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‎src/sparse_array.jl‎

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Base.:*(scalar::Number, A::SparseArray) = A * scalar
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# Base show method (without MIME) - delegates to text/plain
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function Base.show(io::IO, A::SparseArray{T, N}) where {T, N}
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show(io, MIME"text/plain"(), A)
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end
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# Improved display with better formatting
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function Base.show(io::IO, ::MIME"text/plain", A::SparseArray{T, N}) where {T, N}
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compact = get(io, :compact, false)

‎test/test_advanced_arithmetic.jl‎

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module TestAdvancedArithmetic
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using MultidimensionalSparseArrays
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using Test
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@testset "Advanced Arithmetic Operations" begin
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@testset "Addition Edge Cases" begin
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# Test addition with completely disjoint sparse patterns
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A = SparseArray{Int, 2}((3, 3))
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A[1, 1] = 5
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A[2, 2] = 10
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B = SparseArray{Int, 2}((3, 3))
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B[1, 3] = 3
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B[3, 1] = 7
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C = A + B
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@test C[1, 1] == 5
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@test C[2, 2] == 10
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@test C[1, 3] == 3
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@test C[3, 1] == 7
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@test nnz(C) == 4
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@test !hasindex(C, 2, 1)
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@test !hasindex(C, 3, 3)
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# Test addition with overlapping indices
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D = SparseArray{Int, 2}((3, 3))
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D[1, 1] = 2
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D[2, 3] = 8
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E = A + D
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@test E[1, 1] == 7 # 5 + 2
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@test E[2, 2] == 10 # 10 + 0 (D doesn't have [2,2])
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@test E[2, 3] == 8 # 0 + 8 (A doesn't have [2,3])
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@test nnz(E) == 3
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end
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@testset "Subtraction with Zero Results" begin
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A = SparseArray{Int, 2}((3, 3))
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A[1, 1] = 5
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A[2, 2] = 10
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A[1, 3] = 7
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B = SparseArray{Int, 2}((3, 3))
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B[1, 1] = 5 # Same as A[1,1] - should result in zero
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B[2, 2] = 3 # Different from A[2,2]
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B[3, 1] = 4 # Not in A
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C = A - B
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@test !hasindex(C, 1, 1) # 5 - 5 = 0, not stored
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@test C[2, 2] == 7 # 10 - 3 = 7
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@test C[1, 3] == 7 # 7 - 0 = 7
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@test C[3, 1] == -4 # 0 - 4 = -4
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@test nnz(C) == 3
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end
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@testset "Type Promotion in Arithmetic" begin
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# Int + Float64
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A = SparseArray{Int, 2}((2, 2))
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A[1, 1] = 5
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B = SparseArray{Float64, 2}((2, 2))
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B[1, 1] = 2.5
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B[2, 2] = 3.7
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C = A + B
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@test eltype(C) == Float64
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@test C[1, 1] == 7.5
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@test C[2, 2] == 3.7
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# Int + Complex
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D = SparseArray{Complex{Float64}, 2}((2, 2))
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D[1, 1] = 1.0 + 2.0im
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E = A + D
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@test eltype(E) == Complex{Float64}
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@test E[1, 1] == 6.0 + 2.0im
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# Rational arithmetic
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F = SparseArray{Rational{Int}, 2}((2, 2))
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F[1, 1] = 1//3
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G = SparseArray{Rational{Int}, 2}((2, 2))
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G[1, 1] = 1//6
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G[2, 1] = 2//3
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H = F + G
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@test H[1, 1] == 1//2 # 1/3 + 1/6 = 1/2
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@test H[2, 1] == 2//3
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end
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@testset "Scalar Multiplication Edge Cases" begin
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A = SparseArray{Float64, 2}((3, 3))
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A[1, 1] = 2.0
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A[2, 3] = -1.5
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A[3, 2] = 0.0 # Explicitly stored zero
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# Multiplication by zero
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B = A * 0
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@test nnz(B) == 0 # All values become zero, nothing stored
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# Multiplication by negative number
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C = A * (-2)
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@test C[1, 1] == -4.0
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@test C[2, 3] == 3.0
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@test C[3, 2] == 0.0
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@test nnz(C) == 3 # Zero is still stored
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# Multiplication by complex number
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D = A * (1 + 1im)
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@test eltype(D) == Complex{Float64}
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@test D[1, 1] == 2.0 + 2.0im
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@test D[2, 3] == -1.5 - 1.5im
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# Left multiplication
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E = (2 + 3im) * A
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@test E[1, 1] == 4.0 + 6.0im
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@test E[2, 3] == -3.0 - 4.5im
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end
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@testset "Large Sparse Array Arithmetic" begin
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# Test arithmetic on larger arrays to ensure efficiency
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A = SparseArray{Float64, 2}((100, 100))
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B = SparseArray{Float64, 2}((100, 100))
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# Add sparse diagonal pattern
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for i in 1:10:100
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A[i, i] = Float64(i)
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B[i, i] = Float64(i) * 0.5
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end
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# Add some off-diagonal elements
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A[25, 75] = 12.5
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B[75, 25] = 8.3
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C = A + B
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@test nnz(C) == 12 # 10 diagonal + 2 off-diagonal
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@test C[11, 11] == 16.5 # 11 + 5.5
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@test C[25, 75] == 12.5
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@test C[75, 25] == 8.3
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# Scalar multiplication should preserve sparsity
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D = A * 2.0
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@test nnz(D) == nnz(A)
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end
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@testset "Arithmetic with Different Dimensions" begin
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A = SparseArray{Int, 3}((2, 2, 2))
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A[1, 1, 1] = 5
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A[2, 2, 2] = 10
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B = SparseArray{Int, 3}((2, 2, 2))
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B[1, 1, 1] = 3
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B[1, 2, 1] = 7
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C = A + B
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@test C[1, 1, 1] == 8
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@test C[2, 2, 2] == 10
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@test C[1, 2, 1] == 7
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@test nnz(C) == 3
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end
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@testset "Arithmetic Result Optimization" begin
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# Test that arithmetic operations don't store unnecessary zeros
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A = SparseArray{Float64, 2}((3, 3))
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A[1, 1] = 5.0
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A[2, 2] = 3.0
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B = SparseArray{Float64, 2}((3, 3))
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B[1, 1] = 5.0 # Will cancel out in subtraction
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B[3, 3] = 2.0
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C = A - B
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@test !hasindex(C, 1, 1) # Should not store 5.0 - 5.0 = 0.0
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@test C[2, 2] == 3.0
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@test C[3, 3] == -2.0
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@test nnz(C) == 2
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end
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@testset "Precision and Floating Point Arithmetic" begin
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A = SparseArray{Float64, 2}((2, 2))
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A[1, 1] = 0.1 + 0.2 # This is 0.30000000000000004 in floating point
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B = SparseArray{Float64, 2}((2, 2))
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B[1, 1] = 0.3
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C = A - B
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# The result should be close to zero but not exactly zero due to floating point precision
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@test hasindex(C, 1, 1)
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@test abs(C[1, 1]) < 1e-15
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@test C[1, 1] != 0.0
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end
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@testset "Chain Operations" begin
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A = SparseArray{Int, 2}((3, 3))
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A[1, 1] = 1
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A[2, 2] = 2
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B = SparseArray{Int, 2}((3, 3))
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B[1, 1] = 1
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B[1, 3] = 3
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C = SparseArray{Int, 2}((3, 3))
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C[2, 2] = 1
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C[3, 1] = 4
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# Test (A + B) - C
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D = (A + B) - C
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@test D[1, 1] == 2 # (1 + 1) - 0 = 2
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@test D[2, 2] == 1 # (2 + 0) - 1 = 1
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@test D[1, 3] == 3 # (0 + 3) - 0 = 3
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@test D[3, 1] == -4 # (0 + 0) - 4 = -4
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@test nnz(D) == 4
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end
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end
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end

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