Break long lines in test/pardiso/pardiso.jl

JuliaFormater got stuck with this.

Author: j-fu

test/pardiso/pardiso.jl

@@ -18,24 +18,23 @@ cache_kwargs = (; abstol = 1e-8, reltol = 1e-8, maxiter = 30)
 
 prob2 = LinearProblem(A2, b2)
 
-algs=LinearSolve.SciMLLinearSolveAlgorithm[PardisoJL()]
-solvers=Pardiso.AbstractPardisoSolver[]
-extended_algs=LinearSolve.SciMLLinearSolveAlgorithm[PardisoJL()]
+algs = LinearSolve.SciMLLinearSolveAlgorithm[PardisoJL()]
+solvers = Pardiso.AbstractPardisoSolver[]
+extended_algs = LinearSolve.SciMLLinearSolveAlgorithm[PardisoJL()]
 
 if Pardiso.mkl_is_available()
-    push!(algs,MKLPardisoFactorize())
-    push!(solvers,Pardiso.MKLPardisoSolver())
-    extended_algs=vcat(extended_algs,[MKLPardisoFactorize(), MKLPardisoIterate()])
+    push!(algs, MKLPardisoFactorize())
+    push!(solvers, Pardiso.MKLPardisoSolver())
+    extended_algs = vcat(extended_algs, [MKLPardisoFactorize(), MKLPardisoIterate()])
     @info "Testing MKL Pardiso"
 end
-    
+
 if Pardiso.panua_is_available()
-    push!(algs,PanuaPardisoFactorize())
-    push!(solvers,Pardiso.PardisoSolver())
-    extended_algs=vcat(extended_algs,[PanuaPardisoFactorize(), PanuaPardisoIterate()])
+    push!(algs, PanuaPardisoFactorize())
+    push!(solvers, Pardiso.PardisoSolver())
+    extended_algs = vcat(extended_algs, [PanuaPardisoFactorize(), PanuaPardisoIterate()])
     @info "Testing Panua Pardiso"
-end    
-
+end
 
 for alg in extended_algs
     u = solve(prob1, alg; cache_kwargs...).u
@@ -46,25 +45,20 @@ for alg in extended_algs
     @test A2 * u ≈ b2
 end
 
-
-
 Random.seed!(10)
 A = sprand(n, n, 0.8);
 A2 = 2.0 .* A;
 b1 = rand(n);
 b2 = rand(n);
 prob = LinearProblem(copy(A), copy(b1))
 
-
 linsolve = init(prob, UMFPACKFactorization())
 sol11 = solve!(linsolve)
 linsolve = LinearSolve.set_b(sol11.cache, copy(b2))
 sol12 = solve!(linsolve)
 linsolve = LinearSolve.set_A(sol12.cache, copy(A2))
 sol13 = solve!(linsolve)
 
-
-
 for alg in algs
     linsolve = init(prob, alg)
     sol31 = solve!(linsolve)
@@ -77,29 +71,89 @@ for alg in algs
     @test sol13.u ≈ sol33.u
 end
 
-
 # Test for problem from #497
 function makeA()
     n = 60
-    colptr = [1, 4, 7, 11, 15, 17, 22, 26, 30, 34, 38, 40, 46, 50, 54, 58, 62, 64, 70, 74, 78, 82, 86, 88, 94, 98, 102, 106, 110, 112, 118, 122, 126, 130, 134, 136, 142, 146, 150, 154, 158, 160, 166, 170, 174, 178, 182, 184, 190, 194, 198, 202, 206, 208, 214, 218, 222, 224, 226, 228, 232]
-    rowval = [1, 3, 4, 1, 2, 4, 2, 4, 9, 10, 3, 5, 11, 12, 1, 3, 2, 4, 6, 11, 12, 2, 7, 9, 10, 2, 7, 8, 10, 8, 10, 15, 16, 9, 11, 17, 18, 7, 9, 2, 8, 10, 12, 17, 18, 8, 13, 15, 16, 8, 13, 14, 16, 14, 16, 21, 22, 15, 17, 23, 24, 13, 15, 8, 14, 16, 18, 23, 24, 14, 19, 21, 22, 14, 19, 20, 22, 20, 22, 27, 28, 21, 23, 29, 30, 19, 21, 14, 20, 22, 24, 29, 30, 20, 25, 27, 28, 20, 25, 26, 28, 26, 28, 33, 34, 27, 29, 35, 36, 25, 27, 20, 26, 28, 30, 35, 36, 26, 31, 33, 34, 26, 31, 32, 34, 32, 34, 39, 40, 33, 35, 41, 42, 31, 33, 26, 32, 34, 36, 41, 42, 32, 37, 39, 40, 32, 37, 38, 40, 38, 40, 45, 46, 39, 41, 47, 48, 37, 39, 32, 38, 40, 42, 47, 48, 38, 43, 45, 46, 38, 43, 44, 46, 44, 46, 51, 52, 45, 47, 53, 54, 43, 45, 38, 44, 46, 48, 53, 54, 44, 49, 51, 52, 44, 49, 50, 52, 50, 52, 57, 58, 51, 53, 59, 60, 49, 51, 44, 50, 52, 54, 59, 60, 50, 55, 57, 58, 50, 55, 56, 58, 56, 58, 57, 59, 55, 57, 50, 56, 58, 60]
-    nzval = [-0.64, 1.0, -1.0, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -1.0806825309567203, 1.0, 2.370597639417811, -2.3705976394178108, 10.698449178570607, -11.083604432603583, -0.2770901108150896, 1.0]
+    colptr = [1, 4, 7, 11, 15, 17, 22, 26, 30, 34, 38, 40, 46, 50, 54, 58,
+        62, 64, 70, 74, 78, 82, 86, 88, 94, 98, 102, 106, 110, 112,
+        118, 122, 126, 130, 134, 136, 142, 146, 150, 154, 158, 160,
+        166, 170, 174, 178, 182, 184, 190, 194, 198, 202, 206, 208,
+        214, 218, 222, 224, 226, 228, 232]
+    rowval = [1, 3, 4, 1, 2, 4, 2, 4, 9, 10, 3, 5, 11, 12, 1, 3, 2, 4, 6,
+        11, 12, 2, 7, 9, 10, 2, 7, 8, 10, 8, 10, 15, 16, 9, 11, 17,
+        18, 7, 9, 2, 8, 10, 12, 17, 18, 8, 13, 15, 16, 8, 13, 14, 16,
+        14, 16, 21, 22, 15, 17, 23, 24, 13, 15, 8, 14, 16, 18, 23, 24,
+        14, 19, 21, 22, 14, 19, 20, 22, 20, 22, 27, 28, 21, 23, 29, 30,
+        19, 21, 14, 20, 22, 24, 29, 30, 20, 25, 27, 28, 20, 25, 26, 28,
+        26, 28, 33, 34, 27, 29, 35, 36, 25, 27, 20, 26, 28, 30, 35, 36,
+        26, 31, 33, 34, 26, 31, 32, 34, 32, 34, 39, 40, 33, 35, 41, 42,
+        31, 33, 26, 32, 34, 36, 41, 42, 32, 37, 39, 40, 32, 37, 38, 40,
+        38, 40, 45, 46, 39, 41, 47, 48, 37, 39, 32, 38, 40, 42, 47, 48,
+        38, 43, 45, 46, 38, 43, 44, 46, 44, 46, 51, 52, 45, 47, 53, 54,
+        43, 45, 38, 44, 46, 48, 53, 54, 44, 49, 51, 52, 44, 49, 50, 52,
+        50, 52, 57, 58, 51, 53, 59, 60, 49, 51, 44, 50, 52, 54, 59, 60,
+        50, 55, 57, 58, 50, 55, 56, 58, 56, 58, 57, 59, 55, 57, 50, 56,
+        58, 60]
+    nzval = [-0.64, 1.0, -1.0, 0.8606811145510832, -13.792569659442691, 1.0,
+        0.03475000000000006, 1.0, -0.03510101010101016, -0.975,
+        -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, -11.083604432603583, -0.2770901108150896,
+        1.0, -0.025, -0.95, -0.3564, -0.64, 1.0, -1.0, 13.792569659442691,
+        0.8606811145510832, -13.792569659442691, 1.0, 0.03475000000000006,
+        1.0, -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95,
+        -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607,
+        -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564,
+        -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832,
+        -13.792569659442691, 1.0, 0.03475000000000006, 1.0,
+        -0.03510101010101016, -0.975, -1.0806825309567203, 1.0, -0.95,
+        -0.025, 2.370597639417811, -2.3705976394178108, 10.698449178570607,
+        -11.083604432603583, -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564,
+        -0.64, 1.0, -1.0, 13.792569659442691, 0.8606811145510832,
+        -13.792569659442691, 1.0, 0.03475000000000006, 1.0, -0.03510101010101016,
+        -0.975, -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, 10.698449178570607, -11.083604432603583,
+        -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0,
+        -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691,
+        1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975,
+        -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, 10.698449178570607, -11.083604432603583,
+        -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0,
+        -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691,
+        1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975,
+        -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, 10.698449178570607, -11.083604432603583,
+        -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0,
+        -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691,
+        1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975,
+        -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, 10.698449178570607, -11.083604432603583,
+        -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0,
+        -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691,
+        1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975,
+        -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, 10.698449178570607, -11.083604432603583,
+        -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0,
+        -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691,
+        1.0, 0.03475000000000006, 1.0, -0.03510101010101016, -0.975,
+        -1.0806825309567203, 1.0, -0.95, -0.025, 2.370597639417811,
+        -2.3705976394178108, 10.698449178570607, -11.083604432603583,
+        -0.2770901108150896, 1.0, -0.025, -0.95, -0.3564, -0.64, 1.0,
+        -1.0, 13.792569659442691, 0.8606811145510832, -13.792569659442691,
+        1.0, 0.03475000000000006, 1.0, -1.0806825309567203, 1.0,
+        2.370597639417811, -2.3705976394178108, 10.698449178570607,
+        -11.083604432603583, -0.2770901108150896, 1.0]
     A = SparseMatrixCSC(n, n, colptr, rowval, nzval)
-    return(A)
+    return (A)
 end
 
-
 for alg in algs
-    A=makeA()
-    u0=fill(0.1,size(A,2))
-    linprob = LinearProblem(A, A*u0)
+    A = makeA()
+    u0 = fill(0.1, size(A, 2))
+    linprob = LinearProblem(A, A * u0)
     u = LinearSolve.solve(linprob, alg)
-    @test norm(u-u0) < 1.0e-14
+    @test norm(u - u0) < 1.0e-14
 end
 
-
-
-
 # Testing and demonstrating Pardiso.set_iparm! for MKLPardisoSolver
 for solver in solvers
     iparm = [
@@ -172,7 +226,7 @@ for solver in solvers
     for i in iparm
         Pardiso.set_iparm!(solver, i...)
     end
-    
+
     for i in Base.OneTo(length(iparm))
         @test Pardiso.get_iparm(solver, i) == iparm[i][2]
     end
@@ -195,22 +249,21 @@ end
         b0 = A0 * u0
         B0 = MySparseMatrixCSC2(A0)
         A1 = spdiagm(1 => -ones(N - 1), 0 => fill(100.0, N), -1 => -ones(N - 1))
-        b1=A1*u0
-        B1= MySparseMatrixCSC2(A1)
+        b1 = A1 * u0
+        B1 = MySparseMatrixCSC2(A1)
 
-        
         pr = LinearProblem(B0, b0)
         # test default algorithn
-        u=solve(pr,alg)
+        u = solve(pr, alg)
         @test norm(u - u0, Inf) < 1.0e-13
-    
+
         # test factorization with reinit!
         pr = LinearProblem(B0, b0)
-        cache=init(pr,alg)
-        u=solve!(cache)
+        cache = init(pr, alg)
+        u = solve!(cache)
         @test norm(u - u0, Inf) < 1.0e-13
-        reinit!(cache; A=B1, b=b1)
-        u=solve!(cache)
+        reinit!(cache; A = B1, b = b1)
+        u = solve!(cache)
         @test norm(u - u0, Inf) < 1.0e-13
     end
 end