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fix(graph_engine): fixed major bug with jacobian sparsity

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previousl the sparsity calculations for the jacobian matrix were completly broken. The method subgraph_sparsity was returning that all derivities were only depenednt on temperature and density. It should have been reporting that they also depended on some of the abundances. This was resolved by switching to a different structural sparsity engine (for_jac_sparsity). This bug had turned the solver into a fixed point iteration solver which failed for the stiff system we have. Now that it is resolved the solver can once again evolved over Gyr timescales.
This commit is contained in:
Emily Boudreaux
2025-10-29 14:47:11 -04:00
parent 66b2471c13
commit 23df87f915
9 changed files with 258 additions and 107 deletions
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125
src/lib/engine/engine_graph.cpp
View File

@@ -6,6 +6,7 @@
#include "gridfire/partition/partition_ground.h"
#include "gridfire/engine/procedures/construction.h"
#include "gridfire/utils/hashing.h"
#include "gridfire/utils/table_format.h"
#include "fourdst/composition/species.h"
#include "fourdst/composition/atomicSpecies.h"
@@ -164,6 +165,7 @@ namespace gridfire {
}
void GraphEngine::syncInternalMaps() {
LOG_INFO(m_logger, "Synchronizing internal maps for REACLIB graph network (serif::network::GraphNetwork)...");
collectNetworkSpecies();
populateReactionIDMap();
@@ -174,15 +176,18 @@ namespace gridfire {
recordADTape(); // Record the AD tape for the RHS of the ODE (dY/di and dEps/di) for all independent variables i
const size_t n = m_rhsADFun.Domain();
const size_t m = m_rhsADFun.Range();
const size_t inputSize = m_rhsADFun.Domain();
const size_t outputSize = m_rhsADFun.Range();
const std::vector<bool> select_domain(n, true);
const std::vector<bool> select_range(m, true);
// Create a range x range identity pattern
CppAD::sparse_rc<std::vector<size_t>> patternIn(outputSize, outputSize, outputSize);
for (size_t i = 0; i < outputSize; ++i) {
patternIn.set(i, i, i);
}
m_rhsADFun.rev_jac_sparsity(patternIn, false, false, false, m_full_jacobian_sparsity_pattern);
m_rhsADFun.subgraph_sparsity(select_domain, select_range, false, m_full_jacobian_sparsity_pattern);
m_jac_work.clear();
m_full_sparsity_set.clear();
const auto& rows = m_full_jacobian_sparsity_pattern.row();
const auto& cols = m_full_jacobian_sparsity_pattern.col();
@@ -261,6 +266,8 @@ namespace gridfire {
m_jacobianMatrix.resize(numSpecies, numSpecies, false); // Sparse matrix, no initial values
LOG_TRACE_L2(m_logger, "Jacobian matrix resized to {} rows and {} columns.",
m_jacobianMatrix.size1(), m_jacobianMatrix.size2());
m_jacobianMatrixState = JacobianMatrixState::UNINITIALIZED;
}
// --- Basic Accessors and Queries ---
@@ -274,13 +281,12 @@ namespace gridfire {
void GraphEngine::setNetworkReactions(const reaction::ReactionSet &reactions) {
m_reactions = reactions;
m_jacobianMatrixState = JacobianMatrixState::STALE;
syncInternalMaps();
}
bool GraphEngine::involvesSpecies(const fourdst::atomic::Species& species) const {
// Checks if a given species is present in the network's species map for efficient lookup.
const bool found = m_networkSpeciesMap.contains(species.name());
LOG_DEBUG(m_logger, "Checking if species '{}' is involved in the network: {}.", species.name(), found ? "Yes" : "No");
return found;
}
@@ -509,6 +515,9 @@ namespace gridfire {
}
void GraphEngine::setUseReverseReactions(const bool useReverse) {
if (useReverse != m_useReverseReactions) {
m_jacobianMatrixState = JacobianMatrixState::STALE;
}
m_useReverseReactions = useReverse;
}
@@ -568,6 +577,7 @@ namespace gridfire {
if (depth != m_depth) {
m_depth = depth;
m_reactions = build_nuclear_network(comp, m_weakRateInterpolator, m_depth, false);
m_jacobianMatrixState = JacobianMatrixState::STALE;
syncInternalMaps(); // Resync internal maps after changing the depth
} else {
LOG_DEBUG(m_logger, "Rebuild requested with the same depth. No changes made to the network.");
@@ -729,6 +739,7 @@ namespace gridfire {
void GraphEngine::setScreeningModel(const screening::ScreeningType model) {
m_screeningModel = screening::selectScreeningModel(model);
m_screeningType = model;
m_jacobianMatrixState = JacobianMatrixState::STALE; // The screening model affects the jacobian so if its changed the jacobian must be made stale
}
screening::ScreeningType GraphEngine::getScreeningModel() const {
@@ -777,12 +788,24 @@ namespace gridfire {
const double T9,
const double rho
) const {
fourdst::composition::Composition mutableComp = comp;
for (const auto& species : m_networkSpecies) {
if (!comp.hasSpecies(species)) {
mutableComp.registerSpecies(species);
mutableComp.setMassFraction(species, 0.0);
}
}
const bool didFinalize = mutableComp.finalize(false);
if (!didFinalize) {
LOG_CRITICAL(m_logger, "Could not finalize the composition used to generate the jacobian matrix!");
throw std::runtime_error("Could not finalize the composition used to generate the jacobian matrix");
}
LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Generating jacobian matrix for T9={}, rho={}..", T9, rho);
const size_t numSpecies = m_networkSpecies.size();
// 1. Pack the input variables into a vector for CppAD
std::vector<double> adInput(numSpecies + 2, 0.0); // +2 for T9 and rho
const std::vector<double>& Y_dynamic = comp.getMolarAbundanceVector();
const std::vector<double>& Y_dynamic = mutableComp.getMolarAbundanceVector();
for (size_t i = 0; i < numSpecies; ++i) {
adInput[i] = std::max(Y_dynamic[i], 1e-99); // regularize the jacobian...
}
@@ -794,16 +817,22 @@ namespace gridfire {
// 3. Pack jacobian vector into sparse matrix
m_jacobianMatrix.clear();
// std::vector<std::unique_ptr<utils::ColumnBase>> columns;
for (size_t i = 0; i < numSpecies; ++i) {
// std::vector<double> colData;
for (size_t j = 0; j < numSpecies; ++j) {
const double value = dotY[i * (numSpecies + 2) + j];
if (std::abs(value) > MIN_JACOBIAN_THRESHOLD || i == j) { // Always keep diagonal elements to avoid pathological stiffness
m_jacobianMatrix(i, j) = value;
}
// colData.push_back(value);
}
// columns.push_back(std::make_unique<utils::Column<double>>(std::to_string(i), colData));
}
// std::cout << utils::format_table("Jacobian after dense calculation", columns) << std::endl;
// exit(0);
LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Jacobian matrix generated with dimensions: {} rows x {} columns.", m_jacobianMatrix.size1(), m_jacobianMatrix.size2());
m_jacobianMatrixState = JacobianMatrixState::READY_DENSE;
}
void GraphEngine::generateJacobianMatrix(
@@ -844,6 +873,7 @@ namespace gridfire {
const double rho,
const SparsityPattern &sparsityPattern
) const {
//TODO: The issue now seems to be that the jacobian is returning all zeros. I need to sort out why this is
SparsityPattern intersectionSparsityPattern;
for (const auto& entry : sparsityPattern) {
if (m_full_sparsity_set.contains(entry)) {
@@ -891,6 +921,12 @@ namespace gridfire {
CppAD::sparse_rcv<std::vector<size_t>, std::vector<double>> jac_subset(CppAD_sparsity_pattern);
// PERF: one of *the* most pressing things that needs to be done is remove the nead for this call every
// time the jacobian is needed since coloring is expensive and we are throwing away the caching
// power of CppAD by clearing the work vector each time. We do this since we make a new subset every
// time. However, a better solution would be to make the subset stateful so it only changes if the requested
// sparsity pattern changes. This way we could reuse the work vector.
m_jac_work.clear();
m_rhsADFun.sparse_jac_rev(
x,
jac_subset, // Sparse Jacobian output
@@ -910,16 +946,35 @@ namespace gridfire {
m_jacobianMatrix(row, col) = value; // Insert into the sparse matrix
}
}
m_jacobianMatrixState = JacobianMatrixState::READY_SPARSE;
}
double GraphEngine::getJacobianMatrixEntry(
const fourdst::atomic::Species& rowSpecies,
const fourdst::atomic::Species& colSpecies
) const {
//PERF: There may be some way to make this more efficient
const size_t i = getSpeciesIndex(rowSpecies);
const size_t j = getSpeciesIndex(colSpecies);
return m_jacobianMatrix(i, j);
switch (m_jacobianMatrixState) {
case JacobianMatrixState::STALE: {
const std::string staleMsg = std::format("Cannot retrieve jacobian entry for row {}, column {} as jacobian matrix is stale (has not been regenerated since last network topology change)", rowSpecies.name(), colSpecies.name());
throw exceptions::StaleJacobianError(staleMsg);
}
case JacobianMatrixState::UNINITIALIZED: {
const std::string unInitMsg = std::format("Cannot retrieve jacobian entry for row {}, column {} as jacobian matrix is uninitialized (will return all 0s)", rowSpecies.name(), colSpecies.name());
throw exceptions::UninitializedJacobianError(unInitMsg);
}
case JacobianMatrixState::READY_DENSE:
[[fallthrough]];
case JacobianMatrixState::READY_SPARSE: {
const size_t i = getSpeciesIndex(rowSpecies);
const size_t j = getSpeciesIndex(colSpecies);
return m_jacobianMatrix(i, j);
}
default: {
// Code should not be able to get into this state
const std::string msg = std::format("An unknown error has occurred while attempting to retrieve the jacobian element at row {}, column {}. This should be taken as a catastrophic failure and reported to GridFire developers.", rowSpecies.name(), colSpecies.name());
throw exceptions::UnknownJacobianError(msg);
}
}
}
std::unordered_map<fourdst::atomic::Species, int> GraphEngine::getNetReactionStoichiometry(
@@ -1365,4 +1420,46 @@ namespace gridfire {
st[0] = rt[0];
return true;
}
bool GraphEngine::AtomicReverseRate::for_sparse_jac(
size_t q,
const CppAD::vector<bool> &r,
CppAD::vector<bool> &s,
const CppAD::vector<double> &x
) {
constexpr size_t n = 1;
constexpr size_t m = 1;
CPPAD_ASSERT_KNOWN(r.size() == n * q, "for_sparse_jac: 'r' size is incorrect.");
CPPAD_ASSERT_KNOWN(s.size() == m * q, "for_sparse_jac: 's' size is incorrect.");
// S = R
for (size_t j = 0; j < q; j++) {
// s(0,j) = r(0,j)
s[j*m] = r[j*n];
}
return true;
}
bool GraphEngine::AtomicReverseRate::rev_sparse_jac(
size_t q,
const CppAD::vector<bool> &rt,
CppAD::vector<bool> &st,
const CppAD::vector<double> &x
) {
constexpr size_t n = 1;
constexpr size_t m = 1;
CPPAD_ASSERT_KNOWN(rt.size() == n * q, "for_sparse_jac: 'r' size is incorrect.");
CPPAD_ASSERT_KNOWN(st.size() == m * q, "for_sparse_jac: 's' size is incorrect.");
// st = rt
for (size_t j = 0; j < q; j++) {
// st(j, 0) = rt(j, 0)
st[j * n] = rt[j * m];
}
return true;
}
}

85
src/lib/engine/procedures/construction.cpp
View File

@@ -53,48 +53,49 @@ namespace gridfire {
}
}
for (const auto& parent_species: weakInterpolator.available_isotopes()) {
std::expected<Species, fourdst::atomic::SpeciesErrorType> upProduct = fourdst::atomic::az_to_species(
parent_species.a(),
parent_species.z() + 1
);
std::expected<Species, fourdst::atomic::SpeciesErrorType> downProduct = fourdst::atomic::az_to_species(
parent_species.a(),
parent_species.z() - 1
);
if (downProduct.has_value()) { // Only add the reaction if the Species map contains the product
master_reaction_pool.add_reaction(
std::make_unique<rates::weak::WeakReaction>(
parent_species,
rates::weak::WeakReactionType::BETA_PLUS_DECAY,
weakInterpolator
)
);
master_reaction_pool.add_reaction(
std::make_unique<rates::weak::WeakReaction>(
parent_species,
rates::weak::WeakReactionType::ELECTRON_CAPTURE,
weakInterpolator
)
);
}
if (upProduct.has_value()) { // Only add the reaction if the Species map contains the product
master_reaction_pool.add_reaction(
std::make_unique<rates::weak::WeakReaction>(
parent_species,
rates::weak::WeakReactionType::BETA_MINUS_DECAY,
weakInterpolator
)
);
master_reaction_pool.add_reaction(
std::make_unique<rates::weak::WeakReaction>(
parent_species,
rates::weak::WeakReactionType::POSITRON_CAPTURE,
weakInterpolator
)
);
}
}
// --- Clone all possible weak reactions into the master reaction pool ---
// for (const auto& parent_species: weakInterpolator.available_isotopes()) {
// std::expected<Species, fourdst::atomic::SpeciesErrorType> upProduct = fourdst::atomic::az_to_species(
// parent_species.a(),
// parent_species.z() + 1
// );
// std::expected<Species, fourdst::atomic::SpeciesErrorType> downProduct = fourdst::atomic::az_to_species(
// parent_species.a(),
// parent_species.z() - 1
// );
// if (downProduct.has_value()) { // Only add the reaction if the Species map contains the product
// master_reaction_pool.add_reaction(
// std::make_unique<rates::weak::WeakReaction>(
// parent_species,
// rates::weak::WeakReactionType::BETA_PLUS_DECAY,
// weakInterpolator
// )
// );
// master_reaction_pool.add_reaction(
// std::make_unique<rates::weak::WeakReaction>(
// parent_species,
// rates::weak::WeakReactionType::ELECTRON_CAPTURE,
// weakInterpolator
// )
// );
// }
// if (upProduct.has_value()) { // Only add the reaction if the Species map contains the product
// master_reaction_pool.add_reaction(
// std::make_unique<rates::weak::WeakReaction>(
// parent_species,
// rates::weak::WeakReactionType::BETA_MINUS_DECAY,
// weakInterpolator
// )
// );
// master_reaction_pool.add_reaction(
// std::make_unique<rates::weak::WeakReaction>(
// parent_species,
// rates::weak::WeakReactionType::POSITRON_CAPTURE,
// weakInterpolator
// )
// );
// }
// } TODO: Remove comments, weak reactions have been disabled for testing
// --- Step 2: Use non-owning raw pointers for the fast build algorithm ---
std::vector<Reaction*> remainingReactions;