497 lines
21 KiB
C++
497 lines
21 KiB
C++
#include "gridfire/solver/strategies/CVODE_solver_strategy.h"
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#include "gridfire/network.h"
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#include "gridfire/utils/table_format.h"
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#include "gridfire/engine/diagnostics/dynamic_engine_diagnostics.h"
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#include "quill/LogMacros.h"
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#include "fourdst/composition/composition.h"
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// ReSharper disable once CppUnusedIncludeDirective
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#include <cstdint>
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#include <limits>
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#include <string>
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#include <unordered_map>
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#include <stdexcept>
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#include <algorithm>
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#include "fourdst/composition/exceptions/exceptions_composition.h"
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namespace {
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std::unordered_map<int, std::string> cvode_ret_code_map {
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{0, "CV_SUCCESS: The solver succeeded."},
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{1, "CV_TSTOP_RETURN: The solver reached the specified stopping time."},
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{2, "CV_ROOT_RETURN: A root was found."},
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{-99, "CV_WARNING: CVODE succeeded but in an unusual manner"},
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{-1, "CV_TOO_MUCH_WORK: The solver took too many internal steps."},
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{-2, "CV_TOO_MUCH_ACC: The solver could not satisfy the accuracy requested."},
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{-3, "CV_ERR_FAILURE: The solver encountered a non-recoverable error."},
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{-4, "CV_CONV_FAILURE: The solver failed to converge."},
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{-5, "CV_LINIT_FAIL: The linear solver's initialization function failed."},
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{-6, "CV_LSETUP_FAIL: The linear solver's setup function failed."},
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{-7, "CV_LSOLVE_FAIL: The linear solver's solve function failed."},
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{-8, "CV_RHSFUNC_FAIL: The right-hand side function failed in an unrecoverable manner."},
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{-9, "CV_FIRST_RHSFUNC_ERR: The right-hand side function failed at the first call."},
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{-10, "CV_REPTD_RHSFUNC_ERR: The right-hand side function repeatedly failed recoverable."},
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{-11, "CV_UNREC_RHSFUNC_ERR: The right-hand side function failed unrecoverably."},
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{-12, "CV_RTFUNC_FAIL: The rootfinding function failed in an unrecoverable manner."},
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{-13, "CV_NLS_INIT_FAIL: The nonlinear solver's initialization function failed."},
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{-14, "CV_NLS_SETUP_FAIL: The nonlinear solver's setup function failed."},
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{-15, "CV_CONSTR_FAIL : The inequality constraint was violated and the solver was unable to recover."},
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{-16, "CV_NLS_FAIL: The nonlinear solver's solve function failed."},
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{-20, "CV_MEM_FAIL: Memory allocation failed."},
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{-21, "CV_MEM_NULL: The CVODE memory structure is NULL."},
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{-22, "CV_ILL_INPUT: An illegal input was detected."},
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{-23, "CV_NO_MALLOC: The CVODE memory structure has not been allocated."},
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{-24, "CV_BAD_K: The value of k is invalid."},
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{-25, "CV_BAD_T: The value of t is invalid."},
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{-26, "CV_BAD_DKY: The value of dky is invalid."},
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{-27, "CV_TOO_CLOSE: The time points are too close together."},
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{-28, "CV_VECTOROP_ERR: A vector operation failed."},
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{-29, "CV_PROJ_MEM_NULL: The projection memory structure is NULL."},
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{-30, "CV_PROJFUNC_FAIL: The projection function failed in an unrecoverable manner."},
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{-31, "CV_REPTD_PROJFUNC_ERR: THe projection function has repeated recoverable errors."}
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};
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void check_cvode_flag(const int flag, const std::string& func_name) {
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if (flag < 0) {
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if (!cvode_ret_code_map.contains(flag)) {
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throw std::runtime_error("CVODE error in " + func_name + ": Unknown error code: " + std::to_string(flag));
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}
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throw std::runtime_error("CVODE error in " + func_name + ": " + cvode_ret_code_map.at(flag));
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}
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}
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N_Vector init_sun_vector(uint64_t size, SUNContext sun_ctx) {
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#ifdef SUNDIALS_HAVE_OPENMP
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N_Vector vec = N_VNew_OpenMP(size, 0, sun_ctx);
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#elif SUNDIALS_HAVE_PTHREADS
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N_Vector vec = N_VNew_Pthreads(size, sun_ctx);
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#else
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N_Vector vec = N_VNew_Serial(size, sun_ctx);
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#endif
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check_cvode_flag(vec == nullptr ? -1 : 0, "N_VNew");
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return vec;
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}
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}
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namespace gridfire::solver {
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CVODESolverStrategy::CVODESolverStrategy(DynamicEngine &engine): NetworkSolverStrategy<DynamicEngine>(engine) {
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// TODO: In order to support MPI this function must be changed
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const int flag = SUNContext_Create(SUN_COMM_NULL, &m_sun_ctx);
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if (flag < 0) {
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throw std::runtime_error("Failed to create SUNDIALS context (SUNDIALS Errno: " + std::to_string(flag) + ")");
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}
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}
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CVODESolverStrategy::~CVODESolverStrategy() {
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std::cout << "Cleaning up CVODE resources..." << std::endl;
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cleanup_cvode_resources(true);
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if (m_sun_ctx) {
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SUNContext_Free(&m_sun_ctx);
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}
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}
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NetOut CVODESolverStrategy::evaluate(const NetIn& netIn) {
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const double T9 = netIn.temperature / 1e9; // Convert temperature from Kelvin to T9 (T9 = T / 1e9)
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const auto absTol = m_config.get<double>("gridfire:solver:CVODESolverStrategy:absTol", 1.0e-8);
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const auto relTol = m_config.get<double>("gridfire:solver:CVODESolverStrategy:relTol", 1.0e-8);
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fourdst::composition::Composition equilibratedComposition = m_engine.update(netIn);
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size_t numSpecies = m_engine.getNetworkSpecies().size();
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uint64_t N = numSpecies + 1;
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m_cvode_mem = CVodeCreate(CV_BDF, m_sun_ctx);
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check_cvode_flag(m_cvode_mem == nullptr ? -1 : 0, "CVodeCreate");
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initialize_cvode_integration_resources(N, numSpecies, 0.0, equilibratedComposition, absTol, relTol, 0.0);
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CVODEUserData user_data;
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user_data.solver_instance = this;
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user_data.engine = &m_engine;
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double current_time = 0;
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[[maybe_unused]] double last_callback_time = 0;
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m_num_steps = 0;
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double accumulated_energy = 0.0;
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int total_update_stages_triggered = 0;
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while (current_time < netIn.tMax) {
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try {
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user_data.T9 = T9;
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user_data.rho = netIn.density;
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user_data.networkSpecies = &m_engine.getNetworkSpecies();
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user_data.captured_exception.reset();
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check_cvode_flag(CVodeSetUserData(m_cvode_mem, &user_data), "CVodeSetUserData");
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int flag = -1;
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if (m_stdout_logging_enabled) {
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flag = CVode(m_cvode_mem, netIn.tMax, m_Y, ¤t_time, CV_ONE_STEP);
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} else {
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flag = CVode(m_cvode_mem, netIn.tMax, m_Y, ¤t_time, CV_NORMAL);
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}
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if (user_data.captured_exception){
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std::rethrow_exception(std::make_exception_ptr(*user_data.captured_exception));
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}
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check_cvode_flag(flag, "CVode");
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long int n_steps;
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double last_step_size;
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CVodeGetNumSteps(m_cvode_mem, &n_steps);
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CVodeGetLastStep(m_cvode_mem, &last_step_size);
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long int nliters, nlcfails;
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CVodeGetNumNonlinSolvIters(m_cvode_mem, &nliters);
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CVodeGetNumNonlinSolvConvFails(m_cvode_mem, &nlcfails);
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sunrealtype* y_data = N_VGetArrayPointer(m_Y);
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const double current_energy = y_data[numSpecies]; // Specific energy rate
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std::cout << std::scientific << std::setprecision(3)
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<< "Step: " << std::setw(6) << n_steps
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<< " | Time: " << current_time << " [s]"
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<< " | Last Step Size: " << last_step_size
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<< " | Accumulated Energy: " << current_energy << " [erg/g]"
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<< " | NonlinIters: " << std::setw(2) << nliters
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<< " | ConvFails: " << std::setw(2) << nlcfails
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<< std::endl;
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// if (n_steps % 50 == 0) {
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// std::cout << "Logging step diagnostics at step " << n_steps << "..." << std::endl;
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// log_step_diagnostics(user_data);
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// }
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// if (n_steps == 300) {
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// log_step_diagnostics(user_data);
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// exit(0);
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// }
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// log_step_diagnostics(user_data);
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} catch (const exceptions::StaleEngineTrigger& e) {
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exceptions::StaleEngineTrigger::state staleState = e.getState();
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accumulated_energy += e.energy(); // Add the specific energy rate to the accumulated energy
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LOG_INFO(
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m_logger,
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"Engine Update Triggered due to StaleEngineTrigger exception at time {} ({} update{} triggered). Current total specific energy {} [erg/g]",
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current_time,
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total_update_stages_triggered,
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total_update_stages_triggered == 1 ? "" : "s",
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accumulated_energy);
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total_update_stages_triggered++;
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fourdst::composition::Composition temp_comp;
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std::vector<double> mass_fractions;
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size_t num_species_at_stop = e.numSpecies();
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mass_fractions.reserve(num_species_at_stop);
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for (size_t i = 0; i < num_species_at_stop; ++i) {
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const auto& species = m_engine.getNetworkSpecies()[i];
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temp_comp.registerSpecies(species);
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mass_fractions.push_back(e.getMolarAbundance(i) * species.mass()); // Convert from molar abundance to mass fraction
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}
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temp_comp.setMassFraction(m_engine.getNetworkSpecies(), mass_fractions);
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temp_comp.finalize(true);
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NetIn netInTemp = netIn;
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netInTemp.temperature = e.temperature();
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netInTemp.density = e.density();
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netInTemp.composition = temp_comp;
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fourdst::composition::Composition currentComposition = m_engine.update(netInTemp);
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LOG_INFO(
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m_logger,
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"Due to a triggered stale engine the composition was updated from size {} to {} species.",
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num_species_at_stop,
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m_engine.getNetworkSpecies().size()
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);
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numSpecies = m_engine.getNetworkSpecies().size();
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N = numSpecies + 1;
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initialize_cvode_integration_resources(N, numSpecies, current_time, currentComposition, absTol, relTol, accumulated_energy);
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check_cvode_flag(CVodeReInit(m_cvode_mem, current_time, m_Y), "CVodeReInit");
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} catch (fourdst::composition::exceptions::InvalidCompositionError& e) {
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log_step_diagnostics(user_data);
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std::rethrow_exception(std::make_exception_ptr(e));
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}
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}
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sunrealtype* y_data = N_VGetArrayPointer(m_Y);
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accumulated_energy += y_data[numSpecies];
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std::vector<double> finalMassFractions(numSpecies);
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for (size_t i = 0; i < numSpecies; ++i) {
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const double molarMass = m_engine.getNetworkSpecies()[i].mass();
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finalMassFractions[i] = y_data[i] * molarMass; // Convert from molar abundance to mass fraction
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if (finalMassFractions[i] < MIN_ABUNDANCE_THRESHOLD) {
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finalMassFractions[i] = 0.0;
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}
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}
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std::vector<std::string> speciesNames;
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speciesNames.reserve(numSpecies);
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for (const auto& species : m_engine.getNetworkSpecies()) {
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speciesNames.emplace_back(species.name());
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}
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fourdst::composition::Composition outputComposition(speciesNames);
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outputComposition.setMassFraction(speciesNames, finalMassFractions);
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outputComposition.finalize(true);
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NetOut netOut;
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netOut.composition = outputComposition;
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netOut.energy = accumulated_energy;
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check_cvode_flag(CVodeGetNumSteps(m_cvode_mem, reinterpret_cast<long int *>(&netOut.num_steps)), "CVodeGetNumSteps");
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outputComposition.setCompositionMode(false); // set to number fraction mode
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std::vector<double> Y = outputComposition.getNumberFractionVector(); // TODO need to ensure that the canonical vector representation is used throughout the code to make sure tracking does not get messed up
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auto [dEps_dT, dEps_dRho] = m_engine.calculateEpsDerivatives(
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std::vector<double>(Y.begin(), Y.begin() + numSpecies), // TODO: This narrowing should probably be solved. Its possible unforeseen bugs will arise from this
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T9,
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netIn.density
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);
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netOut.dEps_dT = dEps_dT;
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netOut.dEps_dRho = dEps_dRho;
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return netOut;
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}
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void CVODESolverStrategy::set_callback(const std::any &callback) {
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m_callback = std::any_cast<TimestepCallback>(callback);
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}
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bool CVODESolverStrategy::get_stdout_logging_enabled() const {
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return m_stdout_logging_enabled;
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}
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void CVODESolverStrategy::set_stdout_logging_enabled(const bool value) {
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m_stdout_logging_enabled = value;
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}
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std::vector<std::tuple<std::string, std::string>> CVODESolverStrategy::describe_callback_context() const {
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return {};
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}
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int CVODESolverStrategy::cvode_rhs_wrapper(
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sunrealtype t,
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N_Vector y,
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N_Vector ydot,
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void *user_data
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) {
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auto* data = static_cast<CVODEUserData*>(user_data);
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const auto* instance = data->solver_instance;
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try {
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instance->calculate_rhs(t, y, ydot, data);
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return 0;
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} catch (const exceptions::StaleEngineTrigger& e) {
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data->captured_exception = std::make_unique<exceptions::StaleEngineTrigger>(e);
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return 1; // 1 Indicates a recoverable error, CVODE will retry the step
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} catch (...) {
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return -1; // Some unrecoverable error
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}
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}
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int CVODESolverStrategy::cvode_jac_wrapper(
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sunrealtype t,
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N_Vector y,
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N_Vector ydot,
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SUNMatrix J,
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void *user_data,
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N_Vector tmp1,
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N_Vector tmp2,
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N_Vector tmp3
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) {
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const auto* data = static_cast<CVODEUserData*>(user_data);
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const auto* engine = data->engine;
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const size_t numSpecies = engine->getNetworkSpecies().size();
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sunrealtype* J_data = SUNDenseMatrix_Data(J);
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const long int N = SUNDenseMatrix_Columns(J);
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for (size_t j = 0; j < numSpecies; ++j) {
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for (size_t i = 0; i < numSpecies; ++i) {
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// J(i,j) = d(f_i)/d(y_j)
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// Column-major order format for SUNDenseMatrix: J_data[j*N + i]
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J_data[j * N + i] = engine->getJacobianMatrixEntry(i, j);
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}
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}
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// For now assume that the energy derivatives wrt. abundances are zero
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for (size_t i = 0; i < N; ++i) {
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J_data[(N - 1) * N + i] = 0.0; // df(energy_dot)/df(y_i)
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J_data[i * N + (N - 1)] = 0.0; // df(f_i)/df(energy_dot)
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}
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return 0;
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}
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void CVODESolverStrategy::calculate_rhs(
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const sunrealtype t,
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const N_Vector y,
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const N_Vector ydot,
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const CVODEUserData *data
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) const {
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const size_t numSpecies = m_engine.getNetworkSpecies().size();
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sunrealtype* y_data = N_VGetArrayPointer(y);
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std::vector<double> y_vec(y_data, y_data + numSpecies);
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std::ranges::replace_if(y_vec, [](const double val) { return val < 0.0; }, 0.0);
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const auto result = m_engine.calculateRHSAndEnergy(y_vec, data->T9, data->rho);
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if (!result) {
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throw exceptions::StaleEngineTrigger({data->T9, data->rho, y_vec, t, m_num_steps, y_data[numSpecies]});
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}
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sunrealtype* ydot_data = N_VGetArrayPointer(ydot);
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const auto& [dydt, nuclearEnergyGenerationRate] = result.value();
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for (size_t i = 0; i < numSpecies; ++i) {
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ydot_data[i] = dydt[i];
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}
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ydot_data[numSpecies] = nuclearEnergyGenerationRate; // Set the last element to the specific energy rate
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}
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void CVODESolverStrategy::initialize_cvode_integration_resources(
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const uint64_t N,
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const size_t numSpecies,
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const double current_time,
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const fourdst::composition::Composition &composition,
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const double absTol,
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const double relTol,
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const double accumulatedEnergy
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) {
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cleanup_cvode_resources(false); // Cleanup any existing resources before initializing new ones
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m_Y = init_sun_vector(N, m_sun_ctx);
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m_YErr = N_VClone(m_Y);
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sunrealtype *y_data = N_VGetArrayPointer(m_Y);
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for (size_t i = 0; i < numSpecies; i++) {
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const auto& species = m_engine.getNetworkSpecies()[i];
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if (composition.contains(species)) {
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y_data[i] = composition.getMolarAbundance(species);
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} else {
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y_data[i] = std::numeric_limits<double>::min(); // Species not in the composition, set to a small value
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}
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}
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y_data[numSpecies] = accumulatedEnergy; // Specific energy rate, initialized to zero
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check_cvode_flag(CVodeInit(m_cvode_mem, cvode_rhs_wrapper, current_time, m_Y), "CVodeInit");
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check_cvode_flag(CVodeSStolerances(m_cvode_mem, relTol, absTol), "CVodeSStolerances");
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check_cvode_flag(CVodeSetMaxStep(m_cvode_mem, 1.0e20), "CVodeSetMaxStep");
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m_J = SUNDenseMatrix(static_cast<sunindextype>(N), static_cast<sunindextype>(N), m_sun_ctx);
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check_cvode_flag(m_J == nullptr ? -1 : 0, "SUNDenseMatrix");
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m_LS = SUNLinSol_Dense(m_Y, m_J, m_sun_ctx);
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check_cvode_flag(m_LS == nullptr ? -1 : 0, "SUNLinSol_Dense");
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check_cvode_flag(CVodeSetLinearSolver(m_cvode_mem, m_LS, m_J), "CVodeSetLinearSolver");
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check_cvode_flag(CVodeSetJacFn(m_cvode_mem, cvode_jac_wrapper), "CVodeSetJacFn");
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}
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void CVODESolverStrategy::cleanup_cvode_resources(const bool memFree) {
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if (m_LS) SUNLinSolFree(m_LS);
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if (m_J) SUNMatDestroy(m_J);
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if (m_Y) N_VDestroy(m_Y);
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if (m_YErr) N_VDestroy(m_YErr);
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m_LS = nullptr;
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m_J = nullptr;
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m_Y = nullptr;
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m_YErr = nullptr;
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if (memFree) {
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if (m_cvode_mem) CVodeFree(&m_cvode_mem);
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m_cvode_mem = nullptr;
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}
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}
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void CVODESolverStrategy::log_step_diagnostics(const CVODEUserData &user_data) const {
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check_cvode_flag(CVodeGetEstLocalErrors(m_cvode_mem, m_YErr), "CVodeGetEstLocalErrors");
|
|
|
|
sunrealtype *y_data = N_VGetArrayPointer(m_Y);
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|
sunrealtype *y_err_data = N_VGetArrayPointer(m_YErr);
|
|
|
|
|
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std::vector<double> err_ratios;
|
|
std::vector<std::string> speciesNames;
|
|
|
|
const auto absTol = m_config.get<double>("gridfire:solver:CVODESolverStrategy:absTol", 1.0e-8);
|
|
const auto relTol = m_config.get<double>("gridfire:solver:CVODESolverStrategy:relTol", 1.0e-8);
|
|
|
|
const size_t num_components = N_VGetLength(m_Y);
|
|
err_ratios.resize(num_components - 1);
|
|
|
|
std::vector<double> Y_full(y_data, y_data + num_components - 1);
|
|
|
|
std::ranges::replace_if(
|
|
Y_full,
|
|
[](const double val) {
|
|
return val < 0.0 && val > -1.0e-16;
|
|
},
|
|
0.0
|
|
);
|
|
|
|
for (size_t i = 0; i < num_components - 1; i++) {
|
|
const double weight = relTol * std::abs(y_data[i]) + absTol;
|
|
if (weight == 0.0) continue; // Skip components with zero weight
|
|
|
|
const double err_ratio = std::abs(y_err_data[i]) / weight;
|
|
|
|
err_ratios[i] = err_ratio;
|
|
speciesNames.push_back(std::string(user_data.networkSpecies->at(i).name()));
|
|
}
|
|
|
|
if (err_ratios.empty()) {
|
|
return;
|
|
}
|
|
|
|
std::vector<size_t> indices(speciesNames.size());
|
|
for (size_t i = 0; i < indices.size(); ++i) {
|
|
indices[i] = i;
|
|
}
|
|
|
|
std::ranges::sort(
|
|
indices,
|
|
[&err_ratios](const size_t i1, const size_t i2) {
|
|
return err_ratios[i1] > err_ratios[i2];
|
|
}
|
|
);
|
|
|
|
std::vector<std::string> sorted_speciesNames;
|
|
std::vector<double> sorted_err_ratios;
|
|
|
|
sorted_speciesNames.reserve(indices.size());
|
|
sorted_err_ratios.reserve(indices.size());
|
|
|
|
for (const auto idx: indices) {
|
|
sorted_speciesNames.push_back(speciesNames[idx]);
|
|
sorted_err_ratios.push_back(err_ratios[idx]);
|
|
}
|
|
|
|
|
|
|
|
std::vector<std::unique_ptr<utils::ColumnBase>> columns;
|
|
columns.push_back(std::make_unique<utils::Column<std::string>>("Species", sorted_speciesNames));
|
|
columns.push_back(std::make_unique<utils::Column<double>>("Error Ratio", sorted_err_ratios));
|
|
|
|
std::cout << utils::format_table("Species Error Ratios", columns) << std::endl;
|
|
diagnostics::inspect_jacobian_stiffness(*user_data.engine, Y_full, user_data.T9, user_data.rho);
|
|
diagnostics::inspect_species_balance(*user_data.engine, "N-14", Y_full, user_data.T9, user_data.rho);
|
|
diagnostics::inspect_species_balance(*user_data.engine, "n-1", Y_full, user_data.T9, user_data.rho);
|
|
|
|
}
|
|
}
|