransitionOutVCD(nothing, messages[157], marginals[:A])\n",
      "messages[159] = ruleSPEqualityCategorical(messages[158], messages[69], nothing)\n",
      "messages[160] = ruleSVBTransitionOutVCD(nothing, messages[159], marginals[:A])\n",
      "messages[161] = ruleSPEqualityCategorical(messages[160], messages[68], nothing)\n",
      "messages[162] = ruleSVBTransitionOutVCD(nothing, messages[161], marginals[:A])\n",
      "messages[163] = ruleSPEqualityCategorical(messages[162], messages[67], nothing)\n",
      "messages[164] = ruleSVBTransitionOutVCD(nothing, messages[163], marginals[:A])\n",
      "messages[165] = ruleSPEqualityCategorical(messages[164], messages[66], nothing)\n",
      "messages[166] = ruleSVBTransitionOutVCD(nothing, messages[165], marginals[:A])\n",
      "messages[167] = ruleSPEqualityCategorical(messages[166], messages[65], nothing)\n",
      "messages[168] = ruleSVBTransitionOutVCD(nothing, messages[167], marginals[:A])\n",
      "messages[169] = ruleSPEqualityCategorical(messages[168], messages[64], nothing)\n",
      "messages[170] = ruleSVBTransitionOutVCD(nothing, messages[169], marginals[:A])\n",
      "messages[171] = ruleSPEqualityCategorical(messages[170], messages[63], nothing)\n",
      "messages[172] = ruleSVBTransitionOutVCD(nothing, messages[171], marginals[:A])\n",
      "messages[173] = ruleSPEqualityCategorical(messages[172], messages[62], nothing)\n",
      "messages[174] = ruleSVBTransitionOutVCD(nothing, messages[173], marginals[:A])\n",
      "messages[175] = ruleSPEqualityCategorical(messages[174], messages[61], nothing)\n",
      "messages[176] = ruleSVBTransitionOutVCD(nothing, messages[175], marginals[:A])\n",
      "messages[177] = ruleSPEqualityCategorical(messages[176], messages[60], nothing)\n",
      "messages[178] = ruleSVBTransitionOutVCD(nothing, messages[177], marginals[:A])\n",
      "messages[179] = ruleSPEqualityCategorical(messages[178], messages[59], nothing)\n",
      "messages[180] = ruleSVBTransitionOutVCD(nothing, messages[179], marginals[:A])\n",
      "messages[181] = ruleSPEqualityCategorical(messages[180], messages[58], nothing)\n",
      "messages[182] = ruleSVBTransitionOutVCD(nothing, messages[181], marginals[:A])\n",
      "messages[183] = ruleSPEqualityCategorical(messages[182], messages[57], nothing)\n",
      "messages[184] = ruleSVBTransitionOutVCD(nothing, messages[183], marginals[:A])\n",
      "messages[185] = ruleSPEqualityCategorical(messages[184], messages[56], nothing)\n",
      "messages[186] = ruleSVBTransitionOutVCD(nothing, messages[185], marginals[:A])\n",
      "messages[187] = ruleSPEqualityCategorical(messages[186], messages[55], nothing)\n",
      "messages[188] = ruleSVBTransitionOutVCD(nothing, messages[187], marginals[:A])\n",
      "messages[189] = ruleSPEqualityCategorical(messages[188], messages[54], nothing)\n",
      "messages[190] = ruleSVBTransitionOutVCD(nothing, messages[189], marginals[:A])\n",
      "messages[191] = ruleSPEqualityCategorical(messages[190], messages[53], nothing)\n",
      "messages[192] = ruleSVBTransitionOutVCD(nothing, messages[191], marginals[:A])\n",
      "messages[193] = ruleSPEqualityCategorical(messages[192], messages[52], nothing)\n",
      "messages[194] = ruleSVBTransitionOutVCD(nothing, messages[193], marginals[:A])\n",
      "messages[195] = ruleSPEqualityCategorical(messages[194], messages[51], nothing)\n",
      "messages[196] = ruleSVBTransitionOutVCD(nothing, messages[195], marginals[:A])\n",
      "messages[197] = ruleSPEqualityCategorical(messages[196], messages[50], nothing)\n",
      "messages[198] = ruleSVBTransitionOutVCD(nothing, messages[197], marginals[:A])\n",
      "messages[199] = ruleSPEqualityCategorical(messages[198], messages[49], nothing)\n",
      "messages[200] = ruleSVBTransitionOutVCD(nothing, messages[199], marginals[:A])\n",
      "messages[201] = ruleSPEqualityCategorical(messages[200], messages[48], nothing)\n",
      "messages[202] = ruleSVBTransitionOutVCD(nothing, messages[201], marginals[:A])\n",
      "messages[203] = ruleSPEqualityCategorical(messages[202], messages[47], nothing)\n",
      "messages[204] = ruleSVBTransitionOutVCD(nothing, messages[203], marginals[:A])\n",
      "messages[205] = ruleSPEqualityCategorical(messages[204], messages[46], nothing)\n",
      "messages[206] = ruleSVBTransitionOutVCD(nothing, messages[205], marginals[:A])\n",
      "messages[207] = ruleSPEqualityCategorical(messages[206], messages[45], nothing)\n",
      "messages[208] = ruleSVBTransitionOutVCD(nothing, messages[207], marginals[:A])\n",
      "messages[209] = ruleSPEqualityCategorical(messages[208], messages[44], nothing)\n",
      "messages[210] = ruleSVBTransitionOutVCD(nothing, messages[209], marginals[:A])\n",
      "messages[211] = ruleSPEqualityCategorical(messages[210], messages[43], nothing)\n",
      "messages[212] = ruleSVBTransitionOutVCD(nothing, messages[211], marginals[:A])\n",
      "messages[213] = ruleSPEqualityCategorical(messages[212], messages[42], nothing)\n",
      "messages[214] = ruleSVBTransitionOutVCD(nothing, messages[213], marginals[:A])\n",
      "messages[215] = ruleSPEqualityCategorical(messages[214], messages[41], nothing)\n",
      "messages[216] = ruleSVBTransitionOutVCD(nothing, messages[215], marginals[:A])\n",
      "messages[217] = ruleSPEqualityCategorical(messages[216], messages[40], nothing)\n",
      "messages[218] = ruleSVBTransitionOutVCD(nothing, messages[217], marginals[:A])\n",
      "messages[219] = ruleSPEqualityCategorical(messages[218], messages[39], nothing)\n",
      "messages[220] = ruleSVBTransitionOutVCD(nothing, messages[219], marginals[:A])\n",
      "messages[221] = ruleSPEqualityCategorical(messages[220], messages[38], nothing)\n",
      "messages[222] = ruleSVBTransitionOutVCD(nothing, messages[221], marginals[:A])\n",
      "messages[223] = ruleSPEqualityCategorical(messages[222], messages[37], nothing)\n",
      "messages[224] = ruleSVBTransitionOutVCD(nothing, messages[223], marginals[:A])\n",
      "messages[225] = ruleSPEqualityCategorical(messages[224], messages[36], nothing)\n",
      "messages[226] = ruleSVBTransitionOutVCD(nothing, messages[225], marginals[:A])\n",
      "messages[227] = ruleSPEqualityCategorical(messages[226], messages[35], nothing)\n",
      "messages[228] = ruleSVBTransitionOutVCD(nothing, messages[227], marginals[:A])\n",
      "messages[229] = ruleSPEqualityCategorical(messages[228], messages[34], nothing)\n",
      "messages[230] = ruleSVBTransitionOutVCD(nothing, messages[229], marginals[:A])\n",
      "messages[231] = ruleSPEqualityCategorical(messages[230], messages[33], nothing)\n",
      "messages[232] = ruleSVBTransitionOutVCD(nothing, messages[231], marginals[:A])\n",
      "messages[233] = ruleSPEqualityCategorical(messages[232], messages[32], nothing)\n",
      "messages[234] = ruleSVBTransitionOutVCD(nothing, messages[233], marginals[:A])\n",
      "messages[235] = ruleSPEqualityCategorical(messages[234], messages[31], nothing)\n",
      "messages[236] = ruleSVBTransitionOutVCD(nothing, messages[235], marginals[:A])\n",
      "messages[237] = ruleSPEqualityCategorical(messages[236], messages[30], nothing)\n",
      "messages[238] = ruleSVBTransitionOutVCD(nothing, messages[237], marginals[:A])\n",
      "messages[239] = ruleSPEqualityCategorical(messages[238], messages[29], nothing)\n",
      "messages[240] = ruleSVBTransitionOutVCD(nothing, messages[239], marginals[:A])\n",
      "messages[241] = ruleSPEqualityCategorical(messages[240], messages[28], nothing)\n",
      "messages[242] = ruleSVBTransitionOutVCD(nothing, messages[241], marginals[:A])\n",
      "messages[243] = ruleSPEqualityCategorical(messages[242], messages[27], nothing)\n",
      "messages[244] = ruleSVBTransitionOutVCD(nothing, messages[243], marginals[:A])\n",
      "messages[245] = ruleSPEqualityCategorical(messages[244], messages[26], nothing)\n",
      "messages[246] = ruleSVBTransitionOutVCD(nothing, messages[245], marginals[:A])\n",
      "messages[247] = ruleSPEqualityCategorical(messages[246], messages[25], nothing)\n",
      "messages[248] = ruleSVBTransitionOutVCD(nothing, messages[247], marginals[:A])\n",
      "messages[249] = ruleSPEqualityCategorical(messages[248], messages[24], nothing)\n",
      "messages[250] = ruleSVBTransitionOutVCD(nothing, messages[249], marginals[:A])\n",
      "messages[251] = ruleSPEqualityCategorical(messages[250], messages[23], nothing)\n",
      "messages[252] = ruleSVBTransitionOutVCD(nothing, messages[251], marginals[:A])\n",
      "messages[253] = ruleSPEqualityCategorical(messages[252], messages[22], nothing)\n",
      "messages[254] = ruleSVBTransitionOutVCD(nothing, messages[253], marginals[:A])\n",
      "messages[255] = ruleSPEqualityCategorical(messages[254], messages[21], nothing)\n",
      "messages[256] = ruleSVBTransitionOutVCD(nothing, messages[255], marginals[:A])\n",
      "messages[257] = ruleSPEqualityCategorical(messages[256], messages[20], nothing)\n",
      "messages[258] = ruleSVBTransitionOutVCD(nothing, messages[257], marginals[:A])\n",
      "messages[259] = ruleSPEqualityCategorical(messages[258], messages[19], nothing)\n",
      "messages[260] = ruleSVBTransitionOutVCD(nothing, messages[259], marginals[:A])\n",
      "messages[261] = ruleSPEqualityCategorical(messages[260], messages[18], nothing)\n",
      "messages[262] = ruleSVBTransitionOutVCD(nothing, messages[261], marginals[:A])\n",
      "messages[263] = ruleSPEqualityCategorical(messages[262], messages[17], nothing)\n",
      "messages[264] = ruleSVBTransitionOutVCD(nothing, messages[263], marginals[:A])\n",
      "messages[265] = ruleSPEqualityCategorical(messages[264], messages[16], nothing)\n",
      "messages[266] = ruleSVBTransitionOutVCD(nothing, messages[265], marginals[:A])\n",
      "messages[267] = ruleSPEqualityCategorical(messages[266], messages[15], nothing)\n",
      "messages[268] = ruleSVBTransitionOutVCD(nothing, messages[267], marginals[:A])\n",
      "messages[269] = ruleSPEqualityCategorical(messages[268], messages[14], nothing)\n",
      "messages[270] = ruleSVBTransitionOutVCD(nothing, messages[269], marginals[:A])\n",
      "messages[271] = ruleSPEqualityCategorical(messages[270], messages[13], nothing)\n",
      "messages[272] = ruleSVBTransitionOutVCD(nothing, messages[271], marginals[:A])\n",
      "messages[273] = ruleSPEqualityCategorical(messages[272], messages[12], nothing)\n",
      "messages[274] = ruleSVBTransitionOutVCD(nothing, messages[273], marginals[:A])\n",
      "messages[275] = ruleSPEqualityCategorical(messages[274], messages[11], nothing)\n",
      "messages[276] = ruleSVBTransitionOutVCD(nothing, messages[275], marginals[:A])\n",
      "messages[277] = ruleSPEqualityCategorical(messages[276], messages[10], nothing)\n",
      "messages[278] = ruleSVBTransitionOutVCD(nothing, messages[277], marginals[:A])\n",
      "messages[279] = ruleSPEqualityCategorical(messages[278], messages[9], nothing)\n",
      "messages[280] = ruleSVBTransitionOutVCD(nothing, messages[279], marginals[:A])\n",
      "messages[281] = ruleSPEqualityCategorical(messages[280], messages[8], nothing)\n",
      "messages[282] = ruleSVBTransitionOutVCD(nothing, messages[281], marginals[:A])\n",
      "messages[283] = ruleSPEqualityCategorical(messages[282], messages[7], nothing)\n",
      "messages[284] = ruleSVBTransitionOutVCD(nothing, messages[283], marginals[:A])\n",
      "messages[285] = ruleSPEqualityCategorical(messages[284], messages[6], nothing)\n",
      "messages[286] = ruleSVBTransitionOutVCD(nothing, messages[285], marginals[:A])\n",
      "messages[287] = ruleSPEqualityCategorical(messages[286], messages[5], nothing)\n",
      "messages[288] = ruleSVBTransitionOutVCD(nothing, messages[287], marginals[:A])\n",
      "messages[289] = ruleSPEqualityCategorical(messages[288], messages[4], nothing)\n",
      "messages[290] = ruleSVBTransitionOutVCD(nothing, messages[289], marginals[:A])\n",
      "messages[291] = ruleSPEqualityCategorical(messages[290], messages[3], nothing)\n",
      "messages[292] = ruleSVBTransitionOutVCD(nothing, messages[291], marginals[:A])\n",
      "messages[293] = ruleSPEqualityCategorical(messages[292], messages[2], nothing)\n",
      "messages[294] = ruleSVBTransitionOutVCD(nothing, messages[293], marginals[:A])\n",
      "messages[295] = ruleSPEqualityCategorical(messages[294], messages[1], nothing)\n",
      "messages[296] = ruleSVBTransitionOutVCD(nothing, messages[295], marginals[:A])\n",
      "messages[297] = ruleSVBSwitchingGaussianControlledVariancePPPPIn6(marginals[:x_100_x_099], marginals[:z_100], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], nothing)\n",
      "messages[298] = ruleSVBTransitionIn1CVD(messages[297], nothing, marginals[:A])\n",
      "messages[299] = ruleSPEqualityCategorical(nothing, messages[1], messages[298])\n",
      "messages[300] = ruleSVBTransitionIn1CVD(messages[299], nothing, marginals[:A])\n",
      "messages[301] = ruleSPEqualityCategorical(nothing, messages[2], messages[300])\n",
      "messages[302] = ruleSVBTransitionIn1CVD(messages[301], nothing, marginals[:A])\n",
      "messages[303] = ruleSPEqualityCategorical(nothing, messages[3], messages[302])\n",
      "messages[304] = ruleSVBTransitionIn1CVD(messages[303], nothing, marginals[:A])\n",
      "messages[305] = ruleSPEqualityCategorical(nothing, messages[4], messages[304])\n",
      "messages[306] = ruleSVBTransitionIn1CVD(messages[305], nothing, marginals[:A])\n",
      "messages[307] = ruleSPEqualityCategorical(nothing, messages[5], messages[306])\n",
      "messages[308] = ruleSVBTransitionIn1CVD(messages[307], nothing, marginals[:A])\n",
      "messages[309] = ruleSPEqualityCategorical(nothing, messages[6], messages[308])\n",
      "messages[310] = ruleSVBTransitionIn1CVD(messages[309], nothing, marginals[:A])\n",
      "messages[311] = ruleSPEqualityCategorical(nothing, messages[7], messages[310])\n",
      "messages[312] = ruleSVBTransitionIn1CVD(messages[311], nothing, marginals[:A])\n",
      "messages[313] = ruleSPEqualityCategorical(nothing, messages[8], messages[312])\n",
      "messages[314] = ruleSVBTransitionIn1CVD(messages[313], nothing, marginals[:A])\n",
      "messages[315] = ruleSPEqualityCategorical(nothing, messages[9], messages[314])\n",
      "messages[316] = ruleSVBTransitionIn1CVD(messages[315], nothing, marginals[:A])\n",
      "messages[317] = ruleSPEqualityCategorical(nothing, messages[10], messages[316])\n",
      "messages[318] = ruleSVBTransitionIn1CVD(messages[317], nothing, marginals[:A])\n",
      "messages[319] = ruleSPEqualityCategorical(nothing, messages[11], messages[318])\n",
      "messages[320] = ruleSVBTransitionIn1CVD(messages[319], nothing, marginals[:A])\n",
      "messages[321] = ruleSPEqualityCategorical(nothing, messages[12], messages[320])\n",
      "messages[322] = ruleSVBTransitionIn1CVD(messages[321], nothing, marginals[:A])\n",
      "messages[323] = ruleSPEqualityCategorical(nothing, messages[13], messages[322])\n",
      "messages[324] = ruleSVBTransitionIn1CVD(messages[323], nothing, marginals[:A])\n",
      "messages[325] = ruleSPEqualityCategorical(nothing, messages[14], messages[324])\n",
      "messages[326] = ruleSVBTransitionIn1CVD(messages[325], nothing, marginals[:A])\n",
      "messages[327] = ruleSPEqualityCategorical(nothing, messages[15], messages[326])\n",
      "messages[328] = ruleSVBTransitionIn1CVD(messages[327], nothing, marginals[:A])\n",
      "messages[329] = ruleSPEqualityCategorical(nothing, messages[16], messages[328])\n",
      "messages[330] = ruleSVBTransitionIn1CVD(messages[329], nothing, marginals[:A])\n",
      "messages[331] = ruleSPEqualityCategorical(nothing, messages[17], messages[330])\n",
      "messages[332] = ruleSVBTransitionIn1CVD(messages[331], nothing, marginals[:A])\n",
      "messages[333] = ruleSPEqualityCategorical(nothing, messages[18], messages[332])\n",
      "messages[334] = ruleSVBTransitionIn1CVD(messages[333], nothing, marginals[:A])\n",
      "messages[335] = ruleSPEqualityCategorical(nothing, messages[19], messages[334])\n",
      "messages[336] = ruleSVBTransitionIn1CVD(messages[335], nothing, marginals[:A])\n",
      "messages[337] = ruleSPEqualityCategorical(nothing, messages[20], messages[336])\n",
      "messages[338] = ruleSVBTransitionIn1CVD(messages[337], nothing, marginals[:A])\n",
      "messages[339] = ruleSPEqualityCategorical(nothing, messages[21], messages[338])\n",
      "messages[340] = ruleSVBTransitionIn1CVD(messages[339], nothing, marginals[:A])\n",
      "messages[341] = ruleSPEqualityCategorical(nothing, messages[22], messages[340])\n",
      "messages[342] = ruleSVBTransitionIn1CVD(messages[341], nothing, marginals[:A])\n",
      "messages[343] = ruleSPEqualityCategorical(nothing, messages[23], messages[342])\n",
      "messages[344] = ruleSVBTransitionIn1CVD(messages[343], nothing, marginals[:A])\n",
      "messages[345] = ruleSPEqualityCategorical(nothing, messages[24], messages[344])\n",
      "messages[346] = ruleSVBTransitionIn1CVD(messages[345], nothing, marginals[:A])\n",
      "messages[347] = ruleSPEqualityCategorical(nothing, messages[25], messages[346])\n",
      "messages[348] = ruleSVBTransitionIn1CVD(messages[347], nothing, marginals[:A])\n",
      "messages[349] = ruleSPEqualityCategorical(nothing, messages[26], messages[348])\n",
      "messages[350] = ruleSVBTransitionIn1CVD(messages[349], nothing, marginals[:A])\n",
      "messages[351] = ruleSPEqualityCategorical(nothing, messages[27], messages[350])\n",
      "messages[352] = ruleSVBTransitionIn1CVD(messages[351], nothing, marginals[:A])\n",
      "messages[353] = ruleSPEqualityCategorical(nothing, messages[28], messages[352])\n",
      "messages[354] = ruleSVBTransitionIn1CVD(messages[353], nothing, marginals[:A])\n",
      "messages[355] = ruleSPEqualityCategorical(nothing, messages[29], messages[354])\n",
      "messages[356] = ruleSVBTransitionIn1CVD(messages[355], nothing, marginals[:A])\n",
      "messages[357] = ruleSPEqualityCategorical(nothing, messages[30], messages[356])\n",
      "messages[358] = ruleSVBTransitionIn1CVD(messages[357], nothing, marginals[:A])\n",
      "messages[359] = ruleSPEqualityCategorical(nothing, messages[31], messages[358])\n",
      "messages[360] = ruleSVBTransitionIn1CVD(messages[359], nothing, marginals[:A])\n",
      "messages[361] = ruleSPEqualityCategorical(nothing, messages[32], messages[360])\n",
      "messages[362] = ruleSVBTransitionIn1CVD(messages[361], nothing, marginals[:A])\n",
      "messages[363] = ruleSPEqualityCategorical(nothing, messages[33], messages[362])\n",
      "messages[364] = ruleSVBTransitionIn1CVD(messages[363], nothing, marginals[:A])\n",
      "messages[365] = ruleSPEqualityCategorical(nothing, messages[34], messages[364])\n",
      "messages[366] = ruleSVBTransitionIn1CVD(messages[365], nothing, marginals[:A])\n",
      "messages[367] = ruleSPEqualityCategorical(nothing, messages[35], messages[366])\n",
      "messages[368] = ruleSVBTransitionIn1CVD(messages[367], nothing, marginals[:A])\n",
      "messages[369] = ruleSPEqualityCategorical(nothing, messages[36], messages[368])\n",
      "messages[370] = ruleSVBTransitionIn1CVD(messages[369], nothing, marginals[:A])\n",
      "messages[371] = ruleSPEqualityCategorical(nothing, messages[37], messages[370])\n",
      "messages[372] = ruleSVBTransitionIn1CVD(messages[371], nothing, marginals[:A])\n",
      "messages[373] = ruleSPEqualityCategorical(nothing, messages[38], messages[372])\n",
      "messages[374] = ruleSVBTransitionIn1CVD(messages[373], nothing, marginals[:A])\n",
      "messages[375] = ruleSPEqualityCategorical(nothing, messages[39], messages[374])\n",
      "messages[376] = ruleSVBTransitionIn1CVD(messages[375], nothing, marginals[:A])\n",
      "messages[377] = ruleSPEqualityCategorical(nothing, messages[40], messages[376])\n",
      "messages[378] = ruleSVBTransitionIn1CVD(messages[377], nothing, marginals[:A])\n",
      "messages[379] = ruleSPEqualityCategorical(nothing, messages[41], messages[378])\n",
      "messages[380] = ruleSVBTransitionIn1CVD(messages[379], nothing, marginals[:A])\n",
      "messages[381] = ruleSPEqualityCategorical(nothing, messages[42], messages[380])\n",
      "messages[382] = ruleSVBTransitionIn1CVD(messages[381], nothing, marginals[:A])\n",
      "messages[383] = ruleSPEqualityCategorical(nothing, messages[43], messages[382])\n",
      "messages[384] = ruleSVBTransitionIn1CVD(messages[383], nothing, marginals[:A])\n",
      "messages[385] = ruleSPEqualityCategorical(nothing, messages[44], messages[384])\n",
      "messages[386] = ruleSVBTransitionIn1CVD(messages[385], nothing, marginals[:A])\n",
      "messages[387] = ruleSPEqualityCategorical(nothing, messages[45], messages[386])\n",
      "messages[388] = ruleSVBTransitionIn1CVD(messages[387], nothing, marginals[:A])\n",
      "messages[389] = ruleSPEqualityCategorical(nothing, messages[46], messages[388])\n",
      "messages[390] = ruleSVBTransitionIn1CVD(messages[389], nothing, marginals[:A])\n",
      "messages[391] = ruleSPEqualityCategorical(nothing, messages[47], messages[390])\n",
      "messages[392] = ruleSVBTransitionIn1CVD(messages[391], nothing, marginals[:A])\n",
      "messages[393] = ruleSPEqualityCategorical(nothing, messages[48], messages[392])\n",
      "messages[394] = ruleSVBTransitionIn1CVD(messages[393], nothing, marginals[:A])\n",
      "messages[395] = ruleSPEqualityCategorical(nothing, messages[49], messages[394])\n",
      "messages[396] = ruleSVBTransitionIn1CVD(messages[395], nothing, marginals[:A])\n",
      "messages[397] = ruleSPEqualityCategorical(nothing, messages[50], messages[396])\n",
      "messages[398] = ruleSVBTransitionIn1CVD(messages[397], nothing, marginals[:A])\n",
      "messages[399] = ruleSPEqualityCategorical(nothing, messages[51], messages[398])\n",
      "messages[400] = ruleSVBTransitionIn1CVD(messages[399], nothing, marginals[:A])\n",
      "messages[401] = ruleSPEqualityCategorical(nothing, messages[52], messages[400])\n",
      "messages[402] = ruleSVBTransitionIn1CVD(messages[401], nothing, marginals[:A])\n",
      "messages[403] = ruleSPEqualityCategorical(nothing, messages[53], messages[402])\n",
      "messages[404] = ruleSVBTransitionIn1CVD(messages[403], nothing, marginals[:A])\n",
      "messages[405] = ruleSPEqualityCategorical(nothing, messages[54], messages[404])\n",
      "messages[406] = ruleSVBTransitionIn1CVD(messages[405], nothing, marginals[:A])\n",
      "messages[407] = ruleSPEqualityCategorical(nothing, messages[55], messages[406])\n",
      "messages[408] = ruleSVBTransitionIn1CVD(messages[407], nothing, marginals[:A])\n",
      "messages[409] = ruleSPEqualityCategorical(nothing, messages[56], messages[408])\n",
      "messages[410] = ruleSVBTransitionIn1CVD(messages[409], nothing, marginals[:A])\n",
      "messages[411] = ruleSPEqualityCategorical(nothing, messages[57], messages[410])\n",
      "messages[412] = ruleSVBTransitionIn1CVD(messages[411], nothing, marginals[:A])\n",
      "messages[413] = ruleSPEqualityCategorical(nothing, messages[58], messages[412])\n",
      "messages[414] = ruleSVBTransitionIn1CVD(messages[413], nothing, marginals[:A])\n",
      "messages[415] = ruleSPEqualityCategorical(nothing, messages[59], messages[414])\n",
      "messages[416] = ruleSVBTransitionIn1CVD(messages[415], nothing, marginals[:A])\n",
      "messages[417] = ruleSPEqualityCategorical(nothing, messages[60], messages[416])\n",
      "messages[418] = ruleSVBTransitionIn1CVD(messages[417], nothing, marginals[:A])\n",
      "messages[419] = ruleSPEqualityCategorical(nothing, messages[61], messages[418])\n",
      "messages[420] = ruleSVBTransitionIn1CVD(messages[419], nothing, marginals[:A])\n",
      "messages[421] = ruleSPEqualityCategorical(nothing, messages[62], messages[420])\n",
      "messages[422] = ruleSVBTransitionIn1CVD(messages[421], nothing, marginals[:A])\n",
      "messages[423] = ruleSPEqualityCategorical(nothing, messages[63], messages[422])\n",
      "messages[424] = ruleSVBTransitionIn1CVD(messages[423], nothing, marginals[:A])\n",
      "messages[425] = ruleSPEqualityCategorical(nothing, messages[64], messages[424])\n",
      "messages[426] = ruleSVBTransitionIn1CVD(messages[425], nothing, marginals[:A])\n",
      "messages[427] = ruleSPEqualityCategorical(nothing, messages[65], messages[426])\n",
      "messages[428] = ruleSVBTransitionIn1CVD(messages[427], nothing, marginals[:A])\n",
      "messages[429] = ruleSPEqualityCategorical(nothing, messages[66], messages[428])\n",
      "messages[430] = ruleSVBTransitionIn1CVD(messages[429], nothing, marginals[:A])\n",
      "messages[431] = ruleSPEqualityCategorical(nothing, messages[67], messages[430])\n",
      "messages[432] = ruleSVBTransitionIn1CVD(messages[431], nothing, marginals[:A])\n",
      "messages[433] = ruleSPEqualityCategorical(nothing, messages[68], messages[432])\n",
      "messages[434] = ruleSVBTransitionIn1CVD(messages[433], nothing, marginals[:A])\n",
      "messages[435] = ruleSPEqualityCategorical(nothing, messages[69], messages[434])\n",
      "messages[436] = ruleSVBTransitionIn1CVD(messages[435], nothing, marginals[:A])\n",
      "messages[437] = ruleSPEqualityCategorical(nothing, messages[70], messages[436])\n",
      "messages[438] = ruleSVBTransitionIn1CVD(messages[437], nothing, marginals[:A])\n",
      "messages[439] = ruleSPEqualityCategorical(nothing, messages[71], messages[438])\n",
      "messages[440] = ruleSVBTransitionIn1CVD(messages[439], nothing, marginals[:A])\n",
      "messages[441] = ruleSPEqualityCategorical(nothing, messages[72], messages[440])\n",
      "messages[442] = ruleSVBTransitionIn1CVD(messages[441], nothing, marginals[:A])\n",
      "messages[443] = ruleSPEqualityCategorical(nothing, messages[73], messages[442])\n",
      "messages[444] = ruleSVBTransitionIn1CVD(messages[443], nothing, marginals[:A])\n",
      "messages[445] = ruleSPEqualityCategorical(nothing, messages[74], messages[444])\n",
      "messages[446] = ruleSVBTransitionIn1CVD(messages[445], nothing, marginals[:A])\n",
      "messages[447] = ruleSPEqualityCategorical(nothing, messages[75], messages[446])\n",
      "messages[448] = ruleSVBTransitionIn1CVD(messages[447], nothing, marginals[:A])\n",
      "messages[449] = ruleSPEqualityCategorical(nothing, messages[76], messages[448])\n",
      "messages[450] = ruleSVBTransitionIn1CVD(messages[449], nothing, marginals[:A])\n",
      "messages[451] = ruleSPEqualityCategorical(nothing, messages[77], messages[450])\n",
      "messages[452] = ruleSVBTransitionIn1CVD(messages[451], nothing, marginals[:A])\n",
      "messages[453] = ruleSPEqualityCategorical(nothing, messages[78], messages[452])\n",
      "messages[454] = ruleSVBTransitionIn1CVD(messages[453], nothing, marginals[:A])\n",
      "messages[455] = ruleSPEqualityCategorical(nothing, messages[79], messages[454])\n",
      "messages[456] = ruleSVBTransitionIn1CVD(messages[455], nothing, marginals[:A])\n",
      "messages[457] = ruleSPEqualityCategorical(nothing, messages[80], messages[456])\n",
      "messages[458] = ruleSVBTransitionIn1CVD(messages[457], nothing, marginals[:A])\n",
      "messages[459] = ruleSPEqualityCategorical(nothing, messages[81], messages[458])\n",
      "messages[460] = ruleSVBTransitionIn1CVD(messages[459], nothing, marginals[:A])\n",
      "messages[461] = ruleSPEqualityCategorical(nothing, messages[82], messages[460])\n",
      "messages[462] = ruleSVBTransitionIn1CVD(messages[461], nothing, marginals[:A])\n",
      "messages[463] = ruleSPEqualityCategorical(nothing, messages[83], messages[462])\n",
      "messages[464] = ruleSVBTransitionIn1CVD(messages[463], nothing, marginals[:A])\n",
      "messages[465] = ruleSPEqualityCategorical(nothing, messages[84], messages[464])\n",
      "messages[466] = ruleSVBTransitionIn1CVD(messages[465], nothing, marginals[:A])\n",
      "messages[467] = ruleSPEqualityCategorical(nothing, messages[85], messages[466])\n",
      "messages[468] = ruleSVBTransitionIn1CVD(messages[467], nothing, marginals[:A])\n",
      "messages[469] = ruleSPEqualityCategorical(nothing, messages[86], messages[468])\n",
      "messages[470] = ruleSVBTransitionIn1CVD(messages[469], nothing, marginals[:A])\n",
      "messages[471] = ruleSPEqualityCategorical(nothing, messages[87], messages[470])\n",
      "messages[472] = ruleSVBTransitionIn1CVD(messages[471], nothing, marginals[:A])\n",
      "messages[473] = ruleSPEqualityCategorical(nothing, messages[88], messages[472])\n",
      "messages[474] = ruleSVBTransitionIn1CVD(messages[473], nothing, marginals[:A])\n",
      "messages[475] = ruleSPEqualityCategorical(nothing, messages[89], messages[474])\n",
      "messages[476] = ruleSVBTransitionIn1CVD(messages[475], nothing, marginals[:A])\n",
      "messages[477] = ruleSPEqualityCategorical(nothing, messages[90], messages[476])\n",
      "messages[478] = ruleSVBTransitionIn1CVD(messages[477], nothing, marginals[:A])\n",
      "messages[479] = ruleSPEqualityCategorical(nothing, messages[91], messages[478])\n",
      "messages[480] = ruleSVBTransitionIn1CVD(messages[479], nothing, marginals[:A])\n",
      "messages[481] = ruleSPEqualityCategorical(nothing, messages[92], messages[480])\n",
      "messages[482] = ruleSVBTransitionIn1CVD(messages[481], nothing, marginals[:A])\n",
      "messages[483] = ruleSPEqualityCategorical(nothing, messages[93], messages[482])\n",
      "messages[484] = ruleSVBTransitionIn1CVD(messages[483], nothing, marginals[:A])\n",
      "messages[485] = ruleSPEqualityCategorical(nothing, messages[94], messages[484])\n",
      "messages[486] = ruleSVBTransitionIn1CVD(messages[485], nothing, marginals[:A])\n",
      "messages[487] = ruleSPEqualityCategorical(nothing, messages[95], messages[486])\n",
      "messages[488] = ruleSVBTransitionIn1CVD(messages[487], nothing, marginals[:A])\n",
      "messages[489] = ruleSPEqualityCategorical(nothing, messages[96], messages[488])\n",
      "messages[490] = ruleSVBTransitionIn1CVD(messages[489], nothing, marginals[:A])\n",
      "messages[491] = ruleSPEqualityCategorical(nothing, messages[97], messages[490])\n",
      "messages[492] = ruleSVBTransitionIn1CVD(messages[491], nothing, marginals[:A])\n",
      "messages[493] = ruleSPEqualityCategorical(nothing, messages[98], messages[492])\n",
      "messages[494] = ruleSVBTransitionIn1CVD(messages[493], nothing, marginals[:A])\n",
      "\n",
      "marginals[:s_001] = messages[99].dist * messages[494].dist\n",
      "marginals[:s_002] = messages[100].dist * messages[493].dist\n",
      "marginals[:s_003] = messages[102].dist * messages[491].dist\n",
      "marginals[:s_004] = messages[104].dist * messages[489].dist\n",
      "marginals[:s_005] = messages[106].dist * messages[487].dist\n",
      "marginals[:s_006] = messages[108].dist * messages[485].dist\n",
      "marginals[:s_007] = messages[110].dist * messages[483].dist\n",
      "marginals[:s_008] = messages[112].dist * messages[481].dist\n",
      "marginals[:s_009] = messages[114].dist * messages[479].dist\n",
      "marginals[:s_010] = messages[116].dist * messages[477].dist\n",
      "marginals[:s_011] = messages[118].dist * messages[475].dist\n",
      "marginals[:s_012] = messages[120].dist * messages[473].dist\n",
      "marginals[:s_013] = messages[122].dist * messages[471].dist\n",
      "marginals[:s_014] = messages[124].dist * messages[469].dist\n",
      "marginals[:s_015] = messages[126].dist * messages[467].dist\n",
      "marginals[:s_016] = messages[128].dist * messages[465].dist\n",
      "marginals[:s_017] = messages[130].dist * messages[463].dist\n",
      "marginals[:s_018] = messages[132].dist * messages[461].dist\n",
      "marginals[:s_019] = messages[134].dist * messages[459].dist\n",
      "marginals[:s_020] = messages[136].dist * messages[457].dist\n",
      "marginals[:s_021] = messages[138].dist * messages[455].dist\n",
      "marginals[:s_022] = messages[140].dist * messages[453].dist\n",
      "marginals[:s_023] = messages[142].dist * messages[451].dist\n",
      "marginals[:s_024] = messages[144].dist * messages[449].dist\n",
      "marginals[:s_025] = messages[146].dist * messages[447].dist\n",
      "marginals[:s_026] = messages[148].dist * messages[445].dist\n",
      "marginals[:s_027] = messages[150].dist * messages[443].dist\n",
      "marginals[:s_028] = messages[152].dist * messages[441].dist\n",
      "marginals[:s_029] = messages[154].dist * messages[439].dist\n",
      "marginals[:s_030] = messages[156].dist * messages[437].dist\n",
      "marginals[:s_031] = messages[158].dist * messages[435].dist\n",
      "marginals[:s_032] = messages[160].dist * messages[433].dist\n",
      "marginals[:s_033] = messages[162].dist * messages[431].dist\n",
      "marginals[:s_034] = messages[164].dist * messages[429].dist\n",
      "marginals[:s_035] = messages[166].dist * messages[427].dist\n",
      "marginals[:s_036] = messages[168].dist * messages[425].dist\n",
      "marginals[:s_037] = messages[170].dist * messages[423].dist\n",
      "marginals[:s_038] = messages[172].dist * messages[421].dist\n",
      "marginals[:s_039] = messages[174].dist * messages[419].dist\n",
      "marginals[:s_040] = messages[176].dist * messages[417].dist\n",
      "marginals[:s_041] = messages[178].dist * messages[415].dist\n",
      "marginals[:s_042] = messages[180].dist * messages[413].dist\n",
      "marginals[:s_043] = messages[182].dist * messages[411].dist\n",
      "marginals[:s_044] = messages[184].dist * messages[409].dist\n",
      "marginals[:s_045] = messages[186].dist * messages[407].dist\n",
      "marginals[:s_046] = messages[188].dist * messages[405].dist\n",
      "marginals[:s_047] = messages[190].dist * messages[403].dist\n",
      "marginals[:s_048] = messages[192].dist * messages[401].dist\n",
      "marginals[:s_049] = messages[194].dist * messages[399].dist\n",
      "marginals[:s_050] = messages[196].dist * messages[397].dist\n",
      "marginals[:s_051] = messages[198].dist * messages[395].dist\n",
      "marginals[:s_052] = messages[200].dist * messages[393].dist\n",
      "marginals[:s_053] = messages[202].dist * messages[391].dist\n",
      "marginals[:s_054] = messages[204].dist * messages[389].dist\n",
      "marginals[:s_055] = messages[206].dist * messages[387].dist\n",
      "marginals[:s_056] = messages[208].dist * messages[385].dist\n",
      "marginals[:s_057] = messages[210].dist * messages[383].dist\n",
      "marginals[:s_058] = messages[212].dist * messages[381].dist\n",
      "marginals[:s_059] = messages[214].dist * messages[379].dist\n",
      "marginals[:s_060] = messages[216].dist * messages[377].dist\n",
      "marginals[:s_061] = messages[218].dist * messages[375].dist\n",
      "marginals[:s_062] = messages[220].dist * messages[373].dist\n",
      "marginals[:s_063] = messages[222].dist * messages[371].dist\n",
      "marginals[:s_064] = messages[224].dist * messages[369].dist\n",
      "marginals[:s_065] = messages[226].dist * messages[367].dist\n",
      "marginals[:s_066] = messages[228].dist * messages[365].dist\n",
      "marginals[:s_067] = messages[230].dist * messages[363].dist\n",
      "marginals[:s_068] = messages[232].dist * messages[361].dist\n",
      "marginals[:s_069] = messages[234].dist * messages[359].dist\n",
      "marginals[:s_070] = messages[236].dist * messages[357].dist\n",
      "marginals[:s_071] = messages[238].dist * messages[355].dist\n",
      "marginals[:s_072] = messages[240].dist * messages[353].dist\n",
      "marginals[:s_073] = messages[242].dist * messages[351].dist\n",
      "marginals[:s_074] = messages[244].dist * messages[349].dist\n",
      "marginals[:s_075] = messages[246].dist * messages[347].dist\n",
      "marginals[:s_076] = messages[248].dist * messages[345].dist\n",
      "marginals[:s_077] = messages[250].dist * messages[343].dist\n",
      "marginals[:s_078] = messages[252].dist * messages[341].dist\n",
      "marginals[:s_079] = messages[254].dist * messages[339].dist\n",
      "marginals[:s_080] = messages[256].dist * messages[337].dist\n",
      "marginals[:s_081] = messages[258].dist * messages[335].dist\n",
      "marginals[:s_082] = messages[260].dist * messages[333].dist\n",
      "marginals[:s_083] = messages[262].dist * messages[331].dist\n",
      "marginals[:s_084] = messages[264].dist * messages[329].dist\n",
      "marginals[:s_085] = messages[266].dist * messages[327].dist\n",
      "marginals[:s_086] = messages[268].dist * messages[325].dist\n",
      "marginals[:s_087] = messages[270].dist * messages[323].dist\n",
      "marginals[:s_088] = messages[272].dist * messages[321].dist\n",
      "marginals[:s_089] = messages[274].dist * messages[319].dist\n",
      "marginals[:s_090] = messages[276].dist * messages[317].dist\n",
      "marginals[:s_091] = messages[278].dist * messages[315].dist\n",
      "marginals[:s_092] = messages[280].dist * messages[313].dist\n",
      "marginals[:s_093] = messages[282].dist * messages[311].dist\n",
      "marginals[:s_094] = messages[284].dist * messages[309].dist\n",
      "marginals[:s_095] = messages[286].dist * messages[307].dist\n",
      "marginals[:s_096] = messages[288].dist * messages[305].dist\n",
      "marginals[:s_097] = messages[290].dist * messages[303].dist\n",
      "marginals[:s_098] = messages[292].dist * messages[301].dist\n",
      "marginals[:s_099] = messages[294].dist * messages[299].dist\n",
      "marginals[:s_100] = messages[296].dist * messages[297].dist\n",
      "marginals[:s_002_s_001] = ruleMTransitionCCD(messages[493], messages[99], marginals[:A])\n",
      "marginals[:s_003_s_002] = ruleMTransitionCCD(messages[491], messages[101], marginals[:A])\n",
      "marginals[:s_004_s_003] = ruleMTransitionCCD(messages[489], messages[103], marginals[:A])\n",
      "marginals[:s_005_s_004] = ruleMTransitionCCD(messages[487], messages[105], marginals[:A])\n",
      "marginals[:s_006_s_005] = ruleMTransitionCCD(messages[485], messages[107], marginals[:A])\n",
      "marginals[:s_007_s_006] = ruleMTransitionCCD(messages[483], messages[109], marginals[:A])\n",
      "marginals[:s_008_s_007] = ruleMTransitionCCD(messages[481], messages[111], marginals[:A])\n",
      "marginals[:s_009_s_008] = ruleMTransitionCCD(messages[479], messages[113], marginals[:A])\n",
      "marginals[:s_010_s_009] = ruleMTransitionCCD(messages[477], messages[115], marginals[:A])\n",
      "marginals[:s_011_s_010] = ruleMTransitionCCD(messages[475], messages[117], marginals[:A])\n",
      "marginals[:s_012_s_011] = ruleMTransitionCCD(messages[473], messages[119], marginals[:A])\n",
      "marginals[:s_013_s_012] = ruleMTransitionCCD(messages[471], messages[121], marginals[:A])\n",
      "marginals[:s_014_s_013] = ruleMTransitionCCD(messages[469], messages[123], marginals[:A])\n",
      "marginals[:s_015_s_014] = ruleMTransitionCCD(messages[467], messages[125], marginals[:A])\n",
      "marginals[:s_016_s_015] = ruleMTransitionCCD(messages[465], messages[127], marginals[:A])\n",
      "marginals[:s_017_s_016] = ruleMTransitionCCD(messages[463], messages[129], marginals[:A])\n",
      "marginals[:s_018_s_017] = ruleMTransitionCCD(messages[461], messages[131], marginals[:A])\n",
      "marginals[:s_019_s_018] = ruleMTransitionCCD(messages[459], messages[133], marginals[:A])\n",
      "marginals[:s_020_s_019] = ruleMTransitionCCD(messages[457], messages[135], marginals[:A])\n",
      "marginals[:s_021_s_020] = ruleMTransitionCCD(messages[455], messages[137], marginals[:A])\n",
      "marginals[:s_022_s_021] = ruleMTransitionCCD(messages[453], messages[139], marginals[:A])\n",
      "marginals[:s_023_s_022] = ruleMTransitionCCD(messages[451], messages[141], marginals[:A])\n",
      "marginals[:s_024_s_023] = ruleMTransitionCCD(messages[449], messages[143], marginals[:A])\n",
      "marginals[:s_025_s_024] = ruleMTransitionCCD(messages[447], messages[145], marginals[:A])\n",
      "marginals[:s_026_s_025] = ruleMTransitionCCD(messages[445], messages[147], marginals[:A])\n",
      "marginals[:s_027_s_026] = ruleMTransitionCCD(messages[443], messages[149], marginals[:A])\n",
      "marginals[:s_028_s_027] = ruleMTransitionCCD(messages[441], messages[151], marginals[:A])\n",
      "marginals[:s_029_s_028] = ruleMTransitionCCD(messages[439], messages[153], marginals[:A])\n",
      "marginals[:s_030_s_029] = ruleMTransitionCCD(messages[437], messages[155], marginals[:A])\n",
      "marginals[:s_031_s_030] = ruleMTransitionCCD(messages[435], messages[157], marginals[:A])\n",
      "marginals[:s_032_s_031] = ruleMTransitionCCD(messages[433], messages[159], marginals[:A])\n",
      "marginals[:s_033_s_032] = ruleMTransitionCCD(messages[431], messages[161], marginals[:A])\n",
      "marginals[:s_034_s_033] = ruleMTransitionCCD(messages[429], messages[163], marginals[:A])\n",
      "marginals[:s_035_s_034] = ruleMTransitionCCD(messages[427], messages[165], marginals[:A])\n",
      "marginals[:s_036_s_035] = ruleMTransitionCCD(messages[425], messages[167], marginals[:A])\n",
      "marginals[:s_037_s_036] = ruleMTransitionCCD(messages[423], messages[169], marginals[:A])\n",
      "marginals[:s_038_s_037] = ruleMTransitionCCD(messages[421], messages[171], marginals[:A])\n",
      "marginals[:s_039_s_038] = ruleMTransitionCCD(messages[419], messages[173], marginals[:A])\n",
      "marginals[:s_040_s_039] = ruleMTransitionCCD(messages[417], messages[175], marginals[:A])\n",
      "marginals[:s_041_s_040] = ruleMTransitionCCD(messages[415], messages[177], marginals[:A])\n",
      "marginals[:s_042_s_041] = ruleMTransitionCCD(messages[413], messages[179], marginals[:A])\n",
      "marginals[:s_043_s_042] = ruleMTransitionCCD(messages[411], messages[181], marginals[:A])\n",
      "marginals[:s_044_s_043] = ruleMTransitionCCD(messages[409], messages[183], marginals[:A])\n",
      "marginals[:s_045_s_044] = ruleMTransitionCCD(messages[407], messages[185], marginals[:A])\n",
      "marginals[:s_046_s_045] = ruleMTransitionCCD(messages[405], messages[187], marginals[:A])\n",
      "marginals[:s_047_s_046] = ruleMTransitionCCD(messages[403], messages[189], marginals[:A])\n",
      "marginals[:s_048_s_047] = ruleMTransitionCCD(messages[401], messages[191], marginals[:A])\n",
      "marginals[:s_049_s_048] = ruleMTransitionCCD(messages[399], messages[193], marginals[:A])\n",
      "marginals[:s_050_s_049] = ruleMTransitionCCD(messages[397], messages[195], marginals[:A])\n",
      "marginals[:s_051_s_050] = ruleMTransitionCCD(messages[395], messages[197], marginals[:A])\n",
      "marginals[:s_052_s_051] = ruleMTransitionCCD(messages[393], messages[199], marginals[:A])\n",
      "marginals[:s_053_s_052] = ruleMTransitionCCD(messages[391], messages[201], marginals[:A])\n",
      "marginals[:s_054_s_053] = ruleMTransitionCCD(messages[389], messages[203], marginals[:A])\n",
      "marginals[:s_055_s_054] = ruleMTransitionCCD(messages[387], messages[205], marginals[:A])\n",
      "marginals[:s_056_s_055] = ruleMTransitionCCD(messages[385], messages[207], marginals[:A])\n",
      "marginals[:s_057_s_056] = ruleMTransitionCCD(messages[383], messages[209], marginals[:A])\n",
      "marginals[:s_058_s_057] = ruleMTransitionCCD(messages[381], messages[211], marginals[:A])\n",
      "marginals[:s_059_s_058] = ruleMTransitionCCD(messages[379], messages[213], marginals[:A])\n",
      "marginals[:s_060_s_059] = ruleMTransitionCCD(messages[377], messages[215], marginals[:A])\n",
      "marginals[:s_061_s_060] = ruleMTransitionCCD(messages[375], messages[217], marginals[:A])\n",
      "marginals[:s_062_s_061] = ruleMTransitionCCD(messages[373], messages[219], marginals[:A])\n",
      "marginals[:s_063_s_062] = ruleMTransitionCCD(messages[371], messages[221], marginals[:A])\n",
      "marginals[:s_064_s_063] = ruleMTransitionCCD(messages[369], messages[223], marginals[:A])\n",
      "marginals[:s_065_s_064] = ruleMTransitionCCD(messages[367], messages[225], marginals[:A])\n",
      "marginals[:s_066_s_065] = ruleMTransitionCCD(messages[365], messages[227], marginals[:A])\n",
      "marginals[:s_067_s_066] = ruleMTransitionCCD(messages[363], messages[229], marginals[:A])\n",
      "marginals[:s_068_s_067] = ruleMTransitionCCD(messages[361], messages[231], marginals[:A])\n",
      "marginals[:s_069_s_068] = ruleMTransitionCCD(messages[359], messages[233], marginals[:A])\n",
      "marginals[:s_070_s_069] = ruleMTransitionCCD(messages[357], messages[235], marginals[:A])\n",
      "marginals[:s_071_s_070] = ruleMTransitionCCD(messages[355], messages[237], marginals[:A])\n",
      "marginals[:s_072_s_071] = ruleMTransitionCCD(messages[353], messages[239], marginals[:A])\n",
      "marginals[:s_073_s_072] = ruleMTransitionCCD(messages[351], messages[241], marginals[:A])\n",
      "marginals[:s_074_s_073] = ruleMTransitionCCD(messages[349], messages[243], marginals[:A])\n",
      "marginals[:s_075_s_074] = ruleMTransitionCCD(messages[347], messages[245], marginals[:A])\n",
      "marginals[:s_076_s_075] = ruleMTransitionCCD(messages[345], messages[247], marginals[:A])\n",
      "marginals[:s_077_s_076] = ruleMTransitionCCD(messages[343], messages[249], marginals[:A])\n",
      "marginals[:s_078_s_077] = ruleMTransitionCCD(messages[341], messages[251], marginals[:A])\n",
      "marginals[:s_079_s_078] = ruleMTransitionCCD(messages[339], messages[253], marginals[:A])\n",
      "marginals[:s_080_s_079] = ruleMTransitionCCD(messages[337], messages[255], marginals[:A])\n",
      "marginals[:s_081_s_080] = ruleMTransitionCCD(messages[335], messages[257], marginals[:A])\n",
      "marginals[:s_082_s_081] = ruleMTransitionCCD(messages[333], messages[259], marginals[:A])\n",
      "marginals[:s_083_s_082] = ruleMTransitionCCD(messages[331], messages[261], marginals[:A])\n",
      "marginals[:s_084_s_083] = ruleMTransitionCCD(messages[329], messages[263], marginals[:A])\n",
      "marginals[:s_085_s_084] = ruleMTransitionCCD(messages[327], messages[265], marginals[:A])\n",
      "marginals[:s_086_s_085] = ruleMTransitionCCD(messages[325], messages[267], marginals[:A])\n",
      "marginals[:s_087_s_086] = ruleMTransitionCCD(messages[323], messages[269], marginals[:A])\n",
      "marginals[:s_088_s_087] = ruleMTransitionCCD(messages[321], messages[271], marginals[:A])\n",
      "marginals[:s_089_s_088] = ruleMTransitionCCD(messages[319], messages[273], marginals[:A])\n",
      "marginals[:s_090_s_089] = ruleMTransitionCCD(messages[317], messages[275], marginals[:A])\n",
      "marginals[:s_091_s_090] = ruleMTransitionCCD(messages[315], messages[277], marginals[:A])\n",
      "marginals[:s_092_s_091] = ruleMTransitionCCD(messages[313], messages[279], marginals[:A])\n",
      "marginals[:s_093_s_092] = ruleMTransitionCCD(messages[311], messages[281], marginals[:A])\n",
      "marginals[:s_094_s_093] = ruleMTransitionCCD(messages[309], messages[283], marginals[:A])\n",
      "marginals[:s_095_s_094] = ruleMTransitionCCD(messages[307], messages[285], marginals[:A])\n",
      "marginals[:s_096_s_095] = ruleMTransitionCCD(messages[305], messages[287], marginals[:A])\n",
      "marginals[:s_097_s_096] = ruleMTransitionCCD(messages[303], messages[289], marginals[:A])\n",
      "marginals[:s_098_s_097] = ruleMTransitionCCD(messages[301], messages[291], marginals[:A])\n",
      "marginals[:s_099_s_098] = ruleMTransitionCCD(messages[299], messages[293], marginals[:A])\n",
      "marginals[:s_100_s_099] = ruleMTransitionCCD(messages[297], messages[295], marginals[:A])\n",
      "\n",
      "return marginals\n",
      "\n",
      "end\n",
      "\n",
      "function stepX!(data::Dict, marginals::Dict=Dict(), messages::Vector{Message}=Array{Message}(undef, 497); dump::Union{GraphDump, Nothing} = nothing)\n",
      "\n",
      "messages[1] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][99]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_099]))\n",
      "messages[2] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][98]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_098]))\n",
      "messages[3] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][97]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_097]))\n",
      "messages[4] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][96]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_096]))\n",
      "messages[5] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][95]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_095]))\n",
      "messages[6] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][94]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_094]))\n",
      "messages[7] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][93]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_093]))\n",
      "messages[8] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][92]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_092]))\n",
      "messages[9] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][91]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_091]))\n",
      "messages[10] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][90]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_090]))\n",
      "messages[11] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][89]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_089]))\n",
      "messages[12] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][88]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_088]))\n",
      "messages[13] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][87]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_087]))\n",
      "messages[14] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][86]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_086]))\n",
      "messages[15] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][85]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_085]))\n",
      "messages[16] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][84]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_084]))\n",
      "messages[17] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][83]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_083]))\n",
      "messages[18] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][82]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_082]))\n",
      "messages[19] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][81]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_081]))\n",
      "messages[20] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][80]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_080]))\n",
      "messages[21] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][79]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_079]))\n",
      "messages[22] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][78]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_078]))\n",
      "messages[23] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][77]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_077]))\n",
      "messages[24] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][76]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_076]))\n",
      "messages[25] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][75]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_075]))\n",
      "messages[26] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][74]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_074]))\n",
      "messages[27] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][73]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_073]))\n",
      "messages[28] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][72]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_072]))\n",
      "messages[29] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][71]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_071]))\n",
      "messages[30] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][70]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_070]))\n",
      "messages[31] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][69]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_069]))\n",
      "messages[32] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][68]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_068]))\n",
      "messages[33] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][67]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_067]))\n",
      "messages[34] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][66]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_066]))\n",
      "messages[35] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][65]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_065]))\n",
      "messages[36] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][64]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_064]))\n",
      "messages[37] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][63]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_063]))\n",
      "messages[38] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][62]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_062]))\n",
      "messages[39] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][61]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_061]))\n",
      "messages[40] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][60]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_060]))\n",
      "messages[41] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][59]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_059]))\n",
      "messages[42] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][58]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_058]))\n",
      "messages[43] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][57]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_057]))\n",
      "messages[44] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][56]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_056]))\n",
      "messages[45] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][55]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_055]))\n",
      "messages[46] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][54]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_054]))\n",
      "messages[47] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][53]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_053]))\n",
      "messages[48] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][52]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_052]))\n",
      "messages[49] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][51]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_051]))\n",
      "messages[50] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][50]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_050]))\n",
      "messages[51] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][49]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_049]))\n",
      "messages[52] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][48]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_048]))\n",
      "messages[53] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][47]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_047]))\n",
      "messages[54] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][46]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_046]))\n",
      "messages[55] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][45]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_045]))\n",
      "messages[56] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][44]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_044]))\n",
      "messages[57] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][43]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_043]))\n",
      "messages[58] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][42]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_042]))\n",
      "messages[59] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][41]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_041]))\n",
      "messages[60] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][40]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_040]))\n",
      "messages[61] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][39]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_039]))\n",
      "messages[62] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][38]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_038]))\n",
      "messages[63] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][37]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_037]))\n",
      "messages[64] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][36]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_036]))\n",
      "messages[65] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][35]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_035]))\n",
      "messages[66] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][34]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_034]))\n",
      "messages[67] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][33]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_033]))\n",
      "messages[68] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][32]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_032]))\n",
      "messages[69] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][31]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_031]))\n",
      "messages[70] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][30]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_030]))\n",
      "messages[71] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][29]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_029]))\n",
      "messages[72] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][28]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_028]))\n",
      "messages[73] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][27]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_027]))\n",
      "messages[74] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][26]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_026]))\n",
      "messages[75] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][25]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_025]))\n",
      "messages[76] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][24]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_024]))\n",
      "messages[77] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][23]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_023]))\n",
      "messages[78] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][22]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_022]))\n",
      "messages[79] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][21]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_021]))\n",
      "messages[80] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][20]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_020]))\n",
      "messages[81] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][19]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_019]))\n",
      "messages[82] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][18]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_018]))\n",
      "messages[83] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][17]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_017]))\n",
      "messages[84] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][16]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_016]))\n",
      "messages[85] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][15]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_015]))\n",
      "messages[86] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][14]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_014]))\n",
      "messages[87] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][13]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_013]))\n",
      "messages[88] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][12]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_012]))\n",
      "messages[89] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][11]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_011]))\n",
      "messages[90] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][10]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_010]))\n",
      "messages[91] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][9]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_009]))\n",
      "messages[92] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][8]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_008]))\n",
      "messages[93] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][7]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_007]))\n",
      "messages[94] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][6]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_006]))\n",
      "messages[95] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][5]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_005]))\n",
      "messages[96] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][4]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_004]))\n",
      "messages[97] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][3]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_003]))\n",
      "messages[98] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][2]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_002]))\n",
      "messages[99] = ruleVBGaussianMeanPrecisionOut(nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:mx_prior1]), ProbabilityDistribution(Univariate, PointMass, m=data[:wx_prior1]))\n",
      "messages[100] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][1]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_prior1]))\n",
      "messages[101] = ruleSPEqualityGaussian(messages[99], messages[100], nothing)\n",
      "messages[102] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[101], marginals[:z_002], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_002])\n",
      "messages[103] = ruleSPEqualityGaussian(messages[102], messages[98], nothing)\n",
      "messages[104] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[103], marginals[:z_003], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_003])\n",
      "messages[105] = ruleSPEqualityGaussian(messages[104], messages[97], nothing)\n",
      "messages[106] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[105], marginals[:z_004], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_004])\n",
      "messages[107] = ruleSPEqualityGaussian(messages[106], messages[96], nothing)\n",
      "messages[108] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[107], marginals[:z_005], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_005])\n",
      "messages[109] = ruleSPEqualityGaussian(messages[108], messages[95], nothing)\n",
      "messages[110] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[109], marginals[:z_006], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_006])\n",
      "messages[111] = ruleSPEqualityGaussian(messages[110], messages[94], nothing)\n",
      "messages[112] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[111], marginals[:z_007], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_007])\n",
      "messages[113] = ruleSPEqualityGaussian(messages[112], messages[93], nothing)\n",
      "messages[114] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[113], marginals[:z_008], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_008])\n",
      "messages[115] = ruleSPEqualityGaussian(messages[114], messages[92], nothing)\n",
      "messages[116] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[115], marginals[:z_009], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_009])\n",
      "messages[117] = ruleSPEqualityGaussian(messages[116], messages[91], nothing)\n",
      "messages[118] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[117], marginals[:z_010], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_010])\n",
      "messages[119] = ruleSPEqualityGaussian(messages[118], messages[90], nothing)\n",
      "messages[120] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[119], marginals[:z_011], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_011])\n",
      "messages[121] = ruleSPEqualityGaussian(messages[120], messages[89], nothing)\n",
      "messages[122] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[121], marginals[:z_012], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_012])\n",
      "messages[123] = ruleSPEqualityGaussian(messages[122], messages[88], nothing)\n",
      "messages[124] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[123], marginals[:z_013], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_013])\n",
      "messages[125] = ruleSPEqualityGaussian(messages[124], messages[87], nothing)\n",
      "messages[126] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[125], marginals[:z_014], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_014])\n",
      "messages[127] = ruleSPEqualityGaussian(messages[126], messages[86], nothing)\n",
      "messages[128] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[127], marginals[:z_015], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_015])\n",
      "messages[129] = ruleSPEqualityGaussian(messages[128], messages[85], nothing)\n",
      "messages[130] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[129], marginals[:z_016], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_016])\n",
      "messages[131] = ruleSPEqualityGaussian(messages[130], messages[84], nothing)\n",
      "messages[132] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[131], marginals[:z_017], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_017])\n",
      "messages[133] = ruleSPEqualityGaussian(messages[132], messages[83], nothing)\n",
      "messages[134] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[133], marginals[:z_018], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_018])\n",
      "messages[135] = ruleSPEqualityGaussian(messages[134], messages[82], nothing)\n",
      "messages[136] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[135], marginals[:z_019], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_019])\n",
      "messages[137] = ruleSPEqualityGaussian(messages[136], messages[81], nothing)\n",
      "messages[138] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[137], marginals[:z_020], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_020])\n",
      "messages[139] = ruleSPEqualityGaussian(messages[138], messages[80], nothing)\n",
      "messages[140] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[139], marginals[:z_021], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_021])\n",
      "messages[141] = ruleSPEqualityGaussian(messages[140], messages[79], nothing)\n",
      "messages[142] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[141], marginals[:z_022], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_022])\n",
      "messages[143] = ruleSPEqualityGaussian(messages[142], messages[78], nothing)\n",
      "messages[144] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[143], marginals[:z_023], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_023])\n",
      "messages[145] = ruleSPEqualityGaussian(messages[144], messages[77], nothing)\n",
      "messages[146] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[145], marginals[:z_024], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_024])\n",
      "messages[147] = ruleSPEqualityGaussian(messages[146], messages[76], nothing)\n",
      "messages[148] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[147], marginals[:z_025], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_025])\n",
      "messages[149] = ruleSPEqualityGaussian(messages[148], messages[75], nothing)\n",
      "messages[150] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[149], marginals[:z_026], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_026])\n",
      "messages[151] = ruleSPEqualityGaussian(messages[150], messages[74], nothing)\n",
      "messages[152] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[151], marginals[:z_027], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_027])\n",
      "messages[153] = ruleSPEqualityGaussian(messages[152], messages[73], nothing)\n",
      "messages[154] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[153], marginals[:z_028], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_028])\n",
      "messages[155] = ruleSPEqualityGaussian(messages[154], messages[72], nothing)\n",
      "messages[156] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[155], marginals[:z_029], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_029])\n",
      "messages[157] = ruleSPEqualityGaussian(messages[156], messages[71], nothing)\n",
      "messages[158] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[157], marginals[:z_030], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_030])\n",
      "messages[159] = ruleSPEqualityGaussian(messages[158], messages[70], nothing)\n",
      "messages[160] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[159], marginals[:z_031], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_031])\n",
      "messages[161] = ruleSPEqualityGaussian(messages[160], messages[69], nothing)\n",
      "messages[162] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[161], marginals[:z_032], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_032])\n",
      "messages[163] = ruleSPEqualityGaussian(messages[162], messages[68], nothing)\n",
      "messages[164] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[163], marginals[:z_033], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_033])\n",
      "messages[165] = ruleSPEqualityGaussian(messages[164], messages[67], nothing)\n",
      "messages[166] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[165], marginals[:z_034], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_034])\n",
      "messages[167] = ruleSPEqualityGaussian(messages[166], messages[66], nothing)\n",
      "messages[168] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[167], marginals[:z_035], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_035])\n",
      "messages[169] = ruleSPEqualityGaussian(messages[168], messages[65], nothing)\n",
      "messages[170] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[169], marginals[:z_036], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_036])\n",
      "messages[171] = ruleSPEqualityGaussian(messages[170], messages[64], nothing)\n",
      "messages[172] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[171], marginals[:z_037], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_037])\n",
      "messages[173] = ruleSPEqualityGaussian(messages[172], messages[63], nothing)\n",
      "messages[174] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[173], marginals[:z_038], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_038])\n",
      "messages[175] = ruleSPEqualityGaussian(messages[174], messages[62], nothing)\n",
      "messages[176] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[175], marginals[:z_039], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_039])\n",
      "messages[177] = ruleSPEqualityGaussian(messages[176], messages[61], nothing)\n",
      "messages[178] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[177], marginals[:z_040], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_040])\n",
      "messages[179] = ruleSPEqualityGaussian(messages[178], messages[60], nothing)\n",
      "messages[180] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[179], marginals[:z_041], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_041])\n",
      "messages[181] = ruleSPEqualityGaussian(messages[180], messages[59], nothing)\n",
      "messages[182] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[181], marginals[:z_042], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_042])\n",
      "messages[183] = ruleSPEqualityGaussian(messages[182], messages[58], nothing)\n",
      "messages[184] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[183], marginals[:z_043], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_043])\n",
      "messages[185] = ruleSPEqualityGaussian(messages[184], messages[57], nothing)\n",
      "messages[186] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[185], marginals[:z_044], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_044])\n",
      "messages[187] = ruleSPEqualityGaussian(messages[186], messages[56], nothing)\n",
      "messages[188] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[187], marginals[:z_045], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_045])\n",
      "messages[189] = ruleSPEqualityGaussian(messages[188], messages[55], nothing)\n",
      "messages[190] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[189], marginals[:z_046], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_046])\n",
      "messages[191] = ruleSPEqualityGaussian(messages[190], messages[54], nothing)\n",
      "messages[192] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[191], marginals[:z_047], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_047])\n",
      "messages[193] = ruleSPEqualityGaussian(messages[192], messages[53], nothing)\n",
      "messages[194] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[193], marginals[:z_048], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_048])\n",
      "messages[195] = ruleSPEqualityGaussian(messages[194], messages[52], nothing)\n",
      "messages[196] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[195], marginals[:z_049], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_049])\n",
      "messages[197] = ruleSPEqualityGaussian(messages[196], messages[51], nothing)\n",
      "messages[198] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[197], marginals[:z_050], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_050])\n",
      "messages[199] = ruleSPEqualityGaussian(messages[198], messages[50], nothing)\n",
      "messages[200] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[199], marginals[:z_051], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_051])\n",
      "messages[201] = ruleSPEqualityGaussian(messages[200], messages[49], nothing)\n",
      "messages[202] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[201], marginals[:z_052], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_052])\n",
      "messages[203] = ruleSPEqualityGaussian(messages[202], messages[48], nothing)\n",
      "messages[204] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[203], marginals[:z_053], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_053])\n",
      "messages[205] = ruleSPEqualityGaussian(messages[204], messages[47], nothing)\n",
      "messages[206] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[205], marginals[:z_054], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_054])\n",
      "messages[207] = ruleSPEqualityGaussian(messages[206], messages[46], nothing)\n",
      "messages[208] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[207], marginals[:z_055], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_055])\n",
      "messages[209] = ruleSPEqualityGaussian(messages[208], messages[45], nothing)\n",
      "messages[210] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[209], marginals[:z_056], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_056])\n",
      "messages[211] = ruleSPEqualityGaussian(messages[210], messages[44], nothing)\n",
      "messages[212] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[211], marginals[:z_057], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_057])\n",
      "messages[213] = ruleSPEqualityGaussian(messages[212], messages[43], nothing)\n",
      "messages[214] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[213], marginals[:z_058], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_058])\n",
      "messages[215] = ruleSPEqualityGaussian(messages[214], messages[42], nothing)\n",
      "messages[216] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[215], marginals[:z_059], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_059])\n",
      "messages[217] = ruleSPEqualityGaussian(messages[216], messages[41], nothing)\n",
      "messages[218] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[217], marginals[:z_060], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_060])\n",
      "messages[219] = ruleSPEqualityGaussian(messages[218], messages[40], nothing)\n",
      "messages[220] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[219], marginals[:z_061], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_061])\n",
      "messages[221] = ruleSPEqualityGaussian(messages[220], messages[39], nothing)\n",
      "messages[222] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[221], marginals[:z_062], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_062])\n",
      "messages[223] = ruleSPEqualityGaussian(messages[222], messages[38], nothing)\n",
      "messages[224] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[223], marginals[:z_063], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_063])\n",
      "messages[225] = ruleSPEqualityGaussian(messages[224], messages[37], nothing)\n",
      "messages[226] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[225], marginals[:z_064], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_064])\n",
      "messages[227] = ruleSPEqualityGaussian(messages[226], messages[36], nothing)\n",
      "messages[228] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[227], marginals[:z_065], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_065])\n",
      "messages[229] = ruleSPEqualityGaussian(messages[228], messages[35], nothing)\n",
      "messages[230] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[229], marginals[:z_066], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_066])\n",
      "messages[231] = ruleSPEqualityGaussian(messages[230], messages[34], nothing)\n",
      "messages[232] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[231], marginals[:z_067], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_067])\n",
      "messages[233] = ruleSPEqualityGaussian(messages[232], messages[33], nothing)\n",
      "messages[234] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[233], marginals[:z_068], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_068])\n",
      "messages[235] = ruleSPEqualityGaussian(messages[234], messages[32], nothing)\n",
      "messages[236] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[235], marginals[:z_069], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_069])\n",
      "messages[237] = ruleSPEqualityGaussian(messages[236], messages[31], nothing)\n",
      "messages[238] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[237], marginals[:z_070], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_070])\n",
      "messages[239] = ruleSPEqualityGaussian(messages[238], messages[30], nothing)\n",
      "messages[240] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[239], marginals[:z_071], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_071])\n",
      "messages[241] = ruleSPEqualityGaussian(messages[240], messages[29], nothing)\n",
      "messages[242] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[241], marginals[:z_072], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_072])\n",
      "messages[243] = ruleSPEqualityGaussian(messages[242], messages[28], nothing)\n",
      "messages[244] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[243], marginals[:z_073], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_073])\n",
      "messages[245] = ruleSPEqualityGaussian(messages[244], messages[27], nothing)\n",
      "messages[246] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[245], marginals[:z_074], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_074])\n",
      "messages[247] = ruleSPEqualityGaussian(messages[246], messages[26], nothing)\n",
      "messages[248] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[247], marginals[:z_075], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_075])\n",
      "messages[249] = ruleSPEqualityGaussian(messages[248], messages[25], nothing)\n",
      "messages[250] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[249], marginals[:z_076], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_076])\n",
      "messages[251] = ruleSPEqualityGaussian(messages[250], messages[24], nothing)\n",
      "messages[252] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[251], marginals[:z_077], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_077])\n",
      "messages[253] = ruleSPEqualityGaussian(messages[252], messages[23], nothing)\n",
      "messages[254] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[253], marginals[:z_078], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_078])\n",
      "messages[255] = ruleSPEqualityGaussian(messages[254], messages[22], nothing)\n",
      "messages[256] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[255], marginals[:z_079], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_079])\n",
      "messages[257] = ruleSPEqualityGaussian(messages[256], messages[21], nothing)\n",
      "messages[258] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[257], marginals[:z_080], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_080])\n",
      "messages[259] = ruleSPEqualityGaussian(messages[258], messages[20], nothing)\n",
      "messages[260] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[259], marginals[:z_081], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_081])\n",
      "messages[261] = ruleSPEqualityGaussian(messages[260], messages[19], nothing)\n",
      "messages[262] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[261], marginals[:z_082], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_082])\n",
      "messages[263] = ruleSPEqualityGaussian(messages[262], messages[18], nothing)\n",
      "messages[264] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[263], marginals[:z_083], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_083])\n",
      "messages[265] = ruleSPEqualityGaussian(messages[264], messages[17], nothing)\n",
      "messages[266] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[265], marginals[:z_084], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_084])\n",
      "messages[267] = ruleSPEqualityGaussian(messages[266], messages[16], nothing)\n",
      "messages[268] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[267], marginals[:z_085], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_085])\n",
      "messages[269] = ruleSPEqualityGaussian(messages[268], messages[15], nothing)\n",
      "messages[270] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[269], marginals[:z_086], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_086])\n",
      "messages[271] = ruleSPEqualityGaussian(messages[270], messages[14], nothing)\n",
      "messages[272] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[271], marginals[:z_087], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_087])\n",
      "messages[273] = ruleSPEqualityGaussian(messages[272], messages[13], nothing)\n",
      "messages[274] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[273], marginals[:z_088], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_088])\n",
      "messages[275] = ruleSPEqualityGaussian(messages[274], messages[12], nothing)\n",
      "messages[276] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[275], marginals[:z_089], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_089])\n",
      "messages[277] = ruleSPEqualityGaussian(messages[276], messages[11], nothing)\n",
      "messages[278] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[277], marginals[:z_090], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_090])\n",
      "messages[279] = ruleSPEqualityGaussian(messages[278], messages[10], nothing)\n",
      "messages[280] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[279], marginals[:z_091], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_091])\n",
      "messages[281] = ruleSPEqualityGaussian(messages[280], messages[9], nothing)\n",
      "messages[282] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[281], marginals[:z_092], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_092])\n",
      "messages[283] = ruleSPEqualityGaussian(messages[282], messages[8], nothing)\n",
      "messages[284] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[283], marginals[:z_093], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_093])\n",
      "messages[285] = ruleSPEqualityGaussian(messages[284], messages[7], nothing)\n",
      "messages[286] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[285], marginals[:z_094], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_094])\n",
      "messages[287] = ruleSPEqualityGaussian(messages[286], messages[6], nothing)\n",
      "messages[288] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[287], marginals[:z_095], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_095])\n",
      "messages[289] = ruleSPEqualityGaussian(messages[288], messages[5], nothing)\n",
      "messages[290] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[289], marginals[:z_096], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_096])\n",
      "messages[291] = ruleSPEqualityGaussian(messages[290], messages[4], nothing)\n",
      "messages[292] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[291], marginals[:z_097], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_097])\n",
      "messages[293] = ruleSPEqualityGaussian(messages[292], messages[3], nothing)\n",
      "messages[294] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[293], marginals[:z_098], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_098])\n",
      "messages[295] = ruleSPEqualityGaussian(messages[294], messages[2], nothing)\n",
      "messages[296] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[295], marginals[:z_099], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_099])\n",
      "messages[297] = ruleSPEqualityGaussian(messages[296], messages[1], nothing)\n",
      "messages[298] = ruleSVBSwitchingGaussianControlledVarianceIn1MPPPP(nothing, messages[297], marginals[:z_100], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_100])\n",
      "messages[299] = ruleVBGaussianMeanPrecisionM(ProbabilityDistribution(Univariate, PointMass, m=data[:y][100]), nothing, ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_100]))\n",
      "messages[300] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[299], nothing, marginals[:z_100], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_100])\n",
      "messages[301] = ruleSPEqualityGaussian(nothing, messages[1], messages[300])\n",
      "messages[302] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[301], nothing, marginals[:z_099], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_099])\n",
      "messages[303] = ruleSPEqualityGaussian(nothing, messages[2], messages[302])\n",
      "messages[304] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[303], nothing, marginals[:z_098], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_098])\n",
      "messages[305] = ruleSPEqualityGaussian(nothing, messages[3], messages[304])\n",
      "messages[306] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[305], nothing, marginals[:z_097], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_097])\n",
      "messages[307] = ruleSPEqualityGaussian(nothing, messages[4], messages[306])\n",
      "messages[308] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[307], nothing, marginals[:z_096], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_096])\n",
      "messages[309] = ruleSPEqualityGaussian(nothing, messages[5], messages[308])\n",
      "messages[310] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[309], nothing, marginals[:z_095], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_095])\n",
      "messages[311] = ruleSPEqualityGaussian(nothing, messages[6], messages[310])\n",
      "messages[312] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[311], nothing, marginals[:z_094], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_094])\n",
      "messages[313] = ruleSPEqualityGaussian(nothing, messages[7], messages[312])\n",
      "messages[314] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[313], nothing, marginals[:z_093], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_093])\n",
      "messages[315] = ruleSPEqualityGaussian(nothing, messages[8], messages[314])\n",
      "messages[316] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[315], nothing, marginals[:z_092], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_092])\n",
      "messages[317] = ruleSPEqualityGaussian(nothing, messages[9], messages[316])\n",
      "messages[318] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[317], nothing, marginals[:z_091], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_091])\n",
      "messages[319] = ruleSPEqualityGaussian(nothing, messages[10], messages[318])\n",
      "messages[320] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[319], nothing, marginals[:z_090], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_090])\n",
      "messages[321] = ruleSPEqualityGaussian(nothing, messages[11], messages[320])\n",
      "messages[322] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[321], nothing, marginals[:z_089], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_089])\n",
      "messages[323] = ruleSPEqualityGaussian(nothing, messages[12], messages[322])\n",
      "messages[324] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[323], nothing, marginals[:z_088], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_088])\n",
      "messages[325] = ruleSPEqualityGaussian(nothing, messages[13], messages[324])\n",
      "messages[326] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[325], nothing, marginals[:z_087], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_087])\n",
      "messages[327] = ruleSPEqualityGaussian(nothing, messages[14], messages[326])\n",
      "messages[328] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[327], nothing, marginals[:z_086], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_086])\n",
      "messages[329] = ruleSPEqualityGaussian(nothing, messages[15], messages[328])\n",
      "messages[330] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[329], nothing, marginals[:z_085], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_085])\n",
      "messages[331] = ruleSPEqualityGaussian(nothing, messages[16], messages[330])\n",
      "messages[332] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[331], nothing, marginals[:z_084], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_084])\n",
      "messages[333] = ruleSPEqualityGaussian(nothing, messages[17], messages[332])\n",
      "messages[334] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[333], nothing, marginals[:z_083], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_083])\n",
      "messages[335] = ruleSPEqualityGaussian(nothing, messages[18], messages[334])\n",
      "messages[336] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[335], nothing, marginals[:z_082], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_082])\n",
      "messages[337] = ruleSPEqualityGaussian(nothing, messages[19], messages[336])\n",
      "messages[338] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[337], nothing, marginals[:z_081], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_081])\n",
      "messages[339] = ruleSPEqualityGaussian(nothing, messages[20], messages[338])\n",
      "messages[340] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[339], nothing, marginals[:z_080], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_080])\n",
      "messages[341] = ruleSPEqualityGaussian(nothing, messages[21], messages[340])\n",
      "messages[342] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[341], nothing, marginals[:z_079], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_079])\n",
      "messages[343] = ruleSPEqualityGaussian(nothing, messages[22], messages[342])\n",
      "messages[344] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[343], nothing, marginals[:z_078], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_078])\n",
      "messages[345] = ruleSPEqualityGaussian(nothing, messages[23], messages[344])\n",
      "messages[346] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[345], nothing, marginals[:z_077], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_077])\n",
      "messages[347] = ruleSPEqualityGaussian(nothing, messages[24], messages[346])\n",
      "messages[348] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[347], nothing, marginals[:z_076], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_076])\n",
      "messages[349] = ruleSPEqualityGaussian(nothing, messages[25], messages[348])\n",
      "messages[350] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[349], nothing, marginals[:z_075], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_075])\n",
      "messages[351] = ruleSPEqualityGaussian(nothing, messages[26], messages[350])\n",
      "messages[352] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[351], nothing, marginals[:z_074], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_074])\n",
      "messages[353] = ruleSPEqualityGaussian(nothing, messages[27], messages[352])\n",
      "messages[354] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[353], nothing, marginals[:z_073], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_073])\n",
      "messages[355] = ruleSPEqualityGaussian(nothing, messages[28], messages[354])\n",
      "messages[356] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[355], nothing, marginals[:z_072], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_072])\n",
      "messages[357] = ruleSPEqualityGaussian(nothing, messages[29], messages[356])\n",
      "messages[358] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[357], nothing, marginals[:z_071], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_071])\n",
      "messages[359] = ruleSPEqualityGaussian(nothing, messages[30], messages[358])\n",
      "messages[360] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[359], nothing, marginals[:z_070], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_070])\n",
      "messages[361] = ruleSPEqualityGaussian(nothing, messages[31], messages[360])\n",
      "messages[362] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[361], nothing, marginals[:z_069], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_069])\n",
      "messages[363] = ruleSPEqualityGaussian(nothing, messages[32], messages[362])\n",
      "messages[364] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[363], nothing, marginals[:z_068], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_068])\n",
      "messages[365] = ruleSPEqualityGaussian(nothing, messages[33], messages[364])\n",
      "messages[366] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[365], nothing, marginals[:z_067], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_067])\n",
      "messages[367] = ruleSPEqualityGaussian(nothing, messages[34], messages[366])\n",
      "messages[368] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[367], nothing, marginals[:z_066], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_066])\n",
      "messages[369] = ruleSPEqualityGaussian(nothing, messages[35], messages[368])\n",
      "messages[370] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[369], nothing, marginals[:z_065], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_065])\n",
      "messages[371] = ruleSPEqualityGaussian(nothing, messages[36], messages[370])\n",
      "messages[372] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[371], nothing, marginals[:z_064], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_064])\n",
      "messages[373] = ruleSPEqualityGaussian(nothing, messages[37], messages[372])\n",
      "messages[374] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[373], nothing, marginals[:z_063], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_063])\n",
      "messages[375] = ruleSPEqualityGaussian(nothing, messages[38], messages[374])\n",
      "messages[376] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[375], nothing, marginals[:z_062], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_062])\n",
      "messages[377] = ruleSPEqualityGaussian(nothing, messages[39], messages[376])\n",
      "messages[378] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[377], nothing, marginals[:z_061], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_061])\n",
      "messages[379] = ruleSPEqualityGaussian(nothing, messages[40], messages[378])\n",
      "messages[380] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[379], nothing, marginals[:z_060], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_060])\n",
      "messages[381] = ruleSPEqualityGaussian(nothing, messages[41], messages[380])\n",
      "messages[382] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[381], nothing, marginals[:z_059], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_059])\n",
      "messages[383] = ruleSPEqualityGaussian(nothing, messages[42], messages[382])\n",
      "messages[384] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[383], nothing, marginals[:z_058], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_058])\n",
      "messages[385] = ruleSPEqualityGaussian(nothing, messages[43], messages[384])\n",
      "messages[386] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[385], nothing, marginals[:z_057], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_057])\n",
      "messages[387] = ruleSPEqualityGaussian(nothing, messages[44], messages[386])\n",
      "messages[388] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[387], nothing, marginals[:z_056], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_056])\n",
      "messages[389] = ruleSPEqualityGaussian(nothing, messages[45], messages[388])\n",
      "messages[390] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[389], nothing, marginals[:z_055], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_055])\n",
      "messages[391] = ruleSPEqualityGaussian(nothing, messages[46], messages[390])\n",
      "messages[392] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[391], nothing, marginals[:z_054], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_054])\n",
      "messages[393] = ruleSPEqualityGaussian(nothing, messages[47], messages[392])\n",
      "messages[394] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[393], nothing, marginals[:z_053], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_053])\n",
      "messages[395] = ruleSPEqualityGaussian(nothing, messages[48], messages[394])\n",
      "messages[396] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[395], nothing, marginals[:z_052], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_052])\n",
      "messages[397] = ruleSPEqualityGaussian(nothing, messages[49], messages[396])\n",
      "messages[398] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[397], nothing, marginals[:z_051], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_051])\n",
      "messages[399] = ruleSPEqualityGaussian(nothing, messages[50], messages[398])\n",
      "messages[400] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[399], nothing, marginals[:z_050], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_050])\n",
      "messages[401] = ruleSPEqualityGaussian(nothing, messages[51], messages[400])\n",
      "messages[402] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[401], nothing, marginals[:z_049], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_049])\n",
      "messages[403] = ruleSPEqualityGaussian(nothing, messages[52], messages[402])\n",
      "messages[404] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[403], nothing, marginals[:z_048], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_048])\n",
      "messages[405] = ruleSPEqualityGaussian(nothing, messages[53], messages[404])\n",
      "messages[406] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[405], nothing, marginals[:z_047], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_047])\n",
      "messages[407] = ruleSPEqualityGaussian(nothing, messages[54], messages[406])\n",
      "messages[408] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[407], nothing, marginals[:z_046], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_046])\n",
      "messages[409] = ruleSPEqualityGaussian(nothing, messages[55], messages[408])\n",
      "messages[410] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[409], nothing, marginals[:z_045], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_045])\n",
      "messages[411] = ruleSPEqualityGaussian(nothing, messages[56], messages[410])\n",
      "messages[412] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[411], nothing, marginals[:z_044], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_044])\n",
      "messages[413] = ruleSPEqualityGaussian(nothing, messages[57], messages[412])\n",
      "messages[414] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[413], nothing, marginals[:z_043], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_043])\n",
      "messages[415] = ruleSPEqualityGaussian(nothing, messages[58], messages[414])\n",
      "messages[416] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[415], nothing, marginals[:z_042], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_042])\n",
      "messages[417] = ruleSPEqualityGaussian(nothing, messages[59], messages[416])\n",
      "messages[418] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[417], nothing, marginals[:z_041], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_041])\n",
      "messages[419] = ruleSPEqualityGaussian(nothing, messages[60], messages[418])\n",
      "messages[420] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[419], nothing, marginals[:z_040], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_040])\n",
      "messages[421] = ruleSPEqualityGaussian(nothing, messages[61], messages[420])\n",
      "messages[422] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[421], nothing, marginals[:z_039], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_039])\n",
      "messages[423] = ruleSPEqualityGaussian(nothing, messages[62], messages[422])\n",
      "messages[424] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[423], nothing, marginals[:z_038], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_038])\n",
      "messages[425] = ruleSPEqualityGaussian(nothing, messages[63], messages[424])\n",
      "messages[426] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[425], nothing, marginals[:z_037], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_037])\n",
      "messages[427] = ruleSPEqualityGaussian(nothing, messages[64], messages[426])\n",
      "messages[428] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[427], nothing, marginals[:z_036], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_036])\n",
      "messages[429] = ruleSPEqualityGaussian(nothing, messages[65], messages[428])\n",
      "messages[430] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[429], nothing, marginals[:z_035], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_035])\n",
      "messages[431] = ruleSPEqualityGaussian(nothing, messages[66], messages[430])\n",
      "messages[432] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[431], nothing, marginals[:z_034], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_034])\n",
      "messages[433] = ruleSPEqualityGaussian(nothing, messages[67], messages[432])\n",
      "messages[434] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[433], nothing, marginals[:z_033], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_033])\n",
      "messages[435] = ruleSPEqualityGaussian(nothing, messages[68], messages[434])\n",
      "messages[436] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[435], nothing, marginals[:z_032], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_032])\n",
      "messages[437] = ruleSPEqualityGaussian(nothing, messages[69], messages[436])\n",
      "messages[438] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[437], nothing, marginals[:z_031], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_031])\n",
      "messages[439] = ruleSPEqualityGaussian(nothing, messages[70], messages[438])\n",
      "messages[440] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[439], nothing, marginals[:z_030], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_030])\n",
      "messages[441] = ruleSPEqualityGaussian(nothing, messages[71], messages[440])\n",
      "messages[442] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[441], nothing, marginals[:z_029], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_029])\n",
      "messages[443] = ruleSPEqualityGaussian(nothing, messages[72], messages[442])\n",
      "messages[444] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[443], nothing, marginals[:z_028], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_028])\n",
      "messages[445] = ruleSPEqualityGaussian(nothing, messages[73], messages[444])\n",
      "messages[446] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[445], nothing, marginals[:z_027], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_027])\n",
      "messages[447] = ruleSPEqualityGaussian(nothing, messages[74], messages[446])\n",
      "messages[448] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[447], nothing, marginals[:z_026], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_026])\n",
      "messages[449] = ruleSPEqualityGaussian(nothing, messages[75], messages[448])\n",
      "messages[450] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[449], nothing, marginals[:z_025], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_025])\n",
      "messages[451] = ruleSPEqualityGaussian(nothing, messages[76], messages[450])\n",
      "messages[452] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[451], nothing, marginals[:z_024], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_024])\n",
      "messages[453] = ruleSPEqualityGaussian(nothing, messages[77], messages[452])\n",
      "messages[454] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[453], nothing, marginals[:z_023], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_023])\n",
      "messages[455] = ruleSPEqualityGaussian(nothing, messages[78], messages[454])\n",
      "messages[456] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[455], nothing, marginals[:z_022], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_022])\n",
      "messages[457] = ruleSPEqualityGaussian(nothing, messages[79], messages[456])\n",
      "messages[458] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[457], nothing, marginals[:z_021], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_021])\n",
      "messages[459] = ruleSPEqualityGaussian(nothing, messages[80], messages[458])\n",
      "messages[460] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[459], nothing, marginals[:z_020], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_020])\n",
      "messages[461] = ruleSPEqualityGaussian(nothing, messages[81], messages[460])\n",
      "messages[462] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[461], nothing, marginals[:z_019], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_019])\n",
      "messages[463] = ruleSPEqualityGaussian(nothing, messages[82], messages[462])\n",
      "messages[464] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[463], nothing, marginals[:z_018], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_018])\n",
      "messages[465] = ruleSPEqualityGaussian(nothing, messages[83], messages[464])\n",
      "messages[466] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[465], nothing, marginals[:z_017], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_017])\n",
      "messages[467] = ruleSPEqualityGaussian(nothing, messages[84], messages[466])\n",
      "messages[468] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[467], nothing, marginals[:z_016], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_016])\n",
      "messages[469] = ruleSPEqualityGaussian(nothing, messages[85], messages[468])\n",
      "messages[470] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[469], nothing, marginals[:z_015], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_015])\n",
      "messages[471] = ruleSPEqualityGaussian(nothing, messages[86], messages[470])\n",
      "messages[472] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[471], nothing, marginals[:z_014], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_014])\n",
      "messages[473] = ruleSPEqualityGaussian(nothing, messages[87], messages[472])\n",
      "messages[474] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[473], nothing, marginals[:z_013], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_013])\n",
      "messages[475] = ruleSPEqualityGaussian(nothing, messages[88], messages[474])\n",
      "messages[476] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[475], nothing, marginals[:z_012], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_012])\n",
      "messages[477] = ruleSPEqualityGaussian(nothing, messages[89], messages[476])\n",
      "messages[478] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[477], nothing, marginals[:z_011], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_011])\n",
      "messages[479] = ruleSPEqualityGaussian(nothing, messages[90], messages[478])\n",
      "messages[480] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[479], nothing, marginals[:z_010], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_010])\n",
      "messages[481] = ruleSPEqualityGaussian(nothing, messages[91], messages[480])\n",
      "messages[482] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[481], nothing, marginals[:z_009], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_009])\n",
      "messages[483] = ruleSPEqualityGaussian(nothing, messages[92], messages[482])\n",
      "messages[484] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[483], nothing, marginals[:z_008], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_008])\n",
      "messages[485] = ruleSPEqualityGaussian(nothing, messages[93], messages[484])\n",
      "messages[486] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[485], nothing, marginals[:z_007], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_007])\n",
      "messages[487] = ruleSPEqualityGaussian(nothing, messages[94], messages[486])\n",
      "messages[488] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[487], nothing, marginals[:z_006], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_006])\n",
      "messages[489] = ruleSPEqualityGaussian(nothing, messages[95], messages[488])\n",
      "messages[490] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[489], nothing, marginals[:z_005], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_005])\n",
      "messages[491] = ruleSPEqualityGaussian(nothing, messages[96], messages[490])\n",
      "messages[492] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[491], nothing, marginals[:z_004], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_004])\n",
      "messages[493] = ruleSPEqualityGaussian(nothing, messages[97], messages[492])\n",
      "messages[494] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[493], nothing, marginals[:z_003], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_003])\n",
      "messages[495] = ruleSPEqualityGaussian(nothing, messages[98], messages[494])\n",
      "messages[496] = ruleSVBSwitchingGaussianControlledVarianceMIn2PPPP(messages[495], nothing, marginals[:z_002], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_002])\n",
      "messages[497] = ruleSPEqualityGaussian(nothing, messages[100], messages[496])\n",
      "\n",
      "marginals[:x_001] = messages[99].dist * messages[497].dist\n",
      "marginals[:x_002] = messages[102].dist * messages[495].dist\n",
      "marginals[:x_003] = messages[104].dist * messages[493].dist\n",
      "marginals[:x_004] = messages[106].dist * messages[491].dist\n",
      "marginals[:x_005] = messages[108].dist * messages[489].dist\n",
      "marginals[:x_006] = messages[110].dist * messages[487].dist\n",
      "marginals[:x_007] = messages[112].dist * messages[485].dist\n",
      "marginals[:x_008] = messages[114].dist * messages[483].dist\n",
      "marginals[:x_009] = messages[116].dist * messages[481].dist\n",
      "marginals[:x_010] = messages[118].dist * messages[479].dist\n",
      "marginals[:x_011] = messages[120].dist * messages[477].dist\n",
      "marginals[:x_012] = messages[122].dist * messages[475].dist\n",
      "marginals[:x_013] = messages[124].dist * messages[473].dist\n",
      "marginals[:x_014] = messages[126].dist * messages[471].dist\n",
      "marginals[:x_015] = messages[128].dist * messages[469].dist\n",
      "marginals[:x_016] = messages[130].dist * messages[467].dist\n",
      "marginals[:x_017] = messages[132].dist * messages[465].dist\n",
      "marginals[:x_018] = messages[134].dist * messages[463].dist\n",
      "marginals[:x_019] = messages[136].dist * messages[461].dist\n",
      "marginals[:x_020] = messages[138].dist * messages[459].dist\n",
      "marginals[:x_021] = messages[140].dist * messages[457].dist\n",
      "marginals[:x_022] = messages[142].dist * messages[455].dist\n",
      "marginals[:x_023] = messages[144].dist * messages[453].dist\n",
      "marginals[:x_024] = messages[146].dist * messages[451].dist\n",
      "marginals[:x_025] = messages[148].dist * messages[449].dist\n",
      "marginals[:x_026] = messages[150].dist * messages[447].dist\n",
      "marginals[:x_027] = messages[152].dist * messages[445].dist\n",
      "marginals[:x_028] = messages[154].dist * messages[443].dist\n",
      "marginals[:x_029] = messages[156].dist * messages[441].dist\n",
      "marginals[:x_030] = messages[158].dist * messages[439].dist\n",
      "marginals[:x_031] = messages[160].dist * messages[437].dist\n",
      "marginals[:x_032] = messages[162].dist * messages[435].dist\n",
      "marginals[:x_033] = messages[164].dist * messages[433].dist\n",
      "marginals[:x_034] = messages[166].dist * messages[431].dist\n",
      "marginals[:x_035] = messages[168].dist * messages[429].dist\n",
      "marginals[:x_036] = messages[170].dist * messages[427].dist\n",
      "marginals[:x_037] = messages[172].dist * messages[425].dist\n",
      "marginals[:x_038] = messages[174].dist * messages[423].dist\n",
      "marginals[:x_039] = messages[176].dist * messages[421].dist\n",
      "marginals[:x_040] = messages[178].dist * messages[419].dist\n",
      "marginals[:x_041] = messages[180].dist * messages[417].dist\n",
      "marginals[:x_042] = messages[182].dist * messages[415].dist\n",
      "marginals[:x_043] = messages[184].dist * messages[413].dist\n",
      "marginals[:x_044] = messages[186].dist * messages[411].dist\n",
      "marginals[:x_045] = messages[188].dist * messages[409].dist\n",
      "marginals[:x_046] = messages[190].dist * messages[407].dist\n",
      "marginals[:x_047] = messages[192].dist * messages[405].dist\n",
      "marginals[:x_048] = messages[194].dist * messages[403].dist\n",
      "marginals[:x_049] = messages[196].dist * messages[401].dist\n",
      "marginals[:x_050] = messages[198].dist * messages[399].dist\n",
      "marginals[:x_051] = messages[200].dist * messages[397].dist\n",
      "marginals[:x_052] = messages[202].dist * messages[395].dist\n",
      "marginals[:x_053] = messages[204].dist * messages[393].dist\n",
      "marginals[:x_054] = messages[206].dist * messages[391].dist\n",
      "marginals[:x_055] = messages[208].dist * messages[389].dist\n",
      "marginals[:x_056] = messages[210].dist * messages[387].dist\n",
      "marginals[:x_057] = messages[212].dist * messages[385].dist\n",
      "marginals[:x_058] = messages[214].dist * messages[383].dist\n",
      "marginals[:x_059] = messages[216].dist * messages[381].dist\n",
      "marginals[:x_060] = messages[218].dist * messages[379].dist\n",
      "marginals[:x_061] = messages[220].dist * messages[377].dist\n",
      "marginals[:x_062] = messages[222].dist * messages[375].dist\n",
      "marginals[:x_063] = messages[224].dist * messages[373].dist\n",
      "marginals[:x_064] = messages[226].dist * messages[371].dist\n",
      "marginals[:x_065] = messages[228].dist * messages[369].dist\n",
      "marginals[:x_066] = messages[230].dist * messages[367].dist\n",
      "marginals[:x_067] = messages[232].dist * messages[365].dist\n",
      "marginals[:x_068] = messages[234].dist * messages[363].dist\n",
      "marginals[:x_069] = messages[236].dist * messages[361].dist\n",
      "marginals[:x_070] = messages[238].dist * messages[359].dist\n",
      "marginals[:x_071] = messages[240].dist * messages[357].dist\n",
      "marginals[:x_072] = messages[242].dist * messages[355].dist\n",
      "marginals[:x_073] = messages[244].dist * messages[353].dist\n",
      "marginals[:x_074] = messages[246].dist * messages[351].dist\n",
      "marginals[:x_075] = messages[248].dist * messages[349].dist\n",
      "marginals[:x_076] = messages[250].dist * messages[347].dist\n",
      "marginals[:x_077] = messages[252].dist * messages[345].dist\n",
      "marginals[:x_078] = messages[254].dist * messages[343].dist\n",
      "marginals[:x_079] = messages[256].dist * messages[341].dist\n",
      "marginals[:x_080] = messages[258].dist * messages[339].dist\n",
      "marginals[:x_081] = messages[260].dist * messages[337].dist\n",
      "marginals[:x_082] = messages[262].dist * messages[335].dist\n",
      "marginals[:x_083] = messages[264].dist * messages[333].dist\n",
      "marginals[:x_084] = messages[266].dist * messages[331].dist\n",
      "marginals[:x_085] = messages[268].dist * messages[329].dist\n",
      "marginals[:x_086] = messages[270].dist * messages[327].dist\n",
      "marginals[:x_087] = messages[272].dist * messages[325].dist\n",
      "marginals[:x_088] = messages[274].dist * messages[323].dist\n",
      "marginals[:x_089] = messages[276].dist * messages[321].dist\n",
      "marginals[:x_090] = messages[278].dist * messages[319].dist\n",
      "marginals[:x_091] = messages[280].dist * messages[317].dist\n",
      "marginals[:x_092] = messages[282].dist * messages[315].dist\n",
      "marginals[:x_093] = messages[284].dist * messages[313].dist\n",
      "marginals[:x_094] = messages[286].dist * messages[311].dist\n",
      "marginals[:x_095] = messages[288].dist * messages[309].dist\n",
      "marginals[:x_096] = messages[290].dist * messages[307].dist\n",
      "marginals[:x_097] = messages[292].dist * messages[305].dist\n",
      "marginals[:x_098] = messages[294].dist * messages[303].dist\n",
      "marginals[:x_099] = messages[296].dist * messages[301].dist\n",
      "marginals[:x_100] = messages[298].dist * messages[299].dist\n",
      "marginals[:x_002_x_001] = ruleMSwitchingGaussianControlledVariance(messages[495], messages[101], marginals[:z_002], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_002])\n",
      "marginals[:x_003_x_002] = ruleMSwitchingGaussianControlledVariance(messages[493], messages[103], marginals[:z_003], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_003])\n",
      "marginals[:x_004_x_003] = ruleMSwitchingGaussianControlledVariance(messages[491], messages[105], marginals[:z_004], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_004])\n",
      "marginals[:x_005_x_004] = ruleMSwitchingGaussianControlledVariance(messages[489], messages[107], marginals[:z_005], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_005])\n",
      "marginals[:x_006_x_005] = ruleMSwitchingGaussianControlledVariance(messages[487], messages[109], marginals[:z_006], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_006])\n",
      "marginals[:x_007_x_006] = ruleMSwitchingGaussianControlledVariance(messages[485], messages[111], marginals[:z_007], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_007])\n",
      "marginals[:x_008_x_007] = ruleMSwitchingGaussianControlledVariance(messages[483], messages[113], marginals[:z_008], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_008])\n",
      "marginals[:x_009_x_008] = ruleMSwitchingGaussianControlledVariance(messages[481], messages[115], marginals[:z_009], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_009])\n",
      "marginals[:x_010_x_009] = ruleMSwitchingGaussianControlledVariance(messages[479], messages[117], marginals[:z_010], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_010])\n",
      "marginals[:x_011_x_010] = ruleMSwitchingGaussianControlledVariance(messages[477], messages[119], marginals[:z_011], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_011])\n",
      "marginals[:x_012_x_011] = ruleMSwitchingGaussianControlledVariance(messages[475], messages[121], marginals[:z_012], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_012])\n",
      "marginals[:x_013_x_012] = ruleMSwitchingGaussianControlledVariance(messages[473], messages[123], marginals[:z_013], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_013])\n",
      "marginals[:x_014_x_013] = ruleMSwitchingGaussianControlledVariance(messages[471], messages[125], marginals[:z_014], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_014])\n",
      "marginals[:x_015_x_014] = ruleMSwitchingGaussianControlledVariance(messages[469], messages[127], marginals[:z_015], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_015])\n",
      "marginals[:x_016_x_015] = ruleMSwitchingGaussianControlledVariance(messages[467], messages[129], marginals[:z_016], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_016])\n",
      "marginals[:x_017_x_016] = ruleMSwitchingGaussianControlledVariance(messages[465], messages[131], marginals[:z_017], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_017])\n",
      "marginals[:x_018_x_017] = ruleMSwitchingGaussianControlledVariance(messages[463], messages[133], marginals[:z_018], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_018])\n",
      "marginals[:x_019_x_018] = ruleMSwitchingGaussianControlledVariance(messages[461], messages[135], marginals[:z_019], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_019])\n",
      "marginals[:x_020_x_019] = ruleMSwitchingGaussianControlledVariance(messages[459], messages[137], marginals[:z_020], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_020])\n",
      "marginals[:x_021_x_020] = ruleMSwitchingGaussianControlledVariance(messages[457], messages[139], marginals[:z_021], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_021])\n",
      "marginals[:x_022_x_021] = ruleMSwitchingGaussianControlledVariance(messages[455], messages[141], marginals[:z_022], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_022])\n",
      "marginals[:x_023_x_022] = ruleMSwitchingGaussianControlledVariance(messages[453], messages[143], marginals[:z_023], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_023])\n",
      "marginals[:x_024_x_023] = ruleMSwitchingGaussianControlledVariance(messages[451], messages[145], marginals[:z_024], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_024])\n",
      "marginals[:x_025_x_024] = ruleMSwitchingGaussianControlledVariance(messages[449], messages[147], marginals[:z_025], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_025])\n",
      "marginals[:x_026_x_025] = ruleMSwitchingGaussianControlledVariance(messages[447], messages[149], marginals[:z_026], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_026])\n",
      "marginals[:x_027_x_026] = ruleMSwitchingGaussianControlledVariance(messages[445], messages[151], marginals[:z_027], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_027])\n",
      "marginals[:x_028_x_027] = ruleMSwitchingGaussianControlledVariance(messages[443], messages[153], marginals[:z_028], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_028])\n",
      "marginals[:x_029_x_028] = ruleMSwitchingGaussianControlledVariance(messages[441], messages[155], marginals[:z_029], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_029])\n",
      "marginals[:x_030_x_029] = ruleMSwitchingGaussianControlledVariance(messages[439], messages[157], marginals[:z_030], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_030])\n",
      "marginals[:x_031_x_030] = ruleMSwitchingGaussianControlledVariance(messages[437], messages[159], marginals[:z_031], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_031])\n",
      "marginals[:x_032_x_031] = ruleMSwitchingGaussianControlledVariance(messages[435], messages[161], marginals[:z_032], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_032])\n",
      "marginals[:x_033_x_032] = ruleMSwitchingGaussianControlledVariance(messages[433], messages[163], marginals[:z_033], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_033])\n",
      "marginals[:x_034_x_033] = ruleMSwitchingGaussianControlledVariance(messages[431], messages[165], marginals[:z_034], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_034])\n",
      "marginals[:x_035_x_034] = ruleMSwitchingGaussianControlledVariance(messages[429], messages[167], marginals[:z_035], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_035])\n",
      "marginals[:x_036_x_035] = ruleMSwitchingGaussianControlledVariance(messages[427], messages[169], marginals[:z_036], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_036])\n",
      "marginals[:x_037_x_036] = ruleMSwitchingGaussianControlledVariance(messages[425], messages[171], marginals[:z_037], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_037])\n",
      "marginals[:x_038_x_037] = ruleMSwitchingGaussianControlledVariance(messages[423], messages[173], marginals[:z_038], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_038])\n",
      "marginals[:x_039_x_038] = ruleMSwitchingGaussianControlledVariance(messages[421], messages[175], marginals[:z_039], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_039])\n",
      "marginals[:x_040_x_039] = ruleMSwitchingGaussianControlledVariance(messages[419], messages[177], marginals[:z_040], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_040])\n",
      "marginals[:x_041_x_040] = ruleMSwitchingGaussianControlledVariance(messages[417], messages[179], marginals[:z_041], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_041])\n",
      "marginals[:x_042_x_041] = ruleMSwitchingGaussianControlledVariance(messages[415], messages[181], marginals[:z_042], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_042])\n",
      "marginals[:x_043_x_042] = ruleMSwitchingGaussianControlledVariance(messages[413], messages[183], marginals[:z_043], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_043])\n",
      "marginals[:x_044_x_043] = ruleMSwitchingGaussianControlledVariance(messages[411], messages[185], marginals[:z_044], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_044])\n",
      "marginals[:x_045_x_044] = ruleMSwitchingGaussianControlledVariance(messages[409], messages[187], marginals[:z_045], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_045])\n",
      "marginals[:x_046_x_045] = ruleMSwitchingGaussianControlledVariance(messages[407], messages[189], marginals[:z_046], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_046])\n",
      "marginals[:x_047_x_046] = ruleMSwitchingGaussianControlledVariance(messages[405], messages[191], marginals[:z_047], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_047])\n",
      "marginals[:x_048_x_047] = ruleMSwitchingGaussianControlledVariance(messages[403], messages[193], marginals[:z_048], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_048])\n",
      "marginals[:x_049_x_048] = ruleMSwitchingGaussianControlledVariance(messages[401], messages[195], marginals[:z_049], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_049])\n",
      "marginals[:x_050_x_049] = ruleMSwitchingGaussianControlledVariance(messages[399], messages[197], marginals[:z_050], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_050])\n",
      "marginals[:x_051_x_050] = ruleMSwitchingGaussianControlledVariance(messages[397], messages[199], marginals[:z_051], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_051])\n",
      "marginals[:x_052_x_051] = ruleMSwitchingGaussianControlledVariance(messages[395], messages[201], marginals[:z_052], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_052])\n",
      "marginals[:x_053_x_052] = ruleMSwitchingGaussianControlledVariance(messages[393], messages[203], marginals[:z_053], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_053])\n",
      "marginals[:x_054_x_053] = ruleMSwitchingGaussianControlledVariance(messages[391], messages[205], marginals[:z_054], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_054])\n",
      "marginals[:x_055_x_054] = ruleMSwitchingGaussianControlledVariance(messages[389], messages[207], marginals[:z_055], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_055])\n",
      "marginals[:x_056_x_055] = ruleMSwitchingGaussianControlledVariance(messages[387], messages[209], marginals[:z_056], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_056])\n",
      "marginals[:x_057_x_056] = ruleMSwitchingGaussianControlledVariance(messages[385], messages[211], marginals[:z_057], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_057])\n",
      "marginals[:x_058_x_057] = ruleMSwitchingGaussianControlledVariance(messages[383], messages[213], marginals[:z_058], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_058])\n",
      "marginals[:x_059_x_058] = ruleMSwitchingGaussianControlledVariance(messages[381], messages[215], marginals[:z_059], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_059])\n",
      "marginals[:x_060_x_059] = ruleMSwitchingGaussianControlledVariance(messages[379], messages[217], marginals[:z_060], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_060])\n",
      "marginals[:x_061_x_060] = ruleMSwitchingGaussianControlledVariance(messages[377], messages[219], marginals[:z_061], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_061])\n",
      "marginals[:x_062_x_061] = ruleMSwitchingGaussianControlledVariance(messages[375], messages[221], marginals[:z_062], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_062])\n",
      "marginals[:x_063_x_062] = ruleMSwitchingGaussianControlledVariance(messages[373], messages[223], marginals[:z_063], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_063])\n",
      "marginals[:x_064_x_063] = ruleMSwitchingGaussianControlledVariance(messages[371], messages[225], marginals[:z_064], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_064])\n",
      "marginals[:x_065_x_064] = ruleMSwitchingGaussianControlledVariance(messages[369], messages[227], marginals[:z_065], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_065])\n",
      "marginals[:x_066_x_065] = ruleMSwitchingGaussianControlledVariance(messages[367], messages[229], marginals[:z_066], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_066])\n",
      "marginals[:x_067_x_066] = ruleMSwitchingGaussianControlledVariance(messages[365], messages[231], marginals[:z_067], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_067])\n",
      "marginals[:x_068_x_067] = ruleMSwitchingGaussianControlledVariance(messages[363], messages[233], marginals[:z_068], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_068])\n",
      "marginals[:x_069_x_068] = ruleMSwitchingGaussianControlledVariance(messages[361], messages[235], marginals[:z_069], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_069])\n",
      "marginals[:x_070_x_069] = ruleMSwitchingGaussianControlledVariance(messages[359], messages[237], marginals[:z_070], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_070])\n",
      "marginals[:x_071_x_070] = ruleMSwitchingGaussianControlledVariance(messages[357], messages[239], marginals[:z_071], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_071])\n",
      "marginals[:x_072_x_071] = ruleMSwitchingGaussianControlledVariance(messages[355], messages[241], marginals[:z_072], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_072])\n",
      "marginals[:x_073_x_072] = ruleMSwitchingGaussianControlledVariance(messages[353], messages[243], marginals[:z_073], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_073])\n",
      "marginals[:x_074_x_073] = ruleMSwitchingGaussianControlledVariance(messages[351], messages[245], marginals[:z_074], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_074])\n",
      "marginals[:x_075_x_074] = ruleMSwitchingGaussianControlledVariance(messages[349], messages[247], marginals[:z_075], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_075])\n",
      "marginals[:x_076_x_075] = ruleMSwitchingGaussianControlledVariance(messages[347], messages[249], marginals[:z_076], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_076])\n",
      "marginals[:x_077_x_076] = ruleMSwitchingGaussianControlledVariance(messages[345], messages[251], marginals[:z_077], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_077])\n",
      "marginals[:x_078_x_077] = ruleMSwitchingGaussianControlledVariance(messages[343], messages[253], marginals[:z_078], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_078])\n",
      "marginals[:x_079_x_078] = ruleMSwitchingGaussianControlledVariance(messages[341], messages[255], marginals[:z_079], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_079])\n",
      "marginals[:x_080_x_079] = ruleMSwitchingGaussianControlledVariance(messages[339], messages[257], marginals[:z_080], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_080])\n",
      "marginals[:x_081_x_080] = ruleMSwitchingGaussianControlledVariance(messages[337], messages[259], marginals[:z_081], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_081])\n",
      "marginals[:x_082_x_081] = ruleMSwitchingGaussianControlledVariance(messages[335], messages[261], marginals[:z_082], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_082])\n",
      "marginals[:x_083_x_082] = ruleMSwitchingGaussianControlledVariance(messages[333], messages[263], marginals[:z_083], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_083])\n",
      "marginals[:x_084_x_083] = ruleMSwitchingGaussianControlledVariance(messages[331], messages[265], marginals[:z_084], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_084])\n",
      "marginals[:x_085_x_084] = ruleMSwitchingGaussianControlledVariance(messages[329], messages[267], marginals[:z_085], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_085])\n",
      "marginals[:x_086_x_085] = ruleMSwitchingGaussianControlledVariance(messages[327], messages[269], marginals[:z_086], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_086])\n",
      "marginals[:x_087_x_086] = ruleMSwitchingGaussianControlledVariance(messages[325], messages[271], marginals[:z_087], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_087])\n",
      "marginals[:x_088_x_087] = ruleMSwitchingGaussianControlledVariance(messages[323], messages[273], marginals[:z_088], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_088])\n",
      "marginals[:x_089_x_088] = ruleMSwitchingGaussianControlledVariance(messages[321], messages[275], marginals[:z_089], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_089])\n",
      "marginals[:x_090_x_089] = ruleMSwitchingGaussianControlledVariance(messages[319], messages[277], marginals[:z_090], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_090])\n",
      "marginals[:x_091_x_090] = ruleMSwitchingGaussianControlledVariance(messages[317], messages[279], marginals[:z_091], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_091])\n",
      "marginals[:x_092_x_091] = ruleMSwitchingGaussianControlledVariance(messages[315], messages[281], marginals[:z_092], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_092])\n",
      "marginals[:x_093_x_092] = ruleMSwitchingGaussianControlledVariance(messages[313], messages[283], marginals[:z_093], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_093])\n",
      "marginals[:x_094_x_093] = ruleMSwitchingGaussianControlledVariance(messages[311], messages[285], marginals[:z_094], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_094])\n",
      "marginals[:x_095_x_094] = ruleMSwitchingGaussianControlledVariance(messages[309], messages[287], marginals[:z_095], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_095])\n",
      "marginals[:x_096_x_095] = ruleMSwitchingGaussianControlledVariance(messages[307], messages[289], marginals[:z_096], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_096])\n",
      "marginals[:x_097_x_096] = ruleMSwitchingGaussianControlledVariance(messages[305], messages[291], marginals[:z_097], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_097])\n",
      "marginals[:x_098_x_097] = ruleMSwitchingGaussianControlledVariance(messages[303], messages[293], marginals[:z_098], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_098])\n",
      "marginals[:x_099_x_098] = ruleMSwitchingGaussianControlledVariance(messages[301], messages[295], marginals[:z_099], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_099])\n",
      "marginals[:x_100_x_099] = ruleMSwitchingGaussianControlledVariance(messages[299], messages[297], marginals[:z_100], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_100])\n",
      "\n",
      "return marginals\n",
      "\n",
      "end\n",
      "\n",
      "function freeEnergy(data::Dict, marginals::Dict; dump::Union{GraphDump, Nothing}=nothing)\n",
      "\n",
      "F = 0.0\n",
      "\n",
      "F += averageEnergy(Categorical, marginals[:s_001], ProbabilityDistribution(Multivariate, PointMass, m=[0.3333333333333333, 0.3333333333333333, 0.3333333333333333]))\n",
      "F += averageEnergy(Dirichlet, marginals[:A], ProbabilityDistribution(MatrixVariate, PointMass, m=[1.0 1.0 1.0; 1.0 1.0 1.0; 1.0 1.0 1.0]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:ω], ProbabilityDistribution(Multivariate, PointMass, m=data[:mω]), ProbabilityDistribution(MatrixVariate, PointMass, m=data[:wω]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][4]), marginals[:x_004], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_004]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][49]), marginals[:x_049], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_049]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_050_z_049], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_050]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][50]), marginals[:x_050], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_050]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_051_z_050], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_051]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][51]), marginals[:x_051], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_051]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_052_z_051], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_052]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][52]), marginals[:x_052], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_052]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_053_z_052], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_053]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][53]), marginals[:x_053], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_053]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_054_z_053], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_054]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_005_z_004], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_005]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][54]), marginals[:x_054], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_054]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_055_z_054], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_055]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][55]), marginals[:x_055], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_055]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_056_z_055], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_056]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][56]), marginals[:x_056], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_056]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_057_z_056], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_057]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][57]), marginals[:x_057], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_057]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_058_z_057], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_058]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][58]), marginals[:x_058], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_058]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_059_z_058], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_059]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][5]), marginals[:x_005], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_005]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][59]), marginals[:x_059], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_059]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_060_z_059], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_060]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][60]), marginals[:x_060], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_060]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_061_z_060], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_061]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][61]), marginals[:x_061], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_061]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_062_z_061], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_062]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][62]), marginals[:x_062], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_062]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_063_z_062], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_063]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][63]), marginals[:x_063], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_063]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_064_z_063], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_064]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_006_z_005], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_006]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][64]), marginals[:x_064], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_064]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_065_z_064], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_065]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][65]), marginals[:x_065], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_065]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_066_z_065], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_066]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][66]), marginals[:x_066], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_066]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_067_z_066], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_067]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][67]), marginals[:x_067], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_067]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_068_z_067], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_068]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][68]), marginals[:x_068], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_068]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_069_z_068], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_069]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][6]), marginals[:x_006], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_006]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][69]), marginals[:x_069], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_069]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_070_z_069], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_070]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][70]), marginals[:x_070], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_070]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_071_z_070], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_071]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][71]), marginals[:x_071], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_071]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_072_z_071], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_072]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][72]), marginals[:x_072], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_072]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_073_z_072], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_073]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][73]), marginals[:x_073], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_073]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_074_z_073], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_074]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_007_z_006], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_007]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][74]), marginals[:x_074], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_074]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_075_z_074], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_075]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][75]), marginals[:x_075], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_075]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_076_z_075], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_076]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][76]), marginals[:x_076], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_076]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_077_z_076], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_077]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][77]), marginals[:x_077], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_077]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_078_z_077], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_078]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][78]), marginals[:x_078], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_078]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_079_z_078], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_079]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][7]), marginals[:x_007], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_007]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][79]), marginals[:x_079], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_079]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_080_z_079], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_080]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][80]), marginals[:x_080], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_080]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_081_z_080], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_081]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][81]), marginals[:x_081], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_081]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_082_z_081], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_082]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][82]), marginals[:x_082], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_082]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_083_z_082], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_083]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][83]), marginals[:x_083], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_083]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_084_z_083], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_084]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_008_z_007], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_008]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][84]), marginals[:x_084], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_084]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_085_z_084], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_085]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][85]), marginals[:x_085], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_085]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_086_z_085], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_086]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][86]), marginals[:x_086], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_086]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_087_z_086], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_087]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][87]), marginals[:x_087], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_087]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_088_z_087], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_088]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][88]), marginals[:x_088], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_088]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_089_z_088], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_089]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][8]), marginals[:x_008], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_008]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][89]), marginals[:x_089], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_089]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_090_z_089], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_090]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][90]), marginals[:x_090], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_090]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_091_z_090], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_091]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][91]), marginals[:x_091], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_091]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_092_z_091], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_092]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][92]), marginals[:x_092], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_092]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_093_z_092], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_093]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][93]), marginals[:x_093], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_093]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_094_z_093], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_094]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_009_z_008], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_009]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][94]), marginals[:x_094], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_094]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_095_z_094], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_095]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][95]), marginals[:x_095], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_095]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_096_z_095], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_096]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][96]), marginals[:x_096], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_096]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_097_z_096], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_097]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][97]), marginals[:x_097], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_097]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_098_z_097], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_098]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][98]), marginals[:x_098], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_098]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_099_z_098], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_099]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_001], ProbabilityDistribution(Univariate, PointMass, m=data[:mz_prior1]), ProbabilityDistribution(Univariate, PointMass, m=data[:wz_prior1]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][9]), marginals[:x_009], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_009]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][99]), marginals[:x_099], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_099]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_100_z_099], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_100]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][100]), marginals[:x_100], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_100]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_010_z_009], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_010]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][10]), marginals[:x_010], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_010]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_011_z_010], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_011]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][11]), marginals[:x_011], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_011]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_012_z_011], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_012]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][12]), marginals[:x_012], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_012]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_013_z_012], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_013]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][13]), marginals[:x_013], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_013]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_014_z_013], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_014]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:x_001], ProbabilityDistribution(Univariate, PointMass, m=data[:mx_prior1]), ProbabilityDistribution(Univariate, PointMass, m=data[:wx_prior1]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][14]), marginals[:x_014], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_014]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_015_z_014], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_015]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][15]), marginals[:x_015], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_015]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_016_z_015], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_016]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][16]), marginals[:x_016], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_016]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_017_z_016], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_017]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][17]), marginals[:x_017], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_017]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_018_z_017], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_018]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][18]), marginals[:x_018], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_018]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_019_z_018], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_019]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][1]), marginals[:x_001], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_prior1]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][19]), marginals[:x_019], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_019]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_020_z_019], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_020]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][20]), marginals[:x_020], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_020]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_021_z_020], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_021]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][21]), marginals[:x_021], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_021]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_022_z_021], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_022]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][22]), marginals[:x_022], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_022]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_023_z_022], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_023]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][23]), marginals[:x_023], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_023]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_024_z_023], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_024]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_002_z_001], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_002]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][24]), marginals[:x_024], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_024]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_025_z_024], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_025]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][25]), marginals[:x_025], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_025]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_026_z_025], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_026]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][26]), marginals[:x_026], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_026]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_027_z_026], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_027]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][27]), marginals[:x_027], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_027]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_028_z_027], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_028]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][28]), marginals[:x_028], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_028]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_029_z_028], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_029]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][2]), marginals[:x_002], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_002]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][29]), marginals[:x_029], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_029]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_030_z_029], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_030]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][30]), marginals[:x_030], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_030]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_031_z_030], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_031]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][31]), marginals[:x_031], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_031]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_032_z_031], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_032]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][32]), marginals[:x_032], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_032]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_033_z_032], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_033]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][33]), marginals[:x_033], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_033]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_034_z_033], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_034]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_003_z_002], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_003]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][34]), marginals[:x_034], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_034]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_035_z_034], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_035]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][35]), marginals[:x_035], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_035]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_036_z_035], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_036]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][36]), marginals[:x_036], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_036]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_037_z_036], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_037]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][37]), marginals[:x_037], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_037]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_038_z_037], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_038]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][38]), marginals[:x_038], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_038]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_039_z_038], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_039]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][3]), marginals[:x_003], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_003]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][39]), marginals[:x_039], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_039]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_040_z_039], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_040]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][40]), marginals[:x_040], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_040]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_041_z_040], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_041]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][41]), marginals[:x_041], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_041]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_042_z_041], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_042]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][42]), marginals[:x_042], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_042]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_043_z_042], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_043]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][43]), marginals[:x_043], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_043]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_044_z_043], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_044]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_004_z_003], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_004]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][44]), marginals[:x_044], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_044]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_045_z_044], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_045]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][45]), marginals[:x_045], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_045]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_046_z_045], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_046]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][46]), marginals[:x_046], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_046]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_047_z_046], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_047]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][47]), marginals[:x_047], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_047]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_048_z_047], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_048]))\n",
      "F += averageEnergy(GaussianMeanPrecision, ProbabilityDistribution(Univariate, PointMass, m=data[:y][48]), marginals[:x_048], ProbabilityDistribution(Univariate, PointMass, m=data[:wy_transition_048]))\n",
      "F += averageEnergy(GaussianMeanPrecision, marginals[:z_049_z_048], ProbabilityDistribution(Univariate, PointMass, m=data[:wz_transition_049]))\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_002_x_001], marginals[:z_002], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_002])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_011_x_010], marginals[:z_011], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_011])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_012_x_011], marginals[:z_012], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_012])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_013_x_012], marginals[:z_013], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_013])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_014_x_013], marginals[:z_014], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_014])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_015_x_014], marginals[:z_015], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_015])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_016_x_015], marginals[:z_016], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_016])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_017_x_016], marginals[:z_017], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_017])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_018_x_017], marginals[:z_018], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_018])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_019_x_018], marginals[:z_019], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_019])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_020_x_019], marginals[:z_020], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_020])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_003_x_002], marginals[:z_003], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_003])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_021_x_020], marginals[:z_021], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_021])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_022_x_021], marginals[:z_022], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_022])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_023_x_022], marginals[:z_023], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_023])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_024_x_023], marginals[:z_024], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_024])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_025_x_024], marginals[:z_025], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_025])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_026_x_025], marginals[:z_026], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_026])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_027_x_026], marginals[:z_027], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_027])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_028_x_027], marginals[:z_028], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_028])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_029_x_028], marginals[:z_029], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_029])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_030_x_029], marginals[:z_030], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_030])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_004_x_003], marginals[:z_004], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_004])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_031_x_030], marginals[:z_031], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_031])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_032_x_031], marginals[:z_032], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_032])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_033_x_032], marginals[:z_033], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_033])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_034_x_033], marginals[:z_034], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_034])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_035_x_034], marginals[:z_035], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_035])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_036_x_035], marginals[:z_036], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_036])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_037_x_036], marginals[:z_037], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_037])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_038_x_037], marginals[:z_038], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_038])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_039_x_038], marginals[:z_039], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_039])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_040_x_039], marginals[:z_040], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_040])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_005_x_004], marginals[:z_005], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_005])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_041_x_040], marginals[:z_041], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_041])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_042_x_041], marginals[:z_042], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_042])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_043_x_042], marginals[:z_043], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_043])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_044_x_043], marginals[:z_044], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_044])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_045_x_044], marginals[:z_045], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_045])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_046_x_045], marginals[:z_046], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_046])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_047_x_046], marginals[:z_047], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_047])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_048_x_047], marginals[:z_048], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_048])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_049_x_048], marginals[:z_049], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_049])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_050_x_049], marginals[:z_050], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_050])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_006_x_005], marginals[:z_006], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_006])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_051_x_050], marginals[:z_051], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_051])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_052_x_051], marginals[:z_052], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_052])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_053_x_052], marginals[:z_053], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_053])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_054_x_053], marginals[:z_054], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_054])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_055_x_054], marginals[:z_055], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_055])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_056_x_055], marginals[:z_056], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_056])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_057_x_056], marginals[:z_057], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_057])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_058_x_057], marginals[:z_058], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_058])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_059_x_058], marginals[:z_059], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_059])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_060_x_059], marginals[:z_060], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_060])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_007_x_006], marginals[:z_007], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_007])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_061_x_060], marginals[:z_061], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_061])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_062_x_061], marginals[:z_062], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_062])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_063_x_062], marginals[:z_063], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_063])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_064_x_063], marginals[:z_064], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_064])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_065_x_064], marginals[:z_065], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_065])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_066_x_065], marginals[:z_066], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_066])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_067_x_066], marginals[:z_067], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_067])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_068_x_067], marginals[:z_068], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_068])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_069_x_068], marginals[:z_069], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_069])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_070_x_069], marginals[:z_070], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_070])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_008_x_007], marginals[:z_008], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_008])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_071_x_070], marginals[:z_071], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_071])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_072_x_071], marginals[:z_072], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_072])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_073_x_072], marginals[:z_073], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_073])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_074_x_073], marginals[:z_074], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_074])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_075_x_074], marginals[:z_075], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_075])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_076_x_075], marginals[:z_076], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_076])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_077_x_076], marginals[:z_077], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_077])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_078_x_077], marginals[:z_078], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_078])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_079_x_078], marginals[:z_079], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_079])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_080_x_079], marginals[:z_080], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_080])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_009_x_008], marginals[:z_009], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_009])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_081_x_080], marginals[:z_081], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_081])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_082_x_081], marginals[:z_082], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_082])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_083_x_082], marginals[:z_083], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_083])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_084_x_083], marginals[:z_084], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_084])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_085_x_084], marginals[:z_085], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_085])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_086_x_085], marginals[:z_086], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_086])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_087_x_086], marginals[:z_087], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_087])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_088_x_087], marginals[:z_088], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_088])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_089_x_088], marginals[:z_089], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_089])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_090_x_089], marginals[:z_090], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_090])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_010_x_009], marginals[:z_010], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_010])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_091_x_090], marginals[:z_091], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_091])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_092_x_091], marginals[:z_092], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_092])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_093_x_092], marginals[:z_093], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_093])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_094_x_093], marginals[:z_094], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_094])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_095_x_094], marginals[:z_095], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_095])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_096_x_095], marginals[:z_096], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_096])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_097_x_096], marginals[:z_097], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_097])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_098_x_097], marginals[:z_098], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_098])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_099_x_098], marginals[:z_099], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_099])\n",
      "F += averageEnergy(SwitchingGaussianControlledVariance, marginals[:x_100_x_099], marginals[:z_100], ProbabilityDistribution(Multivariate, PointMass, m=[1.0, 1.0, 1.0]), marginals[:ω], marginals[:s_100])\n",
      "F += averageEnergy(Transition, marginals[:s_002_s_001], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_011_s_010], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_012_s_011], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_013_s_012], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_014_s_013], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_015_s_014], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_016_s_015], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_017_s_016], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_018_s_017], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_019_s_018], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_020_s_019], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_003_s_002], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_021_s_020], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_022_s_021], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_023_s_022], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_024_s_023], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_025_s_024], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_026_s_025], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_027_s_026], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_028_s_027], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_029_s_028], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_030_s_029], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_004_s_003], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_031_s_030], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_032_s_031], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_033_s_032], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_034_s_033], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_035_s_034], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_036_s_035], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_037_s_036], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_038_s_037], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_039_s_038], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_040_s_039], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_005_s_004], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_041_s_040], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_042_s_041], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_043_s_042], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_044_s_043], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_045_s_044], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_046_s_045], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_047_s_046], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_048_s_047], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_049_s_048], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_050_s_049], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_006_s_005], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_051_s_050], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_052_s_051], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_053_s_052], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_054_s_053], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_055_s_054], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_056_s_055], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_057_s_056], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_058_s_057], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_059_s_058], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_060_s_059], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_007_s_006], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_061_s_060], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_062_s_061], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_063_s_062], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_064_s_063], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_065_s_064], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_066_s_065], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_067_s_066], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_068_s_067], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_069_s_068], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_070_s_069], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_008_s_007], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_071_s_070], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_072_s_071], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_073_s_072], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_074_s_073], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_075_s_074], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_076_s_075], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_077_s_076], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_078_s_077], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_079_s_078], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_080_s_079], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_009_s_008], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_081_s_080], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_082_s_081], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_083_s_082], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_084_s_083], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_085_s_084], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_086_s_085], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_087_s_086], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_088_s_087], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_089_s_088], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_090_s_089], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_010_s_009], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_091_s_090], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_092_s_091], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_093_s_092], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_094_s_093], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_095_s_094], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_096_s_095], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_097_s_096], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_098_s_097], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_099_s_098], marginals[:A])\n",
      "F += averageEnergy(Transition, marginals[:s_100_s_099], marginals[:A])\n",
      "\n",
      "F -= differentialEntropy(marginals[:A])\n",
      "F -= -1*differentialEntropy(marginals[:s_002])\n",
      "F -= differentialEntropy(marginals[:s_002_s_001])\n",
      "F -= -1*differentialEntropy(marginals[:s_003])\n",
      "F -= differentialEntropy(marginals[:s_003_s_002])\n",
      "F -= -1*differentialEntropy(marginals[:s_004])\n",
      "F -= differentialEntropy(marginals[:s_004_s_003])\n",
      "F -= -1*differentialEntropy(marginals[:s_005])\n",
      "F -= differentialEntropy(marginals[:s_005_s_004])\n",
      "F -= -1*differentialEntropy(marginals[:s_006])\n",
      "F -= differentialEntropy(marginals[:s_006_s_005])\n",
      "F -= -1*differentialEntropy(marginals[:s_007])\n",
      "F -= differentialEntropy(marginals[:s_007_s_006])\n",
      "F -= -1*differentialEntropy(marginals[:s_008])\n",
      "F -= differentialEntropy(marginals[:s_008_s_007])\n",
      "F -= -1*differentialEntropy(marginals[:s_009])\n",
      "F -= differentialEntropy(marginals[:s_009_s_008])\n",
      "F -= -1*differentialEntropy(marginals[:s_010])\n",
      "F -= differentialEntropy(marginals[:s_010_s_009])\n",
      "F -= -1*differentialEntropy(marginals[:s_011])\n",
      "F -= differentialEntropy(marginals[:s_011_s_010])\n",
      "F -= -1*differentialEntropy(marginals[:s_012])\n",
      "F -= differentialEntropy(marginals[:s_012_s_011])\n",
      "F -= -1*differentialEntropy(marginals[:s_013])\n",
      "F -= differentialEntropy(marginals[:s_013_s_012])\n",
      "F -= -1*differentialEntropy(marginals[:s_014])\n",
      "F -= differentialEntropy(marginals[:s_014_s_013])\n",
      "F -= -1*differentialEntropy(marginals[:s_015])\n",
      "F -= differentialEntropy(marginals[:s_015_s_014])\n",
      "F -= -1*differentialEntropy(marginals[:s_016])\n",
      "F -= differentialEntropy(marginals[:s_016_s_015])\n",
      "F -= -1*differentialEntropy(marginals[:s_017])\n",
      "F -= differentialEntropy(marginals[:s_017_s_016])\n",
      "F -= -1*differentialEntropy(marginals[:s_018])\n",
      "F -= differentialEntropy(marginals[:s_018_s_017])\n",
      "F -= -1*differentialEntropy(marginals[:s_019])\n",
      "F -= differentialEntropy(marginals[:s_019_s_018])\n",
      "F -= -1*differentialEntropy(marginals[:s_020])\n",
      "F -= differentialEntropy(marginals[:s_020_s_019])\n",
      "F -= -1*differentialEntropy(marginals[:s_021])\n",
      "F -= differentialEntropy(marginals[:s_021_s_020])\n",
      "F -= -1*differentialEntropy(marginals[:s_022])\n",
      "F -= differentialEntropy(marginals[:s_022_s_021])\n",
      "F -= -1*differentialEntropy(marginals[:s_023])\n",
      "F -= differentialEntropy(marginals[:s_023_s_022])\n",
      "F -= -1*differentialEntropy(marginals[:s_024])\n",
      "F -= differentialEntropy(marginals[:s_024_s_023])\n",
      "F -= -1*differentialEntropy(marginals[:s_025])\n",
      "F -= differentialEntropy(marginals[:s_025_s_024])\n",
      "F -= -1*differentialEntropy(marginals[:s_026])\n",
      "F -= differentialEntropy(marginals[:s_026_s_025])\n",
      "F -= -1*differentialEntropy(marginals[:s_027])\n",
      "F -= differentialEntropy(marginals[:s_027_s_026])\n",
      "F -= -1*differentialEntropy(marginals[:s_028])\n",
      "F -= differentialEntropy(marginals[:s_028_s_027])\n",
      "F -= -1*differentialEntropy(marginals[:s_029])\n",
      "F -= differentialEntropy(marginals[:s_029_s_028])\n",
      "F -= -1*differentialEntropy(marginals[:s_030])\n",
      "F -= differentialEntropy(marginals[:s_030_s_029])\n",
      "F -= -1*differentialEntropy(marginals[:s_031])\n",
      "F -= differentialEntropy(marginals[:s_031_s_030])\n",
      "F -= -1*differentialEntropy(marginals[:s_032])\n",
      "F -= differentialEntropy(marginals[:s_032_s_031])\n",
      "F -= -1*differentialEntropy(marginals[:s_033])\n",
      "F -= differentialEntropy(marginals[:s_033_s_032])\n",
      "F -= -1*differentialEntropy(marginals[:s_034])\n",
      "F -= differentialEntropy(marginals[:s_034_s_033])\n",
      "F -= -1*differentialEntropy(marginals[:s_035])\n",
      "F -= differentialEntropy(marginals[:s_035_s_034])\n",
      "F -= -1*differentialEntropy(marginals[:s_036])\n",
      "F -= differentialEntropy(marginals[:s_036_s_035])\n",
      "F -= -1*differentialEntropy(marginals[:s_037])\n",
      "F -= differentialEntropy(marginals[:s_037_s_036])\n",
      "F -= -1*differentialEntropy(marginals[:s_038])\n",
      "F -= differentialEntropy(marginals[:s_038_s_037])\n",
      "F -= -1*differentialEntropy(marginals[:s_039])\n",
      "F -= differentialEntropy(marginals[:s_039_s_038])\n",
      "F -= -1*differentialEntropy(marginals[:s_040])\n",
      "F -= differentialEntropy(marginals[:s_040_s_039])\n",
      "F -= -1*differentialEntropy(marginals[:s_041])\n",
      "F -= differentialEntropy(marginals[:s_041_s_040])\n",
      "F -= -1*differentialEntropy(marginals[:s_042])\n",
      "F -= differentialEntropy(marginals[:s_042_s_041])\n",
      "F -= -1*differentialEntropy(marginals[:s_043])\n",
      "F -= differentialEntropy(marginals[:s_043_s_042])\n",
      "F -= -1*differentialEntropy(marginals[:s_044])\n",
      "F -= differentialEntropy(marginals[:s_044_s_043])\n",
      "F -= -1*differentialEntropy(marginals[:s_045])\n",
      "F -= differentialEntropy(marginals[:s_045_s_044])\n",
      "F -= -1*differentialEntropy(marginals[:s_046])\n",
      "F -= differentialEntropy(marginals[:s_046_s_045])\n",
      "F -= -1*differentialEntropy(marginals[:s_047])\n",
      "F -= differentialEntropy(marginals[:s_047_s_046])\n",
      "F -= -1*differentialEntropy(marginals[:s_048])\n",
      "F -= differentialEntropy(marginals[:s_048_s_047])\n",
      "F -= -1*differentialEntropy(marginals[:s_049])\n",
      "F -= differentialEntropy(marginals[:s_049_s_048])\n",
      "F -= -1*differentialEntropy(marginals[:s_050])\n",
      "F -= differentialEntropy(marginals[:s_050_s_049])\n",
      "F -= -1*differentialEntropy(marginals[:s_051])\n",
      "F -= differentialEntropy(marginals[:s_051_s_050])\n",
      "F -= -1*differentialEntropy(marginals[:s_052])\n",
      "F -= differentialEntropy(marginals[:s_052_s_051])\n",
      "F -= -1*differentialEntropy(marginals[:s_053])\n",
      "F -= differentialEntropy(marginals[:s_053_s_052])\n",
      "F -= -1*differentialEntropy(marginals[:s_054])\n",
      "F -= differentialEntropy(marginals[:s_054_s_053])\n",
      "F -= -1*differentialEntropy(marginals[:s_055])\n",
      "F -= differentialEntropy(marginals[:s_055_s_054])\n",
      "F -= -1*differentialEntropy(marginals[:s_056])\n",
      "F -= differentialEntropy(marginals[:s_056_s_055])\n",
      "F -= -1*differentialEntropy(marginals[:s_057])\n",
      "F -= differentialEntropy(marginals[:s_057_s_056])\n",
      "F -= -1*differentialEntropy(marginals[:s_058])\n",
      "F -= differentialEntropy(marginals[:s_058_s_057])\n",
      "F -= -1*differentialEntropy(marginals[:s_059])\n",
      "F -= differentialEntropy(marginals[:s_059_s_058])\n",
      "F -= -1*differentialEntropy(marginals[:s_060])\n",
      "F -= differentialEntropy(marginals[:s_060_s_059])\n",
      "F -= -1*differentialEntropy(marginals[:s_061])\n",
      "F -= differentialEntropy(marginals[:s_061_s_060])\n",
      "F -= -1*differentialEntropy(marginals[:s_062])\n",
      "F -= differentialEntropy(marginals[:s_062_s_061])\n",
      "F -= -1*differentialEntropy(marginals[:s_063])\n",
      "F -= differentialEntropy(marginals[:s_063_s_062])\n",
      "F -= -1*differentialEntropy(marginals[:s_064])\n",
      "F -= differentialEntropy(marginals[:s_064_s_063])\n",
      "F -= -1*differentialEntropy(marginals[:s_065])\n",
      "F -= differentialEntropy(marginals[:s_065_s_064])\n",
      "F -= -1*differentialEntropy(marginals[:s_066])\n",
      "F -= differentialEntropy(marginals[:s_066_s_065])\n",
      "F -= -1*differentialEntropy(marginals[:s_067])\n",
      "F -= differentialEntropy(marginals[:s_067_s_066])\n",
      "F -= -1*differentialEntropy(marginals[:s_068])\n",
      "F -= differentialEntropy(marginals[:s_068_s_067])\n",
      "F -= -1*differentialEntropy(marginals[:s_069])\n",
      "F -= differentialEntropy(marginals[:s_069_s_068])\n",
      "F -= -1*differentialEntropy(marginals[:s_070])\n",
      "F -= differentialEntropy(marginals[:s_070_s_069])\n",
      "F -= -1*differentialEntropy(marginals[:s_071])\n",
      "F -= differentialEntropy(marginals[:s_071_s_070])\n",
      "F -= -1*differentialEntropy(marginals[:s_072])\n",
      "F -= differentialEntropy(marginals[:s_072_s_071])\n",
      "F -= -1*differentialEntropy(marginals[:s_073])\n",
      "F -= differentialEntropy(marginals[:s_073_s_072])\n",
      "F -= -1*differentialEntropy(marginals[:s_074])\n",
      "F -= differentialEntropy(marginals[:s_074_s_073])\n",
      "F -= -1*differentialEntropy(marginals[:s_075])\n",
      "F -= differentialEntropy(marginals[:s_075_s_074])\n",
      "F -= -1*differentialEntropy(marginals[:s_076])\n",
      "F -= differentialEntropy(marginals[:s_076_s_075])\n",
      "F -= -1*differentialEntropy(marginals[:s_077])\n",
      "F -= differentialEntropy(marginals[:s_077_s_076])\n",
      "F -= -1*differentialEntropy(marginals[:s_078])\n",
      "F -= differentialEntropy(marginals[:s_078_s_077])\n",
      "F -= -1*differentialEntropy(marginals[:s_079])\n",
      "F -= differentialEntropy(marginals[:s_079_s_078])\n",
      "F -= -1*differentialEntropy(marginals[:s_080])\n",
      "F -= differentialEntropy(marginals[:s_080_s_079])\n",
      "F -= -1*differentialEntropy(marginals[:s_081])\n",
      "F -= differentialEntropy(marginals[:s_081_s_080])\n",
      "F -= -1*differentialEntropy(marginals[:s_082])\n",
      "F -= differentialEntropy(marginals[:s_082_s_081])\n",
      "F -= -1*differentialEntropy(marginals[:s_083])\n",
      "F -= differentialEntropy(marginals[:s_083_s_082])\n",
      "F -= -1*differentialEntropy(marginals[:s_084])\n",
      "F -= differentialEntropy(marginals[:s_084_s_083])\n",
      "F -= -1*differentialEntropy(marginals[:s_085])\n",
      "F -= differentialEntropy(marginals[:s_085_s_084])\n",
      "F -= -1*differentialEntropy(marginals[:s_086])\n",
      "F -= differentialEntropy(marginals[:s_086_s_085])\n",
      "F -= -1*differentialEntropy(marginals[:s_087])\n",
      "F -= differentialEntropy(marginals[:s_087_s_086])\n",
      "F -= -1*differentialEntropy(marginals[:s_088])\n",
      "F -= differentialEntropy(marginals[:s_088_s_087])\n",
      "F -= -1*differentialEntropy(marginals[:s_089])\n",
      "F -= differentialEntropy(marginals[:s_089_s_088])\n",
      "F -= -1*differentialEntropy(marginals[:s_090])\n",
      "F -= differentialEntropy(marginals[:s_090_s_089])\n",
      "F -= -1*differentialEntropy(marginals[:s_091])\n",
      "F -= differentialEntropy(marginals[:s_091_s_090])\n",
      "F -= -1*differentialEntropy(marginals[:s_092])\n",
      "F -= differentialEntropy(marginals[:s_092_s_091])\n",
      "F -= -1*differentialEntropy(marginals[:s_093])\n",
      "F -= differentialEntropy(marginals[:s_093_s_092])\n",
      "F -= -1*differentialEntropy(marginals[:s_094])\n",
      "F -= differentialEntropy(marginals[:s_094_s_093])\n",
      "F -= -1*differentialEntropy(marginals[:s_095])\n",
      "F -= differentialEntropy(marginals[:s_095_s_094])\n",
      "F -= -1*differentialEntropy(marginals[:s_096])\n",
      "F -= differentialEntropy(marginals[:s_096_s_095])\n",
      "F -= -1*differentialEntropy(marginals[:s_097])\n",
      "F -= differentialEntropy(marginals[:s_097_s_096])\n",
      "F -= -1*differentialEntropy(marginals[:s_098])\n",
      "F -= differentialEntropy(marginals[:s_098_s_097])\n",
      "F -= -1*differentialEntropy(marginals[:s_099])\n",
      "F -= differentialEntropy(marginals[:s_099_s_098])\n",
      "F -= differentialEntropy(marginals[:s_100_s_099])\n",
      "F -= -1*differentialEntropy(marginals[:x_002])\n",
      "F -= differentialEntropy(marginals[:x_002_x_001])\n",
      "F -= -1*differentialEntropy(marginals[:x_003])\n",
      "F -= differentialEntropy(marginals[:x_003_x_002])\n",
      "F -= -1*differentialEntropy(marginals[:x_004])\n",
      "F -= differentialEntropy(marginals[:x_004_x_003])\n",
      "F -= -1*differentialEntropy(marginals[:x_005])\n",
      "F -= differentialEntropy(marginals[:x_005_x_004])\n",
      "F -= -1*differentialEntropy(marginals[:x_006])\n",
      "F -= differentialEntropy(marginals[:x_006_x_005])\n",
      "F -= -1*differentialEntropy(marginals[:x_007])\n",
      "F -= differentialEntropy(marginals[:x_007_x_006])\n",
      "F -= -1*differentialEntropy(marginals[:x_008])\n",
      "F -= differentialEntropy(marginals[:x_008_x_007])\n",
      "F -= -1*differentialEntropy(marginals[:x_009])\n",
      "F -= differentialEntropy(marginals[:x_009_x_008])\n",
      "F -= -1*differentialEntropy(marginals[:x_010])\n",
      "F -= differentialEntropy(marginals[:x_010_x_009])\n",
      "F -= -1*differentialEntropy(marginals[:x_011])\n",
      "F -= differentialEntropy(marginals[:x_011_x_010])\n",
      "F -= -1*differentialEntropy(marginals[:x_012])\n",
      "F -= differentialEntropy(marginals[:x_012_x_011])\n",
      "F -= -1*differentialEntropy(marginals[:x_013])\n",
      "F -= differentialEntropy(marginals[:x_013_x_012])\n",
      "F -= -1*differentialEntropy(marginals[:x_014])\n",
      "F -= differentialEntropy(marginals[:x_014_x_013])\n",
      "F -= -1*differentialEntropy(marginals[:x_015])\n",
      "F -= differentialEntropy(marginals[:x_015_x_014])\n",
      "F -= -1*differentialEntropy(marginals[:x_016])\n",
      "F -= differentialEntropy(marginals[:x_016_x_015])\n",
      "F -= -1*differentialEntropy(marginals[:x_017])\n",
      "F -= differentialEntropy(marginals[:x_017_x_016])\n",
      "F -= -1*differentialEntropy(marginals[:x_018])\n",
      "F -= differentialEntropy(marginals[:x_018_x_017])\n",
      "F -= -1*differentialEntropy(marginals[:x_019])\n",
      "F -= differentialEntropy(marginals[:x_019_x_018])\n",
      "F -= -1*differentialEntropy(marginals[:x_020])\n",
      "F -= differentialEntropy(marginals[:x_020_x_019])\n",
      "F -= -1*differentialEntropy(marginals[:x_021])\n",
      "F -= differentialEntropy(marginals[:x_021_x_020])\n",
      "F -= -1*differentialEntropy(marginals[:x_022])\n",
      "F -= differentialEntropy(marginals[:x_022_x_021])\n",
      "F -= -1*differentialEntropy(marginals[:x_023])\n",
      "F -= differentialEntropy(marginals[:x_023_x_022])\n",
      "F -= -1*differentialEntropy(marginals[:x_024])\n",
      "F -= differentialEntropy(marginals[:x_024_x_023])\n",
      "F -= -1*differentialEntropy(marginals[:x_025])\n",
      "F -= differentialEntropy(marginals[:x_025_x_024])\n",
      "F -= -1*differentialEntropy(marginals[:x_026])\n",
      "F -= differentialEntropy(marginals[:x_026_x_025])\n",
      "F -= -1*differentialEntropy(marginals[:x_027])\n",
      "F -= differentialEntropy(marginals[:x_027_x_026])\n",
      "F -= -1*differentialEntropy(marginals[:x_028])\n",
      "F -= differentialEntropy(marginals[:x_028_x_027])\n",
      "F -= -1*differentialEntropy(marginals[:x_029])\n",
      "F -= differentialEntropy(marginals[:x_029_x_028])\n",
      "F -= -1*differentialEntropy(marginals[:x_030])\n",
      "F -= differentialEntropy(marginals[:x_030_x_029])\n",
      "F -= -1*differentialEntropy(marginals[:x_031])\n",
      "F -= differentialEntropy(marginals[:x_031_x_030])\n",
      "F -= -1*differentialEntropy(marginals[:x_032])\n",
      "F -= differentialEntropy(marginals[:x_032_x_031])\n",
      "F -= -1*differentialEntropy(marginals[:x_033])\n",
      "F -= differentialEntropy(marginals[:x_033_x_032])\n",
      "F -= -1*differentialEntropy(marginals[:x_034])\n",
      "F -= differentialEntropy(marginals[:x_034_x_033])\n",
      "F -= -1*differentialEntropy(marginals[:x_035])\n",
      "F -= differentialEntropy(marginals[:x_035_x_034])\n",
      "F -= -1*differentialEntropy(marginals[:x_036])\n",
      "F -= differentialEntropy(marginals[:x_036_x_035])\n",
      "F -= -1*differentialEntropy(marginals[:x_037])\n",
      "F -= differentialEntropy(marginals[:x_037_x_036])\n",
      "F -= -1*differentialEntropy(marginals[:x_038])\n",
      "F -= differentialEntropy(marginals[:x_038_x_037])\n",
      "F -= -1*differentialEntropy(marginals[:x_039])\n",
      "F -= differentialEntropy(marginals[:x_039_x_038])\n",
      "F -= -1*differentialEntropy(marginals[:x_040])\n",
      "F -= differentialEntropy(marginals[:x_040_x_039])\n",
      "F -= -1*differentialEntropy(marginals[:x_041])\n",
      "F -= differentialEntropy(marginals[:x_041_x_040])\n",
      "F -= -1*differentialEntropy(marginals[:x_042])\n",
      "F -= differentialEntropy(marginals[:x_042_x_041])\n",
      "F -= -1*differentialEntropy(marginals[:x_043])\n",
      "F -= differentialEntropy(marginals[:x_043_x_042])\n",
      "F -= -1*differentialEntropy(marginals[:x_044])\n",
      "F -= differentialEntropy(marginals[:x_044_x_043])\n",
      "F -= -1*differentialEntropy(marginals[:x_045])\n",
      "F -= differentialEntropy(marginals[:x_045_x_044])\n",
      "F -= -1*differentialEntropy(marginals[:x_046])\n",
      "F -= differentialEntropy(marginals[:x_046_x_045])\n",
      "F -= -1*differentialEntropy(marginals[:x_047])\n",
      "F -= differentialEntropy(marginals[:x_047_x_046])\n",
      "F -= -1*differentialEntropy(marginals[:x_048])\n",
      "F -= differentialEntropy(marginals[:x_048_x_047])\n",
      "F -= -1*differentialEntropy(marginals[:x_049])\n",
      "F -= differentialEntropy(marginals[:x_049_x_048])\n",
      "F -= -1*differentialEntropy(marginals[:x_050])\n",
      "F -= differentialEntropy(marginals[:x_050_x_049])\n",
      "F -= -1*differentialEntropy(marginals[:x_051])\n",
      "F -= differentialEntropy(marginals[:x_051_x_050])\n",
      "F -= -1*differentialEntropy(marginals[:x_052])\n",
      "F -= differentialEntropy(marginals[:x_052_x_051])\n",
      "F -= -1*differentialEntropy(marginals[:x_053])\n",
      "F -= differentialEntropy(marginals[:x_053_x_052])\n",
      "F -= -1*differentialEntropy(marginals[:x_054])\n",
      "F -= differentialEntropy(marginals[:x_054_x_053])\n",
      "F -= -1*differentialEntropy(marginals[:x_055])\n",
      "F -= differentialEntropy(marginals[:x_055_x_054])\n",
      "F -= -1*differentialEntropy(marginals[:x_056])\n",
      "F -= differentialEntropy(marginals[:x_056_x_055])\n",
      "F -= -1*differentialEntropy(marginals[:x_057])\n",
      "F -= differentialEntropy(marginals[:x_057_x_056])\n",
      "F -= -1*differentialEntropy(marginals[:x_058])\n",
      "F -= differentialEntropy(marginals[:x_058_x_057])\n",
      "F -= -1*differentialEntropy(marginals[:x_059])\n",
      "F -= differentialEntropy(marginals[:x_059_x_058])\n",
      "F -= -1*differentialEntropy(marginals[:x_060])\n",
      "F -= differentialEntropy(marginals[:x_060_x_059])\n",
      "F -= -1*differentialEntropy(marginals[:x_061])\n",
      "F -= differentialEntropy(marginals[:x_061_x_060])\n",
      "F -= -1*differentialEntropy(marginals[:x_062])\n",
      "F -= differentialEntropy(marginals[:x_062_x_061])\n",
      "F -= -1*differentialEntropy(marginals[:x_063])\n",
      "F -= differentialEntropy(marginals[:x_063_x_062])\n",
      "F -= -1*differentialEntropy(marginals[:x_064])\n",
      "F -= differentialEntropy(marginals[:x_064_x_063])\n",
      "F -= -1*differentialEntropy(marginals[:x_065])\n",
      "F -= differentialEntropy(marginals[:x_065_x_064])\n",
      "F -= -1*differentialEntropy(marginals[:x_066])\n",
      "F -= differentialEntropy(marginals[:x_066_x_065])\n",
      "F -= -1*differentialEntropy(marginals[:x_067])\n",
      "F -= differentialEntropy(marginals[:x_067_x_066])\n",
      "F -= -1*differentialEntropy(marginals[:x_068])\n",
      "F -= differentialEntropy(marginals[:x_068_x_067])\n",
      "F -= -1*differentialEntropy(marginals[:x_069])\n",
      "F -= differentialEntropy(marginals[:x_069_x_068])\n",
      "F -= -1*differentialEntropy(marginals[:x_070])\n",
      "F -= differentialEntropy(marginals[:x_070_x_069])\n",
      "F -= -1*differentialEntropy(marginals[:x_071])\n",
      "F -= differentialEntropy(marginals[:x_071_x_070])\n",
      "F -= -1*differentialEntropy(marginals[:x_072])\n",
      "F -= differentialEntropy(marginals[:x_072_x_071])\n",
      "F -= -1*differentialEntropy(marginals[:x_073])\n",
      "F -= differentialEntropy(marginals[:x_073_x_072])\n",
      "F -= -1*differentialEntropy(marginals[:x_074])\n",
      "F -= differentialEntropy(marginals[:x_074_x_073])\n",
      "F -= -1*differentialEntropy(marginals[:x_075])\n",
      "F -= differentialEntropy(marginals[:x_075_x_074])\n",
      "F -= -1*differentialEntropy(marginals[:x_076])\n",
      "F -= differentialEntropy(marginals[:x_076_x_075])\n",
      "F -= -1*differentialEntropy(marginals[:x_077])\n",
      "F -= differentialEntropy(marginals[:x_077_x_076])\n",
      "F -= -1*differentialEntropy(marginals[:x_078])\n",
      "F -= differentialEntropy(marginals[:x_078_x_077])\n",
      "F -= -1*differentialEntropy(marginals[:x_079])\n",
      "F -= differentialEntropy(marginals[:x_079_x_078])\n",
      "F -= -1*differentialEntropy(marginals[:x_080])\n",
      "F -= differentialEntropy(marginals[:x_080_x_079])\n",
      "F -= -1*differentialEntropy(marginals[:x_081])\n",
      "F -= differentialEntropy(marginals[:x_081_x_080])\n",
      "F -= -1*differentialEntropy(marginals[:x_082])\n",
      "F -= differentialEntropy(marginals[:x_082_x_081])\n",
      "F -= -1*differentialEntropy(marginals[:x_083])\n",
      "F -= differentialEntropy(marginals[:x_083_x_082])\n",
      "F -= -1*differentialEntropy(marginals[:x_084])\n",
      "F -= differentialEntropy(marginals[:x_084_x_083])\n",
      "F -= -1*differentialEntropy(marginals[:x_085])\n",
      "F -= differentialEntropy(marginals[:x_085_x_084])\n",
      "F -= -1*differentialEntropy(marginals[:x_086])\n",
      "F -= differentialEntropy(marginals[:x_086_x_085])\n",
      "F -= -1*differentialEntropy(marginals[:x_087])\n",
      "F -= differentialEntropy(marginals[:x_087_x_086])\n",
      "F -= -1*differentialEntropy(marginals[:x_088])\n",
      "F -= differentialEntropy(marginals[:x_088_x_087])\n",
      "F -= -1*differentialEntropy(marginals[:x_089])\n",
      "F -= differentialEntropy(marginals[:x_089_x_088])\n",
      "F -= -1*differentialEntropy(marginals[:x_090])\n",
      "F -= differentialEntropy(marginals[:x_090_x_089])\n",
      "F -= -1*differentialEntropy(marginals[:x_091])\n",
      "F -= differentialEntropy(marginals[:x_091_x_090])\n",
      "F -= -1*differentialEntropy(marginals[:x_092])\n",
      "F -= differentialEntropy(marginals[:x_092_x_091])\n",
      "F -= -1*differentialEntropy(marginals[:x_093])\n",
      "F -= differentialEntropy(marginals[:x_093_x_092])\n",
      "F -= -1*differentialEntropy(marginals[:x_094])\n",
      "F -= differentialEntropy(marginals[:x_094_x_093])\n",
      "F -= -1*differentialEntropy(marginals[:x_095])\n",
      "F -= differentialEntropy(marginals[:x_095_x_094])\n",
      "F -= -1*differentialEntropy(marginals[:x_096])\n",
      "F -= differentialEntropy(marginals[:x_096_x_095])\n",
      "F -= -1*differentialEntropy(marginals[:x_097])\n",
      "F -= differentialEntropy(marginals[:x_097_x_096])\n",
      "F -= -1*differentialEntropy(marginals[:x_098])\n",
      "F -= differentialEntropy(marginals[:x_098_x_097])\n",
      "F -= -1*differentialEntropy(marginals[:x_099])\n",
      "F -= differentialEntropy(marginals[:x_099_x_098])\n",
      "F -= differentialEntropy(marginals[:x_100_x_099])\n",
      "F -= -1*differentialEntropy(marginals[:z_002])\n",
      "F -= differentialEntropy(marginals[:z_002_z_001])\n",
      "F -= -1*differentialEntropy(marginals[:z_003])\n",
      "F -= differentialEntropy(marginals[:z_003_z_002])\n",
      "F -= -1*differentialEntropy(marginals[:z_004])\n",
      "F -= differentialEntropy(marginals[:z_004_z_003])\n",
      "F -= -1*differentialEntropy(marginals[:z_005])\n",
      "F -= differentialEntropy(marginals[:z_005_z_004])\n",
      "F -= -1*differentialEntropy(marginals[:z_006])\n",
      "F -= differentialEntropy(marginals[:z_006_z_005])\n",
      "F -= -1*differentialEntropy(marginals[:z_007])\n",
      "F -= differentialEntropy(marginals[:z_007_z_006])\n",
      "F -= -1*differentialEntropy(marginals[:z_008])\n",
      "F -= differentialEntropy(marginals[:z_008_z_007])\n",
      "F -= -1*differentialEntropy(marginals[:z_009])\n",
      "F -= differentialEntropy(marginals[:z_009_z_008])\n",
      "F -= -1*differentialEntropy(marginals[:z_010])\n",
      "F -= differentialEntropy(marginals[:z_010_z_009])\n",
      "F -= -1*differentialEntropy(marginals[:z_011])\n",
      "F -= differentialEntropy(marginals[:z_011_z_010])\n",
      "F -= -1*differentialEntropy(marginals[:z_012])\n",
      "F -= differentialEntropy(marginals[:z_012_z_011])\n",
      "F -= -1*differentialEntropy(marginals[:z_013])\n",
      "F -= differentialEntropy(marginals[:z_013_z_012])\n",
      "F -= -1*differentialEntropy(marginals[:z_014])\n",
      "F -= differentialEntropy(marginals[:z_014_z_013])\n",
      "F -= -1*differentialEntropy(marginals[:z_015])\n",
      "F -= differentialEntropy(marginals[:z_015_z_014])\n",
      "F -= -1*differentialEntropy(marginals[:z_016])\n",
      "F -= differentialEntropy(marginals[:z_016_z_015])\n",
      "F -= -1*differentialEntropy(marginals[:z_017])\n",
      "F -= differentialEntropy(marginals[:z_017_z_016])\n",
      "F -= -1*differentialEntropy(marginals[:z_018])\n",
      "F -= differentialEntropy(marginals[:z_018_z_017])\n",
      "F -= -1*differentialEntropy(marginals[:z_019])\n",
      "F -= differentialEntropy(marginals[:z_019_z_018])\n",
      "F -= -1*differentialEntropy(marginals[:z_020])\n",
      "F -= differentialEntropy(marginals[:z_020_z_019])\n",
      "F -= -1*differentialEntropy(marginals[:z_021])\n",
      "F -= differentialEntropy(marginals[:z_021_z_020])\n",
      "F -= -1*differentialEntropy(marginals[:z_022])\n",
      "F -= differentialEntropy(marginals[:z_022_z_021])\n",
      "F -= -1*differentialEntropy(marginals[:z_023])\n",
      "F -= differentialEntropy(marginals[:z_023_z_022])\n",
      "F -= -1*differentialEntropy(marginals[:z_024])\n",
      "F -= differentialEntropy(marginals[:z_024_z_023])\n",
      "F -= -1*differentialEntropy(marginals[:z_025])\n",
      "F -= differentialEntropy(marginals[:z_025_z_024])\n",
      "F -= -1*differentialEntropy(marginals[:z_026])\n",
      "F -= differentialEntropy(marginals[:z_026_z_025])\n",
      "F -= -1*differentialEntropy(marginals[:z_027])\n",
      "F -= differentialEntropy(marginals[:z_027_z_026])\n",
      "F -= -1*differentialEntropy(marginals[:z_028])\n",
      "F -= differentialEntropy(marginals[:z_028_z_027])\n",
      "F -= -1*differentialEntropy(marginals[:z_029])\n",
      "F -= differentialEntropy(marginals[:z_029_z_028])\n",
      "F -= -1*differentialEntropy(marginals[:z_030])\n",
      "F -= differentialEntropy(marginals[:z_030_z_029])\n",
      "F -= -1*differentialEntropy(marginals[:z_031])\n",
      "F -= differentialEntropy(marginals[:z_031_z_030])\n",
      "F -= -1*differentialEntropy(marginals[:z_032])\n",
      "F -= differentialEntropy(marginals[:z_032_z_031])\n",
      "F -= -1*differentialEntropy(marginals[:z_033])\n",
      "F -= differentialEntropy(marginals[:z_033_z_032])\n",
      "F -= -1*differentialEntropy(marginals[:z_034])\n",
      "F -= differentialEntropy(marginals[:z_034_z_033])\n",
      "F -= -1*differentialEntropy(marginals[:z_035])\n",
      "F -= differentialEntropy(marginals[:z_035_z_034])\n",
      "F -= -1*differentialEntropy(marginals[:z_036])\n",
      "F -= differentialEntropy(marginals[:z_036_z_035])\n",
      "F -= -1*differentialEntropy(marginals[:z_037])\n",
      "F -= differentialEntropy(marginals[:z_037_z_036])\n",
      "F -= -1*differentialEntropy(marginals[:z_038])\n",
      "F -= differentialEntropy(marginals[:z_038_z_037])\n",
      "F -= -1*differentialEntropy(marginals[:z_039])\n",
      "F -= differentialEntropy(marginals[:z_039_z_038])\n",
      "F -= -1*differentialEntropy(marginals[:z_040])\n",
      "F -= differentialEntropy(marginals[:z_040_z_039])\n",
      "F -= -1*differentialEntropy(marginals[:z_041])\n",
      "F -= differentialEntropy(marginals[:z_041_z_040])\n",
      "F -= -1*differentialEntropy(marginals[:z_042])\n",
      "F -= differentialEntropy(marginals[:z_042_z_041])\n",
      "F -= -1*differentialEntropy(marginals[:z_043])\n",
      "F -= differentialEntropy(marginals[:z_043_z_042])\n",
      "F -= -1*differentialEntropy(marginals[:z_044])\n",
      "F -= differentialEntropy(marginals[:z_044_z_043])\n",
      "F -= -1*differentialEntropy(marginals[:z_045])\n",
      "F -= differentialEntropy(marginals[:z_045_z_044])\n",
      "F -= -1*differentialEntropy(marginals[:z_046])\n",
      "F -= differentialEntropy(marginals[:z_046_z_045])\n",
      "F -= -1*differentialEntropy(marginals[:z_047])\n",
      "F -= differentialEntropy(marginals[:z_047_z_046])\n",
      "F -= -1*differentialEntropy(marginals[:z_048])\n",
      "F -= differentialEntropy(marginals[:z_048_z_047])\n",
      "F -= -1*differentialEntropy(marginals[:z_049])\n",
      "F -= differentialEntropy(marginals[:z_049_z_048])\n",
      "F -= -1*differentialEntropy(marginals[:z_050])\n",
      "F -= differentialEntropy(marginals[:z_050_z_049])\n",
      "F -= -1*differentialEntropy(marginals[:z_051])\n",
      "F -= differentialEntropy(marginals[:z_051_z_050])\n",
      "F -= -1*differentialEntropy(marginals[:z_052])\n",
      "F -= differentialEntropy(marginals[:z_052_z_051])\n",
      "F -= -1*differentialEntropy(marginals[:z_053])\n",
      "F -= differentialEntropy(marginals[:z_053_z_052])\n",
      "F -= -1*differentialEntropy(marginals[:z_054])\n",
      "F -= differentialEntropy(marginals[:z_054_z_053])\n",
      "F -= -1*differentialEntropy(marginals[:z_055])\n",
      "F -= differentialEntropy(marginals[:z_055_z_054])\n",
      "F -= -1*differentialEntropy(marginals[:z_056])\n",
      "F -= differentialEntropy(marginals[:z_056_z_055])\n",
      "F -= -1*differentialEntropy(marginals[:z_057])\n",
      "F -= differentialEntropy(marginals[:z_057_z_056])\n",
      "F -= -1*differentialEntropy(marginals[:z_058])\n",
      "F -= differentialEntropy(marginals[:z_058_z_057])\n",
      "F -= -1*differentialEntropy(marginals[:z_059])\n",
      "F -= differentialEntropy(marginals[:z_059_z_058])\n",
      "F -= -1*differentialEntropy(marginals[:z_060])\n",
      "F -= differentialEntropy(marginals[:z_060_z_059])\n",
      "F -= -1*differentialEntropy(marginals[:z_061])\n",
      "F -= differentialEntropy(marginals[:z_061_z_060])\n",
      "F -= -1*differentialEntropy(marginals[:z_062])\n",
      "F -= differentialEntropy(marginals[:z_062_z_061])\n",
      "F -= -1*differentialEntropy(marginals[:z_063])\n",
      "F -= differentialEntropy(marginals[:z_063_z_062])\n",
      "F -= -1*differentialEntropy(marginals[:z_064])\n",
      "F -= differentialEntropy(marginals[:z_064_z_063])\n",
      "F -= -1*differentialEntropy(marginals[:z_065])\n",
      "F -= differentialEntropy(marginals[:z_065_z_064])\n",
      "F -= -1*differentialEntropy(marginals[:z_066])\n",
      "F -= differentialEntropy(marginals[:z_066_z_065])\n",
      "F -= -1*differentialEntropy(marginals[:z_067])\n",
      "F -= differentialEntropy(marginals[:z_067_z_066])\n",
      "F -= -1*differentialEntropy(marginals[:z_068])\n",
      "F -= differentialEntropy(marginals[:z_068_z_067])\n",
      "F -= -1*differentialEntropy(marginals[:z_069])\n",
      "F -= differentialEntropy(marginals[:z_069_z_068])\n",
      "F -= -1*differentialEntropy(marginals[:z_070])\n",
      "F -= differentialEntropy(marginals[:z_070_z_069])\n",
      "F -= -1*differentialEntropy(marginals[:z_071])\n",
      "F -= differentialEntropy(marginals[:z_071_z_070])\n",
      "F -= -1*differentialEntropy(marginals[:z_072])\n",
      "F -= differentialEntropy(marginals[:z_072_z_071])\n",
      "F -= -1*differentialEntropy(marginals[:z_073])\n",
      "F -= differentialEntropy(marginals[:z_073_z_072])\n",
      "F -= -1*differentialEntropy(marginals[:z_074])\n",
      "F -= differentialEntropy(marginals[:z_074_z_073])\n",
      "F -= -1*differentialEntropy(marginals[:z_075])\n",
      "F -= differentialEntropy(marginals[:z_075_z_074])\n",
      "F -= -1*differentialEntropy(marginals[:z_076])\n",
      "F -= differentialEntropy(marginals[:z_076_z_075])\n",
      "F -= -1*differentialEntropy(marginals[:z_077])\n",
      "F -= differentialEntropy(marginals[:z_077_z_076])\n",
      "F -= -1*differentialEntropy(marginals[:z_078])\n",
      "F -= differentialEntropy(marginals[:z_078_z_077])\n",
      "F -= -1*differentialEntropy(marginals[:z_079])\n",
      "F -= differentialEntropy(marginals[:z_079_z_078])\n",
      "F -= -1*differentialEntropy(marginals[:z_080])\n",
      "F -= differentialEntropy(marginals[:z_080_z_079])\n",
      "F -= -1*differentialEntropy(marginals[:z_081])\n",
      "F -= differentialEntropy(marginals[:z_081_z_080])\n",
      "F -= -1*differentialEntropy(marginals[:z_082])\n",
      "F -= differentialEntropy(marginals[:z_082_z_081])\n",
      "F -= -1*differentialEntropy(marginals[:z_083])\n",
      "F -= differentialEntropy(marginals[:z_083_z_082])\n",
      "F -= -1*differentialEntropy(marginals[:z_084])\n",
      "F -= differentialEntropy(marginals[:z_084_z_083])\n",
      "F -= -1*differentialEntropy(marginals[:z_085])\n",
      "F -= differentialEntropy(marginals[:z_085_z_084])\n",
      "F -= -1*differentialEntropy(marginals[:z_086])\n",
      "F -= differentialEntropy(marginals[:z_086_z_085])\n",
      "F -= -1*differentialEntropy(marginals[:z_087])\n",
      "F -= differentialEntropy(marginals[:z_087_z_086])\n",
      "F -= -1*differentialEntropy(marginals[:z_088])\n",
      "F -= differentialEntropy(marginals[:z_088_z_087])\n",
      "F -= -1*differentialEntropy(marginals[:z_089])\n",
      "F -= differentialEntropy(marginals[:z_089_z_088])\n",
      "F -= -1*differentialEntropy(marginals[:z_090])\n",
      "F -= differentialEntropy(marginals[:z_090_z_089])\n",
      "F -= -1*differentialEntropy(marginals[:z_091])\n",
      "F -= differentialEntropy(marginals[:z_091_z_090])\n",
      "F -= -1*differentialEntropy(marginals[:z_092])\n",
      "F -= differentialEntropy(marginals[:z_092_z_091])\n",
      "F -= -1*differentialEntropy(marginals[:z_093])\n",
      "F -= differentialEntropy(marginals[:z_093_z_092])\n",
      "F -= -1*differentialEntropy(marginals[:z_094])\n",
      "F -= differentialEntropy(marginals[:z_094_z_093])\n",
      "F -= -1*differentialEntropy(marginals[:z_095])\n",
      "F -= differentialEntropy(marginals[:z_095_z_094])\n",
      "F -= -1*differentialEntropy(marginals[:z_096])\n",
      "F -= differentialEntropy(marginals[:z_096_z_095])\n",
      "F -= -1*differentialEntropy(marginals[:z_097])\n",
      "F -= differentialEntropy(marginals[:z_097_z_096])\n",
      "F -= -1*differentialEntropy(marginals[:z_098])\n",
      "F -= differentialEntropy(marginals[:z_098_z_097])\n",
      "F -= -1*differentialEntropy(marginals[:z_099])\n",
      "F -= differentialEntropy(marginals[:z_099_z_098])\n",
      "F -= differentialEntropy(marginals[:z_100_z_099])\n",
      "F -= differentialEntropy(marginals[:ω])\n",
      "\n",
      "if dump !== nothing\n",
      "    push!(dump.steps, AlgorithmStep())\n",
      "end\n",
      "return F\n",
      "\n",
      "end\n",
      "\n",
      "end # block"
     ]
    },
    {
     "ename": "LoadError",
     "evalue": "InterruptException:",
     "output_type": "error",
     "traceback": [
      "InterruptException:",
      "",
      "Stacktrace:",
      "  [1] sigatomic_end",
      "    @ ./c.jl:437 [inlined]",
      "  [2] uv_write(s::Base.PipeEndpoint, p::Ptr{UInt8}, n::UInt64)",
      "    @ Base ./stream.jl:988",
      "  [3] unsafe_write(s::Base.PipeEndpoint, p::Ptr{UInt8}, n::UInt64)",
      "    @ Base ./stream.jl:1064",
      "  [4] unsafe_write",
      "    @ ./io.jl:362 [inlined]",
      "  [5] write",
      "    @ ./strings/io.jl:244 [inlined]",
      "  [6] print",
      "    @ ./strings/io.jl:246 [inlined]",
      "  [7] print(::IJulia.IJuliaStdio{Base.PipeEndpoint}, ::String, ::String, ::Vararg{String})",
      "    @ Base ./strings/io.jl:46",
      "  [8] println(::IJulia.IJuliaStdio{Base.PipeEndpoint}, ::String, ::Vararg{String})",
      "    @ Base ./strings/io.jl:75",
      "  [9] println(xs::String)",
      "    @ Base ./coreio.jl:4",
      " [10] eval",
      "    @ ./boot.jl:373 [inlined]",
      " [11] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)",
      "    @ Base ./loading.jl:1196"
     ]
    }
   ],
   "source": [
    "println(code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "freeEnergy (generic function with 1 method)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate MP algorithm\n",
    "code = generate_mp(n_cats, n_samples)\n",
    "eval(Meta.parse(code))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mDatasets 100%|███████████████████████████████████████████| Time: 0:19:40\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "# Dictionary for storing the results\n",
    "results = Dict()\n",
    "\n",
    "@showprogress \"Datasets\" for i in 1:n_datasets\n",
    "    obs = dataset[i][\"obs\"]\n",
    "    mnv = dataset[i][\"nv\"]\n",
    "    omegas = dataset[i][\"ωs\"] .+ sqrt(1.0)*randn(length(dataset[i][\"ωs\"]))\n",
    "    try\n",
    "        mz,vz,mx,vx,ms, mω, vω,fe = mp(obs, ndims=n_cats, ω_m_prior=omegas,\n",
    "                                      ω_w_prior=diageye(n_cats),\n",
    "                                      y_w_transition_prior=1/mnv)\n",
    "        results[i] = Dict(\"mz\" => mz, \"vz\" => vz,\n",
    "                          \"mx\" => mx, \"vx\" => vx,\n",
    "                          \"ms\" => ms, \"fe\" => fe,\n",
    "                          \"mω\" => mω, \"vω\" => vω,\n",
    "                          \"ωprior\" => omegas)\n",
    "    catch e\n",
    "           println(\"Failed $(i)\")\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "using JLD\n",
    "# Saving results and data\n",
    "# You can use the saved files inside \"Retrieve research results\" section\n",
    "rfilename = \"dump/results_verification_analytic_mixture.jld\"\n",
    "dfilename = \"dump/dataset_test.jld\"\n",
    "JLD.save(rfilename, \"results\", results)\n",
    "JLD.save(dfilename, \"dataset\", dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.7.2"
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