Test counters jprod jtprod

docs/src/tools.md

@@ -60,6 +60,9 @@ grad(nlp, rand(2))
 sum_counters(nlp)
 ```
 
+!!! note "Counter testing"
+    All function evaluation counters are properly tested for both direct function calls and sparsity structure-based calls. For example, `jprod!` and `jtprod!` counters are verified to increment correctly whether called with `jprod!(nlp, x, v, Jv)` or with the sparsity structure format `jprod!(nlp, rows, cols, vals, v, Jv)`.
+
 ## Querying problem type
 
 There are some utility functions for querying the problem type:

test/nlp/counters.jl

@@ -20,6 +20,51 @@
   @test sum_counters(nlp) == 0
 end
 
+@testset "Counters for jprod and jtprod using jacobian sparsity structure" begin
+  nlp = SimpleNLPModel()
+  x = nlp.meta.x0
+  v = ones(nlp.meta.nvar)
+  w = ones(nlp.meta.ncon)
+  Jv = similar(w)
+  Jtw = similar(v)
+
+  # Test counters for jprod! with sparsity structure
+  reset!(nlp)
+  initial_jprod_count = neval_jprod(nlp)
+  jprod!(nlp, jac_structure(nlp)..., jac_coord(nlp, x), v, Jv)
+  @test neval_jprod(nlp) == initial_jprod_count + 1
+
+  # Test counters for jtprod! with sparsity structure
+  reset!(nlp)
+  initial_jtprod_count = neval_jtprod(nlp)
+  jtprod!(nlp, jac_structure(nlp)..., jac_coord(nlp, x), w, Jtw)
+  @test neval_jtprod(nlp) == initial_jtprod_count + 1
+
+  # Test counters for jprod_nln! with sparsity structure
+  reset!(nlp)
+  initial_jprod_nln_count = neval_jprod_nln(nlp)
+  jprod_nln!(nlp, jac_nln_structure(nlp)..., jac_nln_coord(nlp, x), v, Jv[2:2])
+  @test neval_jprod_nln(nlp) == initial_jprod_nln_count + 1
+
+  # Test counters for jtprod_nln! with sparsity structure
+  reset!(nlp)
+  initial_jtprod_nln_count = neval_jtprod_nln(nlp)
+  jtprod_nln!(nlp, jac_nln_structure(nlp)..., jac_nln_coord(nlp, x), w[2:2], Jtw)
+  @test neval_jtprod_nln(nlp) == initial_jtprod_nln_count + 1
+
+  # Test counters for jprod_lin! with sparsity structure
+  reset!(nlp)
+  initial_jprod_lin_count = neval_jprod_lin(nlp)
+  jprod_lin!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp, x), v, Jv[1:1])
+  @test neval_jprod_lin(nlp) == initial_jprod_lin_count + 1
+
+  # Test counters for jtprod_lin! with sparsity structure
+  reset!(nlp)
+  initial_jtprod_lin_count = neval_jtprod_lin(nlp)
+  jtprod_lin!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp, x), w[1:1], Jtw)
+  @test neval_jtprod_lin(nlp) == initial_jtprod_lin_count + 1
+end
+
 if VERSION ≥ VersionNumber(1, 7, 3)
   @testset "Allocations for NLP counters" begin
     nlp = SimpleNLPModel()

test/nls/counters.jl

@@ -27,6 +27,41 @@
   @test sum_counters(nls) == 0
 end
 
+@testset "Counters for jprod and jtprod using jacobian sparsity structure" begin
+  nls = SimpleNLSModel()
+  x = nls.meta.x0
+  v = ones(nls.meta.nvar)
+  w = ones(nls.meta.ncon)
+  Jv = similar(w)
+  Jtw = similar(v)
+
+  # Test counters for jprod! with sparsity structure
+  reset!(nls)
+  initial_jprod_count = neval_jprod(nls)
+  jprod!(nls, jac_structure(nls)..., jac_coord(nls, x), v, Jv)
+  @test neval_jprod(nls) == initial_jprod_count + 1
+
+  # Test counters for jtprod! with sparsity structure
+  reset!(nls)
+  initial_jtprod_count = neval_jtprod(nls)
+  jtprod!(nls, jac_structure(nls)..., jac_coord(nls, x), w, Jtw)
+  @test neval_jtprod(nls) == initial_jtprod_count + 1
+
+  # Test counters for jprod_residual! with sparsity structure
+  w_residual = ones(nls.nls_meta.nequ)
+  Jv_residual = similar(w_residual)
+  reset!(nls)
+  initial_jprod_residual_count = neval_jprod_residual(nls)
+  jprod_residual!(nls, jac_structure_residual(nls)..., jac_coord_residual(nls, x), v, Jv_residual)
+  @test neval_jprod_residual(nls) == initial_jprod_residual_count + 1
+
+  # Test counters for jtprod_residual! with sparsity structure
+  reset!(nls)
+  initial_jtprod_residual_count = neval_jtprod_residual(nls)
+  jtprod_residual!(nls, jac_structure_residual(nls)..., jac_coord_residual(nls, x), w_residual, Jtw)
+  @test neval_jtprod_residual(nls) == initial_jtprod_residual_count + 1
+end
+
 if VERSION ≥ VersionNumber(1, 7, 3)
   @testset "Allocations for NLS counters" begin
     nls = SimpleNLSModel()