fixed sparsity pattern issue

Author: chmerdon

Project.toml

@@ -1,9 +1,10 @@
 name = "ExtendableFEM"
 uuid = "a722555e-65e0-4074-a036-ca7ce79a4aed"
-version = "1.3.0"
 authors = ["Christian Merdon <[email protected]>", "Patrick Jaap <[email protected]>"]
+version = "1.3.0"
 
 [deps]
+ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 CommonSolve = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
 DiffResults = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"
 DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
@@ -25,6 +26,7 @@ TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 UnicodePlots = "b8865327-cd53-5732-bb35-84acbb429228"
 
 [compat]
+ADTypes = "1.16.0"
 Aqua = "0.8"
 CommonSolve = "0.2"
 DiffResults = "1"

src/ExtendableFEM.jl

@@ -68,13 +68,13 @@ using LinearSolve: LinearSolve, LinearProblem, UMFPACKFactorization, deleteat!,
 using Printf: Printf, @printf, @sprintf
 using SparseArrays: SparseArrays, AbstractSparseArray, SparseMatrixCSC, findnz, nnz,
     nzrange, rowvals, sparse
-
+using ADTypes: ADTypes, KnownJacobianSparsityDetector
 using SparseConnectivityTracer: SparseConnectivityTracer, TracerSparsityDetector
 using DifferentiationInterface: DifferentiationInterface,
     AutoSparse,
     AutoForwardDiff,
     prepare_jacobian
-using SparseMatrixColorings: GreedyColoringAlgorithm #, sparsity_pattern
+using SparseMatrixColorings: GreedyColoringAlgorithm, sparsity_pattern
 using Symbolics: Symbolics
 using SciMLBase: SciMLBase
 using TimerOutputs: TimerOutput, print_timer, @timeit

src/common_operators/nonlinear_operator.jl

@@ -229,17 +229,21 @@ function build_assembler!(A::AbstractMatrix, b::AbstractVector, O::NonlinearOper
         Kj = Array{KernelEvaluator, 1}([])
 
         sparse_jacobians = O.parameters[:sparse_jacobians]
-        sparsity_pattern = O.parameters[:sparse_jacobians_pattern]
         use_autodiff = O.jacobian === nothing
         for EG in EGs
             ## prepare parameters
             QPj = QPInfos(xgrid; time = time, x = ones(Tv, size(xgrid[Coordinates], 1)), params = O.parameters[:params])
             kernel_params = (result, input) -> (O.kernel(result, input, QPj))
             input_args = zeros(Tv, op_offsets_args[end] + O.parameters[:extra_inputsize])
             result_kernel = zeros(Tv, op_offsets_test[end])
+            if O.parameters[:sparse_jacobians_pattern] === nothing
+                sparsity_detector = TracerSparsityDetector()
+            else
+                sparsity_detector = KnownJacobianSparsityDetector(O.parameters[:sparse_jacobians_pattern])
+            end
             sparse_forward_backend = AutoSparse(
                 O.parameters[:autodiff_backend];
-                sparsity_detector = TracerSparsityDetector(),
+                sparsity_detector = sparsity_detector,
                 coloring_algorithm = GreedyColoringAlgorithm()
             )
             jac_prep = prepare_jacobian(kernel_params, result_kernel, sparse_forward_backend, input_args)
@@ -287,9 +291,17 @@ function build_assembler!(A::AbstractMatrix, b::AbstractVector, O::NonlinearOper
             value = K.result_kernel
             jac_prep = K.jac_prep
             jac_backend = K.jac_backend
-            # todo: get sparse jacobians to work (need to extract sparsity pattern)
             sparse_jacobians = false
-            jac = zeros(Tv, length(value), length(input_args))
+            if sparse_jacobians
+                if O.parameters[:sparse_jacobians_pattern] === nothing
+                    jac_sparsity_pattern = DifferentiationInterface.sparsity_pattern(jac_prep)
+                else
+                    jac_sparsity_pattern = O.parameters[:sparse_jacobians_pattern]
+                end
+                jac = Tv.(sparse(sparsity_pattern))
+            else
+                jac = zeros(Tv, length(value), length(input_args))
+            end
             kernel_params = K.kernel
             params.time = time