From ef0ac6fbe7d28bb287cf6dc75960867a7501e985 Mon Sep 17 00:00:00 2001
From: Tor Erlend Fjelde <tor.erlend95@gmail.com>
Date: Mon, 5 Jun 2023 20:22:46 +0100
Subject: [PATCH 01/20] added methods for extracting parameter values for a
 model from a given chain

---
 src/DynamicPPL.jl    |   4 +-
 src/model_utils.jl   | 208 +++++++++++++++++++++++++++++++++++++++++++
 test/turing/model.jl |  15 ++++
 3 files changed, 226 insertions(+), 1 deletion(-)
 create mode 100644 src/model_utils.jl

diff --git a/src/DynamicPPL.jl b/src/DynamicPPL.jl
index 594084d66..5fcba5d74 100644
--- a/src/DynamicPPL.jl
+++ b/src/DynamicPPL.jl
@@ -119,7 +119,8 @@ export AbstractVarInfo,
     decondition,
     # Convenience macros
     @addlogprob!,
-    @submodel
+    @submodel,
+    value_iterator_from_chain
 
 # Reexport
 using Distributions: loglikelihood
@@ -165,5 +166,6 @@ include("submodel_macro.jl")
 include("test_utils.jl")
 include("transforming.jl")
 include("logdensityfunction.jl")
+include("model_utils.jl")
 
 end # module
diff --git a/src/model_utils.jl b/src/model_utils.jl
new file mode 100644
index 000000000..fe511918a
--- /dev/null
+++ b/src/model_utils.jl
@@ -0,0 +1,208 @@
+"""
+    varnames_in_chain(model:::Model, chain)
+    varnames_in_chain(varinfo::VarInfo, chain)
+
+Return `true` if all variable names in `model`/`varinfo` are in `chain`.
+"""
+varnames_in_chain(model::Model, chain) = varnames_in_chain(VarInfo(model), chain)
+function varnames_in_chain(varinfo::VarInfo, chain)
+    return all(vn -> varname_in_chain(varinfo, vn, chain), keys(varinfo))
+end
+
+"""
+    varnames_in_chain!(model::Model, chain, out)
+    varnames_in_chain!(varinfo::VarInfo, chain, out)
+
+Return `out` with `true` for all variable names in `model` that are in `chain`.
+"""
+function varnames_in_chain!(model::Model, chain, out)
+    return varnames_in_chain!(VarInfo(model), chain, out)
+end
+function varnames_in_chain!(varinfo::VarInfo, chain, out)
+    for vn in keys(varinfo)
+        varname_in_chain!(varinfo, vn, chain, 1, 1, out)
+    end
+
+    return out
+end
+
+"""
+    varname_in_chain(model::Model, vn, chain, chain_idx, iteration_idx)
+    varname_in_chain(varinfo::VarInfo, vn, chain, chain_idx, iteration_idx)
+
+Return `true` if `vn` is in `chain` at `chain_idx` and `iteration_idx`.
+"""
+function varname_in_chain(model::Model, vn, chain, chain_idx, iteration_idx)
+    return varname_in_chain(VarInfo(model), vn, chain, chain_idx, iteration_idx)
+end
+
+function varname_in_chain(varinfo::AbstractVarInfo, vn, chain, chain_idx, iteration_idx)
+    !haskey(varinfo, vn) && return false
+    return varname_in_chain(varinfo[vn], vn, chain, chain_idx, iteration_idx)
+end
+
+function varname_in_chain(x, vn, chain, chain_idx, iteration_idx)
+    out = OrderedDict{VarName,Bool}()
+    varname_in_chain!(x, vn, chain, out, chain_idx, iteration_idx)
+    return all(values(out))
+end
+
+"""
+    varname_in_chain!(model::Model, vn, chain, out, chain_idx, iteration_idx)
+    varname_in_chain!(varinfo::VarInfo, vn, chain, out, chain_idx, iteration_idx)
+
+Return a dictionary mapping the varname `vn` to `true` if `vn` is in `chain` at
+`chain_idx` and `iteration_idx`.
+
+If `chain_idx` and `iteration_idx` are not provided, then they default to `1`.
+
+This differs from [`varname_in_chain`](@ref) in that it returns a dictionary
+rather than a single boolean. This can be quite useful for debugging purposes.
+"""
+function varname_in_chain!(model::Model, vn, chain, out, chain_idx, iteration_idx)
+    return varname_in_chain!(VarInfo(model), vn, chain, chain_idx, iteration_idx, out)
+end
+
+function varname_in_chain!(
+    vi::AbstractVarInfo, vn_parent, chain, out, chain_idx, iteration_idx
+)
+    return varname_in_chain!(vi[vn_parent], vn_parent, chain, out, chain_idx, iteration_idx)
+end
+
+function varname_in_chain!(x, vn_parent, chain, out, chain_idx, iteration_idx)
+    sym = Symbol(vn_parent)
+    out[vn_parent] = sym ∈ names(chain) && !ismissing(chain[iteration_idx, sym, chain_idx])
+    return out
+end
+
+function varname_in_chain!(
+    x::AbstractArray, vn_parent::VarName{sym}, chain, out, chain_idx, iteration_idx
+) where {sym}
+    # We use `VarName{sym}()` so that the resulting leaf `vn` only contains the tail of the lens.
+    # This way we can use `getlens(vn)` to extract the value from `x` and use `vn_parent ∘ getlens(vn)`
+    # to extract the value from the `chain`.
+    for vn in varname_leaves(VarName{sym}(), x)
+        # Update `out`, possibly in place, and return.
+        l = AbstractPPL.getlens(vn)
+        varname_in_chain!(x, vn_parent ∘ l, chain, out, chain_idx, iteration_idx)
+    end
+    return out
+end
+
+"""
+    values_from_chain(model::Model, chain, chain_idx, iteration_idx)
+    values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
+
+Return a dictionary mapping each variable name in `model`/`varinfo` to its
+value in `chain` at `chain_idx` and `iteration_idx`.
+"""
+function values_from_chain(x, vn_parent, chain, chain_idx, iteration_idx)
+    # HACK: If it's not an array, we fall back to just returning the first value.
+    return only(chain[iteration_idx, Symbol(vn_parent), chain_idx])
+end
+function values_from_chain(
+    x::AbstractArray, vn_parent::VarName{sym}, chain, chain_idx, iteration_idx
+) where {sym}
+    # We use `VarName{sym}()` so that the resulting leaf `vn` only contains the tail of the lens.
+    # This way we can use `getlens(vn)` to extract the value from `x` and use `vn_parent ∘ getlens(vn)`
+    # to extract the value from the `chain`.
+    out = similar(x)
+    for vn in varname_leaves(VarName{sym}(), x)
+        # Update `out`, possibly in place, and return.
+        l = AbstractPPL.getlens(vn)
+        out = Setfield.set(
+            out,
+            BangBang.prefermutation(l),
+            chain[iteration_idx, Symbol(vn_parent ∘ l), chain_idx],
+        )
+    end
+
+    return out
+end
+function values_from_chain(vi::AbstractVarInfo, vn_parent, chain, chain_idx, iteration_idx)
+    # Use the value `vi[vn_parent]` to obtain a buffer.
+    return values_from_chain(vi[vn_parent], vn_parent, chain, chain_idx, iteration_idx)
+end
+
+"""
+    values_from_chain!(model::Model, chain, out, chain_idx, iteration_idx)
+    values_from_chain!(varinfo::VarInfo, chain, out, chain_idx, iteration_idx)
+
+Mutate `out` to map each variable name in `model`/`varinfo` to its value in
+`chain` at `chain_idx` and `iteration_idx`.
+"""
+function values_from_chain!(model::DynamicPPL.Model, chain, out, chain_idx, iteration_idx)
+    return values_from_chain(VarInfo(model), chain, out, chain_idx, iteration_idx)
+end
+
+function values_from_chain!(vi::AbstractVarInfo, chain, out, chain_idx, iteration_idx)
+    for vn in keys(vi)
+        out[vn] = values_from_chain(vi, vn, chain, chain_idx, iteration_idx)
+    end
+    return out
+end
+
+"""
+    value_iterator_from_chain(model::Model, chain)
+    value_iterator_from_chain(varinfo::AbstractVarInfo, chain)
+
+Return an iterator over the values in `chain` for each variable in `model`/`varinfo`.
+
+# Example
+```jldoctest
+julia> using MCMCChains, DynamicPPL, Distributions, StableRNGs
+
+julia> rng = StableRNG(42);
+
+julia> @model function demo_model(x)
+           s ~ InverseGamma(2, 3)
+           m ~ Normal(0, sqrt(s))
+           for i in eachindex(x)
+               x[i] ~ Normal(m, sqrt(s))
+           end
+
+           return s, m
+       end;
+
+julia> model = demo_model([1.0, 2.0]);
+
+julia> chain = Chains(rand(rng, 10, 2, 3), [:s, :m]);
+
+julia> iter = value_iterator_from_chain(model, chain);
+
+julia> first(iter)
+OrderedDict{VarName, Any} with 2 entries:
+  s => 0.580515
+  m => 0.739328
+
+julia> collect(iter)
+10×3 Matrix{OrderedDict{VarName, Any}}:
+ OrderedDict(s=>0.580515, m=>0.739328)  …  OrderedDict(s=>0.186047, m=>0.402423)
+ OrderedDict(s=>0.191241, m=>0.627342)     OrderedDict(s=>0.776277, m=>0.166342)
+ OrderedDict(s=>0.971133, m=>0.637584)     OrderedDict(s=>0.651655, m=>0.712044)
+ OrderedDict(s=>0.74345, m=>0.110359)      OrderedDict(s=>0.469214, m=>0.104502)
+ OrderedDict(s=>0.170969, m=>0.598514)     OrderedDict(s=>0.853546, m=>0.185399)
+ OrderedDict(s=>0.704776, m=>0.322111)  …  OrderedDict(s=>0.638301, m=>0.853802)
+ OrderedDict(s=>0.441044, m=>0.162285)     OrderedDict(s=>0.852959, m=>0.0956922)
+ OrderedDict(s=>0.803972, m=>0.643369)     OrderedDict(s=>0.245049, m=>0.871985)
+ OrderedDict(s=>0.772384, m=>0.646323)     OrderedDict(s=>0.906603, m=>0.385502)
+ OrderedDict(s=>0.70882, m=>0.253105)      OrderedDict(s=>0.413222, m=>0.953288)
+
+julia> # This can be used to `condition` a `Model`.
+       conditioned_model = model | first(iter);
+
+julia> conditioned_model()  # <= results in same values as the `first(iter)` above
+(0.5805148626851955, 0.7393275279160691)
+```
+"""
+function value_iterator_from_chain(model::DynamicPPL.Model, chain)
+    return value_iterator_from_chain(VarInfo(model), chain)
+end
+
+function value_iterator_from_chain(vi::AbstractVarInfo, chain)
+    return Iterators.map(
+        Iterators.product(1:size(chain, 1), 1:size(chain, 3))
+    ) do (iteration_idx, chain_idx)
+        values_from_chain!(vi, chain, OrderedDict{VarName,Any}(), chain_idx, iteration_idx)
+    end
+end
diff --git a/test/turing/model.jl b/test/turing/model.jl
index e27b177eb..b7d19285d 100644
--- a/test/turing/model.jl
+++ b/test/turing/model.jl
@@ -92,4 +92,19 @@
         # Ensure that they're not all the same (some can be, because rejected samples)
         @test any(res34[1:(end - 1)] .!= res34[2:end])
     end
+
+    @testset "value_iterator_from_chain" begin
+        @testset "$model" for model in DynamicPPL.TestUtils.DEMO_MODELS
+            chain = sample(model, Prior(), 10; progress=false)
+            for (i, d) in enumerate(value_iterator_from_chain(model, chain))
+                for vn in keys(d)
+                    val = DynamicPPL.getvalue(d, vn)
+                    for vn_leaf in DynamicPPL.varname_leaves(vn, val)
+                        val_leaf = DynamicPPL.getvalue(d, vn_leaf)
+                        @test val_leaf == chain[i, Symbol(vn_leaf), 1]
+                    end
+                end
+            end
+        end
+    end
 end

From 979db2d8b14a8260a3f62fd30a5d745401b05564 Mon Sep 17 00:00:00 2001
From: Tor Erlend Fjelde <tor.erlend95@gmail.com>
Date: Tue, 6 Jun 2023 15:20:56 +0100
Subject: [PATCH 02/20] added MCMCchains as a dep to docs

---
 docs/Project.toml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/docs/Project.toml b/docs/Project.toml
index b6cce8b37..028ab7ac3 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -4,6 +4,7 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
+MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
@@ -14,6 +15,7 @@ Distributions = "0.25"
 Documenter = "0.27"
 FillArrays = "0.13, 1"
 LogDensityProblems = "2"
+MCMCChains = "6"
 MLUtils = "0.3, 0.4"
 Setfield = "0.7.1, 0.8, 1"
 StableRNGs = "1"

From 7511e4f38ae1f5747d8fa990c5c2b22ed11815b6 Mon Sep 17 00:00:00 2001
From: Tor Erlend Fjelde <tor.erlend95@gmail.com>
Date: Wed, 7 Jun 2023 01:41:50 +0100
Subject: [PATCH 03/20] attempt at fixing doctests

---
 src/model_utils.jl | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index fe511918a..40eebb63b 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -162,7 +162,8 @@ julia> @model function demo_model(x)
            end
 
            return s, m
-       end;
+       end
+demo_model (generic function with 2 methods)
 
 julia> model = demo_model([1.0, 2.0]);
 

From 1a2dfc7dac2f3c494ea03e76ee598e030cf6ed11 Mon Sep 17 00:00:00 2001
From: Tor Erlend Fjelde <tor.erlend95@gmail.com>
Date: Wed, 7 Jun 2023 01:51:11 +0100
Subject: [PATCH 04/20] remove the doctest as it's not working for some reason

---
 docs/Project.toml  | 2 --
 src/model_utils.jl | 2 +-
 2 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/docs/Project.toml b/docs/Project.toml
index 028ab7ac3..b6cce8b37 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -4,7 +4,6 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
-MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
@@ -15,7 +14,6 @@ Distributions = "0.25"
 Documenter = "0.27"
 FillArrays = "0.13, 1"
 LogDensityProblems = "2"
-MCMCChains = "6"
 MLUtils = "0.3, 0.4"
 Setfield = "0.7.1, 0.8, 1"
 StableRNGs = "1"
diff --git a/src/model_utils.jl b/src/model_utils.jl
index 40eebb63b..6600cfff0 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -149,7 +149,7 @@ end
 Return an iterator over the values in `chain` for each variable in `model`/`varinfo`.
 
 # Example
-```jldoctest
+```julia
 julia> using MCMCChains, DynamicPPL, Distributions, StableRNGs
 
 julia> rng = StableRNG(42);

From 642be6cb9b9eb9773a307615f077f3011508669d Mon Sep 17 00:00:00 2001
From: Tor Erlend Fjelde <tor.erlend95@gmail.com>
Date: Wed, 7 Jun 2023 02:10:00 +0100
Subject: [PATCH 05/20] added docs

---
 docs/src/api.md | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/docs/src/api.md b/docs/src/api.md
index 2dfda9119..e18455bcc 100644
--- a/docs/src/api.md
+++ b/docs/src/api.md
@@ -102,10 +102,17 @@ For a chain of samples, one can compute the pointwise log-likelihoods of each ob
 pointwise_loglikelihoods
 ```
 
+For converting a chain into a format that can more easily be fed into a `Model` again, for example using `condition`, you can use [`value_iterator_from_chain`](@ref).
+
+```@docs
+value_iterator_from_chain
+```
+
 ```@docs
 NamedDist
 ```
 
+
 ## Testing Utilities
 
 DynamicPPL provides several demo models and helpers for testing samplers in the `DynamicPPL.TestUtils` submodule.

From 49b6b931086052c0b92f028aae0c6d6662ed982b Mon Sep 17 00:00:00 2001
From: Tor Erlend Fjelde <tor.erlend95@gmail.com>
Date: Wed, 7 Jun 2023 02:12:35 +0100
Subject: [PATCH 06/20] Update docs/src/api.md

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
---
 docs/src/api.md | 1 -
 1 file changed, 1 deletion(-)

diff --git a/docs/src/api.md b/docs/src/api.md
index e18455bcc..714d18e17 100644
--- a/docs/src/api.md
+++ b/docs/src/api.md
@@ -112,7 +112,6 @@ value_iterator_from_chain
 NamedDist
 ```
 
-
 ## Testing Utilities
 
 DynamicPPL provides several demo models and helpers for testing samplers in the `DynamicPPL.TestUtils` submodule.

From 299087e2ca417099942d61da06b6405d6d1607d4 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 4 Jul 2023 18:01:00 +0100
Subject: [PATCH 07/20] added new functions for `varnames_in_chain` and
 `values_from_chain`.

---
 src/model_utils.jl | 125 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 125 insertions(+)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index 6600cfff0..c6f372bfc 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -1,3 +1,128 @@
+### Yong ############################################################## 
+# Yong added the below new functions on 2023-07-04, they are doing the some functionalities as Tor's functions. Some redundancy needs to be removed?
+using Turing, Distributions, DynamicPPL, MCMCChains, Test
+
+#### 1. varname_in_chain ####
+# here we just check if vn and its leaves are present in the chain; we are not checking its presence in model. So we don't need to pass model or varinfo to this function.
+"""
+    varname_in_chain(vn::VarName, chain, chain_idx, iteration_idx)
+
+Return `true` if `vn` or any of `vn_child` is in `chain` at `chain_idx` and `iteration_idx`; also returned is the dictionary containing the names related to `vn` presented in the chain, if any.
+"""
+function varname_in_chain(vn::VarName, chain, chain_idx=1, iteration_idx=1)
+    out = OrderedDict{Symbol,Bool}()
+    for vn_child in namesingroup(chain, Symbol(vn)) # namesingroup: https://github.com/TuringLang/MCMCChains.jl/blob/master/src/chains.jl
+        # print("\n $vn_child of $vn is in chain")
+        out[vn_child] = Symbol(vn_child) ∈ names(chain) && !ismissing(chain[iteration_idx, Symbol(vn_child), chain_idx])
+    end
+    return !isempty(out), out
+end
+
+#### 2. varnames_in_chain ####
+# we iteratively test whether each of keys(VarInfo(model)) is present in the chain or not
+"""
+    varnames_in_chain(model:::Model, chain)
+    varnames_in_chain(varinfo::VarInfo, chain)
+
+Return `true` if all variable names in `model`/`varinfo` are in `chain`; also returned is the dictionary containing the names related to `vn` presented in the chain, if any.
+"""
+varnames_in_chain(model::Model, chain) = varnames_in_chain(VarInfo(model), chain)
+function varnames_in_chain(varinfo::VarInfo, chain)
+    out_logical = OrderedDict()
+    out = OrderedDict()
+    for vn in keys(varinfo)
+        out_logical[Symbol(vn)], out[Symbol(vn)] = varname_in_chain(vn, chain, 1, 1)
+    end
+    return all(values(out_logical)), out
+end
+
+#### 3. values_from_chain ####
+"""
+    vn_values_from_chain(vn, chain, chain_idx, iteration_idx)
+
+Return `true` if `vn` or any of its leaves is in `chain`; also returned is the dictionary containing the names related to `vn` presented in the chain, if any.
+"""
+function vn_values_from_chain(vn::VarName, chain, chain_idx, iteration_idx)
+    out = OrderedDict()
+    # no need to test if varname_in_chain(vn, chain)[1] - if vn is not in chain, then out will be empty.
+    for vn_child in namesingroup(chain, Symbol(vn))
+        try
+            out[vn_child] = chain[iteration_idx, Symbol(vn_child), chain_idx]
+        catch
+            println("Error: retrieve value for $vn_child using chain[$iteration_idx, Symbol($vn_child), $chain_idx] not successful!")
+        end
+    end
+    return !isempty(out), out
+end
+
+"""
+    values_from_chain(model:::Model, chain)
+    values_from_chain(varinfo::VarInfo, chain)
+
+Return a dictionary containing the values of all variables in `model`/`varinfo` presented in `chain`, if any.
+"""
+values_from_chain(model::Model, chain, chain_idx, iteration_idx) = values_from_chain(VarInfo(model), chain, chain_idx, iteration_idx)
+function values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
+    out = OrderedDict()
+    for vn in keys(varinfo)
+        _, out_vn = vn_values_from_chain(vn, chain, chain_idx, iteration_idx)
+        merge!(out, out_vn)
+    end
+    return out
+end
+
+"""
+    values_from_chain(varinfo, chain, chain_idx, iteration_idx_range)
+
+Return a dictionary containing the values of all variables in `model`/`varinfo` presented in `chain`,  as per iteration_idx_range.
+"""
+values_from_chain(model::Model, chain, chain_idx_range, iteration_idx_range) = values_from_chain(VarInfo(model), chain, chain_idx_range, iteration_idx_range)
+function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::UnitRange)
+    all_out = OrderedDict()
+    for chain_idx in chain_idx_range
+        out = OrderedDict()
+        for vn in keys(varinfo)
+            for iteration_idx in iteration_idx_range
+                _, out_vn = vn_values_from_chain(vn, chain, chain_idx, iteration_idx)
+                for key in keys(out_vn)
+                    if haskey(out, key)
+                        out[key] = vcat(out[key], out_vn[key])
+                    else
+                        out[key] = out_vn[key]
+                    end
+                end
+            end
+        end
+        all_out["chain_idx_"*string(chain_idx)] = out
+    end
+    return all_out
+end
+function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::UnitRange)
+    return values_from_chain(varinfo, chain, chain_idx_range:chain_idx_range, iteration_idx_range)
+end
+function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::Int)
+    return values_from_chain(varinfo, chain, chain_idx_range, iteration_idx_range:iteration_idx_range)
+end
+function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::Int) #  this is equivalent to values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
+    return values_from_chain(varinfo, chain, chain_idx_range:chain_idx_range, iteration_idx_range:iteration_idx_range)
+end
+## if either chain_idx_range and iteration_idx_range not specified, then all chains will be included.
+function values_from_chain(varinfo::VarInfo, chain, chain_idx_range, iteration_idx_range)
+    if chain_idx_range === nothing
+        print("chain_idx_range is missing!")
+        chain_idx_range = 1:size(chain)[3]
+    end
+    if iteration_idx_range === nothing
+        print("iteration_idx_range is missing!")    
+        iteration_idx_range = 1:size(chain)[1]
+    end
+    return values_from_chain(varinfo, chain, chain_idx_range, iteration_idx_range)
+end
+
+### Tor ##############################################################
+
+"""
+    Tor(model::Model, chain, chain_idx, iteration_idx)
 """
     varnames_in_chain(model:::Model, chain)
     varnames_in_chain(varinfo::VarInfo, chain)

From 545f7274051d6ee182e70866dcc50081c0ed34cd Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Wed, 5 Jul 2023 09:16:53 +0100
Subject: [PATCH 08/20] cleaned up .

---
 src/model_utils.jl | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index c6f372bfc..94e037836 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -120,9 +120,6 @@ function values_from_chain(varinfo::VarInfo, chain, chain_idx_range, iteration_i
 end
 
 ### Tor ##############################################################
-
-"""
-    Tor(model::Model, chain, chain_idx, iteration_idx)
 """
     varnames_in_chain(model:::Model, chain)
     varnames_in_chain(varinfo::VarInfo, chain)

From 20bdea78b653f182da6c7d98267696bb40d0df1d Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Wed, 5 Jul 2023 10:30:59 +0100
Subject: [PATCH 09/20] added doctests for the new functions.

---
 src/model_utils.jl | 181 ++++++++++++++++++++++++++++++++++++++++++---
 1 file changed, 170 insertions(+), 11 deletions(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index 94e037836..7c5652285 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -1,13 +1,44 @@
 ### Yong ############################################################## 
 # Yong added the below new functions on 2023-07-04, they are doing the some functionalities as Tor's functions. Some redundancy needs to be removed?
-using Turing, Distributions, DynamicPPL, MCMCChains, Test
+using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
 
 #### 1. varname_in_chain ####
 # here we just check if vn and its leaves are present in the chain; we are not checking its presence in model. So we don't need to pass model or varinfo to this function.
 """
     varname_in_chain(vn::VarName, chain, chain_idx, iteration_idx)
 
-Return `true` if `vn` or any of `vn_child` is in `chain` at `chain_idx` and `iteration_idx`; also returned is the dictionary containing the names related to `vn` presented in the chain, if any.
+Return two outputs:
+    - first output: logical `true` if `vn` or ANY of `vn_child` is in `chain` at `chain_idx` and `iteration_idx`; 
+    - second output: a dictionary containing all leaf names of `vn` from the chain, if any.
+
+# Example
+```julia
+julia> using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+
+julia> Random.seed!(111)
+MersenneTwister(111)
+
+julia> @model function test_model(x)
+           s ~ InverseGamma(2, 3)
+           m ~ Normal(0, sqrt(s))
+           x ~ Normal(m, sqrt(s))
+       end
+test_model (generic function with 2 methods)
+
+julia> model = test_model(1.5)
+
+julia> chain = sample(model, NUTS(), 100)
+
+julia> varname_in_chain(VarName(:s), chain, 1, 1)
+(true, OrderedDict{Symbol, Bool}(:s => 1))
+
+julia> varname_in_chain(VarName(:m), chain, 1, 1)
+(true, OrderedDict{Symbol, Bool}(:m => 1))
+
+julia> varname_in_chain(VarName(:x), chain, 1, 1)
+(false, OrderedDict{Symbol, Bool}())
+
+```
 """
 function varname_in_chain(vn::VarName, chain, chain_idx=1, iteration_idx=1)
     out = OrderedDict{Symbol,Bool}()
@@ -19,19 +50,44 @@ function varname_in_chain(vn::VarName, chain, chain_idx=1, iteration_idx=1)
 end
 
 #### 2. varnames_in_chain ####
-# we iteratively test whether each of keys(VarInfo(model)) is present in the chain or not
+# we iteratively check whether each of keys(VarInfo(model)) is present in the chain or not using `varname_in_chain`.
 """
     varnames_in_chain(model:::Model, chain)
     varnames_in_chain(varinfo::VarInfo, chain)
 
-Return `true` if all variable names in `model`/`varinfo` are in `chain`; also returned is the dictionary containing the names related to `vn` presented in the chain, if any.
+Return two outputs:
+    - first output: logical `true` if ALL variable names in `model`/`varinfo` are in `chain`; 
+    - second output: a dictionary containing all leaf names of `vn` presented in the chain, if any.
+
+# Example
+```julia
+julia> using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+
+julia> Random.seed!(111)
+MersenneTwister(111)
+
+julia> @model function test_model(x)
+    s ~ InverseGamma(2, 3)
+    m ~ Normal(0, sqrt(s))
+    x ~ Normal(m, sqrt(s))
+end
+test_model (generic function with 2 methods
+
+julia> model = test_model(1.5)
+
+julia> chain = sample(model, NUTS(), 100)
+
+julia> varnames_in_chain(model, chain)
+(true, OrderedDict{Any, Any}(:s => OrderedDict{Symbol, Bool}(:s => 1), :m => OrderedDict{Symbol, Bool}(:m => 1)))
+
+```
 """
 varnames_in_chain(model::Model, chain) = varnames_in_chain(VarInfo(model), chain)
 function varnames_in_chain(varinfo::VarInfo, chain)
     out_logical = OrderedDict()
     out = OrderedDict()
     for vn in keys(varinfo)
-        out_logical[Symbol(vn)], out[Symbol(vn)] = varname_in_chain(vn, chain, 1, 1)
+        out_logical[Symbol(vn)], out[Symbol(vn)] = varname_in_chain(vn, chain, 1, 1) # by default, we check the first chain and the first iteration.
     end
     return all(values(out_logical)), out
 end
@@ -40,11 +96,42 @@ end
 """
     vn_values_from_chain(vn, chain, chain_idx, iteration_idx)
 
-Return `true` if `vn` or any of its leaves is in `chain`; also returned is the dictionary containing the names related to `vn` presented in the chain, if any.
+Return two outputs:
+    - first output: logical `true` if `vn` or ANY of its leaves is in `chain`
+    - second output: a dictionary containing all leaf names (if any) of `vn` and their values at `chain_idx`, `iteration_idx` from the chain.
+
+# Example
+```julia
+julia> using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+
+julia> Random.seed!(111)
+MersenneTwister(111)
+
+julia> @model function test_model(x)
+    s ~ InverseGamma(2, 3)
+    m ~ Normal(0, sqrt(s))
+    x ~ Normal(m, sqrt(s))
+end
+test_model (generic function with 2 methods)
+
+julia> model = test_model(1.5)
+
+julia> chain = sample(model, NUTS(), 100)
+
+julia> vn_values_from_chain(VarName(:s), chain, 1, 1)
+(true, OrderedDict{Any, Any}(:s => 1.385664578516751))
+
+julia> vn_values_from_chain(VarName(:m), chain, 1, 1)
+(true, OrderedDict{Any, Any}(:m => 0.9529550916018266))
+
+julia> vn_values_from_chain(VarName(:x), chain, 1, 1)
+(false, OrderedDict{Any, Any}())
+
+```
 """
 function vn_values_from_chain(vn::VarName, chain, chain_idx, iteration_idx)
     out = OrderedDict()
-    # no need to test if varname_in_chain(vn, chain)[1] - if vn is not in chain, then out will be empty.
+    # no need to check if varname_in_chain(vn, chain)[1] - if vn is not in chain, then out will be empty.
     for vn_child in namesingroup(chain, Symbol(vn))
         try
             out[vn_child] = chain[iteration_idx, Symbol(vn_child), chain_idx]
@@ -59,7 +146,33 @@ end
     values_from_chain(model:::Model, chain)
     values_from_chain(varinfo::VarInfo, chain)
 
-Return a dictionary containing the values of all variables in `model`/`varinfo` presented in `chain`, if any.
+Return one output:
+    - a dictionary containing the (leaves_name, value) pair of ALL parameters in `model`/`varinfo` at `chain_idx`, `iteration_idx` from the chain (if ANY of the leaves of `vn` is present in the chain).
+
+# Example
+```julia
+
+julia> using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+
+julia> Random.seed!(111)
+MersenneTwister(111)
+
+julia> @model function test_model(x)
+    s ~ InverseGamma(2, 3)
+    m ~ Normal(0, sqrt(s))
+    x ~ Normal(m, sqrt(s))
+end
+
+julia> model = test_model(1.5)
+
+julia> chain = sample(model, NUTS(), 100)
+
+julia> values_from_chain(model, chain, 1, 1)
+OrderedDict{Any, Any} with 2 entries:
+  :s => 1.38566
+  :m => 0.952955
+
+```
 """
 values_from_chain(model::Model, chain, chain_idx, iteration_idx) = values_from_chain(VarInfo(model), chain, chain_idx, iteration_idx)
 function values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
@@ -72,9 +185,55 @@ function values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
 end
 
 """
-    values_from_chain(varinfo, chain, chain_idx, iteration_idx_range)
+    values_from_chain(varinfo, chain, chain_idx_range, iteration_idx_range)
+
+Return one output:
+    - a dictionary containing the values of all leaf names of all parameters in `model`/`varinfo` within `chain_idx_range` and `iteration_idx_range``.
 
-Return a dictionary containing the values of all variables in `model`/`varinfo` presented in `chain`,  as per iteration_idx_range.
+# Example
+```julia
+
+julia> using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+
+julia> Random.seed!(111)
+MersenneTwister(111)
+
+julia> @model function test_model(x)
+    s ~ InverseGamma(2, 3)
+    m ~ Normal(0, sqrt(s))
+    x ~ Normal(m, sqrt(s))
+end
+
+julia> model = test_model(1.5)
+
+julia> chain = sample(model, NUTS(), 100)
+
+julia> values_from_chain(model, chain, 1:2, 1:10)
+Error: retrieve value for s using chain[1, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[2, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[3, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[4, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[5, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[6, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[7, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[8, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[9, Symbol(s), 2] not successful!
+Error: retrieve value for s using chain[10, Symbol(s), 2] not successful!
+Error: retrieve value for m using chain[1, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[2, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[3, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[4, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[5, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[6, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[7, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[8, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[9, Symbol(m), 2] not successful!
+Error: retrieve value for m using chain[10, Symbol(m), 2] not successful!
+OrderedDict{Any, Any} with 2 entries:
+  "chain_idx_1" => OrderedDict{Any, Any}(:s=>[1.38566, 1.6544, 1.36912, 1.18434, 1.33485, 1.966…
+  "chain_idx_2" => OrderedDict{Any, Any}()
+
+```
 """
 values_from_chain(model::Model, chain, chain_idx_range, iteration_idx_range) = values_from_chain(VarInfo(model), chain, chain_idx_range, iteration_idx_range)
 function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::UnitRange)
@@ -106,7 +265,7 @@ end
 function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::Int) #  this is equivalent to values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
     return values_from_chain(varinfo, chain, chain_idx_range:chain_idx_range, iteration_idx_range:iteration_idx_range)
 end
-## if either chain_idx_range and iteration_idx_range not specified, then all chains will be included.
+# if either chain_idx_range or iteration_idx_range is specified as `nothing`, then all chains will be included.
 function values_from_chain(varinfo::VarInfo, chain, chain_idx_range, iteration_idx_range)
     if chain_idx_range === nothing
         print("chain_idx_range is missing!")

From de5f684821ddf99d6a5bc7aa364e2fad152537cb Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Thu, 6 Jul 2023 18:59:43 +0100
Subject: [PATCH 10/20] added `test/model_utils.jl`.

---
 test/model_utils.jl | 116 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 116 insertions(+)
 create mode 100644 test/model_utils.jl

diff --git a/test/model_utils.jl b/test/model_utils.jl
new file mode 100644
index 000000000..c6fa99af3
--- /dev/null
+++ b/test/model_utils.jl
@@ -0,0 +1,116 @@
+using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+Random.seed!(111)
+
+#### prepare the models and chains for testing ####
+# (1) manually create a chain using MCMCChains - we know what parameter names are in the chain
+val = [1 2; 3 4; 5 6; 7 8; 9 10; 11 12; 13 14; 15 16; 17 18; 19 20]
+val = Matrix{Int}(val)
+chn_1 = Chains(val, [:s, :m])
+
+# (2) sample a Turing model to create a chain
+@model function gdemo(x)
+    mu ~ MvNormal([0, 0, 0], [1 0 0; 0 1 0; 0 0 1])
+    x ~ MvNormal(mu, [1 0 0; 0 1 0; 0 0 1])
+end
+model_2 = gdemo([0, 0, 0])  # provide an initial value for `x`
+chn_2 = sample(model_2, NUTS(), 100) # NB: the parameter names in an MCMCChains can be retrieved using `namechn_2.name_map[:parameters]_map`: https://github.com/TuringLang/MCMCChains.jl/blob/master/src/chains.jl
+
+# (3) sample the demo models in DynamicPPL to create a chain - we do not know what parameter names are in the chain beforehand 
+model_3 = DynamicPPL.TestUtils.DEMO_MODELS[12]
+var_info = VarInfo(model_3)
+vns = DynamicPPL.TestUtils.varnames(model_3)
+# generate a chain.
+N = 100
+vals_OrderedDict = mapreduce(hcat, 1:N) do _
+    rand(OrderedDict, model_3)
+end
+vals_mat = mapreduce(hcat, 1:N) do i
+    [vals_OrderedDict[i][vn] for vn in vns]
+end
+i = 1
+for col in eachcol(vals_mat)
+    col_flattened = []
+    [push!(col_flattened, x...) for x in col]
+    if i == 1
+        chain_mat = Matrix(reshape(col_flattened, 1, length(col_flattened)))
+    else
+        chain_mat = vcat(chain_mat, reshape(col_flattened, 1, length(col_flattened)))
+    end
+    i += 1
+end
+chain_mat = convert(Matrix{Float64}, chain_mat)
+# devise parameter names for chain
+sample_values_vec = collect(values(vals_OrderedDict[1]))
+symbol_names = []
+chain_sym_map = Dict()
+for k in 1:length(keys(var_info))
+    vn_parent = keys(var_info)[k]
+    sym = DynamicPPL.getsym(vn_parent)
+    vn_children = DynamicPPL.varname_leaves(vn_parent, sample_values_vec[k])
+    for vn_child in vn_children
+        chain_sym_map[Symbol(vn_child)] = sym
+        symbol_names = [symbol_names; Symbol(vn_child)]
+    end
+end
+chn_3 = Chains(chain_mat, symbol_names)
+
+#### test functions in model_utils.jl ####
+@testset "model_utils.jl" begin
+    @testset "varname_in_chain" begin
+        # chn_1
+        outputs = varname_in_chain(VarName(:s), chn_1, 1, 1)
+        @test outputs[1] == true && outputs[2][:s] == true
+        outputs = varname_in_chain(VarName(:m), chn_1, 1, 1)
+        @test outputs[1] == true && outputs[2][:m] == true
+        outputs = varname_in_chain(VarName(:x), chn_1, 1, 1)
+        @test outputs[1] == false && isempty(outputs[2])
+
+        # chn_2
+        outputs = varname_in_chain(VarName(:mu), chn_2, 1, 1)
+        @test outputs[1] == true && !isempty(outputs[2]) && all(values(outputs[2]) .== 1)
+
+        # chn_3
+        outputs = varname_in_chain(VarName(:a), chn_3, 1, 1)
+        @test outputs[1] == false && isempty(outputs[2])
+        outputs = varname_in_chain(VarName(symbol_names[1]), chn_3, 1, 1)
+        @test !isempty(outputs[2]) && all(values(outputs[2]) .== 1) # note: all(values(outputs[2]) .== 1) is not enough - even an empty dictionary has all(values(outputs[2]) .== 1)
+    end
+    @testset "varnames_in_chain" begin
+        outputs = varnames_in_chain(model_2, chn_2)
+        @test outputs[1] == true && all(values(outputs[2][:mu]))
+        outputs = varnames_in_chain(model_3, chn_3)
+        @test outputs[1] == true
+    end
+    @testset "vn_values_from_chain" begin
+        outputs = vn_values_from_chain(VarName(:mu), chn_2, 1, 1)
+        @test outputs[1] == true && length(values(outputs[2])) == 3
+        outputs = vn_values_from_chain(VarName(:s), chn_3, 1, 1)
+        @test outputs[1] == true && length(values(outputs[2])) == 2
+        outputs = vn_values_from_chain(VarName(Symbol("s[:,1][1]")), chn_3, 1, 2)
+        @test outputs[1] == true
+    end
+    @testset "values_from_chain" begin
+        output = values_from_chain(model_2, chn_2, 1, 1)
+        @test length(output["chain_idx_1"]) == 3
+        output = values_from_chain(model_3, chn_3, 1, 1)
+        @test length(output["chain_idx_1"]) == 4
+
+        output = values_from_chain(model_2, chn_2, 1, 1:10)
+        @test length(output["chain_idx_1"]) == 3 && all([length(vals) == 10 for vals in values(output["chain_idx_1"])])
+        output = values_from_chain(model_3, chn_3, 1, 1:10)
+        @test length(output["chain_idx_1"]) == 4 && all([length(vals) == 10 for vals in values(output["chain_idx_1"])])
+        output = values_from_chain(model_2, chn_2, 1, 1)
+        @test length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        output = values_from_chain(model_2, chn_2, 1:1, 1)
+        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        output = values_from_chain(model_2, chn_2, 1, 1:1)
+        @test length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        output = values_from_chain(model_2, chn_2, 1:1, 1:1)
+        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+
+        output = values_from_chain(model_2, chn_2, nothing, nothing)
+        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 3 && all([length(vals) == 100 for vals in values(output["chain_idx_1"])])
+        output = values_from_chain(model_3, chn_3, nothing, nothing)
+        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 4 && all([length(vals) == 100 for vals in values(output["chain_idx_1"])])
+    end
+end
\ No newline at end of file

From e6888c8fa012c466a25ac2bc159b3d081f739192 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Thu, 6 Jul 2023 21:35:16 +0100
Subject: [PATCH 11/20] only new functions are kept.

---
 src/model_utils.jl | 213 +--------------------------------------------
 1 file changed, 1 insertion(+), 212 deletions(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index 7c5652285..70f16b6a6 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -276,215 +276,4 @@ function values_from_chain(varinfo::VarInfo, chain, chain_idx_range, iteration_i
         iteration_idx_range = 1:size(chain)[1]
     end
     return values_from_chain(varinfo, chain, chain_idx_range, iteration_idx_range)
-end
-
-### Tor ##############################################################
-"""
-    varnames_in_chain(model:::Model, chain)
-    varnames_in_chain(varinfo::VarInfo, chain)
-
-Return `true` if all variable names in `model`/`varinfo` are in `chain`.
-"""
-varnames_in_chain(model::Model, chain) = varnames_in_chain(VarInfo(model), chain)
-function varnames_in_chain(varinfo::VarInfo, chain)
-    return all(vn -> varname_in_chain(varinfo, vn, chain), keys(varinfo))
-end
-
-"""
-    varnames_in_chain!(model::Model, chain, out)
-    varnames_in_chain!(varinfo::VarInfo, chain, out)
-
-Return `out` with `true` for all variable names in `model` that are in `chain`.
-"""
-function varnames_in_chain!(model::Model, chain, out)
-    return varnames_in_chain!(VarInfo(model), chain, out)
-end
-function varnames_in_chain!(varinfo::VarInfo, chain, out)
-    for vn in keys(varinfo)
-        varname_in_chain!(varinfo, vn, chain, 1, 1, out)
-    end
-
-    return out
-end
-
-"""
-    varname_in_chain(model::Model, vn, chain, chain_idx, iteration_idx)
-    varname_in_chain(varinfo::VarInfo, vn, chain, chain_idx, iteration_idx)
-
-Return `true` if `vn` is in `chain` at `chain_idx` and `iteration_idx`.
-"""
-function varname_in_chain(model::Model, vn, chain, chain_idx, iteration_idx)
-    return varname_in_chain(VarInfo(model), vn, chain, chain_idx, iteration_idx)
-end
-
-function varname_in_chain(varinfo::AbstractVarInfo, vn, chain, chain_idx, iteration_idx)
-    !haskey(varinfo, vn) && return false
-    return varname_in_chain(varinfo[vn], vn, chain, chain_idx, iteration_idx)
-end
-
-function varname_in_chain(x, vn, chain, chain_idx, iteration_idx)
-    out = OrderedDict{VarName,Bool}()
-    varname_in_chain!(x, vn, chain, out, chain_idx, iteration_idx)
-    return all(values(out))
-end
-
-"""
-    varname_in_chain!(model::Model, vn, chain, out, chain_idx, iteration_idx)
-    varname_in_chain!(varinfo::VarInfo, vn, chain, out, chain_idx, iteration_idx)
-
-Return a dictionary mapping the varname `vn` to `true` if `vn` is in `chain` at
-`chain_idx` and `iteration_idx`.
-
-If `chain_idx` and `iteration_idx` are not provided, then they default to `1`.
-
-This differs from [`varname_in_chain`](@ref) in that it returns a dictionary
-rather than a single boolean. This can be quite useful for debugging purposes.
-"""
-function varname_in_chain!(model::Model, vn, chain, out, chain_idx, iteration_idx)
-    return varname_in_chain!(VarInfo(model), vn, chain, chain_idx, iteration_idx, out)
-end
-
-function varname_in_chain!(
-    vi::AbstractVarInfo, vn_parent, chain, out, chain_idx, iteration_idx
-)
-    return varname_in_chain!(vi[vn_parent], vn_parent, chain, out, chain_idx, iteration_idx)
-end
-
-function varname_in_chain!(x, vn_parent, chain, out, chain_idx, iteration_idx)
-    sym = Symbol(vn_parent)
-    out[vn_parent] = sym ∈ names(chain) && !ismissing(chain[iteration_idx, sym, chain_idx])
-    return out
-end
-
-function varname_in_chain!(
-    x::AbstractArray, vn_parent::VarName{sym}, chain, out, chain_idx, iteration_idx
-) where {sym}
-    # We use `VarName{sym}()` so that the resulting leaf `vn` only contains the tail of the lens.
-    # This way we can use `getlens(vn)` to extract the value from `x` and use `vn_parent ∘ getlens(vn)`
-    # to extract the value from the `chain`.
-    for vn in varname_leaves(VarName{sym}(), x)
-        # Update `out`, possibly in place, and return.
-        l = AbstractPPL.getlens(vn)
-        varname_in_chain!(x, vn_parent ∘ l, chain, out, chain_idx, iteration_idx)
-    end
-    return out
-end
-
-"""
-    values_from_chain(model::Model, chain, chain_idx, iteration_idx)
-    values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
-
-Return a dictionary mapping each variable name in `model`/`varinfo` to its
-value in `chain` at `chain_idx` and `iteration_idx`.
-"""
-function values_from_chain(x, vn_parent, chain, chain_idx, iteration_idx)
-    # HACK: If it's not an array, we fall back to just returning the first value.
-    return only(chain[iteration_idx, Symbol(vn_parent), chain_idx])
-end
-function values_from_chain(
-    x::AbstractArray, vn_parent::VarName{sym}, chain, chain_idx, iteration_idx
-) where {sym}
-    # We use `VarName{sym}()` so that the resulting leaf `vn` only contains the tail of the lens.
-    # This way we can use `getlens(vn)` to extract the value from `x` and use `vn_parent ∘ getlens(vn)`
-    # to extract the value from the `chain`.
-    out = similar(x)
-    for vn in varname_leaves(VarName{sym}(), x)
-        # Update `out`, possibly in place, and return.
-        l = AbstractPPL.getlens(vn)
-        out = Setfield.set(
-            out,
-            BangBang.prefermutation(l),
-            chain[iteration_idx, Symbol(vn_parent ∘ l), chain_idx],
-        )
-    end
-
-    return out
-end
-function values_from_chain(vi::AbstractVarInfo, vn_parent, chain, chain_idx, iteration_idx)
-    # Use the value `vi[vn_parent]` to obtain a buffer.
-    return values_from_chain(vi[vn_parent], vn_parent, chain, chain_idx, iteration_idx)
-end
-
-"""
-    values_from_chain!(model::Model, chain, out, chain_idx, iteration_idx)
-    values_from_chain!(varinfo::VarInfo, chain, out, chain_idx, iteration_idx)
-
-Mutate `out` to map each variable name in `model`/`varinfo` to its value in
-`chain` at `chain_idx` and `iteration_idx`.
-"""
-function values_from_chain!(model::DynamicPPL.Model, chain, out, chain_idx, iteration_idx)
-    return values_from_chain(VarInfo(model), chain, out, chain_idx, iteration_idx)
-end
-
-function values_from_chain!(vi::AbstractVarInfo, chain, out, chain_idx, iteration_idx)
-    for vn in keys(vi)
-        out[vn] = values_from_chain(vi, vn, chain, chain_idx, iteration_idx)
-    end
-    return out
-end
-
-"""
-    value_iterator_from_chain(model::Model, chain)
-    value_iterator_from_chain(varinfo::AbstractVarInfo, chain)
-
-Return an iterator over the values in `chain` for each variable in `model`/`varinfo`.
-
-# Example
-```julia
-julia> using MCMCChains, DynamicPPL, Distributions, StableRNGs
-
-julia> rng = StableRNG(42);
-
-julia> @model function demo_model(x)
-           s ~ InverseGamma(2, 3)
-           m ~ Normal(0, sqrt(s))
-           for i in eachindex(x)
-               x[i] ~ Normal(m, sqrt(s))
-           end
-
-           return s, m
-       end
-demo_model (generic function with 2 methods)
-
-julia> model = demo_model([1.0, 2.0]);
-
-julia> chain = Chains(rand(rng, 10, 2, 3), [:s, :m]);
-
-julia> iter = value_iterator_from_chain(model, chain);
-
-julia> first(iter)
-OrderedDict{VarName, Any} with 2 entries:
-  s => 0.580515
-  m => 0.739328
-
-julia> collect(iter)
-10×3 Matrix{OrderedDict{VarName, Any}}:
- OrderedDict(s=>0.580515, m=>0.739328)  …  OrderedDict(s=>0.186047, m=>0.402423)
- OrderedDict(s=>0.191241, m=>0.627342)     OrderedDict(s=>0.776277, m=>0.166342)
- OrderedDict(s=>0.971133, m=>0.637584)     OrderedDict(s=>0.651655, m=>0.712044)
- OrderedDict(s=>0.74345, m=>0.110359)      OrderedDict(s=>0.469214, m=>0.104502)
- OrderedDict(s=>0.170969, m=>0.598514)     OrderedDict(s=>0.853546, m=>0.185399)
- OrderedDict(s=>0.704776, m=>0.322111)  …  OrderedDict(s=>0.638301, m=>0.853802)
- OrderedDict(s=>0.441044, m=>0.162285)     OrderedDict(s=>0.852959, m=>0.0956922)
- OrderedDict(s=>0.803972, m=>0.643369)     OrderedDict(s=>0.245049, m=>0.871985)
- OrderedDict(s=>0.772384, m=>0.646323)     OrderedDict(s=>0.906603, m=>0.385502)
- OrderedDict(s=>0.70882, m=>0.253105)      OrderedDict(s=>0.413222, m=>0.953288)
-
-julia> # This can be used to `condition` a `Model`.
-       conditioned_model = model | first(iter);
-
-julia> conditioned_model()  # <= results in same values as the `first(iter)` above
-(0.5805148626851955, 0.7393275279160691)
-```
-"""
-function value_iterator_from_chain(model::DynamicPPL.Model, chain)
-    return value_iterator_from_chain(VarInfo(model), chain)
-end
-
-function value_iterator_from_chain(vi::AbstractVarInfo, chain)
-    return Iterators.map(
-        Iterators.product(1:size(chain, 1), 1:size(chain, 3))
-    ) do (iteration_idx, chain_idx)
-        values_from_chain!(vi, chain, OrderedDict{VarName,Any}(), chain_idx, iteration_idx)
-    end
-end
+end
\ No newline at end of file

From 77c37c9a039fdc5ed735cee629a216cf14f73d5a Mon Sep 17 00:00:00 2001
From: YongchaoHuang <34540771+YongchaoHuang@users.noreply.github.com>
Date: Fri, 7 Jul 2023 18:37:05 +0100
Subject: [PATCH 12/20] Apply suggestions from code review

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
---
 src/model_utils.jl  | 51 +++++++++++++++++++++++++++++++++------------
 test/model_utils.jl | 28 ++++++++++++++++++-------
 2 files changed, 58 insertions(+), 21 deletions(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index 70f16b6a6..9d0f4870c 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -44,7 +44,9 @@ function varname_in_chain(vn::VarName, chain, chain_idx=1, iteration_idx=1)
     out = OrderedDict{Symbol,Bool}()
     for vn_child in namesingroup(chain, Symbol(vn)) # namesingroup: https://github.com/TuringLang/MCMCChains.jl/blob/master/src/chains.jl
         # print("\n $vn_child of $vn is in chain")
-        out[vn_child] = Symbol(vn_child) ∈ names(chain) && !ismissing(chain[iteration_idx, Symbol(vn_child), chain_idx])
+        out[vn_child] =
+            Symbol(vn_child) ∈ names(chain) &&
+            !ismissing(chain[iteration_idx, Symbol(vn_child), chain_idx])
     end
     return !isempty(out), out
 end
@@ -136,7 +138,9 @@ function vn_values_from_chain(vn::VarName, chain, chain_idx, iteration_idx)
         try
             out[vn_child] = chain[iteration_idx, Symbol(vn_child), chain_idx]
         catch
-            println("Error: retrieve value for $vn_child using chain[$iteration_idx, Symbol($vn_child), $chain_idx] not successful!")
+            println(
+                "Error: retrieve value for $vn_child using chain[$iteration_idx, Symbol($vn_child), $chain_idx] not successful!",
+            )
         end
     end
     return !isempty(out), out
@@ -174,7 +178,9 @@ OrderedDict{Any, Any} with 2 entries:
 
 ```
 """
-values_from_chain(model::Model, chain, chain_idx, iteration_idx) = values_from_chain(VarInfo(model), chain, chain_idx, iteration_idx)
+function values_from_chain(model::Model, chain, chain_idx, iteration_idx)
+    return values_from_chain(VarInfo(model), chain, chain_idx, iteration_idx)
+end
 function values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
     out = OrderedDict()
     for vn in keys(varinfo)
@@ -235,8 +241,12 @@ OrderedDict{Any, Any} with 2 entries:
 
 ```
 """
-values_from_chain(model::Model, chain, chain_idx_range, iteration_idx_range) = values_from_chain(VarInfo(model), chain, chain_idx_range, iteration_idx_range)
-function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::UnitRange)
+function values_from_chain(model::Model, chain, chain_idx_range, iteration_idx_range)
+    return values_from_chain(VarInfo(model), chain, chain_idx_range, iteration_idx_range)
+end
+function values_from_chain(
+    varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::UnitRange
+)
     all_out = OrderedDict()
     for chain_idx in chain_idx_range
         out = OrderedDict()
@@ -252,18 +262,33 @@ function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::UnitRange,
                 end
             end
         end
-        all_out["chain_idx_"*string(chain_idx)] = out
+        all_out["chain_idx_" * string(chain_idx)] = out
     end
     return all_out
 end
-function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::UnitRange)
-    return values_from_chain(varinfo, chain, chain_idx_range:chain_idx_range, iteration_idx_range)
+function values_from_chain(
+    varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::UnitRange
+)
+    return values_from_chain(
+        varinfo, chain, chain_idx_range:chain_idx_range, iteration_idx_range
+    )
 end
-function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::Int)
-    return values_from_chain(varinfo, chain, chain_idx_range, iteration_idx_range:iteration_idx_range)
+function values_from_chain(
+    varinfo::VarInfo, chain, chain_idx_range::UnitRange, iteration_idx_range::Int
+)
+    return values_from_chain(
+        varinfo, chain, chain_idx_range, iteration_idx_range:iteration_idx_range
+    )
 end
-function values_from_chain(varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::Int) #  this is equivalent to values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
-    return values_from_chain(varinfo, chain, chain_idx_range:chain_idx_range, iteration_idx_range:iteration_idx_range)
+function values_from_chain(
+    varinfo::VarInfo, chain, chain_idx_range::Int, iteration_idx_range::Int
+) #  this is equivalent to values_from_chain(varinfo::VarInfo, chain, chain_idx, iteration_idx)
+    return values_from_chain(
+        varinfo,
+        chain,
+        chain_idx_range:chain_idx_range,
+        iteration_idx_range:iteration_idx_range,
+    )
 end
 # if either chain_idx_range or iteration_idx_range is specified as `nothing`, then all chains will be included.
 function values_from_chain(varinfo::VarInfo, chain, chain_idx_range, iteration_idx_range)
@@ -272,7 +297,7 @@ function values_from_chain(varinfo::VarInfo, chain, chain_idx_range, iteration_i
         chain_idx_range = 1:size(chain)[3]
     end
     if iteration_idx_range === nothing
-        print("iteration_idx_range is missing!")    
+        print("iteration_idx_range is missing!")
         iteration_idx_range = 1:size(chain)[1]
     end
     return values_from_chain(varinfo, chain, chain_idx_range, iteration_idx_range)
diff --git a/test/model_utils.jl b/test/model_utils.jl
index c6fa99af3..701f760bb 100644
--- a/test/model_utils.jl
+++ b/test/model_utils.jl
@@ -96,21 +96,33 @@ chn_3 = Chains(chain_mat, symbol_names)
         @test length(output["chain_idx_1"]) == 4
 
         output = values_from_chain(model_2, chn_2, 1, 1:10)
-        @test length(output["chain_idx_1"]) == 3 && all([length(vals) == 10 for vals in values(output["chain_idx_1"])])
+        @test length(output["chain_idx_1"]) == 3 &&
+            all([length(vals) == 10 for vals in values(output["chain_idx_1"])])
         output = values_from_chain(model_3, chn_3, 1, 1:10)
-        @test length(output["chain_idx_1"]) == 4 && all([length(vals) == 10 for vals in values(output["chain_idx_1"])])
+        @test length(output["chain_idx_1"]) == 4 &&
+            all([length(vals) == 10 for vals in values(output["chain_idx_1"])])
         output = values_from_chain(model_2, chn_2, 1, 1)
-        @test length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        @test length(output["chain_idx_1"]) == 3 &&
+            all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
         output = values_from_chain(model_2, chn_2, 1:1, 1)
-        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        @test length(keys(output)) == 1 &&
+            length(output["chain_idx_1"]) == 3 &&
+            all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
         output = values_from_chain(model_2, chn_2, 1, 1:1)
-        @test length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        @test length(output["chain_idx_1"]) == 3 &&
+            all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
         output = values_from_chain(model_2, chn_2, 1:1, 1:1)
-        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 3 && all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
+        @test length(keys(output)) == 1 &&
+            length(output["chain_idx_1"]) == 3 &&
+            all([length(vals) == 1 for vals in values(output["chain_idx_1"])])
 
         output = values_from_chain(model_2, chn_2, nothing, nothing)
-        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 3 && all([length(vals) == 100 for vals in values(output["chain_idx_1"])])
+        @test length(keys(output)) == 1 &&
+            length(output["chain_idx_1"]) == 3 &&
+            all([length(vals) == 100 for vals in values(output["chain_idx_1"])])
         output = values_from_chain(model_3, chn_3, nothing, nothing)
-        @test length(keys(output))==1 && length(output["chain_idx_1"]) == 4 && all([length(vals) == 100 for vals in values(output["chain_idx_1"])])
+        @test length(keys(output)) == 1 &&
+            length(output["chain_idx_1"]) == 4 &&
+            all([length(vals) == 100 for vals in values(output["chain_idx_1"])])
     end
 end
\ No newline at end of file

From 140045baac68ce884dedc2a3802d6e4dd695023a Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 13:23:06 +0100
Subject: [PATCH 13/20] added `using Turing` in `DynamicPPL.jl`

---
 src/DynamicPPL.jl | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/DynamicPPL.jl b/src/DynamicPPL.jl
index 51c2c8761..3b5ef5139 100644
--- a/src/DynamicPPL.jl
+++ b/src/DynamicPPL.jl
@@ -21,6 +21,8 @@ using DocStringExtensions
 
 using Random: Random
 
+using Turing
+
 import Base:
     Symbol,
     ==,

From d75a6595cd16071d615a479eef597772321b64f6 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 13:43:23 +0100
Subject: [PATCH 14/20] update `Project.toml`.

---
 docs/Project.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/Project.toml b/docs/Project.toml
index b6cce8b37..54e8b3f82 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -7,6 +7,7 @@ LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 
 [compat]
 DataStructures = "0.18"

From 05085f4d839fd4c44019737b4987022aaadee35b Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 13:50:18 +0100
Subject: [PATCH 15/20] applied reviewdog suggestion.

---
 test/model_utils.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/model_utils.jl b/test/model_utils.jl
index 701f760bb..a1e949f68 100644
--- a/test/model_utils.jl
+++ b/test/model_utils.jl
@@ -10,7 +10,7 @@ chn_1 = Chains(val, [:s, :m])
 # (2) sample a Turing model to create a chain
 @model function gdemo(x)
     mu ~ MvNormal([0, 0, 0], [1 0 0; 0 1 0; 0 0 1])
-    x ~ MvNormal(mu, [1 0 0; 0 1 0; 0 0 1])
+    return x ~ MvNormal(mu, [1 0 0; 0 1 0; 0 0 1])
 end
 model_2 = gdemo([0, 0, 0])  # provide an initial value for `x`
 chn_2 = sample(model_2, NUTS(), 100) # NB: the parameter names in an MCMCChains can be retrieved using `namechn_2.name_map[:parameters]_map`: https://github.com/TuringLang/MCMCChains.jl/blob/master/src/chains.jl

From db24f4eeba7cfd2390f4c69f0b559aebce9a52aa Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 14:46:55 +0100
Subject: [PATCH 16/20] removed `using Turing`.

---
 docs/Project.toml | 1 -
 src/DynamicPPL.jl | 2 --
 2 files changed, 3 deletions(-)

diff --git a/docs/Project.toml b/docs/Project.toml
index 54e8b3f82..b6cce8b37 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -7,7 +7,6 @@ LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
-Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 
 [compat]
 DataStructures = "0.18"
diff --git a/src/DynamicPPL.jl b/src/DynamicPPL.jl
index 3b5ef5139..51c2c8761 100644
--- a/src/DynamicPPL.jl
+++ b/src/DynamicPPL.jl
@@ -21,8 +21,6 @@ using DocStringExtensions
 
 using Random: Random
 
-using Turing
-
 import Base:
     Symbol,
     ==,

From f70004453319b795b6629d3a60009dda4f17bdd1 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 14:46:59 +0100
Subject: [PATCH 17/20] removed `USING tURING`

---
 .vscode/settings.json | 3 +++
 1 file changed, 3 insertions(+)
 create mode 100644 .vscode/settings.json

diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 000000000..0217c48c2
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,3 @@
+{
+    "julia.environmentPath": "/home/yongchao/.julia/dev/DynamicPPL/docs"
+}
\ No newline at end of file

From a4d111ffacc49e97a97507fa8a8c71f121d4cd28 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 14:52:49 +0100
Subject: [PATCH 18/20] removed Turing dependency in `src/model_utils.jl`

---
 src/model_utils.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index 9d0f4870c..d101c8f7d 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -1,6 +1,6 @@
 ### Yong ############################################################## 
 # Yong added the below new functions on 2023-07-04, they are doing the some functionalities as Tor's functions. Some redundancy needs to be removed?
-using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+using Distributions, DynamicPPL, MCMCChains, Random, Test
 
 #### 1. varname_in_chain ####
 # here we just check if vn and its leaves are present in the chain; we are not checking its presence in model. So we don't need to pass model or varinfo to this function.

From 57cd078ded0facfe9976805ccc07ee0fbda47f13 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 14:57:48 +0100
Subject: [PATCH 19/20] removed dependencies in `src/model_utils.jl`

---
 src/model_utils.jl | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index d101c8f7d..4f317a419 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -1,6 +1,7 @@
 ### Yong ############################################################## 
 # Yong added the below new functions on 2023-07-04, they are doing the some functionalities as Tor's functions. Some redundancy needs to be removed?
-using Distributions, DynamicPPL, MCMCChains, Random, Test
+# using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
+using Distributions, Random, Test
 
 #### 1. varname_in_chain ####
 # here we just check if vn and its leaves are present in the chain; we are not checking its presence in model. So we don't need to pass model or varinfo to this function.

From cf30820cf4965ec4c8e96b9fb2dbd9b51c1699c8 Mon Sep 17 00:00:00 2001
From: YongchaoHuang <huangyongchao2012@gmail.com>
Date: Tue, 11 Jul 2023 16:37:32 +0100
Subject: [PATCH 20/20] removed unecessary and improper imports.

---
 src/model_utils.jl  | 3 ---
 test/model_utils.jl | 3 ---
 2 files changed, 6 deletions(-)

diff --git a/src/model_utils.jl b/src/model_utils.jl
index 4f317a419..6710aea05 100644
--- a/src/model_utils.jl
+++ b/src/model_utils.jl
@@ -1,8 +1,5 @@
 ### Yong ############################################################## 
 # Yong added the below new functions on 2023-07-04, they are doing the some functionalities as Tor's functions. Some redundancy needs to be removed?
-# using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
-using Distributions, Random, Test
-
 #### 1. varname_in_chain ####
 # here we just check if vn and its leaves are present in the chain; we are not checking its presence in model. So we don't need to pass model or varinfo to this function.
 """
diff --git a/test/model_utils.jl b/test/model_utils.jl
index a1e949f68..5c490234f 100644
--- a/test/model_utils.jl
+++ b/test/model_utils.jl
@@ -1,6 +1,3 @@
-using Turing, Distributions, DynamicPPL, MCMCChains, Random, Test
-Random.seed!(111)
-
 #### prepare the models and chains for testing ####
 # (1) manually create a chain using MCMCChains - we know what parameter names are in the chain
 val = [1 2; 3 4; 5 6; 7 8; 9 10; 11 12; 13 14; 15 16; 17 18; 19 20]