Support Julia v1.3 (#126)

* Support Julia v1.3

* Skip Float16 det test, add tests for #118

* v0.10.1, add missing similar

* Increase coverage

* Fix tests

.travis.yml

@@ -7,6 +7,7 @@ julia:
   - 1.0
   - 1.1
   - 1.2  
+  - 1.3  
   - nightly
 matrix:
   allow_failures:

Project.toml

@@ -1,6 +1,6 @@
 name = "BandedMatrices"
 uuid = "aae01518-5342-5314-be14-df237901396f"
-version = "0.10"
+version = "0.10.1"
 
 [deps]
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"

appveyor.yml

@@ -2,7 +2,8 @@ environment:
   matrix:
   - julia_version: 1
   - julia_version: 1.1
-  - julia_version: 1.2    
+  - julia_version: 1.2
+  - julia_version: 1.3  
   - julia_version: nightly
 
 platform:

src/BandedMatrices.jl

@@ -10,7 +10,7 @@ import LinearAlgebra.LAPACK: liblapack, chkuplo, chktrans
 import LinearAlgebra: cholesky, cholesky!, cholcopy, norm, diag, eigvals!, eigvals, eigen!, eigen,
             qr, qr!, axpy!, ldiv!, mul!, lu, lu!, ldlt, ldlt!, AbstractTriangular,
             chkstride1, kron, lmul!, rmul!, factorize, StructuredMatrixStyle, logabsdet,
-            svdvals, svdvals!, QRPackedQ, checknonsingular, ipiv2perm, _apply_ipiv!, tril!,
+            svdvals, svdvals!, QRPackedQ, checknonsingular, ipiv2perm, tril!,
             triu!, Givens
 import MatrixFactorizations: ql, ql!, QLPackedQ, reflector!, reflectorApply!
 import SparseArrays: sparse
@@ -70,6 +70,12 @@ else
     import Base: require_one_based_indexing
 end
 
+if VERSION < v"1.3-"
+    const _apply_ipiv_rows! = LinearAlgebra._apply_ipiv!
+else
+    import LinearAlgebra: _apply_ipiv_rows!
+end
+
 include("blas.jl")
 include("lapack.jl")
 

src/banded/BandedMatrix.jl

@@ -260,7 +260,7 @@ end
 similar(bm::AbstractBandedMatrix, n::Integer, m::Integer) = similar(bm, eltype(bm), m, n)
 similar(bm::AbstractBandedMatrix, n::Integer, m::Integer, l::Integer, u::Integer) =
     similar(bm, eltype(bm), m, n, l, u)
-
+similar(bm::AbstractBandedMatrix, nm::Tuple{<:Integer,<:Integer}) = similar(bm, nm...)
 
 
 ## Abstract Array Interface

src/banded/bandedqr.jl

@@ -138,7 +138,8 @@ end
 # rmul!(A::AbstractMatrix, adjQ::Adjoint{<:Any,<:QRPackedQ{<:Any,<:BandedMatrix}}) = banded_rmul!(A, adjA)
 # rmul!(A::StridedMatrix, adjQ::Adjoint{<:Any,<:QRPackedQ{<:Any,<:BandedMatrix}}) = banded_rmul!(A, adjA)
 rmul!(A::StridedVecOrMat{T}, Q::QRPackedQ{T,B}) where {T<:BlasFloat,B<:BandedMatrix{T}} = banded_rmul!(A, Q)
-rmul!(A::StridedVecOrMat{T}, adjQ::Adjoint{T,QRPackedQ{T,B}}) where {T<:BlasFloat,B<:BandedMatrix{T}} = banded_rmul!(A, adjQ)
+rmul!(A::StridedVecOrMat{T}, adjQ::Adjoint{<:Any,QRPackedQ{T,B}}) where {T<:BlasComplex,B<:BandedMatrix{T}} = banded_rmul!(A, adjQ)
+rmul!(A::StridedVecOrMat{T}, adjQ::Adjoint{<:Any,QRPackedQ{T,B}}) where {T<:BlasReal,B<:BandedMatrix{T}} = banded_rmul!(A, adjQ)
 
 
 function _banded_widerect_ldiv!(A::QR{T}, B) where T

src/banded/linalg.jl

@@ -28,11 +28,6 @@ function ldiv!(A::BandedLU{T,<:BandedMatrix}, B::StridedVecOrMat{T}) where {T<:B
     LAPACK.gbtrs!('N', l, u-l, m, data, A.ipiv, B)
 end
 
-function ldiv!(A::BandedLU, B::AbstractVecOrMat)
-    _apply_ipiv!(A, B)
-    ldiv!(UpperTriangular(A.factors), ldiv!(UnitLowerTriangular(A.factors), B))
-end
-
 function ldiv!(A::BandedLU{T}, B::AbstractVecOrMat{Complex{T}}) where T<:Real
     # c2r = reshape(transpose(reinterpret(T, reshape(B, (1, length(B))))), size(B, 1), 2*size(B, 2))
     a = real.(B)

test/test_banded.jl

@@ -339,6 +339,9 @@ Base.similar(::MyMatrix, ::Type{T}, m::Int, n::Int) where T = MyMatrix{T}(undef,
             @test size(similar(banded)) == size(banded)
             @test similar(banded).l == banded.l
             @test similar(banded).u == banded.u
+            @test @inferred(similar(banded,(5,5))) isa BandedMatrix{Int32, Matrix{Int32}}
+            @test @inferred(similar(banded,5,5)) isa BandedMatrix{Int32, Matrix{Int32}}
+            @test @inferred(similar(banded,5,5,1,1)) isa BandedMatrix{Int32, Matrix{Int32}}
 
             banded = convert(BandedMatrix{<:, MyMatrix}, brand(Int32, 10, 12, 1, 2))
             @test banded isa BandedMatrix{Int32, MyMatrix{Int32}}

test/test_bandedqr.jl

@@ -168,29 +168,31 @@ end
     end
 
     @testset "lmul!/rmul!" begin
-        A = brand(100,100,3,4)
-        Q,R = qr(A)
-        x = randn(100)
-        b = randn(100,2)
-        @test lmul!(Q, copy(x)) ≈ Matrix(Q)*x
-        @test lmul!(Q, copy(b)) ≈ Matrix(Q)*b
-        @test lmul!(Q', copy(x)) ≈ Matrix(Q)'*x
-        @test lmul!(Q', copy(b)) ≈ Matrix(Q)'*b
-        c = randn(2,100)
-        @test rmul!(copy(c), Q) ≈ c*Matrix(Q)
-        @test rmul!(copy(c), Q') ≈ c*Matrix(Q')
-
-        A = brand(100,100,3,4)
-        Q,L = ql(A)
-        x = randn(100)
-        b = randn(100,2)
-        @test lmul!(Q, copy(x)) ≈ Matrix(Q)*x
-        @test lmul!(Q, copy(b)) ≈ Matrix(Q)*b
-        @test lmul!(Q', copy(x)) ≈ Matrix(Q)'*x
-        @test lmul!(Q', copy(b)) ≈ Matrix(Q)'*b
-        c = randn(2,100)
-        @test rmul!(copy(c), Q) ≈ c*Matrix(Q)
-        @test rmul!(copy(c), Q') ≈ c*Matrix(Q')
+        for T in (Float32, Float64, ComplexF32, ComplexF64)
+            A = brand(T,100,100,3,4)
+            Q,R = qr(A)
+            x = randn(T,100)
+            b = randn(T,100,2)
+            @test lmul!(Q, copy(x)) ≈ Matrix(Q)*x
+            @test lmul!(Q, copy(b)) ≈ Matrix(Q)*b
+            @test lmul!(Q', copy(x)) ≈ Matrix(Q)'*x
+            @test lmul!(Q', copy(b)) ≈ Matrix(Q)'*b
+            c = randn(T,2,100)
+            @test rmul!(copy(c), Q) ≈ c*Matrix(Q)
+            @test rmul!(copy(c), Q') ≈ c*Matrix(Q')
+
+            A = brand(T,100,100,3,4)
+            Q,L = ql(A)
+            x = randn(T,100)
+            b = randn(T,100,2)
+            @test lmul!(Q, copy(x)) ≈ Matrix(Q)*x
+            @test lmul!(Q, copy(b)) ≈ Matrix(Q)*b
+            @test lmul!(Q', copy(x)) ≈ Matrix(Q)'*x
+            @test lmul!(Q', copy(b)) ≈ Matrix(Q)'*b
+            c = randn(T,2,100)
+            @test rmul!(copy(c), Q) ≈ c*Matrix(Q)
+            @test rmul!(copy(c), Q') ≈ c*Matrix(Q')
+        end
     end
 
     @testset "Mixed types" begin

test/test_linalg.jl

@@ -1,4 +1,4 @@
-using BandedMatrices, LazyArrays, LinearAlgebra, Test
+using BandedMatrices, LazyArrays, LinearAlgebra, FillArrays, Test
 import Base.Broadcast: materialize, broadcasted
 import BandedMatrices: BandedMulAddStyle, BandedColumns
 import LazyArrays: SymmetricLayout, MemoryLayout, Applied
@@ -243,5 +243,12 @@ import LazyArrays: SymmetricLayout, MemoryLayout, Applied
         A = brand(10,10,1,1)
         @test x'A ≈ x'Matrix(A) ≈ transpose(x)A
     end
+
+    @testset "mismatched dimensions (#118)" begin
+        m = BandedMatrix(Eye(3), (0,0))
+        @test_throws DimensionMismatch m * [1,2]
+        @test_throws DimensionMismatch m * [1, 2, 3, 4]
+        @test_throws DimensionMismatch m \ [1, 2]
+    end
 end
 

test/test_symbanded.jl

@@ -145,7 +145,8 @@ end
         y = F\b
         @test x ≈ y
         @test_throws DimensionMismatch F\[b;b]
-        @test det(F) ≈ det(SAL)
+
+        T ≠ Float16 && (@test det(F) ≈ det(SAL))
     end
     for T in (Int16, Int32, Int64, BigInt)
         A = BandedMatrix{T}(undef, (4,4), (1,1))