Use a String for the structure

README.md

@@ -46,7 +46,7 @@ A_gpu = CuSparseMatrixCSR(A_cpu)
 x_gpu = CuVector(x_cpu)
 b_gpu = CuVector(b_cpu)
 
-solver = CudssSolver(A_gpu, 'G', 'F')
+solver = CudssSolver(A_gpu, "G", 'F')
 
 cudss("analysis", solver, x_gpu, b_gpu)
 cudss("factorization", solver, x_gpu, b_gpu)
@@ -75,7 +75,7 @@ A_gpu = CuSparseMatrixCSR(A_cpu |> tril)
 X_gpu = CuMatrix(X_cpu)
 B_gpu = CuMatrix(B_cpu)
 
-structure = T <: Real ? 'S' : 'H'
+structure = T <: Real ? "S" : "H"
 solver = CudssSolver(A_gpu, structure, 'L')
 
 cudss("analysis", solver, X_gpu, B_gpu)

src/helpers.jl

@@ -6,15 +6,15 @@ export CudssMatrix, CudssData, CudssConfig
 """
     matrix = CudssMatrix(v::CuVector)
     matrix = CudssMatrix(A::CuMatrix)
-    matrix = CudssMatrix(A::CuSparseMatrixCSR, struture::Union{Char, String}, view::Char; index::Char='O')
+    matrix = CudssMatrix(A::CuSparseMatrixCSR, struture::String, view::Char; index::Char='O')
 
 `CudssMatrix` is a wrapper for `CuVector`, `CuMatrix` and `CuSparseMatrixCSR`.
 `CudssMatrix` is used to pass matrix of the linear system, as well as solution and right-hand side.
 
 `structure` specifies the stucture for sparse matrices:
-- `'G'` or `"G"`: General matrix -- LDU factorization;
-- `'S'` or `"S"`: Real symmetric matrix -- LDLᵀ factorization;
-- `'H'` or `"H"`: Complex Hermitian matrix -- LDLᴴ factorization;
+- `"G"`: General matrix -- LDU factorization;
+- `"S"`: Real symmetric matrix -- LDLᵀ factorization;
+- `"H"`: Complex Hermitian matrix -- LDLᴴ factorization;
 - `"SPD"`: Symmetric positive-definite matrix -- LLᵀ factorization;
 - `"HPD"`: Hermitian positive-definite matrix -- LLᴴ factorization.
 
@@ -52,7 +52,7 @@ mutable struct CudssMatrix
         obj
     end
 
-    function CudssMatrix(A::CuSparseMatrixCSR, structure::Union{Char, String}, view::Char; index::Char='O')
+    function CudssMatrix(A::CuSparseMatrixCSR, structure::String, view::Char; index::Char='O')
         m,n = size(A)
         matrix_ref = Ref{cudssMatrix_t}()
         cudssMatrixCreateCsr(matrix_ref, m, n, nnz(A), A.rowPtr, CU_NULL,

src/interfaces.jl

@@ -1,16 +1,16 @@
 export CudssSolver, cudss, cudss_set, cudss_get
 
 """
-    solver = CudssSolver(A::CuSparseMatrixCSR, structure::Union{Char, String}, view::Char; index::Char='O')
+    solver = CudssSolver(A::CuSparseMatrixCSR, structure::String, view::Char; index::Char='O')
     solver = CudssSolver(matrix::CudssMatrix, config::CudssConfig, data::CudssData)
 
 `CudssSolver` contains all structures required to solve linear systems with cuDSS.
 One constructor of `CudssSolver` takes as input the same parameters as [`CudssMatrix`](@ref).
 
 `structure` specifies the stucture for sparse matrices:
-- `'G'` or `"G"`: General matrix -- LDU factorization;
-- `'S'` or `"S"`: Real symmetric matrix -- LDLᵀ factorization;
-- `'H'` or `"H"`: Complex Hermitian matrix -- LDLᴴ factorization;
+- `"G"`: General matrix -- LDU factorization;
+- `"S"`: Real symmetric matrix -- LDLᵀ factorization;
+- `"H"`: Complex Hermitian matrix -- LDLᴴ factorization;
 - `"SPD"`: Symmetric positive-definite matrix -- LLᵀ factorization;
 - `"HPD"`: Hermitian positive-definite matrix -- LLᴴ factorization.
 
@@ -34,7 +34,7 @@ mutable struct CudssSolver
     return new(matrix, config, data)
   end
 
-  function CudssSolver(A::CuSparseMatrixCSR, structure::Union{Char, String}, view::Char; index::Char='O')
+  function CudssSolver(A::CuSparseMatrixCSR, structure::String, view::Char; index::Char='O')
     matrix = CudssMatrix(A, structure, view; index)
     config = CudssConfig()
     data = CudssData()

src/types.jl

@@ -58,18 +58,6 @@ end
 
 ## matrix structure type
 
-function Base.convert(::Type{cudssMatrixType_t}, structure::Char)
-    if structure == 'G'
-        return CUDSS_MTYPE_GENERAL
-    elseif structure == 'S'
-        return CUDSS_MTYPE_SYMMETRIC
-    elseif structure == 'H'
-        return CUDSS_MTYPE_HERMITIAN
-    else
-        throw(ArgumentError("Unknown structure $structure"))
-    end
-end
-
 function Base.convert(::Type{cudssMatrixType_t}, structure::String)
     if structure == "G"
         return CUDSS_MTYPE_GENERAL

test/test_cudss.jl

@@ -41,7 +41,7 @@ function cudss_sparse()
     A_cpu = A_cpu + A_cpu'
     A_gpu = CuSparseMatrixCSR(A_cpu)
     @testset "view = $view" for view in ('L', 'U', 'F')
-      @testset "structure = $structure" for structure in ('G', "G", 'S', "S", 'H', "H", "SPD", "HPD")
+      @testset "structure = $structure" for structure in ("G", "S", "H", "SPD", "HPD")
         matrix = CudssMatrix(A_gpu, structure, view) 
         format = Ref{CUDSS.cudssMatrixFormat_t}()
         CUDSS.cudssMatrixGetFormat(matrix, format)
@@ -62,7 +62,7 @@ function cudss_solver()
     A_cpu = sprand(T, n, n, 1.0)
     A_cpu = A_cpu + A_cpu'
     A_gpu = CuSparseMatrixCSR(A_cpu)
-    @testset "structure = $structure" for structure in ('G', "G", 'S', "S", 'H', "H", "SPD", "HPD")
+    @testset "structure = $structure" for structure in ("G", "S", "H", "SPD", "HPD")
       @testset "view = $view" for view in ('L', 'U', 'F')
         solver = CudssSolver(A_gpu, structure, view)
 
@@ -95,7 +95,7 @@ function cudss_solver()
         @testset "data parameter = $parameter" for parameter in CUDSS_DATA_PARAMETERS
           parameter ∈ ("perm_row", "perm_col", "perm_reorder", "diag") && continue
           if parameter ≠ "user_perm"
-            (parameter == "inertia") && !(structure ∈ ('S', "S", 'H', "H")) && continue
+            (parameter == "inertia") && !(structure ∈ ("S", "H")) && continue
             val = cudss_get(solver, parameter)
           else
             perm = Cint[i for i=n:-1:1]
@@ -121,7 +121,7 @@ function cudss_execution()
       x_gpu = CuVector(x_cpu)
       b_gpu = CuVector(b_cpu)
 
-      matrix = CudssMatrix(A_gpu, 'G', 'F')
+      matrix = CudssMatrix(A_gpu, "G", 'F')
       config = CudssConfig()
       data = CudssData()
       solver = CudssSolver(matrix, config, data)
@@ -147,12 +147,12 @@ function cudss_execution()
         X_gpu = CuMatrix(X_cpu)
         B_gpu = CuMatrix(B_cpu)
 
-        structure = T <: Real ? 'S' : 'H'
+        structure = T <: Real ? "S" : "H"
         matrix = CudssMatrix(A_gpu, structure, view)
         config = CudssConfig()
         data = CudssData()
         solver = CudssSolver(matrix, config, data)
-        (structure == 'H') && cudss_set(solver, "pivot_type", 'N')
+        (structure == "H") && cudss_set(solver, "pivot_type", 'N')
 
         cudss("analysis", solver, X_gpu, B_gpu)
         cudss("factorization", solver, X_gpu, B_gpu)