Merge remote-tracking branch 'origin/master' into GChisq

.github/workflows/CI.yml

@@ -2,12 +2,12 @@ name: CI
 
 on:
   pull_request:
-    branches:
-      - master
   push:
     branches:
       - master
     tags: '*'
+  workflow_dispatch:
+  merge_group:
 
 concurrency:
   # Skip intermediate builds: always.
@@ -17,38 +17,28 @@ concurrency:
 
 jobs:
   test:
-    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ github.event_name }}
     runs-on: ${{ matrix.os }}
-    continue-on-error: ${{ matrix.version == 'nightly' }}
     strategy:
       fail-fast: false
       matrix:
         version:
           - '1.3'
           - '1'
-          - 'nightly'
+          - pre
         os:
           - ubuntu-latest
           - macos-latest
           - windows-latest
-        arch:
-          - x64
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
-          arch: ${{ matrix.arch }}
-      - uses: actions/cache@v3
-        env:
-          cache-name: cache-artifacts
-        with:
-          path: ~/.julia/artifacts
-          key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
-          restore-keys: |
-            ${{ runner.os }}-test-${{ env.cache-name }}-
-            ${{ runner.os }}-test-
-            ${{ runner.os }}-
+          # ARM64 on macos-latest is neither supported by older Julia versions nor setup-julia
+          arch: ${{ matrix.os == 'macos-latest' && matrix.version != '1.3' && 'aarch64' || 'x64' }}
+          show-versioninfo: true
+      - uses: julia-actions/cache@v2
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
       - run: |
@@ -57,17 +47,20 @@ jobs:
             Pkg.instantiate()'
       - run: julia --project=perf perf/samplers.jl
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v3
+      - uses: codecov/codecov-action@v5
         with:
+          token: ${{ secrets.CODECOV_TOKEN }} # required
+          fail_ci_if_error: true
           files: lcov.info
   docs:
     name: Documentation
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: '1'
+          show-versioninfo: true
       - run: |
           julia --project=docs -e '
             using Pkg

.github/workflows/IntegrationTest.yml

@@ -32,7 +32,7 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: 1
           arch: x64

Project.toml

@@ -1,9 +1,10 @@
 name = "Distributions"
 uuid = "31c24e10-a181-5473-b8eb-7969acd0382f"
 authors = ["JuliaStats"]
-version = "0.25.103"
+version = "0.25.117"
 
 [deps]
+AliasTables = "66dad0bd-aa9a-41b7-9441-69ab47430ed8"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DensityInterface = "b429d917-457f-4dbc-8f4c-0cc954292b1d"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
@@ -30,15 +31,27 @@ DistributionsDensityInterfaceExt = "DensityInterface"
 DistributionsTestExt = "Test"
 
 [compat]
+AliasTables = "1"
+Aqua = "0.8"
+Calculus = "0.5"
 ChainRulesCore = "1"
+ChainRulesTestUtils = "1"
 DensityInterface = "0.4"
+Distributed = "<0.0.1, 1"
 FillArrays = "0.9, 0.10, 0.11, 0.12, 0.13, 1"
+FiniteDifferences = "0.12"
+ForwardDiff = "0.10"
+JSON = "0.21"
 LinearAlgebra = "<0.0.1, 1"
+OffsetArrays = "1"
 PDMats = "0.10, 0.11"
 Printf = "<0.0.1, 1"
 QuadGK = "2"
 Random = "<0.0.1, 1"
+SparseArrays = "<0.0.1, 1"
 SpecialFunctions = "1.2, 2"
+StableRNGs = "1"
+StaticArrays = "1"
 Statistics = "1"
 StatsAPI = "1.6"
 StatsBase = "0.32, 0.33, 0.34"
@@ -47,6 +60,7 @@ Test = "<0.0.1, 1"
 julia = "1.3"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 Calculus = "49dc2e85-a5d0-5ad3-a950-438e2897f1b9"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
@@ -62,4 +76,4 @@ StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["StableRNGs", "Calculus", "ChainRulesCore", "ChainRulesTestUtils", "DensityInterface", "Distributed", "FiniteDifferences", "ForwardDiff", "JSON", "SparseArrays", "StaticArrays", "Test", "OffsetArrays"]
+test = ["Aqua", "StableRNGs", "Calculus", "ChainRulesCore", "ChainRulesTestUtils", "DensityInterface", "Distributed", "FiniteDifferences", "ForwardDiff", "JSON", "SparseArrays", "StaticArrays", "Test", "OffsetArrays"]

README.md

@@ -4,6 +4,7 @@ Distributions.jl
 [![Build Status](https://github.com/JuliaStats/Distributions.jl/workflows/CI/badge.svg)](https://github.com/JuliaStats/Distributions.jl/actions)
 [![](https://zenodo.org/badge/DOI/10.5281/zenodo.2647458.svg)](https://zenodo.org/record/2647458)
 [![Coverage Status](https://coveralls.io/repos/JuliaStats/Distributions.jl/badge.svg?branch=master)](https://coveralls.io/r/JuliaStats/Distributions.jl?branch=master)
+[![Aqua QA](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)
 
 [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://JuliaStats.github.io/Distributions.jl/latest/)
 [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaStats.github.io/Distributions.jl/stable/)

docs/Project.toml

@@ -3,5 +3,5 @@ Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 GR = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71"
 
 [compat]
-Documenter = "0.26, 0.27"
-GR = "0.72.1"
+Documenter = "1"
+GR = "0.72.1, 0.73"

docs/make.jl

@@ -1,7 +1,7 @@
 using Documenter, Distributions
 import Random: AbstractRNG, rand!
 
-makedocs(
+makedocs(;
     sitename = "Distributions.jl",
     modules  = [Distributions],
     format   = Documenter.HTML(; prettyurls = get(ENV, "CI", nothing) == "true"),
@@ -17,16 +17,18 @@ makedocs(
         "reshape.md",
         "cholesky.md",
         "mixture.md",
+        "product.md",
         "order_statistics.md",
         "convolution.md",
         "fit.md",
         "extends.md",
         "density_interface.md",
-    ]
+    ],
+    warnonly = true,
 )
 
 deploydocs(;
     repo = "github.com/JuliaStats/Distributions.jl.git",
     versions = ["stable" => "v^", "v#.#", "dev" => "master"],
-    push_preview=true,
+    push_preview = true,
 )

docs/src/fit.md

@@ -27,6 +27,8 @@ The function `fit_mle` is for maximum likelihood estimation.
 ### Synopsis
 
 ```@docs
+fit(D, x)
+fit(D, x, w)
 fit_mle(D, x)
 fit_mle(D, x, w)
 ```

docs/src/multivariate.md

@@ -58,7 +58,6 @@ MvNormalCanon
 MvLogitNormal
 MvLogNormal
 Dirichlet
-Product
 ```
 
 ## Addition Methods
@@ -105,15 +104,6 @@ params{D<:Distributions.AbstractMvLogNormal}(::Type{D},m::AbstractVector,S::Abst
 Distributions._logpdf(d::MultivariateDistribution, x::AbstractArray)
 ```
 
-## Product distributions
-
-```@docs
-Distributions.product_distribution
-```
-
-Using `product_distribution` is advised to construct product distributions. 
-For some distributions, it constructs a special multivariate type.
-
 ## Index
 
 ```@index

docs/src/product.md

@@ -0,0 +1,27 @@
+# Product Distributions
+
+Product distributions are joint distributions of multiple independent distributions.
+It is recommended to use `product_distribution` to construct product distributions.
+Depending on the type of the argument, it may construct a different distribution type.
+
+## Multivariate products
+
+```@docs
+Distributions.product_distribution(::AbstractArray{<:Distribution{<:ArrayLikeVariate}})
+Distributions.product_distribution(::AbstractVector{<:Normal})
+Distributions.ProductDistribution
+Distributions.Product
+```
+
+## NamedTuple-variate products
+
+```@docs
+Distributions.product_distribution(::NamedTuple{<:Any,<:Tuple{Distribution,Vararg{Distribution}}})
+Distributions.ProductNamedTupleDistribution
+```
+
+## Index
+
+```@index
+Pages = ["product.md"]
+```

src/Distributions.jl

@@ -27,6 +27,8 @@ import PDMats: dim, PDMat, invquad
 using SpecialFunctions
 using Base.MathConstants: eulergamma
 
+import AliasTables
+
 export
     # re-export Statistics
     mean, median, quantile, std, var, cov, cor,
@@ -39,6 +41,7 @@ export
     Multivariate,
     Matrixvariate,
     CholeskyVariate,
+    NamedTupleVariate,
     Discrete,
     Continuous,
     Sampleable,
@@ -128,7 +131,6 @@ export
     MatrixBeta,
     MatrixFDist,
     MatrixNormal,
-    MatrixReshaped,
     MatrixTDist,
     MixtureModel,
     Multinomial,
@@ -296,6 +298,7 @@ include("univariates.jl")
 include("edgeworth.jl")
 include("multivariates.jl")
 include("matrixvariates.jl")
+include("namedtuple/productnamedtuple.jl")
 include("cholesky/lkjcholesky.jl")
 include("samplers.jl")
 
@@ -366,7 +369,7 @@ Supported distributions:
     NoncentralF, NoncentralHypergeometric, NoncentralT, Normal, NormalCanon,
     NormalInverseGaussian, Pareto, PGeneralizedGaussian, Poisson, PoissonBinomial,
     QQPair, Rayleigh, Rician, Skellam, Soliton, StudentizedRange, SymTriangularDist, TDist, TriangularDist,
-    Triweight, Truncated, TruncatedNormal, Uniform, UnivariateGMM,
+    Triweight, Truncated, Uniform, UnivariateGMM,
     VonMises, VonMisesFisher, WalleniusNoncentralHypergeometric, Weibull,
     Wishart, ZeroMeanIsoNormal, ZeroMeanIsoNormalCanon,
     ZeroMeanDiagNormal, ZeroMeanDiagNormalCanon, ZeroMeanFullNormal,

src/censored.jl

@@ -431,6 +431,7 @@ _in_open_interval(x::Real, l::Real, ::Nothing) = x > l
 _clamp(x, l, u) = clamp(x, l, u)
 _clamp(x, ::Nothing, u) = min(x, u)
 _clamp(x, l, ::Nothing) = max(x, l)
+_clamp(x, ::Nothing, u::Nothing) = x
 
 _to_truncated(d::Censored) = truncated(d.uncensored, d.lower, d.upper)
 

src/cholesky/lkjcholesky.jl

@@ -109,7 +109,12 @@ function insupport(d::LKJCholesky, R::LinearAlgebra.Cholesky)
     return true
 end
 
-function StatsBase.mode(d::LKJCholesky)
+function mode(d::LKJCholesky; check_args::Bool=true)
+    @check_args(
+        LKJCholesky,
+        @setup(η = d.η),
+        (η, η > 1, "mode is defined only when η > 1."),
+    )
     factors = Matrix{eltype(d)}(LinearAlgebra.I, size(d))
     return LinearAlgebra.Cholesky(factors, d.uplo, 0)
 end