# GridFire: PyDynamicEngine Class Reference

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PyDynamicEngine Class Referencefinal

`#include <py_engine.h>`

Inheritance diagram for PyDynamicEngine:
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Collaboration diagram for PyDynamicEngine:
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## Public Member Functions

const std::vector< fourdst::atomic::Species > & | getNetworkSpecies () const override
| PyDynamicEngine Implementation ///.
std::expected< gridfire::engine::StepDerivatives< double >, gridfire::engine::EngineStatus > | calculateRHSAndEnergy (const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Calculate the right-hand side (dY/dt) and energy generation.
gridfire::engine::NetworkJacobian | generateJacobianMatrix (const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Generate the Jacobian matrix for the current state.
gridfire::engine::NetworkJacobian | generateJacobianMatrix (const fourdst::composition::CompositionAbstract &comp, double T9, double rho, const std::vector< fourdst::atomic::Species > &activeSpecies) const override
| Generate the Jacobian matrix for the current state using a subset of active species.
gridfire::engine::NetworkJacobian | generateJacobianMatrix (const fourdst::composition::CompositionAbstract &comp, double T9, double rho, const gridfire::engine::SparsityPattern &sparsityPattern) const override
| Generate the Jacobian matrix for the current state with a specified sparsity pattern.
void | generateStoichiometryMatrix () override
| Generate the stoichiometry matrix for the network.
int | getStoichiometryMatrixEntry (const fourdst::atomic::Species &species, const gridfire::reaction::Reaction &reaction) const override
| Get an entry from the stoichiometry matrix.
double | calculateMolarReactionFlow (const gridfire::reaction::Reaction &reaction, const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Calculate the molar reaction flow for a given reaction.
const gridfire::reaction::ReactionSet & | getNetworkReactions () const override
| Get the set of logical reactions in the network.
void | setNetworkReactions (const gridfire::reaction::ReactionSet &reactions) override
| Set the reactions for the network.
std::expected< std::unordered_map< fourdst::atomic::Species, double >, gridfire::engine::EngineStatus > | getSpeciesTimescales (const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Compute timescales for all species in the network.
std::expected< std::unordered_map< fourdst::atomic::Species, double >, gridfire::engine::EngineStatus > | getSpeciesDestructionTimescales (const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Compute destruction timescales for all species in the network.
fourdst::composition::Composition | update (const gridfire::NetIn &netIn) override
| Update the internal state of the engine.
bool | isStale (const gridfire::NetIn &netIn) override
| Check if the engine's internal state is stale.
void | setScreeningModel (gridfire::screening::ScreeningType model) override
| Set the electron screening model.
gridfire::screening::ScreeningType | getScreeningModel () const override
| Get the current electron screening model.
size_t | getSpeciesIndex (const fourdst::atomic::Species &species) const override
| Get the index of a species in the network.
std::vector< double > | mapNetInToMolarAbundanceVector (const gridfire::NetIn &netIn) const override
| Map a NetIn object to a vector of molar abundances.
gridfire::engine::PrimingReport | primeEngine (const gridfire::NetIn &netIn) override
| Prime the engine with initial conditions.
gridfire::engine::BuildDepthType | getDepth () const override
| Get the depth of the network.
void | rebuild (const fourdst::composition::CompositionAbstract &comp, gridfire::engine::BuildDepthType depth) override
| Rebuild the network with a specified depth.
gridfire::engine::EnergyDerivatives | calculateEpsDerivatives (const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Calculate the derivatives of the energy generation rate with respect to T and rho.
fourdst::composition::Composition | collectComposition (const fourdst::composition::CompositionAbstract &comp, double T9, double rho) const override
| Recursively collect composition from current engine and any sub engines if they exist.
gridfire::engine::SpeciesStatus | getSpeciesStatus (const fourdst::atomic::Species &species) const override
| Get the status of a species in the network.
Public Member Functions inherited from gridfire::engine::Engine
virtual | ~Engine ()=default
| Virtual destructor.

## Private Attributes

std::vector< fourdst::atomic::Species > | m_species_cache

## Member Function Documentation

## calculateEpsDerivatives()

gridfire::engine::EnergyDerivatives PyDynamicEngine::calculateEpsDerivatives | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Calculate the derivatives of the energy generation rate with respect to T and rho.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.

Returns
  EnergyDerivatives containing dEps/dT and dEps/dRho.

This method computes the partial derivatives of the specific nuclear energy generation rate with respect to temperature and density for the current state.

Implements gridfire::engine::DynamicEngine.

## calculateMolarReactionFlow()

double PyDynamicEngine::calculateMolarReactionFlow | ( | const gridfire::reaction::Reaction & | reaction,
|  | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Calculate the molar reaction flow for a given reaction.

Parameters

  reaction | The reaction for which to calculate the flow.
  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.

Returns
  Molar flow rate for the reaction (e.g., mol/g/s).

This method computes the net rate at which the given reaction proceeds under the current state.

Implements gridfire::engine::DynamicEngine.

## calculateRHSAndEnergy()

std::expected< gridfire::engine::StepDerivatives< double >, gridfire::engine::EngineStatus > PyDynamicEngine::calculateRHSAndEnergy | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Calculate the right-hand side (dY/dt) and energy generation.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.

Returns
  expected<StepDerivatives<double>> containing either dY/dt and energy generation rate or a stale engine error indicating that the engine must be updated

This function must be implemented by derived classes to compute the time derivatives of all species and the specific nuclear energy generation rate for the current state.

Implements gridfire::engine::Engine.

## collectComposition()

fourdst::composition::Composition PyDynamicEngine::collectComposition | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Recursively collect composition from current engine and any sub engines if they exist.

If species i is defined in comp and in any sub engine or self composition then the molar abundance of species i in the returned composition will be that defined in comp. If there are species defined in sub engine compositions which are not defined in comp then their molar abundances will be based on the reported values from each sub engine.

Note
  It is up to each engine to decide how to handle filling in the return composition.
  These methods return an unfinalized composition which must then be finalized by the caller

Parameters

  comp | Input composition to "normalize".
  T9 |
  rho |

Returns
  An updated composition which is a superset of comp. This may contain species which were culled, for example, by either QSE partitioning or reaction flow rate culling

Implements gridfire::engine::DynamicEngine.

## generateJacobianMatrix() [1/3]

gridfire::engine::NetworkJacobian PyDynamicEngine::generateJacobianMatrix | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Generate the Jacobian matrix for the current state.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.

This method must compute and store the Jacobian matrix (∂(dY/dt)_i/∂Y_j) for the current state. The matrix can then be accessed via getJacobianMatrixEntry().

Implements gridfire::engine::DynamicEngine.

## generateJacobianMatrix() [2/3]

gridfire::engine::NetworkJacobian PyDynamicEngine::generateJacobianMatrix | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho,
|  | const gridfire::engine::SparsityPattern & | sparsityPattern
| ) |  | const

overridevirtual

Generate the Jacobian matrix for the current state with a specified sparsity pattern.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.
  sparsityPattern | The sparsity pattern to use for the Jacobian matrix.

This method must compute and store the Jacobian matrix (∂(dY/dt)_i/∂Y_j) for the current state using automatic differentiation, taking into account the provided sparsity pattern. The matrix can then be accessed via `getJacobianMatrixEntry()`.

See also
  getJacobianMatrixEntry()

Implements gridfire::engine::DynamicEngine.

## generateJacobianMatrix() [3/3]

gridfire::engine::NetworkJacobian PyDynamicEngine::generateJacobianMatrix | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho,
|  | const std::vector< fourdst::atomic::Species > & | activeSpecies
| ) |  | const

overridevirtual

Generate the Jacobian matrix for the current state using a subset of active species.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.
  activeSpecies | The set of species to include in the Jacobian calculation.

This method must compute and store the Jacobian matrix (∂(dY/dt)_i/∂Y_j) for the current state, considering only the specified subset of active species. The matrix can then be accessed via getJacobianMatrixEntry().

Implements gridfire::engine::DynamicEngine.

## generateStoichiometryMatrix()

void PyDynamicEngine::generateStoichiometryMatrix | ( |  | ) |

overridevirtual

Generate the stoichiometry matrix for the network.

This method must compute and store the stoichiometry matrix, which encodes the net change of each species in each reaction.

Implements gridfire::engine::DynamicEngine.

## getDepth()

gridfire::engine::BuildDepthType PyDynamicEngine::getDepth | ( |  | ) | const

inlineoverridevirtual

Get the depth of the network.

Returns
  The depth of the network, which may indicate the level of detail or complexity in the reaction network.

This method is intended to provide information about the network's structure, such as how many layers of reactions or species are present. It can be useful for diagnostics and understanding the network's complexity.

Reimplemented from gridfire::engine::DynamicEngine.

## getNetworkReactions()

const gridfire::reaction::ReactionSet & PyDynamicEngine::getNetworkReactions | ( |  | ) | const

overridevirtual

Get the set of logical reactions in the network.

Returns
  Reference to the LogicalReactionSet containing all reactions.

Implements gridfire::engine::DynamicEngine.

## getNetworkSpecies()

const std::vector< fourdst::atomic::Species > & PyDynamicEngine::getNetworkSpecies | ( |  | ) | const

overridevirtual

PyDynamicEngine Implementation ///.

Implements gridfire::engine::Engine.

## getScreeningModel()

gridfire::screening::ScreeningType PyDynamicEngine::getScreeningModel | ( |  | ) | const

overridevirtual

Get the current electron screening model.

Returns
  The currently active screening model type.

Usage Example:
  screening::ScreeningType currentModel = myEngine.getScreeningModel();

Implements gridfire::engine::DynamicEngine.

## getSpeciesDestructionTimescales()

std::expected< std::unordered_map< fourdst::atomic::Species, double >, gridfire::engine::EngineStatus > PyDynamicEngine::getSpeciesDestructionTimescales | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Compute destruction timescales for all species in the network.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.

Returns
  Map from Species to their destruction timescales (s).

This method estimates the destruction timescale for each species, which can be useful for understanding reaction flows and equilibrium states.

Implements gridfire::engine::DynamicEngine.

## getSpeciesIndex()

size_t PyDynamicEngine::getSpeciesIndex | ( | const fourdst::atomic::Species & | species | ) | const

overridevirtual

Get the index of a species in the network.

Parameters

  species | The species to look up.

This method allows querying the index of a specific species in the engine's internal representation. It is useful for accessing species data efficiently.

Implements gridfire::engine::DynamicEngine.

## getSpeciesStatus()

gridfire::engine::SpeciesStatus PyDynamicEngine::getSpeciesStatus | ( | const fourdst::atomic::Species & | species | ) | const

overridevirtual

Get the status of a species in the network.

Parameters

  species | The species to check.

Returns
  SpeciesStatus indicating whether the species is active, inactive, or culled.

This method allows querying the current status of a specific species within the engine's network.

Implements gridfire::engine::DynamicEngine.

## getSpeciesTimescales()

std::expected< std::unordered_map< fourdst::atomic::Species, double >, gridfire::engine::EngineStatus > PyDynamicEngine::getSpeciesTimescales | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | double | T9,
|  | double | rho
| ) |  | const

overridevirtual

Compute timescales for all species in the network.

Parameters

  comp | Composition object containing current abundances.
  T9 | Temperature in units of 10^9 K.
  rho | Density in g/cm^3.

Returns
  Map from Species to their characteristic timescales (s).

This method estimates the timescale for abundance change of each species, which can be used for timestep control, diagnostics, and reaction network culling.

Implements gridfire::engine::DynamicEngine.

## getStoichiometryMatrixEntry()

int PyDynamicEngine::getStoichiometryMatrixEntry | ( | const fourdst::atomic::Species & | species,
|  | const gridfire::reaction::Reaction & | reaction
| ) |  | const

overridevirtual

Get an entry from the stoichiometry matrix.

Parameters

  species | species to look up stoichiometry for.
  reaction | reaction to find

Returns
  Stoichiometric coefficient for the species in the reaction.

The stoichiometry matrix must have been generated by generateStoichiometryMatrix().

Implements gridfire::engine::DynamicEngine.

## isStale()

bool PyDynamicEngine::isStale | ( | const gridfire::NetIn & | netIn | ) |

overridevirtual

Check if the engine's internal state is stale.

Parameters

  netIn | A struct containing the current network input, such as temperature, density, and composition.

Returns
  True if the engine's state is stale and needs to be updated; false otherwise.

This method allows derived classes to determine if their internal state is out-of-date with respect to the provided network conditions. If the engine is stale, it may require a call to `update()` before performing calculations.

Usage Example:
  NetIn input = { ... };
  if (myEngine.isStale(input)) {
  // Update the engine before proceeding
  }

Implements gridfire::engine::DynamicEngine.

## mapNetInToMolarAbundanceVector()

std::vector< double > PyDynamicEngine::mapNetInToMolarAbundanceVector | ( | const gridfire::NetIn & | netIn | ) | const

overridevirtual

Map a NetIn object to a vector of molar abundances.

Parameters

  netIn | The input conditions for the network.

Returns
  A vector of molar abundances corresponding to the species in the network.

This method converts the input conditions into a vector of molar abundances, which can be used for further calculations or diagnostics.

Implements gridfire::engine::DynamicEngine.

## primeEngine()

gridfire::engine::PrimingReport PyDynamicEngine::primeEngine | ( | const gridfire::NetIn & | netIn | ) |

overridevirtual

Prime the engine with initial conditions.

Parameters

  netIn | The input conditions for the network.

Returns
  PrimingReport containing information about the priming process.

This method is used to prepare the engine for calculations by setting up initial conditions, reactions, and species. It may involve compiling reaction rates, initializing internal data structures, and performing any necessary pre-computation.

Implements gridfire::engine::DynamicEngine.

## rebuild()

void PyDynamicEngine::rebuild | ( | const fourdst::composition::CompositionAbstract & | comp,
|  | gridfire::engine::BuildDepthType | depth
| ) |  |

inlineoverridevirtual

Rebuild the network with a specified depth.

Parameters

  comp | The composition to rebuild the network with.
  depth | The desired depth of the network.

This method is intended to allow dynamic adjustment of the network's depth, which may involve adding or removing species and reactions based on the specified depth. However, not all engines support this operation.

Reimplemented from gridfire::engine::DynamicEngine.

## setNetworkReactions()

void PyDynamicEngine::setNetworkReactions | ( | const gridfire::reaction::ReactionSet & | reactions | ) |

overridevirtual

Set the reactions for the network.

Parameters

  reactions | The set of reactions to use in the network.

This method replaces the current set of reactions in the network with the provided set. It marks the engine as stale, requiring regeneration of matrices and recalculation of rates.

Implements gridfire::engine::DynamicEngine.

## setScreeningModel()

void PyDynamicEngine::setScreeningModel | ( | gridfire::screening::ScreeningType | model | ) |

overridevirtual

Set the electron screening model.

Parameters

  model | The type of screening model to use for reaction rate calculations.

This method allows changing the screening model at runtime. Screening corrections account for the electrostatic shielding of nuclei by electrons, which affects reaction rates in dense stellar plasmas.

Usage Example:
  myEngine.setScreeningModel(screening::ScreeningType::WEAK);

Postcondition
  The engine will use the specified screening model for subsequent rate calculations.

Implements gridfire::engine::DynamicEngine.

## update()

fourdst::composition::Composition PyDynamicEngine::update | ( | const gridfire::NetIn & | netIn | ) |

overridevirtual

Update the internal state of the engine.

Parameters

  netIn | A struct containing the current network input, such as temperature, density, and composition.

This method is intended to be implemented by derived classes to update their internal state based on the provided network conditions. For example, an adaptive engine might use this to re-evaluate which reactions and species are active. For other engines that do not support manually updating, this method might do nothing.

Usage Example:
  NetIn input = { ... };
  myEngine.update(input);

Postcondition
  The internal state of the engine is updated to reflect the new conditions.

Implements gridfire::engine::DynamicEngine.

## Member Data Documentation

## m_species_cache

std::vector<fourdst::atomic::Species> PyDynamicEngine::m_species_cache

mutableprivate

The documentation for this class was generated from the following files:

- src/python/engine/trampoline/py_engine.h
- src/python/engine/trampoline/py_engine.cpp