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GridFire/src/lib/engine/views/engine_multiscale.cpp

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#include "gridfire/engine/views/engine_multiscale.h"
#include "gridfire/exceptions/error_engine.h"
#include "gridfire/engine/procedures/priming.h"
#include <stdexcept>
#include <vector>
#include <ranges>
#include <unordered_map>
#include <unordered_set>
#include <fstream>
#include <queue>
#include <algorithm>
#include "fourdst/atomic/species.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "xxhash64.h"
#include "fourdst/composition/utils/composition_hash.h"
namespace {
using namespace fourdst::atomic;
std::vector<std::vector<Species>> findConnectedComponentsBFS(
const std::unordered_map<Species, std::vector<Species>>& graph,
const std::vector<Species>& nodes
) {
std::vector<std::vector<Species>> components;
std::unordered_set<Species> visited;
for (const Species& start_node : nodes) {
if (!visited.contains(start_node)) {
std::vector<Species> current_component;
std::queue<Species> q;
q.push(start_node);
visited.insert(start_node);
while (!q.empty()) {
Species u = q.front();
q.pop();
current_component.push_back(u);
if (graph.contains(u)) {
for (const auto& v : graph.at(u)) {
if (!visited.contains(v)) {
visited.insert(v);
q.push(v);
}
}
}
}
components.push_back(current_component);
}
}
return components;
}
struct SpeciesSetIntersection {
const Species species;
std::size_t count;
};
std::expected<SpeciesSetIntersection, std::string> get_intersection_info (
const std::unordered_set<Species>& setA,
const std::unordered_set<Species>& setB
) {
// Iterate over the smaller of the two
auto* outerSet = &setA;
auto* innerSet = &setB;
if (setA.size() > setB.size()) {
outerSet = &setB;
innerSet = &setA;
}
std::size_t matchCount = 0;
const Species* firstMatch = nullptr;
for (const Species& sp : *outerSet) {
if (innerSet->contains(sp)) {
if (matchCount == 0) {
firstMatch = &sp;
}
++matchCount;
if (matchCount > 1) {
break;
}
}
}
if (!firstMatch) {
// No matches found
return std::unexpected{"Intersection is empty"};
}
if (matchCount == 0) {
// No matches found
return std::unexpected{"No intersection found"};
}
// Return the first match and the count of matches
return SpeciesSetIntersection{*firstMatch, matchCount};
}
bool has_distinct_reactant_and_product_species (
const std::unordered_set<Species>& poolSpecies,
const std::unordered_set<Species>& reactants,
const std::unordered_set<Species>& products
) {
const auto reactant_result = get_intersection_info(poolSpecies, reactants);
if (!reactant_result) {
return false; // No reactants found
}
const auto [reactantSample, reactantCount] = reactant_result.value();
const auto product_result = get_intersection_info(poolSpecies, products);
if (!product_result) {
return false; // No products found
}
const auto [productSample, productCount] = product_result.value();
// If either side has ≥2 distinct matches, we can always pick
// one from each that differ.
if (reactantCount > 1 || productCount > 1) {
return true;
}
// Exactly one match on each side → they must differ
return reactantSample != productSample;
}
const std::unordered_map<Eigen::LevenbergMarquardtSpace::Status, std::string> lm_status_map = {
{Eigen::LevenbergMarquardtSpace::Status::NotStarted, "NotStarted"},
{Eigen::LevenbergMarquardtSpace::Status::Running, "Running"},
{Eigen::LevenbergMarquardtSpace::Status::ImproperInputParameters, "ImproperInputParameters"},
{Eigen::LevenbergMarquardtSpace::Status::RelativeReductionTooSmall, "RelativeReductionTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::RelativeErrorTooSmall, "RelativeErrorTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::RelativeErrorAndReductionTooSmall, "RelativeErrorAndReductionTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::CosinusTooSmall, "CosinusTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::TooManyFunctionEvaluation, "TooManyFunctionEvaluation"},
{Eigen::LevenbergMarquardtSpace::Status::FtolTooSmall, "FtolTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::XtolTooSmall, "XtolTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::GtolTooSmall, "GtolTooSmall"},
{Eigen::LevenbergMarquardtSpace::Status::UserAsked, "UserAsked"}
};
}
namespace gridfire {
using fourdst::atomic::Species;
MultiscalePartitioningEngineView::MultiscalePartitioningEngineView(
DynamicEngine& baseEngine
) : m_baseEngine(baseEngine) {}
const std::vector<Species> & MultiscalePartitioningEngineView::getNetworkSpecies() const {
return m_baseEngine.getNetworkSpecies();
}
std::expected<StepDerivatives<double>, expectations::StaleEngineError> MultiscalePartitioningEngineView::calculateRHSAndEnergy(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
LOG_TRACE_L2(m_logger, "Calculating RHS and Energy in MultiscalePartitioningEngineView at T9 = {}, rho = {}.", T9, rho);
LOG_TRACE_L2(m_logger, "Input composition is {}", [&comp]() -> std::string {
std::stringstream ss;
size_t i = 0;
for (const auto& [species, abundance] : comp) {
ss << species.name() << ": " << abundance;
if (i < comp.size() - 1) {
ss << ", ";
}
i++;
}
return ss.str();
}());
const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
LOG_TRACE_L2(m_logger, "Equilibrated composition prior to calling base engine is {}", [&qseComposition, &comp]() -> std::string {
std::stringstream ss;
size_t i = 0;
for (const auto& [species, abundance] : qseComposition) {
ss << species.name() << ": " << abundance;
if (comp.contains(species)) {
ss << " (input: " << comp.getMolarAbundance(species) << ")";
}
if (i < qseComposition.size() - 1) {
ss << ", ";
}
i++;
}
return ss.str();
}());
const auto result = m_baseEngine.calculateRHSAndEnergy(comp, T9, rho);
LOG_TRACE_L2(m_logger, "Base engine calculation of RHS and Energy complete.");
if (!result) {
LOG_TRACE_L2(m_logger, "Base engine returned stale error during RHS and Energy calculation.");
return std::unexpected{result.error()};
}
auto deriv = result.value();
LOG_TRACE_L2(m_logger, "Zeroing out algebraic species derivatives.");
for (const auto& species : m_algebraic_species) {
deriv.dydt[species] = 0.0; // Fix the algebraic species to the equilibrium abundances we calculate.
}
LOG_TRACE_L2(m_logger, "Done Zeroing out algebraic species derivatives.");
return deriv;
}
EnergyDerivatives MultiscalePartitioningEngineView::calculateEpsDerivatives(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
return m_baseEngine.calculateEpsDerivatives(comp, T9, rho);
}
NetworkJacobian MultiscalePartitioningEngineView::generateJacobianMatrix(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
return m_baseEngine.generateJacobianMatrix(comp, T9, rho, m_dynamic_species);
}
NetworkJacobian MultiscalePartitioningEngineView::generateJacobianMatrix(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho,
const std::vector<Species> &activeSpecies
) const {
bool activeSpeciesIsSubset = true;
for (const auto& species : activeSpecies) {
if (!involvesSpecies(species)) activeSpeciesIsSubset = false;
}
if (!activeSpeciesIsSubset) {
std::string msg = std::format(
"Active species set contains species ({}) not present in network partition. Cannot generate jacobian matrix due to this.",
[&]() -> std::string {
std::stringstream ss;
for (const auto& species : activeSpecies) {
if (!this->involvesSpecies(species)) {
ss << species << " ";
}
}
return ss.str();
}()
);
LOG_CRITICAL(m_logger, "{}", msg);
throw std::runtime_error(msg);
}
std::vector<Species> dynamicActiveSpeciesIntersection;
for (const auto& species : activeSpecies) {
if (involvesSpeciesInDynamic(species)) {
dynamicActiveSpeciesIntersection.push_back(species);
}
}
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
return m_baseEngine.generateJacobianMatrix(comp, T9, rho, dynamicActiveSpeciesIntersection);
}
NetworkJacobian MultiscalePartitioningEngineView::generateJacobianMatrix(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho,
const SparsityPattern &sparsityPattern
) const {
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
return m_baseEngine.generateJacobianMatrix(comp, T9, rho, sparsityPattern);
}
void MultiscalePartitioningEngineView::generateStoichiometryMatrix() {
m_baseEngine.generateStoichiometryMatrix();
}
int MultiscalePartitioningEngineView::getStoichiometryMatrixEntry(
const Species& species,
const reaction::Reaction& reaction
) const {
return m_baseEngine.getStoichiometryMatrixEntry(species, reaction);
}
double MultiscalePartitioningEngineView::calculateMolarReactionFlow(
const reaction::Reaction &reaction,
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
return m_baseEngine.calculateMolarReactionFlow(reaction, comp, T9, rho);
}
const reaction::ReactionSet & MultiscalePartitioningEngineView::getNetworkReactions() const {
return m_baseEngine.getNetworkReactions();
}
void MultiscalePartitioningEngineView::setNetworkReactions(const reaction::ReactionSet &reactions) {
LOG_CRITICAL(m_logger, "setNetworkReactions is not supported in MultiscalePartitioningEngineView. Did you mean to call this on the base engine?");
throw exceptions::UnableToSetNetworkReactionsError("setNetworkReactions is not supported in MultiscalePartitioningEngineView. Did you mean to call this on the base engine?");
}
std::expected<std::unordered_map<Species, double>, expectations::StaleEngineError> MultiscalePartitioningEngineView::getSpeciesTimescales(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
const auto result = m_baseEngine.getSpeciesTimescales(comp, T9, rho);
if (!result) {
return std::unexpected{result.error()};
}
std::unordered_map<Species, double> speciesTimescales = result.value();
for (const auto& algebraicSpecies : m_algebraic_species) {
speciesTimescales[algebraicSpecies] = std::numeric_limits<double>::infinity(); // Algebraic species have infinite timescales.
}
return speciesTimescales;
}
std::expected<std::unordered_map<Species, double>, expectations::StaleEngineError>
MultiscalePartitioningEngineView::getSpeciesDestructionTimescales(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
const auto result = m_baseEngine.getSpeciesDestructionTimescales(comp, T9, rho);
if (!result) {
return std::unexpected{result.error()};
}
std::unordered_map<Species, double> speciesDestructionTimescales = result.value();
for (const auto& algebraicSpecies : m_algebraic_species) {
speciesDestructionTimescales[algebraicSpecies] = std::numeric_limits<double>::infinity(); // Algebraic species have infinite destruction timescales.
}
return speciesDestructionTimescales;
}
fourdst::composition::Composition MultiscalePartitioningEngineView::update(const NetIn &netIn) {
const fourdst::composition::Composition baseUpdatedComposition = m_baseEngine.update(netIn);
NetIn baseUpdatedNetIn = netIn;
baseUpdatedNetIn.composition = baseUpdatedComposition;
fourdst::composition::Composition equilibratedComposition = partitionNetwork(baseUpdatedNetIn);
return equilibratedComposition;
}
bool MultiscalePartitioningEngineView::isStale(const NetIn &netIn) {
return m_baseEngine.isStale(netIn);
}
void MultiscalePartitioningEngineView::setScreeningModel(
const screening::ScreeningType model
) {
m_baseEngine.setScreeningModel(model);
}
screening::ScreeningType MultiscalePartitioningEngineView::getScreeningModel() const {
return m_baseEngine.getScreeningModel();
}
const DynamicEngine & MultiscalePartitioningEngineView::getBaseEngine() const {
return m_baseEngine;
}
std::vector<std::vector<Species>> MultiscalePartitioningEngineView::analyzeTimescalePoolConnectivity(
const std::vector<std::vector<Species>> &timescale_pools
) const {
std::vector<std::vector<Species>> final_connected_pools;
for (const auto& pool : timescale_pools) {
if (pool.empty()) {
continue; // Skip empty pools
}
// For each timescale pool, we need to analyze connectivity.
auto connectivity_graph = buildConnectivityGraph(pool);
auto components = findConnectedComponentsBFS(connectivity_graph, pool);
final_connected_pools.insert(final_connected_pools.end(), components.begin(), components.end());
}
return final_connected_pools;
}
fourdst::composition::Composition MultiscalePartitioningEngineView::partitionNetwork(
const NetIn &netIn
) {
// --- Step 0. Prime the network ---
const PrimingReport primingReport = m_baseEngine.primeEngine(netIn);
const fourdst::composition::Composition& comp = primingReport.primedComposition;
const double T9 = netIn.temperature / 1e9;
const double rho = netIn.density;
// --- Step 0.5 Clear previous state ---
LOG_TRACE_L1(m_logger, "Partitioning network...");
LOG_TRACE_L1(m_logger, "Clearing previous state...");
m_qse_groups.clear();
m_dynamic_species.clear();
m_algebraic_species.clear();
m_composition_cache.clear(); // We need to clear the cache now cause the same comp, temp, and density may result in a different value
// --- Step 1. Identify distinct timescale regions ---
LOG_TRACE_L1(m_logger, "Identifying fast reactions...");
const std::vector<std::vector<Species>> timescale_pools = partitionByTimescale(comp, T9, rho);
LOG_TRACE_L1(m_logger, "Found {} timescale pools.", timescale_pools.size());
// --- Step 2. Select the mean slowest pool as the base dynamical group ---
LOG_TRACE_L1(m_logger, "Identifying mean slowest pool...");
const size_t mean_slowest_pool_index = identifyMeanSlowestPool(timescale_pools, comp, T9, rho);
LOG_TRACE_L1(m_logger, "Mean slowest pool index: {}", mean_slowest_pool_index);
// --- Step 3. Push the slowest pool into the dynamic species list ---
for (const auto& slowSpecies : timescale_pools[mean_slowest_pool_index]) {
m_dynamic_species.push_back(slowSpecies);
}
// --- Step 4. Pack Candidate QSE Groups ---
std::vector<std::vector<Species>> candidate_pools;
for (size_t i = 0; i < timescale_pools.size(); ++i) {
if (i == mean_slowest_pool_index) continue; // Skip the slowest pool
LOG_TRACE_L1(m_logger, "Group {} with {} species identified for potential QSE.", i, timescale_pools[i].size());
candidate_pools.push_back(timescale_pools[i]);
}
LOG_TRACE_L1(m_logger, "Preforming connectivity analysis on timescale pools...");
const std::vector<std::vector<Species>> connected_pools = analyzeTimescalePoolConnectivity(candidate_pools);
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"
);
// Sort the QSE groups by mean timescale so that fastest groups get equilibrated first (as these may feed slower groups)
std::ranges::sort(m_qse_groups, [](const QSEGroup& a, const QSEGroup& b) {
return a.mean_timescale < b.mean_timescale;
});
for (const auto& species : m_baseEngine.getNetworkSpecies()) {
bool involvesAlgebraic = involvesSpeciesInQSE(species);
if (std::ranges::find(m_dynamic_species, species) == m_dynamic_species.end() && !involvesAlgebraic) {
// Species is classed as neither dynamic nor algebraic at end of partitioning → add to dynamic set
m_dynamic_species.push_back(species);
}
}
return getNormalizedEquilibratedComposition(comp, 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());
}
}
// const fourdst::composition::Composition qseComposition = getNormalizedEquilibratedComposition(comp, T9, rho);
// 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(netIn.composition.size(), 0.0); // Initialize with zeros
for (const auto& [sp, y] : netIn.composition) {
Y[getSpeciesIndex(sp)] = y; // 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);
}
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::getNormalizedEquilibratedComposition(
const fourdst::composition::CompositionAbstract& comp,
const double T9,
const double rho
) const {
const std::array<uint64_t, 3> hashes = {
fourdst::composition::utils::CompositionHash::hash_exact(comp),
std::hash<double>()(T9),
std::hash<double>()(rho)
};
const uint64_t composite_hash = XXHash64::hash(hashes.begin(), sizeof(uint64_t) * 3, 0);
if (m_composition_cache.contains(composite_hash)) {
LOG_TRACE_L1(m_logger, "Cache Hit in Multiscale Partitioning Engine View for composition at T9 = {}, rho = {}.", T9, rho);
return m_composition_cache.at(composite_hash);
}
fourdst::composition::Composition qseComposition = solveQSEAbundances(comp, T9, rho);
for (const auto &[sp, y]: qseComposition) {
if (y < 0.0 && std::abs(y) < 1e-20) {
qseComposition.setMolarAbundance(sp, 0.0); // normalize small negative abundances to zero
}
}
m_composition_cache[composite_hash] = qseComposition;
return qseComposition;
}
fourdst::composition::Composition MultiscalePartitioningEngineView::collectComposition(
const fourdst::composition::CompositionAbstract &comp,
const double T9,
const double rho
) const {
const fourdst::composition::Composition result = m_baseEngine.collectComposition(comp, T9, rho);
fourdst::composition::Composition qseComposition = solveQSEAbundances(result, T9, rho);
return qseComposition;
}
SpeciesStatus MultiscalePartitioningEngineView::getSpeciesStatus(const Species &species) const {
const SpeciesStatus status = m_baseEngine.getSpeciesStatus(species);
if (status == SpeciesStatus::ACTIVE && involvesSpeciesInQSE(species)) {
return SpeciesStatus::EQUILIBRIUM;
}
return status;
}
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::CompositionAbstract &comp,
const double T9,
const double rho
) const {
LOG_TRACE_L1(m_logger, "Solving for QSE abundances...");
LOG_TRACE_L2(m_logger, "Composition before QSE solving: {}", [&comp]() -> std::string {
std::stringstream ss;
size_t i = 0;
for (const auto& [sp, y] : comp) {
ss << std::format("{}: {}", sp.name(), y);
if (i < comp.size() - 1) {
ss << ", ";
}
i++;
}
return ss.str();
}());
fourdst::composition::Composition outputComposition(comp);
for (const auto&[is_in_equilibrium, algebraic_species, seed_species, mean_timescale] : m_qse_groups) {
LOG_TRACE_L2(m_logger, "Working on QSE group with algebraic species: {}",
[&]() -> std::string {
std::stringstream ss;
size_t count = 0;
for (const auto& species: algebraic_species) {
ss << species.name();
if (count < algebraic_species.size() - 1) {
ss << ", ";
}
count++;
}
return ss.str();
}());
if (!is_in_equilibrium || (algebraic_species.empty() && seed_species.empty())) {
continue;
}
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 = comp.getMolarAbundance(species);
const double Y = std::max(initial_abundance, abundance_floor);
v_initial(i) = std::log(Y);
species_to_index_map.emplace(species, i);
LOG_TRACE_L2(m_logger, "For species {} initial molar abundance is {}, log scaled to {}. Species placed at index {}.", species.name(), Y, v_initial(i), i);
i++;
}
LOG_TRACE_L2(m_logger, "Setting up Eigen Levenberg-Marquardt solver for QSE group...");
EigenFunctor functor(*this, algebraic_species, comp, 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_L2(m_logger, "Minimizing functor...");
Eigen::LevenbergMarquardtSpace::Status status = lm.minimize(v_initial);
LOG_TRACE_L2(m_logger, "Minimizing functor status: {}", lm_status_map.at(status));
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(),
comp.getMolarAbundance(species),
Y_final_qse(i)
);
// double Xi = Y_final_qse(i) * species.mass(); // Convert from molar abundance to mass fraction
if (!outputComposition.contains (species)) {
outputComposition.registerSpecies(species);
}
outputComposition.setMolarAbundance(species, Y_final_qse(i));
i++;
}
}
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;
}
//////////////////////////////////////
/// Eigen Functor Member Functions ///
/////////////////////////////////////
int MultiscalePartitioningEngineView::EigenFunctor::operator()(const InputType &v_qse, OutputType &f_qse) const {
fourdst::composition::Composition comp_trial(m_initial_comp.getRegisteredSpecies());
for (const auto& [sp, y] : m_initial_comp) {
comp_trial.setMolarAbundance(sp, y);
}
Eigen::VectorXd y_qse = v_qse.array().exp(); // Convert to physical abundances using exponential scaling
for (const auto& species: m_qse_solve_species) {
auto index = static_cast<long>(m_qse_solve_species_index_map.at(species));
comp_trial.setMolarAbundance(species, y_qse[index]);
}
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 (v_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);
ss << "(" << v_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.getRegisteredSpecies());
for (const auto& [sp, y] : m_initial_comp) {
comp_trial.setMolarAbundance(sp, y);
}
Eigen::VectorXd y_qse = v_qse.array().exp(); // Convert to physical abundances using exponential scaling
for (const auto& species: m_qse_solve_species) {
const double molarAbundance = y_qse[static_cast<long>(m_qse_solve_species_index_map.at(species))];
comp_trial.setMolarAbundance(species, molarAbundance);
}
std::vector<Species> qse_species_vector(m_qse_solve_species.begin(), m_qse_solve_species.end());
NetworkJacobian jac = 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) = jac(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
}
/////////////////////////////////
/// QSEGroup Member Functions ///
////////////////////////////////
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();
}
}