renamed returned_quantities to returned as requested

docs/src/api.md

@@ -130,10 +130,10 @@ It is possible to manually increase (or decrease) the accumulated log density fr
 @addlogprob!
 ```
 
-Return values of the model function for a collection of samples can be obtained with [`returned_quantities`](@ref).
+Return values of the model function for a collection of samples can be obtained with [`returned(model, chain)`](@ref).
 
 ```@docs
-returned_quantities
+returned(model, chain)
 ```
 
 For a chain of samples, one can compute the pointwise log-likelihoods of each observed random variable with [`pointwise_loglikelihoods`](@ref). Similarly, the log-densities of the priors using

ext/DynamicPPLMCMCChainsExt.jl

@@ -43,7 +43,7 @@ function DynamicPPL.varnames(c::MCMCChains.Chains)
 end
 
 """
-    returned_quantities(model::Model, chain::MCMCChains.Chains)
+    returned(model::Model, chain::MCMCChains.Chains)
 
 Execute `model` for each of the samples in `chain` and return an array of the values
 returned by the `model` for each sample.
@@ -63,7 +63,7 @@ m = demo(data)
 chain = sample(m, alg, n)
 # To inspect the `interesting_quantity(θ, x)` where `θ` is replaced by samples
 # from the posterior/`chain`:
-returned_quantities(m, chain) # <= results in a `Vector` of returned values
+returned(m, chain) # <= results in a `Vector` of returned values
                                #    from `interesting_quantity(θ, x)`
 ```
 ## Concrete (and simple)
@@ -87,7 +87,7 @@ julia> model = demo(randn(10));
 
 julia> chain = sample(model, MH(), 10);
 
-julia> DynamicPPL.returned_quantities(model, chain)
+julia> returned(model, chain)
 10×1 Array{Tuple{Float64},2}:
  (2.1964758025119338,)
  (2.1964758025119338,)
@@ -101,7 +101,7 @@ julia> DynamicPPL.returned_quantities(model, chain)
  (-0.16489786710222099,)
 ```
 """
-function DynamicPPL.returned_quantities(
+function DynamicPPL.returned(
     model::DynamicPPL.Model, chain_full::MCMCChains.Chains
 )
     chain = MCMCChains.get_sections(chain_full, :parameters)

src/DynamicPPL.jl

@@ -122,7 +122,7 @@ export AbstractVarInfo,
     fix,
     unfix,
     prefix,
-    returned_quantities,
+    returned,
     # Convenience macros
     @addlogprob!,
     @submodel,
@@ -132,7 +132,8 @@ export AbstractVarInfo,
     to_sampleable,
     # Deprecated.
     @logprob_str,
-    @prob_str
+    @prob_str,
+    generated_quantities
 
 # Reexport
 using Distributions: loglikelihood

src/deprecated.jl

@@ -1 +1 @@
-@deprecate generated_quantities returned_quantities
+@deprecate generated_quantities(model, params) returned(model, params)

src/model.jl

@@ -1206,9 +1206,9 @@ function Distributions.loglikelihood(model::Model, chain::AbstractMCMC.AbstractC
 end
 
 """
-    returned_quantities(model::Model, parameters::NamedTuple)
-    returned_quantities(model::Model, values, keys)
-    returned_quantities(model::Model, values, keys)
+    returned(model::Model, parameters::NamedTuple)
+    returned(model::Model, values, keys)
+    returned(model::Model, values, keys)
 
 Execute `model` with variables `keys` set to `values` and return the values returned by the `model`.
 
@@ -1218,7 +1218,7 @@ If a `NamedTuple` is given, `keys=keys(parameters)` and `values=values(parameter
 ```jldoctest
 julia> using DynamicPPL, Distributions
 
-julia> using DynamicPPL: returned_quantities
+julia> using DynamicPPL: returned
 
 julia> @model function demo(xs)
            s ~ InverseGamma(2, 3)
@@ -1235,18 +1235,18 @@ julia> model = demo(randn(10));
 
 julia> parameters = (; s = 1.0, m_shifted=10.0);
 
-julia> returned_quantities(model, parameters)
+julia> returned(model, parameters)
 (0.0,)
 
-julia> returned_quantities(model, values(parameters), keys(parameters))
+julia> returned(model, values(parameters), keys(parameters))
 (0.0,)
 ```
 """
-function returned_quantities(model::Model, parameters::NamedTuple)
+function returned(model::Model, parameters::NamedTuple)
     fixed_model = fix(model, parameters)
     return fixed_model()
 end
 
-function returned_quantities(model::Model, values, keys)
-    return returned_quantities(model, NamedTuple{keys}(values))
+function returned(model::Model, values, keys)
+    return returned(model, NamedTuple{keys}(values))
 end

src/submodel_macro.jl

@@ -224,7 +224,7 @@ function prefix_submodel_context(prefix::Bool, ctx)
     return ctx
 end
 
-const SUBMODEL_DEPWARN_MSG = "`@submodel model` and `@submodel prefix=... model` are deprecated, use `left ~ to_sampleable(model)` and `left ~ to_sampleable(prefix(model, ...))`, respectively, instead."
+const SUBMODEL_DEPWARN_MSG = "`@submodel model` and `@submodel prefix=... model` are deprecated, use `left ~ to_sampleable(returned(model))` and `left ~ to_sampleable(returned(prefix(model, ...)))`, respectively, instead."
 
 function submodel(prefix_expr, expr, ctx=esc(:__context__))
     prefix_left, prefix = getargs_assignment(prefix_expr)