CompatHelper: bump compat for DimensionalData to 0.26, (keep existing compat) (#76)

* CompatHelper: bump compat for DimensionalData to 0.26, (keep existing compat)

* Use correct combinedims syntax

* Update docstrings with DimData v0.26 style

* Improve type inference of r2_score

* Increment patch number

* Fix stack overflow on Julia v1.6

---------

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 = "0.3.15"
+version = "0.3.16"
 
 [deps]
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
@@ -27,7 +27,7 @@ InferenceObjectsPosteriorStatsExt = ["PosteriorStats", "StatsBase"]
 ArviZExampleData = "0.1"
 Compat = "3.46.0, 4.2.0"
 Dates = "1.6"
-DimensionalData = "0.24, 0.25"
+DimensionalData = "0.24, 0.25, 0.26"
 EvoTrees = "0.16"
 MCMCDiagnosticTools = "0.3.4"
 MLJBase = "1"

ext/InferenceObjectsMCMCDiagnosticToolsExt/utils.jl

@@ -2,7 +2,7 @@
 function _params_array(data)
     sample_dims = Dimensions.dims(data, InferenceObjects.DEFAULT_SAMPLE_DIMS)
     param_dims = Dimensions.otherdims(data, sample_dims)
-    dims_combined = Dimensions.combinedims(sample_dims, param_dims)
+    dims_combined = Dimensions.combinedims((sample_dims..., param_dims...))
     Dimensions.dimsmatch(Dimensions.dims(data), dims_combined) && return data
     return PermutedDimsArray(data, dims_combined)
 end

ext/InferenceObjectsPosteriorStatsExt/hdi.jl

@@ -1,7 +1,9 @@
 # this pattern ensures that the type is completely specified at compile time
-const HDI_BOUND_DIM = Dimensions.format(
-    Dimensions.Dim{:hdi_bound}([:lower, :upper]), Base.OneTo(2)
-)
+const HDI_BOUND_DIM = let
+    dims = Dimensions.format(Dimensions.Dim{:hdi_bound}([:lower, :upper]), Base.OneTo(2))
+    # some versions of DimensionalData return a tuple here, others return a Dim
+    dims isa Tuple ? only(dims) : dims
+end
 
 @doc """
     hdi(data::InferenceData; kwargs...) -> Dataset
@@ -19,9 +21,9 @@ function PosteriorStats.hdi(data::InferenceObjects.Dataset; kwargs...)
         lower, upper = map(Base.Fix2(_as_dimarray, x), r)
         return cat(lower, upper; dims=HDI_BOUND_DIM)
     end
-    dims = Dimensions.combinedims(
-        Dimensions.otherdims(data, InferenceObjects.DEFAULT_SAMPLE_DIMS), HDI_BOUND_DIM
-    )
+    dims = Dimensions.combinedims((
+        Dimensions.otherdims(data, InferenceObjects.DEFAULT_SAMPLE_DIMS)..., HDI_BOUND_DIM
+    ))
     return DimensionalData.rebuild(
         data;
         data=map(parent, results),

ext/InferenceObjectsPosteriorStatsExt/loo_pit.jl

@@ -23,8 +23,11 @@ julia> idata = load_example_data("centered_eight");
 julia> loo_result = loo(idata; var_name=:obs);
 
 julia> loo_pit(idata, loo_result.psis_result.log_weights; y_name=:obs)
-8-element DimArray{Float64,1} loo_pit_obs with dimensions:
-  Dim{:school} Categorical{String} String[Choate, Deerfield, …, St. Paul's, Mt. Hermon] Unordered
+╭───────────────────────────────────────────╮
+│ 8-element DimArray{Float64,1} loo_pit_obs │
+├───────────────────────────────────────────┴──────────────────────────── dims ┐
+  ↓ school Categorical{String} [Choate, Deerfield, …, St. Paul's, Mt. Hermon] Unordered
+└──────────────────────────────────────────────────────────────────────────────┘
  "Choate"            0.943511
  "Deerfield"         0.63797
  "Phillips Andover"  0.316697
@@ -78,8 +81,11 @@ julia> using ArviZExampleData, PosteriorStats
 julia> idata = load_example_data("centered_eight");
 
 julia> loo_pit(idata; y_name=:obs)
-8-element DimArray{Float64,1} loo_pit_obs with dimensions:
-  Dim{:school} Categorical{String} String[Choate, Deerfield, …, St. Paul's, Mt. Hermon] Unordered
+╭───────────────────────────────────────────╮
+│ 8-element DimArray{Float64,1} loo_pit_obs │
+├───────────────────────────────────────────┴──────────────────────────── dims ┐
+  ↓ school Categorical{String} [Choate, Deerfield, …, St. Paul's, Mt. Hermon] Unordered
+└──────────────────────────────────────────────────────────────────────────────┘
  "Choate"            0.943511
  "Deerfield"         0.63797
  "Phillips Andover"  0.316697

ext/InferenceObjectsPosteriorStatsExt/r2_score.jl

@@ -29,5 +29,9 @@ function PosteriorStats.r2_score(
     y_pred_name::Union{Symbol,Nothing}=nothing,
 )
     (_, y), (_, y_pred) = observations_and_predictions(idata, y_name, y_pred_name)
-    return PosteriorStats.r2_score(y, _draw_chains_params_array(y_pred))
+    y_data = y isa DimensionalData.AbstractDimArray ? parent(y) : y
+    y_data, y_pred_data = map((y, _draw_chains_params_array(y_pred))) do arr
+        return arr isa DimensionalData.AbstractDimArray ? parent(arr) : arr
+    end
+    return PosteriorStats.r2_score(y_data, y_pred_data)
 end

ext/InferenceObjectsPosteriorStatsExt/utils.jl

@@ -167,7 +167,7 @@ end
 function _draw_chains_params_array(x::DimensionalData.AbstractDimArray)
     sample_dims = Dimensions.dims(x, InferenceObjects.DEFAULT_SAMPLE_DIMS)
     param_dims = Dimensions.otherdims(x, sample_dims)
-    dims_combined = Dimensions.combinedims(sample_dims, param_dims)
+    dims_combined = Dimensions.combinedims((sample_dims..., param_dims...))
     Dimensions.dimsmatch(Dimensions.dims(x), dims_combined) && return x
     return PermutedDimsArray(x, dims_combined)
 end

src/inference_data.jl

@@ -300,16 +300,18 @@ InferenceData with groups:
   > posterior
 
 julia> idata_cat1.posterior
-Dataset with dimensions:
-  Dim{:draw},
-  Dim{:chain},
-  Dim{:a_dim} Categorical{String} String["x", "y", "z"] ForwardOrdered
-and 2 layers:
-  :a Float64 dims: Dim{:draw}, Dim{:chain}, Dim{:a_dim} (100×8×3)
-  :b Float64 dims: Dim{:draw}, Dim{:chain} (100×8)
-
-with metadata Dict{String, Any} with 1 entry:
-  "created_at" => "2023-04-03T18:41:35.779"
+╭─────────────────╮
+│ 100×8×3 Dataset │
+├─────────────────┴──────────────────────────────────── dims ┐
+  ↓ draw ,
+  → chain,
+  ↗ a_dim Categorical{String} ["x", "y", "z"] ForwardOrdered
+├──────────────────────────────────────────────────── layers ┤
+  :a eltype: Float64 dims: draw, chain, a_dim size: 100×8×3
+  :b eltype: Float64 dims: draw, chain size: 100×8
+├────────────────────────────────────────────────── metadata ┤
+  Dict{String, Any} with 1 entry:
+  "created_at" => "2024-03-11T14:10:48.434"
 ```
 
 Alternatively, we can concatenate along a new `run` dimension, which will be created.
@@ -320,17 +322,19 @@ InferenceData with groups:
   > posterior
 
 julia> idata_cat2.posterior
-Dataset with dimensions:
-  Dim{:draw},
-  Dim{:chain},
-  Dim{:a_dim} Categorical{String} String["x", "y", "z"] ForwardOrdered,
-  Dim{:run}
-and 2 layers:
-  :a Float64 dims: Dim{:draw}, Dim{:chain}, Dim{:a_dim}, Dim{:run} (100×4×3×2)
-  :b Float64 dims: Dim{:draw}, Dim{:chain}, Dim{:run} (100×4×2)
-
-with metadata Dict{String, Any} with 1 entry:
-  "created_at" => "2023-04-03T18:41:35.779"
+╭───────────────────╮
+│ 100×4×3×2 Dataset │
+├───────────────────┴─────────────────────────────────── dims ┐
+  ↓ draw ,
+  → chain,
+  ↗ a_dim Categorical{String} ["x", "y", "z"] ForwardOrdered,
+  ⬔ run
+├─────────────────────────────────────────────────────────────┴ layers ┐
+  :a eltype: Float64 dims: draw, chain, a_dim, run size: 100×4×3×2
+  :b eltype: Float64 dims: draw, chain, run size: 100×4×2
+├──────────────────────────────────────────────────────────── metadata ┤
+  Dict{String, Any} with 1 entry:
+  "created_at" => "2024-03-11T14:10:48.434"
 ```
 
 We can also concatenate only a subset of groups and merge the rest, which is useful when
@@ -351,25 +355,30 @@ InferenceData with groups:
   > observed_data
 
 julia> idata_cat3.posterior
-Dataset with dimensions:
-  Dim{:draw},
-  Dim{:chain},
-  Dim{:a_dim} Categorical{String} String["x", "y", "z"] ForwardOrdered,
-  Dim{:run}
-and 2 layers:
-  :a Float64 dims: Dim{:draw}, Dim{:chain}, Dim{:a_dim}, Dim{:run} (100×4×3×2)
-  :b Float64 dims: Dim{:draw}, Dim{:chain}, Dim{:run} (100×4×2)
-
-with metadata Dict{String, Any} with 1 entry:
-  "created_at" => "2023-04-03T18:41:35.779"
+╭───────────────────╮
+│ 100×4×3×2 Dataset │
+├───────────────────┴─────────────────────────────────── dims ┐
+  ↓ draw ,
+  → chain,
+  ↗ a_dim Categorical{String} ["x", "y", "z"] ForwardOrdered,
+  ⬔ run
+├─────────────────────────────────────────────────────────────┴ layers ┐
+  :a eltype: Float64 dims: draw, chain, a_dim, run size: 100×4×3×2
+  :b eltype: Float64 dims: draw, chain, run size: 100×4×2
+├──────────────────────────────────────────────────────────── metadata ┤
+  Dict{String, Any} with 1 entry:
+  "created_at" => "2024-03-11T14:10:48.434"
 
 julia> idata_cat3.observed_data
-Dataset with dimensions: Dim{:y_dim_1}
-and 1 layer:
-  :y Float64 dims: Dim{:y_dim_1} (10)
-
-with metadata Dict{String, Any} with 1 entry:
-  "created_at" => "2023-02-17T15:11:00.59"
+╭────────────────────╮
+│ 10-element Dataset │
+├────────────── dims ┤
+  ↓ y_dim_1
+├────────────────────┴─────────────── layers ┐
+  :y eltype: Float64 dims: y_dim_1 size: 10
+├────────────────────────────────────────────┴ metadata ┐
+  Dict{String, Any} with 1 entry:
+  "created_at" => "2024-03-11T14:10:53.539"
 ```
 """
 function Base.cat(data::InferenceData, others::InferenceData...; groups=keys(data), dims)