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Correct effective degrees of freedom computation for fpca_direct #16

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Correct effective degrees of freedom computation for fpca_direct #16

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3653ec2
bugfix: correct dof computation for fpca_direct
marcogalliani Oct 27, 2025
d4020fa
bug fix: fpca unable to accept vector of smoothing parameters
AlePalu Feb 8, 2026
fa20b6e
chore: point submodule to my fork.
marcogalliani Jun 17, 2026
98d5295
Merge branch 'stable' of github.com:fdaPDE/fdaPDE-cpp into stable
marcogalliani Jun 17, 2026
0120619
chore: update submodule reference to latest commit
marcogalliani Jun 17, 2026
8a0341b
core updates.
marcogalliani Jun 18, 2026
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2 changes: 2 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -30,3 +30,5 @@ cmake-build-debug/
#docs files
*.puml
.Rproj.user

experiments/
2 changes: 1 addition & 1 deletion .gitmodules
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
[submodule "fdaPDE/core"]
path = fdaPDE/core
url = https://github.com/fdaPDE/fdaPDE-core
url = https://github.com/marcogalliani/fdaPDE-core
branch = stable
2 changes: 1 addition & 1 deletion fdaPDE/core
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Submodule core updated 34 files
+3 −39 fdaPDE/optimization.h
+1 −1 fdaPDE/src/assembly.h
+1 −0 fdaPDE/src/fields/matrix_field.h
+1 −2 fdaPDE/src/fields/spline.h
+16 −13 fdaPDE/src/finite_elements/fe_assembler_base.h
+30 −25 fdaPDE/src/finite_elements/fe_evaluator.h
+62 −48 fdaPDE/src/geoframe/data_layer.h
+18 −5 fdaPDE/src/geoframe/geo_layer.h
+12 −11 fdaPDE/src/geoframe/geoframe.h
+2 −6 fdaPDE/src/linear_algebra/rp_chol.h
+66 −65 fdaPDE/src/linear_algebra/sparse_block_matrix.h
+7 −7 fdaPDE/src/optimization/backtracking_line_search.h
+54 −38 fdaPDE/src/optimization/bfgs.h
+22 −45 fdaPDE/src/optimization/callbacks.h
+0 −131 fdaPDE/src/optimization/conjugate_gradient.h
+38 −38 fdaPDE/src/optimization/gradient_descent.h
+99 −0 fdaPDE/src/optimization/grid.h
+0 −104 fdaPDE/src/optimization/grid_search.h
+72 −46 fdaPDE/src/optimization/lbfgs.h
+0 −195 fdaPDE/src/optimization/nelder_mead.h
+39 −41 fdaPDE/src/optimization/newton.h
+0 −96 fdaPDE/src/optimization/wolfe.h
+69 −0 fdaPDE/src/optimization/wolfe_line_search.h
+1 −1 fdaPDE/src/splines/bs_space.h
+16 −13 fdaPDE/src/splines/sp_assembler_base.h
+3 −1 fdaPDE/src/splines/sp_bilinear_form_assembler.h
+3 −1 fdaPDE/src/splines/sp_linear_form_assembler.h
+19 −11 fdaPDE/src/splines/sp_objects.h
+0 −12 fdaPDE/src/utility/binary.h
+2 −52 fdaPDE/src/utility/matrix.h
+43 −22 fdaPDE/src/utility/meta.h
+4 −4 test/main.cpp
+38 −50 test/src/rand_linear_algebra_test.cpp
+25 −19 test/src/utils/utils.h
21 changes: 12 additions & 9 deletions fdaPDE/src/models/fpca.h
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Expand Up @@ -77,7 +77,8 @@ template <typename VariationalSolver> class fpca_power_iteration_impl {
case OptimizeGCV: {
auto gcv_functor = [&](auto lambda) { return gcv_(X, lambda, V.col(i)); };
GridSearch<n_lambda> optimizer;
opt_lambda = optimizer.optimize(gcv_functor, lambda_grid);
auto opt_ = optimizer.optimize(gcv_functor, lambda_grid);
for (int i = 0; i < n_lambda; ++i) { opt_lambda[i] = opt_[i]; }
} break;
case OptimizeMSRE: {
} break;
Expand Down Expand Up @@ -134,12 +135,12 @@ template <typename VariationalSolver> class fpca_power_iteration_impl {
double gcv_(const matrix_t& X, const LambdaT lambda, const InitT& f0) {
const auto& [f, s] = solve_(X, lambda, f0);
// evaluate GCV index at convergence
std::array<double, n_lambda> lambda_vec;
std::copy(lambda.data(), lambda.data() + n_lambda, lambda_vec.begin());
if (edf_map_.find(lambda_vec) == edf_map_.end()) { // cache Tr[S]
edf_map_[lambda_vec] = smoother_->edf();
std::array<double, n_lambda> lambda_;
for (int i = 0; i < n_lambda; ++i) { lambda_[i] = lambda[i]; }
if (edf_map_.find(lambda_) == edf_map_.end()) { // cache Tr[S]
edf_map_[lambda_] = smoother_->edf();
}
int dor = n_locs_ - edf_map_.at(lambda_vec);
int dor = n_locs_ - edf_map_.at(lambda_);
return (n_locs_ / std::pow(dor, 2)) * ((smoother_->Psi() * f) - smoother_->response()).squaredNorm();
}
std::unordered_map<std::array<double, n_lambda>, double, internals::std_array_hash<double, n_lambda>> edf_map_;
Expand Down Expand Up @@ -199,7 +200,8 @@ template <typename VariationalSolver> class fpca_subspace_iteration_impl {
case OptimizeGCV: {
auto gcv_functor = [&](auto lambda) { return gcv_(X, rank, lambda, V); };
GridSearch<n_lambda> optimizer;
opt_lambda = optimizer.optimize(gcv_functor, lambda_grid);
auto opt_ = optimizer.optimize(gcv_functor, lambda_grid);
for (int i = 0; i < n_lambda; ++i) { opt_lambda[i] = opt_[i]; }
} break;
case OptimizeMSRE: {
} break;
Expand Down Expand Up @@ -313,7 +315,8 @@ template <typename VariationalSolver> class fpca_direct_impl {
case OptimizeGCV: {
auto gcv_functor = [&](auto lambda) { return gcv_(X, rank, lambda, flag); };
GridSearch<n_lambda> optimizer;
opt_lambda = optimizer.optimize(gcv_functor, lambda_grid);
auto opt_ = optimizer.optimize(gcv_functor, lambda_grid);
for (int i = 0; i < n_lambda; ++i) { opt_lambda[i] = opt_[i]; }
} break;
case OptimizeMSRE: {
} break;
Expand Down Expand Up @@ -371,7 +374,7 @@ template <typename VariationalSolver> class fpca_direct_impl {
double gcv_(const matrix_t& X, int rank, const LambdaT lambda, int flag) {
const auto& [F, S] = solve_(X, rank, lambda, flag);
// evaluate GCV index at convergence (note that Tr[S] = \|D^(-1)\|_F^2)
int dor = n_locs_ - invD_.squaredNorm();
int dor = n_locs_ - (invD_*smoother_->Psi().transpose()).squaredNorm();
return (n_locs_ / std::pow(dor, 2)) * (X.transpose() * S - (smoother_->Psi() * F)).squaredNorm();
}
int n_locs_ = 0, n_units_ = 0, n_dofs_ = 0;
Expand Down