From dd7abf86924c5948d0cab49813003af77eef1d7c Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Wed, 19 May 2021 20:55:29 +0200
Subject: [PATCH 01/36] Add Turing to extras

To add a compat entry
---
 Project.toml | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/Project.toml b/Project.toml
index 5740e60c9..77ab4f190 100644
--- a/Project.toml
+++ b/Project.toml
@@ -11,6 +11,7 @@ NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
 PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
 REPL = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
@@ -25,6 +26,7 @@ PyCall = "1.91.2"
 PyPlot = "2.8.2"
 Requires = "0.5.2, 1.0"
 StatsBase = "0.32, 0.33"
+Turing = "0.15"
 julia = "^1"
 
 [extras]
@@ -33,6 +35,7 @@ MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 MonteCarloMeasurements = "0987c9cc-fe09-11e8-30f0-b96dd679fdca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 
 [targets]
-test = ["CmdStan", "MCMCChains", "MonteCarloMeasurements", "Random", "Test"]
+test = ["CmdStan", "MCMCChains", "MonteCarloMeasurements", "Random", "Test", "Turing"]

From dff0ed1730a177b4bc2f604e292c89bc7471643b Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Wed, 19 May 2021 20:56:42 +0200
Subject: [PATCH 02/36] Add initial implementation of from_turing

---
 src/ArviZ.jl  |  6 ++++
 src/turing.jl | 83 +++++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 89 insertions(+)
 create mode 100644 src/turing.jl

diff --git a/src/ArviZ.jl b/src/ArviZ.jl
index eb6926ff3..2ce2d1084 100644
--- a/src/ArviZ.jl
+++ b/src/ArviZ.jl
@@ -2,6 +2,7 @@ __precompile__()
 module ArviZ
 
 using Base: @__doc__
+using Random
 using Requires
 using REPL
 using NamedTupleTools
@@ -76,6 +77,7 @@ export InferenceData,
     from_dict,
     from_cmdstan,
     from_mcmcchains,
+    from_turing,
     concat,
     concat!
 
@@ -109,6 +111,10 @@ function __init__()
         import .MCMCChains: Chains, sections
         include("mcmcchains.jl")
     end
+    @require Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0" begin
+        import .Turing: Turing
+        include("turing.jl")
+    end
     return nothing
 end
 
diff --git a/src/turing.jl b/src/turing.jl
new file mode 100644
index 000000000..d253ae85f
--- /dev/null
+++ b/src/turing.jl
@@ -0,0 +1,83 @@
+function from_turing(
+    chns=nothing;
+    model=nothing,
+    rng=Random.default_rng(),
+    nchains=ndraws = chns isa Turing.MCMCChains.Chains ? last(size(chns)) : 1,
+    ndraws=chns isa Turing.MCMCChains.Chains ? first(size(chns)) : 1_000,
+    library=Turing,
+    observed_data=nothing,
+    constant_data=nothing,
+    posterior_predictive=nothing,
+    prior=nothing,
+    prior_predictive=nothing,
+    log_likelihood=nothing,
+    kwargs...,
+)
+    groups = Dict{Symbol,Any}(
+        :observed_data => observed_data,
+        :constant_data => constant_data,
+        :posterior_predictive => posterior_predictive,
+        :prior => prior,
+        :prior_predictive => prior_predictive,
+        :log_likelihood => log_likelihood,
+    )
+    model === nothing && return from_mcmcchains(chns; library=library, groups..., kwargs...)
+    if groups[:prior] === nothing
+        groups[:prior] = reduce(
+            Turing.chainscat,
+            map(
+                _ -> Turing.sample(rng, model, Turing.Prior(), ndraws; progress=false),
+                1:nchains,
+            ),
+        )
+    end
+
+    groups[:observed_data] === nothing &&
+        return from_mcmcchains(chns; library=library, groups..., kwargs...)
+
+    observed_data = groups[:observed_data]
+    data_var_names = Set(
+        observed_data isa Dict ? Symbol.(keys(observed_data)) : propertynames(observed_data)
+    )
+
+    if groups[:constant_data] === nothing
+        groups[:constant_data] = NamedTuple(
+            filter(p -> first(p) ∉ data_var_names, pairs(model.args))
+        )
+    end
+
+    # Instantiate the predictive model
+    args_pred = NamedTuple(
+        k => k in data_var_names ? similar(v, Missing) : v for (k, v) in pairs(model.args)
+    )
+    model_predict = Turing.DynamicPPL.Model(model.name, model.f, args_pred, model.defaults)
+
+    # and then sample!
+    if groups[:prior_predictive] === nothing && groups[:prior] isa Turing.MCMCChains.Chains
+        groups[:prior_predictive] = Turing.predict(rng, model_predict, groups[:prior])
+    end
+
+    if chns isa Turing.MCMCChains.Chains
+        if groups[:posterior_predictive] === nothing && chns isa Turing.MCMCChains.Chains
+            groups[:posterior_predictive] = Turing.predict(rng, model_predict, chns)
+        end
+
+        if groups[:log_likelihood] === nothing &&
+           groups[:posterior_predictive] isa MCMCChains.Chains
+            loglikelihoods = Turing.pointwise_loglikelihoods(
+                model, Turing.MCMCChains.get_sections(chns, :parameters)
+            )
+
+            # Bundle loglikelihoods into a `Chains` object so we can reuse our own variable
+            # name parsing
+            pred_names = string.(keys(groups[:posterior_predictive]))
+            loglikelihoods_vals = getindex.(Ref(loglikelihoods), pred_names)
+            loglikelihoods_arr = permutedims(cat(loglikelihoods_vals...; dims=3), (1, 3, 2))
+            groups[:log_likelihood] = Turing.MCMCChains.Chains(
+                loglikelihoods_arr, pred_names
+            )
+        end
+    end
+
+    return from_mcmcchains(chns; library=Turing, groups..., kwargs...)
+end

From 55cbc78777872a5db38514c8c470b2121526828c Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Wed, 19 May 2021 20:57:17 +0200
Subject: [PATCH 03/36] Handle non-array eltype constraints

---
 src/utils.jl | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/src/utils.jl b/src/utils.jl
index d907d5c13..486541970 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -213,12 +213,17 @@ _asstringkeydict(x::Dict{String}) = x
 
 enforce_stat_eltypes(stats) = convert_to_eltypes(stats, sample_stats_eltypes)
 
+_convert_to_eltype(v::AbstractArray, T) = convert(Array{T}, v)
+_convert_to_eltype(v, T) = convert(T, v)
 function convert_to_eltypes(data::Dict, data_eltypes)
-    return Dict(k => convert(Array{get(data_eltypes, k, eltype(v))}, v) for (k, v) in data)
+    return Dict(
+        k => _convert_to_eltype(v, get(data_eltypes, k, eltype(v))) for (k, v) in data
+    )
 end
 function convert_to_eltypes(data::NamedTuple, data_eltypes)
     return NamedTuple(
-        k => convert(Array{get(data_eltypes, k, eltype(v))}, v) for (k, v) in pairs(data)
+        k => _convert_to_eltype(v, get(data_eltypes, k, eltype(v))) for
+        (k, v) in pairs(data)
     )
 end
 

From d25e5927693bf9ed21114fbc841548eed08e3047 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 13:11:50 +0200
Subject: [PATCH 04/36] Apply suggestions from code review

Co-authored-by: Tor Erlend Fjelde <tor.erlend95@gmail.com>
---
 src/turing.jl | 13 ++-----------
 1 file changed, 2 insertions(+), 11 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index d253ae85f..16f7bfc19 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -23,13 +23,7 @@ function from_turing(
     )
     model === nothing && return from_mcmcchains(chns; library=library, groups..., kwargs...)
     if groups[:prior] === nothing
-        groups[:prior] = reduce(
-            Turing.chainscat,
-            map(
-                _ -> Turing.sample(rng, model, Turing.Prior(), ndraws; progress=false),
-                1:nchains,
-            ),
-        )
+        groups[:prior] = Turing.sample(rng, model, Turing.Prior(), Turing.MCMCThreads(), ndraws, nchains; progress=false)
     end
 
     groups[:observed_data] === nothing &&
@@ -47,10 +41,7 @@ function from_turing(
     end
 
     # Instantiate the predictive model
-    args_pred = NamedTuple(
-        k => k in data_var_names ? similar(v, Missing) : v for (k, v) in pairs(model.args)
-    )
-    model_predict = Turing.DynamicPPL.Model(model.name, model.f, args_pred, model.defaults)
+model_predict = Turing.DynamicPPL.Model{data_var_names}(model.name, model.f, args_pred, model.defaults)
 
     # and then sample!
     if groups[:prior_predictive] === nothing && groups[:prior] isa Turing.MCMCChains.Chains

From 31f902b6b6147fdf2a4c3ba3d7522c033a128ae6 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 13:29:07 +0200
Subject: [PATCH 05/36] Repair predictive model code

---
 src/turing.jl | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index 16f7bfc19..55c3a78c8 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -30,18 +30,21 @@ function from_turing(
         return from_mcmcchains(chns; library=library, groups..., kwargs...)
 
     observed_data = groups[:observed_data]
-    data_var_names = Set(
+    observed_data_keys = Set(
         observed_data isa Dict ? Symbol.(keys(observed_data)) : propertynames(observed_data)
     )
 
     if groups[:constant_data] === nothing
         groups[:constant_data] = NamedTuple(
-            filter(p -> first(p) ∉ data_var_names, pairs(model.args))
+            filter(p -> first(p) ∉ observed_data_keys, pairs(model.args))
         )
     end
 
     # Instantiate the predictive model
-model_predict = Turing.DynamicPPL.Model{data_var_names}(model.name, model.f, args_pred, model.defaults)
+    data_var_names = filter(in(observed_data_keys), keys(model.args))
+    model_predict = Turing.DynamicPPL.Model{data_var_names}(
+        model.name, model.f, model.args, model.defaults
+    )
 
     # and then sample!
     if groups[:prior_predictive] === nothing && groups[:prior] isa Turing.MCMCChains.Chains

From e1da410528ed0e15164509106c851b83a3b4bf9a Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 13:29:19 +0200
Subject: [PATCH 06/36] Run formatter

---
 src/turing.jl | 13 +++++++++++--
 1 file changed, 11 insertions(+), 2 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index 55c3a78c8..e2e139ff8 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -23,11 +23,20 @@ function from_turing(
     )
     model === nothing && return from_mcmcchains(chns; library=library, groups..., kwargs...)
     if groups[:prior] === nothing
-        groups[:prior] = Turing.sample(rng, model, Turing.Prior(), Turing.MCMCThreads(), ndraws, nchains; progress=false)
+        groups[:prior] = Turing.sample(
+            rng,
+            model,
+            Turing.Prior(),
+            Turing.MCMCThreads(),
+            ndraws,
+            nchains;
+            progress=false,
+        )
     end
 
-    groups[:observed_data] === nothing &&
+    if groups[:observed_data] === nothing
         return from_mcmcchains(chns; library=library, groups..., kwargs...)
+    end
 
     observed_data = groups[:observed_data]
     observed_data_keys = Set(

From 454c23e5d34b6394f39bbbe4d07db3adfd3f3996 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 13:29:34 +0200
Subject: [PATCH 07/36] Constrain type of model

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

diff --git a/src/turing.jl b/src/turing.jl
index e2e139ff8..20e3037eb 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -1,6 +1,6 @@
 function from_turing(
     chns=nothing;
-    model=nothing,
+    model::Union{Nothing,Turing.DynamicPPL.Model}=nothing,
     rng=Random.default_rng(),
     nchains=ndraws = chns isa Turing.MCMCChains.Chains ? last(size(chns)) : 1,
     ndraws=chns isa Turing.MCMCChains.Chains ? first(size(chns)) : 1_000,

From 98511f4abf759aa666ab4c9ae4cccdc2d9307c8a Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 14:43:06 +0200
Subject: [PATCH 08/36] Add model name to attributes

---
 src/turing.jl | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/src/turing.jl b/src/turing.jl
index 20e3037eb..ff6675556 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -82,5 +82,13 @@ function from_turing(
         end
     end
 
-    return from_mcmcchains(chns; library=Turing, groups..., kwargs...)
+    idata = from_mcmcchains(chns; library=library, groups..., kwargs...)
+
+    # add model name to generated InferenceData groups
+    for name in groupnames(idata)
+        name in (:observed_data,) && continue
+        ds = getproperty(idata, name)
+        setattribute!(ds, :model_name, nameof(model))
+    end
+    return idata
 end

From 191cfd7736c544ce407c526d6052bbffd2f554a9 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 14:43:45 +0200
Subject: [PATCH 09/36] Support specifying groups to not be generated

---
 src/turing.jl | 54 ++++++++++++++++++++++++++++++++-------------------
 1 file changed, 34 insertions(+), 20 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index ff6675556..599225c9b 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -5,12 +5,12 @@ function from_turing(
     nchains=ndraws = chns isa Turing.MCMCChains.Chains ? last(size(chns)) : 1,
     ndraws=chns isa Turing.MCMCChains.Chains ? first(size(chns)) : 1_000,
     library=Turing,
-    observed_data=nothing,
-    constant_data=nothing,
-    posterior_predictive=nothing,
-    prior=nothing,
-    prior_predictive=nothing,
-    log_likelihood=nothing,
+    observed_data=true,
+    constant_data=true,
+    posterior_predictive=true,
+    prior=true,
+    prior_predictive=true,
+    log_likelihood=true,
     kwargs...,
 )
     groups = Dict{Symbol,Any}(
@@ -21,8 +21,15 @@ function from_turing(
         :prior_predictive => prior_predictive,
         :log_likelihood => log_likelihood,
     )
+    groups_to_generate = Set(k for (k, v) in groups if v === true)
+    for (name, value) in groups
+        if value isa Bool
+            groups[name] = nothing
+        end
+    end
+
     model === nothing && return from_mcmcchains(chns; library=library, groups..., kwargs...)
-    if groups[:prior] === nothing
+    if :prior in groups_to_generate
         groups[:prior] = Turing.sample(
             rng,
             model,
@@ -43,7 +50,7 @@ function from_turing(
         observed_data isa Dict ? Symbol.(keys(observed_data)) : propertynames(observed_data)
     )
 
-    if groups[:constant_data] === nothing
+    if :constant_data in groups_to_generate
         groups[:constant_data] = NamedTuple(
             filter(p -> first(p) ∉ observed_data_keys, pairs(model.args))
         )
@@ -56,29 +63,36 @@ function from_turing(
     )
 
     # and then sample!
-    if groups[:prior_predictive] === nothing && groups[:prior] isa Turing.MCMCChains.Chains
-        groups[:prior_predictive] = Turing.predict(rng, model_predict, groups[:prior])
+    if :prior_predictive in groups_to_generate
+        if groups[:prior] isa Turing.MCMCChains.Chains
+            groups[:prior_predictive] = Turing.predict(rng, model_predict, groups[:prior])
+        elseif groups[:prior] !== nothing
+            @warn "Could not generate group :prior_predictive because group :prior was not an MCMCChains.Chains."
+        end
     end
 
-    if chns isa Turing.MCMCChains.Chains
-        if groups[:posterior_predictive] === nothing && chns isa Turing.MCMCChains.Chains
+    if :posterior_predictive in groups_to_generate
+        if chns isa Turing.MCMCChains.Chains
             groups[:posterior_predictive] = Turing.predict(rng, model_predict, chns)
+        elseif chns !== nothing
+            @warn "Could not generate group :posterior_predictive because group :posterior was not an MCMCChains.Chains."
         end
+    end
 
-        if groups[:log_likelihood] === nothing &&
-           groups[:posterior_predictive] isa MCMCChains.Chains
-            loglikelihoods = Turing.pointwise_loglikelihoods(
-                model, Turing.MCMCChains.get_sections(chns, :parameters)
-            )
-
+    if :log_likelihood in groups_to_generate
+        if chns isa Turing.MCMCChains.Chains
+            chains_only_params = Turing.MCMCChains.get_sections(chns, :parameters)
+            loglikelihoods = Turing.pointwise_loglikelihoods(model, chains_only_params)
+            pred_names = sort(collect(keys(loglikelihoods)); by=split_locname)
+            loglikelihoods_vals = getindex.(Ref(loglikelihoods), pred_names)
             # Bundle loglikelihoods into a `Chains` object so we can reuse our own variable
             # name parsing
-            pred_names = string.(keys(groups[:posterior_predictive]))
-            loglikelihoods_vals = getindex.(Ref(loglikelihoods), pred_names)
             loglikelihoods_arr = permutedims(cat(loglikelihoods_vals...; dims=3), (1, 3, 2))
             groups[:log_likelihood] = Turing.MCMCChains.Chains(
                 loglikelihoods_arr, pred_names
             )
+        elseif chns !== nothing
+            @warn "Could not generate log_likelihood because posterior must be an MCMCChains.Chains."
         end
     end
 

From 2c6cc324c22cfc31766b302f7f3dce614dfe2ef7 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 14:44:38 +0200
Subject: [PATCH 10/36] Constrain type of rng

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

diff --git a/src/turing.jl b/src/turing.jl
index 599225c9b..eeaa199c5 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -1,7 +1,7 @@
 function from_turing(
     chns=nothing;
     model::Union{Nothing,Turing.DynamicPPL.Model}=nothing,
-    rng=Random.default_rng(),
+    rng::AbstractRNG=Random.default_rng(),
     nchains=ndraws = chns isa Turing.MCMCChains.Chains ? last(size(chns)) : 1,
     ndraws=chns isa Turing.MCMCChains.Chains ? first(size(chns)) : 1_000,
     library=Turing,

From 134a6a12c6e2aca0d59767b2148327224ce19a43 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 15:07:58 +0200
Subject: [PATCH 11/36] Add docstring

---
 src/turing.jl | 60 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 60 insertions(+)

diff --git a/src/turing.jl b/src/turing.jl
index eeaa199c5..0e618cc69 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -1,3 +1,63 @@
+"""
+    from_turing([posterior::Chains]; kwargs...) -> InferenceData
+
+Convert data from Turing into an [`InferenceData`](@ref).
+
+This permits passing a Turing `Model` and a random number generator to
+`model` and `rng` keywords to automatically generate groups. By default,
+if `posterior`, `observed_data`, and `model` are provided, then the 
+`prior`, `prior_predictive`, `posterior_predictive`, and `log_likelihood`
+groups are automatically generated. To avoid generating a group, provide
+group data or set it to `false`.
+
+# Arguments
+
+- `posterior::Chains`: Draws from the posterior
+
+# Keywords
+
+- `model::Turing.DynamicPPL.Model`: A Turing model conditioned on observed and
+constant data. `constant_data` must be provided for the model to be used.
+- `rng::AbstractRNG=Random.default_rng()`: a random number generator used for
+sampling from the prior, posterior predictive and prior predictive
+distributions.
+- `nchains::Int`: Number of chains for prior samples, defaulting to the number
+of chains in the posterior, if provided, else 1.
+- `ndraws::Int`: Number of draws per chain for prior samples, defaulting to the
+number of draws per chain in the posterior, if provided, else 1,000.
+- `kwargs`: For remaining keywords, see [`from_mcmcchains`](@ref).
+
+# Examples
+
+```jldoctest
+julia> using Turing, Random
+
+julia> rng = Random.seed!(42);
+
+julia> @model function demo(xs, y)
+           s ~ InverseGamma(2, 3)
+           m ~ Normal(0, √s)
+           for i in eachindex(xs)
+               xs[i] ~ Normal(m, √s)
+           end
+           y ~ Normal(m, √s)
+       end;
+
+julia> observed_data = (xs=[0.87, 0.08, 0.53], y=-0.85);
+
+julia> model = demo(observed_data...);
+
+julia> chn = sample(rng, model, NUTS(), 1_000; progress=false);
+
+julia> from_turing(chn; model=model, rng=rng, observed_data=observed_data, prior=false)
+InferenceData with groups:
+	> posterior
+	> posterior_predictive
+	> log_likelihood
+	> sample_stats
+	> observed_data
+```
+"""
 function from_turing(
     chns=nothing;
     model::Union{Nothing,Turing.DynamicPPL.Model}=nothing,

From 9e3edb7a0b9e473e657cb5f017bfc55057d810a9 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 15:10:17 +0200
Subject: [PATCH 12/36] Document from_turing

---
 docs/make.jl      | 2 +-
 docs/src/api.md   | 1 +
 src/mcmcchains.jl | 2 ++
 3 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/docs/make.jl b/docs/make.jl
index 5a01f02cb..4189e6cbf 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -1,5 +1,5 @@
 using Documenter, ArviZ
-using MCMCChains: MCMCChains # make `from_mcmcchains` available for API docs
+using Turing # make `from_mcmcchains` and `from_turing` available for API docs
 
 makedocs(;
     modules=[ArviZ],
diff --git a/docs/src/api.md b/docs/src/api.md
index e882101f7..42766a299 100644
--- a/docs/src/api.md
+++ b/docs/src/api.md
@@ -71,6 +71,7 @@
 | [`from_namedtuple`](@ref)           | Convert `NamedTuple` data into an `InferenceData`. |
 | [`from_dict`](@ref)                 | Convert `Dict` data into an `InferenceData`.       |
 | [`from_cmdstan`](@ref)              | Convert CmdStan data into an `InferenceData`.      |
+| [`from_turing`](@ref)               | Convert data from Turing into an `InferenceData`.  |
 | [`from_mcmcchains`](@ref)           | Convert `MCMCChains` data into an `InferenceData`. |
 | [`concat`](@ref)                    | Concatenate `InferenceData` objects.               |
 | [`concat!`](@ref)                   | Concatenate `InferenceData` objects in-place.      |
diff --git a/src/mcmcchains.jl b/src/mcmcchains.jl
index 049867ae0..f736937d2 100644
--- a/src/mcmcchains.jl
+++ b/src/mcmcchains.jl
@@ -124,6 +124,8 @@ Convert data in an `MCMCChains.Chains` format into an [`InferenceData`](@ref).
 Any keyword argument below without an an explicitly annotated type above is allowed, so long
 as it can be passed to [`convert_to_inference_data`](@ref).
 
+For chains data from Turing, see [`from_turing`](@ref) for more options.
+
 # Arguments
 
 - `posterior::Chains`: Draws from the posterior

From 34084768a160193cd2fab760ebe1560150e5f6b6 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 15:13:01 +0200
Subject: [PATCH 13/36] Also generate constant_data

---
 src/turing.jl | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index 0e618cc69..2f8fc579b 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -34,10 +34,10 @@ julia> using Turing, Random
 
 julia> rng = Random.seed!(42);
 
-julia> @model function demo(xs, y)
+julia> @model function demo(xs, y, n=length(xs))
            s ~ InverseGamma(2, 3)
            m ~ Normal(0, √s)
-           for i in eachindex(xs)
+           for i in 1:n
                xs[i] ~ Normal(m, √s)
            end
            y ~ Normal(m, √s)
@@ -56,6 +56,7 @@ InferenceData with groups:
 	> log_likelihood
 	> sample_stats
 	> observed_data
+	> constant_data
 ```
 """
 function from_turing(

From 180e56083b6b5985926bf9d1ef2bd47ae10db304 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 16:46:46 +0200
Subject: [PATCH 14/36] Make code more modular

---
 src/turing.jl | 73 ++++++++++++++++++++++++++++++---------------------
 1 file changed, 43 insertions(+), 30 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index 2f8fc579b..98bdbaf4d 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -1,4 +1,4 @@
-"""
+@doc doc"""
     from_turing([posterior::Chains]; kwargs...) -> InferenceData
 
 Convert data from Turing into an [`InferenceData`](@ref).
@@ -91,15 +91,7 @@ function from_turing(
 
     model === nothing && return from_mcmcchains(chns; library=library, groups..., kwargs...)
     if :prior in groups_to_generate
-        groups[:prior] = Turing.sample(
-            rng,
-            model,
-            Turing.Prior(),
-            Turing.MCMCThreads(),
-            ndraws,
-            nchains;
-            progress=false,
-        )
+        groups[:prior] = _sample_prior(rng, model, nchains, ndraws)
     end
 
     if groups[:observed_data] === nothing
@@ -112,21 +104,16 @@ function from_turing(
     )
 
     if :constant_data in groups_to_generate
-        groups[:constant_data] = NamedTuple(
+        groups[:constant_data] = Dict(
             filter(p -> first(p) ∉ observed_data_keys, pairs(model.args))
         )
     end
 
-    # Instantiate the predictive model
-    data_var_names = filter(in(observed_data_keys), keys(model.args))
-    model_predict = Turing.DynamicPPL.Model{data_var_names}(
-        model.name, model.f, model.args, model.defaults
-    )
-
-    # and then sample!
     if :prior_predictive in groups_to_generate
         if groups[:prior] isa Turing.MCMCChains.Chains
-            groups[:prior_predictive] = Turing.predict(rng, model_predict, groups[:prior])
+            groups[:prior_predictive] = _sample_predictive(
+                rng, model, groups[:prior], observed_data_keys
+            )
         elseif groups[:prior] !== nothing
             @warn "Could not generate group :prior_predictive because group :prior was not an MCMCChains.Chains."
         end
@@ -134,7 +121,9 @@ function from_turing(
 
     if :posterior_predictive in groups_to_generate
         if chns isa Turing.MCMCChains.Chains
-            groups[:posterior_predictive] = Turing.predict(rng, model_predict, chns)
+            groups[:posterior_predictive] = _sample_predictive(
+                rng, model, chns, observed_data_keys
+            )
         elseif chns !== nothing
             @warn "Could not generate group :posterior_predictive because group :posterior was not an MCMCChains.Chains."
         end
@@ -142,16 +131,7 @@ function from_turing(
 
     if :log_likelihood in groups_to_generate
         if chns isa Turing.MCMCChains.Chains
-            chains_only_params = Turing.MCMCChains.get_sections(chns, :parameters)
-            loglikelihoods = Turing.pointwise_loglikelihoods(model, chains_only_params)
-            pred_names = sort(collect(keys(loglikelihoods)); by=split_locname)
-            loglikelihoods_vals = getindex.(Ref(loglikelihoods), pred_names)
-            # Bundle loglikelihoods into a `Chains` object so we can reuse our own variable
-            # name parsing
-            loglikelihoods_arr = permutedims(cat(loglikelihoods_vals...; dims=3), (1, 3, 2))
-            groups[:log_likelihood] = Turing.MCMCChains.Chains(
-                loglikelihoods_arr, pred_names
-            )
+            groups[:log_likelihood] = _compute_log_likelihood(model, chns)
         elseif chns !== nothing
             @warn "Could not generate log_likelihood because posterior must be an MCMCChains.Chains."
         end
@@ -167,3 +147,36 @@ function from_turing(
     end
     return idata
 end
+
+function _sample_prior(rng::AbstractRNG, model::Turing.DynamicPPL.Model, nchains, ndraws)
+    return Turing.sample(
+        rng, model, Turing.Prior(), Turing.MCMCThreads(), ndraws, nchains; progress=false
+    )
+end
+
+function _build_predictive_model(model::Turing.DynamicPPL.Model, data_keys)
+    var_names = filter(in(data_keys), keys(model.args))
+    return Turing.DynamicPPL.Model{var_names}(
+        model.name, model.f, model.args, model.defaults
+    )
+end
+
+function _sample_predictive(
+    rng::AbstractRNG, model::Turing.DynamicPPL.Model, chns, data_keys
+)
+    model_predict = _build_predictive_model(model, data_keys)
+    return Turing.predict(rng, model_predict, chns)
+end
+
+function _compute_log_likelihood(
+    model::Turing.DynamicPPL.Model, chns::Turing.MCMCChains.Chains
+)
+    chains_only_params = Turing.MCMCChains.get_sections(chns, :parameters)
+    loglikelihoods = Turing.pointwise_loglikelihoods(model, chains_only_params)
+    pred_names = sort(collect(keys(loglikelihoods)); by=split_locname)
+    loglikelihoods_vals = getindex.(Ref(loglikelihoods), pred_names)
+    # Bundle loglikelihoods into a `Chains` object so we can reuse our own variable
+    # name parsing
+    loglikelihoods_arr = permutedims(cat(loglikelihoods_vals...; dims=3), (1, 3, 2))
+    return Turing.MCMCChains.Chains(loglikelihoods_arr, pred_names)
+end

From 85ddd695c8313b6168b052decafc36f69c63d6a9 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 16:47:01 +0200
Subject: [PATCH 15/36] Add Turing tests

---
 test/runtests.jl    |  1 +
 test/test_turing.jl | 74 +++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 75 insertions(+)
 create mode 100644 test/test_turing.jl

diff --git a/test/runtests.jl b/test/runtests.jl
index 20ffc06bf..18b64ad76 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -13,4 +13,5 @@ using Test
     include("test_plots.jl")
     include("test_namedtuple.jl")
     include("test_mcmcchains.jl")
+    include("test_turing.jl")
 end
diff --git a/test/test_turing.jl b/test/test_turing.jl
new file mode 100644
index 000000000..2dbe60c43
--- /dev/null
+++ b/test/test_turing.jl
@@ -0,0 +1,74 @@
+using Turing
+using ArviZ
+using ArviZ: groupnames
+using Test
+using Random
+
+@testset "from_turing" begin
+    nchains = 4
+    ndraws = 10
+    Turing.@model function demo(xs, y, n=length(xs))
+        s ~ InverseGamma(2, 3)
+        m ~ Normal(0, √s)
+        for i in 1:n
+            xs[i] ~ Normal(m, √s)
+        end
+        return y ~ Normal(m, √s)
+    end
+    xs = randn(5)
+    y = randn()
+    observed_data = (xs=xs, y=y)
+    model = demo(observed_data...)
+    chn = Turing.sample(
+        model, Turing.MH(), Turing.MCMCThreads(), ndraws, nchains; progress=false
+    )
+    @test size(chn) == (10, 3, 4)
+
+    idata1 = from_turing(chn)
+    @test sort(groupnames(idata1)) == [:posterior, :sample_stats]
+    @test idata1.posterior.inference_library == "Turing"
+
+    idata2 = from_turing(; model=model)
+    @test sort(groupnames(idata2)) == [:prior, :sample_stats_prior]
+    @test length(idata2.prior.chain.values) == 1
+    @test length(idata2.prior.draw.values) == 1_000
+    @test idata1.posterior.inference_library == "Turing"
+
+    idata3 = from_turing(chn; model=model)
+    @test sort(groupnames(idata3)) ==
+          sort([:posterior, :sample_stats, :prior, :sample_stats_prior])
+    @test length(idata3.prior.chain.values) == nchains
+    @test length(idata3.prior.draw.values) == ndraws
+
+    idata4 = from_turing(chn; model=model, prior=false)
+    @test sort(groupnames(idata4)) == [:posterior, :sample_stats]
+
+    idata5 = from_turing(
+        chn; model=model, observed_data=observed_data, nchains=3, ndraws=100
+    )
+    @test sort(groupnames(idata5)) == sort([
+        :posterior,
+        :posterior_predictive,
+        :log_likelihood,
+        :sample_stats,
+        :prior,
+        :prior_predictive,
+        :sample_stats_prior,
+        :observed_data,
+        :constant_data,
+    ])
+    @test length(idata5.prior.chain.values) == 3
+    @test length(idata5.prior.draw.values) == 100
+
+    rng1 = Random.MersenneTwister(42)
+    idata6 = from_turing(chn; model=model, observed_data=observed_data, rng=rng1)
+    rng2 = Random.MersenneTwister(42)
+    idata7 = from_turing(chn; model=model, observed_data=observed_data, rng=rng2)
+    @testset for name in groupnames(idata6)
+        group1 = getproperty(idata6, name)
+        group2 = getproperty(idata7, name)
+        @testset for var_name in group1.variables.keys()
+            @test group1[var_name].values == group2[var_name].values
+        end
+    end
+end

From 4f50d7a21096d35a9c4868081351fd7f06cb2bcc Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 18:14:15 +0200
Subject: [PATCH 16/36] Force library to be Turing

---
 src/turing.jl       | 8 ++++----
 test/test_turing.jl | 1 +
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index 98bdbaf4d..b9e85e596 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -65,7 +65,6 @@ function from_turing(
     rng::AbstractRNG=Random.default_rng(),
     nchains=ndraws = chns isa Turing.MCMCChains.Chains ? last(size(chns)) : 1,
     ndraws=chns isa Turing.MCMCChains.Chains ? first(size(chns)) : 1_000,
-    library=Turing,
     observed_data=true,
     constant_data=true,
     posterior_predictive=true,
@@ -89,13 +88,13 @@ function from_turing(
         end
     end
 
-    model === nothing && return from_mcmcchains(chns; library=library, groups..., kwargs...)
+    model === nothing && return from_mcmcchains(chns; groups..., library=Turing, kwargs...)
     if :prior in groups_to_generate
         groups[:prior] = _sample_prior(rng, model, nchains, ndraws)
     end
 
     if groups[:observed_data] === nothing
-        return from_mcmcchains(chns; library=library, groups..., kwargs...)
+        return from_mcmcchains(chns; groups..., library=Turing, kwargs...)
     end
 
     observed_data = groups[:observed_data]
@@ -137,13 +136,14 @@ function from_turing(
         end
     end
 
-    idata = from_mcmcchains(chns; library=library, groups..., kwargs...)
+    idata = from_mcmcchains(chns; groups..., kwargs...)
 
     # add model name to generated InferenceData groups
     for name in groupnames(idata)
         name in (:observed_data,) && continue
         ds = getproperty(idata, name)
         setattribute!(ds, :model_name, nameof(model))
+        setattribute!(ds, :inference_library, :Turing)
     end
     return idata
 end
diff --git a/test/test_turing.jl b/test/test_turing.jl
index 2dbe60c43..7bcc97d0c 100644
--- a/test/test_turing.jl
+++ b/test/test_turing.jl
@@ -46,6 +46,7 @@ using Random
     idata5 = from_turing(
         chn; model=model, observed_data=observed_data, nchains=3, ndraws=100
     )
+    @test idata5.posterior.inference_library == "Turing"
     @test sort(groupnames(idata5)) == sort([
         :posterior,
         :posterior_predictive,

From 1b58b6b5b75622efb7df7e543a72eb6934666cc4 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 21:39:25 +0200
Subject: [PATCH 17/36] Overload setattribute! for InferenceData

---
 src/data.jl | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/src/data.jl b/src/data.jl
index 058d38a1c..0efb513d3 100644
--- a/src/data.jl
+++ b/src/data.jl
@@ -165,3 +165,10 @@ function reorder_groups!(data::InferenceData; group_order=SUPPORTED_GROUPS)
     setproperty!(obj, :_groups, string.([sorted_names; other_names]))
     return data
 end
+
+function setattribute!(data::InferenceData, key, value)
+    for (_, group) in groups(data)
+        setattribute!(group, key, value)
+    end
+    return data
+end

From 12ca8742f809281945b9be5ea9e3e6907ffc88af Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 21:40:03 +0200
Subject: [PATCH 18/36] Add function to add inference library info

---
 Project.toml |  2 ++
 src/ArviZ.jl |  1 +
 src/data.jl  | 10 ++++++++++
 3 files changed, 13 insertions(+)

diff --git a/Project.toml b/Project.toml
index 77ab4f190..bcdfc43f4 100644
--- a/Project.toml
+++ b/Project.toml
@@ -8,6 +8,7 @@ Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
 NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50"
+PkgVersion = "eebad327-c553-4316-9ea0-9fa01ccd7688"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
 PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
 REPL = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
@@ -22,6 +23,7 @@ DataFrames = "0.20, 0.21, 0.22, 1.0"
 MCMCChains = "0.3.15, 0.4, 1.0, 2.0, 3.0, 4.0"
 MonteCarloMeasurements = "0.6.4, 0.7, 0.8"
 NamedTupleTools = "0.11.0, 0.12, 0.13"
+PkgVersion = "0.1"
 PyCall = "1.91.2"
 PyPlot = "2.8.2"
 Requires = "0.5.2, 1.0"
diff --git a/src/ArviZ.jl b/src/ArviZ.jl
index 2ce2d1084..ab828b756 100644
--- a/src/ArviZ.jl
+++ b/src/ArviZ.jl
@@ -7,6 +7,7 @@ using Requires
 using REPL
 using NamedTupleTools
 using DataFrames
+using PkgVersion: PkgVersion
 
 using PyCall
 using Conda
diff --git a/src/data.jl b/src/data.jl
index 0efb513d3..9ce412850 100644
--- a/src/data.jl
+++ b/src/data.jl
@@ -172,3 +172,13 @@ function setattribute!(data::InferenceData, key, value)
     end
     return data
 end
+
+_add_library_attributes!(data, ::Nothing) = ds
+function _add_library_attributes!(data, library)
+    setattribute!(data, :inference_library, string(library))
+    if library isa Module
+        lib_version = string(PkgVersion.Version(library))
+        setattribute!(data, :inference_library_version, lib_version)
+    end
+    return data
+end

From a7bb79fb2d1ea5b7889e17cb171df55ac8ca9119 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 21:42:24 +0200
Subject: [PATCH 19/36] Globally use library utility

---
 src/mcmcchains.jl | 25 +++++++------------------
 src/namedtuple.jl | 14 +++-----------
 src/turing.jl     | 14 ++++++--------
 3 files changed, 16 insertions(+), 37 deletions(-)

diff --git a/src/mcmcchains.jl b/src/mcmcchains.jl
index f736937d2..50bd7a1c4 100644
--- a/src/mcmcchains.jl
+++ b/src/mcmcchains.jl
@@ -172,7 +172,6 @@ function from_mcmcchains(
     kwargs...,
 )
     kwargs = convert(Dict, merge((; dims=Dict()), kwargs))
-    library = string(library)
     rekey_fun = d -> rekey(d, stats_key_map)
 
     # Convert chains to dicts
@@ -203,23 +202,18 @@ function from_mcmcchains(
             group_data = popsubdict!(post_dict, group_data)
         end
         group_dataset = if group_data isa Chains
-            convert_to_dataset(group_data; library=library, eltypes=eltypes, kwargs...)
+            convert_to_dataset(group_data; eltypes=eltypes, kwargs...)
         else
-            convert_to_dataset(group_data; library=library, kwargs...)
+            convert_to_dataset(group_data; kwargs...)
         end
-        setattribute!(group_dataset, "inference_library", library)
         concat!(all_idata, InferenceData(; group => group_dataset))
     end
 
-    attrs_library = Dict("inference_library" => library)
-    if posterior === nothing
-        attrs = attrs_library
-    else
-        attrs = merge(attributes_dict(posterior), attrs_library)
-    end
+    attrs = posterior === nothing ? Dict() : attributes_dict(posterior)
     kwargs = convert(Dict, merge((; attrs=attrs, dims=Dict()), kwargs))
     post_idata = _from_dict(post_dict; sample_stats=stats_dict, kwargs...)
     concat!(all_idata, post_idata)
+    _add_library_attributes!(all_idata, library)
     return all_idata
 end
 function from_mcmcchains(
@@ -243,18 +237,13 @@ function from_mcmcchains(
         posterior_predictive,
         predictions,
         log_likelihood;
-        library=library,
         eltypes=eltypes,
         kwargs...,
     )
 
     if prior !== nothing
         pre_prior_idata = convert_to_inference_data(
-            prior;
-            posterior_predictive=prior_predictive,
-            library=library,
-            eltypes=eltypes,
-            kwargs...,
+            prior; posterior_predictive=prior_predictive, eltypes=eltypes, kwargs...
         )
         prior_idata = rekey(
             pre_prior_idata,
@@ -274,10 +263,10 @@ function from_mcmcchains(
     ]
         group_data === nothing && continue
         group_data = convert_to_eltypes(group_data, eltypes)
-        group_dataset = convert_to_constant_dataset(group_data; library=library, kwargs...)
+        group_dataset = convert_to_constant_dataset(group_data; kwargs...)
         concat!(all_idata, InferenceData(; group => group_dataset))
     end
-
+    _add_library_attributes!(all_idata, library)
     return all_idata
 end
 
diff --git a/src/namedtuple.jl b/src/namedtuple.jl
index 06b3c7b73..600bad340 100644
--- a/src/namedtuple.jl
+++ b/src/namedtuple.jl
@@ -140,20 +140,14 @@ function from_namedtuple(
             isempty(group_data) && continue
         end
         group_dataset = convert_to_dataset(group_data; kwargs...)
-        if library !== nothing
-            setattribute!(group_dataset, "inference_library", string(library))
-        end
         concat!(all_idata, InferenceData(; group => group_dataset))
     end
 
     (post_dict === nothing || isempty(post_dict)) && return all_idata
 
     group_dataset = convert_to_dataset(post_dict; kwargs...)
-    if library !== nothing
-        setattribute!(group_dataset, "inference_library", string(library))
-    end
     concat!(all_idata, InferenceData(; posterior=group_dataset))
-
+    _add_library_attributes!(all_idata, library)
     return all_idata
 end
 function from_namedtuple(
@@ -177,7 +171,6 @@ function from_namedtuple(
         sample_stats,
         predictions,
         log_likelihood;
-        library=library,
         kwargs...,
     )
 
@@ -186,7 +179,6 @@ function from_namedtuple(
             prior;
             posterior_predictive=prior_predictive,
             sample_stats=sample_stats_prior,
-            library=library,
             kwargs...,
         )
         prior_idata = rekey(
@@ -207,10 +199,10 @@ function from_namedtuple(
     ]
         group_data === nothing && continue
         group_dict = convert(Dict, group_data)
-        group_dataset = convert_to_constant_dataset(group_dict; library=library, kwargs...)
+        group_dataset = convert_to_constant_dataset(group_dict; kwargs...)
         concat!(all_idata, InferenceData(; group => group_dataset))
     end
-
+    _add_library_attributes!(all_idata, library)
     return all_idata
 end
 function from_namedtuple(data::AbstractVector{<:NamedTuple}; kwargs...)
diff --git a/src/turing.jl b/src/turing.jl
index b9e85e596..a52a996df 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -73,6 +73,9 @@ function from_turing(
     log_likelihood=true,
     kwargs...,
 )
+    kwargs = Dict{Symbol,Any}(kwargs)
+    kwargs[:library] = Turing
+
     groups = Dict{Symbol,Any}(
         :observed_data => observed_data,
         :constant_data => constant_data,
@@ -88,13 +91,13 @@ function from_turing(
         end
     end
 
-    model === nothing && return from_mcmcchains(chns; groups..., library=Turing, kwargs...)
+    model === nothing && return from_mcmcchains(chns; groups..., kwargs...)
     if :prior in groups_to_generate
         groups[:prior] = _sample_prior(rng, model, nchains, ndraws)
     end
 
     if groups[:observed_data] === nothing
-        return from_mcmcchains(chns; groups..., library=Turing, kwargs...)
+        return from_mcmcchains(chns; groups..., kwargs...)
     end
 
     observed_data = groups[:observed_data]
@@ -139,12 +142,7 @@ function from_turing(
     idata = from_mcmcchains(chns; groups..., kwargs...)
 
     # add model name to generated InferenceData groups
-    for name in groupnames(idata)
-        name in (:observed_data,) && continue
-        ds = getproperty(idata, name)
-        setattribute!(ds, :model_name, nameof(model))
-        setattribute!(ds, :inference_library, :Turing)
-    end
+    setattribute!(idata, :model_name, nameof(model))
     return idata
 end
 

From 42c882382f32215bc51375d17f861c3f01ab245a Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 21:42:40 +0200
Subject: [PATCH 20/36] Test library utility for Turing

---
 test/test_turing.jl | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/test/test_turing.jl b/test/test_turing.jl
index 7bcc97d0c..a61ebb774 100644
--- a/test/test_turing.jl
+++ b/test/test_turing.jl
@@ -27,12 +27,14 @@ using Random
     idata1 = from_turing(chn)
     @test sort(groupnames(idata1)) == [:posterior, :sample_stats]
     @test idata1.posterior.inference_library == "Turing"
+    VersionNumber(idata1.posterior.inference_library_version)
 
     idata2 = from_turing(; model=model)
     @test sort(groupnames(idata2)) == [:prior, :sample_stats_prior]
     @test length(idata2.prior.chain.values) == 1
     @test length(idata2.prior.draw.values) == 1_000
-    @test idata1.posterior.inference_library == "Turing"
+    @test idata2.prior.inference_library == "Turing"
+    VersionNumber(idata2.prior.inference_library_version)
 
     idata3 = from_turing(chn; model=model)
     @test sort(groupnames(idata3)) ==
@@ -47,6 +49,8 @@ using Random
         chn; model=model, observed_data=observed_data, nchains=3, ndraws=100
     )
     @test idata5.posterior.inference_library == "Turing"
+    VersionNumber(idata5.posterior.inference_library_version)
+
     @test sort(groupnames(idata5)) == sort([
         :posterior,
         :posterior_predictive,

From 842447f9c60efb3e985457c128b15f8c556c876c Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 21:43:37 +0200
Subject: [PATCH 21/36] Increment version number

---
 Project.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Project.toml b/Project.toml
index bcdfc43f4..ffea08692 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "ArviZ"
 uuid = "131c737c-5715-5e2e-ad31-c244f01c1dc7"
 authors = ["Seth Axen <seth.axen@gmail.com>"]
-version = "0.5.4"
+version = "0.5.5"
 
 [deps]
 Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"

From c9b45624840fd0ca710fab1cd6f704c92d528a13 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 21:58:04 +0200
Subject: [PATCH 22/36] Repair Turing example

---
 src/turing.jl | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index a52a996df..d6a23c12a 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -30,7 +30,7 @@ number of draws per chain in the posterior, if provided, else 1,000.
 # Examples
 
 ```jldoctest
-julia> using Turing, Random
+julia> using Turing, Random, ArviZ
 
 julia> rng = Random.seed!(42);
 
@@ -47,7 +47,7 @@ julia> observed_data = (xs=[0.87, 0.08, 0.53], y=-0.85);
 
 julia> model = demo(observed_data...);
 
-julia> chn = sample(rng, model, NUTS(), 1_000; progress=false);
+julia> chn = sample(rng, model, MH(), 1_000; progress=false);
 
 julia> from_turing(chn; model=model, rng=rng, observed_data=observed_data, prior=false)
 InferenceData with groups:

From e0d9ae309eb13d7230dc52973d6f6fa659e26af1 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 22:05:55 +0200
Subject: [PATCH 23/36] Don't import Turing's exports

Causes clash with ess
---
 docs/make.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/make.jl b/docs/make.jl
index 4189e6cbf..bcae8bc22 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -1,5 +1,5 @@
 using Documenter, ArviZ
-using Turing # make `from_mcmcchains` and `from_turing` available for API docs
+using Turing: Turing  # make `from_mcmcchains` and `from_turing` available for API docs
 
 makedocs(;
     modules=[ArviZ],

From a90df635497eb05ed9e7a06df7d0b7d2e9057a64 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 22:06:04 +0200
Subject: [PATCH 24/36] Return correct variable name

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

diff --git a/src/data.jl b/src/data.jl
index 9ce412850..d407b1a25 100644
--- a/src/data.jl
+++ b/src/data.jl
@@ -173,7 +173,7 @@ function setattribute!(data::InferenceData, key, value)
     return data
 end
 
-_add_library_attributes!(data, ::Nothing) = ds
+_add_library_attributes!(data, ::Nothing) = data
 function _add_library_attributes!(data, library)
     setattribute!(data, :inference_library, string(library))
     if library isa Module

From ea273efc38b8856a0fd80c6a39d5903367e92c07 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 22:32:34 +0200
Subject: [PATCH 25/36] Indent wrapped lines

---
 src/turing.jl | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index d6a23c12a..4457af78f 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -17,14 +17,14 @@ group data or set it to `false`.
 # Keywords
 
 - `model::Turing.DynamicPPL.Model`: A Turing model conditioned on observed and
-constant data. `constant_data` must be provided for the model to be used.
+     constant data. `constant_data` must be provided for the model to be used.
 - `rng::AbstractRNG=Random.default_rng()`: a random number generator used for
-sampling from the prior, posterior predictive and prior predictive
-distributions.
+     sampling from the prior, posterior predictive and prior predictive
+     distributions.
 - `nchains::Int`: Number of chains for prior samples, defaulting to the number
-of chains in the posterior, if provided, else 1.
+     of chains in the posterior, if provided, else 1.
 - `ndraws::Int`: Number of draws per chain for prior samples, defaulting to the
-number of draws per chain in the posterior, if provided, else 1,000.
+     number of draws per chain in the posterior, if provided, else 1,000.
 - `kwargs`: For remaining keywords, see [`from_mcmcchains`](@ref).
 
 # Examples

From 6e93fa72a8d42ab10ea9553d1922ebb33ed5b82b Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 22:34:31 +0200
Subject: [PATCH 26/36] Update quickstart.md

---
 docs/src/quickstart.md | 49 ++++++------------------------------------
 1 file changed, 7 insertions(+), 42 deletions(-)

diff --git a/docs/src/quickstart.md b/docs/src/quickstart.md
index b72b5493f..6237313b5 100644
--- a/docs/src/quickstart.md
+++ b/docs/src/quickstart.md
@@ -121,7 +121,7 @@ idata = from_mcmcchains(
     turing_chns;
     coords=Dict("school" => schools),
     dims=Dict("y" => ["school"], "σ" => ["school"], "θ" => ["school"]),
-    library="Turing",
+    library=Turing,
 )
 ```
 
@@ -154,52 +154,17 @@ gcf()
 
 ### Additional information in Turing.jl
 
-With a few more steps, we can use Turing to compute additional useful groups to add to the [`InferenceData`](@ref).
-
-To sample from the prior, one simply calls `sample` but with the `Prior` sampler:
-
-```@example turing
-prior = sample(param_mod, Prior(), nsamples; progress=false)
-```
-
-To draw from the prior and posterior predictive distributions we can instantiate a "predictive model", i.e. a Turing model but with the observations set to `missing`, and then calling `predict` on the predictive model and the previously drawn samples:
-
-```@example turing
-# Instantiate the predictive model
-param_mod_predict = turing_model(similar(y, Missing), σ)
-# and then sample!
-prior_predictive = predict(param_mod_predict, prior)
-posterior_predictive = predict(param_mod_predict, turing_chns)
-```
-
-And to extract the pointwise log-likelihoods, which is useful if you want to compute metrics such as [`loo`](@ref),
-
-```@example turing
-loglikelihoods = Turing.pointwise_loglikelihoods(
-    param_mod, MCMCChains.get_sections(turing_chns, :parameters)
-)
-```
-
-This can then be included in the [`from_mcmcchains`](@ref) call from above:
+We would like to compute additional useful groups to add to the [`InferenceData`](@ref).
+ArviZ includes a Turing-specific converter [`from_turing`](@ref) that, given a model, posterior samples, and data, can add the missing groups:
 
 ```@example turing
-using LinearAlgebra
-# Ensure the ordering of the loglikelihoods matches the ordering of `posterior_predictive`
-ynames = string.(keys(posterior_predictive))
-loglikelihoods_vals = getindex.(Ref(loglikelihoods), ynames)
-# Reshape into `(nchains, nsamples, size(y)...)`
-loglikelihoods_arr = permutedims(cat(loglikelihoods_vals...; dims=3), (2, 1, 3))
-
-idata = from_mcmcchains(
+idata = from_turing(
     turing_chns;
-    posterior_predictive=posterior_predictive,
-    log_likelihood=Dict("y" => loglikelihoods_arr),
-    prior=prior,
-    prior_predictive=prior_predictive,
-    observed_data=Dict("y" => y),
+    model=param_mod,
+    observed_data=Dict("y"=>y,),
+    rng=rng,
     coords=Dict("school" => schools),
     dims=Dict("y" => ["school"], "σ" => ["school"], "θ" => ["school"]),
-    library="Turing",
 )
 ```
 

From 92e8a2549d9f37728ec80279de07406d090bb6fa Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Thu, 20 May 2021 23:03:12 +0200
Subject: [PATCH 27/36] Run formatter

---
 docs/src/quickstart.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/src/quickstart.md b/docs/src/quickstart.md
index 6237313b5..3b028d18f 100644
--- a/docs/src/quickstart.md
+++ b/docs/src/quickstart.md
@@ -161,7 +161,7 @@ ArviZ includes a Turing-specific converter [`from_turing`](@ref) that, given a m
 idata = from_turing(
     turing_chns;
     model=param_mod,
-    observed_data=Dict("y"=>y,),
+    observed_data=Dict("y" => y),
     rng=rng,
     coords=Dict("school" => schools),
     dims=Dict("y" => ["school"], "σ" => ["school"], "θ" => ["school"]),

From 1581eb0f89063d38c3d8b2f4df8a4d4258c0e3ad Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 00:00:01 +0200
Subject: [PATCH 28/36] Deep copy arguments

These are apparently overwritten by  predict
---
 src/turing.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/turing.jl b/src/turing.jl
index 4457af78f..20aa8cb8b 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -155,7 +155,7 @@ end
 function _build_predictive_model(model::Turing.DynamicPPL.Model, data_keys)
     var_names = filter(in(data_keys), keys(model.args))
     return Turing.DynamicPPL.Model{var_names}(
-        model.name, model.f, model.args, model.defaults
+        model.name, model.f, deepcopy(model.args), deepcopy(model.defaults)
     )
 end
 

From b863095a01971f48128f08dc18b9d2fe39e1e3d8 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 01:07:40 +0200
Subject: [PATCH 29/36] Capture status in string

---
 docs/src/quickstart.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/src/quickstart.md b/docs/src/quickstart.md
index 3b028d18f..f452d450c 100644
--- a/docs/src/quickstart.md
+++ b/docs/src/quickstart.md
@@ -409,7 +409,7 @@ gcf()
 
 ```@example
 using Pkg
-Pkg.status()
+Text(sprint(io -> Pkg.status(io=io)))
 ```
 
 ```@example

From 13ad03a168089a8d067dede4063a87c5bad1deb0 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 10:28:37 +0200
Subject: [PATCH 30/36] Better handle adding library info

---
 src/data.jl    |  9 +++++++++
 src/dataset.jl | 23 ++++++++++++++---------
 2 files changed, 23 insertions(+), 9 deletions(-)

diff --git a/src/data.jl b/src/data.jl
index d407b1a25..0a0182fd3 100644
--- a/src/data.jl
+++ b/src/data.jl
@@ -173,12 +173,21 @@ function setattribute!(data::InferenceData, key, value)
     return data
 end
 
+function deleteattribute!(data::InferenceData, key)
+    for (_, group) in groups(data)
+        deleteattribute!(group, key)
+    end
+    return data
+end
+
 _add_library_attributes!(data, ::Nothing) = data
 function _add_library_attributes!(data, library)
     setattribute!(data, :inference_library, string(library))
     if library isa Module
         lib_version = string(PkgVersion.Version(library))
         setattribute!(data, :inference_library_version, lib_version)
+    else
+        deleteattribute!(data, :inference_library_version)
     end
     return data
 end
diff --git a/src/dataset.jl b/src/dataset.jl
index 4a22f29c1..b8cc9d212 100644
--- a/src/dataset.jl
+++ b/src/dataset.jl
@@ -69,7 +69,14 @@ end
 attributes(data::Dataset) = getproperty(PyObject(data), :_attrs)
 
 function setattribute!(data::Dataset, key, value)
-    attrs = merge(attributes(data), Dict(key => value))
+    attrs = merge(attributes(data), Dict(string(key) => value))
+    setproperty!(PyObject(data), :_attrs, attrs)
+    return attrs
+end
+
+function deleteattribute!(data::Dataset, key)
+    attrs = attributes(data)
+    delete!(attrs, string(key))
     setproperty!(PyObject(data), :_attrs, attrs)
     return attrs
 end
@@ -132,11 +139,10 @@ function convert_to_constant_dataset(
     end
 
     default_attrs = base.make_attrs()
-    if library !== nothing
-        default_attrs = merge(default_attrs, Dict("inference_library" => string(library)))
-    end
     attrs = merge(default_attrs, attrs)
-    return Dataset(; data_vars=data, coords=coords, attrs=attrs)
+    ds =  Dataset(; data_vars=data, coords=coords, attrs=attrs)
+    _add_library_attributes!(ds, library)
+    return ds
 end
 
 @doc doc"""
@@ -164,10 +170,9 @@ ArviZ.dict_to_dataset(Dict("x" => randn(4, 100), "y" => randn(4, 100)))
 dict_to_dataset
 
 function dict_to_dataset(data; library=nothing, attrs=Dict(), kwargs...)
-    if library !== nothing
-        attrs = merge(attrs, Dict("inference_library" => string(library)))
-    end
-    return arviz.dict_to_dataset(data; attrs=attrs, kwargs...)
+    ds = arviz.dict_to_dataset(data; attrs=attrs, kwargs...)
+    _add_library_attributes!(ds, library)
+    return ds
 end
 
 @doc doc"""

From a188e2769f4563e52cf2540a338b47cecabb909e Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 10:29:59 +0200
Subject: [PATCH 31/36] Run formatter

---
 docs/src/quickstart.md | 2 +-
 src/dataset.jl         | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/src/quickstart.md b/docs/src/quickstart.md
index f452d450c..abf66b38e 100644
--- a/docs/src/quickstart.md
+++ b/docs/src/quickstart.md
@@ -409,7 +409,7 @@ gcf()
 
 ```@example
 using Pkg
-Text(sprint(io -> Pkg.status(io=io)))
+Text(sprint(io -> Pkg.status(; io=io)))
 ```
 
 ```@example
diff --git a/src/dataset.jl b/src/dataset.jl
index b8cc9d212..13d1bcf47 100644
--- a/src/dataset.jl
+++ b/src/dataset.jl
@@ -140,7 +140,7 @@ function convert_to_constant_dataset(
 
     default_attrs = base.make_attrs()
     attrs = merge(default_attrs, attrs)
-    ds =  Dataset(; data_vars=data, coords=coords, attrs=attrs)
+    ds = Dataset(; data_vars=data, coords=coords, attrs=attrs)
     _add_library_attributes!(ds, library)
     return ds
 end

From ee474aee9599164fe98e6b9002b1d9f0333d1265 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 12:46:59 +0200
Subject: [PATCH 32/36] Add attribute and library tests

---
 test/test_data.jl    | 29 +++++++++++++++++++++++++++++
 test/test_dataset.jl | 16 ++++++++++++++++
 2 files changed, 45 insertions(+)

diff --git a/test/test_data.jl b/test/test_data.jl
index 84ba5d652..ed3af32df 100644
--- a/test/test_data.jl
+++ b/test/test_data.jl
@@ -32,6 +32,17 @@ using MonteCarloMeasurements: Particles
         @test :posterior in keys(g)
     end
 
+    @testset "attributes" begin
+        ArviZ.setattribute!(data, "tmp", 3)
+        for (_, group) in ArviZ.groups(data)
+            @test Pair("tmp", 3) ∈ ArviZ.attributes(group)
+        end
+        ArviZ.deleteattribute!(data, "tmp")
+        for (_, group) in ArviZ.groups(data)
+            @test "tmp" ∉ keys(ArviZ.attributes(group))
+        end
+    end
+
     @testset "isempty" begin
         @test !isempty(data)
         @test isempty(InferenceData())
@@ -67,6 +78,24 @@ using MonteCarloMeasurements: Particles
     end
 end
 
+@testset "add library attributes" begin
+    idata = load_arviz_data("centered_eight")
+    ArviZ.deleteattribute!(idata, :inference_library)
+    ArviZ.setattribute!(idata, :inference_library_version, "3.0.0")
+    @test ArviZ._add_library_attributes!(idata, nothing) === idata
+    ArviZ._add_library_attributes!(idata, "MyLib")
+    for (_, group) in ArviZ.groups(idata)
+        @test Pair("inference_library", "MyLib") ∈ ArviZ.attributes(group)
+        @test "inference_library_version" ∉ keys(ArviZ.attributes(group))
+    end
+    ArviZ._add_library_attributes!(idata, ArviZ)
+    arviz_version = string(ArviZ.PkgVersion.Version(ArviZ))
+    for (_, group) in ArviZ.groups(idata)
+        @test Pair("inference_library", "ArviZ") ∈ ArviZ.attributes(group)
+        @test Pair("inference_library_version", arviz_version) ∈ ArviZ.attributes(group)
+    end
+end
+
 @testset "+(::InferenceData, ::InferenceData)" begin
     rng = MersenneTwister(42)
     idata1 = from_dict(;
diff --git a/test/test_dataset.jl b/test/test_dataset.jl
index eb5920093..f57d9e4ad 100644
--- a/test/test_dataset.jl
+++ b/test/test_dataset.jl
@@ -47,6 +47,22 @@
         @test convert(ArviZ.Dataset, [1.0, 2.0, 3.0, 4.0]) isa ArviZ.Dataset
     end
 
+    @testset "attributes" begin
+        attrs = dataset.attrs
+        attrs2 = ArviZ.attributes(dataset)
+        @test attrs == attrs2
+        ArviZ.setattribute!(dataset, "tmp1", 3)
+        ArviZ.setattribute!(dataset, :tmp2, 4)
+        attrs3 = ArviZ.attributes(dataset)
+        @test Pair("tmp1", 3) ∈ attrs3
+        @test Pair("tmp2", 4) ∈ attrs3
+        ArviZ.deleteattribute!(dataset, :tmp1)
+        ArviZ.deleteattribute!(dataset, "tmp2")
+        attrs4 = ArviZ.attributes(dataset)
+        @test "tmp1" ∉ keys(attrs4)
+        @test "tmp2" ∉ keys(attrs4)
+    end
+
     @testset "show(::ArviZ.Dataset)" begin
         @testset "$mimetype" for mimetype in ("plain", "html")
             text = repr(MIME("text/$(mimetype)"), dataset)

From 5ee652af8644b450392354d3a738f9db20e035bd Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 23:49:20 +0200
Subject: [PATCH 33/36] Extract observed_data from model

---
 src/turing.jl       | 41 ++++++++++++++++++++++++++++++++---------
 test/test_turing.jl | 20 ++++++++++----------
 2 files changed, 42 insertions(+), 19 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index 20aa8cb8b..c949ab97b 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -96,18 +96,21 @@ function from_turing(
         groups[:prior] = _sample_prior(rng, model, nchains, ndraws)
     end
 
-    if groups[:observed_data] === nothing
-        return from_mcmcchains(chns; groups..., kwargs...)
+    if :observed_data ∈ groups_to_generate
+        groups[:observed_data] = _get_observed_data(
+            model, chns isa Turing.MCMCChains.Chains ? chns : groups[:prior]
+        )
     end
 
     observed_data = groups[:observed_data]
-    observed_data_keys = Set(
-        observed_data isa Dict ? Symbol.(keys(observed_data)) : propertynames(observed_data)
-    )
+    if observed_data === nothing
+        return from_mcmcchains(chns; groups..., kwargs...)
+    end
+    observed_data_keys = Set(Symbol.(keys(observed_data)))
 
     if :constant_data in groups_to_generate
         groups[:constant_data] = Dict(
-            filter(p -> first(p) ∉ observed_data_keys, pairs(model.args))
+            filter(∉(observed_data_keys) ∘ first, pairs(model.args))
         )
     end
 
@@ -117,7 +120,7 @@ function from_turing(
                 rng, model, groups[:prior], observed_data_keys
             )
         elseif groups[:prior] !== nothing
-            @warn "Could not generate group :prior_predictive because group :prior was not an MCMCChains.Chains."
+            @warn "Could not generate group :prior_predictive because group :prior is not an MCMCChains.Chains."
         end
     end
 
@@ -127,7 +130,7 @@ function from_turing(
                 rng, model, chns, observed_data_keys
             )
         elseif chns !== nothing
-            @warn "Could not generate group :posterior_predictive because group :posterior was not an MCMCChains.Chains."
+            @warn "Could not generate group :posterior_predictive because group :posterior is not an MCMCChains.Chains."
         end
     end
 
@@ -135,7 +138,7 @@ function from_turing(
         if chns isa Turing.MCMCChains.Chains
             groups[:log_likelihood] = _compute_log_likelihood(model, chns)
         elseif chns !== nothing
-            @warn "Could not generate log_likelihood because posterior must be an MCMCChains.Chains."
+            @warn "Could not generate group :log_likelihood because group :posterior is not an MCMCChains.Chains."
         end
     end
 
@@ -178,3 +181,23 @@ function _compute_log_likelihood(
     loglikelihoods_arr = permutedims(cat(loglikelihoods_vals...; dims=3), (1, 3, 2))
     return Turing.MCMCChains.Chains(loglikelihoods_arr, pred_names)
 end
+
+function _get_observed_data(model::Turing.DynamicPPL.Model, chns)
+    # use likelihood to find nmes of data variables
+    if chns isa Turing.MCMCChains.Chains
+        chns_small = chns[1, :, 1]
+    else
+        chns_small = _sample_prior(Random.MersenneTwister(0), model, 1, 1)
+    end
+    log_like = _compute_log_likelihood(model, chns_small)
+    obs_data_keys = keys(Turing.MCMCChains.get_params(log_like))
+    # get values of data variables stored in model
+    args = model.args
+    args_obs_data_keys = filter(in(keys(args)), obs_data_keys)
+    if args_obs_data_keys != obs_data_keys
+        @warn "Failed to extract group :observed_data from model. Expected keys " *
+              "$(obs_data_keys) but only found keys $(keys(obs_data)) in model arguments."
+        return nothing
+    end
+    return NamedTuple{args_obs_data_keys}(getproperty.(Ref(args), args_obs_data_keys))
+end
diff --git a/test/test_turing.jl b/test/test_turing.jl
index a61ebb774..6f0b6ffb6 100644
--- a/test/test_turing.jl
+++ b/test/test_turing.jl
@@ -5,7 +5,7 @@ using Test
 using Random
 
 @testset "from_turing" begin
-    nchains = 4
+    nchains = 2
     ndraws = 10
     Turing.@model function demo(xs, y, n=length(xs))
         s ~ InverseGamma(2, 3)
@@ -22,14 +22,14 @@ using Random
     chn = Turing.sample(
         model, Turing.MH(), Turing.MCMCThreads(), ndraws, nchains; progress=false
     )
-    @test size(chn) == (10, 3, 4)
+    @test size(chn) == (ndraws, 3, nchains)
 
     idata1 = from_turing(chn)
     @test sort(groupnames(idata1)) == [:posterior, :sample_stats]
     @test idata1.posterior.inference_library == "Turing"
     VersionNumber(idata1.posterior.inference_library_version)
 
-    idata2 = from_turing(; model=model)
+    idata2 = from_turing(; model=model, observed_data=false)
     @test sort(groupnames(idata2)) == [:prior, :sample_stats_prior]
     @test length(idata2.prior.chain.values) == 1
     @test length(idata2.prior.draw.values) == 1_000
@@ -42,15 +42,12 @@ using Random
     @test length(idata3.prior.chain.values) == nchains
     @test length(idata3.prior.draw.values) == ndraws
 
-    idata4 = from_turing(chn; model=model, prior=false)
+    idata4 = from_turing(chn; model=model, prior=false, observed_data=false)
     @test sort(groupnames(idata4)) == [:posterior, :sample_stats]
 
-    idata5 = from_turing(
-        chn; model=model, observed_data=observed_data, nchains=3, ndraws=100
-    )
+    idata5 = from_turing(chn; model=model, nchains=3, ndraws=100)
     @test idata5.posterior.inference_library == "Turing"
     VersionNumber(idata5.posterior.inference_library_version)
-
     @test sort(groupnames(idata5)) == sort([
         :posterior,
         :posterior_predictive,
@@ -64,11 +61,14 @@ using Random
     ])
     @test length(idata5.prior.chain.values) == 3
     @test length(idata5.prior.draw.values) == 100
+    @test idata5.observed_data.xs.values == xs
+    @test only(idata5.observed_data.y.values) == y
+    @test only(idata5.constant_data.n.values) == 5
 
     rng1 = Random.MersenneTwister(42)
-    idata6 = from_turing(chn; model=model, observed_data=observed_data, rng=rng1)
+    idata6 = from_turing(chn; model=model, rng=rng1)
     rng2 = Random.MersenneTwister(42)
-    idata7 = from_turing(chn; model=model, observed_data=observed_data, rng=rng2)
+    idata7 = from_turing(chn; model=model, rng=rng2)
     @testset for name in groupnames(idata6)
         group1 = getproperty(idata6, name)
         group2 = getproperty(idata7, name)

From 09c37da7be947b0d23f3dcc89b142493eca22892 Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Fri, 21 May 2021 23:52:36 +0200
Subject: [PATCH 34/36] Update example

---
 src/turing.jl | 17 +++++++----------
 1 file changed, 7 insertions(+), 10 deletions(-)

diff --git a/src/turing.jl b/src/turing.jl
index c949ab97b..c296887d1 100644
--- a/src/turing.jl
+++ b/src/turing.jl
@@ -5,10 +5,9 @@ Convert data from Turing into an [`InferenceData`](@ref).
 
 This permits passing a Turing `Model` and a random number generator to
 `model` and `rng` keywords to automatically generate groups. By default,
-if `posterior`, `observed_data`, and `model` are provided, then the 
-`prior`, `prior_predictive`, `posterior_predictive`, and `log_likelihood`
-groups are automatically generated. To avoid generating a group, provide
-group data or set it to `false`.
+if `posterior` and `model` are provided, then all remaining groups are
+automatically generated. To avoid generating a group, provide group data
+or set it to `false`.
 
 # Arguments
 
@@ -17,7 +16,7 @@ group data or set it to `false`.
 # Keywords
 
 - `model::Turing.DynamicPPL.Model`: A Turing model conditioned on observed and
-     constant data. `constant_data` must be provided for the model to be used.
+     constant data.
 - `rng::AbstractRNG=Random.default_rng()`: a random number generator used for
      sampling from the prior, posterior predictive and prior predictive
      distributions.
@@ -43,13 +42,11 @@ julia> @model function demo(xs, y, n=length(xs))
            y ~ Normal(m, √s)
        end;
 
-julia> observed_data = (xs=[0.87, 0.08, 0.53], y=-0.85);
+julia> model = demo(randn(3), randn());
 
-julia> model = demo(observed_data...);
+julia> chn = sample(rng, model, MH(), 100; progress=false);
 
-julia> chn = sample(rng, model, MH(), 1_000; progress=false);
-
-julia> from_turing(chn; model=model, rng=rng, observed_data=observed_data, prior=false)
+julia> idata = from_turing(chn; model=model, rng=rng, prior=false)
 InferenceData with groups:
 	> posterior
 	> posterior_predictive

From a05bfd230f1bf7b32ad2d733529f23c751ad5a8a Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Sat, 22 May 2021 00:43:58 +0200
Subject: [PATCH 35/36] Update quickstart

---
 docs/src/quickstart.md | 1 -
 1 file changed, 1 deletion(-)

diff --git a/docs/src/quickstart.md b/docs/src/quickstart.md
index abf66b38e..045d362b7 100644
--- a/docs/src/quickstart.md
+++ b/docs/src/quickstart.md
@@ -161,7 +161,6 @@ ArviZ includes a Turing-specific converter [`from_turing`](@ref) that, given a m
 idata = from_turing(
     turing_chns;
     model=param_mod,
-    observed_data=Dict("y" => y),
     rng=rng,
     coords=Dict("school" => schools),
     dims=Dict("y" => ["school"], "σ" => ["school"], "θ" => ["school"]),

From bf474a11597432d9dadb5c495386d520122c1eea Mon Sep 17 00:00:00 2001
From: Seth Axen <seth.axen@gmail.com>
Date: Sat, 22 May 2021 12:57:33 +0200
Subject: [PATCH 36/36] Fix test

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

diff --git a/test/test_turing.jl b/test/test_turing.jl
index 6f0b6ffb6..444f84192 100644
--- a/test/test_turing.jl
+++ b/test/test_turing.jl
@@ -36,7 +36,7 @@ using Random
     @test idata2.prior.inference_library == "Turing"
     VersionNumber(idata2.prior.inference_library_version)
 
-    idata3 = from_turing(chn; model=model)
+    idata3 = from_turing(chn; model=model, observed_data=false)
     @test sort(groupnames(idata3)) ==
           sort([:posterior, :sample_stats, :prior, :sample_stats_prior])
     @test length(idata3.prior.chain.values) == nchains