Sparse matrices with Int indices (#62)

adrhill · May 14, 2024 · 57e3e73 · 57e3e73
1 parent 95607e0
commit 57e3e73
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Showing 3 changed files with 15 additions and 14 deletions.
diff --git a/src/adtypes.jl b/src/adtypes.jl
@@ -9,7 +9,7 @@ Singleton struct for integration with the sparsity detection framework of ADType
 julia> using ADTypes, SparseConnectivityTracer
 
 julia> ADTypes.jacobian_sparsity(diff, rand(4), TracerSparsityDetector())
-3×4 SparseArrays.SparseMatrixCSC{Bool, UInt64} with 6 stored entries:
+3×4 SparseArrays.SparseMatrixCSC{Bool, Int64} with 6 stored entries:
  1  1  ⋅  ⋅
  ⋅  1  1  ⋅
  ⋅  ⋅  1  1
@@ -21,7 +21,7 @@ julia> using ADTypes, SparseConnectivityTracer
 julia> f(x) = x[1] + x[2]*x[3] + 1/x[4];
 
 julia> ADTypes.hessian_sparsity(f, rand(4), TracerSparsityDetector())
-4×4 SparseArrays.SparseMatrixCSC{Bool, UInt64} with 3 stored entries:
+4×4 SparseArrays.SparseMatrixCSC{Bool, Int64} with 3 stored entries:
  ⋅  ⋅  ⋅  ⋅
  ⋅  ⋅  1  ⋅
  ⋅  1  ⋅  ⋅

diff --git a/src/pattern.jl b/src/pattern.jl
@@ -51,7 +51,7 @@ julia> x = rand(3);
 julia> f(x) = [x[1]^2, 2 * x[1] * x[2]^2, sign(x[3])];
 
 julia> connectivity_pattern(f, x)
-3×3 SparseArrays.SparseMatrixCSC{Bool, UInt64} with 4 stored entries:
+3×3 SparseArrays.SparseMatrixCSC{Bool, Int64} with 4 stored entries:
  1  ⋅  ⋅
  1  1  ⋅
  ⋅  ⋅  1
@@ -82,8 +82,8 @@ function connectivity_pattern_to_mat(
     xt::AbstractArray{T}, yt::AbstractArray{<:Number}
 ) where {T<:ConnectivityTracer}
     n, m = length(xt), length(yt)
-    I = UInt64[] # row indices
-    J = UInt64[] # column indices
+    I = Int[] # row indices
+    J = Int[] # column indices
     V = Bool[]   # values
     for (i, y) in enumerate(yt)
         if y isa T
@@ -113,7 +113,7 @@ julia> x = rand(3);
 julia> f(x) = [x[1]^2, 2 * x[1] * x[2]^2, sign(x[3])];
 
 julia> jacobian_pattern(f, x)
-3×3 SparseArrays.SparseMatrixCSC{Bool, UInt64} with 3 stored entries:
+3×3 SparseArrays.SparseMatrixCSC{Bool, Int64} with 3 stored entries:
  1  ⋅  ⋅
  1  1  ⋅
  ⋅  ⋅  ⋅
@@ -143,8 +143,8 @@ function jacobian_pattern_to_mat(
     xt::AbstractArray{T}, yt::AbstractArray{<:Number}
 ) where {T<:JacobianTracer}
     n, m = length(xt), length(yt)
-    I = UInt64[] # row indices
-    J = UInt64[] # column indices
+    I = Int[] # row indices
+    J = Int[] # column indices
     V = Bool[]   # values
     for (i, y) in enumerate(yt)
         if y isa T
@@ -174,7 +174,7 @@ julia> x = rand(5);
 julia> f(x) = x[1] + x[2]*x[3] + 1/x[4] + 1*x[5];
 
 julia> hessian_pattern(f, x)
-5×5 SparseArrays.SparseMatrixCSC{Bool, UInt64} with 3 stored entries:
+5×5 SparseArrays.SparseMatrixCSC{Bool, Int64} with 3 stored entries:
  ⋅  ⋅  ⋅  ⋅  ⋅
  ⋅  ⋅  1  ⋅  ⋅
  ⋅  1  ⋅  ⋅  ⋅
@@ -184,7 +184,7 @@ julia> hessian_pattern(f, x)
 julia> g(x) = f(x) + x[2]^x[5];
 
 julia> hessian_pattern(g, x)
-5×5 SparseArrays.SparseMatrixCSC{Bool, UInt64} with 7 stored entries:
+5×5 SparseArrays.SparseMatrixCSC{Bool, Int64} with 7 stored entries:
  ⋅  ⋅  ⋅  ⋅  ⋅
  ⋅  1  1  ⋅  1
  ⋅  1  ⋅  ⋅  ⋅
@@ -204,8 +204,8 @@ function hessian_pattern_to_mat(
 ) where {TI,S,D}
     # Allocate Hessian matrix
     n = length(xt)
-    I = UInt64[] # row indices
-    J = UInt64[] # column indices
+    I = Int[] # row indices
+    J = Int[] # column indices
     V = Bool[]   # values
 
     for i in keys(yt.inputs)

diff --git a/test/adtypes.jl b/test/adtypes.jl
@@ -10,8 +10,8 @@ y = zeros(9)
 J1 = jacobian_sparsity(diff, x, sd)
 J2 = jacobian_sparsity((y, x) -> y .= diff(x), y, x, sd)
 @test J1 == J2
-@test J1 isa SparseMatrixCSC
-@test J2 isa SparseMatrixCSC
+@test J1 isa SparseMatrixCSC{Bool,Int}
+@test J2 isa SparseMatrixCSC{Bool,Int}
 @test nnz(J1) == nnz(J2) == 18
 
 H1 = hessian_sparsity(x -> sum(diff(x)), x, sd)
@@ -20,6 +20,7 @@ H1 = hessian_sparsity(x -> sum(diff(x)), x, sd)
 x = rand(5)
 f(x) = x[1] + x[2] * x[3] + 1 / x[4] + 1 * x[5]
 H2 = hessian_sparsity(f, x, sd)
+@test H2 isa SparseMatrixCSC{Bool,Int}
 @test H2 ≈ [
     0 0 0 0 0
     0 0 1 0 0