Merge branch 'main' into breaking

tiemvanderdeure · web-flow · commit 2e5a8122a76d · 2025-10-15T19:35:33.000+02:00
diff --git a/CondaPkg.toml b/CondaPkg.toml
@@ -2,3 +2,5 @@
 xarray = ""
 numpy = ""
 openssl = "<=julia"
+# Python 3.14 segfaults something awful
+python = "3.13.*"
diff --git a/Project.toml b/Project.toml
@@ -41,11 +41,11 @@ DimensionalDataAlgebraOfGraphicsExt = "AlgebraOfGraphics"
 DimensionalDataCategoricalArraysExt = "CategoricalArrays"
 DimensionalDataChainRulesCoreExt = "ChainRulesCore"
 DimensionalDataDiskArraysExt = "DiskArrays"
-DimensionalDataMakie = "Makie"
+DimensionalDataMakieExt = "Makie"
 DimensionalDataNearestNeighborsExt = "NearestNeighbors"
-DimensionalDataPythonCall = "PythonCall"
+DimensionalDataPythonCallExt = "PythonCall"
 DimensionalDataSparseArraysExt = "SparseArrays"
-DimensionalDataStatsBase = "StatsBase"
+DimensionalDataStatsBaseExt = "StatsBase"
 
 [compat]
 AbstractFFTs = "1"
diff --git a/docs/src/.vitepress/config.mts b/docs/src/.vitepress/config.mts
@@ -31,6 +31,7 @@ const navTemp = {
         { text: 'DiskArrays', link: '/diskarrays' },
         { text: 'Xarray', link: '/xarray' },
         { text: 'Extending DimensionalData', link: '/extending_dd' },
+        { text: 'FFT', link: '/fft' },
       ],
     },
   ],
diff --git a/docs/src/extending_dd.md b/docs/src/extending_dd.md
@@ -89,7 +89,7 @@ format(dims, array)
 This lets DimensionalData detect the lookup properties, fill in missing fields
 of a `Lookup`, pass keywords from `Dimension` to detected `Lookup` 
 constructors, and accept a wider range of dimension inputs like tuples of `Symbol` 
-and `Type`.  The way you indicate that something needs to be filled is by using the `Auto` types, like `AutoOrder`](@ref) or `AutoSampling`.
+and `Type`.  The way you indicate that something needs to be filled is by using the `Auto` types, like [`AutoOrder`](@ref) or `AutoSampling`.
 
 Not calling `format` in the outer constructors of an `AbstractDimArray`
 has undefined behaviour.
diff --git a/docs/src/fft.md b/docs/src/fft.md
@@ -0,0 +1,21 @@
+# Fast Fourier Transform (FFT)
+`DimensionalData.jl` implements the Fast Fourier Transform (FFT) for `DimensionalArray` objects, allowing users to perform frequency domain analysis while preserving dimensional metadata.
+
+It uses lookups to scale the forward and inverse transforms to remain physically meaningful. As such, it implements the following conventions. If we denote a signal as a function of time ``a(x)`` sampled at discrete intervals ``dx``, the discrete Fourier transform (DFT) is defined as:
+```math
+\operatorname{DFT}(A)[k] =
+\sum_{n=1}^{\operatorname{length}(A)} \exp\left(i2π x[n]f[k] \right) A[n] dx.
+```
+The inverse discrete Fourier transform (IDFT) is defined as:
+```math
+\operatorname{IDFT}(A)[n] =
+\sum_{k=1}^{\operatorname{length}(A)} \exp\left(-i2π x[n]f[k] \right) A[k] df.
+```
+
+These conventions ensure that the transforms are unitary, meaning that applying the DFT followed by the IDFT returns the original signal without any additional scaling factors. The scaling factors applied to the forward and inverse transforms are different from the "standard" discrete Fourier transform definitions, which typically does not scale the forward transform, and includes a normalization factor of `1/N` in the inverse transform.
+
+## API
+
+The following functions are provided for performing FFTs on `DimensionalArray` objects:
+
+TODO
diff --git a/ext/DimensionalDataAbstractFFTsExt.jl b/ext/DimensionalDataAbstractFFTsExt.jl
@@ -269,7 +269,7 @@ for i in (:fft, :ifft, :rfft)
 
         ```math
         \\operatorname{DFT}(A)[k] =
-        \\sum_{n=1}^{\\operatorname{length}(A)} \\exp\\left($(signal)\\pi x[n]f[k] \\right) A[n] dx.
+        \\sum_{n=1}^{\\operatorname{length}(A)} \\exp\\left($(signal)2\\pi x[n]f[k] \\right) A[n] dx.
         ```
         where `x` is the lookup dimension of the input data, `f` is the lookup dimension of the output data, and `dx` is the step of the lookup dimension of the input data.
 
@@ -292,7 +292,7 @@ end
 
         ```math
         \\operatorname{DFT}(A)[k] =
-        \\sum_{n=1}^{\\operatorname{length}(A)} \\exp\\left(i\\pi x[n]f[k] \\right) A[n] dx.
+        \\sum_{n=1}^{\\operatorname{length}(A)} \\exp\\left(i2\\pi x[n]f[k] \\right) A[n] dx.
         ```
         where `x` is the lookup dimension of the input data, `f` is the lookup dimension of the output data, and `dx` is the step of the lookup dimension of the input data.
 
diff --git a/ext/DimensionalDataMakieExt.jl b/ext/DimensionalDataMakieExt.jl
@@ -1,4 +1,4 @@
-module DimensionalDataMakie
+module DimensionalDataMakieExt
 
 using DimensionalData
 using Makie
diff --git a/ext/DimensionalDataPythonCallExt.jl b/ext/DimensionalDataPythonCallExt.jl
@@ -1,4 +1,4 @@
-module DimensionalDataPythonCall
+module DimensionalDataPythonCallExt
 
 using DimensionalData
 import DimensionalData as DD
diff --git a/ext/DimensionalDataSparseArraysExt.jl b/ext/DimensionalDataSparseArraysExt.jl
diff --git a/ext/DimensionalDataStatsBaseExt.jl b/ext/DimensionalDataStatsBaseExt.jl
@@ -1,4 +1,4 @@
-module DimensionalDataStatsBase
+module DimensionalDataStatsBaseExt
 
 using DimensionalData
 using Statistics
@@ -24,4 +24,4 @@ function _weighted(f::F, A, w, dims) where F
     end
 end
 
-end
+end
diff --git a/src/array/methods.jl b/src/array/methods.jl
@@ -18,11 +18,11 @@ for (m, f) in ((:Base, :sum), (:Base, :prod), (:Base, :maximum), (:Base, :minimu
         # Local dispatch methods
         # - Return a reduced DimArray
         @inline function $_f(A::AbstractDimArray, dims; kw...)
-            ds = _astuple(DD.dims(A, dims)) # Need to remove unused dims before `dimnum`
+            ds = DD.dims(A, _astuple(dims)) # Need to remove unused dims before `dimnum`
             rebuild(A, $m.$f(parent(A); dims=dimnum(A, ds), kw...), reducedims(A, ds))
         end
         @inline function $_f(f, A::AbstractDimArray, dims; kw...)
-            ds = _astuple(DD.dims(A, dims)) # Need to remove unused dims before `dimnum`
+            ds = DD.dims(A, _astuple(dims)) # Need to remove unused dims before `dimnum`
             rebuild(A, $m.$f(f, parent(A); dims=dimnum(A, ds), kw...), reducedims(A, ds))
         end
         # - Return a scalar
diff --git a/test/methods.jl b/test/methods.jl
@@ -67,6 +67,11 @@ end
     @test sum(da; dims=:) == 10
     @test sum(x -> 2x, da; dims=:) == 20
 
+    @test sum(da; dims = 5) == sum(da; dims = :notadim) == 
+        sum(da; dims = (:notadim,)) == da
+    @test maximum(da; dims = 5) == maximum(da; dims = :notadim) == 
+        maximum(da; dims = (:notadim,)) == da
+
     a = [1 2; 3 4]
     dimz = X(143:2:145), Y(-38:2:-36)
     da = DimArray(a, dimz)

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-module DimensionalDataMakie`
	`1`	`+module DimensionalDataMakieExt`
`2`	`2`
`3`	`3`	`using DimensionalData`
`4`	`4`	`using Makie`
Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-module DimensionalDataPythonCall`
	`1`	`+module DimensionalDataPythonCallExt`
`2`	`2`
`3`	`3`	`using DimensionalData`
`4`	`4`	`import DimensionalData as DD`