Merge branch 'rafaqz:main' into stack

.github/workflows/Documenter.yml

@@ -37,18 +37,10 @@ jobs:
         uses: actions/checkout@v4
         with: # Fetches the last commit only
           fetch-depth: 0
-      - name: Setup Node
-        uses: actions/setup-node@v3
-        with:
-            node-version: 20
-            cache: npm # or pnpm / yarn
-            cache-dependency-path: 'docs/package-lock.json' # this should be a package-lock.json file
       - name: Setup Julia
         uses: julia-actions/setup-julia@v1
       - name: Pull Julia cache
         uses: julia-actions/cache@v1
-      - name: Instantiate NPM
-        run: cd docs/; npm i; cd ..
       - name: Generate logo
         run: julia --project=docs -e "using Pkg; Pkg.instantiate()"; julia --project=docs/ --color=yes docs/logo.jl
       - uses: julia-actions/julia-docdeploy@v1

.github/workflows/ci.yml

@@ -12,21 +12,25 @@ jobs:
   test:
     name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
     runs-on: ${{ matrix.os }}
+    continue-on-error: ${{ matrix.allow_failure }}
     strategy:
       fail-fast: true
       matrix:
         version:
+          - '1.10'
           - '1'
         os:
           - ubuntu-latest
           - macOS-latest
           - windows-latest
         arch:
           - x64
+        allow_failure: [false]
         include:
           - version: 'nightly'
             os: ubuntu-latest
             arch: x64
+            allow_failure: true
     steps:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@v1

.gitignore

@@ -23,5 +23,7 @@ docs/.vitepress/cache
 docs/src/.vitepress/dist
 docs/src/.vitepress/cache
 node_modules
+docs/package-lock.json
 *.png
-*.svg
+*.svg
+*.ico

Project.toml

@@ -1,7 +1,7 @@
 name = "DimensionalData"
 uuid = "0703355e-b756-11e9-17c0-8b28908087d0"
 authors = ["Rafael Schouten <[email protected]>"]
-version = "0.25.8"
+version = "0.29.1"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -24,17 +24,27 @@ TableTraits = "3783bdb8-4a98-5b6b-af9a-565f29a5fe9c"
 Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
 
 [weakdeps]
+AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
+CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
+DiskArrays = "3c3547ce-8d99-4f5e-a174-61eb10b00ae3"
 Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
+StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [extensions]
+DimensionalDataAlgebraOfGraphicsExt = "AlgebraOfGraphics"
+DimensionalDataCategoricalArraysExt = "CategoricalArrays"
+DimensionalDataDiskArraysExt = "DiskArrays"
 DimensionalDataMakie = "Makie"
+DimensionalDataStatsBase = "StatsBase"
 
 [compat]
 Adapt = "2, 3.0, 4"
+AlgebraOfGraphics = "0.8"
 Aqua = "0.8"
 ArrayInterface = "7"
 BenchmarkTools = "1"
-CairoMakie = "0.10, 0.11"
+CairoMakie = "0.10, 0.11, 0.12"
+CategoricalArrays = "0.10"
 ColorTypes = "0.11"
 Combinatorics = "1"
 ConstructionBase = "1"
@@ -43,16 +53,19 @@ DataAPI = "1.16"
 DataFrames = "1"
 Dates = "1"
 Distributions = "0.25"
+DiskArrays = "0.3, 0.4"
 Documenter = "1"
 Extents = "0.1"
+GPUArrays = "10"
 ImageFiltering = "0.7"
 ImageTransformations = "0.10"
 Interfaces = "0.3"
 IntervalSets = "0.5, 0.6, 0.7"
 InvertedIndices = "1"
 IteratorInterfaceExtensions = "1"
+JLArrays = "0.1"
 LinearAlgebra = "1"
-Makie = "0.19, 0.20"
+Makie = "0.20, 0.21"
 OffsetArrays = "1"
 Plots = "1"
 PrecompileTools = "1"
@@ -61,34 +74,41 @@ RecipesBase = "0.7, 0.8, 1"
 SafeTestsets = "0.1"
 SparseArrays = "1"
 Statistics = "1"
+StatsBase = "0.34"
 StatsPlots = "0.15"
 TableTraits = "1"
 Tables = "1"
 Test = "1"
 Unitful = "1"
-julia = "1.6"
+julia = "1.9"
 
 [extras]
+AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
+CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
 ColorTypes = "3da002f7-5984-5a60-b8a6-cbb66c0b333f"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
 CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+DiskArrays = "3c3547ce-8d99-4f5e-a174-61eb10b00ae3"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+GPUArrays = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7"
 ImageFiltering = "6a3955dd-da59-5b1f-98d4-e7296123deb5"
 ImageTransformations = "02fcd773-0e25-5acc-982a-7f6622650795"
+JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["Aqua", "ArrayInterface", "BenchmarkTools", "ColorTypes", "Combinatorics", "CoordinateTransformations", "DataFrames", "Distributions", "Documenter", "ImageFiltering", "ImageTransformations", "CairoMakie", "OffsetArrays", "Plots", "Random", "SafeTestsets", "StatsPlots", "Test", "Unitful"]
+test = ["AlgebraOfGraphics", "Aqua", "ArrayInterface", "BenchmarkTools", "CategoricalArrays", "ColorTypes", "Combinatorics", "CoordinateTransformations", "DataFrames", "DiskArrays", "Distributions", "Documenter", "GPUArrays", "ImageFiltering", "ImageTransformations", "JLArrays", "CairoMakie", "OffsetArrays", "Plots", "Random", "SafeTestsets", "StatsBase", "StatsPlots", "Test", "Unitful"]

README.md

@@ -6,30 +6,31 @@
 [![Codecov](https://codecov.io/gh/rafaqz/DimensionalData.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/rafaqz/DimensionalData.jl/tree/main)
 [![Aqua.jl Quality Assurance](https://img.shields.io/badge/Aqua.jl-%F0%9F%8C%A2-aqua.svg)](https://github.com/JuliaTesting/Aqua.jl)
 
-<img src="https://rafaqz.github.io/DimensionalData.jl/dev/logoDD.png" align="right" style="padding-left:10px;" width="180"/>
+<img src="https://rafaqz.github.io/DimensionalData.jl/dev/logo.png" align="right" style="padding-left:10px;" width="180"/>
 
 > [!TIP]
 > Visit the latest documentation at https://rafaqz.github.io/DimensionalData.jl/dev/
 
 DimensionalData.jl provides tools and abstractions for working with datasets that have named dimensions, and optionally a lookup index. It provides no-cost abstractions for named indexing, and fast index lookups.
 
-DimensionalData is a pluggable, generalised version of [AxisArrays.jl](https://github.com/JuliaArrays/AxisArrays.jl) with a cleaner syntax, and additional functionality found in NamedDims.jl. It has similar goals to pythons [xarray](http://xarray.pydata.org/en/stable/), and is primarily written for use with spatial data in [Rasters.jl](https://github.com/rafaqz/Rasters.jl).
+DimensionalData is a pluggable, generalised version of [AxisArrays.jl](https://github.com/JuliaArrays/AxisArrays.jl) with a cleaner syntax, and additional functionality found in NamedDims.jl. It has similar goals to pythons [xarray](https://xarray.dev/), and is primarily written for use with spatial data in [Rasters.jl](https://github.com/rafaqz/Rasters.jl).
 
-> [!IMPORTANT]
-> INSTALLATION
+## Installation
 
 ```shell
 julia>]
 pkg> add DimensionalData
 ```
 
+## Quick start
+
 Start using the package:
 
 ```julia
 using DimensionalData
 ```
 
-The basic syntax is:
+The basic syntax to create a dimensional array (`DimArray`) is:
 
 ```julia
 A = DimArray(rand(50, 31), (X(), Y(10.0:40.0)));
@@ -76,7 +77,7 @@ A[Y=1:10, X=1]
  19.0  0.605331
 ```
 
-We can also subset by lookup, using a `Selector`, lets try `At`: 
+One can also subset by lookup, using a `Selector`, let's try `At`: 
 
 ```julia
 A[Y(At(25))]
@@ -112,25 +113,24 @@ boxplot(rand(X('a':'d'), Y(2:5:20)))
 
 And the plot will have the right ticks and labels.
 
-[See the docs for more details](https://rafaqz.github.io/DimensionalData.jl/)
+[See the docs for more details](https://rafaqz.github.io/DimensionalData.jl/stable/)
 
 > [!NOTE]
 > Recent changes have greatly reduced the exported API.
 
-Previously exported methods can me brought into global scope by `using`
-the sub-modules they have been moved to - `LookupArrays` and `Dimensions`:
+Previously exported methods can be brought into global scope by `using`
+the sub-modules they have been moved to - `Lookup` and `Dimensions`:
 
 ```julia
 using DimensionalData
-using DimensionalData.LookupArrays, DimensionalData.Dimensions
+using DimensionalData.Lookup, DimensionalData.Dimensions
 ```
 
-> [!IMPORTANT]
-> Alternative Packages
+## Alternative packages
 
 There are a lot of similar Julia packages in this space. AxisArrays.jl, NamedDims.jl, NamedArrays.jl are registered alternative that each cover some of the functionality provided by DimensionalData.jl. DimensionalData.jl should be able to replicate most of their syntax and functionality.
 
 [AxisKeys.jl](https://github.com/mcabbott/AxisKeys.jl) and [AbstractIndices.jl](https://github.com/Tokazama/AbstractIndices.jl) are some other interesting developments. For more detail on why there are so many similar options and where things are headed, read this [thread](https://github.com/JuliaCollections/AxisArraysFuture/issues/1).
 
 The main functionality is explained here, but the full list of features is
-listed at the [API](https://rafaqz.github.io/DimensionalData.jl/reference) page.
+listed at the [API](https://rafaqz.github.io/DimensionalData.jl/stable/api/reference) page.

benchmarks/benchmarks.jl

@@ -80,17 +80,16 @@ a = rand(5, 4, 3);
 da = DimArray(a, (Y((1u"m", 5u"m")), X(1:4), Ti(1:3)))
 dimz = dims(da)
 
-if VERSION > v"1.1-"
-    suite["eachslice"] = BenchmarkGroup()
-    suite["eachslice"]["array_intdim"] = @benchmarkable (()->eachslice($a; dims = 2))();
-    suite["eachslice"]["dimarray_intdim"] = @benchmarkable (()->eachslice($da; dims = 2))();
-    suite["eachslice"]["dimarray_dim"] = @benchmarkable (()->eachslice($da; dims = Y()))();
-    suite["eachslice_to_vector"] = BenchmarkGroup()
-    suite["eachslice_to_vector"]["array_intdim"] = @benchmarkable [slice for slice in eachslice($a; dims = 2)];
-    suite["eachslice_to_vector"]["dimarray_intdim"] = @benchmarkable [slice for slice in eachslice($da; dims = 2)];
-    suite["eachslice_to_vector"]["dimarray_dim"] = @benchmarkable [slice for slice in eachslice($da; dims = X())];
-    # @test [slice for slice in eachslice(da; dims=1)] == [slice for slice in eachslice(da; dims=Y)]
-end
+suite["eachslice"] = BenchmarkGroup()
+suite["eachslice"]["array_intdim"] = @benchmarkable (()->eachslice($a; dims = 2))();
+suite["eachslice"]["dimarray_intdim"] = @benchmarkable (()->eachslice($da; dims = 2))();
+suite["eachslice"]["dimarray_dim"] = @benchmarkable (()->eachslice($da; dims = Y()))();
+suite["eachslice_to_vector"] = BenchmarkGroup()
+suite["eachslice_to_vector"]["array_intdim"] = @benchmarkable [slice for slice in eachslice($a; dims = 2)];
+suite["eachslice_to_vector"]["dimarray_intdim"] = @benchmarkable [slice for slice in eachslice($da; dims = 2)];
+suite["eachslice_to_vector"]["dimarray_dim"] = @benchmarkable [slice for slice in eachslice($da; dims = X())];
+# @test [slice for slice in eachslice(da; dims=1)] == [slice for slice in eachslice(da; dims=Y)]
+
 
 
 suite["mean"] = BenchmarkGroup()

docs/Project.toml

@@ -1,4 +1,5 @@
 [deps]
+AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
@@ -12,6 +13,8 @@ Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DocumenterVitepress = "4710194d-e776-4893-9690-8d956a29c365"
 Extents = "411431e0-e8b7-467b-b5e0-f676ba4f2910"
 Interfaces = "85a1e053-f937-4924-92a5-1367d23b7b87"
+IntervalSets = "8197267c-284f-5f27-9208-e0e47529a953"
+Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"

docs/logo.jl

@@ -39,6 +39,7 @@ meshscatter!(ax, base_points; marker=Rect3f(Vec3f(-0.5,-0.5,0), Vec3f(1,1,1)),
     markersize = Vec3f.(0.5,0.5, z), color=z, colormap=tuple.(colors, 1), transparency=false)
 
 mkpath(joinpath(@__DIR__, "src", "assets"))
-save(joinpath(@__DIR__, "src", "assets", "logoDD.svg"), fig; pt_per_unit=0.75)
-save(joinpath(@__DIR__, "src", "assets", "logoDD.png"), fig; px_per_unit=2)
-save(joinpath(@__DIR__, "src", "assets", "favicon.png"), fig; px_per_unit=0.25)
+save(joinpath(@__DIR__, "src", "assets", "logo.svg"), fig; pt_per_unit=0.75)
+save(joinpath(@__DIR__, "src", "assets", "logo.png"), fig; px_per_unit=2)
+save(joinpath(@__DIR__, "src", "assets", "favicon.png"), fig; px_per_unit=0.25)
+mv(joinpath(@__DIR__, "src", "assets", "favicon.png"), joinpath(@__DIR__, "src", "assets", "favicon.ico"))

docs/make.jl

@@ -1,13 +1,19 @@
 using DocumenterVitepress
 using Documenter
 using DimensionalData
+using Dates
 using DimensionalData.Dimensions
 using DimensionalData.Lookups
 
 # Names are available everywhere so that [`function`](@ref) works.
 # ====================
 
-DocMeta.setdocmeta!(DimensionalData, :DocTestSetup, :(using DimensionalData, DimensionalData.Dimensions, DimensionalData.Dimensions.Lookups); recursive=true)
+doctest_setup = quote
+    using DimensionalData
+    using DimensionalData.Dimensions
+    using DimensionalData.Dimensions.Lookups
+end
+DocMeta.setdocmeta!(DimensionalData, :DocTestSetup, doctest_setup; recursive=true)
 
 # Build documentation.
 # ====================
@@ -22,8 +28,7 @@ makedocs(; sitename="DimensionalData", authors="Rafael Schouten et al.",
     ),
     draft=false,
     source="src", 
-    build="build", 
-    # warnonly = true,
+    build="build",
 )
 
 # Deploy built documentation.