Implement vcat(::AbstractBandedMatrix...) (#448)

* implement bandwidths for OneElement

* make improvements

* fix sparse(::SparseMatrixCSC)

* fix bandwidths for SparseMatrixCSC, add for SparseVector

* add bandwidths(::Zeros) behaviour for empty sparse structures

* add unit tests

* overload vcat(::AbstractBandedMatrix...)

* style

* include tests in runtests.jl

* fix issue involving LazyBandedMatrices

* fixed mistake

* make improvements

* add vcat between BandedMatrices and OneElements

* fix issue involving calculation of bandwidths. Add unit tests for OneElement

* fix issue involving bandwidths larger than dimensions

* restore vcat

* v1.7.4

---------

Co-authored-by: Sheehan Olver <[email protected]>

Author: max-vassili3v

src/BandedMatrices.jl

@@ -34,7 +34,7 @@ import ArrayLayouts: AbstractTridiagonalLayout, BidiagonalLayout, BlasMatLdivVec
                      symmetricuplo, transposelayout, triangulardata, triangularlayout, zero!,
                      QRPackedQLayout, AdjQRPackedQLayout
 
-import FillArrays: AbstractFill, getindex_value, _broadcasted_zeros, unique_value, OneElement, RectDiagonal, OneElementMatrix, OneElementVector
+import FillArrays: AbstractFill, getindex_value, _broadcasted_zeros, unique_value, OneElement, RectDiagonal, OneElementMatrix, OneElementVector, ZerosMatrix, ZerosVector
 
 const libblas = LinearAlgebra.BLAS.libblas
 const liblapack = LinearAlgebra.BLAS.liblapack

src/generic/AbstractBandedMatrix.jl

@@ -401,3 +401,57 @@ function sum(A::AbstractBandedMatrix; dims=:)
         throw(ArgumentError("dimension must be ≥ 1, got $dims"))
     end
 end
+
+###
+# vcat
+###
+
+function LinearAlgebra.vcat(x::AbstractBandedMatrix...)
+    #avoid unnecessary steps for singleton
+    if length(x) == 1
+        return x[1]
+    end
+
+    #instantiate the returned banded matrix with zeros and required bandwidths/dimensions
+    m = size(x[1], 2)
+    l,u = -m, typemin(Int64)
+    n = 0
+    isempty = true
+
+    #Check for dimension error and calculate bandwidths
+    for A in x
+        if size(A, 2) != m
+            sizes = Tuple(size(b, 2) for b in x)
+            throw(DimensionMismatch("number of columns of each matrix must match (got $sizes)"))
+        end
+
+        l_A, u_A = bandwidths(A)
+        if l_A + u_A >= 0
+            isempty = false
+            u = max(u, min(m - 1, u_A) - n)
+            l = max(l, min(size(A, 1) - 1, l_A) + n)
+        end
+
+        n += size(A, 1)
+    end
+
+    type = promote_type(eltype.(x)...)
+    if isempty
+        return BandedMatrix{type}(undef, (n, m), bandwidths(Zeros(1)))
+    end
+    ret = BandedMatrix(Zeros{type}(n, m), (l, u))
+
+    #Populate the banded matrix
+    row_offset = 0
+    for A in x
+        n_A = size(A, 1)
+
+        for i = 1:n_A, j = rowrange(A, i)
+            ret[row_offset + i, j] = A[i, j]
+        end
+
+        row_offset += n_A
+    end
+
+    ret
+end

src/interfaceimpl.jl

@@ -116,3 +116,6 @@ function getindex(D::Bidiagonal{T,V}, b::Band) where {T,V}
     D.uplo == 'U' && b.i == 1 && return copy(D.ev)
     convert(V, Zeros{T}(size(D,1)-abs(b.i)))
 end
+
+
+Base.vcat(x::Union{OneElement, ZerosMatrix, AdjOrTrans{<:Any,<:ZerosVector}, AbstractBandedMatrix}...) = vcat(BandedMatrix.(x)...)

test/runtests.jl

@@ -27,3 +27,4 @@ include("test_tribanded.jl")
 include("test_interface.jl")
 include("test_miscs.jl")
 include("test_sum.jl")
+include("test_cat.jl")

test/test_cat.jl

@@ -0,0 +1,37 @@
+module TestCat
+
+using BandedMatrices, LinearAlgebra, Test, Random, FillArrays, SparseArrays
+
+@testset "vcat" begin
+    @testset "banded matrices" begin
+        a = BandedMatrix(0 => 1:2)
+        @test vcat(a) == a
+
+        b = BandedMatrix(0 => 1:3,-1 => 1:2, -2 => 1:1)
+        @test_throws DimensionMismatch vcat(a,b)
+
+        c = BandedMatrix(0 => [1.0, 2.0, 3.0], 1 => [1.0, 2.0], 2 => [1.0])
+        @test eltype(vcat(b, c)) == Float64
+        @test vcat(b, c) == vcat(Matrix(b), Matrix(c))
+
+        for i in ((1,2), (-3,4), (0,-1))
+            a = BandedMatrix(ones(Float64, rand(1:10), 5), i)
+            b = BandedMatrix(ones(Int64, rand(1:10), 5), i)
+            c = BandedMatrix(ones(Int32, rand(1:10), 5), i)
+            d = vcat(a, b, c)
+            sd = vcat(sparse(a), sparse(b), sparse(c))
+            @test eltype(d) == Float64
+            @test d == sd
+            @test bandwidths(d) == bandwidths(sd)
+        end
+    end
+
+    @testset "one element" begin
+        n = rand(3:20)
+        x,y = OneElement(1, (1,1), (1,n)), OneElement(1, (1,n), (1,n))
+        b = BandedMatrix((0 => ones(n-2), 1 => -2ones(n - 2), 2 => ones(n - 2)), (n-2, n))
+        @test vcat(x,b,y) == Tridiagonal([ones(n - 2); 0], [1 ; -2ones(n - 2); 1], [0; ones(n - 2)])
+    end
+end
+
+end