1810 lines
82 KiB
C++
1810 lines
82 KiB
C++
#include "gridfire/engine/views/engine_multiscale.h"
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#include "gridfire/exceptions/error_engine.h"
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#include "gridfire/engine/procedures/priming.h"
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#include "gridfire/utils/general_composition.h"
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#include <stdexcept>
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#include <vector>
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#include <ranges>
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#include <unordered_map>
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#include <unordered_set>
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#include <fstream>
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#include <queue>
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#include <algorithm>
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#include "quill/LogMacros.h"
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#include "quill/Logger.h"
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namespace {
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using namespace fourdst::atomic;
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//TODO: Replace all calls to this function with composition.getMolarAbundanceVector() so that
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// we don't have to keep this function around. (Cant do this right now because there is not a
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// guarantee that this function will return the same ordering as the canonical vector representation)
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std::vector<double> packCompositionToVector(
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const fourdst::composition::Composition& composition,
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const gridfire::DynamicEngine& engine
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) {
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std::vector<double> Y(engine.getNetworkSpecies().size(), 0.0);
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const auto& allSpecies = engine.getNetworkSpecies();
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for (size_t i = 0; i < allSpecies.size(); ++i) {
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const auto& species = allSpecies[i];
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if (!composition.contains(species)) {
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Y[i] = 0.0; // Species not in the composition, set to zero
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} else {
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Y[i] = composition.getMolarAbundance(species);
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}
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}
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return Y;
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}
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template <class T>
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void hash_combine(std::size_t& seed, const T& v) {
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std::hash<T> hashed;
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seed ^= hashed(v) + 0x9e3779b9 + (seed << 6) + (seed >> 2);
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}
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std::vector<std::vector<Species>> findConnectedComponentsBFS(
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const std::unordered_map<Species, std::vector<Species>>& graph,
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const std::vector<Species>& nodes
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) {
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std::vector<std::vector<Species>> components;
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std::unordered_set<Species> visited;
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for (const Species& start_node : nodes) {
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if (!visited.contains(start_node)) {
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std::vector<Species> current_component;
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std::queue<Species> q;
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q.push(start_node);
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visited.insert(start_node);
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while (!q.empty()) {
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Species u = q.front();
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q.pop();
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current_component.push_back(u);
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if (graph.contains(u)) {
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for (const auto& v : graph.at(u)) {
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if (!visited.contains(v)) {
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visited.insert(v);
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q.push(v);
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}
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}
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}
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}
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components.push_back(current_component);
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}
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}
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return components;
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}
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struct SpeciesSetIntersection {
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const Species species;
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std::size_t count;
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};
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std::expected<SpeciesSetIntersection, std::string> get_intersection_info (
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const std::unordered_set<Species>& setA,
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const std::unordered_set<Species>& setB
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) {
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// Iterate over the smaller of the two
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auto* outerSet = &setA;
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auto* innerSet = &setB;
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if (setA.size() > setB.size()) {
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outerSet = &setB;
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innerSet = &setA;
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}
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std::size_t matchCount = 0;
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const Species* firstMatch = nullptr;
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for (const Species& sp : *outerSet) {
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if (innerSet->contains(sp)) {
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if (matchCount == 0) {
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firstMatch = &sp;
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}
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++matchCount;
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if (matchCount > 1) {
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break;
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}
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}
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}
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if (!firstMatch) {
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// No matches found
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return std::unexpected{"Intersection is empty"};
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}
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if (matchCount == 0) {
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// No matches found
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return std::unexpected{"No intersection found"};
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}
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// Return the first match and the count of matches
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return SpeciesSetIntersection{*firstMatch, matchCount};
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}
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bool has_distinct_reactant_and_product_species (
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const std::unordered_set<Species>& poolSpecies,
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const std::unordered_set<Species>& reactants,
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const std::unordered_set<Species>& products
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) {
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const auto reactant_result = get_intersection_info(poolSpecies, reactants);
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if (!reactant_result) {
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return false; // No reactants found
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}
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const auto [reactantSample, reactantCount] = reactant_result.value();
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const auto product_result = get_intersection_info(poolSpecies, products);
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if (!product_result) {
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return false; // No products found
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}
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const auto [productSample, productCount] = product_result.value();
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// If either side has ≥2 distinct matches, we can always pick
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// one from each that differ.
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if (reactantCount > 1 || productCount > 1) {
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return true;
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}
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// Exactly one match on each side → they must differ
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return reactantSample != productSample;
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}
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const std::unordered_map<Eigen::LevenbergMarquardtSpace::Status, std::string> lm_status_map = {
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{Eigen::LevenbergMarquardtSpace::Status::NotStarted, "NotStarted"},
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{Eigen::LevenbergMarquardtSpace::Status::Running, "Running"},
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{Eigen::LevenbergMarquardtSpace::Status::ImproperInputParameters, "ImproperInputParameters"},
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{Eigen::LevenbergMarquardtSpace::Status::RelativeReductionTooSmall, "RelativeReductionTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::RelativeErrorTooSmall, "RelativeErrorTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::RelativeErrorAndReductionTooSmall, "RelativeErrorAndReductionTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::CosinusTooSmall, "CosinusTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::TooManyFunctionEvaluation, "TooManyFunctionEvaluation"},
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{Eigen::LevenbergMarquardtSpace::Status::FtolTooSmall, "FtolTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::XtolTooSmall, "XtolTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::GtolTooSmall, "GtolTooSmall"},
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{Eigen::LevenbergMarquardtSpace::Status::UserAsked, "UserAsked"}
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};
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}
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namespace gridfire {
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using fourdst::atomic::Species;
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MultiscalePartitioningEngineView::MultiscalePartitioningEngineView(
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DynamicEngine& baseEngine
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) : m_baseEngine(baseEngine) {}
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const std::vector<Species> & MultiscalePartitioningEngineView::getNetworkSpecies() const {
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return m_baseEngine.getNetworkSpecies();
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}
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std::expected<StepDerivatives<double>, expectations::StaleEngineError> MultiscalePartitioningEngineView::calculateRHSAndEnergy(
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const fourdst::composition::Composition& comp,
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const double T9,
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const double rho
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) const {
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// Check the cache to see if the network needs to be repartitioned. Note that the QSECacheKey manages binning of T9, rho, and Y_full to ensure that small changes (which would likely not result in a repartitioning) do not trigger a cache miss.
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const auto result = m_baseEngine.calculateRHSAndEnergy(comp, T9, rho);
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if (!result) {
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return std::unexpected{result.error()};
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}
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auto deriv = result.value();
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for (const auto& species : m_algebraic_species) {
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deriv.dydt[species] = 0.0; // Fix the algebraic species to the equilibrium abundances we calculate.
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}
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return deriv;
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}
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EnergyDerivatives MultiscalePartitioningEngineView::calculateEpsDerivatives(
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const fourdst::composition::Composition& comp,
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const double T9,
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const double rho
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) const {
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return m_baseEngine.calculateEpsDerivatives(comp, T9, rho);
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}
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void MultiscalePartitioningEngineView::generateJacobianMatrix(
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const fourdst::composition::Composition& comp,
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const double T9,
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const double rho
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) const {
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// We do not need to generate the jacobian for QSE species since those entries are by definition 0
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m_baseEngine.generateJacobianMatrix(comp, T9, rho, m_dynamic_species);
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}
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void MultiscalePartitioningEngineView::generateJacobianMatrix(
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const fourdst::composition::Composition &comp,
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const double T9,
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const double rho,
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const std::vector<Species> &activeSpecies
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) const {
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const bool activeSpeciesIsSubset = std::ranges::any_of(activeSpecies, [&](const auto& species) -> bool {
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return !involvesSpecies(species);
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});
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if (!activeSpeciesIsSubset) {
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std::string msg = std::format(
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"Active species set contains species ({}) not present in network partition. Cannot generate jacobian matrix due to this.",
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[&]() -> std::string {
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std::stringstream ss;
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for (const auto& species : activeSpecies) {
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if (!this->involvesSpecies(species)) {
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ss << species << " ";
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}
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}
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return ss.str();
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}()
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);
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LOG_CRITICAL(m_logger, "{}", msg);
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throw std::runtime_error(msg);
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}
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std::vector<Species> dynamicActiveSpeciesIntersection;
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for (const auto& species : activeSpecies) {
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if (involvesSpeciesInDynamic(species)) {
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dynamicActiveSpeciesIntersection.push_back(species);
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}
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}
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m_baseEngine.generateJacobianMatrix(comp, T9, rho, dynamicActiveSpeciesIntersection);
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}
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void MultiscalePartitioningEngineView::generateJacobianMatrix(
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const fourdst::composition::Composition &comp,
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const double T9,
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const double rho,
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const SparsityPattern &sparsityPattern
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) const {
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return m_baseEngine.generateJacobianMatrix(comp, T9, rho, sparsityPattern);
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}
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double MultiscalePartitioningEngineView::getJacobianMatrixEntry(
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const Species& rowSpecies,
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const Species& colSpecies
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) const {
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// Check if the species we are differentiating with respect to is algebraic or dynamic. If it is algebraic we can reduce the work significantly...
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if (std::ranges::contains(m_algebraic_species, colSpecies)) {
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return 0.0;
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}
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if (std::ranges::contains(m_algebraic_species, rowSpecies)) {
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return 0.0;
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}
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return m_baseEngine.getJacobianMatrixEntry(rowSpecies, colSpecies);
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}
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void MultiscalePartitioningEngineView::generateStoichiometryMatrix() {
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m_baseEngine.generateStoichiometryMatrix();
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}
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int MultiscalePartitioningEngineView::getStoichiometryMatrixEntry(
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const Species& species,
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const reaction::Reaction& reaction
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) const {
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return m_baseEngine.getStoichiometryMatrixEntry(species, reaction);
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}
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double MultiscalePartitioningEngineView::calculateMolarReactionFlow(
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const reaction::Reaction &reaction,
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const fourdst::composition::Composition &comp,
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const double T9,
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const double rho
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) const {
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// Fix the algebraic species to the equilibrium abundances we calculate.
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fourdst::composition::Composition comp_mutable = comp;
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const bool didFinalize = comp_mutable.finalize(false);
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if (!didFinalize) {
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LOG_ERROR(m_logger, "Failed to finalize composition before setting algebraic species abundances.");
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m_logger->flush_log();
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throw std::runtime_error("Failed to finalize composition before setting algebraic species abundances.");
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}
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for (const auto& species : m_algebraic_species) {
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const double Yi = m_algebraic_abundances.at(species);
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double Xi = utils::massFractionFromMolarAbundanceAndComposition(comp_mutable, species, Yi);
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comp_mutable.setMassFraction(species, Xi); // Convert Yi (mol/g) to Xi (mass fraction)
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if (!comp_mutable.finalize(false)) {
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LOG_ERROR(m_logger, "Failed to finalize composition after setting algebraic species abundance for species '{}'.", species.name());
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m_logger->flush_log();
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throw std::runtime_error("Failed to finalize composition after setting algebraic species abundance for species: " + std::string(species.name()));
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}
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}
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if (!comp_mutable.finalize()) {
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LOG_ERROR(m_logger, "Failed to finalize composition after setting algebraic species abundances.");
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m_logger->flush_log();
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throw std::runtime_error("Failed to finalize composition after setting algebraic species abundances.");
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}
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return m_baseEngine.calculateMolarReactionFlow(reaction, comp_mutable, T9, rho);
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}
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const reaction::ReactionSet & MultiscalePartitioningEngineView::getNetworkReactions() const {
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return m_baseEngine.getNetworkReactions();
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}
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void MultiscalePartitioningEngineView::setNetworkReactions(const reaction::ReactionSet &reactions) {
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LOG_CRITICAL(m_logger, "setNetworkReactions is not supported in MultiscalePartitioningEngineView. Did you mean to call this on the base engine?");
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throw exceptions::UnableToSetNetworkReactionsError("setNetworkReactions is not supported in MultiscalePartitioningEngineView. Did you mean to call this on the base engine?");
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}
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std::expected<std::unordered_map<Species, double>, expectations::StaleEngineError> MultiscalePartitioningEngineView::getSpeciesTimescales(
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const fourdst::composition::Composition &comp,
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const double T9,
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const double rho
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) const {
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const auto result = m_baseEngine.getSpeciesTimescales(comp, T9, rho);
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if (!result) {
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return std::unexpected{result.error()};
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}
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std::unordered_map<Species, double> speciesTimescales = result.value();
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for (const auto& algebraicSpecies : m_algebraic_species) {
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speciesTimescales[algebraicSpecies] = std::numeric_limits<double>::infinity(); // Algebraic species have infinite timescales.
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}
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return speciesTimescales;
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}
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std::expected<std::unordered_map<Species, double>, expectations::StaleEngineError>
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MultiscalePartitioningEngineView::getSpeciesDestructionTimescales(
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const fourdst::composition::Composition &comp,
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const double T9,
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const double rho
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) const {
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const auto result = m_baseEngine.getSpeciesDestructionTimescales(comp, T9, rho);
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if (!result) {
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return std::unexpected{result.error()};
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}
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std::unordered_map<Species, double> speciesDestructionTimescales = result.value();
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for (const auto& algebraicSpecies : m_algebraic_species) {
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speciesDestructionTimescales[algebraicSpecies] = std::numeric_limits<double>::infinity(); // Algebraic species have infinite destruction timescales.
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}
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return speciesDestructionTimescales;
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}
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fourdst::composition::Composition MultiscalePartitioningEngineView::update(const NetIn &netIn) {
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const fourdst::composition::Composition baseUpdatedComposition = m_baseEngine.update(netIn);
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NetIn baseUpdatedNetIn = netIn;
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baseUpdatedNetIn.composition = baseUpdatedComposition;
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const fourdst::composition::Composition equilibratedComposition = equilibrateNetwork(baseUpdatedNetIn);
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std::unordered_map<Species, double> algebraicAbundances;
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for (const auto& species : m_algebraic_species) {
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algebraicAbundances[species] = equilibratedComposition.getMolarAbundance(species);
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}
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m_algebraic_abundances = std::move(algebraicAbundances);
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return equilibratedComposition;
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}
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bool MultiscalePartitioningEngineView::isStale(const NetIn &netIn) {
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const auto key = QSECacheKey(
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netIn.temperature,
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netIn.density,
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packCompositionToVector(netIn.composition, m_baseEngine)
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);
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if (m_qse_abundance_cache.contains(key)) {
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return m_baseEngine.isStale(netIn); // The cache hit indicates the engine is not stale for the given conditions.
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}
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return true;
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}
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void MultiscalePartitioningEngineView::setScreeningModel(
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const screening::ScreeningType model
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) {
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m_baseEngine.setScreeningModel(model);
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}
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screening::ScreeningType MultiscalePartitioningEngineView::getScreeningModel() const {
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return m_baseEngine.getScreeningModel();
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}
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const DynamicEngine & MultiscalePartitioningEngineView::getBaseEngine() const {
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return m_baseEngine;
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}
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std::vector<std::vector<Species>> MultiscalePartitioningEngineView::analyzeTimescalePoolConnectivity(
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const std::vector<std::vector<Species>> ×cale_pools,
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const fourdst::composition::Composition &comp,
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double T9,
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double rho
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) const {
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std::vector<std::vector<Species>> final_connected_pools;
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for (const auto& pool : timescale_pools) {
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if (pool.empty()) {
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continue; // Skip empty pools
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}
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// For each timescale pool, we need to analyze connectivity.
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auto connectivity_graph = buildConnectivityGraph(pool);
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auto components = findConnectedComponentsBFS(connectivity_graph, pool);
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final_connected_pools.insert(final_connected_pools.end(), components.begin(), components.end());
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}
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return final_connected_pools;
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}
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void MultiscalePartitioningEngineView::partitionNetwork(
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const fourdst::composition::Composition &comp,
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const double T9,
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const double rho
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) {
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// --- Step 0. Clear previous state ---
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LOG_TRACE_L1(m_logger, "Partitioning network...");
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LOG_TRACE_L1(m_logger, "Clearing previous state...");
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m_qse_groups.clear();
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m_dynamic_species.clear();
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m_algebraic_species.clear();
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// --- Step 1. Identify distinct timescale regions ---
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LOG_TRACE_L1(m_logger, "Identifying fast reactions...");
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const std::vector<std::vector<Species>> timescale_pools = partitionByTimescale(comp, T9, rho);
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LOG_TRACE_L1(m_logger, "Found {} timescale pools.", timescale_pools.size());
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// --- Step 2. Select the mean slowest pool as the base dynamical group ---
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LOG_TRACE_L1(m_logger, "Identifying mean slowest pool...");
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const size_t mean_slowest_pool_index = identifyMeanSlowestPool(timescale_pools, comp, T9, rho);
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LOG_TRACE_L1(m_logger, "Mean slowest pool index: {}", mean_slowest_pool_index);
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// --- Step 3. Push the slowest pool into the dynamic species list ---
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for (const auto& slowSpecies : timescale_pools[mean_slowest_pool_index]) {
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m_dynamic_species.push_back(slowSpecies);
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}
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// --- Step 4. Pack Candidate QSE Groups ---
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std::vector<std::vector<Species>> candidate_pools;
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for (size_t i = 0; i < timescale_pools.size(); ++i) {
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if (i == mean_slowest_pool_index) continue; // Skip the slowest pool
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LOG_TRACE_L1(m_logger, "Group {} with {} species identified for potential QSE.", i, timescale_pools[i].size());
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candidate_pools.push_back(timescale_pools[i]);
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}
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LOG_TRACE_L1(m_logger, "Preforming connectivity analysis on timescale pools...");
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const std::vector<std::vector<Species>> connected_pools = analyzeTimescalePoolConnectivity(candidate_pools, comp, T9, rho);
|
|
LOG_TRACE_L1(m_logger, "Found {} connected pools (compared to {} timescale pools) for QSE analysis.", connected_pools.size(), timescale_pools.size());
|
|
|
|
|
|
// --- Step 5. Identify potential seed species for each candidate pool ---
|
|
LOG_TRACE_L1(m_logger, "Identifying potential seed species for candidate pools...");
|
|
const std::vector<QSEGroup> candidate_groups = constructCandidateGroups(connected_pools, comp, T9, rho);
|
|
LOG_TRACE_L1(m_logger, "Found {} candidate QSE groups for further analysis", candidate_groups.size());
|
|
LOG_TRACE_L2(
|
|
m_logger,
|
|
"{}",
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
int j = 0;
|
|
for (const auto& group : candidate_groups) {
|
|
ss << "CandidateQSEGroup(Algebraic: {";
|
|
int i = 0;
|
|
for (const auto& species : group.algebraic_species) {
|
|
ss << species.name();
|
|
if (i < group.algebraic_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
}
|
|
ss << "}, Seed: {";
|
|
i = 0;
|
|
for (const auto& species : group.seed_species) {
|
|
ss << species.name();
|
|
if (i < group.seed_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
i++;
|
|
}
|
|
ss << "})";
|
|
if (j < candidate_groups.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
j++;
|
|
}
|
|
return ss.str();
|
|
}()
|
|
);
|
|
|
|
LOG_TRACE_L1(m_logger, "Validating candidate groups with flux analysis...");
|
|
const auto [validated_groups, invalidate_groups] = validateGroupsWithFluxAnalysis(candidate_groups, comp, T9, rho);
|
|
LOG_TRACE_L1(
|
|
m_logger,
|
|
"Validated {} group(s) QSE groups. {}",
|
|
validated_groups.size(),
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
int count = 0;
|
|
for (const auto& group : validated_groups) {
|
|
ss << "Group " << count + 1;
|
|
if (group.is_in_equilibrium) {
|
|
ss << " is in equilibrium";
|
|
} else {
|
|
ss << " is not in equilibrium";
|
|
}
|
|
if (count < validated_groups.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
return ss.str();
|
|
}()
|
|
);
|
|
|
|
// Push the invalidated groups' species into the dynamic set
|
|
for (const auto& group : invalidate_groups) {
|
|
for (const auto& species : group.algebraic_species) {
|
|
m_dynamic_species.push_back(species);
|
|
}
|
|
}
|
|
|
|
m_qse_groups = validated_groups;
|
|
LOG_TRACE_L1(m_logger, "Identified {} QSE groups.", m_qse_groups.size());
|
|
|
|
for (const auto& group : m_qse_groups) {
|
|
// Add algebraic species to the algebraic set
|
|
for (const auto& species : group.algebraic_species) {
|
|
if (std::ranges::find(m_algebraic_species, species) == m_algebraic_species.end()) {
|
|
m_algebraic_species.push_back(species);
|
|
}
|
|
}
|
|
}
|
|
|
|
LOG_INFO(
|
|
m_logger,
|
|
"Partitioning complete. Found {} dynamic species, {} algebraic (QSE) species ({}) spread over {} QSE group{}.",
|
|
m_dynamic_species.size(),
|
|
m_algebraic_species.size(),
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
size_t count = 0;
|
|
for (const auto& species : m_algebraic_species) {
|
|
ss << species.name();
|
|
if (m_algebraic_species.size() > 1 && count < m_algebraic_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
return ss.str();
|
|
}(),
|
|
m_qse_groups.size(),
|
|
m_qse_groups.size() == 1 ? "" : "s"
|
|
);
|
|
}
|
|
|
|
void MultiscalePartitioningEngineView::partitionNetwork(
|
|
const NetIn &netIn
|
|
) {
|
|
const double T9 = netIn.temperature / 1e9; // Convert temperature from Kelvin to T9 (T9 = T / 1e9)
|
|
const double rho = netIn.density; // Density in g/cm^3
|
|
|
|
partitionNetwork(netIn.composition, T9, rho);
|
|
}
|
|
|
|
void MultiscalePartitioningEngineView::exportToDot(
|
|
const std::string &filename,
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9,
|
|
const double rho
|
|
) const {
|
|
std::ofstream dotFile(filename);
|
|
if (!dotFile.is_open()) {
|
|
LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
|
|
throw std::runtime_error("Failed to open file for writing: " + filename);
|
|
}
|
|
|
|
const auto& all_species = m_baseEngine.getNetworkSpecies();
|
|
const auto& all_reactions = m_baseEngine.getNetworkReactions();
|
|
|
|
// --- 1. Pre-computation and Categorization ---
|
|
|
|
// Categorize species into algebraic, seed, and core dynamic
|
|
std::unordered_set<Species> algebraic_species;
|
|
std::unordered_set<Species> seed_species;
|
|
for (const auto& group : m_qse_groups) {
|
|
if (group.is_in_equilibrium) {
|
|
algebraic_species.insert(group.algebraic_species.begin(), group.algebraic_species.end());
|
|
seed_species.insert(group.seed_species.begin(), group.seed_species.end());
|
|
}
|
|
}
|
|
|
|
// Calculate reaction flows and find min/max for logarithmic scaling of transparency
|
|
std::vector<double> reaction_flows;
|
|
reaction_flows.reserve(all_reactions.size());
|
|
double min_log_flow = std::numeric_limits<double>::max();
|
|
double max_log_flow = std::numeric_limits<double>::lowest();
|
|
|
|
for (const auto& reaction : all_reactions) {
|
|
double flow = std::abs(m_baseEngine.calculateMolarReactionFlow(*reaction, comp, T9, rho));
|
|
reaction_flows.push_back(flow);
|
|
if (flow > 1e-99) { // Avoid log(0)
|
|
double log_flow = std::log10(flow);
|
|
min_log_flow = std::min(min_log_flow, log_flow);
|
|
max_log_flow = std::max(max_log_flow, log_flow);
|
|
}
|
|
}
|
|
const double log_flow_range = (max_log_flow > min_log_flow) ? (max_log_flow - min_log_flow) : 1.0;
|
|
|
|
// --- 2. Write DOT file content ---
|
|
|
|
dotFile << "digraph PartitionedNetwork {\n";
|
|
dotFile << " graph [rankdir=TB, splines=true, overlap=false, bgcolor=\"#f8fafc\", label=\"Multiscale Partitioned Network View\", fontname=\"Helvetica\", fontsize=16, labeljust=l];\n";
|
|
dotFile << " node [shape=circle, style=filled, fontname=\"Helvetica\", width=0.8, fixedsize=true];\n";
|
|
dotFile << " edge [fontname=\"Helvetica\", fontsize=10];\n\n";
|
|
|
|
// --- Node Definitions ---
|
|
// Define all species nodes first, so they can be referenced by clusters and ranks later.
|
|
dotFile << " // --- Species Nodes Definitions ---\n";
|
|
std::map<int, std::vector<std::string>> species_by_mass;
|
|
for (const auto & species : all_species) {
|
|
std::string fillcolor = "#f1f5f9"; // Default: Other/Uninvolved
|
|
|
|
// Determine color based on category. A species can be a seed and also in the core dynamic group.
|
|
// The more specific category (algebraic, then seed) takes precedence.
|
|
if (algebraic_species.contains(species)) {
|
|
fillcolor = "#e0f2fe"; // Light Blue: Algebraic (in QSE)
|
|
} else if (seed_species.contains(species)) {
|
|
fillcolor = "#a7f3d0"; // Light Green: Seed (Dynamic, feeds a QSE group)
|
|
} else if (std::ranges::contains(m_dynamic_species, species)) {
|
|
fillcolor = "#dcfce7"; // Pale Green: Core Dynamic
|
|
}
|
|
dotFile << " \"" << species.name() << "\" [label=\"" << species.name() << "\", fillcolor=\"" << fillcolor << "\"];\n";
|
|
|
|
// Group species by mass number for ranked layout.
|
|
// If species.a() returns incorrect values (e.g., 0 for many species), they will be grouped together here.
|
|
species_by_mass[species.a()].emplace_back(species.name());
|
|
}
|
|
dotFile << "\n";
|
|
|
|
// --- Layout and Ranking ---
|
|
// Enforce a top-down layout based on mass number.
|
|
dotFile << " // --- Layout using Ranks ---\n";
|
|
for (const auto &species_list: species_by_mass | std::views::values) {
|
|
dotFile << " { rank=same; ";
|
|
for (const auto& name : species_list) {
|
|
dotFile << "\"" << name << "\"; ";
|
|
}
|
|
dotFile << "}\n";
|
|
}
|
|
dotFile << "\n";
|
|
|
|
// Chain by mass to get top down ordering
|
|
dotFile << " // --- Chain by Mass ---\n";
|
|
for (const auto& [mass, species_list] : species_by_mass) {
|
|
// Find the next largest mass in the species list
|
|
int minLargestMass = std::numeric_limits<int>::max();
|
|
for (const auto &next_mass: species_by_mass | std::views::keys) {
|
|
if (next_mass > mass && next_mass < minLargestMass) {
|
|
minLargestMass = next_mass;
|
|
}
|
|
}
|
|
if (minLargestMass != std::numeric_limits<int>::max()) {
|
|
// Connect the current mass to the next largest mass
|
|
dotFile << " \"" << species_list[0] << "\" -> \"" << species_by_mass[minLargestMass][0] << "\" [style=invis];\n";
|
|
}
|
|
}
|
|
|
|
// --- QSE Group Clusters ---
|
|
// Draw a prominent box around the algebraic species of each valid QSE group.
|
|
dotFile << " // --- QSE Group Clusters ---\n";
|
|
int group_counter = 0;
|
|
for (const auto& group : m_qse_groups) {
|
|
if (!group.is_in_equilibrium || group.algebraic_species.empty()) {
|
|
continue;
|
|
}
|
|
dotFile << " subgraph cluster_qse_" << group_counter++ << " {\n";
|
|
dotFile << " label = \"QSE Group " << group_counter << "\";\n";
|
|
dotFile << " style = \"filled,rounded\";\n";
|
|
dotFile << " color = \"#38bdf8\";\n"; // A bright, visible blue for the border
|
|
dotFile << " penwidth = 2.0;\n"; // Thicker border
|
|
dotFile << " bgcolor = \"#f0f9ff80\";\n"; // Light blue fill with transparency
|
|
dotFile << " subgraph cluster_seed_" << group_counter << " {\n";
|
|
dotFile << " label = \"Seed Species\";\n";
|
|
dotFile << " style = \"filled,rounded\";\n";
|
|
dotFile << " color = \"#a7f3d0\";\n"; // Light green for seed species
|
|
dotFile << " penwidth = 1.5;\n"; // Thinner border for seed cluster
|
|
std::vector<std::string> seed_node_ids;
|
|
seed_node_ids.reserve(group.seed_species.size());
|
|
for (const auto& species : group.seed_species) {
|
|
std::stringstream ss;
|
|
ss << "node_" << group_counter << "_seed_" << species.name();
|
|
dotFile << " " << ss.str() << " [label=\"" << species.name() << "\"];\n";
|
|
seed_node_ids.push_back(ss.str());
|
|
}
|
|
for (size_t i = 0; i < seed_node_ids.size() - 1; ++i) {
|
|
dotFile << " " << seed_node_ids[i] << " -> " << seed_node_ids[i + 1] << " [style=invis];\n";
|
|
}
|
|
dotFile << " }\n";
|
|
dotFile << " subgraph cluster_algebraic_" << group_counter << " {\n";
|
|
dotFile << " label = \"Algebraic Species\";\n";
|
|
dotFile << " style = \"filled,rounded\";\n";
|
|
dotFile << " color = \"#e0f2fe\";\n"; // Light blue for algebraic species
|
|
dotFile << " penwidth = 1.5;\n"; // Thinner border for algebraic cluster
|
|
std::vector<std::string> algebraic_node_ids;
|
|
algebraic_node_ids.reserve(group.algebraic_species.size());
|
|
for (const Species& species : group.algebraic_species) {
|
|
std::stringstream ss;
|
|
ss << "node_" << group_counter << "_algebraic_" << species.name();
|
|
dotFile << " " << ss.str() << " [label=\"" << species.name() << "\"];\n";
|
|
algebraic_node_ids.push_back(ss.str());
|
|
}
|
|
// Make invisible edges between algebraic indices to keep them in top-down order
|
|
for (size_t i = 0; i < algebraic_node_ids.size() - 1; ++i) {
|
|
dotFile << " " << algebraic_node_ids[i] << " -> " << algebraic_node_ids[i + 1] << " [style=invis];\n";
|
|
}
|
|
dotFile << " }\n";
|
|
dotFile << " }\n";
|
|
}
|
|
dotFile << "\n";
|
|
|
|
|
|
// --- Legend ---
|
|
// Add a legend to explain colors and conventions.
|
|
dotFile << " // --- Legend ---\n";
|
|
dotFile << " subgraph cluster_legend {\n";
|
|
dotFile << " rank = sink"; // Try to push the legend to the bottom
|
|
dotFile << " label = \"Legend\";\n";
|
|
dotFile << " bgcolor = \"#ffffff\";\n";
|
|
dotFile << " color = \"#e2e8f0\";\n";
|
|
dotFile << " node [shape=box, style=filled, fontname=\"Helvetica\"];\n";
|
|
dotFile << " key_core [label=\"Core Dynamic\", fillcolor=\"#dcfce7\"];\n";
|
|
dotFile << " key_seed [label=\"Seed (Dynamic)\", fillcolor=\"#a7f3d0\"];\n";
|
|
dotFile << " key_qse [label=\"Algebraic (QSE)\", fillcolor=\"#e0f2fe\"];\n";
|
|
dotFile << " key_other [label=\"Other\", fillcolor=\"#f1f5f9\"];\n";
|
|
dotFile << " key_info [label=\"Edge Opacity ~ log(Reaction Flow)\", shape=plaintext];\n";
|
|
dotFile << " ";// Use invisible edges to stack legend items vertically
|
|
dotFile << " key_core -> key_seed -> key_qse -> key_other -> key_info [style=invis];\n";
|
|
dotFile << " }\n\n";
|
|
|
|
// --- Reaction Edges ---
|
|
// Draw edges with transparency scaled by the log of the molar reaction flow.
|
|
dotFile << " // --- Reaction Edges ---\n";
|
|
for (size_t i = 0; i < all_reactions.size(); ++i) {
|
|
const auto& reaction = all_reactions[i];
|
|
const double flow = reaction_flows[i];
|
|
|
|
if (flow < 1e-99) continue; // Don't draw edges for negligible flows
|
|
|
|
double log_flow_val = std::log10(flow);
|
|
double norm_alpha = (log_flow_val - min_log_flow) / log_flow_range;
|
|
int alpha_val = 0x30 + static_cast<int>(norm_alpha * (0xFF - 0x30)); // Scale from ~20% to 100% opacity
|
|
alpha_val = std::clamp(alpha_val, 0x00, 0xFF);
|
|
|
|
std::stringstream alpha_hex;
|
|
alpha_hex << std::setw(2) << std::setfill('0') << std::hex << alpha_val;
|
|
std::string edge_color = "#475569" + alpha_hex.str();
|
|
|
|
std::string reactionNodeId = "reaction_" + std::string(reaction.id());
|
|
dotFile << " \"" << reactionNodeId << "\" [shape=point, fillcolor=black, width=0.05, height=0.05];\n";
|
|
for (const auto& reactant : reaction.reactants()) {
|
|
dotFile << " \"" << reactant.name() << "\" -> \"" << reactionNodeId << "\" [color=\"" << edge_color << "\", arrowhead=none];\n";
|
|
}
|
|
for (const auto& product : reaction.products()) {
|
|
dotFile << " \"" << reactionNodeId << "\" -> \"" << product.name() << "\" [color=\"" << edge_color << "\"];\n";
|
|
}
|
|
dotFile << "\n";
|
|
}
|
|
|
|
dotFile << "}\n";
|
|
dotFile.close();
|
|
}
|
|
|
|
|
|
std::vector<double> MultiscalePartitioningEngineView::mapNetInToMolarAbundanceVector(const NetIn &netIn) const {
|
|
std::vector<double> Y(m_dynamic_species.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
|
|
}
|
|
|
|
std::vector<Species> MultiscalePartitioningEngineView::getFastSpecies() const {
|
|
const auto& all_species = m_baseEngine.getNetworkSpecies();
|
|
std::vector<Species> fast_species;
|
|
fast_species.reserve(all_species.size() - m_dynamic_species.size());
|
|
for (const auto& species : all_species) {
|
|
auto it = std::ranges::find(m_dynamic_species, species);
|
|
if (it == m_dynamic_species.end()) {
|
|
fast_species.push_back(species);
|
|
}
|
|
}
|
|
return fast_species;
|
|
}
|
|
|
|
const std::vector<Species> & MultiscalePartitioningEngineView::getDynamicSpecies() const {
|
|
return m_dynamic_species;
|
|
}
|
|
|
|
PrimingReport MultiscalePartitioningEngineView::primeEngine(const NetIn &netIn) {
|
|
return m_baseEngine.primeEngine(netIn);
|
|
}
|
|
|
|
fourdst::composition::Composition MultiscalePartitioningEngineView::equilibrateNetwork(
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9,
|
|
const double rho
|
|
) {
|
|
partitionNetwork(comp, T9, rho);
|
|
fourdst::composition::Composition qseComposition = solveQSEAbundances(comp, T9, rho);
|
|
|
|
for (const auto &symbol: qseComposition | std::views::keys) {
|
|
const double speciesMassFraction = qseComposition.getMassFraction(symbol);
|
|
if (speciesMassFraction < 0.0 && std::abs(speciesMassFraction) < 1e-20) {
|
|
qseComposition.setMassFraction(symbol, 0.0); // Avoid negative mass fractions
|
|
}
|
|
}
|
|
|
|
bool didFinalize = qseComposition.finalize(true);
|
|
if (!didFinalize) {
|
|
LOG_ERROR(m_logger, "Failed to finalize composition after solving QSE abundances.");
|
|
m_logger->flush_log();
|
|
throw std::runtime_error("Failed to finalize composition after solving QSE abundances.");
|
|
}
|
|
|
|
return qseComposition;
|
|
}
|
|
|
|
fourdst::composition::Composition MultiscalePartitioningEngineView::equilibrateNetwork(
|
|
const NetIn &netIn
|
|
) {
|
|
const PrimingReport primingReport = m_baseEngine.primeEngine(netIn);
|
|
|
|
const double T9 = netIn.temperature / 1e9; // Convert temperature from Kelvin to T9 (T9 = T / 1e9)
|
|
const double rho = netIn.density; // Density in g/cm^3
|
|
|
|
return equilibrateNetwork(primingReport.primedComposition, T9, rho);
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::involvesSpecies(
|
|
const Species &species
|
|
) const {
|
|
if (involvesSpeciesInQSE(species)) return true; // check this first since the vector is likely to be smaller so short circuit cost is less on average
|
|
if (involvesSpeciesInDynamic(species)) return true;
|
|
return false;
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::involvesSpeciesInQSE(
|
|
const Species &species
|
|
) const {
|
|
return std::ranges::find(m_algebraic_species, species) != m_algebraic_species.end();
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::involvesSpeciesInDynamic(
|
|
const Species &species
|
|
) const {
|
|
return std::ranges::find(m_dynamic_species, species) != m_dynamic_species.end();
|
|
}
|
|
|
|
fourdst::composition::Composition MultiscalePartitioningEngineView::collectComposition(
|
|
fourdst::composition::Composition &comp
|
|
) const {
|
|
fourdst::composition::Composition result = m_baseEngine.collectComposition(comp);
|
|
bool didFinalize = result.finalize(false);
|
|
if (!didFinalize) {
|
|
std::string msg = "Failed to finalize collected composition from MultiscalePartitioningEngine view after calling base engines collectComposition method.";
|
|
LOG_ERROR(m_logger, "{}", msg);
|
|
throw exceptions::BadCollectionError(msg);
|
|
}
|
|
std::map<Species, double> Ym; // Use an ordered map here so that this is ordered by atomic mass (which is the </> comparator for Species)
|
|
for (const auto& [speciesName, entry] : result) {
|
|
Ym.emplace(entry.isotope(), result.getMolarAbundance(speciesName));
|
|
}
|
|
for (const auto& [species, Yi] : m_algebraic_abundances) {
|
|
if (!Ym.contains(species)) {
|
|
throw exceptions::BadCollectionError("MuiltiscalePartitioningEngineView failed to collect composition for species " + std::string(species.name()) + " as the base engine did not report that species present in its composition!");
|
|
}
|
|
Ym.at(species) = Yi;
|
|
}
|
|
std::vector<double> M;
|
|
std::vector<double> Y;
|
|
std::vector<std::string> speciesNames;
|
|
M.reserve(Ym.size());
|
|
Y.reserve(Ym.size());
|
|
|
|
for (const auto& [species, Yi] : Ym) {
|
|
M.emplace_back(species.mass());
|
|
Y.emplace_back(Yi);
|
|
speciesNames.emplace_back(species.name());
|
|
}
|
|
|
|
std::vector<double> X = utils::massFractionFromMolarAbundanceAndMolarMass(Y, M);
|
|
|
|
return fourdst::composition::Composition(speciesNames, X);
|
|
}
|
|
|
|
size_t MultiscalePartitioningEngineView::getSpeciesIndex(const Species &species) const {
|
|
return m_baseEngine.getSpeciesIndex(species);
|
|
}
|
|
|
|
|
|
std::vector<std::vector<Species>> MultiscalePartitioningEngineView::partitionByTimescale(
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9,
|
|
const double rho
|
|
) const {
|
|
LOG_TRACE_L1(m_logger, "Partitioning by timescale...");
|
|
const auto destructionTimescale= m_baseEngine.getSpeciesDestructionTimescales(comp, T9, rho);
|
|
const auto netTimescale = m_baseEngine.getSpeciesTimescales(comp, T9, rho);
|
|
|
|
if (!destructionTimescale) {
|
|
LOG_ERROR(m_logger, "Failed to get species destruction timescales due to stale engine state");
|
|
m_logger->flush_log();
|
|
throw exceptions::StaleEngineError("Failed to get species destruction timescales due to stale engine state");
|
|
}
|
|
if (!netTimescale) {
|
|
LOG_ERROR(m_logger, "Failed to get net species timescales due to stale engine state");
|
|
m_logger->flush_log();
|
|
throw exceptions::StaleEngineError("Failed to get net species timescales due to stale engine state");
|
|
}
|
|
const std::unordered_map<Species, double>& destruction_timescales = destructionTimescale.value();
|
|
[[maybe_unused]] const std::unordered_map<Species, double>& net_timescales = netTimescale.value();
|
|
|
|
LOG_TRACE_L3(
|
|
m_logger,
|
|
"{}",
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
for (const auto& [species, destruction_timescale] : destruction_timescales) {
|
|
ss << std::format("For {} destruction timescale is {}s\n", species.name(), destruction_timescale);
|
|
}
|
|
return ss.str();
|
|
}()
|
|
);
|
|
|
|
const auto& all_species = m_baseEngine.getNetworkSpecies();
|
|
|
|
std::vector<std::pair<double, Species>> sorted_destruction_timescales;
|
|
for (const auto & species : all_species) {
|
|
double destruction_timescale = destruction_timescales.at(species);
|
|
if (std::isfinite(destruction_timescale) && destruction_timescale > 0) {
|
|
LOG_TRACE_L3(m_logger, "Species {} has finite destruction timescale: destruction: {} s, net: {} s", species.name(), destruction_timescale, net_timescales.at(species));
|
|
sorted_destruction_timescales.emplace_back(destruction_timescale, species);
|
|
} else {
|
|
LOG_TRACE_L3(m_logger, "Species {} has infinite or negative destruction timescale: destruction: {} s, net: {} s", species.name(), destruction_timescale, net_timescales.at(species));
|
|
}
|
|
}
|
|
|
|
std::ranges::sort(
|
|
sorted_destruction_timescales,
|
|
[](const auto& a, const auto& b)
|
|
{
|
|
return a.first > b.first;
|
|
}
|
|
);
|
|
|
|
std::vector<std::vector<Species>> final_pools;
|
|
if (sorted_destruction_timescales.empty()) {
|
|
return final_pools;
|
|
}
|
|
|
|
constexpr double ABSOLUTE_QSE_TIMESCALE_THRESHOLD = 3.156e7; // Absolute threshold for QSE timescale (1 yr)
|
|
constexpr double MIN_GAP_THRESHOLD = 2.0; // Require a 2 order of magnitude gap
|
|
constexpr double MAX_MOLAR_ABUNDANCE_THRESHOLD = 1e-10; // Maximum molar abundance which a fast species is allowed to have (anything more abundant is always considered dynamic)
|
|
constexpr double MIN_MOLAR_ABUNDANCE_THRESHOLD = 1e-50; // Minimum molar abundance to consider a species at all (anything less abundance will be classed as dynamic but with the intent that some latter view will deal with it)
|
|
|
|
LOG_TRACE_L1(m_logger, "Found {} species with finite timescales.", sorted_destruction_timescales.size());
|
|
LOG_TRACE_L1(m_logger, "Absolute QSE timescale threshold: {} seconds ({} years).",
|
|
ABSOLUTE_QSE_TIMESCALE_THRESHOLD, ABSOLUTE_QSE_TIMESCALE_THRESHOLD / 3.156e7);
|
|
LOG_TRACE_L1(m_logger, "Minimum gap threshold: {} orders of magnitude.", MIN_GAP_THRESHOLD);
|
|
LOG_TRACE_L1(m_logger, "Maximum molar abundance threshold for fast species consideration : {}.", MAX_MOLAR_ABUNDANCE_THRESHOLD);
|
|
LOG_TRACE_L1(m_logger, "Minimum molar abundance threshold for species consideration : {}.", MIN_MOLAR_ABUNDANCE_THRESHOLD);
|
|
|
|
std::vector<Species> dynamic_pool_species;
|
|
std::vector<std::pair<double, Species>> fast_candidates;
|
|
|
|
// 1. First Pass: Absolute Timescale Cutoff
|
|
for (const auto& [destruction_timescale, species] : sorted_destruction_timescales) {
|
|
if (species == n_1) {
|
|
LOG_TRACE_L3(m_logger, "Skipping neutron (n) from timescale analysis. Neutrons are always considered dynamic due to their extremely high connectivity.");
|
|
dynamic_pool_species.push_back(species);
|
|
continue;
|
|
}
|
|
if (destruction_timescale > ABSOLUTE_QSE_TIMESCALE_THRESHOLD) {
|
|
LOG_TRACE_L3(m_logger, "Species {} with timescale {} is considered dynamic (slower than qse timescale threshold).",
|
|
species.name(), destruction_timescale);
|
|
dynamic_pool_species.push_back(species);
|
|
} else {
|
|
const double Yi = comp.getMolarAbundance(species);
|
|
if (Yi > MAX_MOLAR_ABUNDANCE_THRESHOLD) {
|
|
LOG_TRACE_L3(m_logger, "Species {} with abundance {} is considered dynamic (above minimum abundance threshold of {}).",
|
|
species.name(), Yi, MAX_MOLAR_ABUNDANCE_THRESHOLD);
|
|
dynamic_pool_species.push_back(species);
|
|
continue;
|
|
}
|
|
if (Yi < MIN_MOLAR_ABUNDANCE_THRESHOLD) {
|
|
LOG_TRACE_L3(m_logger, "Species {} with abundance {} is considered dynamic (below minimum abundance threshold of {}). Likely another network view (such as adaptive engine view) will be needed to deal with this species",
|
|
species.name(), Yi, MIN_MOLAR_ABUNDANCE_THRESHOLD);
|
|
dynamic_pool_species.push_back(species);
|
|
continue;
|
|
}
|
|
LOG_TRACE_L3(m_logger, "Species {} with timescale {} and molar abundance {} is a candidate fast species (faster than qse timescale threshold and less than the molar abundance threshold).",
|
|
species.name(), destruction_timescale, Yi);
|
|
fast_candidates.emplace_back(destruction_timescale, species);
|
|
}
|
|
}
|
|
|
|
if (!dynamic_pool_species.empty()) {
|
|
LOG_TRACE_L1(m_logger, "Found {} dynamic species (slower than QSE timescale threshold).", dynamic_pool_species.size());
|
|
final_pools.push_back(dynamic_pool_species);
|
|
}
|
|
|
|
if (fast_candidates.empty()) {
|
|
LOG_TRACE_L1(m_logger, "No fast candidates found.");
|
|
return final_pools;
|
|
}
|
|
|
|
// 2. Second Pass: Gap Detection on the remaining "fast" candidates
|
|
std::vector<size_t> split_points;
|
|
for (size_t i = 0; i < fast_candidates.size() - 1; ++i) {
|
|
const double t1 = fast_candidates[i].first;
|
|
const double t2 = fast_candidates[i+1].first;
|
|
if (std::log10(t1) - std::log10(t2) > MIN_GAP_THRESHOLD) {
|
|
LOG_TRACE_L3(m_logger, "Detected gap between species {} (timescale {:0.2E}) and {} (timescale {:0.2E}).",
|
|
fast_candidates[i].second.name(), t1,
|
|
fast_candidates[i+1].second.name(), t2);
|
|
split_points.push_back(i + 1);
|
|
}
|
|
}
|
|
|
|
size_t last_split = 0;
|
|
for (const size_t split : split_points) {
|
|
std::vector<Species> pool;
|
|
for (size_t i = last_split; i < split; ++i) {
|
|
pool.push_back(fast_candidates[i].second);
|
|
}
|
|
final_pools.push_back(pool);
|
|
last_split = split;
|
|
}
|
|
|
|
std::vector<Species> final_fast_pool;
|
|
for (size_t i = last_split; i < fast_candidates.size(); ++i) {
|
|
final_fast_pool.push_back(fast_candidates[i].second);
|
|
}
|
|
final_pools.push_back(final_fast_pool);
|
|
|
|
LOG_TRACE_L1(m_logger, "Final partitioned pools: {}",
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
int oc = 0;
|
|
for (const auto& pool : final_pools) {
|
|
ss << "[";
|
|
int ic = 0;
|
|
for (const auto& species : pool) {
|
|
ss << species.name();
|
|
if (ic < pool.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
ic++;
|
|
}
|
|
ss << "]";
|
|
if (oc < final_pools.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
oc++;
|
|
}
|
|
return ss.str();
|
|
}());
|
|
return final_pools;
|
|
|
|
}
|
|
|
|
std::pair<std::vector<MultiscalePartitioningEngineView::QSEGroup>, std::vector<MultiscalePartitioningEngineView::
|
|
QSEGroup>>
|
|
MultiscalePartitioningEngineView::validateGroupsWithFluxAnalysis(
|
|
const std::vector<QSEGroup> &candidate_groups,
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9, const double rho
|
|
) const {
|
|
std::vector<QSEGroup> validated_groups;
|
|
std::vector<QSEGroup> invalidated_groups;
|
|
validated_groups.reserve(candidate_groups.size());
|
|
for (auto& group : candidate_groups) {
|
|
constexpr double FLUX_RATIO_THRESHOLD = 5;
|
|
|
|
const std::unordered_set<Species> algebraic_group_members(
|
|
group.algebraic_species.begin(),
|
|
group.algebraic_species.end()
|
|
);
|
|
|
|
const std::unordered_set<Species> seed_group_members(
|
|
group.seed_species.begin(),
|
|
group.seed_species.end()
|
|
);
|
|
|
|
// Values for measuring the flux coupling vs leakage
|
|
double coupling_flux = 0.0;
|
|
double leakage_flux = 0.0;
|
|
|
|
for (const auto& reaction: m_baseEngine.getNetworkReactions()) {
|
|
const double flow = std::abs(m_baseEngine.calculateMolarReactionFlow(*reaction, comp, T9, rho));
|
|
if (flow == 0.0) {
|
|
continue; // Skip reactions with zero flow
|
|
}
|
|
bool has_internal_algebraic_reactant = false;
|
|
|
|
for (const auto& reactant : reaction->reactants()) {
|
|
if (algebraic_group_members.contains(reactant)) {
|
|
has_internal_algebraic_reactant = true;
|
|
LOG_TRACE_L3(m_logger, "Adjusting destruction flux (+= {} mol g^-1 s^-1) for QSEGroup due to reactant {} from reaction {}",
|
|
flow, reactant.name(), reaction->id());
|
|
}
|
|
|
|
}
|
|
|
|
bool has_internal_algebraic_product = false;
|
|
|
|
for (const auto& product : reaction->products()) {
|
|
if (algebraic_group_members.contains(product)) {
|
|
has_internal_algebraic_product = true;
|
|
LOG_TRACE_L3(m_logger, "Adjusting creation flux (+= {} mol g^-1 s^-1) for QSEGroup due to product {} from reaction {}",
|
|
flow, product.name(), reaction->id());
|
|
}
|
|
}
|
|
|
|
if (!has_internal_algebraic_product && !has_internal_algebraic_reactant) {
|
|
LOG_TRACE_L3(m_logger, "{}: Skipping reaction {} as it has no internal algebraic species in reactants or products.", group.toString(), reaction->id());
|
|
continue;
|
|
}
|
|
|
|
double algebraic_participants = 0;
|
|
double seed_participants = 0;
|
|
double external_participants = 0;
|
|
|
|
std::unordered_set<Species> participants;
|
|
for(const auto& p : reaction->reactants()) participants.insert(p);
|
|
for(const auto& p : reaction->products()) participants.insert(p);
|
|
|
|
for (const auto& species : participants) {
|
|
if (algebraic_group_members.contains(species)) {
|
|
LOG_TRACE_L3(m_logger, "{}: Species {} is an algebraic participant in reaction {}.", group.toString(), species.name(), reaction->id());
|
|
algebraic_participants++;
|
|
} else if (seed_group_members.contains(species)) {
|
|
LOG_TRACE_L3(m_logger, "{}: Species {} is a seed participant in reaction {}.", group.toString(), species.name(), reaction->id());
|
|
seed_participants++;
|
|
} else {
|
|
LOG_TRACE_L3(m_logger, "{}: Species {} is an external participant in reaction {}.", group.toString(), species.name(), reaction->id());
|
|
external_participants++;
|
|
}
|
|
}
|
|
|
|
const double total_participants = algebraic_participants + seed_participants + external_participants;
|
|
|
|
if (total_participants == 0) {
|
|
LOG_CRITICAL(m_logger, "Some catastrophic error has occurred. Reaction {} has no participants.", reaction->id());
|
|
throw std::runtime_error("Some catastrophic error has occurred. Reaction " + std::string(reaction->id()) + " has no participants.");
|
|
}
|
|
|
|
const double leakage_fraction = external_participants / total_participants;
|
|
const double coupling_fraction = (algebraic_participants + seed_participants) / total_participants;
|
|
|
|
leakage_flux += flow * leakage_fraction;
|
|
coupling_flux += flow * coupling_fraction;
|
|
|
|
|
|
}
|
|
|
|
if (coupling_flux / leakage_flux > FLUX_RATIO_THRESHOLD) {
|
|
LOG_TRACE_L1(
|
|
m_logger,
|
|
"Group containing {} is in equilibrium due to high coupling flux and balanced creation and destruction rate: <coupling: leakage flux = {}, coupling flux = {}, ratio = {} (Threshold: {})>",
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
int count = 0;
|
|
for (const auto& species: group.algebraic_species) {
|
|
ss << species.name();
|
|
if (count < group.algebraic_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
return ss.str();
|
|
}(),
|
|
leakage_flux,
|
|
coupling_flux,
|
|
coupling_flux / leakage_flux,
|
|
FLUX_RATIO_THRESHOLD
|
|
);
|
|
validated_groups.emplace_back(group);
|
|
validated_groups.back().is_in_equilibrium = true;
|
|
} else {
|
|
LOG_TRACE_L1(
|
|
m_logger,
|
|
"Group containing {} is NOT in equilibrium: <coupling: leakage flux = {}, coupling flux = {}, ratio = {} (Threshold: {})>",
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
int count = 0;
|
|
for (const auto& species : group.algebraic_species) {
|
|
ss << species.name();
|
|
if (count < group.algebraic_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
return ss.str();
|
|
}(),
|
|
leakage_flux,
|
|
coupling_flux,
|
|
coupling_flux / leakage_flux,
|
|
FLUX_RATIO_THRESHOLD
|
|
);
|
|
invalidated_groups.emplace_back(group);
|
|
invalidated_groups.back().is_in_equilibrium = false;
|
|
}
|
|
}
|
|
return {validated_groups, invalidated_groups};
|
|
}
|
|
|
|
fourdst::composition::Composition MultiscalePartitioningEngineView::solveQSEAbundances(
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9,
|
|
const double rho
|
|
) {
|
|
LOG_TRACE_L1(m_logger, "Solving for QSE abundances...");
|
|
|
|
// Sort by timescale to solve fastest QSE groups first (these can seed slower groups)
|
|
std::ranges::sort(m_qse_groups, [](const QSEGroup& a, const QSEGroup& b) {
|
|
return a.mean_timescale < b.mean_timescale;
|
|
});
|
|
fourdst::composition::Composition outputComposition = comp;
|
|
|
|
for (const auto&[is_in_equilibrium, algebraic_species, seed_species, mean_timescale] : m_qse_groups) {
|
|
if (!is_in_equilibrium || (algebraic_species.empty() && seed_species.empty())) {
|
|
continue;
|
|
}
|
|
fourdst::composition::Composition normalized_composition = comp;
|
|
for (const auto& species: algebraic_species) {
|
|
if (!normalized_composition.contains(species)) {
|
|
normalized_composition.registerSpecies(species);
|
|
normalized_composition.setMassFraction(species, 0.0);
|
|
}
|
|
}
|
|
for (const auto& species: seed_species) {
|
|
if (!normalized_composition.contains(species)) {
|
|
normalized_composition.registerSpecies(species);
|
|
normalized_composition.setMassFraction(species, 0.0);
|
|
}
|
|
}
|
|
bool normCompFinalizedOkay = normalized_composition.finalize(true);
|
|
if (!normCompFinalizedOkay) {
|
|
LOG_ERROR(m_logger, "Failed to finalize composition before QSE solve.");
|
|
throw std::runtime_error("Failed to finalize composition before QSE solve.");
|
|
}
|
|
|
|
Eigen::VectorXd Y_scale(algebraic_species.size());
|
|
Eigen::VectorXd v_initial(algebraic_species.size());
|
|
long i = 0;
|
|
std::unordered_map<Species, size_t> species_to_index_map;
|
|
for (const auto& species : algebraic_species) {
|
|
constexpr double abundance_floor = 1.0e-100;
|
|
const double initial_abundance = normalized_composition.getMolarAbundance(species);
|
|
const double Y = std::max(initial_abundance, abundance_floor);
|
|
v_initial(i) = std::log(Y);
|
|
species_to_index_map.emplace(species, i);
|
|
i++;
|
|
}
|
|
|
|
EigenFunctor functor(*this, algebraic_species, normalized_composition, T9, rho, Y_scale, species_to_index_map);
|
|
Eigen::LevenbergMarquardt lm(functor);
|
|
lm.parameters.ftol = 1.0e-10;
|
|
lm.parameters.xtol = 1.0e-10;
|
|
|
|
LOG_TRACE_L1(m_logger, "Minimizing functor...");
|
|
Eigen::LevenbergMarquardtSpace::Status status = lm.minimize(v_initial);
|
|
|
|
if (status <= 0 || status >= 4) {
|
|
std::stringstream msg;
|
|
msg << "While working on QSE group with algebraic species: ";
|
|
size_t count = 0;
|
|
for (const auto& species: algebraic_species) {
|
|
msg << species;
|
|
if (count < algebraic_species.size() - 1) {
|
|
msg << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
msg << " the QSE solver failed to converge with status: " << lm_status_map.at(status);
|
|
msg << ". This likely indicates that the QSE groups were not properly partitioned";
|
|
msg << " (for example if the algebraic set here contains species which should be dynamic like He-4 or H-1).";
|
|
LOG_ERROR(m_logger, "{}", msg.str());
|
|
throw std::runtime_error(msg.str());
|
|
}
|
|
LOG_TRACE_L1(m_logger, "QSE Group minimization succeeded with status: {}", lm_status_map.at(status));
|
|
Eigen::VectorXd Y_final_qse = v_initial.array().exp(); // Convert back to physical abundances using exponential scaling
|
|
i = 0;
|
|
for (const auto& species: algebraic_species) {
|
|
LOG_TRACE_L1(
|
|
m_logger,
|
|
"During QSE solving species {} started with a molar abundance of {} and ended with an abundance of {}.",
|
|
species.name(),
|
|
normalized_composition.getMolarAbundance(species),
|
|
Y_final_qse(i)
|
|
);
|
|
// double Xi = Y_final_qse(i) * species.mass(); // Convert from molar abundance to mass fraction
|
|
double Xi = utils::massFractionFromMolarAbundanceAndComposition(normalized_composition, species, Y_final_qse(i));
|
|
if (!outputComposition.hasSpecies(species)) {
|
|
outputComposition.registerSpecies(species);
|
|
}
|
|
outputComposition.setMassFraction(species, Xi);
|
|
i++;
|
|
}
|
|
}
|
|
bool didFinalize = outputComposition.finalize(false);
|
|
if (!didFinalize) {
|
|
LOG_ERROR(m_logger, "Failed to finalize composition after solving QSE abundances.");
|
|
m_logger->flush_log();
|
|
throw std::runtime_error("Failed to finalize composition after solving QSE abundances.");
|
|
}
|
|
return outputComposition;
|
|
}
|
|
|
|
size_t MultiscalePartitioningEngineView::identifyMeanSlowestPool(
|
|
const std::vector<std::vector<Species>> &pools,
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9,
|
|
const double rho
|
|
) const {
|
|
const auto& result = m_baseEngine.getSpeciesDestructionTimescales(comp, T9, rho);
|
|
if (!result) {
|
|
LOG_ERROR(m_logger, "Failed to get species timescales due to stale engine state");
|
|
m_logger->flush_log();
|
|
throw exceptions::StaleEngineError("Failed to get species timescales due to stale engine state");
|
|
}
|
|
const std::unordered_map<Species, double> all_timescales = result.value();
|
|
|
|
size_t slowest_pool_index = 0; // Default to the first pool if no valid pool is found
|
|
double slowest_mean_timescale = std::numeric_limits<double>::min();
|
|
size_t count = 0;
|
|
for (const auto& pool : pools) {
|
|
double mean_timescale = 0.0;
|
|
for (const auto& species : pool) {
|
|
const double timescale = all_timescales.at(species);
|
|
mean_timescale += timescale;
|
|
}
|
|
mean_timescale = mean_timescale / static_cast<double>(pool.size());
|
|
if (std::isinf(mean_timescale)) {
|
|
LOG_CRITICAL(m_logger, "Encountered infinite mean timescale for pool {} with species: {}",
|
|
count, [&]() -> std::string {
|
|
std::stringstream ss;
|
|
size_t iCount = 0;
|
|
for (const auto& species : pool) {
|
|
ss << species.name() << ": " << all_timescales.at(species);
|
|
if (iCount < pool.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
iCount++;
|
|
}
|
|
return ss.str();
|
|
}()
|
|
);
|
|
m_logger->flush_log();
|
|
throw std::logic_error("Encountered infinite mean destruction timescale for a pool while identifying the mean slowest pool set, indicating a potential issue with species timescales. Check log file for more details on specific pool composition...");
|
|
}
|
|
if (mean_timescale > slowest_mean_timescale) {
|
|
slowest_mean_timescale = mean_timescale;
|
|
slowest_pool_index = &pool - &pools[0]; // Get the index of the pool
|
|
}
|
|
}
|
|
return slowest_pool_index;
|
|
}
|
|
|
|
std::unordered_map<Species, std::vector<Species>> MultiscalePartitioningEngineView::buildConnectivityGraph(
|
|
const std::vector<Species> &species_pool
|
|
) const {
|
|
std::unordered_map<Species, std::vector<Species>> connectivity_graph;
|
|
const std::set<Species> pool_set(species_pool.begin(), species_pool.end());
|
|
|
|
const std::unordered_set<Species> pool_species = [&]() -> std::unordered_set<Species> {
|
|
std::unordered_set<Species> result;
|
|
for (const auto& species : species_pool) {
|
|
result.insert(species);
|
|
}
|
|
return result;
|
|
}();
|
|
|
|
std::map<size_t, std::vector<reaction::LogicalReaclibReaction*>> speciesReactionMap;
|
|
std::vector<const reaction::LogicalReaclibReaction*> candidate_reactions;
|
|
|
|
for (const auto& reaction : m_baseEngine.getNetworkReactions()) {
|
|
const std::vector<Species> &reactants = reaction->reactants();
|
|
const std::vector<Species> &products = reaction->products();
|
|
|
|
std::unordered_set<Species> reactant_set(reactants.begin(), reactants.end());
|
|
std::unordered_set<Species> product_set(products.begin(), products.end());
|
|
|
|
// Only consider reactions where at least one distinct reactant and product are in the pool
|
|
if (has_distinct_reactant_and_product_species(pool_species, reactant_set, product_set)) {
|
|
std::set<Species> involvedSet;
|
|
involvedSet.insert(reactants.begin(), reactants.end());
|
|
involvedSet.insert(products.begin(), products.end());
|
|
|
|
std::vector<Species> intersection;
|
|
intersection.reserve(involvedSet.size());
|
|
|
|
for (const auto& s : pool_species) { // Find intersection with pool species
|
|
if (involvedSet.contains(s)) {
|
|
intersection.push_back(s);
|
|
}
|
|
}
|
|
|
|
// Add clique
|
|
for (const auto& u : intersection) {
|
|
for (const auto& v : intersection) {
|
|
if (u != v) { // Avoid self-loops
|
|
connectivity_graph[u].push_back(v);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
return connectivity_graph;
|
|
}
|
|
|
|
std::vector<MultiscalePartitioningEngineView::QSEGroup> MultiscalePartitioningEngineView::constructCandidateGroups(
|
|
const std::vector<std::vector<Species>> &candidate_pools,
|
|
const fourdst::composition::Composition &comp,
|
|
const double T9,
|
|
const double rho
|
|
) const {
|
|
const auto& all_reactions = m_baseEngine.getNetworkReactions();
|
|
const auto& result = m_baseEngine.getSpeciesDestructionTimescales(comp, T9, rho);
|
|
if (!result) {
|
|
LOG_ERROR(m_logger, "Failed to get species timescales due to stale engine state");
|
|
m_logger->flush_log();
|
|
throw exceptions::StaleEngineError("Failed to get species timescales due to stale engine state");
|
|
}
|
|
const std::unordered_map<Species, double> destruction_timescales = result.value();
|
|
|
|
std::vector<QSEGroup> candidate_groups;
|
|
for (const auto& pool : candidate_pools) {
|
|
if (pool.empty()) continue; // Skip empty pools
|
|
|
|
// For each pool first identify all topological bridge connections
|
|
std::vector<std::pair<const reaction::Reaction*, double>> bridge_reactions;
|
|
for (const auto& ash: pool) {
|
|
for (const auto& reaction : all_reactions) {
|
|
if (reaction->contains(ash)) {
|
|
// Check to make sure there is at least one reactant that is not in the pool
|
|
// This lets seed nuclei bring mass into the QSE group.
|
|
bool has_external_reactant = false;
|
|
for (const auto& reactant : reaction->reactants()) {
|
|
if (std::ranges::find(pool, reactant) == pool.end()) {
|
|
has_external_reactant = true;
|
|
LOG_TRACE_L3(m_logger, "Found external reactant {} in reaction {} for species {}.", reactant.name(), reaction->id(), ash.name());
|
|
break; // Found an external reactant, no need to check further
|
|
}
|
|
}
|
|
if (has_external_reactant) {
|
|
double flow = std::abs(m_baseEngine.calculateMolarReactionFlow(*reaction, comp, T9, rho));
|
|
LOG_TRACE_L3(m_logger, "Found bridge reaction {} with flow {} for species {}.", reaction->id(), flow, ash.name());
|
|
bridge_reactions.emplace_back(reaction.get(), flow);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
std::ranges::sort(
|
|
bridge_reactions,
|
|
[](const auto& a, const auto& b) {
|
|
return a.second > b.second; // Sort by flow in descending order
|
|
});
|
|
|
|
constexpr double MIN_GAP_THRESHOLD = 1; // Minimum logarithmic molar flow gap threshold for bridge reactions
|
|
std::vector<size_t> split_points;
|
|
for (size_t i = 0; i < bridge_reactions.size() - 1; ++i) {
|
|
const double f1 = bridge_reactions[i].second;
|
|
const double f2 = bridge_reactions[i + 1].second;
|
|
if (std::log10(f1) - std::log10(f2) > MIN_GAP_THRESHOLD) {
|
|
LOG_TRACE_L3(m_logger, "Detected gap between bridge reactions with flows {} and {}.", f1, f2);
|
|
split_points.push_back(i + 1);
|
|
}
|
|
}
|
|
|
|
if (split_points.empty()) { // If no split points were found, we consider the whole set of bridge reactions as one group.
|
|
split_points.push_back(bridge_reactions.size() - 1);
|
|
}
|
|
|
|
std::vector<Species> seed_species;
|
|
for (auto &reaction: bridge_reactions | std::views::keys) {
|
|
for (const auto& fuel : reaction->reactants()) {
|
|
// Only add the fuel if it is not already in the pool
|
|
if (std::ranges::find(pool, fuel) == pool.end()) {
|
|
seed_species.push_back(fuel);
|
|
}
|
|
}
|
|
}
|
|
std::set<Species> pool_species(pool.begin(), pool.end());
|
|
for (const auto& species : seed_species) {
|
|
pool_species.insert(species);
|
|
}
|
|
const std::set<Species> poolSet(pool.begin(), pool.end());
|
|
const std::set<Species> seedSet(seed_species.begin(), seed_species.end());
|
|
|
|
double mean_timescale = 0.0;
|
|
for (const auto& species : poolSet) {
|
|
if (destruction_timescales.contains(species)) {
|
|
mean_timescale += std::min(destruction_timescales.at(species), species.halfLife()); // Use the minimum of destruction timescale and half-life
|
|
} else {
|
|
mean_timescale += species.halfLife();
|
|
}
|
|
}
|
|
mean_timescale /= static_cast<double>(poolSet.size());
|
|
QSEGroup qse_group(false, poolSet, seedSet, mean_timescale);
|
|
candidate_groups.push_back(qse_group);
|
|
}
|
|
return candidate_groups;
|
|
}
|
|
|
|
|
|
int MultiscalePartitioningEngineView::EigenFunctor::operator()(const InputType &v_qse, OutputType &f_qse) const {
|
|
fourdst::composition::Composition comp_trial = m_initial_comp;
|
|
Eigen::VectorXd y_qse = v_qse.array().exp(); // Convert to physical abundances using exponential scaling
|
|
|
|
for (const auto& species: m_qse_solve_species) {
|
|
if (!comp_trial.hasSymbol(std::string(species.name()))) {
|
|
comp_trial.registerSpecies(species);
|
|
}
|
|
auto index = static_cast<long>(m_qse_solve_species_index_map.at(species));
|
|
const double molarAbundance = y_qse[index];
|
|
double massFraction = utils::massFractionFromMolarAbundanceAndComposition(m_initial_comp, species, molarAbundance);
|
|
comp_trial.setMassFraction(species, massFraction);
|
|
}
|
|
|
|
|
|
const bool didFinalize = comp_trial.finalize(false);
|
|
if (!didFinalize) {
|
|
LOG_TRACE_L1(m_view->m_logger, "While evaluating the functor, failed to finalize composition. This is likely because the solver took a step outside of physical abundances. This is not an error; rather, the solver will be told to take a different step.");
|
|
f_qse.resize(static_cast<long>(m_qse_solve_species.size()));
|
|
f_qse.setConstant(1.0e20); // Return a large residual to indicate failure
|
|
return 0;
|
|
}
|
|
|
|
const auto result = m_view->getBaseEngine().calculateRHSAndEnergy(comp_trial, m_T9, m_rho);
|
|
if (!result) {
|
|
throw exceptions::StaleEngineError("Failed to calculate RHS and energy due to stale engine state");
|
|
}
|
|
const auto&[dydt, nuclearEnergyGenerationRate] = result.value();
|
|
f_qse.resize(static_cast<long>(m_qse_solve_species.size()));
|
|
long i = 0;
|
|
// TODO: make sure that just counting up i is a valid approach, this is a possible place an indexing bug may have crept in
|
|
for (const auto& species: m_qse_solve_species) {
|
|
const double dydt_i = dydt.at(species);
|
|
f_qse(i) = dydt_i/y_qse(i); // We square the residuals to improve numerical stability in the solver
|
|
i++;
|
|
}
|
|
LOG_TRACE_L2(
|
|
m_view->m_logger,
|
|
"Functor evaluation at T9 = {}, rho = {}, y_qse = <{}> complete. ||f|| = {}",
|
|
m_T9,
|
|
m_rho,
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
for (long j = 0; j < y_qse.size(); ++j) {
|
|
ss << y_qse(j);
|
|
if (j < y_qse.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
}
|
|
return ss.str();
|
|
}(),
|
|
f_qse.norm()
|
|
);
|
|
LOG_TRACE_L3(
|
|
m_view->m_logger,
|
|
"{}",
|
|
[&]() -> std::string {
|
|
std::stringstream ss;
|
|
const std::vector species(m_qse_solve_species.begin(), m_qse_solve_species.end());
|
|
for (long j = 0; j < f_qse.size(); ++j) {
|
|
ss << "Residual for species " << species.at(j).name() << " f(" << j << ") = " << f_qse(j) << "\n";
|
|
}
|
|
return ss.str();
|
|
}()
|
|
);
|
|
return 0;
|
|
}
|
|
|
|
int MultiscalePartitioningEngineView::EigenFunctor::df(const InputType &v_qse, JacobianType &J_qse) const {
|
|
fourdst::composition::Composition comp_trial = m_initial_comp;
|
|
Eigen::VectorXd y_qse = v_qse.array().exp(); // Convert to physical abundances using exponential scaling
|
|
|
|
for (const auto& species: m_qse_solve_species) {
|
|
if (!comp_trial.hasSymbol(std::string(species.name()))) {
|
|
comp_trial.registerSpecies(species);
|
|
}
|
|
const double molarAbundance = y_qse[static_cast<long>(m_qse_solve_species_index_map.at(species))];
|
|
double massFraction = utils::massFractionFromMolarAbundanceAndComposition(m_initial_comp, species, molarAbundance);
|
|
comp_trial.setMassFraction(species, massFraction);
|
|
}
|
|
|
|
const bool didFinalize = comp_trial.finalize(false);
|
|
if (!didFinalize) {
|
|
LOG_TRACE_L1(m_view->m_logger, "While evaluating the Jacobian, failed to finalize composition. This is likely because the solver took a step outside of physical abundances. This is not an error; rather, the solver will be told to take a different step. Returning Identity");
|
|
J_qse.resize(static_cast<long>(m_qse_solve_species.size()), static_cast<long>(m_qse_solve_species.size()));
|
|
J_qse.setIdentity();
|
|
return 0;
|
|
}
|
|
|
|
std::vector<Species> qse_species_vector(m_qse_solve_species.begin(), m_qse_solve_species.end());
|
|
m_view->getBaseEngine().generateJacobianMatrix(comp_trial, m_T9, m_rho, qse_species_vector);
|
|
const auto result = m_view->getBaseEngine().calculateRHSAndEnergy(comp_trial, m_T9, m_rho);
|
|
if (!result) {
|
|
throw exceptions::StaleEngineError("Failed to calculate RHS and energy due to stale engine state");
|
|
}
|
|
const auto&[dydt, nuclearEnergyGenerationRate] = result.value();
|
|
|
|
const long N = static_cast<long>(m_qse_solve_species.size());
|
|
J_qse.resize(N, N);
|
|
long rowID = 0;
|
|
for (const auto& rowSpecies : m_qse_solve_species) {
|
|
long colID = 0;
|
|
for (const auto& colSpecies: m_qse_solve_species) {
|
|
J_qse(rowID, colID) = m_view->getBaseEngine().getJacobianMatrixEntry(
|
|
rowSpecies,
|
|
colSpecies
|
|
);
|
|
colID += 1;
|
|
LOG_TRACE_L3(m_view->m_logger, "Jacobian[{}, {}] (d(dY({}))/dY({})) = {}", rowID, colID - 1, rowSpecies.name(), colSpecies.name(), J_qse(rowID, colID - 1));
|
|
}
|
|
rowID += 1;
|
|
}
|
|
|
|
for (long i = 0; i < J_qse.rows(); ++i) {
|
|
for (long j = 0; j < J_qse.cols(); ++j) {
|
|
double on_diag_correction = 0.0;
|
|
if (i == j) {
|
|
auto rowSpecies = *(std::next(m_qse_solve_species.begin(), i));
|
|
const double Fi = dydt.at(rowSpecies);
|
|
on_diag_correction = Fi / y_qse(i);
|
|
}
|
|
J_qse(i, j) = y_qse(j) * (J_qse(i, j) - on_diag_correction) / y_qse(i); // Apply chain rule J'(i,j) = y_j * (J(i,j) - δ_ij(F_i/Y_i)) / Y_i
|
|
}
|
|
}
|
|
|
|
return 0; // Success
|
|
}
|
|
|
|
|
|
QSECacheKey::QSECacheKey(
|
|
const double T9,
|
|
const double rho,
|
|
const std::vector<double> &Y
|
|
) :
|
|
m_T9(T9),
|
|
m_rho(rho),
|
|
m_Y(Y) {
|
|
m_hash = hash();
|
|
}
|
|
|
|
size_t QSECacheKey::hash() const {
|
|
std::size_t seed = 0;
|
|
|
|
hash_combine(seed, m_Y.size());
|
|
|
|
hash_combine(seed, bin(m_T9, m_cacheConfig.T9_tol));
|
|
hash_combine(seed, bin(m_rho, m_cacheConfig.rho_tol));
|
|
|
|
double negThresh = 1e-10; // Threshold for considering a value as negative.
|
|
for (double Yi : m_Y) {
|
|
if (Yi < 0.0 && std::abs(Yi) < negThresh) {
|
|
Yi = 0.0; // Avoid negative abundances
|
|
} else if (Yi < 0.0 && std::abs(Yi) >= negThresh) {
|
|
throw std::invalid_argument("Yi should be positive for valid hashing (expected Yi > 0, received " + std::to_string(Yi) + ")");
|
|
}
|
|
hash_combine(seed, bin(Yi, m_cacheConfig.Yi_tol));
|
|
}
|
|
|
|
return seed;
|
|
|
|
}
|
|
|
|
long QSECacheKey::bin(const double value, const double tol) {
|
|
return static_cast<long>(std::floor(value / tol));
|
|
}
|
|
|
|
bool QSECacheKey::operator==(const QSECacheKey &other) const {
|
|
return m_hash == other.m_hash;
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::QSEGroup::operator==(const QSEGroup &other) const {
|
|
return mean_timescale == other.mean_timescale;
|
|
}
|
|
|
|
void MultiscalePartitioningEngineView::QSEGroup::removeSpecies(const Species &species) {
|
|
if (algebraic_species.contains(species)) {
|
|
algebraic_species.erase(species);
|
|
}
|
|
if (seed_species.contains(species)) {
|
|
seed_species.erase(species);
|
|
}
|
|
}
|
|
|
|
void MultiscalePartitioningEngineView::QSEGroup::addSpeciesToAlgebraic(const Species &species) {
|
|
if (seed_species.contains(species)) {
|
|
const std::string msg = std::format("Cannot add species {} to algebraic set as it is already in the seed set.", species.name());
|
|
throw std::invalid_argument(msg);
|
|
}
|
|
if (!algebraic_species.contains(species)) {
|
|
algebraic_species.insert(species);
|
|
}
|
|
}
|
|
|
|
void MultiscalePartitioningEngineView::QSEGroup::addSpeciesToSeed(const Species &species) {
|
|
if (algebraic_species.contains(species)) {
|
|
const std::string msg = std::format("Cannot add species {} to seed set as it is already in the algebraic set.", species.name());
|
|
throw std::invalid_argument(msg);
|
|
}
|
|
if (!seed_species.contains(species)) {
|
|
seed_species.insert(species);
|
|
}
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::QSEGroup::operator<(const QSEGroup &other) const {
|
|
return mean_timescale < other.mean_timescale;
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::QSEGroup::operator>(const QSEGroup &other) const {
|
|
return mean_timescale > other.mean_timescale;
|
|
}
|
|
|
|
bool MultiscalePartitioningEngineView::QSEGroup::operator!=(const QSEGroup &other) const {
|
|
return !(*this == other);
|
|
}
|
|
|
|
std::string MultiscalePartitioningEngineView::QSEGroup::toString() const {
|
|
std::stringstream ss;
|
|
ss << "QSEGroup(Algebraic: [";
|
|
size_t count = 0;
|
|
for (const auto& species : algebraic_species) {
|
|
ss << species.name();
|
|
if (count < algebraic_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
ss << "], Seed: [";
|
|
count = 0;
|
|
for (const auto& species : seed_species) {
|
|
ss << species.name();
|
|
if (count < seed_species.size() - 1) {
|
|
ss << ", ";
|
|
}
|
|
count++;
|
|
}
|
|
ss << "], Mean Timescale: " << mean_timescale << ", Is In Equilibrium: " << (is_in_equilibrium ? "True" : "False") << ")";
|
|
return ss.str();
|
|
|
|
}
|
|
|
|
void MultiscalePartitioningEngineView::CacheStats::hit(const operators op) {
|
|
if (op == operators::All) {
|
|
throw std::invalid_argument("Cannot use 'ALL' as an operator for a hit");
|
|
}
|
|
|
|
m_hit ++;
|
|
m_operatorHits[op]++;
|
|
}
|
|
void MultiscalePartitioningEngineView::CacheStats::miss(const operators op) {
|
|
if (op == operators::All) {
|
|
throw std::invalid_argument("Cannot use 'ALL' as an operator for a miss");
|
|
}
|
|
|
|
m_miss ++;
|
|
m_operatorMisses[op]++;
|
|
}
|
|
|
|
size_t MultiscalePartitioningEngineView::CacheStats::hits(const operators op) const {
|
|
if (op == operators::All) {
|
|
return m_hit;
|
|
}
|
|
return m_operatorHits.at(op);
|
|
}
|
|
|
|
size_t MultiscalePartitioningEngineView::CacheStats::misses(const operators op) const {
|
|
if (op == operators::All) {
|
|
return m_miss;
|
|
}
|
|
return m_operatorMisses.at(op);
|
|
}
|
|
|
|
}
|