infrence error

[jakubMitura14]

Hello I created some simple baysian network ; training works well but inference to get some results is not - what am I doing wrong - below complete working example - just need to change path I attach example data

using MLUtils
using LossFunctions
using Statistics
using RxInfer
using Random
# using Plots # Uncomment if plotting is needed
using StableRNGs
using LinearAlgebra # For Matrix(I, n, n) used for diageye
using CSV, DataFrames # Added for data loading


# Hardcoded dataset path
dataset_path = "/workspaces/aider_my/cardio_onco_model/data/exp_raw/synth_data/synth_prediction_data_simple.csv"

# Hardcoded cardinalities
cardinalities = Dict{String, Int}(
    "Obesity" => 2,
    "MI" => 2,
    "Cachexia" => 2,
    "metabol" => 4,
)

# Load the dataset
df = CSV.read(dataset_path, DataFrame)

# Function to one-hot encode a single value (0-based index input)
function one_hot_encode(value, cardinality)
    # Assumes value is 0-based index
    encoded = zeros(Float64, cardinality)
    if 0 <= value < cardinality
        encoded[value + 1] = 1.0 # Julia arrays are 1-based
    else
        # Handle unexpected values (e.g., missing, out of range) if necessary
        # For now, return a zero vector or throw an error
        println("Warning: Value $value is not a valid 0-based index for cardinality $cardinality. Returning zero vector.")
    end
    return encoded
end

# Prepare data variables (one-hot encoded)
function prepare_data_arrays(df_in, cardinalities)
    return (
            Cachexia_data = [one_hot_encode(row."Cachexia", cardinalities["Cachexia"]) for row in eachrow(df_in)],
            MI_data = [one_hot_encode(row."MI", cardinalities["MI"]) for row in eachrow(df_in)],
            Obesity_data = [one_hot_encode(row."Obesity", cardinalities["Obesity"]) for row in eachrow(df_in)],
            )
end



# --- Model Definition ---
# Defines the structure of the Bayesian network and how variables relate.
@model function cardio_model(Cachexia_data, MI_data, Obesity_data, cpt_Cachexia_Obesity_metabol, cpt_metabol_MI)
    # Variable Cachexia (no parents)
    Cachexia ~ Categorical([0.5, 0.5])
    Cachexia_data ~ DiscreteTransition(Cachexia, Matrix(I, 2, 2))

    # Variable Obesity (no parents)
    Obesity ~ Categorical([0.5, 0.5])
    Obesity_data ~ DiscreteTransition(Obesity, Matrix(I, 2, 2))

    # Variable metabol (parents: Cachexia, Obesity)
    metabol ~ DiscreteTransition(Cachexia, cpt_Cachexia_Obesity_metabol, Obesity)

    # Variable MI (parents: metabol)
    MI ~ DiscreteTransition(metabol, cpt_metabol_MI)
    MI_data ~ DiscreteTransition(MI, Matrix(I, 2, 2))
end

# --- Learn Model Definition ---
# Defines how to learn the model parameters (CPTs) from data.
@model function learn_cardio_model(Cachexia_data, MI_data, Obesity_data)
    # CPT Definitions
    cpt_Cachexia_Obesity_metabol ~ DirichletCollection(ones(4, 2, 2))
    cpt_metabol_MI ~ DirichletCollection(ones(2, 4))

    # Model learning loop
for i in 1:length(MI_data)
    MI_data[i] ~ cardio_model(Cachexia_data=Cachexia_data[i], Obesity_data=Obesity_data[i], cpt_Cachexia_Obesity_metabol= cpt_Cachexia_Obesity_metabol, cpt_metabol_MI= cpt_metabol_MI)
end
end

# --- Initialization ---
# Specifies initial beliefs about the distributions before observing data.
initialization = @initialization begin
    # Initialize CPT distributions (q)
    q(cpt_Cachexia_Obesity_metabol) = DirichletCollection(ones(4, 2, 2))
    q(cpt_metabol_MI) = DirichletCollection(ones(2, 4))

    # Initialize prior means (μ) for all variables
for init in cardio_model
    μ(Cachexia) = Categorical([0.5, 0.5])
    μ(Obesity) = Categorical([0.5, 0.5])
    μ(metabol) = Categorical([0.25, 0.25, 0.25, 0.25])
    μ(MI) = Categorical([0.5, 0.5])
end
end

# --- Constraints ---
# Specifies the factorization assumptions for the variational distribution.
constraints = @constraints begin
 for q in cardio_model
    # Define factorization constraints for CPTs
        q(cpt_Cachexia_Obesity_metabol, metabol, Cachexia, Obesity) = q(metabol, Cachexia, Obesity)q(cpt_Cachexia_Obesity_metabol)
        q(cpt_metabol_MI, MI, metabol) = q(MI, metabol)q(cpt_metabol_MI)
 end
end

# --- Inference Call ---
# Dynamically construct the data argument for the infer function



train_data = prepare_data_arrays(df, cardinalities)
val_data = prepare_data_arrays(df, cardinalities)

result = infer(model=learn_cardio_model(),
            data=train_data,
            constraints=constraints,
            initialization=initialization,
            iterations=5, # Consider making iterations configurable
            showprogress=true,
            free_energy = true,
            options=(limit_stack_depth=500,)) # Consider making options configurable
pred_init = @initialization begin
    q(cpt_Cachexia_Obesity_metabol) =result.posteriors[:cpt_Cachexia_Obesity_metabol]
    q(cpt_metabol_MI) =result.posteriors[:cpt_metabol_MI]
    end

# For each validation sample, predict MI
predicted_probs = Float64[]
predicted_labels = Int[]
true_labels = Int[]

for i in 1:length(val_data.MI_data)


    # Run inference for this sample
    pred_result = infer(
        model = cardio_model(),
        data = (Cachexia_data=[val_data[:Cachexia_data][i]], MI_data=missing, Obesity_data=[val_data[:Obesity_data][i]], cpt_Cachexia_Obesity_metabol=result.posteriors[:cpt_Cachexia_Obesity_metabol], cpt_metabol_MI=result.posteriors[:cpt_metabol_MI]),
        initialization = pred_init,
        iterations = 1,
        showprogress = true,
        options = (limit_stack_depth=50,)
    )

    # Extract predicted probability for MI == 1
    mi_posterior = pred_result.posteriors[:MI]
    # For Categorical, probability for class 2 (indexing: 1=0, 2=1)
    prob_MI_1 = mi_posterior.p[2]
    push!(predicted_probs, prob_MI_1)
    push!(predicted_labels, prob_MI_1 > 0.5 ? 1 : 0)

    # True label: MI_data is one-hot, so find index of 1 (1-based, subtract 1 for 0/1)
    true_label = findfirst(x -> x == 1.0, val_data.MI_data[i]) - 1
    push!(true_labels, true_label)
end

# Compute accuracy and Brier score for this fold
acc = sum(predicted_labels .== true_labels) / length(true_labels)
brier = mean((predicted_probs .- Float64.(true_labels)).^2)
println("  Accuracy", acc)
println("  Brier score", brier)

error

┌ Error: We encountered an error during inference, here are some helpful resources to get you back on track:
│ 
│ 1. Check our Sharp bits documentation which covers common issues:
│ https://docs.rxinfer.com/stable/manuals/sharpbits/overview/
│ 2. Browse our existing discussions - your question may already be answered:
│ https://github.com/ReactiveBayes/RxInfer.jl/discussions
│ 3. Take inspiration from our set of examples:
│ https://examples.rxinfer.com/
│ 
│ Still stuck? We'd love to help! You can:
│ - Start a discussion for questions and help. Feedback and questions from new users is also welcome! If you are stuck, please reach out and we will solve it together.
│ https://github.com/ReactiveBayes/RxInfer.jl/discussions
│ - Report a bug or request a feature:
│ https://github.com/ReactiveBayes/RxInfer.jl/issues
│ - (Optional) Share your session data with `RxInfer.share_session_data()` to help us better understand the issue
│ https://docs.rxinfer.com/stable/manuals/telemetry/
│ 
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│ whether you're new to Bayesian inference, have questions about use cases, or just want to share your experience.
│ 
│ To help us help you, please include:
│ - A minimal example that reproduces the issue
│ - The complete error message and stack trace
│ - (Optional) If you shared your session data, please include the session ID in the issue
│ 
│ Use `RxInfer.disable_inference_error_hint!()` to disable this message. 
└ @ RxInfer ~/.julia/packages/RxInfer/jqOCS/src/inference/inference.jl:264
ERROR: LoadError: MethodError: no method matching probvec(::PointMass{Vector{Vector{Float64}}})
The function `probvec` exists, but no method is defined for this combination of argument types.

Closest candidates are:
  probvec(::Message)
   @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/helpers/macrohelpers.jl:99
  probvec(::Bernoulli)
   @ ExponentialFamily ~/.julia/packages/ExponentialFamily/bfGzP/src/distributions/bernoulli.jl:7
  probvec(::Categorical{P} where P<:Real)
   @ ExponentialFamily ~/.julia/packages/ExponentialFamily/bfGzP/src/distributions/categorical.jl:20
  ...

Stacktrace:
  [1] macro expansion
    @ ~/.julia/packages/Tullio/2zyFP/src/macro.jl:982 [inlined]
  [2] macro expansion
    @ ~/.julia/packages/ReactiveMP/9o9rC/src/rules/discrete_transition/predefined/structured_vmp.jl:6 [inlined]
  [3] (::ReactiveMP.var"#3444#3448"{Tuple{Marginal{PointMass{Vector{Vector{Float64}}}, Nothing}, Marginal{PointMass{Matrix{Bool}}, Nothing}}})()
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/rule.jl:428
  [4] rule(fform::Type{DiscreteTransition}, on::Val{:in}, vconstraint::Marginalisation, messages_names::Nothing, messages::Nothing, marginals_names::Val{(:out, :a)}, marginals::Tuple{Marginal{PointMass{Vector{Vector{Float64}}}, Nothing}, Marginal{PointMass{Matrix{Bool}}, Nothing}}, meta::Nothing, addons#1075::Nothing, node#1076::Nothing)
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/rule.jl:430
  [5] (::ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing})(messages::Nothing, marginals::Tuple{Marginal{PointMass{Vector{Vector{Float64}}}, Nothing}, Marginal{PointMass{Matrix{Bool}}, Nothing}})
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/message.jl:353
  [6] as_message(message::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}}, cache::Nothing, messages::Nothing, marginals::Tuple{Marginal{PointMass{Vector{Vector{Float64}}}, Nothing}, Marginal{PointMass{Matrix{Bool}}, Nothing}})
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/message.jl:235
  [7] as_message(message::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}}, cache::Nothing)
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/message.jl:231
  [8] as_message(message::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}})
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/message.jl:223
  [9] materialize!(type::ReactiveMP.EqualityRightOutbound, chain::ReactiveMP.EqualityChain{Rocket.ScheduleOnOperator{RxInfer.LimitStackScheduler}, ReactiveMP.var"#15#17"{GenericProd, CompositeFormConstraint{Tuple{UnspecifiedFormConstraint, RxInfer.EnsureSupportedFunctionalForm}}}}, node_index::Int64)
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/nodes/equality.jl:125
 [10] (::ReactiveMP.ChainOutboundMapping)(::Tuple{LazyObservable{Missing}, SingleObservable{Missing, AsapScheduler}})
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/nodes/equality.jl:165
 [11] next_received!(wrapper::Rocket.CombineLatestUpdatesActorWrapper{Tuple{LazyObservable{Missing}, SingleObservable{Missing, AsapScheduler}}, Rocket.RecentSubjectInstance{Message, Subject{Message, AsapScheduler, AsapScheduler}}, PushNew, Rocket.UInt8UpdatesStatus, ReactiveMP.ChainOutboundMapping, typeof(ReactiveMP.reset_vstatus)}, data::Missing, index::Int64)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/observable/combined_updates.jl:71
 [12] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined_updates.jl:34 [inlined]
 [13] scheduled_next!(actor::Rocket.CombineLatestUpdatesInnerActor{Missing, Rocket.CombineLatestUpdatesActorWrapper{Tuple{LazyObservable{Missing}, SingleObservable{Missing, AsapScheduler}}, Rocket.RecentSubjectInstance{Message, Subject{Message, AsapScheduler, AsapScheduler}}, PushNew, Rocket.UInt8UpdatesStatus, ReactiveMP.ChainOutboundMapping, typeof(ReactiveMP.reset_vstatus)}}, value::Missing, ::AsapScheduler)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/schedulers/asap.jl:23
 [14] on_next!(subject::Subject{Missing, AsapScheduler, AsapScheduler}, data::Missing)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/subjects/subject.jl:62
 [15] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [16] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [17] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/subjects/recent.jl:62 [inlined]
 [18] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [19] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [20] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/operators/map.jl:62 [inlined]
 [21] #7
    @ ~/.julia/packages/RxInfer/jqOCS/src/rocket.jl:86 [inlined]
 [22] limitstack(callback::RxInfer.var"#7#8"{Rocket.MapActor{Tuple{LazyObservable{Missing}, ProxyObservable{AbstractMessage, Rocket.RefCountSource{AbstractMessage, ConnectableObservable{AbstractMessage, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, ProxyObservable{AbstractMessage, ReactiveMP.MessageObservable{AbstractMessage}, Rocket.TapProxy{ReactiveMP.ChainInvalidationCallback}}}}, Rocket.RefCountProxy}}, Rocket.RecentSubjectInstance{Missing, Subject{Missing, AsapScheduler, AsapScheduler}}, Rocket.var"#168#169"{Missing}}, Tuple{LazyObservable{Missing}, ProxyObservable{AbstractMessage, Rocket.RefCountSource{AbstractMessage, ConnectableObservable{AbstractMessage, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, ProxyObservable{AbstractMessage, ReactiveMP.MessageObservable{AbstractMessage}, Rocket.TapProxy{ReactiveMP.ChainInvalidationCallback}}}}, Rocket.RefCountProxy}}}, instance::RxInfer.LimitStackScheduler)
    @ RxInfer ~/.julia/packages/RxInfer/jqOCS/src/rocket.jl:52
 [23] scheduled_next!
    @ ~/.julia/packages/RxInfer/jqOCS/src/rocket.jl:86 [inlined]
 [24] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:207 [inlined]
 [25] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/scheduled.jl:12 [inlined]
 [26] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:206 [inlined]
 [27] next_received!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined_updates.jl:72 [inlined]
 [28] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined_updates.jl:34 [inlined]
 [29] scheduled_next!(actor::Rocket.CombineLatestUpdatesInnerActor{AbstractMessage, Rocket.CombineLatestUpdatesActorWrapper{Tuple{LazyObservable{Missing}, ProxyObservable{AbstractMessage, Rocket.RefCountSource{AbstractMessage, ConnectableObservable{AbstractMessage, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, ProxyObservable{AbstractMessage, ReactiveMP.MessageObservable{AbstractMessage}, Rocket.TapProxy{ReactiveMP.ChainInvalidationCallback}}}}, Rocket.RefCountProxy}}, Rocket.ScheduledActor{Tuple{LazyObservable{Missing}, ProxyObservable{AbstractMessage, Rocket.RefCountSource{AbstractMessage, ConnectableObservable{AbstractMessage, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, ProxyObservable{AbstractMessage, ReactiveMP.MessageObservable{AbstractMessage}, Rocket.TapProxy{ReactiveMP.ChainInvalidationCallback}}}}, Rocket.RefCountProxy}}, RxInfer.LimitStackScheduler, Rocket.MapActor{Tuple{LazyObservable{Missing}, ProxyObservable{AbstractMessage, Rocket.RefCountSource{AbstractMessage, ConnectableObservable{AbstractMessage, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, ProxyObservable{AbstractMessage, ReactiveMP.MessageObservable{AbstractMessage}, Rocket.TapProxy{ReactiveMP.ChainInvalidationCallback}}}}, Rocket.RefCountProxy}}, Rocket.RecentSubjectInstance{Missing, Subject{Missing, AsapScheduler, AsapScheduler}}, Rocket.var"#168#169"{Missing}}}, PushNew, Rocket.UInt8UpdatesStatus, typeof(identity), Nothing}}, value::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}}, ::AsapScheduler)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/schedulers/asap.jl:23
 [30] on_next!(subject::Subject{AbstractMessage, AsapScheduler, AsapScheduler}, data::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}})
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/subjects/subject.jl:62
 [31] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [32] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [33] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/subjects/recent.jl:62 [inlined]
 [34] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [35] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [36] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/operators/tap.jl:63 [inlined]
 [37] scheduled_next!(actor::Rocket.TapActor{AbstractMessage, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, ReactiveMP.ChainInvalidationCallback}, value::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}}, ::AsapScheduler)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/schedulers/asap.jl:23
 [38] on_next!(subject::Subject{AbstractMessage, AsapScheduler, AsapScheduler}, data::DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}})
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/subjects/subject.jl:62
 [39] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [40] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [41] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/subjects/recent.jl:62 [inlined]
 [42] #7
    @ ~/.julia/packages/RxInfer/jqOCS/src/rocket.jl:86 [inlined]
 [43] limitstack(callback::RxInfer.var"#7#8"{Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}, DeferredMessage{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}}}, instance::RxInfer.LimitStackScheduler)
    @ RxInfer ~/.julia/packages/RxInfer/jqOCS/src/rocket.jl:52
 [44] scheduled_next!
    @ ~/.julia/packages/RxInfer/jqOCS/src/rocket.jl:86 [inlined]
 [45] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:255 [inlined]
 [46] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:203 [inlined]
 [47] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/scheduled.jl:12 [inlined]
 [48] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:206 [inlined]
 [49] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/operators/map.jl:62 [inlined]
 [50] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:206 [inlined]
 [51] next_received!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined.jl:101 [inlined]
 [52] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined.jl:68 [inlined]
 [53] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:206 [inlined]
 [54] next_received!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined_updates.jl:72 [inlined]
 [55] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/observable/combined_updates.jl:34 [inlined]
 [56] scheduled_next!(actor::Rocket.CombineLatestUpdatesInnerActor{Marginal, Rocket.CombineLatestUpdatesActorWrapper{Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, Rocket.CombineLatestInnerActor{Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}, Rocket.CombineLatestActorWrapper{Rocket.MStorage2{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}}, Rocket.MapActor{Tuple{Nothing, Tuple{ReactiveMP.MarginalObservable, ReactiveMP.MarginalObservable}}, Rocket.ScheduledActor{AbstractMessage, RxInfer.LimitStackScheduler, Rocket.RecentSubjectInstance{AbstractMessage, Subject{AbstractMessage, AsapScheduler, AsapScheduler}}}, ReactiveMP.var"#182#185"{ReactiveMP.MessageMapping{DiscreteTransition, Val{:in}, Marginalisation, Nothing, Val{(:out, :a)}, Nothing, Nothing, Nothing, Nothing}}}, PushNew, Rocket.UInt8UpdatesStatus}}, PushNew, Rocket.UInt8UpdatesStatus, typeof(identity), Nothing}}, value::Marginal{PointMass{Vector{Vector{Float64}}}, Nothing}, ::AsapScheduler)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/schedulers/asap.jl:23
 [57] on_next!(subject::Subject{Marginal, AsapScheduler, AsapScheduler}, data::Marginal{PointMass{Vector{Vector{Float64}}}, Nothing})
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/subjects/subject.jl:62
 [58] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [59] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [60] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/subjects/recent.jl:62 [inlined]
 [61] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [62] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [63] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/operators/map.jl:62 [inlined]
 [64] scheduled_next!(actor::Rocket.MapActor{Message, Rocket.RecentSubjectInstance{Marginal, Subject{Marginal, AsapScheduler, AsapScheduler}}, typeof(as_marginal)}, value::Message{PointMass{Vector{Vector{Float64}}}, Nothing}, ::AsapScheduler)
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/schedulers/asap.jl:23
 [65] on_next!(subject::Subject{Message, AsapScheduler, AsapScheduler}, data::Message{PointMass{Vector{Vector{Float64}}}, Nothing})
    @ Rocket ~/.julia/packages/Rocket/Qsjhz/src/subjects/subject.jl:62
 [66] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [67] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [68] on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/subjects/recent.jl:62 [inlined]
 [69] actor_on_next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:250 [inlined]
 [70] next!
    @ ~/.julia/packages/Rocket/Qsjhz/src/actor.jl:202 [inlined]
 [71] update!
    @ ~/.julia/packages/ReactiveMP/9o9rC/src/variables/data.jl:85 [inlined]
 [72] update!(datavar::DataVariable{Rocket.RecentSubjectInstance{Message, Subject{Message, AsapScheduler, AsapScheduler}}, ReactiveMP.MarginalObservable}, data::Vector{Vector{Float64}})
    @ ReactiveMP ~/.julia/packages/ReactiveMP/9o9rC/src/variables/data.jl:84
 [73] batch_inference(; model::GraphPPL.ModelGenerator{typeof(cardio_model), @Kwargs{}, GraphPPL.PluginsCollection{Tuple{}}, RxInfer.ReactiveMPGraphPPLBackend{Static.False}, String}, data::@NamedTuple{Cachexia_data::Vector{Vector{Float64}}, MI_data::Missing, Obesity_data::Vector{Vector{Float64}}, cpt_Cachexia_Obesity_metabol::Vector{DirichletCollection{Float64, 3, Array{Float64, 3}}}, cpt_metabol_MI::Vector{DirichletCollection{Float64, 2, Matrix{Float64}}}}, initialization::RxInfer.InitSpecification, constraints::Nothing, meta::Nothing, options::@NamedTuple{limit_stack_depth::Int64}, returnvars::Nothing, predictvars::Nothing, iterations::Int64, free_energy::Bool, free_energy_diagnostics::Tuple{RxInfer.ObjectiveDiagnosticCheckNaNs, RxInfer.ObjectiveDiagnosticCheckInfs}, allow_node_contraction::Bool, showprogress::Bool, callbacks::Nothing, addons::Nothing, postprocess::DefaultPostprocess, warn::Bool, catch_exception::Bool)
    @ RxInfer ~/.julia/packages/RxInfer/jqOCS/src/inference/batch.jl:308
 [74] batch_inference
    @ ~/.julia/packages/RxInfer/jqOCS/src/inference/batch.jl:96 [inlined]
 [75] #314
    @ ~/.julia/packages/RxInfer/jqOCS/src/inference/inference.jl:533 [inlined]
 [76] with_session(f::RxInfer.var"#314#316"{GraphPPL.ModelGenerator{typeof(cardio_model), @Kwargs{}, GraphPPL.PluginsCollection{Tuple{}}, RxInfer.ReactiveMPGraphPPLBackend{Static.False}, String}, @NamedTuple{Cachexia_data::Vector{Vector{Float64}}, MI_data::Missing, Obesity_data::Vector{Vector{Float64}}, cpt_Cachexia_Obesity_metabol::Vector{DirichletCollection{Float64, 3, Array{Float64, 3}}}, cpt_metabol_MI::Vector{DirichletCollection{Float64, 2, Matrix{Float64}}}}, Nothing, Nothing, RxInfer.InitSpecification, Nothing, Nothing, @NamedTuple{limit_stack_depth::Int64}, Nothing, Nothing, Nothing, Nothing, Int64, Bool, Tuple{RxInfer.ObjectiveDiagnosticCheckNaNs, RxInfer.ObjectiveDiagnosticCheckInfs}, Bool, Bool, Bool, Nothing, Nothing, DefaultPostprocess, Nothing, Bool, Bool, Bool}, session::RxInfer.Session, label::Symbol)
    @ RxInfer ~/.julia/packages/RxInfer/jqOCS/src/session.jl:253
 [77] #infer#313
    @ ~/.julia/packages/RxInfer/jqOCS/src/inference/inference.jl:503 [inlined]
in expression starting at /workspaces/aider_my/cardio_onco_model/src/with_file_gen.jl/bayesian_network_generator_gen.jl:138

synth_prediction_data_simple.csv

[jakubMitura14]

Ok I resolved error just in infrence for evaluation (pred_result = infer()... ) avoid using init as cpts are added ;
and wrap each cpt with mean(last( cpt .. ))