CompatHelper: bump compat for PosteriorStats in [weakdeps] to 0.4, (keep existing compat) (#102)

* CompatHelper: bump compat for PosteriorStats in [weakdeps] to 0.4, (keep existing compat)

* Remove imports and exports

Not used in extensions

* Only overload and test waic if defined

* Increment patch version

* Update r2_score docstring

* Update summarize doctest

---------

Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: Seth Axen <[email protected]>

Author: 3 people

Project.toml

@@ -1,7 +1,7 @@
 name = "InferenceObjects"
 uuid = "b5cf5a8d-e756-4ee3-b014-01d49d192c00"
 authors = ["Seth Axen <[email protected]> and contributors"]
-version = "0.4.13"
+version = "0.4.14"
 
 [deps]
 ANSIColoredPrinters = "a4c015fc-c6ff-483c-b24f-f7ea428134e9"
@@ -32,7 +32,7 @@ MLJBase = "1"
 NCDatasets = "0.12.6, 0.13, 0.14"
 OffsetArrays = "1"
 OrderedCollections = "1.6"
-PosteriorStats = "0.3"
+PosteriorStats = "0.3, 0.4"
 Random = "1"
 StatsBase = "0.33.7, 0.34"
 Tables = "1.11.0"

ext/InferenceObjectsPosteriorStatsExt/InferenceObjectsPosteriorStatsExt.jl

@@ -6,17 +6,16 @@ using InferenceObjects: InferenceObjects
 using PosteriorStats: PosteriorStats
 using StatsBase: StatsBase
 
-import PosteriorStats: eti, hdi, loo, loo_pit, r2_score, summarize, waic
 import StatsBase: summarystats
 
-export eti, hdi, loo, loo_pit, r2_score, summarize, waic, summarystats
-
 maplayers = isdefined(DimensionalData, :maplayers) ? DimensionalData.maplayers : map
 
 include("utils.jl")
 include("ci.jl")
 include("loo.jl")
-include("waic.jl")
+@static if isdefined(PosteriorStats, :waic)
+    include("waic.jl")
+end
 include("loo_pit.jl")
 include("r2_score.jl")
 include("summarize.jl")

ext/InferenceObjectsPosteriorStatsExt/ci.jl

@@ -1,16 +1,16 @@
 
 for (ci_fun, ci_desc) in
     (:eti => "equal-tailed interval (ETI)", :hdi => "highest density interval (HDI)")
+    ci_name = string(ci_fun)
     @eval begin
-        # this pattern ensures that the type is completely specified at compile time
         @doc """
-            $($ci_fun)(data::InferenceData; kwargs...) -> Dataset
-            $($ci_fun)(data::Dataset; kwargs...) -> Dataset
+            $($ci_name)(data::InferenceData; kwargs...) -> Dataset
+            $($ci_name)(data::Dataset; kwargs...) -> Dataset
 
         Calculate the $($ci_desc) for each parameter in the data.
 
         For more details and a description of the `kwargs`, see
-        [`PosteriorStats.$($ci_fun)`](@extref).
+        [`PosteriorStats.$($ci_name)`](@extref).
         """
         function PosteriorStats.$(ci_fun)(data::InferenceObjects.InferenceData; kwargs...)
             return PosteriorStats.$(ci_fun)(data.posterior; kwargs...)

ext/InferenceObjectsPosteriorStatsExt/r2_score.jl

@@ -1,5 +1,5 @@
 @doc """
-    r2_score(idata::InferenceData; y_name, y_pred_name) -> (; r2, r2_std)
+    r2_score(idata::InferenceData; y_name, y_pred_name, kwargs...) -> (; r2, <ci>)
 
 Compute ``R²`` from `idata`, automatically formatting the predictions to the correct shape.
 
@@ -9,8 +9,8 @@ Compute ``R²`` from `idata`, automatically formatting the predictions to the co
     the only observed data variable is used.
   - `y_pred_name`: Name of posterior predictive variable in `idata.posterior_predictive`.
     If not provided, then `y_name` is used.
-
-See [`PosteriorStats.r2_score`](@extref) for more details.
+  - `kwargs...`: Additional keyword arguments to pass to
+    [`PosteriorStats.r2_score`](@extref).
 
 # Examples
 
@@ -19,10 +19,8 @@ julia> using ArviZExampleData, PosteriorStats
 
 julia> idata = load_example_data("regression10d");
 
-julia> r2_score(idata) |> pairs
-pairs(::NamedTuple) with 2 entries:
-  :r2     => 0.998385
-  :r2_std => 0.000100621
+julia> r2_score(idata)
+(r2 = 0.998384805658226, eti = 0.9982167674001565 .. 0.9985401916739318)
 ```
 """
 function PosteriorStats.r2_score(

ext/InferenceObjectsPosteriorStatsExt/summarize.jl

@@ -33,17 +33,17 @@ julia> data = load_example_data("centered_eight");
 
 julia> summarize(data)
 SummaryStats
-                          mean  std  eti94          ess_tail  ess_bulk  rhat  mcse_mean  mcse_std
- mu                        4.2  3.3  -2.11 .. 9.90       622       241  1.03       0.21     0.088
- theta[Choate]             6.4  5.9  -3.05 .. 19.1       937       572  1.01       0.25     0.20
- theta[Deerfield]          5.0  4.9  -4.49 .. 14.2      1214       532  1.01       0.21     0.15
- theta[Phillips Andover]   3.4  5.4  -8.17 .. 12.7      1017       511  1.01       0.23     0.17
- theta[Phillips Exeter]    4.8  5.2  -4.84 .. 14.5       911       572  1.01       0.21     0.21
- theta[Hotchkiss]          3.5  4.8  -6.11 .. 12.0       789       347  1.02       0.25     0.15
- theta[Lawrenceville]      3.7  5.2  -6.62 .. 12.6       957       506  1.01       0.22     0.21
- theta[St. Paul's]         6.5  5.2  -2.38 .. 18.3      1031       528  1.01       0.22     0.15
- theta[Mt. Hermon]         4.8  5.7  -5.52 .. 16.0      1045       538  1.01       0.24     0.23
- tau                       4.3  3.0   1.06 .. 11.5       214       128  1.03       0.22     0.14
+                          mean  std  eti89          ess_tail  ess_bulk  rhat  mcse_mean  mcse_std
+ mu                        4.2  3.3  -1.15 .. 9.15       622       241  1.03       0.21     0.088
+ theta[Choate]             6.4  5.9  -1.72 .. 16.6       937       572  1.01       0.25     0.20
+ theta[Deerfield]          5.0  4.9  -3.03 .. 12.4      1214       532  1.01       0.21     0.15
+ theta[Phillips Andover]   3.4  5.4  -5.69 .. 11.3      1017       511  1.01       0.23     0.17
+ theta[Phillips Exeter]    4.8  5.2  -3.08 .. 12.7       911       572  1.01       0.21     0.21
+ theta[Hotchkiss]          3.5  4.8  -4.29 .. 10.6       789       347  1.02       0.25     0.15
+ theta[Lawrenceville]      3.7  5.2  -4.41 .. 11.4       957       506  1.01       0.22     0.21
+ theta[St. Paul's]         6.5  5.2  -1.05 .. 15.8      1031       528  1.01       0.22     0.15
+ theta[Mt. Hermon]         4.8  5.7  -3.78 .. 13.9      1045       538  1.01       0.24     0.23
+ tau                       4.3  3.0   1.27 .. 9.95       214       128  1.03       0.22     0.14
 ```
 
 Compute the mean, standard deviation, median, and median absolute deviation of the `theta`

test/posteriorstats.jl

@@ -172,7 +172,7 @@ _as_array(x::AbstractArray) = x
         end
     end
 
-    @testset "waic" begin
+    isdefined(PosteriorStats, :waic) && @testset "waic" begin
         @testset for sz in ((1000, 4), (1000, 4, 2), (100, 4, 2, 3))
             atol_perm = cbrt(eps())