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Cleanup some dead code #243

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merged 2 commits into from
Nov 29, 2024
Merged

Cleanup some dead code #243

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c5bf173
cleanup and add some comments
sunxd3 Nov 29, 2024
70da021
version bump
sunxd3 Nov 29, 2024
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "JuliaBUGS"
uuid = "ba9fb4c0-828e-4473-b6a1-cd2560fee5bf"
version = "0.7.1"
version = "0.7.2"

[deps]
AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
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16 changes: 13 additions & 3 deletions src/model.jl
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Expand Up @@ -431,9 +431,8 @@ function check_var_group(var_group::Vector{<:VarName}, model::BUGSModel)
end

function AbstractPPL.evaluate!!(rng::Random.AbstractRNG, model::BUGSModel)
(; evaluation_env, g) = model
vi = deepcopy(evaluation_env)
logp = 0.0
evaluation_env = deepcopy(model.evaluation_env)
for (i, vn) in enumerate(model.flattened_graph_node_data.sorted_nodes)
is_stochastic = model.flattened_graph_node_data.is_stochastic_vals[i]
node_function = model.flattened_graph_node_data.node_function_vals[i]
Expand All @@ -444,7 +443,16 @@ function AbstractPPL.evaluate!!(rng::Random.AbstractRNG, model::BUGSModel)
else
dist = node_function(model.evaluation_env, loop_vars)
value = rand(rng, dist) # just sample from the prior
logp += logpdf(dist, value)
if model.transformed
# see below for why we need to transform the value
value_transformed = Bijectors.transform(Bijectors.bijector(dist), value)
logp +=
Distributions.logpdf(dist, value) + Bijectors.logabsdetjac(
Bijectors.inverse(Bijectors.bijector(dist)), value_transformed
)
else
logp += Distributions.logpdf(dist, value)
end
evaluation_env = setindex!!(evaluation_env, value, vn)
end
end
Expand All @@ -467,6 +475,8 @@ function AbstractPPL.evaluate!!(model::BUGSModel)
if model.transformed
# although the values stored in `evaluation_env` are in their original space,
# here we behave as accepting a vector of parameters in the transformed space
# this is so that we have consistent logp values between
# (1) set values in original space then evaluate (2) directly evaluate with the values in transformed space
value_transformed = Bijectors.transform(Bijectors.bijector(dist), value)
logp +=
Distributions.logpdf(dist, value) + Bijectors.logabsdetjac(
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