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GridFire/src/lib/engine/engine_graph.cpp

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#include "gridfire/engine/engine_graph.h"
#include "gridfire/reaction/reaction.h"
#include "gridfire/network.h"
#include "gridfire/screening/screening_types.h"
#include "gridfire/engine/procedures/priming.h"
#include "gridfire/partition/partition_ground.h"
#include "gridfire/engine/procedures/construction.h"
#include "fourdst/composition/species.h"
#include "fourdst/composition/atomicSpecies.h"
#include "quill/LogMacros.h"
#include <cstdint>
#include <iostream>
#include <set>
#include <stdexcept>
#include <string>
#include <string_view>
#include <unordered_map>
#include <utility>
#include <vector>
#include <fstream>
#include <ranges>
#include <boost/numeric/odeint.hpp>
#include "cppad/cppad.hpp"
#include "cppad/utility/sparse_rc.hpp"
#include "cppad/utility/sparse_rcv.hpp"
namespace gridfire {
GraphEngine::GraphEngine(
const fourdst::composition::Composition &composition,
const BuildDepthType buildDepth
): GraphEngine(composition, partition::GroundStatePartitionFunction(), buildDepth) {}
GraphEngine::GraphEngine(
const fourdst::composition::Composition &composition,
const partition::PartitionFunction& partitionFunction,
const BuildDepthType buildDepth) :
m_reactions(build_reaclib_nuclear_network(composition, buildDepth, false)),
m_depth(buildDepth),
m_partitionFunction(partitionFunction.clone())
{
syncInternalMaps();
}
GraphEngine::GraphEngine(
const reaction::LogicalReactionSet &reactions
) :
m_reactions(reactions) {
syncInternalMaps();
}
std::expected<StepDerivatives<double>, expectations::StaleEngineError> GraphEngine::calculateRHSAndEnergy(
const std::vector<double> &Y,
const double T9,
const double rho
) const {
if (m_usePrecomputation) {
std::vector<double> bare_rates;
std::vector<double> bare_reverse_rates;
bare_rates.reserve(m_reactions.size());
bare_reverse_rates.reserve(m_reactions.size());
// TODO: Add cache to this
for (const auto& reaction: m_reactions) {
bare_rates.push_back(reaction.calculate_rate(T9));
bare_reverse_rates.push_back(calculateReverseRate(reaction, T9));
}
// --- The public facing interface can always use the precomputed version since taping is done internally ---
return calculateAllDerivativesUsingPrecomputation(Y, bare_rates, bare_reverse_rates, T9, rho);
} else {
return calculateAllDerivatives<double>(Y, T9, rho);
}
}
void GraphEngine::syncInternalMaps() {
LOG_INFO(m_logger, "Synchronizing internal maps for REACLIB graph network (serif::network::GraphNetwork)...");
collectNetworkSpecies();
populateReactionIDMap();
populateSpeciesToIndexMap();
collectAtomicReverseRateAtomicBases();
generateStoichiometryMatrix();
reserveJacobianMatrix();
recordADTape();
const size_t n = m_rhsADFun.Domain();
const size_t m = m_rhsADFun.Range();
const std::vector<bool> select_domain(n, true);
const std::vector<bool> select_range(m, true);
m_rhsADFun.subgraph_sparsity(select_domain, select_range, false, m_full_jacobian_sparsity_pattern);
m_jac_work.clear();
precomputeNetwork();
LOG_INFO(m_logger, "Internal maps synchronized. Network contains {} species and {} reactions.",
m_networkSpecies.size(), m_reactions.size());
}
// --- Network Graph Construction Methods ---
void GraphEngine::collectNetworkSpecies() {
m_networkSpecies.clear();
m_networkSpeciesMap.clear();
std::set<std::string_view> uniqueSpeciesNames;
for (const auto& reaction: m_reactions) {
for (const auto& reactant: reaction.reactants()) {
uniqueSpeciesNames.insert(reactant.name());
}
for (const auto& product: reaction.products()) {
uniqueSpeciesNames.insert(product.name());
}
}
for (const auto& name: uniqueSpeciesNames) {
auto it = fourdst::atomic::species.find(std::string(name));
if (it != fourdst::atomic::species.end()) {
m_networkSpecies.push_back(it->second);
m_networkSpeciesMap.insert({name, it->second});
} else {
LOG_ERROR(m_logger, "Species '{}' not found in global atomic species database.", name);
m_logger->flush_log();
throw std::runtime_error("Species not found in global atomic species database: " + std::string(name));
}
}
}
void GraphEngine::populateReactionIDMap() {
LOG_TRACE_L1(m_logger, "Populating reaction ID map for REACLIB graph network (serif::network::GraphNetwork)...");
m_reactionIDMap.clear();
for (auto& reaction: m_reactions) {
m_reactionIDMap.emplace(reaction.id(), &reaction);
}
LOG_TRACE_L1(m_logger, "Populated {} reactions in the reaction ID map.", m_reactionIDMap.size());
}
void GraphEngine::populateSpeciesToIndexMap() {
m_speciesToIndexMap.clear();
for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
m_speciesToIndexMap.insert({m_networkSpecies[i], i});
}
}
void GraphEngine::reserveJacobianMatrix() const {
// The implementation of this function (and others) constrains this nuclear network to a constant temperature and density during
// each evaluation.
const size_t numSpecies = m_networkSpecies.size();
m_jacobianMatrix.clear();
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());
}
// --- Basic Accessors and Queries ---
const std::vector<fourdst::atomic::Species>& GraphEngine::getNetworkSpecies() const {
// Returns a constant reference to the vector of unique species in the network.
LOG_TRACE_L3(m_logger, "Providing access to network species vector. Size: {}.", m_networkSpecies.size());
return m_networkSpecies;
}
const reaction::LogicalReactionSet& GraphEngine::getNetworkReactions() const {
// Returns a constant reference to the set of reactions in the network.
LOG_TRACE_L3(m_logger, "Providing access to network reactions set. Size: {}.", m_reactions.size());
return m_reactions;
}
void GraphEngine::setNetworkReactions(const reaction::LogicalReactionSet &reactions) {
m_reactions = reactions;
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;
}
// --- Validation Methods ---
bool GraphEngine::validateConservation() const {
LOG_TRACE_L1(m_logger, "Validating mass (A) and charge (Z) conservation across all reactions in the network.");
for (const auto& reaction : m_reactions) {
uint64_t totalReactantA = 0;
uint64_t totalReactantZ = 0;
uint64_t totalProductA = 0;
uint64_t totalProductZ = 0;
// Calculate total A and Z for reactants
for (const auto& reactant : reaction.reactants()) {
auto it = m_networkSpeciesMap.find(reactant.name());
if (it != m_networkSpeciesMap.end()) {
totalReactantA += it->second.a();
totalReactantZ += it->second.z();
} else {
// This scenario indicates a severe data integrity issue:
// a reactant is part of a reaction but not in the network's species map.
LOG_ERROR(m_logger, "CRITICAL ERROR: Reactant species '{}' in reaction '{}' not found in network species map during conservation validation.",
reactant.name(), reaction.id());
return false;
}
}
// Calculate total A and Z for products
for (const auto& product : reaction.products()) {
auto it = m_networkSpeciesMap.find(product.name());
if (it != m_networkSpeciesMap.end()) {
totalProductA += it->second.a();
totalProductZ += it->second.z();
} else {
// Similar critical error for product species
LOG_ERROR(m_logger, "CRITICAL ERROR: Product species '{}' in reaction '{}' not found in network species map during conservation validation.",
product.name(), reaction.id());
return false;
}
}
// Compare totals for conservation
if (totalReactantA != totalProductA) {
LOG_ERROR(m_logger, "Mass number (A) not conserved for reaction '{}': Reactants A={} vs Products A={}.",
reaction.id(), totalReactantA, totalProductA);
return false;
}
if (totalReactantZ != totalProductZ) {
LOG_ERROR(m_logger, "Atomic number (Z) not conserved for reaction '{}': Reactants Z={} vs Products Z={}.",
reaction.id(), totalReactantZ, totalProductZ);
return false;
}
}
LOG_TRACE_L1(m_logger, "Mass (A) and charge (Z) conservation validated successfully for all reactions.");
return true; // All reactions passed the conservation check
}
void GraphEngine::validateComposition(const fourdst::composition::Composition &composition, double culling, double T9) {
// Check if the requested network has already been cached.
// PERF: Rebuilding this should be pretty fast but it may be a good point of optimization in the future.
const reaction::LogicalReactionSet validationReactionSet = build_reaclib_nuclear_network(composition, false);
// TODO: need some more robust method here to
// A. Build the basic network from the composition's species with non zero mass fractions.
// B. rebuild a new composition from the reaction set's reactants + products (with the mass fractions from the things that are only products set to 0)
// C. Rebuild the reaction set from the new composition
// D. Cull reactions where all reactants have mass fractions below the culling threshold.
// E. Be careful about maintaining caching through all of this
// This allows for dynamic network modification while retaining caching for networks which are very similar.
if (validationReactionSet != m_reactions) {
LOG_DEBUG(m_logger, "Reaction set not cached. Rebuilding the reaction set for T9={} and culling={}.", T9, culling);
m_reactions = validationReactionSet;
syncInternalMaps(); // Re-sync internal maps after updating reactions. Note this will also retrace the AD tape.
}
}
double GraphEngine::calculateReverseRate(
const reaction::Reaction &reaction,
const double T9
) const {
if (!m_useReverseReactions) {
LOG_TRACE_L3_LIMIT_EVERY_N(std::numeric_limits<int>::max(), m_logger, "Reverse reactions are disabled. Returning 0.0 for reverse rate of reaction '{}'.", reaction.id());
return 0.0; // If reverse reactions are not used, return 0.0
}
const double expFactor = std::exp(-reaction.qValue() / (m_constants.kB * T9));
if (s_debug) {
std::cout << "\texpFactor = exp(-qValue/(kB * T9))\n";
std::cout << "\texpFactor: " << expFactor << " for reaction: " << reaction.peName() << std::endl;
std::cout << "\tQ-value: " << reaction.qValue() << " at T9: " << T9 << std::endl;
std::cout << "\tT9: " << T9 << std::endl;
std::cout << "\tkB * T9: " << m_constants.kB * T9 << std::endl;
std::cout << "\tqValue/(kB * T9): " << reaction.qValue() / (m_constants.kB * T9) << std::endl;
}
double reverseRate = 0.0;
const double forwardRate = reaction.calculate_rate(T9);
if (reaction.reactants().size() == 2 && reaction.products().size() == 2) {
reverseRate = calculateReverseRateTwoBody(reaction, T9, forwardRate, expFactor);
} else {
LOG_WARNING_LIMIT_EVERY_N(1000000, m_logger, "Reverse rate calculation for reactions with more than two reactants or products is not implemented (reaction id {}).", reaction.peName());
}
LOG_TRACE_L2_LIMIT_EVERY_N(1000, m_logger, "Calculated reverse rate for reaction '{}': {:.3E} at T9={:.3E}.", reaction.id(), reverseRate, T9);
return reverseRate;
}
double GraphEngine::calculateReverseRateTwoBody(
const reaction::Reaction &reaction,
const double T9,
const double forwardRate,
const double expFactor
) const {
std::vector<double> reactantPartitionFunctions;
std::vector<double> productPartitionFunctions;
reactantPartitionFunctions.reserve(reaction.reactants().size());
productPartitionFunctions.reserve(reaction.products().size());
std::unordered_map<fourdst::atomic::Species, int> reactantMultiplicity;
std::unordered_map<fourdst::atomic::Species, int> productMultiplicity;
reactantMultiplicity.reserve(reaction.reactants().size());
productMultiplicity.reserve(reaction.products().size());
for (const auto& reactant : reaction.reactants()) {
reactantMultiplicity[reactant] += 1;
}
for (const auto& product : reaction.products()) {
productMultiplicity[product] += 1;
}
double reactantSymmetryFactor = 1.0;
double productSymmetryFactor = 1.0;
for (const auto& count : reactantMultiplicity | std::views::values) {
reactantSymmetryFactor *= std::tgamma(count + 1);
}
for (const auto& count : productMultiplicity | std::views::values) {
productSymmetryFactor *= std::tgamma(count + 1);
}
const double symmetryFactor = reactantSymmetryFactor / productSymmetryFactor;
// Accumulate mass terms
auto mass_op = [](double acc, const auto& species) { return acc * species.a(); };
const double massNumerator = std::accumulate(
reaction.reactants().begin(),
reaction.reactants().end(),
1.0,
mass_op
);
const double massDenominator = std::accumulate(
reaction.products().begin(),
reaction.products().end(),
1.0,
mass_op
);
// Accumulate partition functions
auto pf_op = [&](double acc, const auto& species) {
return acc * m_partitionFunction->evaluate(species.z(), species.a(), T9);
};
const double partitionFunctionNumerator = std::accumulate(
reaction.reactants().begin(),
reaction.reactants().end(),
1.0,
pf_op
);
const double partitionFunctionDenominator = std::accumulate(
reaction.products().begin(),
reaction.products().end(),
1.0,
pf_op
);
const double CT = std::pow(massNumerator/massDenominator, 1.5) *
(partitionFunctionNumerator/partitionFunctionDenominator);
const double reverseRate = forwardRate * symmetryFactor * CT * expFactor;
if (!std::isfinite(reverseRate)) {
return 0.0; // If the reverse rate is not finite, return 0.0
}
return reverseRate; // Return the calculated reverse rate
}
double GraphEngine::calculateReverseRateTwoBodyDerivative(
const reaction::Reaction &reaction,
const double T9,
const double reverseRate
) const {
if (!m_useReverseReactions) {
LOG_TRACE_L3_LIMIT_EVERY_N(std::numeric_limits<int>::max(), m_logger, "Reverse reactions are disabled. Returning 0.0 for reverse rate of reaction '{}'.", reaction.id());
return 0.0; // If reverse reactions are not used, return 0.0
}
const double d_log_kFwd = reaction.calculate_forward_rate_log_derivative(T9);
auto log_deriv_pf_op = [&](double acc, const auto& species) {
const double g = m_partitionFunction->evaluate(species.z(), species.a(), T9);
const double dg_dT = m_partitionFunction->evaluateDerivative(species.z(), species.a(), T9);
return (g == 0.0) ? acc : acc + (dg_dT / g);
};
const double reactant_log_derivative_sum = std::accumulate(
reaction.reactants().begin(),
reaction.reactants().end(),
0.0,
log_deriv_pf_op
);
const double product_log_derivative_sum = std::accumulate(
reaction.products().begin(),
reaction.products().end(),
0.0,
log_deriv_pf_op
);
const double d_log_C = reactant_log_derivative_sum - product_log_derivative_sum;
const double d_log_exp = reaction.qValue() / (m_constants.kB * T9 * T9);
const double log_total_derivative = d_log_kFwd + d_log_C + d_log_exp;
return reverseRate * log_total_derivative; // Return the derivative of the reverse rate with respect to T9
}
bool GraphEngine::isUsingReverseReactions() const {
return m_useReverseReactions;
}
void GraphEngine::setUseReverseReactions(const bool useReverse) {
m_useReverseReactions = useReverse;
}
int GraphEngine::getSpeciesIndex(const fourdst::atomic::Species &species) const {
return m_speciesToIndexMap.at(species); // Returns the index of the species in the stoichiometry matrix
}
std::vector<double> GraphEngine::mapNetInToMolarAbundanceVector(const NetIn &netIn) const {
std::vector<double> Y(m_networkSpecies.size(), 0.0); // Initialize with zeros
for (const auto& [symbol, entry] : netIn.composition) {
Y[getSpeciesIndex(entry.isotope())] = netIn.composition.getMolarAbundance(symbol); // Map species to their molar abundance
}
return Y; // Return the vector of molar abundances
}
PrimingReport GraphEngine::primeEngine(const NetIn &netIn) {
NetIn fullNetIn;
fourdst::composition::Composition composition;
std::vector<std::string> symbols;
symbols.reserve(m_networkSpecies.size());
for (const auto &symbol: m_networkSpecies) {
symbols.emplace_back(symbol.name());
}
composition.registerSymbol(symbols);
for (const auto& [symbol, entry] : netIn.composition) {
if (m_networkSpeciesMap.contains(symbol)) {
composition.setMassFraction(symbol, entry.mass_fraction());
} else {
composition.setMassFraction(symbol, 0.0);
}
}
composition.finalize(true);
fullNetIn.composition = composition;
fullNetIn.temperature = netIn.temperature;
fullNetIn.density = netIn.density;
auto primingReport = primeNetwork(fullNetIn, *this);
return primingReport;
}
BuildDepthType GraphEngine::getDepth() const {
return m_depth;
}
void GraphEngine::rebuild(const fourdst::composition::Composition& comp, const BuildDepthType depth) {
if (depth != m_depth) {
m_depth = depth;
m_reactions = build_reaclib_nuclear_network(comp, m_depth, false);
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.");
}
}
StepDerivatives<double> GraphEngine::calculateAllDerivativesUsingPrecomputation(
const std::vector<double> &Y_in,
const std::vector<double> &bare_rates,
const std::vector<double> &bare_reverse_rates,
const double T9,
const double rho
) const {
// --- Calculate screening factors ---
const std::vector<double> screeningFactors = m_screeningModel->calculateScreeningFactors(
m_reactions,
m_networkSpecies,
Y_in,
T9,
rho
);
// --- Optimized loop ---
std::vector<double> molarReactionFlows;
molarReactionFlows.reserve(m_precomputedReactions.size());
for (const auto& precomp : m_precomputedReactions) {
double forwardAbundanceProduct = 1.0;
// bool below_threshold = false;
for (size_t i = 0; i < precomp.unique_reactant_indices.size(); ++i) {
const size_t reactantIndex = precomp.unique_reactant_indices[i];
const int power = precomp.reactant_powers[i];
// const double abundance = Y_in[reactantIndex];
// if (abundance < MIN_ABUNDANCE_THRESHOLD) {
// below_threshold = true;
// break;
// }
forwardAbundanceProduct *= std::pow(Y_in[reactantIndex], power);
}
// if (below_threshold) {
// molarReactionFlows.push_back(0.0);
// continue; // Skip this reaction if any reactant is below the abundance threshold
// }
const double bare_rate = bare_rates[precomp.reaction_index];
const double screeningFactor = screeningFactors[precomp.reaction_index];
const size_t numReactants = m_reactions[precomp.reaction_index].reactants().size();
const size_t numProducts = m_reactions[precomp.reaction_index].products().size();
const double forwardMolarReactionFlow =
screeningFactor *
bare_rate *
precomp.symmetry_factor *
forwardAbundanceProduct *
std::pow(rho, numReactants > 1 ? numReactants - 1 : 0.0);
double reverseMolarReactionFlow = 0.0;
if (precomp.reverse_symmetry_factor != 0.0 and m_useReverseReactions) {
const double bare_reverse_rate = bare_reverse_rates[precomp.reaction_index];
double reverseAbundanceProduct = 1.0;
for (size_t i = 0; i < precomp.unique_product_indices.size(); ++i) {
reverseAbundanceProduct *= std::pow(Y_in[precomp.unique_product_indices[i]], precomp.product_powers[i]);
}
reverseMolarReactionFlow = screeningFactor *
bare_reverse_rate *
precomp.reverse_symmetry_factor *
reverseAbundanceProduct *
std::pow(rho, numProducts > 1 ? numProducts - 1 : 0.0);
}
molarReactionFlows.push_back(forwardMolarReactionFlow - reverseMolarReactionFlow);
}
// --- Assemble molar abundance derivatives ---
StepDerivatives<double> result;
result.dydt.assign(m_networkSpecies.size(), 0.0); // Initialize derivatives to zero
for (size_t j = 0; j < m_precomputedReactions.size(); ++j) {
const auto& precomp = m_precomputedReactions[j];
const double R_j = molarReactionFlows[j];
for (size_t i = 0; i < precomp.affected_species_indices.size(); ++i) {
const size_t speciesIndex = precomp.affected_species_indices[i];
const int stoichiometricCoefficient = precomp.stoichiometric_coefficients[i];
// Update the derivative for this species
result.dydt[speciesIndex] += static_cast<double>(stoichiometricCoefficient) * R_j;
}
}
// --- Calculate the nuclear energy generation rate ---
double massProductionRate = 0.0; // [mol][s^-1]
for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
const auto& species = m_networkSpecies[i];
massProductionRate += result.dydt[i] * species.mass() * m_constants.u;
}
result.nuclearEnergyGenerationRate = -massProductionRate * m_constants.Na * m_constants.c * m_constants.c; // [erg][s^-1][g^-1]
return result;
}
// --- Generate Stoichiometry Matrix ---
void GraphEngine::generateStoichiometryMatrix() {
LOG_TRACE_L1(m_logger, "Generating stoichiometry matrix...");
// Task 1: Set dimensions and initialize the matrix
size_t numSpecies = m_networkSpecies.size();
size_t numReactions = m_reactions.size();
m_stoichiometryMatrix.resize(numSpecies, numReactions, false);
LOG_TRACE_L1(m_logger, "Stoichiometry matrix initialized with dimensions: {} rows (species) x {} columns (reactions).",
numSpecies, numReactions);
// Task 2: Populate the stoichiometry matrix
// Iterate through all reactions, assign them a column index, and fill in their stoichiometric coefficients.
size_t reactionColumnIndex = 0;
for (const auto& reaction : m_reactions) {
// Get the net stoichiometry for the current reaction
std::unordered_map<fourdst::atomic::Species, int> netStoichiometry = reaction.stoichiometry();
// Iterate through the species and their coefficients in the stoichiometry map
for (const auto& [species, coefficient] : netStoichiometry) {
// Find the row index for this species
auto it = m_speciesToIndexMap.find(species);
if (it != m_speciesToIndexMap.end()) {
const size_t speciesRowIndex = it->second;
// Set the matrix element. Boost.uBLAS handles sparse insertion.
m_stoichiometryMatrix(speciesRowIndex, reactionColumnIndex) = coefficient;
} else {
// This scenario should ideally not happen if m_networkSpeciesMap and m_speciesToIndexMap are correctly synced
LOG_ERROR(m_logger, "CRITICAL ERROR: Species '{}' from reaction '{}' stoichiometry not found in species to index map.",
species.name(), reaction.id());
m_logger -> flush_log();
throw std::runtime_error("Species not found in species to index map: " + std::string(species.name()));
}
}
reactionColumnIndex++; // Move to the next column for the next reaction
}
LOG_TRACE_L1(m_logger, "Stoichiometry matrix population complete. Number of non-zero elements: {}.",
m_stoichiometryMatrix.nnz()); // Assuming nnz() exists for compressed_matrix
}
StepDerivatives<double> GraphEngine::calculateAllDerivatives(
const std::vector<double> &Y_in,
const double T9,
const double rho
) const {
return calculateAllDerivatives<double>(Y_in, T9, rho);
}
StepDerivatives<ADDouble> GraphEngine::calculateAllDerivatives(
const std::vector<ADDouble> &Y_in,
const ADDouble &T9,
const ADDouble &rho
) const {
return calculateAllDerivatives<ADDouble>(Y_in, T9, rho);
}
void GraphEngine::setScreeningModel(const screening::ScreeningType model) {
m_screeningModel = screening::selectScreeningModel(model);
m_screeningType = model;
}
screening::ScreeningType GraphEngine::getScreeningModel() const {
return m_screeningType;
}
void GraphEngine::setPrecomputation(const bool precompute) {
m_usePrecomputation = precompute;
}
bool GraphEngine::isPrecomputationEnabled() const {
return m_usePrecomputation;
}
const partition::PartitionFunction & GraphEngine::getPartitionFunction() const {
return *m_partitionFunction;
}
double GraphEngine::calculateMolarReactionFlow(
const reaction::Reaction &reaction,
const std::vector<double> &Y,
const double T9,
const double rho
) const {
return calculateMolarReactionFlow<double>(reaction, Y, T9, rho);
}
void GraphEngine::generateJacobianMatrix(
const std::vector<double> &Y_dynamic,
const double T9,
const double rho
) const {
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
for (size_t i = 0; i < numSpecies; ++i) {
adInput[i] = std::max(Y_dynamic[i], 1e-99); // regularize the jacobian...
}
adInput[numSpecies] = T9; // T9
adInput[numSpecies + 1] = rho; // rho
// 2. Calculate the full jacobian
const std::vector<double> dotY = m_rhsADFun.Jacobian(adInput);
// 3. Pack jacobian vector into sparse matrix
m_jacobianMatrix.clear();
for (size_t i = 0; i < numSpecies; ++i) {
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;
}
}
}
LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Jacobian matrix generated with dimensions: {} rows x {} columns.", m_jacobianMatrix.size1(), m_jacobianMatrix.size2());
}
void GraphEngine::generateJacobianMatrix(
const std::vector<double> &Y_dynamic,
const double T9,
const double rho,
const SparsityPattern &sparsityPattern
) const {
// --- Pack the input variables into a vector for CppAD ---
const size_t numSpecies = m_networkSpecies.size();
std::vector<double> x(numSpecies + 2, 0.0);
for (size_t i = 0; i < numSpecies; ++i) {
x[i] = Y_dynamic[i];
}
x[numSpecies] = T9;
x[numSpecies + 1] = rho;
// --- Convert into CppAD Sparsity pattern ---
const size_t nnz = sparsityPattern.size(); // Number of non-zero entries in the sparsity pattern
std::vector<size_t> row_indices(nnz);
std::vector<size_t> col_indices(nnz);
for (size_t k = 0; k < nnz; ++k) {
row_indices[k] = sparsityPattern[k].first;
col_indices[k] = sparsityPattern[k].second;
}
std::vector<double> values(nnz);
const size_t num_rows_jac = numSpecies;
const size_t num_cols_jac = numSpecies + 2; // +2 for T9 and rho
CppAD::sparse_rc<std::vector<size_t>> CppAD_sparsity_pattern(num_rows_jac, num_cols_jac, nnz);
for (size_t k = 0; k < nnz; ++k) {
CppAD_sparsity_pattern.set(k, sparsityPattern[k].first, sparsityPattern[k].second);
}
CppAD::sparse_rcv<std::vector<size_t>, std::vector<double>> jac_subset(CppAD_sparsity_pattern);
m_rhsADFun.sparse_jac_rev(
x,
jac_subset, // Sparse Jacobian output
m_full_jacobian_sparsity_pattern,
"cppad",
m_jac_work // Work vector for CppAD
);
// --- Convert the sparse Jacobian back to the Boost uBLAS format ---
m_jacobianMatrix.clear();
for (size_t k = 0; k < nnz; ++k) {
const size_t row = jac_subset.row()[k];
const size_t col = jac_subset.col()[k];
const double value = jac_subset.val()[k];
if (std::abs(value) > MIN_JACOBIAN_THRESHOLD) {
m_jacobianMatrix(row, col) = value; // Insert into the sparse matrix
}
}
}
double GraphEngine::getJacobianMatrixEntry(const int i, const int j) const {
// LOG_TRACE_L3(m_logger, "Getting jacobian matrix entry for {},{} = {}", i, j, m_jacobianMatrix(i, j));
return m_jacobianMatrix(i, j);
}
std::unordered_map<fourdst::atomic::Species, int> GraphEngine::getNetReactionStoichiometry(
const reaction::Reaction &reaction
) {
return reaction.stoichiometry();
}
int GraphEngine::getStoichiometryMatrixEntry(
const int speciesIndex,
const int reactionIndex
) const {
return m_stoichiometryMatrix(speciesIndex, reactionIndex);
}
void GraphEngine::exportToDot(const std::string &filename) const {
LOG_TRACE_L1(m_logger, "Exporting network graph to DOT file: {}", filename);
std::ofstream dotFile(filename);
if (!dotFile.is_open()) {
LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
m_logger->flush_log();
throw std::runtime_error("Failed to open file for writing: " + filename);
}
dotFile << "digraph NuclearReactionNetwork {\n";
dotFile << " graph [rankdir=LR, splines=true, overlap=false, bgcolor=\"#f0f0f0\"];\n";
dotFile << " node [shape=circle, style=filled, fillcolor=\"#a7c7e7\", fontname=\"Helvetica\"];\n";
dotFile << " edge [fontname=\"Helvetica\", fontsize=10];\n\n";
// 1. Define all species as nodes
dotFile << " // --- Species Nodes ---\n";
for (const auto& species : m_networkSpecies) {
dotFile << " \"" << species.name() << "\" [label=\"" << species.name() << "\"];\n";
}
dotFile << "\n";
// 2. Define all reactions as intermediate nodes and connect them
dotFile << " // --- Reaction Edges ---\n";
for (const auto& reaction : m_reactions) {
// Create a unique ID for the reaction node
std::string reactionNodeId = "reaction_" + std::string(reaction.id());
// Define the reaction node (small, black dot)
dotFile << " \"" << reactionNodeId << "\" [shape=point, fillcolor=black, width=0.1, height=0.1, label=\"\"];\n";
// Draw edges from reactants to the reaction node
for (const auto& reactant : reaction.reactants()) {
dotFile << " \"" << reactant.name() << "\" -> \"" << reactionNodeId << "\";\n";
}
// Draw edges from the reaction node to products
for (const auto& product : reaction.products()) {
dotFile << " \"" << reactionNodeId << "\" -> \"" << product.name() << "\" [label=\"" << reaction.qValue() << " MeV\"];\n";
}
dotFile << "\n";
}
dotFile << "}\n";
dotFile.close();
LOG_TRACE_L1(m_logger, "Successfully exported network to {}", filename);
}
void GraphEngine::exportToCSV(const std::string &filename) const {
LOG_TRACE_L1(m_logger, "Exporting network graph to CSV file: {}", filename);
std::ofstream csvFile(filename, std::ios::out | std::ios::trunc);
if (!csvFile.is_open()) {
LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
m_logger->flush_log();
throw std::runtime_error("Failed to open file for writing: " + filename);
}
csvFile << "Reaction;Reactants;Products;Q-value;sources;rates\n";
for (const auto& reaction : m_reactions) {
// Dynamic cast to REACLIBReaction to access specific properties
csvFile << reaction.id() << ";";
// Reactants
size_t count = 0;
for (const auto& reactant : reaction.reactants()) {
csvFile << reactant.name();
if (++count < reaction.reactants().size()) {
csvFile << ",";
}
}
csvFile << ";";
count = 0;
for (const auto& product : reaction.products()) {
csvFile << product.name();
if (++count < reaction.products().size()) {
csvFile << ",";
}
}
csvFile << ";" << reaction.qValue() << ";";
// Reaction coefficients
auto sources = reaction.sources();
count = 0;
for (const auto& source : sources) {
csvFile << source;
if (++count < sources.size()) {
csvFile << ",";
}
}
csvFile << ";";
// Reaction coefficients
count = 0;
for (const auto& rates : reaction) {
csvFile << rates;
if (++count < reaction.size()) {
csvFile << ",";
}
}
csvFile << "\n";
}
csvFile.close();
LOG_TRACE_L1(m_logger, "Successfully exported network graph to {}", filename);
}
std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> GraphEngine::getSpeciesTimescales(
const std::vector<double> &Y,
const double T9,
const double rho
) const {
auto [dydt, _] = calculateAllDerivatives<double>(Y, T9, rho);
std::unordered_map<fourdst::atomic::Species, double> speciesTimescales;
speciesTimescales.reserve(m_networkSpecies.size());
for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
double timescale = std::numeric_limits<double>::infinity();
const auto species = m_networkSpecies[i];
if (std::abs(dydt[i]) > 0.0) {
timescale = std::abs(Y[i] / dydt[i]);
}
speciesTimescales.emplace(species, timescale);
}
return speciesTimescales;
}
std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> GraphEngine::getSpeciesDestructionTimescales(
const std::vector<double> &Y,
const double T9,
const double rho
) const {
auto [dydt, _] = calculateAllDerivatives<double>(Y, T9, rho);
std::unordered_map<fourdst::atomic::Species, double> speciesDestructionTimescales;
speciesDestructionTimescales.reserve(m_networkSpecies.size());
for (const auto& species : m_networkSpecies) {
double netDestructionFlow = 0.0;
for (const auto& reaction : m_reactions) {
if (reaction.stoichiometry(species) < 0) {
const double flow = calculateMolarReactionFlow<double>(reaction, Y, T9, rho);
netDestructionFlow += flow;
}
}
double timescale = std::numeric_limits<double>::infinity();
if (netDestructionFlow != 0.0) {
timescale = Y[getSpeciesIndex(species)] / netDestructionFlow;
}
speciesDestructionTimescales.emplace(species, timescale);
}
return speciesDestructionTimescales;
}
fourdst::composition::Composition GraphEngine::update(const NetIn &netIn) {
fourdst::composition::Composition baseUpdatedComposition = netIn.composition;
for (const auto& species : m_networkSpecies) {
if (!netIn.composition.contains(species)) {
baseUpdatedComposition.registerSpecies(species);
baseUpdatedComposition.setMassFraction(species, 0.0);
}
}
baseUpdatedComposition.finalize(false);
return baseUpdatedComposition;
}
bool GraphEngine::isStale(const NetIn &netIn) {
return false;
}
void GraphEngine::recordADTape() {
LOG_TRACE_L1(m_logger, "Recording AD tape for the RHS calculation...");
// Task 1: Set dimensions and initialize the matrix
const size_t numSpecies = m_networkSpecies.size();
if (numSpecies == 0) {
LOG_ERROR(m_logger, "Cannot record AD tape: No species in the network.");
m_logger->flush_log();
throw std::runtime_error("Cannot record AD tape: No species in the network.");
}
const size_t numADInputs = numSpecies + 2; // Note here that by not letting T9 and rho be independent variables, we are constraining the network to a constant temperature and density during each evaluation.
// --- CppAD Tape Recording ---
// 1. Declare independent variable (adY)
// We also initialize the dummy variable for tape recording (these tell CppAD what the derivative chain looks like).
// Their numeric values are irrelevant except for in so far as they avoid numerical instabilities.
// Distribute total mass fraction uniformly between species in the dummy variable space
const auto uniformMassFraction = static_cast<CppAD::AD<double>>(1.0 / static_cast<double>(numSpecies));
std::vector<CppAD::AD<double>> adInput(numADInputs, uniformMassFraction);
adInput[numSpecies] = 1.0; // Dummy T9
adInput[numSpecies + 1] = 1.0; // Dummy rho
// 3. Declare independent variables (what CppAD will differentiate wrt.)
// This also beings the tape recording process.
CppAD::Independent(adInput);
std::vector<CppAD::AD<double>> adY(numSpecies);
for(size_t i = 0; i < numSpecies; ++i) {
adY[i] = adInput[i];
}
const CppAD::AD<double> adT9 = adInput[numSpecies];
const CppAD::AD<double> adRho = adInput[numSpecies + 1];
// 5. Call the actual templated function
// We let T9 and rho be constant, so we pass them as fixed values.
auto [dydt, nuclearEnergyGenerationRate] = calculateAllDerivatives<CppAD::AD<double>>(adY, adT9, adRho);
m_rhsADFun.Dependent(adInput, dydt);
LOG_TRACE_L1(m_logger, "AD tape recorded successfully for the RHS calculation. Number of independent variables: {}.",
adInput.size());
}
void GraphEngine::collectAtomicReverseRateAtomicBases() {
m_atomicReverseRates.clear();
m_atomicReverseRates.reserve(m_reactions.size());
for (const auto& reaction: m_reactions) {
if (reaction.qValue() != 0.0) {
m_atomicReverseRates.push_back(std::make_unique<AtomicReverseRate>(reaction, *this));
} else {
m_atomicReverseRates.push_back(nullptr);
}
}
}
void GraphEngine::precomputeNetwork() {
LOG_TRACE_L1(m_logger, "Pre-computing constant components of GraphNetwork state...");
// --- Reverse map for fast species lookups ---
std::unordered_map<fourdst::atomic::Species, size_t> speciesIndexMap;
for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
speciesIndexMap[m_networkSpecies[i]] = i;
}
m_precomputedReactions.clear();
m_precomputedReactions.reserve(m_reactions.size());
for (size_t i = 0; i < m_reactions.size(); ++i) {
const auto& reaction = m_reactions[i];
PrecomputedReaction precomp;
precomp.reaction_index = i;
// --- Precompute forward reaction information ---
// Count occurrences for each reactant to determine powers and symmetry
std::unordered_map<size_t, int> reactantCounts;
for (const auto& reactant: reaction.reactants()) {
size_t reactantIndex = speciesIndexMap.at(reactant);
reactantCounts[reactantIndex]++;
}
double symmetryDenominator = 1.0;
for (const auto& [index, count] : reactantCounts) {
precomp.unique_reactant_indices.push_back(index);
precomp.reactant_powers.push_back(count);
symmetryDenominator *= std::tgamma(count + 1);
}
precomp.symmetry_factor = 1.0/symmetryDenominator;
// --- Precompute reverse reaction information ---
if (reaction.qValue() != 0.0) {
std::unordered_map<size_t, int> productCounts;
for (const auto& product : reaction.products()) {
productCounts[speciesIndexMap.at(product)]++;
}
double reverseSymmetryDenominator = 1.0;
for (const auto& [index, count] : productCounts) {
precomp.unique_product_indices.push_back(index);
precomp.product_powers.push_back(count);
reverseSymmetryDenominator *= std::tgamma(count + 1);
}
precomp.reverse_symmetry_factor = 1.0/reverseSymmetryDenominator;
} else {
precomp.unique_product_indices.clear();
precomp.product_powers.clear();
precomp.reverse_symmetry_factor = 0.0; // No reverse reaction for Q = 0 reactions
}
// --- Precompute stoichiometry information ---
const auto stoichiometryMap = reaction.stoichiometry();
precomp.affected_species_indices.reserve(stoichiometryMap.size());
precomp.stoichiometric_coefficients.reserve(stoichiometryMap.size());
for (const auto& [species, coeff] : stoichiometryMap) {
precomp.affected_species_indices.push_back(speciesIndexMap.at(species));
precomp.stoichiometric_coefficients.push_back(coeff);
}
m_precomputedReactions.push_back(std::move(precomp));
}
}
bool GraphEngine::AtomicReverseRate::forward(
const size_t p,
const size_t q,
const CppAD::vector<bool> &vx,
CppAD::vector<bool> &vy,
const CppAD::vector<double> &tx,
CppAD::vector<double> &ty
) {
if ( p != 0) { return false; }
const double T9 = tx[0];
const double reverseRate = m_engine.calculateReverseRate(m_reaction, T9);
// std::cout << m_reaction.peName() << " reverseRate: " << reverseRate << " at T9: " << T9 << "\n";
ty[0] = reverseRate; // Store the reverse rate in the output vector
if (vx.size() > 0) {
vy[0] = vx[0];
}
return true;
}
bool GraphEngine::AtomicReverseRate::reverse(
size_t q,
const CppAD::vector<double> &tx,
const CppAD::vector<double> &ty,
CppAD::vector<double> &px,
const CppAD::vector<double> &py
) {
const double T9 = tx[0];
const double reverseRate = ty[0];
const double derivative = m_engine.calculateReverseRateTwoBodyDerivative(m_reaction, T9, reverseRate);
// std::cout << m_reaction.peName() << " reverseRate Derivative: " << derivative << "\n";
px[0] = py[0] * derivative; // Return the derivative of the reverse rate with respect to T9
return true;
}
bool GraphEngine::AtomicReverseRate::for_sparse_jac(
size_t q,
const CppAD::vector<std::set<size_t>> &r,
CppAD::vector<std::set<size_t>> &s
) {
s[0] = r[0];
return true;
}
bool GraphEngine::AtomicReverseRate::rev_sparse_jac(
size_t q,
const CppAD::vector<std::set<size_t>> &rt,
CppAD::vector<std::set<size_t>> &st
) {
st[0] = rt[0];
return true;
}
}
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