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GridFire/src/lib/solver/strategies/CVODE_solver_strategy.cpp

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#include "gridfire/solver/strategies/CVODE_solver_strategy.h"
#include "gridfire/network.h"
#include "gridfire/utils/table_format.h"
#include "gridfire/engine/diagnostics/dynamic_engine_diagnostics.h"
#include "quill/LogMacros.h"
#include "fourdst/composition/composition.h"
// ReSharper disable once CppUnusedIncludeDirective
#include <cstdint>
#include <limits>
#include <string>
#include <unordered_map>
#include <stdexcept>
#include <algorithm>
#include "fourdst/composition/exceptions/exceptions_composition.h"
#include "gridfire/engine/engine_graph.h"
#include "gridfire/solver/strategies/triggers/engine_partitioning_trigger.h"
#include "gridfire/trigger/procedures/trigger_pprint.h"
namespace {
std::unordered_map<int, std::string> cvode_ret_code_map {
{0, "CV_SUCCESS: The solver succeeded."},
{1, "CV_TSTOP_RETURN: The solver reached the specified stopping time."},
{2, "CV_ROOT_RETURN: A root was found."},
{-99, "CV_WARNING: CVODE succeeded but in an unusual manner"},
{-1, "CV_TOO_MUCH_WORK: The solver took too many internal steps."},
{-2, "CV_TOO_MUCH_ACC: The solver could not satisfy the accuracy requested."},
{-3, "CV_ERR_FAILURE: The solver encountered a non-recoverable error."},
{-4, "CV_CONV_FAILURE: The solver failed to converge."},
{-5, "CV_LINIT_FAIL: The linear solver's initialization function failed."},
{-6, "CV_LSETUP_FAIL: The linear solver's setup function failed."},
{-7, "CV_LSOLVE_FAIL: The linear solver's solve function failed."},
{-8, "CV_RHSFUNC_FAIL: The right-hand side function failed in an unrecoverable manner."},
{-9, "CV_FIRST_RHSFUNC_ERR: The right-hand side function failed at the first call."},
{-10, "CV_REPTD_RHSFUNC_ERR: The right-hand side function repeatedly failed recoverable."},
{-11, "CV_UNREC_RHSFUNC_ERR: The right-hand side function failed unrecoverably."},
{-12, "CV_RTFUNC_FAIL: The rootfinding function failed in an unrecoverable manner."},
{-13, "CV_NLS_INIT_FAIL: The nonlinear solver's initialization function failed."},
{-14, "CV_NLS_SETUP_FAIL: The nonlinear solver's setup function failed."},
{-15, "CV_CONSTR_FAIL : The inequality constraint was violated and the solver was unable to recover."},
{-16, "CV_NLS_FAIL: The nonlinear solver's solve function failed."},
{-20, "CV_MEM_FAIL: Memory allocation failed."},
{-21, "CV_MEM_NULL: The CVODE memory structure is NULL."},
{-22, "CV_ILL_INPUT: An illegal input was detected."},
{-23, "CV_NO_MALLOC: The CVODE memory structure has not been allocated."},
{-24, "CV_BAD_K: The value of k is invalid."},
{-25, "CV_BAD_T: The value of t is invalid."},
{-26, "CV_BAD_DKY: The value of dky is invalid."},
{-27, "CV_TOO_CLOSE: The time points are too close together."},
{-28, "CV_VECTOROP_ERR: A vector operation failed."},
{-29, "CV_PROJ_MEM_NULL: The projection memory structure is NULL."},
{-30, "CV_PROJFUNC_FAIL: The projection function failed in an unrecoverable manner."},
{-31, "CV_REPTD_PROJFUNC_ERR: THe projection function has repeated recoverable errors."}
};
void check_cvode_flag(const int flag, const std::string& func_name) {
if (flag < 0) {
if (!cvode_ret_code_map.contains(flag)) {
throw std::runtime_error("CVODE error in " + func_name + ": Unknown error code: " + std::to_string(flag));
}
throw std::runtime_error("CVODE error in " + func_name + ": " + cvode_ret_code_map.at(flag));
}
}
N_Vector init_sun_vector(uint64_t size, SUNContext sun_ctx) {
#ifdef SUNDIALS_HAVE_OPENMP
N_Vector vec = N_VNew_OpenMP(size, 0, sun_ctx);
#elif SUNDIALS_HAVE_PTHREADS
N_Vector vec = N_VNew_Pthreads(size, sun_ctx);
#else
N_Vector vec = N_VNew_Serial(static_cast<long long>(size), sun_ctx);
#endif
check_cvode_flag(vec == nullptr ? -1 : 0, "N_VNew");
return vec;
}
}
namespace gridfire::solver {
CVODESolverStrategy::TimestepContext::TimestepContext(
const double t,
const N_Vector &state,
const double dt,
const double last_step_time,
const double t9,
const double rho,
const size_t num_steps,
const DynamicEngine &engine,
const std::vector<fourdst::atomic::Species> &networkSpecies
) :
t(t),
state(state),
dt(dt),
last_step_time(last_step_time),
T9(t9),
rho(rho),
num_steps(num_steps),
engine(engine),
networkSpecies(networkSpecies)
{}
std::vector<std::tuple<std::string, std::string>> CVODESolverStrategy::TimestepContext::describe() const {
std::vector<std::tuple<std::string, std::string>> description;
description.emplace_back("t", "Current Time");
description.emplace_back("state", "Current State Vector (N_Vector)");
description.emplace_back("dt", "Last Timestep Size");
description.emplace_back("last_step_time", "Time at Last Step");
description.emplace_back("T9", "Temperature in GK");
description.emplace_back("rho", "Density in g/cm^3");
description.emplace_back("num_steps", "Number of Steps Taken So Far");
description.emplace_back("engine", "Reference to the DynamicEngine");
description.emplace_back("networkSpecies", "Reference to the list of network species");
return description;
}
CVODESolverStrategy::CVODESolverStrategy(DynamicEngine &engine): NetworkSolverStrategy<DynamicEngine>(engine) {
// TODO: In order to support MPI this function must be changed
const int flag = SUNContext_Create(SUN_COMM_NULL, &m_sun_ctx);
if (flag < 0) {
throw std::runtime_error("Failed to create SUNDIALS context (SUNDIALS Errno: " + std::to_string(flag) + ")");
}
}
CVODESolverStrategy::~CVODESolverStrategy() {
std::cout << "Cleaning up CVODE resources..." << std::endl;
cleanup_cvode_resources(true);
if (m_sun_ctx) {
SUNContext_Free(&m_sun_ctx);
}
}
NetOut CVODESolverStrategy::evaluate(const NetIn& netIn) {
auto trigger = trigger::solver::CVODE::makeEnginePartitioningTrigger(1e12, 1e10, 1, true, 10);
const double T9 = netIn.temperature / 1e9; // Convert temperature from Kelvin to T9 (T9 = T / 1e9)
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);
fourdst::composition::Composition equilibratedComposition = m_engine.update(netIn);
std::cout << "Equilibrium d molar abundances: " << equilibratedComposition.getMolarAbundance(fourdst::atomic::H_2) << std::endl;
std::cout << "Equilibrium d mass fraction: " << equilibratedComposition.getMassFraction(fourdst::atomic::H_2) << std::endl;
std::cout << "EXITED AT EXPECTED TESTING POINT" << std::endl;
exit(0);
size_t numSpecies = m_engine.getNetworkSpecies().size();
uint64_t N = numSpecies + 1;
m_cvode_mem = CVodeCreate(CV_BDF, m_sun_ctx);
check_cvode_flag(m_cvode_mem == nullptr ? -1 : 0, "CVodeCreate");
initialize_cvode_integration_resources(N, numSpecies, 0.0, equilibratedComposition, absTol, relTol, 0.0);
CVODEUserData user_data;
user_data.solver_instance = this;
user_data.engine = &m_engine;
double current_time = 0;
// ReSharper disable once CppTooWideScope
[[maybe_unused]] double last_callback_time = 0;
m_num_steps = 0;
double accumulated_energy = 0.0;
int total_update_stages_triggered = 0;
while (current_time < netIn.tMax) {
user_data.T9 = T9;
user_data.rho = netIn.density;
user_data.networkSpecies = &m_engine.getNetworkSpecies();
user_data.captured_exception.reset();
check_cvode_flag(CVodeSetUserData(m_cvode_mem, &user_data), "CVodeSetUserData");
int flag{};
if (m_stdout_logging_enabled) {
flag = CVode(m_cvode_mem, netIn.tMax, m_Y, &current_time, CV_ONE_STEP);
} else {
flag = CVode(m_cvode_mem, netIn.tMax, m_Y, &current_time, CV_NORMAL);
}
if (user_data.captured_exception){
std::rethrow_exception(std::make_exception_ptr(*user_data.captured_exception));
}
check_cvode_flag(flag, "CVode");
long int n_steps;
double last_step_size;
CVodeGetNumSteps(m_cvode_mem, &n_steps);
CVodeGetLastStep(m_cvode_mem, &last_step_size);
long int nliters, nlcfails;
CVodeGetNumNonlinSolvIters(m_cvode_mem, &nliters);
CVodeGetNumNonlinSolvConvFails(m_cvode_mem, &nlcfails);
sunrealtype* y_data = N_VGetArrayPointer(m_Y);
const double current_energy = y_data[numSpecies]; // Specific energy rate
std::cout << std::scientific << std::setprecision(3)
<< "Step: " << std::setw(6) << n_steps
<< " | Time: " << current_time << " [s]"
<< " | Last Step Size: " << last_step_size
<< " | Accumulated Energy: " << current_energy << " [erg/g]"
<< " | NonLinIters: " << std::setw(2) << nliters
<< " | ConvFails: " << std::setw(2) << nlcfails
<< std::endl;
auto ctx = TimestepContext(
current_time,
reinterpret_cast<N_Vector>(y_data),
last_step_size,
last_callback_time,
T9,
netIn.density,
n_steps,
m_engine,
m_engine.getNetworkSpecies());
if (trigger->check(ctx)) {
trigger::printWhy(trigger->why(ctx));
trigger->update(ctx);
accumulated_energy += current_energy; // Add the specific energy rate to the accumulated energy
LOG_INFO(
m_logger,
"Engine Update Triggered at time {} ({} update{} triggered). Current total specific energy {} [erg/g]",
current_time,
total_update_stages_triggered,
total_update_stages_triggered == 1 ? "" : "s",
accumulated_energy);
total_update_stages_triggered++;
fourdst::composition::Composition temp_comp;
std::vector<double> mass_fractions;
size_t num_species_at_stop = m_engine.getNetworkSpecies().size();
if (num_species_at_stop > m_Y->ops->nvgetlength(m_Y) - 1) {
LOG_ERROR(
m_logger,
"Number of species at engine update ({}) exceeds the number of species in the CVODE solver ({}). This should never happen.",
num_species_at_stop,
m_Y->ops->nvgetlength(m_Y) - 1 // -1 due to energy in the last index
);
throw std::runtime_error("Number of species at engine update exceeds the number of species in the CVODE solver. This should never happen.");
}
mass_fractions.reserve(num_species_at_stop);
for (size_t i = 0; i < num_species_at_stop; ++i) {
const auto& species = m_engine.getNetworkSpecies()[i];
temp_comp.registerSpecies(species);
mass_fractions.push_back(y_data[i] * species.mass()); // Convert from molar abundance to mass fraction
}
temp_comp.setMassFraction(m_engine.getNetworkSpecies(), mass_fractions);
bool didFinalize = temp_comp.finalize(true);
if (!didFinalize) {
LOG_ERROR(m_logger, "Failed to finalize composition during engine update. Check input mass fractions for validity.");
throw std::runtime_error("Failed to finalize composition during engine update.");
}
NetIn netInTemp = netIn;
netInTemp.temperature = T9 * 1e9; // Convert back to Kelvin
netInTemp.density = netIn.density;
netInTemp.composition = temp_comp;
fourdst::composition::Composition currentComposition = m_engine.update(netInTemp);
LOG_INFO(
m_logger,
"Due to a triggered stale engine the composition was updated from size {} to {} species.",
num_species_at_stop,
m_engine.getNetworkSpecies().size()
);
numSpecies = m_engine.getNetworkSpecies().size();
N = numSpecies + 1;
cleanup_cvode_resources(true);
m_cvode_mem = CVodeCreate(CV_BDF, m_sun_ctx);
check_cvode_flag(m_cvode_mem == nullptr ? -1 : 0, "CVodeCreate");
initialize_cvode_integration_resources(N, numSpecies, current_time, currentComposition, absTol, relTol, accumulated_energy);
check_cvode_flag(CVodeReInit(m_cvode_mem, current_time, m_Y), "CVodeReInit");
}
}
sunrealtype* y_data = N_VGetArrayPointer(m_Y);
accumulated_energy += y_data[numSpecies];
std::vector<double> finalMassFractions(numSpecies);
for (size_t i = 0; i < numSpecies; ++i) {
const double molarMass = m_engine.getNetworkSpecies()[i].mass();
finalMassFractions[i] = y_data[i] * molarMass; // Convert from molar abundance to mass fraction
if (finalMassFractions[i] < MIN_ABUNDANCE_THRESHOLD) {
finalMassFractions[i] = 0.0;
}
}
std::vector<std::string> speciesNames;
speciesNames.reserve(numSpecies);
for (const auto& species : m_engine.getNetworkSpecies()) {
speciesNames.emplace_back(species.name());
}
fourdst::composition::Composition outputComposition(speciesNames);
outputComposition.setMassFraction(speciesNames, finalMassFractions);
bool didFinalize = outputComposition.finalize(true);
if (!didFinalize) {
LOG_ERROR(m_logger, "Failed to finalize output composition after CVODE integration. Check output mass fractions for validity.");
throw std::runtime_error("Failed to finalize output composition after CVODE integration.");
}
NetOut netOut;
netOut.composition = outputComposition;
netOut.energy = accumulated_energy;
check_cvode_flag(CVodeGetNumSteps(m_cvode_mem, reinterpret_cast<long int *>(&netOut.num_steps)), "CVodeGetNumSteps");
auto [dEps_dT, dEps_dRho] = m_engine.calculateEpsDerivatives(
outputComposition,
T9,
netIn.density
);
netOut.dEps_dT = dEps_dT;
netOut.dEps_dRho = dEps_dRho;
return netOut;
}
void CVODESolverStrategy::set_callback(const std::any &callback) {
m_callback = std::any_cast<TimestepCallback>(callback);
}
bool CVODESolverStrategy::get_stdout_logging_enabled() const {
return m_stdout_logging_enabled;
}
void CVODESolverStrategy::set_stdout_logging_enabled(const bool value) {
m_stdout_logging_enabled = value;
}
std::vector<std::tuple<std::string, std::string>> CVODESolverStrategy::describe_callback_context() const {
return {};
}
int CVODESolverStrategy::cvode_rhs_wrapper(
sunrealtype t,
N_Vector y,
N_Vector ydot,
void *user_data
) {
auto* data = static_cast<CVODEUserData*>(user_data);
const auto* instance = data->solver_instance;
try {
instance->calculate_rhs(t, y, ydot, data);
return 0;
} catch (const exceptions::StaleEngineTrigger& e) {
data->captured_exception = std::make_unique<exceptions::StaleEngineTrigger>(e);
return 1; // 1 Indicates a recoverable error, CVODE will retry the step
} catch (...) {
return -1; // Some unrecoverable error
}
}
int CVODESolverStrategy::cvode_jac_wrapper(
sunrealtype t,
N_Vector y,
N_Vector ydot,
SUNMatrix J,
void *user_data,
N_Vector tmp1,
N_Vector tmp2,
N_Vector tmp3
) {
const auto* data = static_cast<CVODEUserData*>(user_data);
const auto* engine = data->engine;
const size_t numSpecies = engine->getNetworkSpecies().size();
sunrealtype* J_data = SUNDenseMatrix_Data(J);
const long int N = SUNDenseMatrix_Columns(J);
for (size_t j = 0; j < numSpecies; ++j) {
for (size_t i = 0; i < numSpecies; ++i) {
const fourdst::atomic::Species& species_j = engine->getNetworkSpecies()[j];
const fourdst::atomic::Species& species_i = engine->getNetworkSpecies()[i];
// J(i,j) = d(f_i)/d(y_j)
// Column-major order format for SUNDenseMatrix: J_data[j*N + i]
J_data[j * N + i] = engine->getJacobianMatrixEntry(species_i, species_j);
}
}
// For now assume that the energy derivatives wrt. abundances are zero
for (size_t i = 0; i < N; ++i) {
J_data[(N - 1) * N + i] = 0.0; // df(energy_dot)/df(y_i)
J_data[i * N + (N - 1)] = 0.0; // df(f_i)/df(energy_dot)
}
return 0;
}
void CVODESolverStrategy::calculate_rhs(
const sunrealtype t,
N_Vector y,
N_Vector ydot,
const CVODEUserData *data
) const {
const size_t numSpecies = m_engine.getNetworkSpecies().size();
sunrealtype* y_data = N_VGetArrayPointer(y);
// PERF: The trade off of ensured index consistency is some performance here. If this becomes a bottleneck we can revisit.
// The specific trade off is that we have decided to enforce that all interfaces accept composition objects rather
// than raw vectors of molar abundances. This then lets any method lookup the species by name rather than relying on
// the index in the vector being consistent. The trade off is that sometimes we need to construct a composition object
// which, at the moment, requires a somewhat expensive set of operations. Perhaps in the future we could enforce
// some consistent memory layout for the composition object to make this cheeper. That optimization would need to be
// done in the libcomposition library though...
std::vector<double> y_vec(y_data, y_data + numSpecies);
std::vector<std::string> symbols;
symbols.reserve(numSpecies);
for (const auto& species : m_engine.getNetworkSpecies()) {
symbols.emplace_back(species.name());
}
std::vector<double> X;
X.reserve(numSpecies);
for (size_t i = 0; i < numSpecies; ++i) {
const double molarMass = m_engine.getNetworkSpecies()[i].mass();
X.push_back(y_vec[i] * molarMass); // Convert from molar abundance to mass fraction
}
fourdst::composition::Composition composition(symbols, X);
std::ranges::replace_if(y_vec, [](const double val) { return val < 0.0; }, 0.0);
const auto result = m_engine.calculateRHSAndEnergy(composition, data->T9, data->rho);
if (!result) {
throw exceptions::StaleEngineTrigger({data->T9, data->rho, y_vec, t, m_num_steps, y_data[numSpecies]});
}
sunrealtype* ydot_data = N_VGetArrayPointer(ydot);
const auto& [dydt, nuclearEnergyGenerationRate] = result.value();
for (size_t i = 0; i < numSpecies; ++i) {
ydot_data[i] = dydt.at(m_engine.getNetworkSpecies()[i]);
}
ydot_data[numSpecies] = nuclearEnergyGenerationRate; // Set the last element to the specific energy rate
}
void CVODESolverStrategy::initialize_cvode_integration_resources(
const uint64_t N,
const size_t numSpecies,
const double current_time,
const fourdst::composition::Composition &composition,
const double absTol,
const double relTol,
const double accumulatedEnergy
) {
cleanup_cvode_resources(false); // Cleanup any existing resources before initializing new ones
m_Y = init_sun_vector(N, m_sun_ctx);
m_YErr = N_VClone(m_Y);
sunrealtype *y_data = N_VGetArrayPointer(m_Y);
for (size_t i = 0; i < numSpecies; i++) {
const auto& species = m_engine.getNetworkSpecies()[i];
if (composition.contains(species)) {
y_data[i] = composition.getMolarAbundance(species);
} else {
y_data[i] = std::numeric_limits<double>::min(); // Species not in the composition, set to a small value
}
}
y_data[numSpecies] = accumulatedEnergy; // Specific energy rate, initialized to zero
check_cvode_flag(CVodeInit(m_cvode_mem, cvode_rhs_wrapper, current_time, m_Y), "CVodeInit");
check_cvode_flag(CVodeSStolerances(m_cvode_mem, relTol, absTol), "CVodeSStolerances");
// Constraints
// We constrain the solution vector using CVODE's built in constraint flags as outlines on page 53 of the CVODE manual
// https://computing.llnl.gov/sites/default/files/cv_guide-5.7.0.pdf
// For completeness and redundancy against future dead links the flags have been copied here
// 0.0: No constraint on the corresponding component of y.
// 1.0: The corresponding component of y is constrained to be >= 0.
// -1.0: The corresponding component of y is constrained to be <= 0.
// 2.0: The corresponding component of y is constrained to be > 0.
// -2.0: The corresponding component of y is constrained to be < 0
// Here we use 1.0 for all species to ensure they remain non-negative.
m_constraints = N_VClone(m_Y);
if (m_constraints == nullptr) {
LOG_ERROR(m_logger, "Failed to create constraints vector for CVODE");
throw std::runtime_error("Failed to create constraints vector for CVODE");
}
N_VConst(1.0, m_constraints); // Set all constraints to >= 0 (note this is where the flag values are set)
check_cvode_flag(CVodeSetConstraints(m_cvode_mem, m_constraints), "CVodeSetConstraints");
check_cvode_flag(CVodeSetMaxStep(m_cvode_mem, 1.0e20), "CVodeSetMaxStep");
m_J = SUNDenseMatrix(static_cast<sunindextype>(N), static_cast<sunindextype>(N), m_sun_ctx);
check_cvode_flag(m_J == nullptr ? -1 : 0, "SUNDenseMatrix");
m_LS = SUNLinSol_Dense(m_Y, m_J, m_sun_ctx);
check_cvode_flag(m_LS == nullptr ? -1 : 0, "SUNLinSol_Dense");
check_cvode_flag(CVodeSetLinearSolver(m_cvode_mem, m_LS, m_J), "CVodeSetLinearSolver");
check_cvode_flag(CVodeSetJacFn(m_cvode_mem, cvode_jac_wrapper), "CVodeSetJacFn");
}
void CVODESolverStrategy::cleanup_cvode_resources(const bool memFree) {
if (m_LS) SUNLinSolFree(m_LS);
if (m_J) SUNMatDestroy(m_J);
if (m_Y) N_VDestroy(m_Y);
if (m_YErr) N_VDestroy(m_YErr);
if (m_constraints) N_VDestroy(m_constraints);
m_LS = nullptr;
m_J = nullptr;
m_Y = nullptr;
m_YErr = nullptr;
m_constraints = nullptr;
if (memFree) {
if (m_cvode_mem) CVodeFree(&m_cvode_mem);
m_cvode_mem = nullptr;
}
}
void CVODESolverStrategy::log_step_diagnostics(const CVODEUserData &user_data) const {
check_cvode_flag(CVodeGetEstLocalErrors(m_cvode_mem, m_YErr), "CVodeGetEstLocalErrors");
sunrealtype *y_data = N_VGetArrayPointer(m_Y);
sunrealtype *y_err_data = N_VGetArrayPointer(m_YErr);
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.emplace_back(user_data.networkSpecies->at(i).name());
}
fourdst::composition::Composition composition(speciesNames, Y_full);
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, composition, user_data.T9, user_data.rho);
diagnostics::inspect_species_balance(*user_data.engine, "N-14", composition, user_data.T9, user_data.rho);
diagnostics::inspect_species_balance(*user_data.engine, "n-1", composition, user_data.T9, user_data.rho);
}
}