Merge branch 'main' into do/csc-interface-baseline

Author: termi-official

.github/workflows/ci.yml

@@ -24,24 +24,17 @@ jobs:
           - ubuntu-latest
           - windows-latest
           - macOS-13 # intel
-          - macOS-14 # arm
         julia-arch:
           - x64
           - x86
-          - aarch64
         exclude:
-          - os: ubuntu-latest
-            julia-arch: aarch64
-          - os: windows-latest
-            julia-arch: aarch64
           - os: macOS-13
             julia-arch: x86
-          - os: macOS-13
+        include:
+          - os: macOS-latest
             julia-arch: aarch64
-          - os: macOS-14
-            julia-arch: x86
-          - os: macOS-14
-            julia-arch: x64
+            julia-version: 'nightly'
+            
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v2

Project.toml

@@ -19,7 +19,7 @@ Pkg = "<0.0.1, 1"
 Printf = "<0.0.1, 1"
 Random = "<0.0.1, 1"
 Serialization = "<0.0.1, 1"
-SuiteSparse_jll = "7.7.0"
+SuiteSparse_jll = "7.8.0"
 Test = "<0.0.1, 1"
 julia = "1.11"
 

docs/make.jl

@@ -8,6 +8,7 @@ makedocs(
     sitename = "SparseArrays",
     pages = Any[
         "SparseArrays" => "index.md",
+        "Sparse Linear Algebra API" => "solvers.md",
         ];
     warnonly = [:missing_docs, :cross_references],
     )

docs/src/index.md

@@ -210,19 +210,17 @@ section of the standard library reference.
 
 Sparse matrix solvers call functions from [SuiteSparse](http://suitesparse.com). The following factorizations are available:
 
+1. [`cholesky`](@ref SparseArrays.CHOLMOD.cholesky)
+2. [`ldlt`](@ref SparseArrays.CHOLMOD.ldlt)
+3. [`lu`](@ref SparseArrays.UMFPACK.lu)
+4. [`qr`](@ref SparseArrays.SPQR.qr)
+
 | Type                  | Description                                   |
 |:----------------------|:--------------------------------------------- |
 | `CHOLMOD.Factor`      | Cholesky and LDLt factorizations              |
 | `UMFPACK.UmfpackLU`   | LU factorization                              |
 | `SPQR.QRSparse`       | QR factorization                              |
 
-These factorizations are described in more detail in the [Sparse Linear Algebra API section](@ref stdlib-sparse-linalg-api):
-
-1. [`cholesky`](@ref SparseArrays.CHOLMOD.cholesky)
-2. [`ldlt`](@ref SparseArrays.CHOLMOD.ldlt)
-3. [`lu`](@ref SparseArrays.UMFPACK.lu)
-4. [`qr`](@ref SparseArrays.SPQR.qr)
-
 ```@meta
 DocTestSetup = nothing
 ```
@@ -267,25 +265,6 @@ SparseArrays.ftranspose!
 DocTestSetup = nothing
 ```
 
-# [Sparse Linear Algebra API](@id stdlib-sparse-linalg-api)
-
-```@docs
-SparseArrays.CHOLMOD.cholesky
-SparseArrays.CHOLMOD.cholesky!
-SparseArrays.CHOLMOD.lowrankupdate
-SparseArrays.CHOLMOD.lowrankupdate!
-SparseArrays.CHOLMOD.lowrankdowndate
-SparseArrays.CHOLMOD.lowrankdowndate!
-SparseArrays.CHOLMOD.lowrankupdowndate!
-SparseArrays.CHOLMOD.ldlt
-SparseArrays.UMFPACK.lu
-SparseArrays.SPQR.qr
-```
-
-```@meta
-DocTestSetup = nothing
-```
-
 # Noteworthy External Sparse Packages
 
 Several other Julia packages provide sparse matrix implementations that should be mentioned:

docs/src/solvers.md

@@ -0,0 +1,20 @@
+# Sparse Linear Algebra (API)
+
+```@meta
+DocTestSetup = :(using LinearAlgebra, SparseArrays)
+```
+
+```@docs; canonical=false
+SparseArrays.CHOLMOD.cholesky
+SparseArrays.CHOLMOD.cholesky!
+SparseArrays.CHOLMOD.lowrankdowndate
+SparseArrays.CHOLMOD.lowrankdowndate!
+SparseArrays.CHOLMOD.lowrankupdowndate!
+SparseArrays.CHOLMOD.ldlt
+SparseArrays.SPQR.qr
+SparseArrays.UMFPACK.lu
+```
+
+```@meta
+DocTestSetup = nothing
+```

src/solvers/spqr.jl

@@ -146,7 +146,7 @@ Matrix{T}(Q::QRSparseQ) where {T} = lmul!(Q, Matrix{T}(I, size(Q, 1), min(size(Q
 
 # From SPQR manual p. 6
 _default_tol(A::AbstractSparseMatrixCSC) =
-    20*sum(size(A))*eps(real(eltype(A)))*maximum(norm(view(A, :, i)) for i in 1:size(A, 2))
+    20*sum(size(A))*eps()*maximum(norm(view(A, :, i)) for i in 1:size(A, 2))
 
 """
     qr(A::SparseMatrixCSC; tol=_default_tol(A), ordering=ORDERING_DEFAULT) -> QRSparse