diff --git a/Doxyfile b/Doxyfile index 181e6582..177be146 100644 --- a/Doxyfile +++ b/Doxyfile @@ -991,7 +991,7 @@ WARN_LOGFILE = # spaces. See also FILE_PATTERNS and EXTENSION_MAPPING # Note: If this tag is empty the current directory is searched. -INPUT = src docs/static/mainpage.md +INPUT = src docs/static/mainpage.md docs/static/usage.md # This tag can be used to specify the character encoding of the source files # that Doxygen parses. Internally Doxygen uses the UTF-8 encoding. Doxygen uses diff --git a/README.md b/README.md index 59f0734c..8f377a41 100644 --- a/README.md +++ b/README.md @@ -250,11 +250,29 @@ gridfire::AdaptiveEngineView adaptiveView(baseEngine); ### Python Example ```python import gridfire + + +from fourdst.composition import Composition + +symbols = ["H-1", ...] +X = [0.708, ...] + +comp = Composition() +comp.registerSymbols(symbols) +comp.setMassFraction(X) +comp.finalize(true) # Initialize GraphEngine with predefined composition -engine = gridfire.GraphEngine(composition="example_composition") +engine = gridfire.GraphEngine(comp) +netIn = gridfire.types.NetIn +netIn.composition = comp +netIn.tMax = 1e-3 +netIn.temperature = 1.5e7 +netIn.density = 1.6e2 +netIn.dt0 = 1e-12 + # Perform one integration step -engine.step(dt=1e-3) -print(engine.abundances) +netOut = engine.evaluate(netIn) +print(netOut) ``` ## Common Workflow Example @@ -311,4 +329,4 @@ GridFire integrates with and builds upon several key 4D-STAR libraries: - [libcomposition](https://github.com/4D-STAR/libcomposition) ([docs](https://4d-star.github.io/libcomposition/)): Composition management toolkit. - [libconfig](https://github.com/4D-STAR/libconfig): Configuration file parsing utilities. - [liblogging](https://github.com/4D-STAR/liblogging): Flexible logging framework. -- [libconstants](https://github.com/4D-STAR/libconstants): Physical constants \ No newline at end of file +- [libconstants](https://github.com/4D-STAR/libconstants): Physical constants diff --git a/docs/html/classgridfire_1_1_graph_engine-members.html b/docs/html/classgridfire_1_1_graph_engine-members.html index 50843fe3..29eca4b0 100644 --- a/docs/html/classgridfire_1_1_graph_engine-members.html +++ b/docs/html/classgridfire_1_1_graph_engine-members.html @@ -176,9 +176,8 @@ $(function(){initNavTree('classgridfire_1_1_graph_engine.html',''); initResizabl setUseReverseReactions(bool useReverse)gridfire::GraphEngine syncInternalMaps()gridfire::GraphEngineprivate update(const NetIn &netIn) overridegridfire::GraphEnginevirtual - validateComposition(const fourdst::composition::Composition &composition, double culling, double T9)gridfire::GraphEngineprivate - validateConservation() constgridfire::GraphEngineprivate - ~Engine()=defaultgridfire::Enginevirtual + validateConservation() constgridfire::GraphEngineprivate + ~Engine()=defaultgridfire::Enginevirtual diff --git a/docs/html/classgridfire_1_1_graph_engine.html b/docs/html/classgridfire_1_1_graph_engine.html index c0ceaa27..b2cfe5c0 100644 --- a/docs/html/classgridfire_1_1_graph_engine.html +++ b/docs/html/classgridfire_1_1_graph_engine.html @@ -261,9 +261,6 @@ Private Member Functions bool validateConservation () const  Validates mass and charge conservation across all reactions.
  -void validateComposition (const fourdst::composition::Composition &composition, double culling, double T9) - Validates the composition against the current reaction set.
StepDerivatives< double > calculateAllDerivativesUsingPrecomputation (const std::vector< double > &Y_in, const std::vector< double > &bare_rates, const std::vector< double > &bare_reverse_rates, double T9, double rho) const   template<IsArithmeticOrAD T> @@ -358,7 +355,7 @@ Private Attributes
See also
engine_abstract.h
-

Definition at line 101 of file engine_graph.h.

+

Definition at line 100 of file engine_graph.h.

Constructor & Destructor Documentation

◆ GraphEngine() [1/3]

@@ -518,7 +515,7 @@ Private Attributes
Returns
StepDerivatives<ADDouble> containing dY/dt and energy generation rate.

This method calculates the time derivatives of all species and the specific nuclear energy generation rate for the current state using automatic differentiation.

-

Definition at line 616 of file engine_graph.cpp.

+

Definition at line 594 of file engine_graph.cpp.

@@ -566,7 +563,7 @@ Private Attributes
Returns
StepDerivatives<double> containing dY/dt and energy generation rate.

This method calculates the time derivatives of all species and the specific nuclear energy generation rate for the current state using double precision arithmetic.

-

Definition at line 608 of file engine_graph.cpp.

+

Definition at line 586 of file engine_graph.cpp.

@@ -622,7 +619,7 @@ template<IsArithmeticOrAD T>
Returns
StepDerivatives<T> containing dY/dt and energy generation rate.

This method calculates the time derivatives of all species and the specific nuclear energy generation rate for the current state.

-

Definition at line 745 of file engine_graph.h.

+

Definition at line 715 of file engine_graph.h.

@@ -668,7 +665,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 470 of file engine_graph.cpp.

+

Definition at line 448 of file engine_graph.cpp.

@@ -724,7 +721,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 645 of file engine_graph.cpp.

+

Definition at line 623 of file engine_graph.cpp.

@@ -786,7 +783,7 @@ template<IsArithmeticOrAD T>
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.

-

Definition at line 826 of file engine_graph.h.

+

Definition at line 796 of file engine_graph.h.

@@ -839,7 +836,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 667 of file engine_graph.h.

+

Definition at line 648 of file engine_graph.h.

@@ -870,7 +867,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 262 of file engine_graph.cpp.

+

Definition at line 242 of file engine_graph.cpp.

@@ -911,7 +908,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 291 of file engine_graph.cpp.

+

Definition at line 269 of file engine_graph.cpp.

@@ -947,7 +944,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 368 of file engine_graph.cpp.

+

Definition at line 346 of file engine_graph.cpp.

@@ -1025,7 +1022,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 969 of file engine_graph.cpp.

+

Definition at line 947 of file engine_graph.cpp.

@@ -1090,7 +1087,7 @@ template<IsArithmeticOrAD T>

Example usage:

engine.exportToCSV("network.csv");
-

Definition at line 810 of file engine_graph.cpp.

+

Definition at line 788 of file engine_graph.cpp.

@@ -1125,7 +1122,7 @@ template<IsArithmeticOrAD T>

Example usage:

engine.exportToDot("network.dot");
-

Definition at line 762 of file engine_graph.cpp.

+

Definition at line 740 of file engine_graph.cpp.

@@ -1175,7 +1172,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 654 of file engine_graph.cpp.

+

Definition at line 632 of file engine_graph.cpp.

@@ -1218,7 +1215,7 @@ template<IsArithmeticOrAD T>

Reimplemented from gridfire::DynamicEngine.

-

Definition at line 687 of file engine_graph.cpp.

+

Definition at line 665 of file engine_graph.cpp.

@@ -1250,7 +1247,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 567 of file engine_graph.cpp.

+

Definition at line 545 of file engine_graph.cpp.

@@ -1279,7 +1276,7 @@ template<IsArithmeticOrAD T>

Reimplemented from gridfire::DynamicEngine.

-

Definition at line 456 of file engine_graph.cpp.

+

Definition at line 434 of file engine_graph.cpp.

@@ -1324,7 +1321,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 744 of file engine_graph.cpp.

+

Definition at line 722 of file engine_graph.cpp.

@@ -1360,7 +1357,7 @@ template<IsArithmeticOrAD T>
Returns
Map of species to their stoichiometric coefficients.
-

Definition at line 749 of file engine_graph.cpp.

+

Definition at line 727 of file engine_graph.cpp.

@@ -1451,7 +1448,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 641 of file engine_graph.cpp.

+

Definition at line 619 of file engine_graph.cpp.

@@ -1486,7 +1483,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 629 of file engine_graph.cpp.

+

Definition at line 607 of file engine_graph.cpp.

@@ -1524,7 +1521,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 883 of file engine_graph.cpp.

+

Definition at line 861 of file engine_graph.cpp.

@@ -1553,7 +1550,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 417 of file engine_graph.cpp.

+

Definition at line 395 of file engine_graph.cpp.

@@ -1603,7 +1600,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 864 of file engine_graph.cpp.

+

Definition at line 842 of file engine_graph.cpp.

@@ -1648,7 +1645,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 755 of file engine_graph.cpp.

+

Definition at line 733 of file engine_graph.cpp.

@@ -1711,7 +1708,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 637 of file engine_graph.cpp.

+

Definition at line 615 of file engine_graph.cpp.

@@ -1740,7 +1737,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 920 of file engine_graph.cpp.

+

Definition at line 898 of file engine_graph.cpp.

@@ -1767,7 +1764,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 409 of file engine_graph.cpp.

+

Definition at line 387 of file engine_graph.cpp.

@@ -1796,7 +1793,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 421 of file engine_graph.cpp.

+

Definition at line 399 of file engine_graph.cpp.

@@ -1883,7 +1880,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 982 of file engine_graph.cpp.

+

Definition at line 960 of file engine_graph.cpp.

@@ -1912,7 +1909,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 429 of file engine_graph.cpp.

+

Definition at line 407 of file engine_graph.cpp.

@@ -1945,7 +1942,7 @@ template<IsArithmeticOrAD T>

Reimplemented from gridfire::DynamicEngine.

-

Definition at line 460 of file engine_graph.cpp.

+

Definition at line 438 of file engine_graph.cpp.

@@ -1981,7 +1978,7 @@ template<IsArithmeticOrAD T> -

Definition at line 924 of file engine_graph.cpp.

+

Definition at line 902 of file engine_graph.cpp.

@@ -2059,7 +2056,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 633 of file engine_graph.cpp.

+

Definition at line 611 of file engine_graph.cpp.

@@ -2101,7 +2098,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 624 of file engine_graph.cpp.

+

Definition at line 602 of file engine_graph.cpp.

@@ -2120,7 +2117,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 413 of file engine_graph.cpp.

+

Definition at line 391 of file engine_graph.cpp.

@@ -2193,54 +2190,7 @@ template<IsArithmeticOrAD T>

Implements gridfire::DynamicEngine.

-

Definition at line 908 of file engine_graph.cpp.

- - - - -

◆ validateComposition()

- -
-
- - - - - -
- - - - - - - - - - - - - - - - -
void gridfire::GraphEngine::validateComposition (const fourdst::composition::Composition & composition,
double culling,
double T9 )
-
-private
-
- -

Validates the composition against the current reaction set.

-
Parameters
- - - - -
compositionThe composition to validate.
cullingThe culling threshold to use.
T9The temperature to use.
-
-
-

This method validates the composition against the current reaction set. If the composition is not compatible with the reaction set, the reaction set is rebuilt from the composition.

- -

Definition at line 242 of file engine_graph.cpp.

+

Definition at line 886 of file engine_graph.cpp.

@@ -2296,7 +2246,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 467 of file engine_graph.h.

+

Definition at line 466 of file engine_graph.h.

@@ -2320,7 +2270,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 448 of file engine_graph.h.

+

Definition at line 447 of file engine_graph.h.

@@ -2344,7 +2294,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 451 of file engine_graph.h.

+

Definition at line 450 of file engine_graph.h.

@@ -2368,7 +2318,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 476 of file engine_graph.h.

+

Definition at line 475 of file engine_graph.h.

@@ -2394,7 +2344,7 @@ template<IsArithmeticOrAD T>

Full sparsity pattern for the Jacobian matrix.

-

Definition at line 465 of file engine_graph.h.

+

Definition at line 464 of file engine_graph.h.

@@ -2420,7 +2370,7 @@ template<IsArithmeticOrAD T>

Work object for sparse Jacobian calculations.

-

Definition at line 464 of file engine_graph.h.

+

Definition at line 463 of file engine_graph.h.

@@ -2446,7 +2396,7 @@ template<IsArithmeticOrAD T>

Jacobian matrix (species x species).

-

Definition at line 462 of file engine_graph.h.

+

Definition at line 461 of file engine_graph.h.

@@ -2470,7 +2420,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 449 of file engine_graph.h.

+

Definition at line 448 of file engine_graph.h.

@@ -2496,7 +2446,7 @@ template<IsArithmeticOrAD T>

Vector of unique species in the network.

-

Definition at line 456 of file engine_graph.h.

+

Definition at line 455 of file engine_graph.h.

@@ -2522,7 +2472,7 @@ template<IsArithmeticOrAD T>

Map from species name to Species object.

-

Definition at line 457 of file engine_graph.h.

+

Definition at line 456 of file engine_graph.h.

@@ -2548,7 +2498,7 @@ template<IsArithmeticOrAD T>

Partition function for the network.

-

Definition at line 479 of file engine_graph.h.

+

Definition at line 478 of file engine_graph.h.

@@ -2574,7 +2524,7 @@ template<IsArithmeticOrAD T>

Precomputed reactions for efficiency.

-

Definition at line 478 of file engine_graph.h.

+

Definition at line 477 of file engine_graph.h.

@@ -2600,7 +2550,7 @@ template<IsArithmeticOrAD T>

Map from reaction ID to REACLIBReaction. //PERF: This makes copies of REACLIBReaction and could be a performance bottleneck.

-

Definition at line 454 of file engine_graph.h.

+

Definition at line 453 of file engine_graph.h.

@@ -2626,7 +2576,7 @@ template<IsArithmeticOrAD T>

Set of REACLIB reactions in the network.

-

Definition at line 453 of file engine_graph.h.

+

Definition at line 452 of file engine_graph.h.

@@ -2652,7 +2602,7 @@ template<IsArithmeticOrAD T>

CppAD function for the right-hand side of the ODE.

-

Definition at line 463 of file engine_graph.h.

+

Definition at line 462 of file engine_graph.h.

@@ -2676,7 +2626,7 @@ template<IsArithmeticOrAD T>
-

Definition at line 470 of file engine_graph.h.

+

Definition at line 469 of file engine_graph.h.

@@ -2702,7 +2652,7 @@ template<IsArithmeticOrAD T>

Screening type for the reaction network. Default to no screening.

-

Definition at line 469 of file engine_graph.h.

+

Definition at line 468 of file engine_graph.h.

@@ -2728,7 +2678,7 @@ template<IsArithmeticOrAD T>

Map from species to their index in the stoichiometry matrix.

-

Definition at line 458 of file engine_graph.h.

+

Definition at line 457 of file engine_graph.h.

@@ -2754,7 +2704,7 @@ template<IsArithmeticOrAD T>

Stoichiometry matrix (species x reactions).

-

Definition at line 460 of file engine_graph.h.

+

Definition at line 459 of file engine_graph.h.

@@ -2780,7 +2730,7 @@ template<IsArithmeticOrAD T>

Flag to enable or disable using precomputed reactions for efficiency. Mathematically, this should not change the results. Generally end users should not need to change this.

-

Definition at line 472 of file engine_graph.h.

+

Definition at line 471 of file engine_graph.h.

@@ -2806,7 +2756,7 @@ template<IsArithmeticOrAD T>

Flag to enable or disable reverse reactions. If false, only forward reactions are considered.

-

Definition at line 474 of file engine_graph.h.

+

Definition at line 473 of file engine_graph.h.

diff --git a/docs/html/classgridfire_1_1_graph_engine.js b/docs/html/classgridfire_1_1_graph_engine.js index f5a9b4ac..4c6c9730 100644 --- a/docs/html/classgridfire_1_1_graph_engine.js +++ b/docs/html/classgridfire_1_1_graph_engine.js @@ -53,7 +53,6 @@ var classgridfire_1_1_graph_engine = [ "setUseReverseReactions", "classgridfire_1_1_graph_engine.html#a409991d527ea4d4b05d1af907fe5d197", null ], [ "syncInternalMaps", "classgridfire_1_1_graph_engine.html#acdce8d87e23a2cd1504bc9472e538c0f", null ], [ "update", "classgridfire_1_1_graph_engine.html#a5ac7cff23e70bd07ba7e510b753e2ab6", null ], - [ "validateComposition", "classgridfire_1_1_graph_engine.html#aeeafeab40a5f4dbfae78bdc87e25e93f", null ], [ "validateConservation", "classgridfire_1_1_graph_engine.html#acf4cfccea20f5cb31c9886bf233a28be", null ], [ "m_atomicReverseRates", "classgridfire_1_1_graph_engine.html#a816797b1d656d416844489692af44cf6", null ], [ "m_config", "classgridfire_1_1_graph_engine.html#a3b17102b143435ddfdc015d7a50c4b18", null ], diff --git a/docs/html/classgridfire_1_1_graph_engine_1_1_atomic_reverse_rate.html b/docs/html/classgridfire_1_1_graph_engine_1_1_atomic_reverse_rate.html index da57776f..2f8f7ca8 100644 --- a/docs/html/classgridfire_1_1_graph_engine_1_1_atomic_reverse_rate.html +++ b/docs/html/classgridfire_1_1_graph_engine_1_1_atomic_reverse_rate.html @@ -135,7 +135,7 @@ Private Attributes

Detailed Description

-

Definition at line 407 of file engine_graph.h.

+

Definition at line 406 of file engine_graph.h.

Constructor & Destructor Documentation

◆ AtomicReverseRate()

@@ -164,7 +164,7 @@ Private Attributes
-

Definition at line 409 of file engine_graph.h.

+

Definition at line 408 of file engine_graph.h.

@@ -201,7 +201,7 @@ Private Attributes
-

Definition at line 1091 of file engine_graph.cpp.

+

Definition at line 1069 of file engine_graph.cpp.

@@ -252,7 +252,7 @@ Private Attributes
-

Definition at line 1051 of file engine_graph.cpp.

+

Definition at line 1029 of file engine_graph.cpp.

@@ -288,7 +288,7 @@ Private Attributes
-

Definition at line 1100 of file engine_graph.cpp.

+

Definition at line 1078 of file engine_graph.cpp.

@@ -334,7 +334,7 @@ Private Attributes
-

Definition at line 1073 of file engine_graph.cpp.

+

Definition at line 1051 of file engine_graph.cpp.

@@ -359,7 +359,7 @@ Private Attributes
-

Definition at line 445 of file engine_graph.h.

+

Definition at line 444 of file engine_graph.h.

@@ -383,7 +383,7 @@ Private Attributes
-

Definition at line 444 of file engine_graph.h.

+

Definition at line 443 of file engine_graph.h.

diff --git a/docs/html/classgridfire_1_1_multiscale_partitioning_engine_view.html b/docs/html/classgridfire_1_1_multiscale_partitioning_engine_view.html index 4a6ebf49..19f3ea2c 100644 --- a/docs/html/classgridfire_1_1_multiscale_partitioning_engine_view.html +++ b/docs/html/classgridfire_1_1_multiscale_partitioning_engine_view.html @@ -332,7 +332,7 @@ Private Attributes
// The integrator will call calculateRHSAndEnergy, etc. on the multiscaleEngine.
auto Y_initial = multiscaleEngine.mapNetInToMolarAbundanceVector({equilibratedComp, ...});
auto derivatives = multiscaleEngine.calculateRHSAndEnergy(Y_initial, T9, rho);
-
gridfire::GraphEngine
A reaction network engine that uses a graph-based representation.
Definition engine_graph.h:101
+
gridfire::GraphEngine
A reaction network engine that uses a graph-based representation.
Definition engine_graph.h:100
gridfire::MultiscalePartitioningEngineView
An engine view that partitions the reaction network into multiple groups based on timescales.
Definition engine_multiscale.h:174
gridfire::NetIn
Definition network.h:53
diff --git a/docs/html/doxygen_crawl.html b/docs/html/doxygen_crawl.html index cb832667..1743ce56 100644 --- a/docs/html/doxygen_crawl.html +++ b/docs/html/doxygen_crawl.html @@ -260,7 +260,6 @@ - @@ -861,6 +860,14 @@ + + + + + + + + @@ -899,7 +906,6 @@ - @@ -979,6 +985,7 @@ + @@ -1340,6 +1347,7 @@ + diff --git a/docs/html/engine_2bindings_8cpp_source.html b/docs/html/engine_2bindings_8cpp_source.html index 822585f9..fcd6aa16 100644 --- a/docs/html/engine_2bindings_8cpp_source.html +++ b/docs/html/engine_2bindings_8cpp_source.html @@ -510,19 +510,19 @@ $(function(){initNavTree('engine_2bindings_8cpp_source.html',''); initResizable(
gridfire::DynamicEngine
Abstract class for engines supporting Jacobian and stoichiometry operations.
Definition engine_abstract.h:130
gridfire::FileDefinedEngineView::getNetworkFile
std::string getNetworkFile() const
Definition engine_defined.h:266
gridfire::FileDefinedEngineView::getParser
const io::NetworkFileParser & getParser() const
Definition engine_defined.h:267
-
gridfire::GraphEngine::isPrecomputationEnabled
bool isPrecomputationEnabled() const
Definition engine_graph.cpp:637
-
gridfire::GraphEngine::calculateReverseRateTwoBody
double calculateReverseRateTwoBody(const reaction::Reaction &reaction, const double T9, const double forwardRate, const double expFactor) const
Definition engine_graph.cpp:291
-
gridfire::GraphEngine::calculateReverseRate
double calculateReverseRate(const reaction::Reaction &reaction, double T9) const
Definition engine_graph.cpp:262
-
gridfire::GraphEngine::setUseReverseReactions
void setUseReverseReactions(bool useReverse)
Definition engine_graph.cpp:413
-
gridfire::GraphEngine::setPrecomputation
void setPrecomputation(bool precompute)
Definition engine_graph.cpp:633
-
gridfire::GraphEngine::exportToCSV
void exportToCSV(const std::string &filename) const
Exports the network to a CSV file for analysis.
Definition engine_graph.cpp:810
-
gridfire::GraphEngine::getNetReactionStoichiometry
static std::unordered_map< fourdst::atomic::Species, int > getNetReactionStoichiometry(const reaction::Reaction &reaction)
Gets the net stoichiometry for a given reaction.
Definition engine_graph.cpp:749
+
gridfire::GraphEngine::isPrecomputationEnabled
bool isPrecomputationEnabled() const
Definition engine_graph.cpp:615
+
gridfire::GraphEngine::calculateReverseRateTwoBody
double calculateReverseRateTwoBody(const reaction::Reaction &reaction, const double T9, const double forwardRate, const double expFactor) const
Definition engine_graph.cpp:269
+
gridfire::GraphEngine::calculateReverseRate
double calculateReverseRate(const reaction::Reaction &reaction, double T9) const
Definition engine_graph.cpp:242
+
gridfire::GraphEngine::setUseReverseReactions
void setUseReverseReactions(bool useReverse)
Definition engine_graph.cpp:391
+
gridfire::GraphEngine::setPrecomputation
void setPrecomputation(bool precompute)
Definition engine_graph.cpp:611
+
gridfire::GraphEngine::exportToCSV
void exportToCSV(const std::string &filename) const
Exports the network to a CSV file for analysis.
Definition engine_graph.cpp:788
+
gridfire::GraphEngine::getNetReactionStoichiometry
static std::unordered_map< fourdst::atomic::Species, int > getNetReactionStoichiometry(const reaction::Reaction &reaction)
Gets the net stoichiometry for a given reaction.
Definition engine_graph.cpp:727
gridfire::GraphEngine::involvesSpecies
bool involvesSpecies(const fourdst::atomic::Species &species) const
Checks if a given species is involved in the network.
Definition engine_graph.cpp:179
-
gridfire::GraphEngine::generateJacobianMatrix
void generateJacobianMatrix(const std::vector< double > &Y_dynamic, const double T9, const double rho) const override
Generates the Jacobian matrix for the current state.
Definition engine_graph.cpp:654
-
gridfire::GraphEngine::exportToDot
void exportToDot(const std::string &filename) const
Exports the network to a DOT file for visualization.
Definition engine_graph.cpp:762
-
gridfire::GraphEngine::getPartitionFunction
const partition::PartitionFunction & getPartitionFunction() const
Definition engine_graph.cpp:641
-
gridfire::GraphEngine::isUsingReverseReactions
bool isUsingReverseReactions() const
Definition engine_graph.cpp:409
-
gridfire::GraphEngine::calculateReverseRateTwoBodyDerivative
double calculateReverseRateTwoBodyDerivative(const reaction::Reaction &reaction, const double T9, const double reverseRate) const
Definition engine_graph.cpp:368
+
gridfire::GraphEngine::generateJacobianMatrix
void generateJacobianMatrix(const std::vector< double > &Y_dynamic, const double T9, const double rho) const override
Generates the Jacobian matrix for the current state.
Definition engine_graph.cpp:632
+
gridfire::GraphEngine::exportToDot
void exportToDot(const std::string &filename) const
Exports the network to a DOT file for visualization.
Definition engine_graph.cpp:740
+
gridfire::GraphEngine::getPartitionFunction
const partition::PartitionFunction & getPartitionFunction() const
Definition engine_graph.cpp:619
+
gridfire::GraphEngine::isUsingReverseReactions
bool isUsingReverseReactions() const
Definition engine_graph.cpp:387
+
gridfire::GraphEngine::calculateReverseRateTwoBodyDerivative
double calculateReverseRateTwoBodyDerivative(const reaction::Reaction &reaction, const double T9, const double reverseRate) const
Definition engine_graph.cpp:346
gridfire::MultiscalePartitioningEngineView::getDynamicSpecies
const std::vector< fourdst::atomic::Species > & getDynamicSpecies() const
Gets the dynamic species in the network.
Definition engine_multiscale.cpp:789
gridfire::MultiscalePartitioningEngineView::getBaseEngine
const DynamicEngine & getBaseEngine() const override
Gets the base engine.
Definition engine_multiscale.cpp:412
gridfire::MultiscalePartitioningEngineView::getFastSpecies
std::vector< fourdst::atomic::Species > getFastSpecies() const
Gets the fast species in the network.
Definition engine_multiscale.cpp:776
diff --git a/docs/html/engine_8h.html b/docs/html/engine_8h.html index 0ca53cf9..615f74dd 100644 --- a/docs/html/engine_8h.html +++ b/docs/html/engine_8h.html @@ -156,7 +156,7 @@ GraphEngine Example
// Create a GraphEngine
gridfire::GraphEngine engine(composition);
-
gridfire::GraphEngine
A reaction network engine that uses a graph-based representation.
Definition engine_graph.h:101
+
gridfire::GraphEngine
A reaction network engine that uses a graph-based representation.
Definition engine_graph.h:100
engine_graph.h

AdaptiveEngineView Example

diff --git a/docs/html/engine__graph_8cpp_source.html b/docs/html/engine__graph_8cpp_source.html index 5bf678f6..8cfce702 100644 --- a/docs/html/engine__graph_8cpp_source.html +++ b/docs/html/engine__graph_8cpp_source.html @@ -372,1020 +372,995 @@ $(function(){initNavTree('engine__graph_8cpp_source.html',''); initResizable(tru
241
-
242 void GraphEngine::validateComposition(const fourdst::composition::Composition &composition, double culling, double T9) {
-
243 // Check if the requested network has already been cached.
-
244 // PERF: Rebuilding this should be pretty fast but it may be a good point of optimization in the future.
-
245 const reaction::LogicalReactionSet validationReactionSet = build_reaclib_nuclear_network(composition, false);
-
246 // TODO: need some more robust method here to
-
247 // A. Build the basic network from the composition's species with non zero mass fractions.
-
248 // B. rebuild a new composition from the reaction set's reactants + products (with the mass fractions from the things that are only products set to 0)
-
249 // C. Rebuild the reaction set from the new composition
-
250 // D. Cull reactions where all reactants have mass fractions below the culling threshold.
-
251 // E. Be careful about maintaining caching through all of this
-
252
-
253
-
254 // This allows for dynamic network modification while retaining caching for networks which are very similar.
-
255 if (validationReactionSet != m_reactions) {
-
256 LOG_DEBUG(m_logger, "Reaction set not cached. Rebuilding the reaction set for T9={} and culling={}.", T9, culling);
-
257 m_reactions = validationReactionSet;
-
258 syncInternalMaps(); // Re-sync internal maps after updating reactions. Note this will also retrace the AD tape.
-
259 }
-
260 }
+
242 double GraphEngine::calculateReverseRate(
+
243 const reaction::Reaction &reaction,
+
244 const double T9
+
245 ) const {
+
246 if (!m_useReverseReactions) {
+
247 LOG_TRACE_L3_LIMIT_EVERY_N(std::numeric_limits<int>::max(), m_logger, "Reverse reactions are disabled. Returning 0.0 for reverse rate of reaction '{}'.", reaction.id());
+
248 return 0.0; // If reverse reactions are not used, return 0.0
+
249 }
+
250 const double temp = T9 * 1e9; // Convert T9 to Kelvin
+
251
+
252 // In debug builds we check the units on kB to ensure it is in erg/K. This is removed in release builds to avoid overhead. (Note assert is a no-op in release builds)
+
253 assert(Constants::getInstance().get("kB").unit == "erg / K");
+
254
+
255 const double kBMeV = m_constants.kB * 624151; // Convert kB to MeV/K NOTE: This relies on the fact that m_constants.kB is in erg/K!
+
256 const double expFactor = std::exp(-reaction.qValue() / (kBMeV * temp));
+
257 double reverseRate = 0.0;
+
258 const double forwardRate = reaction.calculate_rate(T9);
+
259
+
260 if (reaction.reactants().size() == 2 && reaction.products().size() == 2) {
+
261 reverseRate = calculateReverseRateTwoBody(reaction, T9, forwardRate, expFactor);
+
262 } else {
+
263 LOG_WARNING_LIMIT_EVERY_N(1000000, m_logger, "Reverse rate calculation for reactions with more than two reactants or products is not implemented (reaction id {}).", reaction.peName());
+
264 }
+
265 LOG_TRACE_L2_LIMIT_EVERY_N(1000, m_logger, "Calculated reverse rate for reaction '{}': {:.3E} at T9={:.3E}.", reaction.id(), reverseRate, T9);
+
266 return reverseRate;
+
267 }
-
261
-
-
262 double GraphEngine::calculateReverseRate(
-
263 const reaction::Reaction &reaction,
-
264 const double T9
-
265 ) const {
-
266 if (!m_useReverseReactions) {
-
267 LOG_TRACE_L3_LIMIT_EVERY_N(std::numeric_limits<int>::max(), m_logger, "Reverse reactions are disabled. Returning 0.0 for reverse rate of reaction '{}'.", reaction.id());
-
268 return 0.0; // If reverse reactions are not used, return 0.0
-
269 }
-
270 const double expFactor = std::exp(-reaction.qValue() / (m_constants.kB * T9));
-
271 if (s_debug) {
-
272 std::cout << "\texpFactor = exp(-qValue/(kB * T9))\n";
-
273 std::cout << "\texpFactor: " << expFactor << " for reaction: " << reaction.peName() << std::endl;
-
274 std::cout << "\tQ-value: " << reaction.qValue() << " at T9: " << T9 << std::endl;
-
275 std::cout << "\tT9: " << T9 << std::endl;
-
276 std::cout << "\tkB * T9: " << m_constants.kB * T9 << std::endl;
-
277 std::cout << "\tqValue/(kB * T9): " << reaction.qValue() / (m_constants.kB * T9) << std::endl;
-
278 }
-
279 double reverseRate = 0.0;
-
280 const double forwardRate = reaction.calculate_rate(T9);
-
281
-
282 if (reaction.reactants().size() == 2 && reaction.products().size() == 2) {
-
283 reverseRate = calculateReverseRateTwoBody(reaction, T9, forwardRate, expFactor);
-
284 } else {
-
285 LOG_WARNING_LIMIT_EVERY_N(1000000, m_logger, "Reverse rate calculation for reactions with more than two reactants or products is not implemented (reaction id {}).", reaction.peName());
-
286 }
-
287 LOG_TRACE_L2_LIMIT_EVERY_N(1000, m_logger, "Calculated reverse rate for reaction '{}': {:.3E} at T9={:.3E}.", reaction.id(), reverseRate, T9);
-
288 return reverseRate;
-
289 }
-
-
290
-
-
291 double GraphEngine::calculateReverseRateTwoBody(
-
292 const reaction::Reaction &reaction,
-
293 const double T9,
-
294 const double forwardRate,
-
295 const double expFactor
-
296 ) const {
-
297 std::vector<double> reactantPartitionFunctions;
-
298 std::vector<double> productPartitionFunctions;
-
299
-
300 reactantPartitionFunctions.reserve(reaction.reactants().size());
-
301 productPartitionFunctions.reserve(reaction.products().size());
+
268
+
+ + +
271 const double T9,
+
272 const double forwardRate,
+
273 const double expFactor
+
274 ) const {
+
275 std::vector<double> reactantPartitionFunctions;
+
276 std::vector<double> productPartitionFunctions;
+
277
+
278 reactantPartitionFunctions.reserve(reaction.reactants().size());
+
279 productPartitionFunctions.reserve(reaction.products().size());
+
280
+
281 std::unordered_map<fourdst::atomic::Species, int> reactantMultiplicity;
+
282 std::unordered_map<fourdst::atomic::Species, int> productMultiplicity;
+
283
+
284 reactantMultiplicity.reserve(reaction.reactants().size());
+
285 productMultiplicity.reserve(reaction.products().size());
+
286
+
287 for (const auto& reactant : reaction.reactants()) {
+
288 reactantMultiplicity[reactant] += 1;
+
289 }
+
290 for (const auto& product : reaction.products()) {
+
291 productMultiplicity[product] += 1;
+
292 }
+
293 double reactantSymmetryFactor = 1.0;
+
294 double productSymmetryFactor = 1.0;
+
295 for (const auto& count : reactantMultiplicity | std::views::values) {
+
296 reactantSymmetryFactor *= std::tgamma(count + 1);
+
297 }
+
298 for (const auto& count : productMultiplicity | std::views::values) {
+
299 productSymmetryFactor *= std::tgamma(count + 1);
+
300 }
+
301 const double symmetryFactor = reactantSymmetryFactor / productSymmetryFactor;
302
-
303 std::unordered_map<fourdst::atomic::Species, int> reactantMultiplicity;
-
304 std::unordered_map<fourdst::atomic::Species, int> productMultiplicity;
-
305
-
306 reactantMultiplicity.reserve(reaction.reactants().size());
-
307 productMultiplicity.reserve(reaction.products().size());
-
308
-
309 for (const auto& reactant : reaction.reactants()) {
-
310 reactantMultiplicity[reactant] += 1;
-
311 }
-
312 for (const auto& product : reaction.products()) {
-
313 productMultiplicity[product] += 1;
-
314 }
-
315 double reactantSymmetryFactor = 1.0;
-
316 double productSymmetryFactor = 1.0;
-
317 for (const auto& count : reactantMultiplicity | std::views::values) {
-
318 reactantSymmetryFactor *= std::tgamma(count + 1);
-
319 }
-
320 for (const auto& count : productMultiplicity | std::views::values) {
-
321 productSymmetryFactor *= std::tgamma(count + 1);
-
322 }
-
323 const double symmetryFactor = reactantSymmetryFactor / productSymmetryFactor;
-
324
-
325 // Accumulate mass terms
-
326 auto mass_op = [](double acc, const auto& species) { return acc * species.a(); };
-
327 const double massNumerator = std::accumulate(
-
328 reaction.reactants().begin(),
-
329 reaction.reactants().end(),
-
330 1.0,
-
331 mass_op
-
332 );
-
333 const double massDenominator = std::accumulate(
-
334 reaction.products().begin(),
-
335 reaction.products().end(),
-
336 1.0,
-
337 mass_op
-
338 );
-
339
-
340 // Accumulate partition functions
-
341 auto pf_op = [&](double acc, const auto& species) {
-
342 return acc * m_partitionFunction->evaluate(species.z(), species.a(), T9);
-
343 };
-
344 const double partitionFunctionNumerator = std::accumulate(
-
345 reaction.reactants().begin(),
-
346 reaction.reactants().end(),
-
347 1.0,
-
348 pf_op
-
349 );
-
350 const double partitionFunctionDenominator = std::accumulate(
-
351 reaction.products().begin(),
-
352 reaction.products().end(),
-
353 1.0,
-
354 pf_op
-
355 );
+
303 // Accumulate mass terms
+
304 auto mass_op = [](double acc, const auto& species) { return acc * species.a(); };
+
305 const double massNumerator = std::accumulate(
+
306 reaction.reactants().begin(),
+
307 reaction.reactants().end(),
+
308 1.0,
+
309 mass_op
+
310 );
+
311 const double massDenominator = std::accumulate(
+
312 reaction.products().begin(),
+
313 reaction.products().end(),
+
314 1.0,
+
315 mass_op
+
316 );
+
317
+
318 // Accumulate partition functions
+
319 auto pf_op = [&](double acc, const auto& species) {
+
320 return acc * m_partitionFunction->evaluate(species.z(), species.a(), T9);
+
321 };
+
322 const double partitionFunctionNumerator = std::accumulate(
+
323 reaction.reactants().begin(),
+
324 reaction.reactants().end(),
+
325 1.0,
+
326 pf_op
+
327 );
+
328 const double partitionFunctionDenominator = std::accumulate(
+
329 reaction.products().begin(),
+
330 reaction.products().end(),
+
331 1.0,
+
332 pf_op
+
333 );
+
334
+
335 const double CT = std::pow(massNumerator/massDenominator, 1.5) *
+
336 (partitionFunctionNumerator/partitionFunctionDenominator);
+
337
+
338 const double reverseRate = forwardRate * symmetryFactor * CT * expFactor;
+
339 if (!std::isfinite(reverseRate)) {
+
340 return 0.0; // If the reverse rate is not finite, return 0.0
+
341 }
+
342 return reverseRate; // Return the calculated reverse rate
+
343
+
344 }
+
+
345
+
+ + +
348 const double T9,
+
349 const double reverseRate
+
350 ) const {
+ +
352 LOG_TRACE_L3_LIMIT_EVERY_N(std::numeric_limits<int>::max(), m_logger, "Reverse reactions are disabled. Returning 0.0 for reverse rate of reaction '{}'.", reaction.id());
+
353 return 0.0; // If reverse reactions are not used, return 0.0
+
354 }
+
355 const double d_log_kFwd = reaction.calculate_forward_rate_log_derivative(T9);
356
-
357 const double CT = std::pow(massNumerator/massDenominator, 1.5) *
-
358 (partitionFunctionNumerator/partitionFunctionDenominator);
-
359
-
360 const double reverseRate = forwardRate * symmetryFactor * CT * expFactor;
-
361 if (!std::isfinite(reverseRate)) {
-
362 return 0.0; // If the reverse rate is not finite, return 0.0
-
363 }
-
364 return reverseRate; // Return the calculated reverse rate
-
365
-
366 }
-
-
367
-
- - -
370 const double T9,
-
371 const double reverseRate
-
372 ) const {
- -
374 LOG_TRACE_L3_LIMIT_EVERY_N(std::numeric_limits<int>::max(), m_logger, "Reverse reactions are disabled. Returning 0.0 for reverse rate of reaction '{}'.", reaction.id());
-
375 return 0.0; // If reverse reactions are not used, return 0.0
-
376 }
-
377 const double d_log_kFwd = reaction.calculate_forward_rate_log_derivative(T9);
+
357 auto log_deriv_pf_op = [&](double acc, const auto& species) {
+
358 const double g = m_partitionFunction->evaluate(species.z(), species.a(), T9);
+
359 const double dg_dT = m_partitionFunction->evaluateDerivative(species.z(), species.a(), T9);
+
360 return (g == 0.0) ? acc : acc + (dg_dT / g);
+
361 };
+
362
+
363 const double reactant_log_derivative_sum = std::accumulate(
+
364 reaction.reactants().begin(),
+
365 reaction.reactants().end(),
+
366 0.0,
+
367 log_deriv_pf_op
+
368 );
+
369
+
370 const double product_log_derivative_sum = std::accumulate(
+
371 reaction.products().begin(),
+
372 reaction.products().end(),
+
373 0.0,
+
374 log_deriv_pf_op
+
375 );
+
376
+
377 const double d_log_C = reactant_log_derivative_sum - product_log_derivative_sum;
378
-
379 auto log_deriv_pf_op = [&](double acc, const auto& species) {
-
380 const double g = m_partitionFunction->evaluate(species.z(), species.a(), T9);
-
381 const double dg_dT = m_partitionFunction->evaluateDerivative(species.z(), species.a(), T9);
-
382 return (g == 0.0) ? acc : acc + (dg_dT / g);
-
383 };
+
379 const double d_log_exp = reaction.qValue() / (m_constants.kB * T9 * T9);
+
380
+
381 const double log_total_derivative = d_log_kFwd + d_log_C + d_log_exp;
+
382
+
383 return reverseRate * log_total_derivative; // Return the derivative of the reverse rate with respect to T9
384
-
385 const double reactant_log_derivative_sum = std::accumulate(
-
386 reaction.reactants().begin(),
-
387 reaction.reactants().end(),
-
388 0.0,
-
389 log_deriv_pf_op
-
390 );
-
391
-
392 const double product_log_derivative_sum = std::accumulate(
-
393 reaction.products().begin(),
-
394 reaction.products().end(),
-
395 0.0,
-
396 log_deriv_pf_op
-
397 );
+
385 }
+
+
386
+
+ + +
389 }
+
+
390
+
+
391 void GraphEngine::setUseReverseReactions(const bool useReverse) {
+
392 m_useReverseReactions = useReverse;
+
393 }
+
+
394
+
+
395 int GraphEngine::getSpeciesIndex(const fourdst::atomic::Species &species) const {
+
396 return m_speciesToIndexMap.at(species); // Returns the index of the species in the stoichiometry matrix
+
397 }
+
398
-
399 const double d_log_C = reactant_log_derivative_sum - product_log_derivative_sum;
-
400
-
401 const double d_log_exp = reaction.qValue() / (m_constants.kB * T9 * T9);
-
402
-
403 const double log_total_derivative = d_log_kFwd + d_log_C + d_log_exp;
-
404
-
405 return reverseRate * log_total_derivative; // Return the derivative of the reverse rate with respect to T9
+
+
399 std::vector<double> GraphEngine::mapNetInToMolarAbundanceVector(const NetIn &netIn) const {
+
400 std::vector<double> Y(m_networkSpecies.size(), 0.0); // Initialize with zeros
+
401 for (const auto& [symbol, entry] : netIn.composition) {
+
402 Y[getSpeciesIndex(entry.isotope())] = netIn.composition.getMolarAbundance(symbol); // Map species to their molar abundance
+
403 }
+
404 return Y; // Return the vector of molar abundances
+
405 }
+
406
-
407 }
-
-
408
-
-
409 bool GraphEngine::isUsingReverseReactions() const {
-
410 return m_useReverseReactions;
-
411 }
-
-
412
-
-
413 void GraphEngine::setUseReverseReactions(const bool useReverse) {
-
414 m_useReverseReactions = useReverse;
-
415 }
-
-
416
-
-
417 int GraphEngine::getSpeciesIndex(const fourdst::atomic::Species &species) const {
-
418 return m_speciesToIndexMap.at(species); // Returns the index of the species in the stoichiometry matrix
-
419 }
-
-
420
-
-
421 std::vector<double> GraphEngine::mapNetInToMolarAbundanceVector(const NetIn &netIn) const {
-
422 std::vector<double> Y(m_networkSpecies.size(), 0.0); // Initialize with zeros
-
423 for (const auto& [symbol, entry] : netIn.composition) {
-
424 Y[getSpeciesIndex(entry.isotope())] = netIn.composition.getMolarAbundance(symbol); // Map species to their molar abundance
-
425 }
-
426 return Y; // Return the vector of molar abundances
-
427 }
-
+
+
407 PrimingReport GraphEngine::primeEngine(const NetIn &netIn) {
+
408 NetIn fullNetIn;
+
409 fourdst::composition::Composition composition;
+
410
+
411 std::vector<std::string> symbols;
+
412 symbols.reserve(m_networkSpecies.size());
+
413 for (const auto &symbol: m_networkSpecies) {
+
414 symbols.emplace_back(symbol.name());
+
415 }
+
416 composition.registerSymbol(symbols);
+
417 for (const auto& [symbol, entry] : netIn.composition) {
+
418 if (m_networkSpeciesMap.contains(symbol)) {
+
419 composition.setMassFraction(symbol, entry.mass_fraction());
+
420 } else {
+
421 composition.setMassFraction(symbol, 0.0);
+
422 }
+
423 }
+
424 composition.finalize(true);
+
425 fullNetIn.composition = composition;
+
426 fullNetIn.temperature = netIn.temperature;
+
427 fullNetIn.density = netIn.density;
428
-
- -
430 NetIn fullNetIn;
-
431 fourdst::composition::Composition composition;
-
432
-
433 std::vector<std::string> symbols;
-
434 symbols.reserve(m_networkSpecies.size());
-
435 for (const auto &symbol: m_networkSpecies) {
-
436 symbols.emplace_back(symbol.name());
-
437 }
-
438 composition.registerSymbol(symbols);
-
439 for (const auto& [symbol, entry] : netIn.composition) {
-
440 if (m_networkSpeciesMap.contains(symbol)) {
-
441 composition.setMassFraction(symbol, entry.mass_fraction());
-
442 } else {
-
443 composition.setMassFraction(symbol, 0.0);
-
444 }
+
429 auto primingReport = primeNetwork(fullNetIn, *this);
+
430
+
431 return primingReport;
+
432 }
+
+
433
+
+ +
435 return m_depth;
+
436 }
+
+
437
+
+
438 void GraphEngine::rebuild(const fourdst::composition::Composition& comp, const BuildDepthType depth) {
+
439 if (depth != m_depth) {
+
440 m_depth = depth;
+ +
442 syncInternalMaps(); // Resync internal maps after changing the depth
+
443 } else {
+
444 LOG_DEBUG(m_logger, "Rebuild requested with the same depth. No changes made to the network.");
445 }
-
446 composition.finalize(true);
-
447 fullNetIn.composition = composition;
-
448 fullNetIn.temperature = netIn.temperature;
-
449 fullNetIn.density = netIn.density;
-
450
-
451 auto primingReport = primeNetwork(fullNetIn, *this);
-
452
-
453 return primingReport;
-
454 }
+
446 }
-
455
-
- -
457 return m_depth;
-
458 }
+
447
+
+ +
449 const std::vector<double> &Y_in,
+
450 const std::vector<double> &bare_rates,
+
451 const std::vector<double> &bare_reverse_rates,
+
452 const double T9,
+
453 const double rho
+
454 ) const {
+
455 // --- Calculate screening factors ---
+
456 const std::vector<double> screeningFactors = m_screeningModel->calculateScreeningFactors(
+ + +
459 Y_in,
+
460 T9,
+
461 rho
+
462 );
+
463
+
464 // --- Optimized loop ---
+
465 std::vector<double> molarReactionFlows;
+
466 molarReactionFlows.reserve(m_precomputedReactions.size());
+
467
+
468 for (const auto& precomp : m_precomputedReactions) {
+
469 double forwardAbundanceProduct = 1.0;
+
470 // bool below_threshold = false;
+
471 for (size_t i = 0; i < precomp.unique_reactant_indices.size(); ++i) {
+
472 const size_t reactantIndex = precomp.unique_reactant_indices[i];
+
473 const int power = precomp.reactant_powers[i];
+
474 // const double abundance = Y_in[reactantIndex];
+
475 // if (abundance < MIN_ABUNDANCE_THRESHOLD) {
+
476 // below_threshold = true;
+
477 // break;
+
478 // }
+
479
+
480 forwardAbundanceProduct *= std::pow(Y_in[reactantIndex], power);
+
481 }
+
482 // if (below_threshold) {
+
483 // molarReactionFlows.push_back(0.0);
+
484 // continue; // Skip this reaction if any reactant is below the abundance threshold
+
485 // }
+
486
+
487 const double bare_rate = bare_rates[precomp.reaction_index];
+
488 const double screeningFactor = screeningFactors[precomp.reaction_index];
+
489 const size_t numReactants = m_reactions[precomp.reaction_index].reactants().size();
+
490 const size_t numProducts = m_reactions[precomp.reaction_index].products().size();
+
491
+
492 const double forwardMolarReactionFlow =
+
493 screeningFactor *
+
494 bare_rate *
+
495 precomp.symmetry_factor *
+
496 forwardAbundanceProduct *
+
497 std::pow(rho, numReactants > 1 ? numReactants - 1 : 0.0);
+
498
+
499 double reverseMolarReactionFlow = 0.0;
+
500 if (precomp.reverse_symmetry_factor != 0.0 and m_useReverseReactions) {
+
501 const double bare_reverse_rate = bare_reverse_rates[precomp.reaction_index];
+
502 double reverseAbundanceProduct = 1.0;
+
503 for (size_t i = 0; i < precomp.unique_product_indices.size(); ++i) {
+
504 reverseAbundanceProduct *= std::pow(Y_in[precomp.unique_product_indices[i]], precomp.product_powers[i]);
+
505 }
+
506 reverseMolarReactionFlow = screeningFactor *
+
507 bare_reverse_rate *
+
508 precomp.reverse_symmetry_factor *
+
509 reverseAbundanceProduct *
+
510 std::pow(rho, numProducts > 1 ? numProducts - 1 : 0.0);
+
511 }
+
512
+
513 molarReactionFlows.push_back(forwardMolarReactionFlow - reverseMolarReactionFlow);
+
514
+
515 }
+
516
+
517 // --- Assemble molar abundance derivatives ---
+ +
519 result.dydt.assign(m_networkSpecies.size(), 0.0); // Initialize derivatives to zero
+
520 for (size_t j = 0; j < m_precomputedReactions.size(); ++j) {
+
521 const auto& precomp = m_precomputedReactions[j];
+
522 const double R_j = molarReactionFlows[j];
+
523
+
524 for (size_t i = 0; i < precomp.affected_species_indices.size(); ++i) {
+
525 const size_t speciesIndex = precomp.affected_species_indices[i];
+
526 const int stoichiometricCoefficient = precomp.stoichiometric_coefficients[i];
+
527
+
528 // Update the derivative for this species
+
529 result.dydt[speciesIndex] += static_cast<double>(stoichiometricCoefficient) * R_j;
+
530 }
+
531 }
+
532
+
533 // --- Calculate the nuclear energy generation rate ---
+
534 double massProductionRate = 0.0; // [mol][s^-1]
+
535 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
+
536 const auto& species = m_networkSpecies[i];
+
537 massProductionRate += result.dydt[i] * species.mass() * m_constants.u;
+
538 }
+
539 result.nuclearEnergyGenerationRate = -massProductionRate * m_constants.Na * m_constants.c * m_constants.c; // [erg][s^-1][g^-1]
+
540 return result;
+
541
+
542 }
-
459
-
-
460 void GraphEngine::rebuild(const fourdst::composition::Composition& comp, const BuildDepthType depth) {
-
461 if (depth != m_depth) {
-
462 m_depth = depth;
- -
464 syncInternalMaps(); // Resync internal maps after changing the depth
-
465 } else {
-
466 LOG_DEBUG(m_logger, "Rebuild requested with the same depth. No changes made to the network.");
-
467 }
-
468 }
+
543
+
544 // --- Generate Stoichiometry Matrix ---
+
+ +
546 LOG_TRACE_L1(m_logger, "Generating stoichiometry matrix...");
+
547
+
548 // Task 1: Set dimensions and initialize the matrix
+
549 size_t numSpecies = m_networkSpecies.size();
+
550 size_t numReactions = m_reactions.size();
+
551 m_stoichiometryMatrix.resize(numSpecies, numReactions, false);
+
552
+
553 LOG_TRACE_L1(m_logger, "Stoichiometry matrix initialized with dimensions: {} rows (species) x {} columns (reactions).",
+
554 numSpecies, numReactions);
+
555
+
556 // Task 2: Populate the stoichiometry matrix
+
557 // Iterate through all reactions, assign them a column index, and fill in their stoichiometric coefficients.
+
558 size_t reactionColumnIndex = 0;
+
559 for (const auto& reaction : m_reactions) {
+
560 // Get the net stoichiometry for the current reaction
+
561 std::unordered_map<fourdst::atomic::Species, int> netStoichiometry = reaction.stoichiometry();
+
562
+
563 // Iterate through the species and their coefficients in the stoichiometry map
+
564 for (const auto& [species, coefficient] : netStoichiometry) {
+
565 // Find the row index for this species
+
566 auto it = m_speciesToIndexMap.find(species);
+
567 if (it != m_speciesToIndexMap.end()) {
+
568 const size_t speciesRowIndex = it->second;
+
569 // Set the matrix element. Boost.uBLAS handles sparse insertion.
+
570 m_stoichiometryMatrix(speciesRowIndex, reactionColumnIndex) = coefficient;
+
571 } else {
+
572 // This scenario should ideally not happen if m_networkSpeciesMap and m_speciesToIndexMap are correctly synced
+
573 LOG_ERROR(m_logger, "CRITICAL ERROR: Species '{}' from reaction '{}' stoichiometry not found in species to index map.",
+
574 species.name(), reaction.id());
+
575 m_logger -> flush_log();
+
576 throw std::runtime_error("Species not found in species to index map: " + std::string(species.name()));
+
577 }
+
578 }
+
579 reactionColumnIndex++; // Move to the next column for the next reaction
+
580 }
+
581
+
582 LOG_TRACE_L1(m_logger, "Stoichiometry matrix population complete. Number of non-zero elements: {}.",
+
583 m_stoichiometryMatrix.nnz()); // Assuming nnz() exists for compressed_matrix
+
584 }
-
469
-
- -
471 const std::vector<double> &Y_in,
-
472 const std::vector<double> &bare_rates,
-
473 const std::vector<double> &bare_reverse_rates,
-
474 const double T9,
-
475 const double rho
-
476 ) const {
-
477 // --- Calculate screening factors ---
-
478 const std::vector<double> screeningFactors = m_screeningModel->calculateScreeningFactors(
- - -
481 Y_in,
-
482 T9,
-
483 rho
-
484 );
-
485
-
486 // --- Optimized loop ---
-
487 std::vector<double> molarReactionFlows;
-
488 molarReactionFlows.reserve(m_precomputedReactions.size());
-
489
-
490 for (const auto& precomp : m_precomputedReactions) {
-
491 double forwardAbundanceProduct = 1.0;
-
492 // bool below_threshold = false;
-
493 for (size_t i = 0; i < precomp.unique_reactant_indices.size(); ++i) {
-
494 const size_t reactantIndex = precomp.unique_reactant_indices[i];
-
495 const int power = precomp.reactant_powers[i];
-
496 // const double abundance = Y_in[reactantIndex];
-
497 // if (abundance < MIN_ABUNDANCE_THRESHOLD) {
-
498 // below_threshold = true;
-
499 // break;
-
500 // }
-
501
-
502 forwardAbundanceProduct *= std::pow(Y_in[reactantIndex], power);
-
503 }
-
504 // if (below_threshold) {
-
505 // molarReactionFlows.push_back(0.0);
-
506 // continue; // Skip this reaction if any reactant is below the abundance threshold
-
507 // }
-
508
-
509 const double bare_rate = bare_rates[precomp.reaction_index];
-
510 const double screeningFactor = screeningFactors[precomp.reaction_index];
-
511 const size_t numReactants = m_reactions[precomp.reaction_index].reactants().size();
-
512 const size_t numProducts = m_reactions[precomp.reaction_index].products().size();
-
513
-
514 const double forwardMolarReactionFlow =
-
515 screeningFactor *
-
516 bare_rate *
-
517 precomp.symmetry_factor *
-
518 forwardAbundanceProduct *
-
519 std::pow(rho, numReactants > 1 ? numReactants - 1 : 0.0);
-
520
-
521 double reverseMolarReactionFlow = 0.0;
-
522 if (precomp.reverse_symmetry_factor != 0.0 and m_useReverseReactions) {
-
523 const double bare_reverse_rate = bare_reverse_rates[precomp.reaction_index];
-
524 double reverseAbundanceProduct = 1.0;
-
525 for (size_t i = 0; i < precomp.unique_product_indices.size(); ++i) {
-
526 reverseAbundanceProduct *= std::pow(Y_in[precomp.unique_product_indices[i]], precomp.product_powers[i]);
-
527 }
-
528 reverseMolarReactionFlow = screeningFactor *
-
529 bare_reverse_rate *
-
530 precomp.reverse_symmetry_factor *
-
531 reverseAbundanceProduct *
-
532 std::pow(rho, numProducts > 1 ? numProducts - 1 : 0.0);
-
533 }
-
534
-
535 molarReactionFlows.push_back(forwardMolarReactionFlow - reverseMolarReactionFlow);
-
536
-
537 }
-
538
-
539 // --- Assemble molar abundance derivatives ---
- -
541 result.dydt.assign(m_networkSpecies.size(), 0.0); // Initialize derivatives to zero
-
542 for (size_t j = 0; j < m_precomputedReactions.size(); ++j) {
-
543 const auto& precomp = m_precomputedReactions[j];
-
544 const double R_j = molarReactionFlows[j];
-
545
-
546 for (size_t i = 0; i < precomp.affected_species_indices.size(); ++i) {
-
547 const size_t speciesIndex = precomp.affected_species_indices[i];
-
548 const int stoichiometricCoefficient = precomp.stoichiometric_coefficients[i];
-
549
-
550 // Update the derivative for this species
-
551 result.dydt[speciesIndex] += static_cast<double>(stoichiometricCoefficient) * R_j;
-
552 }
-
553 }
-
554
-
555 // --- Calculate the nuclear energy generation rate ---
-
556 double massProductionRate = 0.0; // [mol][s^-1]
-
557 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
-
558 const auto& species = m_networkSpecies[i];
-
559 massProductionRate += result.dydt[i] * species.mass() * m_constants.u;
-
560 }
-
561 result.nuclearEnergyGenerationRate = -massProductionRate * m_constants.Na * m_constants.c * m_constants.c; // [erg][s^-1][g^-1]
-
562 return result;
-
563
-
564 }
+
585
+
+ +
587 const std::vector<double> &Y_in,
+
588 const double T9,
+
589 const double rho
+
590 ) const {
+
591 return calculateAllDerivatives<double>(Y_in, T9, rho);
+
592 }
-
565
-
566 // --- Generate Stoichiometry Matrix ---
-
- -
568 LOG_TRACE_L1(m_logger, "Generating stoichiometry matrix...");
-
569
-
570 // Task 1: Set dimensions and initialize the matrix
-
571 size_t numSpecies = m_networkSpecies.size();
-
572 size_t numReactions = m_reactions.size();
-
573 m_stoichiometryMatrix.resize(numSpecies, numReactions, false);
-
574
-
575 LOG_TRACE_L1(m_logger, "Stoichiometry matrix initialized with dimensions: {} rows (species) x {} columns (reactions).",
-
576 numSpecies, numReactions);
-
577
-
578 // Task 2: Populate the stoichiometry matrix
-
579 // Iterate through all reactions, assign them a column index, and fill in their stoichiometric coefficients.
-
580 size_t reactionColumnIndex = 0;
-
581 for (const auto& reaction : m_reactions) {
-
582 // Get the net stoichiometry for the current reaction
-
583 std::unordered_map<fourdst::atomic::Species, int> netStoichiometry = reaction.stoichiometry();
-
584
-
585 // Iterate through the species and their coefficients in the stoichiometry map
-
586 for (const auto& [species, coefficient] : netStoichiometry) {
-
587 // Find the row index for this species
-
588 auto it = m_speciesToIndexMap.find(species);
-
589 if (it != m_speciesToIndexMap.end()) {
-
590 const size_t speciesRowIndex = it->second;
-
591 // Set the matrix element. Boost.uBLAS handles sparse insertion.
-
592 m_stoichiometryMatrix(speciesRowIndex, reactionColumnIndex) = coefficient;
-
593 } else {
-
594 // This scenario should ideally not happen if m_networkSpeciesMap and m_speciesToIndexMap are correctly synced
-
595 LOG_ERROR(m_logger, "CRITICAL ERROR: Species '{}' from reaction '{}' stoichiometry not found in species to index map.",
-
596 species.name(), reaction.id());
-
597 m_logger -> flush_log();
-
598 throw std::runtime_error("Species not found in species to index map: " + std::string(species.name()));
-
599 }
-
600 }
-
601 reactionColumnIndex++; // Move to the next column for the next reaction
-
602 }
-
603
-
604 LOG_TRACE_L1(m_logger, "Stoichiometry matrix population complete. Number of non-zero elements: {}.",
-
605 m_stoichiometryMatrix.nnz()); // Assuming nnz() exists for compressed_matrix
-
606 }
+
593
+
+ +
595 const std::vector<ADDouble> &Y_in,
+
596 const ADDouble &T9,
+
597 const ADDouble &rho
+
598 ) const {
+
599 return calculateAllDerivatives<ADDouble>(Y_in, T9, rho);
+
600 }
-
607
-
- -
609 const std::vector<double> &Y_in,
-
610 const double T9,
-
611 const double rho
-
612 ) const {
-
613 return calculateAllDerivatives<double>(Y_in, T9, rho);
-
614 }
+
601
+ -
615
-
- -
617 const std::vector<ADDouble> &Y_in,
-
618 const ADDouble &T9,
-
619 const ADDouble &rho
-
620 ) const {
-
621 return calculateAllDerivatives<ADDouble>(Y_in, T9, rho);
-
622 }
+
606
+ -
623
-
- - -
626 m_screeningType = model;
-
627 }
+
610
+
+
611 void GraphEngine::setPrecomputation(const bool precompute) {
+
612 m_usePrecomputation = precompute;
+
613 }
-
628
-
- -
630 return m_screeningType;
-
631 }
+
614
+
+ +
616 return m_usePrecomputation;
+
617 }
-
632
-
-
633 void GraphEngine::setPrecomputation(const bool precompute) {
-
634 m_usePrecomputation = precompute;
-
635 }
+
618
+ -
636
-
- -
638 return m_usePrecomputation;
-
639 }
+
622
+
+ + +
625 const std::vector<double> &Y,
+
626 const double T9,
+
627 const double rho
+
628 ) const {
+ +
630 }
+
631
+
+ +
633 const std::vector<double> &Y_dynamic,
+
634 const double T9,
+
635 const double rho
+
636 ) const {
+
637
+
638 LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Generating jacobian matrix for T9={}, rho={}..", T9, rho);
+
639 const size_t numSpecies = m_networkSpecies.size();
640
-
- -
642 return *m_partitionFunction;
-
643 }
+
641 // 1. Pack the input variables into a vector for CppAD
+
642 std::vector<double> adInput(numSpecies + 2, 0.0); // +2 for T9 and rho
+
643 for (size_t i = 0; i < numSpecies; ++i) {
+
644 adInput[i] = std::max(Y_dynamic[i], 1e-99); // regularize the jacobian...
+
645 }
+
646 adInput[numSpecies] = T9; // T9
+
647 adInput[numSpecies + 1] = rho; // rho
+
648
+
649 // 2. Calculate the full jacobian
+
650 const std::vector<double> dotY = m_rhsADFun.Jacobian(adInput);
+
651
+
652 // 3. Pack jacobian vector into sparse matrix
+
653 m_jacobianMatrix.clear();
+
654 for (size_t i = 0; i < numSpecies; ++i) {
+
655 for (size_t j = 0; j < numSpecies; ++j) {
+
656 const double value = dotY[i * (numSpecies + 2) + j];
+
657 if (std::abs(value) > MIN_JACOBIAN_THRESHOLD || i == j) { // Always keep diagonal elements to avoid pathological stiffness
+
658 m_jacobianMatrix(i, j) = value;
+
659 }
+
660 }
+
661 }
+
662 LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Jacobian matrix generated with dimensions: {} rows x {} columns.", m_jacobianMatrix.size1(), m_jacobianMatrix.size2());
+
663 }
-
644
-
- - -
647 const std::vector<double> &Y,
-
648 const double T9,
-
649 const double rho
-
650 ) const {
- -
652 }
-
-
653
-
- -
655 const std::vector<double> &Y_dynamic,
-
656 const double T9,
-
657 const double rho
-
658 ) const {
-
659
-
660 LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Generating jacobian matrix for T9={}, rho={}..", T9, rho);
-
661 const size_t numSpecies = m_networkSpecies.size();
-
662
-
663 // 1. Pack the input variables into a vector for CppAD
-
664 std::vector<double> adInput(numSpecies + 2, 0.0); // +2 for T9 and rho
-
665 for (size_t i = 0; i < numSpecies; ++i) {
-
666 adInput[i] = std::max(Y_dynamic[i], 1e-99); // regularize the jacobian...
-
667 }
-
668 adInput[numSpecies] = T9; // T9
-
669 adInput[numSpecies + 1] = rho; // rho
-
670
-
671 // 2. Calculate the full jacobian
-
672 const std::vector<double> dotY = m_rhsADFun.Jacobian(adInput);
-
673
-
674 // 3. Pack jacobian vector into sparse matrix
-
675 m_jacobianMatrix.clear();
-
676 for (size_t i = 0; i < numSpecies; ++i) {
-
677 for (size_t j = 0; j < numSpecies; ++j) {
-
678 const double value = dotY[i * (numSpecies + 2) + j];
-
679 if (std::abs(value) > MIN_JACOBIAN_THRESHOLD || i == j) { // Always keep diagonal elements to avoid pathological stiffness
-
680 m_jacobianMatrix(i, j) = value;
-
681 }
-
682 }
-
683 }
-
684 LOG_TRACE_L1_LIMIT_EVERY_N(1000, m_logger, "Jacobian matrix generated with dimensions: {} rows x {} columns.", m_jacobianMatrix.size1(), m_jacobianMatrix.size2());
-
685 }
-
-
686
-
- -
688 const std::vector<double> &Y_dynamic,
-
689 const double T9,
-
690 const double rho,
-
691 const SparsityPattern &sparsityPattern
-
692 ) const {
-
693 // --- Pack the input variables into a vector for CppAD ---
-
694 const size_t numSpecies = m_networkSpecies.size();
-
695 std::vector<double> x(numSpecies + 2, 0.0);
-
696 for (size_t i = 0; i < numSpecies; ++i) {
-
697 x[i] = Y_dynamic[i];
-
698 }
-
699 x[numSpecies] = T9;
-
700 x[numSpecies + 1] = rho;
-
701
-
702 // --- Convert into CppAD Sparsity pattern ---
-
703 const size_t nnz = sparsityPattern.size(); // Number of non-zero entries in the sparsity pattern
-
704 std::vector<size_t> row_indices(nnz);
-
705 std::vector<size_t> col_indices(nnz);
-
706
-
707 for (size_t k = 0; k < nnz; ++k) {
-
708 row_indices[k] = sparsityPattern[k].first;
-
709 col_indices[k] = sparsityPattern[k].second;
-
710 }
-
711
-
712 std::vector<double> values(nnz);
-
713 const size_t num_rows_jac = numSpecies;
-
714 const size_t num_cols_jac = numSpecies + 2; // +2 for T9 and rho
+
664
+
+ +
666 const std::vector<double> &Y_dynamic,
+
667 const double T9,
+
668 const double rho,
+
669 const SparsityPattern &sparsityPattern
+
670 ) const {
+
671 // --- Pack the input variables into a vector for CppAD ---
+
672 const size_t numSpecies = m_networkSpecies.size();
+
673 std::vector<double> x(numSpecies + 2, 0.0);
+
674 for (size_t i = 0; i < numSpecies; ++i) {
+
675 x[i] = Y_dynamic[i];
+
676 }
+
677 x[numSpecies] = T9;
+
678 x[numSpecies + 1] = rho;
+
679
+
680 // --- Convert into CppAD Sparsity pattern ---
+
681 const size_t nnz = sparsityPattern.size(); // Number of non-zero entries in the sparsity pattern
+
682 std::vector<size_t> row_indices(nnz);
+
683 std::vector<size_t> col_indices(nnz);
+
684
+
685 for (size_t k = 0; k < nnz; ++k) {
+
686 row_indices[k] = sparsityPattern[k].first;
+
687 col_indices[k] = sparsityPattern[k].second;
+
688 }
+
689
+
690 std::vector<double> values(nnz);
+
691 const size_t num_rows_jac = numSpecies;
+
692 const size_t num_cols_jac = numSpecies + 2; // +2 for T9 and rho
+
693
+
694 CppAD::sparse_rc<std::vector<size_t>> CppAD_sparsity_pattern(num_rows_jac, num_cols_jac, nnz);
+
695 for (size_t k = 0; k < nnz; ++k) {
+
696 CppAD_sparsity_pattern.set(k, sparsityPattern[k].first, sparsityPattern[k].second);
+
697 }
+
698
+
699 CppAD::sparse_rcv<std::vector<size_t>, std::vector<double>> jac_subset(CppAD_sparsity_pattern);
+
700
+
701 m_rhsADFun.sparse_jac_rev(
+
702 x,
+
703 jac_subset, // Sparse Jacobian output
+ +
705 "cppad",
+
706 m_jac_work // Work vector for CppAD
+
707 );
+
708
+
709 // --- Convert the sparse Jacobian back to the Boost uBLAS format ---
+
710 m_jacobianMatrix.clear();
+
711 for (size_t k = 0; k < nnz; ++k) {
+
712 const size_t row = jac_subset.row()[k];
+
713 const size_t col = jac_subset.col()[k];
+
714 const double value = jac_subset.val()[k];
715
-
716 CppAD::sparse_rc<std::vector<size_t>> CppAD_sparsity_pattern(num_rows_jac, num_cols_jac, nnz);
-
717 for (size_t k = 0; k < nnz; ++k) {
-
718 CppAD_sparsity_pattern.set(k, sparsityPattern[k].first, sparsityPattern[k].second);
+
716 if (std::abs(value) > MIN_JACOBIAN_THRESHOLD) {
+
717 m_jacobianMatrix(row, col) = value; // Insert into the sparse matrix
+
718 }
719 }
-
720
-
721 CppAD::sparse_rcv<std::vector<size_t>, std::vector<double>> jac_subset(CppAD_sparsity_pattern);
-
722
-
723 m_rhsADFun.sparse_jac_rev(
-
724 x,
-
725 jac_subset, // Sparse Jacobian output
- -
727 "cppad",
-
728 m_jac_work // Work vector for CppAD
-
729 );
-
730
-
731 // --- Convert the sparse Jacobian back to the Boost uBLAS format ---
-
732 m_jacobianMatrix.clear();
-
733 for (size_t k = 0; k < nnz; ++k) {
-
734 const size_t row = jac_subset.row()[k];
-
735 const size_t col = jac_subset.col()[k];
-
736 const double value = jac_subset.val()[k];
-
737
-
738 if (std::abs(value) > MIN_JACOBIAN_THRESHOLD) {
-
739 m_jacobianMatrix(row, col) = value; // Insert into the sparse matrix
-
740 }
-
741 }
-
742 }
+
720 }
-
743
-
-
744 double GraphEngine::getJacobianMatrixEntry(const int i, const int j) const {
-
745 // LOG_TRACE_L3(m_logger, "Getting jacobian matrix entry for {},{} = {}", i, j, m_jacobianMatrix(i, j));
-
746 return m_jacobianMatrix(i, j);
-
747 }
+
721
+
+
722 double GraphEngine::getJacobianMatrixEntry(const int i, const int j) const {
+
723 // LOG_TRACE_L3(m_logger, "Getting jacobian matrix entry for {},{} = {}", i, j, m_jacobianMatrix(i, j));
+
724 return m_jacobianMatrix(i, j);
+
725 }
-
748
-
-
749 std::unordered_map<fourdst::atomic::Species, int> GraphEngine::getNetReactionStoichiometry(
- -
751 ) {
-
752 return reaction.stoichiometry();
-
753 }
+
726
+
+
727 std::unordered_map<fourdst::atomic::Species, int> GraphEngine::getNetReactionStoichiometry(
+ +
729 ) {
+
730 return reaction.stoichiometry();
+
731 }
+
732
+
+ +
734 const int speciesIndex,
+
735 const int reactionIndex
+
736 ) const {
+
737 return m_stoichiometryMatrix(speciesIndex, reactionIndex);
+
738 }
+
+
739
+
+
740 void GraphEngine::exportToDot(const std::string &filename) const {
+
741 LOG_TRACE_L1(m_logger, "Exporting network graph to DOT file: {}", filename);
+
742
+
743 std::ofstream dotFile(filename);
+
744 if (!dotFile.is_open()) {
+
745 LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
+
746 m_logger->flush_log();
+
747 throw std::runtime_error("Failed to open file for writing: " + filename);
+
748 }
+
749
+
750 dotFile << "digraph NuclearReactionNetwork {\n";
+
751 dotFile << " graph [rankdir=LR, splines=true, overlap=false, bgcolor=\"#f0f0f0\"];\n";
+
752 dotFile << " node [shape=circle, style=filled, fillcolor=\"#a7c7e7\", fontname=\"Helvetica\"];\n";
+
753 dotFile << " edge [fontname=\"Helvetica\", fontsize=10];\n\n";
754
-
- -
756 const int speciesIndex,
-
757 const int reactionIndex
-
758 ) const {
-
759 return m_stoichiometryMatrix(speciesIndex, reactionIndex);
-
760 }
-
+
755 // 1. Define all species as nodes
+
756 dotFile << " // --- Species Nodes ---\n";
+
757 for (const auto& species : m_networkSpecies) {
+
758 dotFile << " \"" << species.name() << "\" [label=\"" << species.name() << "\"];\n";
+
759 }
+
760 dotFile << "\n";
761
-
-
762 void GraphEngine::exportToDot(const std::string &filename) const {
-
763 LOG_TRACE_L1(m_logger, "Exporting network graph to DOT file: {}", filename);
-
764
-
765 std::ofstream dotFile(filename);
-
766 if (!dotFile.is_open()) {
-
767 LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
-
768 m_logger->flush_log();
-
769 throw std::runtime_error("Failed to open file for writing: " + filename);
-
770 }
-
771
-
772 dotFile << "digraph NuclearReactionNetwork {\n";
-
773 dotFile << " graph [rankdir=LR, splines=true, overlap=false, bgcolor=\"#f0f0f0\"];\n";
-
774 dotFile << " node [shape=circle, style=filled, fillcolor=\"#a7c7e7\", fontname=\"Helvetica\"];\n";
-
775 dotFile << " edge [fontname=\"Helvetica\", fontsize=10];\n\n";
-
776
-
777 // 1. Define all species as nodes
-
778 dotFile << " // --- Species Nodes ---\n";
-
779 for (const auto& species : m_networkSpecies) {
-
780 dotFile << " \"" << species.name() << "\" [label=\"" << species.name() << "\"];\n";
+
762 // 2. Define all reactions as intermediate nodes and connect them
+
763 dotFile << " // --- Reaction Edges ---\n";
+
764 for (const auto& reaction : m_reactions) {
+
765 // Create a unique ID for the reaction node
+
766 std::string reactionNodeId = "reaction_" + std::string(reaction.id());
+
767
+
768 // Define the reaction node (small, black dot)
+
769 dotFile << " \"" << reactionNodeId << "\" [shape=point, fillcolor=black, width=0.1, height=0.1, label=\"\"];\n";
+
770
+
771 // Draw edges from reactants to the reaction node
+
772 for (const auto& reactant : reaction.reactants()) {
+
773 dotFile << " \"" << reactant.name() << "\" -> \"" << reactionNodeId << "\";\n";
+
774 }
+
775
+
776 // Draw edges from the reaction node to products
+
777 for (const auto& product : reaction.products()) {
+
778 dotFile << " \"" << reactionNodeId << "\" -> \"" << product.name() << "\" [label=\"" << reaction.qValue() << " MeV\"];\n";
+
779 }
+
780 dotFile << "\n";
781 }
-
782 dotFile << "\n";
-
783
-
784 // 2. Define all reactions as intermediate nodes and connect them
-
785 dotFile << " // --- Reaction Edges ---\n";
-
786 for (const auto& reaction : m_reactions) {
-
787 // Create a unique ID for the reaction node
-
788 std::string reactionNodeId = "reaction_" + std::string(reaction.id());
-
789
-
790 // Define the reaction node (small, black dot)
-
791 dotFile << " \"" << reactionNodeId << "\" [shape=point, fillcolor=black, width=0.1, height=0.1, label=\"\"];\n";
-
792
-
793 // Draw edges from reactants to the reaction node
-
794 for (const auto& reactant : reaction.reactants()) {
-
795 dotFile << " \"" << reactant.name() << "\" -> \"" << reactionNodeId << "\";\n";
-
796 }
-
797
-
798 // Draw edges from the reaction node to products
-
799 for (const auto& product : reaction.products()) {
-
800 dotFile << " \"" << reactionNodeId << "\" -> \"" << product.name() << "\" [label=\"" << reaction.qValue() << " MeV\"];\n";
-
801 }
-
802 dotFile << "\n";
-
803 }
-
804
-
805 dotFile << "}\n";
-
806 dotFile.close();
-
807 LOG_TRACE_L1(m_logger, "Successfully exported network to {}", filename);
-
808 }
+
782
+
783 dotFile << "}\n";
+
784 dotFile.close();
+
785 LOG_TRACE_L1(m_logger, "Successfully exported network to {}", filename);
+
786 }
-
809
-
-
810 void GraphEngine::exportToCSV(const std::string &filename) const {
-
811 LOG_TRACE_L1(m_logger, "Exporting network graph to CSV file: {}", filename);
-
812
-
813 std::ofstream csvFile(filename, std::ios::out | std::ios::trunc);
-
814 if (!csvFile.is_open()) {
-
815 LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
-
816 m_logger->flush_log();
-
817 throw std::runtime_error("Failed to open file for writing: " + filename);
-
818 }
-
819 csvFile << "Reaction;Reactants;Products;Q-value;sources;rates\n";
-
820 for (const auto& reaction : m_reactions) {
-
821 // Dynamic cast to REACLIBReaction to access specific properties
-
822 csvFile << reaction.id() << ";";
-
823 // Reactants
-
824 size_t count = 0;
-
825 for (const auto& reactant : reaction.reactants()) {
-
826 csvFile << reactant.name();
-
827 if (++count < reaction.reactants().size()) {
-
828 csvFile << ",";
-
829 }
-
830 }
-
831 csvFile << ";";
-
832 count = 0;
-
833 for (const auto& product : reaction.products()) {
-
834 csvFile << product.name();
-
835 if (++count < reaction.products().size()) {
-
836 csvFile << ",";
-
837 }
-
838 }
-
839 csvFile << ";" << reaction.qValue() << ";";
-
840 // Reaction coefficients
-
841 auto sources = reaction.sources();
-
842 count = 0;
-
843 for (const auto& source : sources) {
-
844 csvFile << source;
-
845 if (++count < sources.size()) {
-
846 csvFile << ",";
-
847 }
-
848 }
-
849 csvFile << ";";
-
850 // Reaction coefficients
-
851 count = 0;
-
852 for (const auto& rates : reaction) {
-
853 csvFile << rates;
-
854 if (++count < reaction.size()) {
-
855 csvFile << ",";
-
856 }
-
857 }
-
858 csvFile << "\n";
-
859 }
-
860 csvFile.close();
-
861 LOG_TRACE_L1(m_logger, "Successfully exported network graph to {}", filename);
-
862 }
+
787
+
+
788 void GraphEngine::exportToCSV(const std::string &filename) const {
+
789 LOG_TRACE_L1(m_logger, "Exporting network graph to CSV file: {}", filename);
+
790
+
791 std::ofstream csvFile(filename, std::ios::out | std::ios::trunc);
+
792 if (!csvFile.is_open()) {
+
793 LOG_ERROR(m_logger, "Failed to open file for writing: {}", filename);
+
794 m_logger->flush_log();
+
795 throw std::runtime_error("Failed to open file for writing: " + filename);
+
796 }
+
797 csvFile << "Reaction;Reactants;Products;Q-value;sources;rates\n";
+
798 for (const auto& reaction : m_reactions) {
+
799 // Dynamic cast to REACLIBReaction to access specific properties
+
800 csvFile << reaction.id() << ";";
+
801 // Reactants
+
802 size_t count = 0;
+
803 for (const auto& reactant : reaction.reactants()) {
+
804 csvFile << reactant.name();
+
805 if (++count < reaction.reactants().size()) {
+
806 csvFile << ",";
+
807 }
+
808 }
+
809 csvFile << ";";
+
810 count = 0;
+
811 for (const auto& product : reaction.products()) {
+
812 csvFile << product.name();
+
813 if (++count < reaction.products().size()) {
+
814 csvFile << ",";
+
815 }
+
816 }
+
817 csvFile << ";" << reaction.qValue() << ";";
+
818 // Reaction coefficients
+
819 auto sources = reaction.sources();
+
820 count = 0;
+
821 for (const auto& source : sources) {
+
822 csvFile << source;
+
823 if (++count < sources.size()) {
+
824 csvFile << ",";
+
825 }
+
826 }
+
827 csvFile << ";";
+
828 // Reaction coefficients
+
829 count = 0;
+
830 for (const auto& rates : reaction) {
+
831 csvFile << rates;
+
832 if (++count < reaction.size()) {
+
833 csvFile << ",";
+
834 }
+
835 }
+
836 csvFile << "\n";
+
837 }
+
838 csvFile.close();
+
839 LOG_TRACE_L1(m_logger, "Successfully exported network graph to {}", filename);
+
840 }
-
863
-
-
864 std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> GraphEngine::getSpeciesTimescales(
-
865 const std::vector<double> &Y,
-
866 const double T9,
-
867 const double rho
-
868 ) const {
-
869 auto [dydt, _] = calculateAllDerivatives<double>(Y, T9, rho);
-
870 std::unordered_map<fourdst::atomic::Species, double> speciesTimescales;
-
871 speciesTimescales.reserve(m_networkSpecies.size());
-
872 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
-
873 double timescale = std::numeric_limits<double>::infinity();
-
874 const auto species = m_networkSpecies[i];
-
875 if (std::abs(dydt[i]) > 0.0) {
-
876 timescale = std::abs(Y[i] / dydt[i]);
-
877 }
-
878 speciesTimescales.emplace(species, timescale);
-
879 }
-
880 return speciesTimescales;
-
881 }
+
841
+
+
842 std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> GraphEngine::getSpeciesTimescales(
+
843 const std::vector<double> &Y,
+
844 const double T9,
+
845 const double rho
+
846 ) const {
+
847 auto [dydt, _] = calculateAllDerivatives<double>(Y, T9, rho);
+
848 std::unordered_map<fourdst::atomic::Species, double> speciesTimescales;
+
849 speciesTimescales.reserve(m_networkSpecies.size());
+
850 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
+
851 double timescale = std::numeric_limits<double>::infinity();
+
852 const auto species = m_networkSpecies[i];
+
853 if (std::abs(dydt[i]) > 0.0) {
+
854 timescale = std::abs(Y[i] / dydt[i]);
+
855 }
+
856 speciesTimescales.emplace(species, timescale);
+
857 }
+
858 return speciesTimescales;
+
859 }
-
882
-
-
883 std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> GraphEngine::getSpeciesDestructionTimescales(
-
884 const std::vector<double> &Y,
-
885 const double T9,
-
886 const double rho
-
887 ) const {
-
888 auto [dydt, _] = calculateAllDerivatives<double>(Y, T9, rho);
-
889 std::unordered_map<fourdst::atomic::Species, double> speciesDestructionTimescales;
-
890 speciesDestructionTimescales.reserve(m_networkSpecies.size());
-
891 for (const auto& species : m_networkSpecies) {
-
892 double netDestructionFlow = 0.0;
-
893 for (const auto& reaction : m_reactions) {
-
894 if (reaction.stoichiometry(species) < 0) {
-
895 const double flow = calculateMolarReactionFlow<double>(reaction, Y, T9, rho);
-
896 netDestructionFlow += flow;
-
897 }
-
898 }
-
899 double timescale = std::numeric_limits<double>::infinity();
-
900 if (netDestructionFlow != 0.0) {
-
901 timescale = Y[getSpeciesIndex(species)] / netDestructionFlow;
-
902 }
-
903 speciesDestructionTimescales.emplace(species, timescale);
-
904 }
-
905 return speciesDestructionTimescales;
-
906 }
+
860
+
+
861 std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> GraphEngine::getSpeciesDestructionTimescales(
+
862 const std::vector<double> &Y,
+
863 const double T9,
+
864 const double rho
+
865 ) const {
+
866 auto [dydt, _] = calculateAllDerivatives<double>(Y, T9, rho);
+
867 std::unordered_map<fourdst::atomic::Species, double> speciesDestructionTimescales;
+
868 speciesDestructionTimescales.reserve(m_networkSpecies.size());
+
869 for (const auto& species : m_networkSpecies) {
+
870 double netDestructionFlow = 0.0;
+
871 for (const auto& reaction : m_reactions) {
+
872 if (reaction.stoichiometry(species) < 0) {
+
873 const double flow = calculateMolarReactionFlow<double>(reaction, Y, T9, rho);
+
874 netDestructionFlow += flow;
+
875 }
+
876 }
+
877 double timescale = std::numeric_limits<double>::infinity();
+
878 if (netDestructionFlow != 0.0) {
+
879 timescale = Y[getSpeciesIndex(species)] / netDestructionFlow;
+
880 }
+
881 speciesDestructionTimescales.emplace(species, timescale);
+
882 }
+
883 return speciesDestructionTimescales;
+
884 }
-
907
-
-
908 fourdst::composition::Composition GraphEngine::update(const NetIn &netIn) {
-
909 fourdst::composition::Composition baseUpdatedComposition = netIn.composition;
-
910 for (const auto& species : m_networkSpecies) {
-
911 if (!netIn.composition.contains(species)) {
-
912 baseUpdatedComposition.registerSpecies(species);
-
913 baseUpdatedComposition.setMassFraction(species, 0.0);
-
914 }
-
915 }
-
916 baseUpdatedComposition.finalize(false);
-
917 return baseUpdatedComposition;
-
918 }
+
885
+
+
886 fourdst::composition::Composition GraphEngine::update(const NetIn &netIn) {
+
887 fourdst::composition::Composition baseUpdatedComposition = netIn.composition;
+
888 for (const auto& species : m_networkSpecies) {
+
889 if (!netIn.composition.contains(species)) {
+
890 baseUpdatedComposition.registerSpecies(species);
+
891 baseUpdatedComposition.setMassFraction(species, 0.0);
+
892 }
+
893 }
+
894 baseUpdatedComposition.finalize(false);
+
895 return baseUpdatedComposition;
+
896 }
-
919
-
-
920 bool GraphEngine::isStale(const NetIn &netIn) {
-
921 return false;
-
922 }
+
897
+
+
898 bool GraphEngine::isStale(const NetIn &netIn) {
+
899 return false;
+
900 }
-
923
-
- -
925 LOG_TRACE_L1(m_logger, "Recording AD tape for the RHS calculation...");
-
926
-
927 // Task 1: Set dimensions and initialize the matrix
-
928 const size_t numSpecies = m_networkSpecies.size();
-
929 if (numSpecies == 0) {
-
930 LOG_ERROR(m_logger, "Cannot record AD tape: No species in the network.");
-
931 m_logger->flush_log();
-
932 throw std::runtime_error("Cannot record AD tape: No species in the network.");
-
933 }
-
934 const size_t numADInputs = numSpecies + 2; // Note here that by not letting T9 and rho be independent variables, we are constraining the network to a constant temperature and density during each evaluation.
+
901
+
+ +
903 LOG_TRACE_L1(m_logger, "Recording AD tape for the RHS calculation...");
+
904
+
905 // Task 1: Set dimensions and initialize the matrix
+
906 const size_t numSpecies = m_networkSpecies.size();
+
907 if (numSpecies == 0) {
+
908 LOG_ERROR(m_logger, "Cannot record AD tape: No species in the network.");
+
909 m_logger->flush_log();
+
910 throw std::runtime_error("Cannot record AD tape: No species in the network.");
+
911 }
+
912 const size_t numADInputs = numSpecies + 2; // Note here that by not letting T9 and rho be independent variables, we are constraining the network to a constant temperature and density during each evaluation.
+
913
+
914 // --- CppAD Tape Recording ---
+
915 // 1. Declare independent variable (adY)
+
916 // We also initialize the dummy variable for tape recording (these tell CppAD what the derivative chain looks like).
+
917 // Their numeric values are irrelevant except for in so far as they avoid numerical instabilities.
+
918
+
919 // Distribute total mass fraction uniformly between species in the dummy variable space
+
920 const auto uniformMassFraction = static_cast<CppAD::AD<double>>(1.0 / static_cast<double>(numSpecies));
+
921 std::vector<CppAD::AD<double>> adInput(numADInputs, uniformMassFraction);
+
922 adInput[numSpecies] = 1.0; // Dummy T9
+
923 adInput[numSpecies + 1] = 1.0; // Dummy rho
+
924
+
925 // 3. Declare independent variables (what CppAD will differentiate wrt.)
+
926 // This also beings the tape recording process.
+
927 CppAD::Independent(adInput);
+
928
+
929 std::vector<CppAD::AD<double>> adY(numSpecies);
+
930 for(size_t i = 0; i < numSpecies; ++i) {
+
931 adY[i] = adInput[i];
+
932 }
+
933 const CppAD::AD<double> adT9 = adInput[numSpecies];
+
934 const CppAD::AD<double> adRho = adInput[numSpecies + 1];
935
-
936 // --- CppAD Tape Recording ---
-
937 // 1. Declare independent variable (adY)
-
938 // We also initialize the dummy variable for tape recording (these tell CppAD what the derivative chain looks like).
-
939 // Their numeric values are irrelevant except for in so far as they avoid numerical instabilities.
+
936
+
937 // 5. Call the actual templated function
+
938 // We let T9 and rho be constant, so we pass them as fixed values.
+
939 auto [dydt, nuclearEnergyGenerationRate] = calculateAllDerivatives<CppAD::AD<double>>(adY, adT9, adRho);
940
-
941 // Distribute total mass fraction uniformly between species in the dummy variable space
-
942 const auto uniformMassFraction = static_cast<CppAD::AD<double>>(1.0 / static_cast<double>(numSpecies));
-
943 std::vector<CppAD::AD<double>> adInput(numADInputs, uniformMassFraction);
-
944 adInput[numSpecies] = 1.0; // Dummy T9
-
945 adInput[numSpecies + 1] = 1.0; // Dummy rho
+
941 m_rhsADFun.Dependent(adInput, dydt);
+
942
+
943 LOG_TRACE_L1(m_logger, "AD tape recorded successfully for the RHS calculation. Number of independent variables: {}.",
+
944 adInput.size());
+
945 }
+
946
-
947 // 3. Declare independent variables (what CppAD will differentiate wrt.)
-
948 // This also beings the tape recording process.
-
949 CppAD::Independent(adInput);
+
+ +
948 m_atomicReverseRates.clear();
+
949 m_atomicReverseRates.reserve(m_reactions.size());
950
-
951 std::vector<CppAD::AD<double>> adY(numSpecies);
-
952 for(size_t i = 0; i < numSpecies; ++i) {
-
953 adY[i] = adInput[i];
-
954 }
-
955 const CppAD::AD<double> adT9 = adInput[numSpecies];
-
956 const CppAD::AD<double> adRho = adInput[numSpecies + 1];
-
957
-
958
-
959 // 5. Call the actual templated function
-
960 // We let T9 and rho be constant, so we pass them as fixed values.
-
961 auto [dydt, nuclearEnergyGenerationRate] = calculateAllDerivatives<CppAD::AD<double>>(adY, adT9, adRho);
+
951 for (const auto& reaction: m_reactions) {
+
952 if (reaction.qValue() != 0.0) {
+
953 m_atomicReverseRates.push_back(std::make_unique<AtomicReverseRate>(reaction, *this));
+
954 } else {
+
955 m_atomicReverseRates.push_back(nullptr);
+
956 }
+
957 }
+
958 }
+
+
959
+
+ +
961 LOG_TRACE_L1(m_logger, "Pre-computing constant components of GraphNetwork state...");
962
-
963 m_rhsADFun.Dependent(adInput, dydt);
-
964
-
965 LOG_TRACE_L1(m_logger, "AD tape recorded successfully for the RHS calculation. Number of independent variables: {}.",
-
966 adInput.size());
-
967 }
-
+
963 // --- Reverse map for fast species lookups ---
+
964 std::unordered_map<fourdst::atomic::Species, size_t> speciesIndexMap;
+
965 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
+
966 speciesIndexMap[m_networkSpecies[i]] = i;
+
967 }
968
-
- -
970 m_atomicReverseRates.clear();
-
971 m_atomicReverseRates.reserve(m_reactions.size());
-
972
-
973 for (const auto& reaction: m_reactions) {
-
974 if (reaction.qValue() != 0.0) {
-
975 m_atomicReverseRates.push_back(std::make_unique<AtomicReverseRate>(reaction, *this));
-
976 } else {
-
977 m_atomicReverseRates.push_back(nullptr);
-
978 }
-
979 }
-
980 }
-
-
981
-
- -
983 LOG_TRACE_L1(m_logger, "Pre-computing constant components of GraphNetwork state...");
+ +
970 m_precomputedReactions.reserve(m_reactions.size());
+
971
+
972 for (size_t i = 0; i < m_reactions.size(); ++i) {
+
973 const auto& reaction = m_reactions[i];
+
974 PrecomputedReaction precomp;
+
975 precomp.reaction_index = i;
+
976
+
977 // --- Precompute forward reaction information ---
+
978 // Count occurrences for each reactant to determine powers and symmetry
+
979 std::unordered_map<size_t, int> reactantCounts;
+
980 for (const auto& reactant: reaction.reactants()) {
+
981 size_t reactantIndex = speciesIndexMap.at(reactant);
+
982 reactantCounts[reactantIndex]++;
+
983 }
984
-
985 // --- Reverse map for fast species lookups ---
-
986 std::unordered_map<fourdst::atomic::Species, size_t> speciesIndexMap;
-
987 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
-
988 speciesIndexMap[m_networkSpecies[i]] = i;
-
989 }
-
990
- -
992 m_precomputedReactions.reserve(m_reactions.size());
-
993
-
994 for (size_t i = 0; i < m_reactions.size(); ++i) {
-
995 const auto& reaction = m_reactions[i];
-
996 PrecomputedReaction precomp;
-
997 precomp.reaction_index = i;
-
998
-
999 // --- Precompute forward reaction information ---
-
1000 // Count occurrences for each reactant to determine powers and symmetry
-
1001 std::unordered_map<size_t, int> reactantCounts;
-
1002 for (const auto& reactant: reaction.reactants()) {
-
1003 size_t reactantIndex = speciesIndexMap.at(reactant);
-
1004 reactantCounts[reactantIndex]++;
-
1005 }
-
1006
-
1007 double symmetryDenominator = 1.0;
-
1008 for (const auto& [index, count] : reactantCounts) {
-
1009 precomp.unique_reactant_indices.push_back(index);
-
1010 precomp.reactant_powers.push_back(count);
-
1011
-
1012 symmetryDenominator *= std::tgamma(count + 1);
+
985 double symmetryDenominator = 1.0;
+
986 for (const auto& [index, count] : reactantCounts) {
+
987 precomp.unique_reactant_indices.push_back(index);
+
988 precomp.reactant_powers.push_back(count);
+
989
+
990 symmetryDenominator *= std::tgamma(count + 1);
+
991 }
+
992
+
993 precomp.symmetry_factor = 1.0/symmetryDenominator;
+
994
+
995 // --- Precompute reverse reaction information ---
+
996 if (reaction.qValue() != 0.0) {
+
997 std::unordered_map<size_t, int> productCounts;
+
998 for (const auto& product : reaction.products()) {
+
999 productCounts[speciesIndexMap.at(product)]++;
+
1000 }
+
1001 double reverseSymmetryDenominator = 1.0;
+
1002 for (const auto& [index, count] : productCounts) {
+
1003 precomp.unique_product_indices.push_back(index);
+
1004 precomp.product_powers.push_back(count);
+
1005 reverseSymmetryDenominator *= std::tgamma(count + 1);
+
1006 }
+
1007
+
1008 precomp.reverse_symmetry_factor = 1.0/reverseSymmetryDenominator;
+
1009 } else {
+
1010 precomp.unique_product_indices.clear();
+
1011 precomp.product_powers.clear();
+
1012 precomp.reverse_symmetry_factor = 0.0; // No reverse reaction for Q = 0 reactions
1013 }
1014
-
1015 precomp.symmetry_factor = 1.0/symmetryDenominator;
-
1016
-
1017 // --- Precompute reverse reaction information ---
-
1018 if (reaction.qValue() != 0.0) {
-
1019 std::unordered_map<size_t, int> productCounts;
-
1020 for (const auto& product : reaction.products()) {
-
1021 productCounts[speciesIndexMap.at(product)]++;
-
1022 }
-
1023 double reverseSymmetryDenominator = 1.0;
-
1024 for (const auto& [index, count] : productCounts) {
-
1025 precomp.unique_product_indices.push_back(index);
-
1026 precomp.product_powers.push_back(count);
-
1027 reverseSymmetryDenominator *= std::tgamma(count + 1);
-
1028 }
-
1029
-
1030 precomp.reverse_symmetry_factor = 1.0/reverseSymmetryDenominator;
-
1031 } else {
-
1032 precomp.unique_product_indices.clear();
-
1033 precomp.product_powers.clear();
-
1034 precomp.reverse_symmetry_factor = 0.0; // No reverse reaction for Q = 0 reactions
-
1035 }
-
1036
-
1037 // --- Precompute stoichiometry information ---
-
1038 const auto stoichiometryMap = reaction.stoichiometry();
-
1039 precomp.affected_species_indices.reserve(stoichiometryMap.size());
-
1040 precomp.stoichiometric_coefficients.reserve(stoichiometryMap.size());
-
1041
-
1042 for (const auto& [species, coeff] : stoichiometryMap) {
-
1043 precomp.affected_species_indices.push_back(speciesIndexMap.at(species));
-
1044 precomp.stoichiometric_coefficients.push_back(coeff);
-
1045 }
-
1046
-
1047 m_precomputedReactions.push_back(std::move(precomp));
-
1048 }
+
1015 // --- Precompute stoichiometry information ---
+
1016 const auto stoichiometryMap = reaction.stoichiometry();
+
1017 precomp.affected_species_indices.reserve(stoichiometryMap.size());
+
1018 precomp.stoichiometric_coefficients.reserve(stoichiometryMap.size());
+
1019
+
1020 for (const auto& [species, coeff] : stoichiometryMap) {
+
1021 precomp.affected_species_indices.push_back(speciesIndexMap.at(species));
+
1022 precomp.stoichiometric_coefficients.push_back(coeff);
+
1023 }
+
1024
+
1025 m_precomputedReactions.push_back(std::move(precomp));
+
1026 }
+
1027 }
+
+
1028
+
+ +
1030 const size_t p,
+
1031 const size_t q,
+
1032 const CppAD::vector<bool> &vx,
+
1033 CppAD::vector<bool> &vy,
+
1034 const CppAD::vector<double> &tx,
+
1035 CppAD::vector<double> &ty
+
1036 ) {
+
1037
+
1038 if ( p != 0) { return false; }
+
1039 const double T9 = tx[0];
+
1040
+
1041 const double reverseRate = m_engine.calculateReverseRate(m_reaction, T9);
+
1042 // std::cout << m_reaction.peName() << " reverseRate: " << reverseRate << " at T9: " << T9 << "\n";
+
1043 ty[0] = reverseRate; // Store the reverse rate in the output vector
+
1044
+
1045 if (vx.size() > 0) {
+
1046 vy[0] = vx[0];
+
1047 }
+
1048 return true;
1049 }
1050
- -
1052 const size_t p,
-
1053 const size_t q,
-
1054 const CppAD::vector<bool> &vx,
-
1055 CppAD::vector<bool> &vy,
-
1056 const CppAD::vector<double> &tx,
-
1057 CppAD::vector<double> &ty
-
1058 ) {
-
1059
-
1060 if ( p != 0) { return false; }
-
1061 const double T9 = tx[0];
-
1062
-
1063 const double reverseRate = m_engine.calculateReverseRate(m_reaction, T9);
-
1064 // std::cout << m_reaction.peName() << " reverseRate: " << reverseRate << " at T9: " << T9 << "\n";
-
1065 ty[0] = reverseRate; // Store the reverse rate in the output vector
-
1066
-
1067 if (vx.size() > 0) {
-
1068 vy[0] = vx[0];
-
1069 }
-
1070 return true;
-
1071 }
+ +
1052 size_t q,
+
1053 const CppAD::vector<double> &tx,
+
1054 const CppAD::vector<double> &ty,
+
1055 CppAD::vector<double> &px,
+
1056 const CppAD::vector<double> &py
+
1057 ) {
+
1058 const double T9 = tx[0];
+
1059 const double reverseRate = ty[0];
+
1060
+
1061 const double derivative = m_engine.calculateReverseRateTwoBodyDerivative(m_reaction, T9, reverseRate);
+
1062 // std::cout << m_reaction.peName() << " reverseRate Derivative: " << derivative << "\n";
+
1063
+
1064 px[0] = py[0] * derivative; // Return the derivative of the reverse rate with respect to T9
+
1065
+
1066 return true;
+
1067 }
-
1072
-
- -
1074 size_t q,
-
1075 const CppAD::vector<double> &tx,
-
1076 const CppAD::vector<double> &ty,
-
1077 CppAD::vector<double> &px,
-
1078 const CppAD::vector<double> &py
-
1079 ) {
-
1080 const double T9 = tx[0];
-
1081 const double reverseRate = ty[0];
-
1082
-
1083 const double derivative = m_engine.calculateReverseRateTwoBodyDerivative(m_reaction, T9, reverseRate);
-
1084 // std::cout << m_reaction.peName() << " reverseRate Derivative: " << derivative << "\n";
-
1085
-
1086 px[0] = py[0] * derivative; // Return the derivative of the reverse rate with respect to T9
-
1087
-
1088 return true;
-
1089 }
+
1068
+
+ +
1070 size_t q,
+
1071 const CppAD::vector<std::set<size_t>> &r,
+
1072 CppAD::vector<std::set<size_t>> &s
+
1073 ) {
+
1074 s[0] = r[0];
+
1075 return true;
+
1076 }
-
1090
-
- -
1092 size_t q,
-
1093 const CppAD::vector<std::set<size_t>> &r,
-
1094 CppAD::vector<std::set<size_t>> &s
-
1095 ) {
-
1096 s[0] = r[0];
-
1097 return true;
-
1098 }
+
1077
+
+ +
1079 size_t q,
+
1080 const CppAD::vector<std::set<size_t>> &rt,
+
1081 CppAD::vector<std::set<size_t>> &st
+
1082 ) {
+
1083 st[0] = rt[0];
+
1084 return true;
+
1085 }
-
1099
-
- -
1101 size_t q,
-
1102 const CppAD::vector<std::set<size_t>> &rt,
-
1103 CppAD::vector<std::set<size_t>> &st
-
1104 ) {
-
1105 st[0] = rt[0];
-
1106 return true;
-
1107 }
-
-
1108}
-
bool reverse(size_t q, const CppAD::vector< double > &tx, const CppAD::vector< double > &ty, CppAD::vector< double > &px, const CppAD::vector< double > &py) override
- -
bool rev_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &rt, CppAD::vector< std::set< size_t > > &st) override
-
const reaction::Reaction & m_reaction
-
bool forward(size_t p, size_t q, const CppAD::vector< bool > &vx, CppAD::vector< bool > &vy, const CppAD::vector< double > &tx, CppAD::vector< double > &ty) override
-
bool for_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &r, CppAD::vector< std::set< size_t > > &s) override
-
bool isPrecomputationEnabled() const
-
double calculateReverseRateTwoBody(const reaction::Reaction &reaction, const double T9, const double forwardRate, const double expFactor) const
-
double calculateReverseRate(const reaction::Reaction &reaction, double T9) const
+
1086}
+
bool reverse(size_t q, const CppAD::vector< double > &tx, const CppAD::vector< double > &ty, CppAD::vector< double > &px, const CppAD::vector< double > &py) override
+ +
bool rev_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &rt, CppAD::vector< std::set< size_t > > &st) override
+
const reaction::Reaction & m_reaction
+
bool forward(size_t p, size_t q, const CppAD::vector< bool > &vx, CppAD::vector< bool > &vy, const CppAD::vector< double > &tx, CppAD::vector< double > &ty) override
+
bool for_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &r, CppAD::vector< std::set< size_t > > &s) override
+
bool isPrecomputationEnabled() const
+
double calculateReverseRateTwoBody(const reaction::Reaction &reaction, const double T9, const double forwardRate, const double expFactor) const
+
double calculateReverseRate(const reaction::Reaction &reaction, double T9) const
const std::vector< fourdst::atomic::Species > & getNetworkSpecies() const override
Gets the list of species in the network.
- -
BuildDepthType getDepth() const override
-
bool m_usePrecomputation
Flag to enable or disable using precomputed reactions for efficiency. Mathematically,...
-
CppAD::sparse_rc< std::vector< size_t > > m_full_jacobian_sparsity_pattern
Full sparsity pattern for the Jacobian matrix.
-
CppAD::sparse_jac_work m_jac_work
Work object for sparse Jacobian calculations.
+ +
BuildDepthType getDepth() const override
+
bool m_usePrecomputation
Flag to enable or disable using precomputed reactions for efficiency. Mathematically,...
+
CppAD::sparse_rc< std::vector< size_t > > m_full_jacobian_sparsity_pattern
Full sparsity pattern for the Jacobian matrix.
+
CppAD::sparse_jac_work m_jac_work
Work object for sparse Jacobian calculations.
void populateReactionIDMap()
Populates the reaction ID map.
-
std::vector< double > mapNetInToMolarAbundanceVector(const NetIn &netIn) const override
-
void collectAtomicReverseRateAtomicBases()
-
CppAD::ADFun< double > m_rhsADFun
CppAD function for the right-hand side of the ODE.
-
boost::numeric::ublas::compressed_matrix< double > m_jacobianMatrix
Jacobian matrix (species x species).
-
double getJacobianMatrixEntry(const int i, const int j) const override
Gets an entry from the previously generated Jacobian matrix.
-
std::unordered_map< std::string_view, fourdst::atomic::Species > m_networkSpeciesMap
Map from species name to Species object.
-
bool m_useReverseReactions
Flag to enable or disable reverse reactions. If false, only forward reactions are considered.
-
std::unique_ptr< partition::PartitionFunction > m_partitionFunction
Partition function for the network.
+
std::vector< double > mapNetInToMolarAbundanceVector(const NetIn &netIn) const override
+
void collectAtomicReverseRateAtomicBases()
+
CppAD::ADFun< double > m_rhsADFun
CppAD function for the right-hand side of the ODE.
+
boost::numeric::ublas::compressed_matrix< double > m_jacobianMatrix
Jacobian matrix (species x species).
+
double getJacobianMatrixEntry(const int i, const int j) const override
Gets an entry from the previously generated Jacobian matrix.
+
std::unordered_map< std::string_view, fourdst::atomic::Species > m_networkSpeciesMap
Map from species name to Species object.
+
bool m_useReverseReactions
Flag to enable or disable reverse reactions. If false, only forward reactions are considered.
+
std::unique_ptr< partition::PartitionFunction > m_partitionFunction
Partition function for the network.
void setNetworkReactions(const reaction::LogicalReactionSet &reactions) override
-
void setUseReverseReactions(bool useReverse)
+
void setUseReverseReactions(bool useReverse)
void populateSpeciesToIndexMap()
Populates the species-to-index map.
-
quill::Logger * m_logger
-
screening::ScreeningType m_screeningType
Screening type for the reaction network. Default to no screening.
-
fourdst::composition::Composition update(const NetIn &netIn) override
Update the internal state of the engine.
-
std::vector< PrecomputedReaction > m_precomputedReactions
Precomputed reactions for efficiency.
-
std::unordered_map< std::string_view, reaction::Reaction * > m_reactionIDMap
Map from reaction ID to REACLIBReaction. //PERF: This makes copies of REACLIBReaction and could be a ...
-
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesTimescales(const std::vector< double > &Y, double T9, double rho) const override
Computes timescales for all species in the network.
-
screening::ScreeningType getScreeningModel() const override
Get the current electron screening model.
-
int getStoichiometryMatrixEntry(const int speciesIndex, const int reactionIndex) const override
Gets an entry from the stoichiometry matrix.
-
void setPrecomputation(bool precompute)
-
BuildDepthType m_depth
-
void setScreeningModel(screening::ScreeningType) override
Set the electron screening model.
-
std::vector< std::unique_ptr< AtomicReverseRate > > m_atomicReverseRates
-
void exportToCSV(const std::string &filename) const
Exports the network to a CSV file for analysis.
-
static std::unordered_map< fourdst::atomic::Species, int > getNetReactionStoichiometry(const reaction::Reaction &reaction)
Gets the net stoichiometry for a given reaction.
+
quill::Logger * m_logger
+
screening::ScreeningType m_screeningType
Screening type for the reaction network. Default to no screening.
+
fourdst::composition::Composition update(const NetIn &netIn) override
Update the internal state of the engine.
+
std::vector< PrecomputedReaction > m_precomputedReactions
Precomputed reactions for efficiency.
+
std::unordered_map< std::string_view, reaction::Reaction * > m_reactionIDMap
Map from reaction ID to REACLIBReaction. //PERF: This makes copies of REACLIBReaction and could be a ...
+
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesTimescales(const std::vector< double > &Y, double T9, double rho) const override
Computes timescales for all species in the network.
+
screening::ScreeningType getScreeningModel() const override
Get the current electron screening model.
+
int getStoichiometryMatrixEntry(const int speciesIndex, const int reactionIndex) const override
Gets an entry from the stoichiometry matrix.
+
void setPrecomputation(bool precompute)
+
BuildDepthType m_depth
+
void setScreeningModel(screening::ScreeningType) override
Set the electron screening model.
+
std::vector< std::unique_ptr< AtomicReverseRate > > m_atomicReverseRates
+
void exportToCSV(const std::string &filename) const
Exports the network to a CSV file for analysis.
+
static std::unordered_map< fourdst::atomic::Species, int > getNetReactionStoichiometry(const reaction::Reaction &reaction)
Gets the net stoichiometry for a given reaction.
void reserveJacobianMatrix() const
Reserves space for the Jacobian matrix.
-
int getSpeciesIndex(const fourdst::atomic::Species &species) const override
-
double calculateMolarReactionFlow(const reaction::Reaction &reaction, const std::vector< double > &Y, const double T9, const double rho) const override
Calculates the molar reaction flow for a given reaction.
- -
std::vector< fourdst::atomic::Species > m_networkSpecies
Vector of unique species in the network.
-
void recordADTape()
Records the AD tape for the right-hand side of the ODE.
-
StepDerivatives< double > calculateAllDerivativesUsingPrecomputation(const std::vector< double > &Y_in, const std::vector< double > &bare_rates, const std::vector< double > &bare_reverse_rates, double T9, double rho) const
+
int getSpeciesIndex(const fourdst::atomic::Species &species) const override
+
double calculateMolarReactionFlow(const reaction::Reaction &reaction, const std::vector< double > &Y, const double T9, const double rho) const override
Calculates the molar reaction flow for a given reaction.
+ +
std::vector< fourdst::atomic::Species > m_networkSpecies
Vector of unique species in the network.
+
void recordADTape()
Records the AD tape for the right-hand side of the ODE.
+
StepDerivatives< double > calculateAllDerivativesUsingPrecomputation(const std::vector< double > &Y_in, const std::vector< double > &bare_rates, const std::vector< double > &bare_reverse_rates, double T9, double rho) const
bool involvesSpecies(const fourdst::atomic::Species &species) const
Checks if a given species is involved in the network.
std::expected< StepDerivatives< double >, expectations::StaleEngineError > calculateRHSAndEnergy(const std::vector< double > &Y, const double T9, const double rho) const override
Calculates the right-hand side (dY/dt) and energy generation rate.
-
reaction::LogicalReactionSet m_reactions
Set of REACLIB reactions in the network.
+
reaction::LogicalReactionSet m_reactions
Set of REACLIB reactions in the network.
void syncInternalMaps()
Synchronizes the internal maps.
bool validateConservation() const
Validates mass and charge conservation across all reactions.
-
void generateJacobianMatrix(const std::vector< double > &Y_dynamic, const double T9, const double rho) const override
Generates the Jacobian matrix for the current state.
-
boost::numeric::ublas::compressed_matrix< int > m_stoichiometryMatrix
Stoichiometry matrix (species x reactions).
+
void generateJacobianMatrix(const std::vector< double > &Y_dynamic, const double T9, const double rho) const override
Generates the Jacobian matrix for the current state.
+
boost::numeric::ublas::compressed_matrix< int > m_stoichiometryMatrix
Stoichiometry matrix (species x reactions).
const reaction::LogicalReactionSet & getNetworkReactions() const override
Gets the set of logical reactions in the network.
-
std::unordered_map< fourdst::atomic::Species, size_t > m_speciesToIndexMap
Map from species to their index in the stoichiometry matrix.
-
void rebuild(const fourdst::composition::Composition &comp, const BuildDepthType depth) override
-
void exportToDot(const std::string &filename) const
Exports the network to a DOT file for visualization.
-
const partition::PartitionFunction & getPartitionFunction() const
-
bool isUsingReverseReactions() const
-
PrimingReport primeEngine(const NetIn &netIn) override
-
void generateStoichiometryMatrix() override
Generates the stoichiometry matrix for the network.
+
std::unordered_map< fourdst::atomic::Species, size_t > m_speciesToIndexMap
Map from species to their index in the stoichiometry matrix.
+
void rebuild(const fourdst::composition::Composition &comp, const BuildDepthType depth) override
+
void exportToDot(const std::string &filename) const
Exports the network to a DOT file for visualization.
+
const partition::PartitionFunction & getPartitionFunction() const
+
bool isUsingReverseReactions() const
+
PrimingReport primeEngine(const NetIn &netIn) override
+
void generateStoichiometryMatrix() override
Generates the stoichiometry matrix for the network.
void collectNetworkSpecies()
Collects the unique species in the network.
-
void validateComposition(const fourdst::composition::Composition &composition, double culling, double T9)
Validates the composition against the current reaction set.
-
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesDestructionTimescales(const std::vector< double > &Y, double T9, double rho) const override
-
bool isStale(const NetIn &netIn) override
-
std::unique_ptr< screening::ScreeningModel > m_screeningModel
-
double calculateReverseRateTwoBodyDerivative(const reaction::Reaction &reaction, const double T9, const double reverseRate) const
-
StepDerivatives< T > calculateAllDerivatives(const std::vector< T > &Y_in, T T9, T rho) const
Calculates all derivatives (dY/dt) and the energy generation rate.
+
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesDestructionTimescales(const std::vector< double > &Y, double T9, double rho) const override
+
bool isStale(const NetIn &netIn) override
+
std::unique_ptr< screening::ScreeningModel > m_screeningModel
+
double calculateReverseRateTwoBodyDerivative(const reaction::Reaction &reaction, const double T9, const double reverseRate) const
+
StepDerivatives< T > calculateAllDerivatives(const std::vector< T > &Y_in, T T9, T rho) const
Calculates all derivatives (dY/dt) and the energy generation rate.
GraphEngine(const fourdst::composition::Composition &composition, const BuildDepthType=NetworkBuildDepth::Full)
Constructs a GraphEngine from a composition.
Abstract interface for evaluating nuclear partition functions.
Represents a single nuclear reaction from a specific data source.
Definition reaction.h:72
@@ -1397,28 +1372,27 @@ $(function(){initNavTree('engine__graph_8cpp_source.html',''); initResizable(tru
std::unique_ptr< ScreeningModel > selectScreeningModel(ScreeningType type)
A factory function to select and create a screening model.
ScreeningType
Enumerates the available plasma screening models.
-
CppAD::AD< double > ADDouble
Alias for CppAD AD type for double precision.
+
CppAD::AD< double > ADDouble
Alias for CppAD AD type for double precision.
std::variant< NetworkBuildDepth, int > BuildDepthType
Variant specifying either a predefined NetworkBuildDepth or a custom integer depth.
Definition building.h:37
std::vector< std::pair< size_t, size_t > > SparsityPattern
PrimingReport primeNetwork(const NetIn &, DynamicEngine &engine)
Primes absent species in the network to their equilibrium abundances.
Definition priming.cpp:39
-
static constexpr double MIN_JACOBIAN_THRESHOLD
Minimum value for Jacobian matrix entries.
+
static constexpr double MIN_JACOBIAN_THRESHOLD
Minimum value for Jacobian matrix entries.
reaction::LogicalReactionSet build_reaclib_nuclear_network(const fourdst::composition::Composition &composition, BuildDepthType maxLayers=NetworkBuildDepth::Full, bool reverse=false)
Builds a nuclear reaction network from the Reaclib library based on an initial composition.
-
static bool s_debug
Defines classes for representing and managing nuclear reactions.
- - -
std::vector< int > product_powers
Powers of each unique product in the reverse reaction.
- - -
double reverse_symmetry_factor
Symmetry factor for reverse reactions.
- - -
std::vector< size_t > unique_product_indices
Unique product indices for reverse reactions.
- + + +
std::vector< int > product_powers
Powers of each unique product in the reverse reaction.
+ + +
double reverse_symmetry_factor
Symmetry factor for reverse reactions.
+ + +
std::vector< size_t > unique_product_indices
Unique product indices for reverse reactions.
+
double density
Density in g/cm^3.
Definition network.h:58
fourdst::composition::Composition composition
Composition of the network.
Definition network.h:54
diff --git a/docs/html/engine__graph_8h.html b/docs/html/engine__graph_8h.html index bd754ee6..156efd9d 100644 --- a/docs/html/engine__graph_8h.html +++ b/docs/html/engine__graph_8h.html @@ -157,8 +157,6 @@ Typedefs - - diff --git a/docs/html/engine__graph_8h.js b/docs/html/engine__graph_8h.js index b5403d0c..652fe276 100644 --- a/docs/html/engine__graph_8h.js +++ b/docs/html/engine__graph_8h.js @@ -7,6 +7,5 @@ var engine__graph_8h = [ "gridfire::ADDouble", "namespacegridfire.html#a1121d0b2d005195333412559fa29d3cc", null ], [ "gridfire::MIN_ABUNDANCE_THRESHOLD", "namespacegridfire.html#a96c062f94713921e5d7568ecedcdcb06", null ], [ "gridfire::MIN_DENSITY_THRESHOLD", "namespacegridfire.html#ada3c137c014ecd8d06200fea2d1a9f50", null ], - [ "gridfire::MIN_JACOBIAN_THRESHOLD", "namespacegridfire.html#ae01b1738df1921db565bcbd68dd6cf64", null ], - [ "gridfire::s_debug", "namespacegridfire.html#afd6f117eb2da3bab3873edc09d0926cf", null ] + [ "gridfire::MIN_JACOBIAN_THRESHOLD", "namespacegridfire.html#ae01b1738df1921db565bcbd68dd6cf64", null ] ]; \ No newline at end of file diff --git a/docs/html/engine__graph_8h_source.html b/docs/html/engine__graph_8h_source.html index 967f320f..2d412b57 100644 --- a/docs/html/engine__graph_8h_source.html +++ b/docs/html/engine__graph_8h_source.html @@ -140,629 +140,609 @@ $(function(){initNavTree('engine__graph_8h_source.html',''); initResizable(true)
36// REACLIBReactions are quite large data structures, so this could be a performance bottleneck.
37// static bool isF17 = false;
38namespace gridfire {
-
39 static bool s_debug = false; // Global debug flag for the GraphEngine
-
45 typedef CppAD::AD<double> ADDouble;
-
46
-
47 using fourdst::config::Config;
-
48 using fourdst::logging::LogManager;
-
49 using fourdst::constant::Constants;
-
50
-
58 static constexpr double MIN_DENSITY_THRESHOLD = 1e-18;
-
59
-
67 static constexpr double MIN_ABUNDANCE_THRESHOLD = 1e-18;
-
68
-
75 static constexpr double MIN_JACOBIAN_THRESHOLD = 1e-24;
-
76
-
77
-
-
101 class GraphEngine final : public DynamicEngine{
-
102 public:
-
113 explicit GraphEngine(
-
114 const fourdst::composition::Composition &composition,
- -
116 );
-
117
-
118 explicit GraphEngine(
-
119 const fourdst::composition::Composition &composition,
-
120 const partition::PartitionFunction& partitionFunction,
-
121 const BuildDepthType buildDepth = NetworkBuildDepth::Full
-
122 );
-
123
-
132 explicit GraphEngine(const reaction::LogicalReactionSet &reactions);
-
133
-
147 [[nodiscard]] std::expected<StepDerivatives<double>, expectations::StaleEngineError> calculateRHSAndEnergy(
-
148 const std::vector<double>& Y,
-
149 const double T9,
-
150 const double rho
-
151 ) const override;
-
152
- -
167 const std::vector<double>& Y_dynamic,
-
168 const double T9,
-
169 const double rho
-
170 ) const override;
-
171
- -
173 const std::vector<double> &Y_dynamic,
-
174 double T9,
-
175 double rho,
-
176 const SparsityPattern &sparsityPattern
-
177 ) const override;
-
178
-
185 void generateStoichiometryMatrix() override;
-
186
-
199 [[nodiscard]] double calculateMolarReactionFlow(
- -
201 const std::vector<double>&Y,
-
202 const double T9,
-
203 const double rho
-
204 ) const override;
-
205
-
210 [[nodiscard]] const std::vector<fourdst::atomic::Species>& getNetworkSpecies() const override;
-
211
-
216 [[nodiscard]] const reaction::LogicalReactionSet& getNetworkReactions() const override;
-
217
-
218 void setNetworkReactions(const reaction::LogicalReactionSet& reactions) override;
-
219
-
231 [[nodiscard]] double getJacobianMatrixEntry(
-
232 const int i,
-
233 const int j
-
234 ) const override;
-
235
-
242 [[nodiscard]] static std::unordered_map<fourdst::atomic::Species, int> getNetReactionStoichiometry(
- -
244 );
-
245
-
257 [[nodiscard]] int getStoichiometryMatrixEntry(
-
258 const int speciesIndex,
-
259 const int reactionIndex
-
260 ) const override;
-
261
-
273 [[nodiscard]] std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> getSpeciesTimescales(
-
274 const std::vector<double>& Y,
-
275 double T9,
-
276 double rho
-
277 ) const override;
-
278
-
279 [[nodiscard]] std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> getSpeciesDestructionTimescales(
-
280 const std::vector<double>& Y,
-
281 double T9,
-
282 double rho
-
283 ) const override;
-
284
-
285 fourdst::composition::Composition update(const NetIn &netIn) override;
-
286
-
287 bool isStale(const NetIn &netIn) override;
-
288
-
295 [[nodiscard]] bool involvesSpecies(
-
296 const fourdst::atomic::Species& species
-
297 ) const;
-
298
-
315 void exportToDot(
-
316 const std::string& filename
-
317 ) const;
-
318
-
335 void exportToCSV(
-
336 const std::string& filename
-
337 ) const;
-
338
- -
340
-
341 [[nodiscard]] screening::ScreeningType getScreeningModel() const override;
-
342
-
343 void setPrecomputation(bool precompute);
-
344
-
345 [[nodiscard]] bool isPrecomputationEnabled() const;
-
346
-
347 [[nodiscard]] const partition::PartitionFunction& getPartitionFunction() const;
-
348
-
349 [[nodiscard]] double calculateReverseRate(
- -
351 double T9
-
352 ) const;
-
353
-
354 [[nodiscard]] double calculateReverseRateTwoBody(
- -
356 const double T9,
-
357 const double forwardRate,
-
358 const double expFactor
-
359 ) const;
-
360
-
361 [[nodiscard]] double calculateReverseRateTwoBodyDerivative(
- -
363 const double T9,
-
364 const double reverseRate
-
365 ) const;
-
366
-
367 [[nodiscard]] bool isUsingReverseReactions() const;
-
368
-
369 void setUseReverseReactions(bool useReverse);
-
370
-
371 [[nodiscard]] int getSpeciesIndex(
-
372 const fourdst::atomic::Species& species
-
373 ) const override;
-
374
-
375 [[nodiscard]] std::vector<double> mapNetInToMolarAbundanceVector(const NetIn &netIn) const override;
-
376
-
377 [[nodiscard]] PrimingReport primeEngine(const NetIn &netIn) override;
-
378
-
379 [[nodiscard]] BuildDepthType getDepth() const override;
-
380
-
381 void rebuild(const fourdst::composition::Composition& comp, const BuildDepthType depth) override;
+
44 typedef CppAD::AD<double> ADDouble;
+
45
+
46 using fourdst::config::Config;
+
47 using fourdst::logging::LogManager;
+
48 using fourdst::constant::Constants;
+
49
+
57 static constexpr double MIN_DENSITY_THRESHOLD = 1e-18;
+
58
+
66 static constexpr double MIN_ABUNDANCE_THRESHOLD = 1e-18;
+
67
+
74 static constexpr double MIN_JACOBIAN_THRESHOLD = 1e-24;
+
75
+
76
+
+
100 class GraphEngine final : public DynamicEngine{
+
101 public:
+
112 explicit GraphEngine(
+
113 const fourdst::composition::Composition &composition,
+ +
115 );
+
116
+
117 explicit GraphEngine(
+
118 const fourdst::composition::Composition &composition,
+
119 const partition::PartitionFunction& partitionFunction,
+
120 const BuildDepthType buildDepth = NetworkBuildDepth::Full
+
121 );
+
122
+
131 explicit GraphEngine(const reaction::LogicalReactionSet &reactions);
+
132
+
146 [[nodiscard]] std::expected<StepDerivatives<double>, expectations::StaleEngineError> calculateRHSAndEnergy(
+
147 const std::vector<double>& Y,
+
148 const double T9,
+
149 const double rho
+
150 ) const override;
+
151
+ +
166 const std::vector<double>& Y_dynamic,
+
167 const double T9,
+
168 const double rho
+
169 ) const override;
+
170
+ +
172 const std::vector<double> &Y_dynamic,
+
173 double T9,
+
174 double rho,
+
175 const SparsityPattern &sparsityPattern
+
176 ) const override;
+
177
+
184 void generateStoichiometryMatrix() override;
+
185
+
198 [[nodiscard]] double calculateMolarReactionFlow(
+ +
200 const std::vector<double>&Y,
+
201 const double T9,
+
202 const double rho
+
203 ) const override;
+
204
+
209 [[nodiscard]] const std::vector<fourdst::atomic::Species>& getNetworkSpecies() const override;
+
210
+
215 [[nodiscard]] const reaction::LogicalReactionSet& getNetworkReactions() const override;
+
216
+
217 void setNetworkReactions(const reaction::LogicalReactionSet& reactions) override;
+
218
+
230 [[nodiscard]] double getJacobianMatrixEntry(
+
231 const int i,
+
232 const int j
+
233 ) const override;
+
234
+
241 [[nodiscard]] static std::unordered_map<fourdst::atomic::Species, int> getNetReactionStoichiometry(
+ +
243 );
+
244
+
256 [[nodiscard]] int getStoichiometryMatrixEntry(
+
257 const int speciesIndex,
+
258 const int reactionIndex
+
259 ) const override;
+
260
+
272 [[nodiscard]] std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> getSpeciesTimescales(
+
273 const std::vector<double>& Y,
+
274 double T9,
+
275 double rho
+
276 ) const override;
+
277
+
278 [[nodiscard]] std::expected<std::unordered_map<fourdst::atomic::Species, double>, expectations::StaleEngineError> getSpeciesDestructionTimescales(
+
279 const std::vector<double>& Y,
+
280 double T9,
+
281 double rho
+
282 ) const override;
+
283
+
284 fourdst::composition::Composition update(const NetIn &netIn) override;
+
285
+
286 bool isStale(const NetIn &netIn) override;
+
287
+
294 [[nodiscard]] bool involvesSpecies(
+
295 const fourdst::atomic::Species& species
+
296 ) const;
+
297
+
314 void exportToDot(
+
315 const std::string& filename
+
316 ) const;
+
317
+
334 void exportToCSV(
+
335 const std::string& filename
+
336 ) const;
+
337
+ +
339
+
340 [[nodiscard]] screening::ScreeningType getScreeningModel() const override;
+
341
+
342 void setPrecomputation(bool precompute);
+
343
+
344 [[nodiscard]] bool isPrecomputationEnabled() const;
+
345
+
346 [[nodiscard]] const partition::PartitionFunction& getPartitionFunction() const;
+
347
+
348 [[nodiscard]] double calculateReverseRate(
+ +
350 double T9
+
351 ) const;
+
352
+
353 [[nodiscard]] double calculateReverseRateTwoBody(
+ +
355 const double T9,
+
356 const double forwardRate,
+
357 const double expFactor
+
358 ) const;
+
359
+
360 [[nodiscard]] double calculateReverseRateTwoBodyDerivative(
+ +
362 const double T9,
+
363 const double reverseRate
+
364 ) const;
+
365
+
366 [[nodiscard]] bool isUsingReverseReactions() const;
+
367
+
368 void setUseReverseReactions(bool useReverse);
+
369
+
370 [[nodiscard]] int getSpeciesIndex(
+
371 const fourdst::atomic::Species& species
+
372 ) const override;
+
373
+
374 [[nodiscard]] std::vector<double> mapNetInToMolarAbundanceVector(const NetIn &netIn) const override;
+
375
+
376 [[nodiscard]] PrimingReport primeEngine(const NetIn &netIn) override;
+
377
+
378 [[nodiscard]] BuildDepthType getDepth() const override;
+
379
+
380 void rebuild(const fourdst::composition::Composition& comp, const BuildDepthType depth) override;
+
381
382
-
383
-
384 private:
-
- -
386 // Forward cacheing
- -
388 std::vector<size_t> unique_reactant_indices;
-
389 std::vector<int> reactant_powers;
- -
391 std::vector<size_t> affected_species_indices;
- -
393
-
394 // Reverse cacheing
-
395 std::vector<size_t> unique_product_indices;
-
396 std::vector<int> product_powers;
- -
398 };
+
383 private:
+
+ +
385 // Forward cacheing
+ +
387 std::vector<size_t> unique_reactant_indices;
+
388 std::vector<int> reactant_powers;
+ +
390 std::vector<size_t> affected_species_indices;
+ +
392
+
393 // Reverse cacheing
+
394 std::vector<size_t> unique_product_indices;
+
395 std::vector<int> product_powers;
+ +
397 };
-
399
-
-
400 struct constants {
-
401 const double u = Constants::getInstance().get("u").value;
-
402 const double Na = Constants::getInstance().get("N_a").value;
-
403 const double c = Constants::getInstance().get("c").value;
-
404 const double kB = Constants::getInstance().get("kB").value;
-
405 };
+
398
+
+
399 struct constants {
+
400 const double u = Constants::getInstance().get("u").value;
+
401 const double Na = Constants::getInstance().get("N_a").value;
+
402 const double c = Constants::getInstance().get("c").value;
+
403 const double kB = Constants::getInstance().get("kB").value;
+
404 };
-
406 private:
-
-
407 class AtomicReverseRate final : public CppAD::atomic_base<double> {
-
408 public:
-
- - -
411 const GraphEngine& engine
-
412 ):
-
413 atomic_base<double>("AtomicReverseRate"),
- -
415 m_engine(engine) {}
+
405 private:
+
+
406 class AtomicReverseRate final : public CppAD::atomic_base<double> {
+
407 public:
+
+ + +
410 const GraphEngine& engine
+
411 ):
+
412 atomic_base<double>("AtomicReverseRate"),
+ +
414 m_engine(engine) {}
-
416
-
417 bool forward(
-
418 size_t p,
-
419 size_t q,
-
420 const CppAD::vector<bool>& vx,
-
421 CppAD::vector<bool>& vy,
-
422 const CppAD::vector<double>& tx,
-
423 CppAD::vector<double>& ty
-
424 ) override;
-
425 bool reverse(
-
426 size_t q,
-
427 const CppAD::vector<double>& tx,
-
428 const CppAD::vector<double>& ty,
-
429 CppAD::vector<double>& px,
-
430 const CppAD::vector<double>& py
-
431 ) override;
-
432 bool for_sparse_jac(
-
433 size_t q,
-
434 const CppAD::vector<std::set<size_t>>&r,
-
435 CppAD::vector<std::set<size_t>>& s
-
436 ) override;
-
437 bool rev_sparse_jac(
-
438 size_t q,
-
439 const CppAD::vector<std::set<size_t>>&rt,
-
440 CppAD::vector<std::set<size_t>>& st
-
441 ) override;
-
442
-
443 private:
- - -
446 };
+
415
+
416 bool forward(
+
417 size_t p,
+
418 size_t q,
+
419 const CppAD::vector<bool>& vx,
+
420 CppAD::vector<bool>& vy,
+
421 const CppAD::vector<double>& tx,
+
422 CppAD::vector<double>& ty
+
423 ) override;
+
424 bool reverse(
+
425 size_t q,
+
426 const CppAD::vector<double>& tx,
+
427 const CppAD::vector<double>& ty,
+
428 CppAD::vector<double>& px,
+
429 const CppAD::vector<double>& py
+
430 ) override;
+
431 bool for_sparse_jac(
+
432 size_t q,
+
433 const CppAD::vector<std::set<size_t>>&r,
+
434 CppAD::vector<std::set<size_t>>& s
+
435 ) override;
+
436 bool rev_sparse_jac(
+
437 size_t q,
+
438 const CppAD::vector<std::set<size_t>>&rt,
+
439 CppAD::vector<std::set<size_t>>& st
+
440 ) override;
+
441
+
442 private:
+ + +
445 };
-
447 private:
-
448 Config& m_config = Config::getInstance();
-
449 quill::Logger* m_logger = LogManager::getInstance().getLogger("log");
-
450
- -
452
- -
454 std::unordered_map<std::string_view, reaction::Reaction*> m_reactionIDMap;
-
455
-
456 std::vector<fourdst::atomic::Species> m_networkSpecies;
-
457 std::unordered_map<std::string_view, fourdst::atomic::Species> m_networkSpeciesMap;
-
458 std::unordered_map<fourdst::atomic::Species, size_t> m_speciesToIndexMap;
-
459
-
460 boost::numeric::ublas::compressed_matrix<int> m_stoichiometryMatrix;
-
461
-
462 mutable boost::numeric::ublas::compressed_matrix<double> m_jacobianMatrix;
-
463 mutable CppAD::ADFun<double> m_rhsADFun;
-
464 mutable CppAD::sparse_jac_work m_jac_work;
-
465 CppAD::sparse_rc<std::vector<size_t>> m_full_jacobian_sparsity_pattern;
-
466
-
467 std::vector<std::unique_ptr<AtomicReverseRate>> m_atomicReverseRates;
-
468
- -
470 std::unique_ptr<screening::ScreeningModel> m_screeningModel = screening::selectScreeningModel(m_screeningType);
-
471
- -
473
- -
475
- -
477
-
478 std::vector<PrecomputedReaction> m_precomputedReactions;
-
479 std::unique_ptr<partition::PartitionFunction> m_partitionFunction;
-
480
-
481 private:
-
489 void syncInternalMaps();
-
490
- -
498
- -
506
- -
514
-
522 void reserveJacobianMatrix() const;
-
523
-
533 void recordADTape();
-
534
- -
536
-
537 void precomputeNetwork();
-
538
-
539
-
549 [[nodiscard]] bool validateConservation() const;
-
550
- -
563 const fourdst::composition::Composition &composition,
-
564 double culling,
-
565 double T9
-
566 );
-
567
-
568
-
569
- -
571 const std::vector<double> &Y_in,
-
572 const std::vector<double>& bare_rates,
-
573 const std::vector<double> &bare_reverse_rates,
-
574 double T9, double rho
-
575 ) const;
-
576
-
590 template <IsArithmeticOrAD T>
- - -
593 const std::vector<T> &Y,
-
594 const T T9,
-
595 const T rho
-
596 ) const;
-
597
-
598 template<IsArithmeticOrAD T>
- -
600 T T9,
-
601 T rho,
-
602 std::vector<T> screeningFactors,
-
603 std::vector<T> Y,
-
604 size_t reactionIndex,
- +
446 private:
+
447 Config& m_config = Config::getInstance();
+
448 quill::Logger* m_logger = LogManager::getInstance().getLogger("log");
+
449
+ +
451
+ +
453 std::unordered_map<std::string_view, reaction::Reaction*> m_reactionIDMap;
+
454
+
455 std::vector<fourdst::atomic::Species> m_networkSpecies;
+
456 std::unordered_map<std::string_view, fourdst::atomic::Species> m_networkSpeciesMap;
+
457 std::unordered_map<fourdst::atomic::Species, size_t> m_speciesToIndexMap;
+
458
+
459 boost::numeric::ublas::compressed_matrix<int> m_stoichiometryMatrix;
+
460
+
461 mutable boost::numeric::ublas::compressed_matrix<double> m_jacobianMatrix;
+
462 mutable CppAD::ADFun<double> m_rhsADFun;
+
463 mutable CppAD::sparse_jac_work m_jac_work;
+
464 CppAD::sparse_rc<std::vector<size_t>> m_full_jacobian_sparsity_pattern;
+
465
+
466 std::vector<std::unique_ptr<AtomicReverseRate>> m_atomicReverseRates;
+
467
+ +
469 std::unique_ptr<screening::ScreeningModel> m_screeningModel = screening::selectScreeningModel(m_screeningType);
+
470
+ +
472
+ +
474
+ +
476
+
477 std::vector<PrecomputedReaction> m_precomputedReactions;
+
478 std::unique_ptr<partition::PartitionFunction> m_partitionFunction;
+
479
+
480 private:
+
488 void syncInternalMaps();
+
489
+ +
497
+ +
505
+ +
513
+
521 void reserveJacobianMatrix() const;
+
522
+
532 void recordADTape();
+
533
+ +
535
+
536 void precomputeNetwork();
+
537
+
538
+
548 [[nodiscard]] bool validateConservation() const;
+
549
+
550
+ +
552 const std::vector<double> &Y_in,
+
553 const std::vector<double>& bare_rates,
+
554 const std::vector<double> &bare_reverse_rates,
+
555 double T9, double rho
+
556 ) const;
+
557
+
571 template <IsArithmeticOrAD T>
+ + +
574 const std::vector<T> &Y,
+
575 const T T9,
+
576 const T rho
+
577 ) const;
+
578
+
579 template<IsArithmeticOrAD T>
+ +
581 T T9,
+
582 T rho,
+
583 std::vector<T> screeningFactors,
+
584 std::vector<T> Y,
+
585 size_t reactionIndex,
+ +
587 ) const;
+
588
+
601 template<IsArithmeticOrAD T>
+ +
603 const std::vector<T> &Y_in,
+
604 T T9,
+
605 T rho
606 ) const;
607
-
620 template<IsArithmeticOrAD T>
- -
622 const std::vector<T> &Y_in,
-
623 T T9,
-
624 T rho
-
625 ) const;
-
626
- -
640 const std::vector<double>& Y_in,
-
641 const double T9,
-
642 const double rho
-
643 ) const;
-
644
- -
658 const std::vector<ADDouble>& Y_in,
-
659 const ADDouble &T9,
-
660 const ADDouble &rho
-
661 ) const;
-
662 };
+ +
621 const std::vector<double>& Y_in,
+
622 const double T9,
+
623 const double rho
+
624 ) const;
+
625
+ +
639 const std::vector<ADDouble>& Y_in,
+
640 const ADDouble &T9,
+
641 const ADDouble &rho
+
642 ) const;
+
643 };
-
663
-
664
-
665
-
666 template <IsArithmeticOrAD T>
-
- -
668 T T9,
-
669 T rho,
-
670 std::vector<T> screeningFactors,
-
671 std::vector<T> Y,
-
672 size_t reactionIndex,
- -
674 ) const {
- -
676 return static_cast<T>(0.0); // If reverse reactions are not used, return zero
-
677 }
-
678 s_debug = false;
-
679 if (reaction.peName() == "p(p,e+)d" || reaction.peName() =="d(d,n)he3" || reaction.peName() == "c12(p,g)n13") {
-
680 if constexpr (!std::is_same_v<T, ADDouble>) {
-
681 s_debug = true;
-
682 std::cout << "Calculating reverse molar flow for reaction: " << reaction.peName() << std::endl;
-
683 std::cout << "\tT9: " << T9 << ", rho: " << rho << std::endl;
-
684 }
-
685 }
-
686 T reverseMolarFlow = static_cast<T>(0.0);
-
687
-
688 if (reaction.qValue() != 0.0) {
-
689 T reverseRateConstant = static_cast<T>(0.0);
-
690 if constexpr (std::is_same_v<T, ADDouble>) { // Check if T is an AD type at compile time
-
691 const auto& atomic_func_ptr = m_atomicReverseRates[reactionIndex];
-
692 if (atomic_func_ptr != nullptr) {
-
693 // A. Instantiate the atomic operator for the specific reaction
-
694 // B. Marshal the input vector
-
695 std::vector<T> ax = { T9 };
-
696
-
697 std::vector<T> ay(1);
-
698 (*atomic_func_ptr)(ax, ay);
-
699 reverseRateConstant = static_cast<T>(ay[0]);
-
700 } else {
-
701 return reverseMolarFlow; // If no atomic function is available, return zero
-
702 }
-
703 } else {
-
704 // A,B If not calling with an AD type, calculate the reverse rate directly
-
705 if (s_debug) {
-
706 std::cout << "\tUsing double overload\n";
-
707 }
-
708 reverseRateConstant = calculateReverseRate(reaction, T9);
-
709 }
-
710
-
711 // C. Get product multiplicities
-
712 std::unordered_map<fourdst::atomic::Species, int> productCounts;
-
713 for (const auto& product : reaction.products()) {
-
714 productCounts[product]++;
-
715 }
-
716
-
717 // D. Calculate the symmetry factor
-
718 T reverseSymmetryFactor = static_cast<T>(1.0);
-
719 for (const auto &count: productCounts | std::views::values) {
-
720 reverseSymmetryFactor /= static_cast<T>(std::tgamma(static_cast<double>(count + 1))); // Gamma function for factorial
-
721 }
-
722
-
723 // E. Calculate the abundance term
-
724 T productAbundanceTerm = static_cast<T>(1.0);
-
725 for (const auto& [species, count] : productCounts) {
-
726 const unsigned long speciesIndex = m_speciesToIndexMap.at(species);
-
727 productAbundanceTerm *= CppAD::pow(Y[speciesIndex], count);
-
728 }
-
729
-
730 // F. Determine the power for the density term
-
731 const size_t num_products = reaction.products().size();
-
732 const T rho_power = CppAD::pow(rho, static_cast<T>(num_products > 1 ? num_products - 1 : 0)); // Density raised to the power of (N-1) for N products
+
644
+
645
+
646
+
647 template <IsArithmeticOrAD T>
+
+ +
649 T T9,
+
650 T rho,
+
651 std::vector<T> screeningFactors,
+
652 std::vector<T> Y,
+
653 size_t reactionIndex,
+ +
655 ) const {
+ +
657 return static_cast<T>(0.0); // If reverse reactions are not used, return zero
+
658 }
+
659 T reverseMolarFlow = static_cast<T>(0.0);
+
660
+
661 if (reaction.qValue() != 0.0) {
+
662 T reverseRateConstant = static_cast<T>(0.0);
+
663 if constexpr (std::is_same_v<T, ADDouble>) { // Check if T is an AD type at compile time
+
664 const auto& atomic_func_ptr = m_atomicReverseRates[reactionIndex];
+
665 if (atomic_func_ptr != nullptr) {
+
666 // A. Instantiate the atomic operator for the specific reaction
+
667 // B. Marshal the input vector
+
668 std::vector<T> ax = { T9 };
+
669
+
670 std::vector<T> ay(1);
+
671 (*atomic_func_ptr)(ax, ay);
+
672 reverseRateConstant = static_cast<T>(ay[0]);
+
673 } else {
+
674 return reverseMolarFlow; // If no atomic function is available, return zero
+
675 }
+
676 } else {
+
677 // A,B If not calling with an AD type, calculate the reverse rate directly
+
678 reverseRateConstant = calculateReverseRate(reaction, T9);
+
679 }
+
680
+
681 // C. Get product multiplicities
+
682 std::unordered_map<fourdst::atomic::Species, int> productCounts;
+
683 for (const auto& product : reaction.products()) {
+
684 productCounts[product]++;
+
685 }
+
686
+
687 // D. Calculate the symmetry factor
+
688 T reverseSymmetryFactor = static_cast<T>(1.0);
+
689 for (const auto &count: productCounts | std::views::values) {
+
690 reverseSymmetryFactor /= static_cast<T>(std::tgamma(static_cast<double>(count + 1))); // Gamma function for factorial
+
691 }
+
692
+
693 // E. Calculate the abundance term
+
694 T productAbundanceTerm = static_cast<T>(1.0);
+
695 for (const auto& [species, count] : productCounts) {
+
696 const unsigned long speciesIndex = m_speciesToIndexMap.at(species);
+
697 productAbundanceTerm *= CppAD::pow(Y[speciesIndex], count);
+
698 }
+
699
+
700 // F. Determine the power for the density term
+
701 const size_t num_products = reaction.products().size();
+
702 const T rho_power = CppAD::pow(rho, static_cast<T>(num_products > 1 ? num_products - 1 : 0)); // Density raised to the power of (N-1) for N products
+
703
+
704 // G. Assemble the reverse molar flow rate
+
705 reverseMolarFlow = screeningFactors[reactionIndex] *
+
706 reverseRateConstant *
+
707 productAbundanceTerm *
+
708 reverseSymmetryFactor *
+
709 rho_power;
+
710 }
+
711 return reverseMolarFlow;
+
712 }
+
+
713
+
714 template<IsArithmeticOrAD T>
+
+ +
716 const std::vector<T> &Y_in, T T9, T rho) const {
+
717 std::vector<T> screeningFactors = m_screeningModel->calculateScreeningFactors(
+ + +
720 Y_in,
+
721 T9,
+
722 rho
+
723 );
+
724
+
725 // --- Setup output derivatives structure ---
+
726 StepDerivatives<T> result;
+
727 result.dydt.resize(m_networkSpecies.size(), static_cast<T>(0.0));
+
728
+
729 // --- AD Pre-setup (flags to control conditionals in an AD safe / branch aware manner) ---
+
730 // ----- Constants for AD safe calculations ---
+
731 const T zero = static_cast<T>(0.0);
+
732 const T one = static_cast<T>(1.0);
733
-
734 // G. Assemble the reverse molar flow rate
-
735 reverseMolarFlow = screeningFactors[reactionIndex] *
-
736 reverseRateConstant *
-
737 productAbundanceTerm *
-
738 reverseSymmetryFactor *
-
739 rho_power;
-
740 }
-
741 return reverseMolarFlow;
-
742 }
-
-
743
-
744 template<IsArithmeticOrAD T>
-
- -
746 const std::vector<T> &Y_in, T T9, T rho) const {
-
747 std::vector<T> screeningFactors = m_screeningModel->calculateScreeningFactors(
- - -
750 Y_in,
-
751 T9,
-
752 rho
-
753 );
-
754
-
755 // --- Setup output derivatives structure ---
-
756 StepDerivatives<T> result;
-
757 result.dydt.resize(m_networkSpecies.size(), static_cast<T>(0.0));
-
758
-
759 // --- AD Pre-setup (flags to control conditionals in an AD safe / branch aware manner) ---
-
760 // ----- Constants for AD safe calculations ---
-
761 const T zero = static_cast<T>(0.0);
-
762 const T one = static_cast<T>(1.0);
-
763
-
764 // ----- Initialize variables for molar concentration product and thresholds ---
-
765 // Note: the logic here is that we use CppAD::CondExprLt to test thresholds and if they are less we set the flag
-
766 // to zero so that the final returned reaction flow is 0. This is as opposed to standard if statements
-
767 // which create branches that break the AD tape.
-
768 const T rho_threshold = static_cast<T>(MIN_DENSITY_THRESHOLD);
-
769
-
770 // --- Check if the density is below the threshold where we ignore reactions ---
-
771 T threshold_flag = CppAD::CondExpLt(rho, rho_threshold, zero, one); // If rho < threshold, set flag to 0
-
772
-
773 std::vector<T> Y = Y_in;
-
774 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
-
775 // We use CppAD::CondExpLt to handle AD taping and prevent branching
-
776 // Note that while this is syntactically more complex this is equivalent to
-
777 // if (Y[i] < 0) {Y[i] = 0;}
-
778 // The issue is that this would introduce a branch which would require the auto diff tape to be re-recorded
-
779 // each timestep, which is very inefficient.
-
780 Y[i] = CppAD::CondExpLt(Y[i], zero, zero, Y[i]); // Ensure no negative abundances
-
781 }
-
782
-
783 const T u = static_cast<T>(m_constants.u); // Atomic mass unit in grams
-
784 const T N_A = static_cast<T>(m_constants.Na); // Avogadro's number in mol^-1
-
785 const T c = static_cast<T>(m_constants.c); // Speed of light in cm/s
-
786
-
787 // --- SINGLE LOOP OVER ALL REACTIONS ---
-
788 for (size_t reactionIndex = 0; reactionIndex < m_reactions.size(); ++reactionIndex) {
-
789 const auto& reaction = m_reactions[reactionIndex];
+
734 // ----- Initialize variables for molar concentration product and thresholds ---
+
735 // Note: the logic here is that we use CppAD::CondExprLt to test thresholds and if they are less we set the flag
+
736 // to zero so that the final returned reaction flow is 0. This is as opposed to standard if statements
+
737 // which create branches that break the AD tape.
+
738 const T rho_threshold = static_cast<T>(MIN_DENSITY_THRESHOLD);
+
739
+
740 // --- Check if the density is below the threshold where we ignore reactions ---
+
741 T threshold_flag = CppAD::CondExpLt(rho, rho_threshold, zero, one); // If rho < threshold, set flag to 0
+
742
+
743 std::vector<T> Y = Y_in;
+
744 for (size_t i = 0; i < m_networkSpecies.size(); ++i) {
+
745 // We use CppAD::CondExpLt to handle AD taping and prevent branching
+
746 // Note that while this is syntactically more complex this is equivalent to
+
747 // if (Y[i] < 0) {Y[i] = 0;}
+
748 // The issue is that this would introduce a branch which would require the auto diff tape to be re-recorded
+
749 // each timestep, which is very inefficient.
+
750 Y[i] = CppAD::CondExpLt(Y[i], zero, zero, Y[i]); // Ensure no negative abundances
+
751 }
+
752
+
753 const T u = static_cast<T>(m_constants.u); // Atomic mass unit in grams
+
754 const T N_A = static_cast<T>(m_constants.Na); // Avogadro's number in mol^-1
+
755 const T c = static_cast<T>(m_constants.c); // Speed of light in cm/s
+
756
+
757 // --- SINGLE LOOP OVER ALL REACTIONS ---
+
758 for (size_t reactionIndex = 0; reactionIndex < m_reactions.size(); ++reactionIndex) {
+
759 const auto& reaction = m_reactions[reactionIndex];
+
760
+
761 // 1. Calculate forward reaction rate
+
762 const T forwardMolarReactionFlow = screeningFactors[reactionIndex] *
+ +
764
+
765 // 2. Calculate reverse reaction rate
+
766 T reverseMolarFlow = calculateReverseMolarReactionFlow<T>(
+
767 T9,
+
768 rho,
+
769 screeningFactors,
+
770 Y,
+
771 reactionIndex,
+ +
773 );
+
774
+
775 const T molarReactionFlow = forwardMolarReactionFlow - reverseMolarFlow; // Net molar reaction flow
+
776
+
777 // 3. Use the rate to update all relevant species derivatives (dY/dt)
+
778 for (size_t speciesIndex = 0; speciesIndex < m_networkSpecies.size(); ++speciesIndex) {
+
779 const T nu_ij = static_cast<T>(m_stoichiometryMatrix(speciesIndex, reactionIndex));
+
780 result.dydt[speciesIndex] += threshold_flag * nu_ij * molarReactionFlow;
+
781 }
+
782 }
+
783
+
784 T massProductionRate = static_cast<T>(0.0); // [mol][s^-1]
+
785 for (const auto& [species, index] : m_speciesToIndexMap) {
+
786 massProductionRate += result.dydt[index] * species.mass() * u;
+
787 }
+
788
+
789 result.nuclearEnergyGenerationRate = -massProductionRate * N_A * c * c; // [cm^2][s^-3] = [erg][s^-1][g^-1]
790
-
791 // 1. Calculate forward reaction rate
-
792 const T forwardMolarReactionFlow = screeningFactors[reactionIndex] *
- +
791 return result;
+
792 }
+
+
793
794
-
795 // 2. Calculate reverse reaction rate
-
796 T reverseMolarFlow = calculateReverseMolarReactionFlow<T>(
-
797 T9,
-
798 rho,
-
799 screeningFactors,
-
800 Y,
-
801 reactionIndex,
- -
803 );
-
804
-
805 const T molarReactionFlow = forwardMolarReactionFlow - reverseMolarFlow; // Net molar reaction flow
+
795 template <IsArithmeticOrAD T>
+
+ + +
798 const std::vector<T> &Y,
+
799 const T T9,
+
800 const T rho
+
801 ) const {
+
802
+
803 // --- Pre-setup (flags to control conditionals in an AD safe / branch aware manner) ---
+
804 // ----- Constants for AD safe calculations ---
+
805 const T zero = static_cast<T>(0.0);
806
-
807 // 3. Use the rate to update all relevant species derivatives (dY/dt)
-
808 for (size_t speciesIndex = 0; speciesIndex < m_networkSpecies.size(); ++speciesIndex) {
-
809 const T nu_ij = static_cast<T>(m_stoichiometryMatrix(speciesIndex, reactionIndex));
-
810 result.dydt[speciesIndex] += threshold_flag * nu_ij * molarReactionFlow;
-
811 }
-
812 }
-
813
-
814 T massProductionRate = static_cast<T>(0.0); // [mol][s^-1]
-
815 for (const auto& [species, index] : m_speciesToIndexMap) {
-
816 massProductionRate += result.dydt[index] * species.mass() * u;
-
817 }
-
818
-
819 result.nuclearEnergyGenerationRate = -massProductionRate * N_A * c * c; // [cm^2][s^-3] = [erg][s^-1][g^-1]
+
807 // --- Calculate the molar reaction rate (in units of [s^-1][cm^3(N-1)][mol^(1-N)] for N reactants) ---
+
808 const T k_reaction = reaction.calculate_rate(T9);
+
809
+
810 // --- Cound the number of each reactant species to account for species multiplicity ---
+
811 std::unordered_map<std::string, int> reactant_counts;
+
812 reactant_counts.reserve(reaction.reactants().size());
+
813 for (const auto& reactant : reaction.reactants()) {
+
814 reactant_counts[std::string(reactant.name())]++;
+
815 }
+
816 const int totalReactants = static_cast<int>(reaction.reactants().size());
+
817
+
818 // --- Accumulator for the molar concentration ---
+
819 auto molar_concentration_product = static_cast<T>(1.0);
820
-
821 return result;
-
822 }
+
821 // --- Loop through each unique reactant species and calculate the molar concentration for that species then multiply that into the accumulator ---
+
822 for (const auto& [species_name, count] : reactant_counts) {
+
823 // --- Resolve species to molar abundance ---
+
824 // PERF: Could probably optimize out this lookup
+
825 const auto species_it = m_speciesToIndexMap.find(m_networkSpeciesMap.at(species_name));
+
826 const size_t species_index = species_it->second;
+
827 const T Yi = Y[species_index];
+
828
+
829 // --- If count is > 1 , we need to raise the molar concentration to the power of count since there are really count bodies in that reaction ---
+
830 molar_concentration_product *= CppAD::pow(Yi, static_cast<T>(count)); // ni^count
+
831
+
832 // --- Apply factorial correction for identical reactions ---
+
833 if (count > 1) {
+
834 molar_concentration_product /= static_cast<T>(std::tgamma(static_cast<double>(count + 1))); // Gamma function for factorial
+
835 }
+
836 }
+
837 // --- Final reaction flow calculation [mol][s^-1][g^-1] ---
+
838 // Note: If the threshold flag ever gets set to zero this will return zero.
+
839 // This will result basically in multiple branches being written to the AD tape, which will make
+
840 // the tape more expensive to record, but it will also mean that we only need to record it once for
+
841 // the entire network.
+
842 const T densityTerm = CppAD::pow(rho, totalReactants > 1 ? static_cast<T>(totalReactants - 1) : zero); // Density raised to the power of (N-1) for N reactants
+
843 return molar_concentration_product * k_reaction * densityTerm;
+
844 }
-
823
-
824
-
825 template <IsArithmeticOrAD T>
-
- - -
828 const std::vector<T> &Y,
-
829 const T T9,
-
830 const T rho
-
831 ) const {
-
832
-
833 // --- Pre-setup (flags to control conditionals in an AD safe / branch aware manner) ---
-
834 // ----- Constants for AD safe calculations ---
-
835 const T zero = static_cast<T>(0.0);
-
836
-
837 // --- Calculate the molar reaction rate (in units of [s^-1][cm^3(N-1)][mol^(1-N)] for N reactants) ---
-
838 const T k_reaction = reaction.calculate_rate(T9);
-
839
-
840 // --- Cound the number of each reactant species to account for species multiplicity ---
-
841 std::unordered_map<std::string, int> reactant_counts;
-
842 reactant_counts.reserve(reaction.reactants().size());
-
843 for (const auto& reactant : reaction.reactants()) {
-
844 reactant_counts[std::string(reactant.name())]++;
-
845 }
-
846 const int totalReactants = static_cast<int>(reaction.reactants().size());
-
847
-
848 // --- Accumulator for the molar concentration ---
-
849 auto molar_concentration_product = static_cast<T>(1.0);
-
850
-
851 // --- Loop through each unique reactant species and calculate the molar concentration for that species then multiply that into the accumulator ---
-
852 for (const auto& [species_name, count] : reactant_counts) {
-
853 // --- Resolve species to molar abundance ---
-
854 // PERF: Could probably optimize out this lookup
-
855 const auto species_it = m_speciesToIndexMap.find(m_networkSpeciesMap.at(species_name));
-
856 const size_t species_index = species_it->second;
-
857 const T Yi = Y[species_index];
-
858
-
859 // --- If count is > 1 , we need to raise the molar concentration to the power of count since there are really count bodies in that reaction ---
-
860 molar_concentration_product *= CppAD::pow(Yi, static_cast<T>(count)); // ni^count
-
861
-
862 // --- Apply factorial correction for identical reactions ---
-
863 if (count > 1) {
-
864 molar_concentration_product /= static_cast<T>(std::tgamma(static_cast<double>(count + 1))); // Gamma function for factorial
-
865 }
-
866 }
-
867 // --- Final reaction flow calculation [mol][s^-1][g^-1] ---
-
868 // Note: If the threshold flag ever gets set to zero this will return zero.
-
869 // This will result basically in multiple branches being written to the AD tape, which will make
-
870 // the tape more expensive to record, but it will also mean that we only need to record it once for
-
871 // the entire network.
-
872 const T densityTerm = CppAD::pow(rho, totalReactants > 1 ? static_cast<T>(totalReactants - 1) : zero); // Density raised to the power of (N-1) for N reactants
-
873 return molar_concentration_product * k_reaction * densityTerm;
-
874 }
-
-
875
-
876};
+
845
+
846};
Abstract class for engines supporting Jacobian and stoichiometry operations.
-
AtomicReverseRate(const reaction::Reaction &reaction, const GraphEngine &engine)
-
bool reverse(size_t q, const CppAD::vector< double > &tx, const CppAD::vector< double > &ty, CppAD::vector< double > &px, const CppAD::vector< double > &py) override
- -
bool rev_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &rt, CppAD::vector< std::set< size_t > > &st) override
-
const reaction::Reaction & m_reaction
-
bool forward(size_t p, size_t q, const CppAD::vector< bool > &vx, CppAD::vector< bool > &vy, const CppAD::vector< double > &tx, CppAD::vector< double > &ty) override
-
bool for_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &r, CppAD::vector< std::set< size_t > > &s) override
-
bool isPrecomputationEnabled() const
-
double calculateReverseRateTwoBody(const reaction::Reaction &reaction, const double T9, const double forwardRate, const double expFactor) const
-
double calculateReverseRate(const reaction::Reaction &reaction, double T9) const
+
AtomicReverseRate(const reaction::Reaction &reaction, const GraphEngine &engine)
+
bool reverse(size_t q, const CppAD::vector< double > &tx, const CppAD::vector< double > &ty, CppAD::vector< double > &px, const CppAD::vector< double > &py) override
+ +
bool rev_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &rt, CppAD::vector< std::set< size_t > > &st) override
+
const reaction::Reaction & m_reaction
+
bool forward(size_t p, size_t q, const CppAD::vector< bool > &vx, CppAD::vector< bool > &vy, const CppAD::vector< double > &tx, CppAD::vector< double > &ty) override
+
bool for_sparse_jac(size_t q, const CppAD::vector< std::set< size_t > > &r, CppAD::vector< std::set< size_t > > &s) override
+
bool isPrecomputationEnabled() const
+
double calculateReverseRateTwoBody(const reaction::Reaction &reaction, const double T9, const double forwardRate, const double expFactor) const
+
double calculateReverseRate(const reaction::Reaction &reaction, double T9) const
const std::vector< fourdst::atomic::Species > & getNetworkSpecies() const override
Gets the list of species in the network.
- -
BuildDepthType getDepth() const override
-
T calculateReverseMolarReactionFlow(T T9, T rho, std::vector< T > screeningFactors, std::vector< T > Y, size_t reactionIndex, const reaction::LogicalReaction &reaction) const
-
bool m_usePrecomputation
Flag to enable or disable using precomputed reactions for efficiency. Mathematically,...
-
CppAD::sparse_rc< std::vector< size_t > > m_full_jacobian_sparsity_pattern
Full sparsity pattern for the Jacobian matrix.
-
CppAD::sparse_jac_work m_jac_work
Work object for sparse Jacobian calculations.
+ +
BuildDepthType getDepth() const override
+
T calculateReverseMolarReactionFlow(T T9, T rho, std::vector< T > screeningFactors, std::vector< T > Y, size_t reactionIndex, const reaction::LogicalReaction &reaction) const
+
bool m_usePrecomputation
Flag to enable or disable using precomputed reactions for efficiency. Mathematically,...
+
CppAD::sparse_rc< std::vector< size_t > > m_full_jacobian_sparsity_pattern
Full sparsity pattern for the Jacobian matrix.
+
CppAD::sparse_jac_work m_jac_work
Work object for sparse Jacobian calculations.
void populateReactionIDMap()
Populates the reaction ID map.
-
std::vector< double > mapNetInToMolarAbundanceVector(const NetIn &netIn) const override
-
void collectAtomicReverseRateAtomicBases()
-
CppAD::ADFun< double > m_rhsADFun
CppAD function for the right-hand side of the ODE.
-
boost::numeric::ublas::compressed_matrix< double > m_jacobianMatrix
Jacobian matrix (species x species).
-
double getJacobianMatrixEntry(const int i, const int j) const override
Gets an entry from the previously generated Jacobian matrix.
-
std::unordered_map< std::string_view, fourdst::atomic::Species > m_networkSpeciesMap
Map from species name to Species object.
-
bool m_useReverseReactions
Flag to enable or disable reverse reactions. If false, only forward reactions are considered.
-
std::unique_ptr< partition::PartitionFunction > m_partitionFunction
Partition function for the network.
+
std::vector< double > mapNetInToMolarAbundanceVector(const NetIn &netIn) const override
+
void collectAtomicReverseRateAtomicBases()
+
CppAD::ADFun< double > m_rhsADFun
CppAD function for the right-hand side of the ODE.
+
boost::numeric::ublas::compressed_matrix< double > m_jacobianMatrix
Jacobian matrix (species x species).
+
double getJacobianMatrixEntry(const int i, const int j) const override
Gets an entry from the previously generated Jacobian matrix.
+
std::unordered_map< std::string_view, fourdst::atomic::Species > m_networkSpeciesMap
Map from species name to Species object.
+
bool m_useReverseReactions
Flag to enable or disable reverse reactions. If false, only forward reactions are considered.
+
std::unique_ptr< partition::PartitionFunction > m_partitionFunction
Partition function for the network.
void setNetworkReactions(const reaction::LogicalReactionSet &reactions) override
- -
void setUseReverseReactions(bool useReverse)
+ +
void setUseReverseReactions(bool useReverse)
void populateSpeciesToIndexMap()
Populates the species-to-index map.
-
quill::Logger * m_logger
-
screening::ScreeningType m_screeningType
Screening type for the reaction network. Default to no screening.
-
fourdst::composition::Composition update(const NetIn &netIn) override
Update the internal state of the engine.
-
std::vector< PrecomputedReaction > m_precomputedReactions
Precomputed reactions for efficiency.
-
std::unordered_map< std::string_view, reaction::Reaction * > m_reactionIDMap
Map from reaction ID to REACLIBReaction. //PERF: This makes copies of REACLIBReaction and could be a ...
-
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesTimescales(const std::vector< double > &Y, double T9, double rho) const override
Computes timescales for all species in the network.
-
screening::ScreeningType getScreeningModel() const override
Get the current electron screening model.
-
int getStoichiometryMatrixEntry(const int speciesIndex, const int reactionIndex) const override
Gets an entry from the stoichiometry matrix.
-
void setPrecomputation(bool precompute)
-
BuildDepthType m_depth
-
void setScreeningModel(screening::ScreeningType) override
Set the electron screening model.
-
std::vector< std::unique_ptr< AtomicReverseRate > > m_atomicReverseRates
-
void exportToCSV(const std::string &filename) const
Exports the network to a CSV file for analysis.
-
static std::unordered_map< fourdst::atomic::Species, int > getNetReactionStoichiometry(const reaction::Reaction &reaction)
Gets the net stoichiometry for a given reaction.
+
quill::Logger * m_logger
+
screening::ScreeningType m_screeningType
Screening type for the reaction network. Default to no screening.
+
fourdst::composition::Composition update(const NetIn &netIn) override
Update the internal state of the engine.
+
std::vector< PrecomputedReaction > m_precomputedReactions
Precomputed reactions for efficiency.
+
std::unordered_map< std::string_view, reaction::Reaction * > m_reactionIDMap
Map from reaction ID to REACLIBReaction. //PERF: This makes copies of REACLIBReaction and could be a ...
+
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesTimescales(const std::vector< double > &Y, double T9, double rho) const override
Computes timescales for all species in the network.
+
screening::ScreeningType getScreeningModel() const override
Get the current electron screening model.
+
int getStoichiometryMatrixEntry(const int speciesIndex, const int reactionIndex) const override
Gets an entry from the stoichiometry matrix.
+
void setPrecomputation(bool precompute)
+
BuildDepthType m_depth
+
void setScreeningModel(screening::ScreeningType) override
Set the electron screening model.
+
std::vector< std::unique_ptr< AtomicReverseRate > > m_atomicReverseRates
+
void exportToCSV(const std::string &filename) const
Exports the network to a CSV file for analysis.
+
static std::unordered_map< fourdst::atomic::Species, int > getNetReactionStoichiometry(const reaction::Reaction &reaction)
Gets the net stoichiometry for a given reaction.
void reserveJacobianMatrix() const
Reserves space for the Jacobian matrix.
-
int getSpeciesIndex(const fourdst::atomic::Species &species) const override
-
double calculateMolarReactionFlow(const reaction::Reaction &reaction, const std::vector< double > &Y, const double T9, const double rho) const override
Calculates the molar reaction flow for a given reaction.
- -
std::vector< fourdst::atomic::Species > m_networkSpecies
Vector of unique species in the network.
-
void recordADTape()
Records the AD tape for the right-hand side of the ODE.
-
StepDerivatives< double > calculateAllDerivativesUsingPrecomputation(const std::vector< double > &Y_in, const std::vector< double > &bare_rates, const std::vector< double > &bare_reverse_rates, double T9, double rho) const
+
int getSpeciesIndex(const fourdst::atomic::Species &species) const override
+
double calculateMolarReactionFlow(const reaction::Reaction &reaction, const std::vector< double > &Y, const double T9, const double rho) const override
Calculates the molar reaction flow for a given reaction.
+ +
std::vector< fourdst::atomic::Species > m_networkSpecies
Vector of unique species in the network.
+
void recordADTape()
Records the AD tape for the right-hand side of the ODE.
+
StepDerivatives< double > calculateAllDerivativesUsingPrecomputation(const std::vector< double > &Y_in, const std::vector< double > &bare_rates, const std::vector< double > &bare_reverse_rates, double T9, double rho) const
bool involvesSpecies(const fourdst::atomic::Species &species) const
Checks if a given species is involved in the network.
std::expected< StepDerivatives< double >, expectations::StaleEngineError > calculateRHSAndEnergy(const std::vector< double > &Y, const double T9, const double rho) const override
Calculates the right-hand side (dY/dt) and energy generation rate.
-
reaction::LogicalReactionSet m_reactions
Set of REACLIB reactions in the network.
+
reaction::LogicalReactionSet m_reactions
Set of REACLIB reactions in the network.
void syncInternalMaps()
Synchronizes the internal maps.
bool validateConservation() const
Validates mass and charge conservation across all reactions.
-
void generateJacobianMatrix(const std::vector< double > &Y_dynamic, const double T9, const double rho) const override
Generates the Jacobian matrix for the current state.
-
boost::numeric::ublas::compressed_matrix< int > m_stoichiometryMatrix
Stoichiometry matrix (species x reactions).
+
void generateJacobianMatrix(const std::vector< double > &Y_dynamic, const double T9, const double rho) const override
Generates the Jacobian matrix for the current state.
+
boost::numeric::ublas::compressed_matrix< int > m_stoichiometryMatrix
Stoichiometry matrix (species x reactions).
const reaction::LogicalReactionSet & getNetworkReactions() const override
Gets the set of logical reactions in the network.
-
std::unordered_map< fourdst::atomic::Species, size_t > m_speciesToIndexMap
Map from species to their index in the stoichiometry matrix.
-
void rebuild(const fourdst::composition::Composition &comp, const BuildDepthType depth) override
-
void exportToDot(const std::string &filename) const
Exports the network to a DOT file for visualization.
-
const partition::PartitionFunction & getPartitionFunction() const
-
bool isUsingReverseReactions() const
-
PrimingReport primeEngine(const NetIn &netIn) override
-
void generateStoichiometryMatrix() override
Generates the stoichiometry matrix for the network.
+
std::unordered_map< fourdst::atomic::Species, size_t > m_speciesToIndexMap
Map from species to their index in the stoichiometry matrix.
+
void rebuild(const fourdst::composition::Composition &comp, const BuildDepthType depth) override
+
void exportToDot(const std::string &filename) const
Exports the network to a DOT file for visualization.
+
const partition::PartitionFunction & getPartitionFunction() const
+
bool isUsingReverseReactions() const
+
PrimingReport primeEngine(const NetIn &netIn) override
+
void generateStoichiometryMatrix() override
Generates the stoichiometry matrix for the network.
void collectNetworkSpecies()
Collects the unique species in the network.
-
void validateComposition(const fourdst::composition::Composition &composition, double culling, double T9)
Validates the composition against the current reaction set.
-
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesDestructionTimescales(const std::vector< double > &Y, double T9, double rho) const override
-
bool isStale(const NetIn &netIn) override
-
std::unique_ptr< screening::ScreeningModel > m_screeningModel
-
double calculateReverseRateTwoBodyDerivative(const reaction::Reaction &reaction, const double T9, const double reverseRate) const
-
StepDerivatives< T > calculateAllDerivatives(const std::vector< T > &Y_in, T T9, T rho) const
Calculates all derivatives (dY/dt) and the energy generation rate.
+
std::expected< std::unordered_map< fourdst::atomic::Species, double >, expectations::StaleEngineError > getSpeciesDestructionTimescales(const std::vector< double > &Y, double T9, double rho) const override
+
bool isStale(const NetIn &netIn) override
+
std::unique_ptr< screening::ScreeningModel > m_screeningModel
+
double calculateReverseRateTwoBodyDerivative(const reaction::Reaction &reaction, const double T9, const double reverseRate) const
+
StepDerivatives< T > calculateAllDerivatives(const std::vector< T > &Y_in, T T9, T rho) const
Calculates all derivatives (dY/dt) and the energy generation rate.
GraphEngine(const fourdst::composition::Composition &composition, const BuildDepthType=NetworkBuildDepth::Full)
Constructs a GraphEngine from a composition.
Abstract interface for evaluating nuclear partition functions.
Represents a "logical" reaction that aggregates rates from multiple sources.
Definition reaction.h:310
@@ -776,34 +756,33 @@ $(function(){initNavTree('engine__graph_8h_source.html',''); initResizable(true)
@ BARE
No screening applied. The screening factor is always 1.0.
-
CppAD::AD< double > ADDouble
Alias for CppAD AD type for double precision.
+
CppAD::AD< double > ADDouble
Alias for CppAD AD type for double precision.
std::variant< NetworkBuildDepth, int > BuildDepthType
Variant specifying either a predefined NetworkBuildDepth or a custom integer depth.
Definition building.h:37
std::vector< std::pair< size_t, size_t > > SparsityPattern
-
static constexpr double MIN_ABUNDANCE_THRESHOLD
Minimum abundance threshold below which species are ignored.
-
static constexpr double MIN_DENSITY_THRESHOLD
Minimum density threshold below which reactions are ignored.
-
static constexpr double MIN_JACOBIAN_THRESHOLD
Minimum value for Jacobian matrix entries.
-
static bool s_debug
+
static constexpr double MIN_ABUNDANCE_THRESHOLD
Minimum abundance threshold below which species are ignored.
+
static constexpr double MIN_DENSITY_THRESHOLD
Minimum density threshold below which reactions are ignored.
+
static constexpr double MIN_JACOBIAN_THRESHOLD
Minimum value for Jacobian matrix entries.
Defines classes for representing and managing nuclear reactions.
- - -
std::vector< int > product_powers
Powers of each unique product in the reverse reaction.
- - -
double reverse_symmetry_factor
Symmetry factor for reverse reactions.
- - -
std::vector< size_t > unique_product_indices
Unique product indices for reverse reactions.
- - -
const double kB
Boltzmann constant in erg/K.
-
const double u
Atomic mass unit in g.
-
const double Na
Avogadro's number.
-
const double c
Speed of light in cm/s.
+ + +
std::vector< int > product_powers
Powers of each unique product in the reverse reaction.
+ + +
double reverse_symmetry_factor
Symmetry factor for reverse reactions.
+ + +
std::vector< size_t > unique_product_indices
Unique product indices for reverse reactions.
+ + +
const double kB
Boltzmann constant in erg/K.
+
const double u
Atomic mass unit in g.
+
const double Na
Avogadro's number.
+
const double c
Speed of light in cm/s.
Captures the result of a network priming operation.
Definition reporting.h:67
Structure holding derivatives and energy generation for a network step.
diff --git a/docs/html/engine__multiscale_8cpp_source.html b/docs/html/engine__multiscale_8cpp_source.html index 68e165c9..1a0937b5 100644 --- a/docs/html/engine__multiscale_8cpp_source.html +++ b/docs/html/engine__multiscale_8cpp_source.html @@ -1842,7 +1842,7 @@ $(function(){initNavTree('engine__multiscale_8cpp_source.html',''); initResizabl
1642
1643}
Abstract class for engines supporting Jacobian and stoichiometry operations.
-
A reaction network engine that uses a graph-based representation.
+
A reaction network engine that uses a graph-based representation.
const std::vector< fourdst::atomic::Species > & getNetworkSpecies() const override
Gets the list of species in the network.
GraphEngine & m_baseEngine
The base engine to which this view delegates calculations.
PrimingReport primeEngine(const NetIn &netIn) override
Primes the engine with a specific species.
diff --git a/docs/html/engine__multiscale_8h_source.html b/docs/html/engine__multiscale_8h_source.html index d2859293..7c1da546 100644 --- a/docs/html/engine__multiscale_8h_source.html +++ b/docs/html/engine__multiscale_8h_source.html @@ -467,7 +467,7 @@ $(function(){initNavTree('engine__multiscale_8h_source.html',''); initResizable(
1116
Abstract class for engines supporting Jacobian and stoichiometry operations.
Abstract base class for a "view" of a reaction network engine.
-
A reaction network engine that uses a graph-based representation.
+
A reaction network engine that uses a graph-based representation.
GraphEngine & m_baseEngine
The base engine to which this view delegates calculations.
PrimingReport primeEngine(const NetIn &netIn) override
Primes the engine with a specific species.
MultiscalePartitioningEngineView(GraphEngine &baseEngine)
Constructs a MultiscalePartitioningEngineView.
diff --git a/docs/html/functions_func_v.html b/docs/html/functions_func_v.html index bb60d171..1390eb8f 100644 --- a/docs/html/functions_func_v.html +++ b/docs/html/functions_func_v.html @@ -102,7 +102,6 @@ $(function(){initNavTree('functions_func_v.html',''); initResizable(true); });
Here is a list of all functions with links to the classes they belong to:

- v -

    -
  • validateComposition() : gridfire::GraphEngine
  • validateConservation() : gridfire::GraphEngine
  • validateGroupsWithFluxAnalysis() : gridfire::MultiscalePartitioningEngineView
  • validateNetworkState() : gridfire::DefinedEngineView
  • diff --git a/docs/html/functions_v.html b/docs/html/functions_v.html index 3b036453..74ddadf5 100644 --- a/docs/html/functions_v.html +++ b/docs/html/functions_v.html @@ -102,7 +102,6 @@ $(function(){initNavTree('functions_v.html',''); initResizable(true); });
    Here is a list of all class members with links to the classes they belong to:

    - v -

      -
    • validateComposition() : gridfire::GraphEngine
    • validateConservation() : gridfire::GraphEngine
    • validateGroupsWithFluxAnalysis() : gridfire::MultiscalePartitioningEngineView
    • validateNetworkState() : gridfire::DefinedEngineView
    • diff --git a/docs/html/index.html b/docs/html/index.html index 9b2d16d1..1be05803 100644 --- a/docs/html/index.html +++ b/docs/html/index.html @@ -105,12 +105,12 @@ $(function(){initNavTree('index.html',''); initResizable(true); });

      GridFire Logo


      -

      GridFire is a C++ library designed to perform general nuclear network evolution using the Reaclib library. It is part of the larger SERiF project within the 4D-STAR collaboration.

      -

      Design Philosophy and Workflow: GridFire is architected to balance physical fidelity, computational efficiency, and extensibility when simulating complex nuclear reaction networks. Users begin by defining a composition, which is used to construct a full GraphEngine representation of the reaction network. To manage the inherent stiffness and multi-scale nature of these networks, GridFire employs a layered view strategy: partitioning algorithms isolate fast and slow processes, adaptive culling removes negligible reactions at runtime, and implicit solvers stably integrate the remaining stiff system. This modular pipeline allows researchers to tailor accuracy versus performance trade-offs, reuse common engine components, and extend screening or partitioning models without modifying core integration routines.

      +

      GridFire is a C++ library designed to perform general nuclear network evolution using the Reaclib library. It is part of the larger SERiF project within the 4D-STAR collaboration. GridFire is primarily focused on modeling the most relevant burning stages for stellar evolution modeling. Currently, there is limited support for inverse reactions. Therefore, GridFire has a limited set of tools to evolves a fusing plasma in NSE; however, this is not the primary focus of the library and has therefor not had significant development. For those interested in modeling super nova, neutron star mergers, or other high-energy astrophysical phenomena, we strongly recomment using SkyNet.

      +

      Design Philosophy and Workflow: GridFire is architected to balance physical fidelity, computational efficiency, and extensibility when simulating complex nuclear reaction networks. Users begin by defining a composition, which is used to construct a full GraphEngine representation of the reaction network. To manage the inherent stiffness and multiscale nature of these networks, GridFire employs a layered view strategy: partitioning algorithms isolate fast and slow processes, adaptive culling removes negligible reactions at runtime, and implicit solvers stably integrate the remaining stiff system. This modular pipeline allows researchers to tailor accuracy versus performance trade-offs, reuse common engine components, and extend screening or partitioning models without modifying core integration routines.

      Funding

      GridFire is a part of the 4D-STAR collaboration.

      -

      4D-STAR is funded by European Research Council (ERC) under the Horizon Europe programme (Synergy Grant agreement No. 101071505: 4D-STAR) Work for this project is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research.

      +

      4D-STAR is funded by European Research Council (ERC) under the Horizon Europe programme (Synergy Grant agreement No. 101071505: 4D-STAR) Work for this project is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council.

      Build and Installation Instructions

      @@ -123,8 +123,10 @@ Prerequisites

    • Boost libraries (>= 1.75.0) installed system-wide
    -

    Note: Boost is the only external library dependency; no additional libraries are required beyond a C++ compiler, Meson, Python, and Boost.

    -

    Windows is not supported at this time.

    +

    Note: Boost is the only external library dependency; no additional libraries are required beyond a C++ compiler, Meson, Python, and Boost.

    +
    +
    +

    Note: Windows is not supported at this time and there are no plans to support it in the future. Windows users are encouraged to use WSL2 or a Linux VM.

    Dependency Installation on Common Platforms

    @@ -161,13 +163,16 @@ Developer Workflow

    Code Architecture and Logical Flow

    -

    GridFire is organized into modular components that collaborate to simulate nuclear reaction networks with high fidelity:

    +

    GridFire is organized into a series of composable modules, each responsible for a specific aspect of nuclear reaction network modeling. The core components include:

    • Engine Module: Core interfaces and implementations (e.g., GraphEngine) that evaluate reaction network rate equations and energy generation.
    • Screening Module: Implements nuclear reaction screening corrections (WeakScreening, BareScreening, etc.) affecting reaction rates.
    • -
    • Rates Module: Parses and manages Reaclib reaction rate data, providing temperature- and density-dependent rate evaluations.
    • -
    • Python Interface: Exposes C++ functionality to Python, enabling rapid prototyping and integration into workflows.
    • +
    • Reaction Module: Parses and manages Reaclib reaction rate data, providing temperature- and density-dependent rate evaluations.
    • +
    • Partition Module: Implements partition functions (e.g., GroundStatePartitionFunction, RauscherThielemannPartitionFunction) to weight reaction rates based on nuclear properties.
    • +
    • Solver Module: Defines numerical integration strategies (e.g., DirectNetworkSolver) for solving the stiff ODE systems arising from reaction networks.
    • +
    • Python Interface: Exposes almost all C++ functionality to Python, allowing users to define compositions, configure engines, and run simulations directly from Python scripts.
    +

    Generally a user will start by selecting a base engine (currently we only offer GraphEngine), which constructs the full reaction network graph from a given composition. The user can then apply various engine views to adapt the network topology, such as partitioning fast and slow reactions, adaptively culling low-flow pathways, or priming the network with specific species. Finally, a numerical solver is selected to integrate the network over time, producing updated abundances and diagnostics.

    GraphEngine Configuration Options

    GraphEngine exposes runtime configuration methods to tailor network construction and rate evaluations:

    @@ -269,7 +274,7 @@ C++ Example: GraphEngine Initialization
    // Define a composition and initialize the engine
    fourdst::composition::Composition comp;
    gridfire::GraphEngine engine(comp);
    -
    A reaction network engine that uses a graph-based representation.
    +
    A reaction network engine that uses a graph-based representation.

C++ Example: Adaptive Network View

@@ -285,12 +290,31 @@ C++ Example: Adaptive Network View

Python Example

import gridfire
+
+
+
from fourdst.composition import Composition
+
+
symbols = ["H-1", ...]
+
X = [0.708, ...]
+
+
comp = Composition()
+
comp.registerSymbols(symbols)
+
comp.setMassFraction(X)
+
comp.finalize(true)
# Initialize GraphEngine with predefined composition
-
engine = gridfire.GraphEngine(composition="example_composition")
+
engine = gridfire.GraphEngine(comp)
+
netIn = gridfire.types.NetIn
+
netIn.composition = comp
+
netIn.tMax = 1e-3
+
netIn.temperature = 1.5e7
+
netIn.density = 1.6e2
+
netIn.dt0 = 1e-12
+
# Perform one integration step
-
engine.step(dt=1e-3)
-
print(engine.abundances)
-

+
netOut = engine.evaluate(netIn)
+
print(netOut)
+

More detailed python usage can be found here

+

Common Workflow Example

A representative workflow often composes multiple engine views to balance accuracy, stability, and performance when integrating stiff nuclear networks:

diff --git a/docs/html/md_docs_2static_2usage.html b/docs/html/md_docs_2static_2usage.html new file mode 100644 index 00000000..6a320b04 --- /dev/null +++ b/docs/html/md_docs_2static_2usage.html @@ -0,0 +1,273 @@ + + + + + + + +GridFire: GridFire Python Usage Guide + + + + + + + + + + + + + + + + + +
+
+

Variables

static bool gridfire::s_debug = false
 
static constexpr double gridfire::MIN_DENSITY_THRESHOLD = 1e-18
 Minimum density threshold below which reactions are ignored.
 
+ + + + + +
+
GridFire 0.0.1a +
+
General Purpose Nuclear Network
+
+
+ + + + + + + + +
+
+ +
+
+
+ +
+ +
+
+ + +
+
+
+
+
+
Loading...
+
Searching...
+
No Matches
+
+
+
+
+ +
+
GridFire Python Usage Guide
+
+
+

+

This tutorial walks you through installing GridFire’s Python bindings, choosing engines and views thoughtfully, running a simulation, and visualizing your results.

+
+

+1. Installation

+

+1.1 PyPI Release

+

The quickest way to get started is:

pip install gridfire
+

+1.2 Development from Source

+

If you want the cutting-edge features or need to hack the C++ backend:

git clone https://github.com/4DSTAR/GridFire.git
+
cd GridFire
+
# Create a virtualenv to isolate dependencies
+
python3 -m venv .venv && source .venv/bin/activate
+
+
# Install Python bindings (meson-python & pybind11 under the hood)
+
pip install .
+

You can also build manually with Meson (generally end users will not need to do this):

meson setup build-python
+
meson compile -C build_gridfire
+

+

+2. Why These Engines and Views?

+

GridFire’s design balances physical fidelity and performance. Here’s why we pick each component:

+
    +
  1. GraphEngine: Constructs the full reaction network from Reaclib rates and composition. Use this when:
      +
    • You need maximum physical accuracy (no reactions are omitted).
      +
    • +
    • You are exploring new burning pathways or validating against literature.
      +
    • +
    +
  2. +
  3. MultiscalePartitioningEngineView: Implements the Hix & Thielemann partitioning strategy:
      +
    • Fast reactions vs slow reactions are split onto separate kernels.
      +
    • +
    • This reduces stiffness by isolating processes on very different timescales.
      +
    • +
    • Choose when your network spans orders of magnitude in timescales (e.g., rapid proton captures vs. slow beta decays).
      +
    • +
    +
  4. +
  5. AdaptiveEngineView: Dynamically culls low-flow reactions at runtime:
      +
    • At each timestep, reactions with negligible contribution are temporarily removed.
      +
    • +
    • This greatly accelerates large networks without significant loss of accuracy.
      +
    • +
    • Ideal for long integrations where the active set evolves over time.
      +
    • +
    +
  6. +
  7. Leading-Edge Views:
    +
      +
    • NetworkPrimingEngineView to inject seed species and study ignition phenomena.
      +
    • +
    • DefinedEngineView to freeze the network to a user-specified subset (e.g., focus on the CNO cycle).
      +
    • +
    +
  8. +
+

By composing these views in sequence, you can tailor accuracy vs performance for your scientific question. Commonly one might use a flow like GraphEngine → Partitioning → Adaptive to capture both full-network physics and manageable stiffness.

+
+

+3. Step-by-Step Example

+

Adapted from tests/python/test.py. Comments explain each choice.

+
import matplotlib.pyplot as plt
+
from gridfire.engine import GraphEngine, MultiscalePartitioningEngineView, AdaptiveEngineView
+
from gridfire.solver import DirectNetworkSolver
+
from gridfire.type import NetIn
+
from fourdst.composition import Composition
+
+
# 1. Define your composition (e.g., M-dwarf surface mix)
+
symbols = ["H-1","He-3","He-4","C-12","N-14","O-16","Ne-20","Mg-24"]
+
abundances = [0.708,2.94e-5,0.276,0.003,0.0011,9.62e-3,1.62e-3,5.16e-4]
+
comp = Composition()
+
comp.registerSymbols(symbols)
+
comp.setMassFraction(symbols, abundances)
+
comp.finalize(normalize=True) # scale to total mass = 1
+
+
# 2. Prepare the NetIn object
+
netIn = NetIn()
+
netIn.composition = comp
+
netIn.temperature = 1.5e7 # Kelvin
+
netIn.density = 1.6e2 # g/cm³
+
netIn.tMax = 3.15e7 # seconds to evolve (~1yr)
+
netIn.dt0 = 1e-12 # initial timestep
+
+
# 3. Construct the full network engine
+
build_depth = 2 # shallow test network for speed; Full = -1
+
baseEngine = GraphEngine(comp, buildDepth=build_depth)
+
baseEngine.setUseReverseReactions(False) # At these temps we can turn off reverse reactions
+
+
# 4. Partition fast/slow reactions (reduces stiffness)
+
partitionedEngine = MultiscalePartitioningEngineView(baseEngine)
+
+
# 5. Adaptively cull negligible flows (improves speed)
+
adaptiveEngine = AdaptiveEngineView(partitionedEngine)
+
+
# 6. Choose an ODE solver (implicit Rosenbrock4)
+
solver = DirectNetworkSolver(adaptiveEngine, absTol=1e-12, relTol=1e-8)
+
+
# 7. Run the integration
+
+
netOut = solver.evaluate(netIn)
+
+
# 8. Final result:
+
print(f"Final H-1 fraction: {netOut.composition.getMassFraction('H-1')}")
+ +

Why these choices?
+

    +
  • buildDepth=2: In Emily’s preliminary tests, depth=2 captures key reaction loops without the overhead of a full network.
    +
  • +
  • Partition & Adaptive Views: Partitioning reduces stiffness between rapid charged-particle captures and slower β-decays; adaptive culling keeps the working set minimal.
    +
  • +
  • Implicit solver: Rosenbrock4 handles stiff systems robustly, letting you push to longer tMax.
  • +
+
+

+4. Visualizing Reaction Networks

+

GridFire engines and views provide built-in export methods for Graphviz DOT and CSV formats:

+
# Export the base network to DOT for Graphviz
+
baseEngine.exportToDot('network.dot')
+
# Optionally generate a PNG (shell):
+
# dot -Tpng network.dot -o network.png
+
+
# Export a partitioned view of the network
+
partitionedEngine.exportToDot('partitioned.dot')
+
+
# Export to CSV for programmatic analysis
+
baseEngine.exportToCSV('network.csv')
+

You can then use tools like Graphviz or pandas:

# Convert DOT to PNG
+
dot -Tpng network.dot -o network.png
+
import pandas as pd
+
+
# Load and inspect reaction list
+
df = pd.read_csv('network.csv')
+
print(df.head())
+

For time-series data, record intermediates with an observer and save with pandas or numpy:

import pandas as pd
+
+
# Build a DataFrame of time vs species fraction
+
df = pd.DataFrame({'time': t, 'H-1': X_H1})
+
df.to_csv('H1_evolution.csv', index=False)
+

Then plot in pandas or Excel for custom figures.

+
+

+5. Beyond the Basics

+
    +
  • Custom Partition Functions: In Python, subclass gridfire.partition.PartitionFunction, override evaluate, supports, and clone to implement new weighting schemes.
    +
  • +
  • Parameter Studies: Loop over buildDepth, solver tolerances, or initial compositions to get a sense of the sensitity of the network to input conditions or build a monte carlo grid.
    +
  • +
  • Error Handling:
    try:
    +
    results = solver.evaluate(netIn)
    +
    except GridFireRuntimeError as e:
    +
    print('Fatal engine error:', e)
    +
    except GridFireValueError as e:
    +
    print('Invalid input:', e)
    +
  • +
+

For full API details, consult the docstrings in src/python/ and the C++ implementation in src/lib/. Enjoy exploring nuclear astrophysics with GridFire!

+
+
+
+ + + + diff --git a/docs/html/menudata.js b/docs/html/menudata.js index 08f6b909..2b8393a0 100644 --- a/docs/html/menudata.js +++ b/docs/html/menudata.js @@ -24,6 +24,7 @@ */ var menudata={children:[ {text:"Main Page",url:"index.html"}, +{text:"Related Pages",url:"pages.html"}, {text:"Namespaces",url:"namespaces.html",children:[ {text:"Namespace List",url:"namespaces.html"}, {text:"Namespace Members",url:"namespacemembers.html",children:[ diff --git a/docs/html/namespacegridfire.html b/docs/html/namespacegridfire.html index e97a9157..5e084d1c 100644 --- a/docs/html/namespacegridfire.html +++ b/docs/html/namespacegridfire.html @@ -265,8 +265,6 @@ Functions - - @@ -300,7 +298,7 @@ Variables

Alias for CppAD AD type for double precision.

This alias simplifies the use of the CppAD automatic differentiation type.

-

Definition at line 45 of file engine_graph.h.

+

Definition at line 44 of file engine_graph.h.

@@ -824,7 +822,7 @@ Resolved integer depth from maxLayers must not be zero.

Minimum abundance threshold below which species are ignored.

Species with abundances below this threshold are treated as zero in reaction rate calculations. This helps to improve performance by avoiding unnecessary calculations for trace species.

-

Definition at line 67 of file engine_graph.h.

+

Definition at line 66 of file engine_graph.h.

@@ -851,7 +849,7 @@ Resolved integer depth from maxLayers must not be zero.

Minimum density threshold below which reactions are ignored.

Reactions are not calculated if the density falls below this threshold. This helps to improve performance by avoiding unnecessary calculations in very low-density regimes.

-

Definition at line 58 of file engine_graph.h.

+

Definition at line 57 of file engine_graph.h.

@@ -878,7 +876,7 @@ Resolved integer depth from maxLayers must not be zero.

Minimum value for Jacobian matrix entries.

Jacobian matrix entries with absolute values below this threshold are treated as zero to maintain sparsity and improve performance.

-

Definition at line 75 of file engine_graph.h.

+

Definition at line 74 of file engine_graph.h.

@@ -923,30 +921,6 @@ Resolved integer depth from maxLayers must not be zero.

Definition at line 47 of file reporting.h.

- - - -

◆ s_debug

- -
-
-

Variables

static bool s_debug = false
 
static constexpr double MIN_DENSITY_THRESHOLD = 1e-18
 Minimum density threshold below which reactions are ignored.
 
- - - - -
- - - - -
bool gridfire::s_debug = false
-
-static
-
- -

Definition at line 39 of file engine_graph.h.

-
diff --git a/docs/html/namespacegridfire.js b/docs/html/namespacegridfire.js index 9719655d..11e12427 100644 --- a/docs/html/namespacegridfire.js +++ b/docs/html/namespacegridfire.js @@ -70,6 +70,5 @@ var namespacegridfire = [ "MIN_DENSITY_THRESHOLD", "namespacegridfire.html#ada3c137c014ecd8d06200fea2d1a9f50", null ], [ "MIN_JACOBIAN_THRESHOLD", "namespacegridfire.html#ae01b1738df1921db565bcbd68dd6cf64", null ], [ "PrimingReportStatusStrings", "namespacegridfire.html#a02be158966bf82a91b159b7a962c3fa5", null ], - [ "s_debug", "namespacegridfire.html#afd6f117eb2da3bab3873edc09d0926cf", null ], [ "s_operator_parens_called", "namespacegridfire.html#a8b632637f62614f509cde0e404a79054", null ] ]; \ No newline at end of file diff --git a/docs/html/namespacemembers.html b/docs/html/namespacemembers.html index 990e7d87..24eb0393 100644 --- a/docs/html/namespacemembers.html +++ b/docs/html/namespacemembers.html @@ -215,7 +215,6 @@ $(function(){initNavTree('namespacemembers.html',''); initResizable(true); });

- s -

  • s_all_reaclib_reactions_ptr : gridfire::reaclib
  • -
  • s_debug : gridfire
  • s_initialized : gridfire::reaclib
  • s_operator_parens_called : gridfire
  • ScreeningType : gridfire::screening
  • diff --git a/docs/html/namespacemembers_vars.html b/docs/html/namespacemembers_vars.html index b5126642..cc5450b0 100644 --- a/docs/html/namespacemembers_vars.html +++ b/docs/html/namespacemembers_vars.html @@ -108,7 +108,6 @@ $(function(){initNavTree('namespacemembers_vars.html',''); initResizable(true);
  • PrimingReportStatusStrings : gridfire
  • RT_TEMPERATURE_GRID_T9 : gridfire::partition
  • s_all_reaclib_reactions_ptr : gridfire::reaclib
  • -
  • s_debug : gridfire
  • s_initialized : gridfire::reaclib
  • s_operator_parens_called : gridfire
  • stringToBasePartitionType : gridfire::partition
  • diff --git a/docs/html/navtreedata.js b/docs/html/navtreedata.js index 7a474bfa..6ece5967 100644 --- a/docs/html/navtreedata.js +++ b/docs/html/navtreedata.js @@ -25,7 +25,7 @@ var NAVTREE = [ [ "GridFire", "index.html", [ - [ "Namespaces", "namespaces.html", [ + [ "GridFire Python Usage Guide", "md_docs_2static_2usage.html", [ [ "Funding", "index.html#autotoc_md1", null ], [ "Build and Installation Instructions", "index.html#autotoc_md2", [ [ "Prerequisites", "index.html#autotoc_md3", null ], @@ -52,6 +52,16 @@ var NAVTREE = ] ], [ "Common Workflow Example", "index.html#autotoc_md21", null ], [ "Related Projects", "index.html#autotoc_md22", null ], + [ "Installation", "md_docs_2static_2usage.html#autotoc_md25", [ + [ "1.1 PyPI Release", "md_docs_2static_2usage.html#autotoc_md26", null ], + [ "1.2 Development from Source", "md_docs_2static_2usage.html#autotoc_md27", null ] + ] ], + [ "Why These Engines and Views?", "md_docs_2static_2usage.html#autotoc_md29", null ], + [ "Step-by-Step Example", "md_docs_2static_2usage.html#autotoc_md31", null ], + [ "Visualizing Reaction Networks", "md_docs_2static_2usage.html#autotoc_md33", null ], + [ "Beyond the Basics", "md_docs_2static_2usage.html#autotoc_md35", null ] + ] ], + [ "Namespaces", "namespaces.html", [ [ "Namespace List", "namespaces.html", "namespaces_dup" ], [ "Namespace Members", "namespacemembers.html", [ [ "All", "namespacemembers.html", null ], @@ -94,12 +104,12 @@ var NAVTREEINDEX = [ "_2_users_2tboudreaux_2_programming_24_d_s_t_a_r_2_grid_fire_2src_2include_2gridfire_2engine_2engine_approx8_8h-example.html", "classgridfire_1_1_dynamic_engine.html#afa108dd5227dbb1045e90d7b3bd8b84f", -"classgridfire_1_1_multiscale_partitioning_engine_view.html#a716d7357e944e8394d8b8e0b5e7625eb", -"classgridfire_1_1io_1_1_m_e_s_a_network_file_parser.html#ab7f82597abf17f16c401bcdf528bd099", -"classgridfire_1_1reaction_1_1_templated_reaction_set.html#a54c8cd7c34564277fe28eefc623f666e", -"functions_k.html", 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    static constexpr double MIN_ABUNDANCE_THRESHOLD
    Minimum abundance threshold below which species are ignored.
    +
    static constexpr double MIN_ABUNDANCE_THRESHOLD
    Minimum abundance threshold below which species are ignored.
    diff --git a/docs/html/structgridfire_1_1_graph_engine_1_1_precomputed_reaction.html b/docs/html/structgridfire_1_1_graph_engine_1_1_precomputed_reaction.html index 76b05e84..10eba120 100644 --- a/docs/html/structgridfire_1_1_graph_engine_1_1_precomputed_reaction.html +++ b/docs/html/structgridfire_1_1_graph_engine_1_1_precomputed_reaction.html @@ -132,7 +132,7 @@ Public Attributes

    Detailed Description

    -

    Definition at line 385 of file engine_graph.h.

    +

    Definition at line 384 of file engine_graph.h.

    Member Data Documentation

    ◆ affected_species_indices

    @@ -146,7 +146,7 @@ Public Attributes
-

Definition at line 391 of file engine_graph.h.

+

Definition at line 390 of file engine_graph.h.

@@ -164,7 +164,7 @@ Public Attributes

Powers of each unique product in the reverse reaction.

-

Definition at line 396 of file engine_graph.h.

+

Definition at line 395 of file engine_graph.h.

@@ -180,7 +180,7 @@ Public Attributes
-

Definition at line 389 of file engine_graph.h.

+

Definition at line 388 of file engine_graph.h.

@@ -196,7 +196,7 @@ Public Attributes
-

Definition at line 387 of file engine_graph.h.

+

Definition at line 386 of file engine_graph.h.

@@ -214,7 +214,7 @@ Public Attributes

Symmetry factor for reverse reactions.

-

Definition at line 397 of file engine_graph.h.

+

Definition at line 396 of file engine_graph.h.

@@ -230,7 +230,7 @@ Public Attributes
-

Definition at line 392 of file engine_graph.h.

+

Definition at line 391 of file engine_graph.h.

@@ -246,7 +246,7 @@ Public Attributes
-

Definition at line 390 of file engine_graph.h.

+

Definition at line 389 of file engine_graph.h.

@@ -264,7 +264,7 @@ Public Attributes

Unique product indices for reverse reactions.

-

Definition at line 395 of file engine_graph.h.

+

Definition at line 394 of file engine_graph.h.

@@ -280,7 +280,7 @@ Public Attributes
-

Definition at line 388 of file engine_graph.h.

+

Definition at line 387 of file engine_graph.h.

diff --git a/docs/html/structgridfire_1_1_graph_engine_1_1constants.html b/docs/html/structgridfire_1_1_graph_engine_1_1constants.html index 48ca8284..d032d9a9 100644 --- a/docs/html/structgridfire_1_1_graph_engine_1_1constants.html +++ b/docs/html/structgridfire_1_1_graph_engine_1_1constants.html @@ -123,7 +123,7 @@ Public Attributes

Detailed Description

-

Definition at line 400 of file engine_graph.h.

+

Definition at line 399 of file engine_graph.h.

Member Data Documentation

◆ c

@@ -139,7 +139,7 @@ Public Attributes

Speed of light in cm/s.

-

Definition at line 403 of file engine_graph.h.

+

Definition at line 402 of file engine_graph.h.

@@ -157,7 +157,7 @@ Public Attributes

Boltzmann constant in erg/K.

-

Definition at line 404 of file engine_graph.h.

+

Definition at line 403 of file engine_graph.h.

@@ -175,7 +175,7 @@ Public Attributes

Avogadro's number.

-

Definition at line 402 of file engine_graph.h.

+

Definition at line 401 of file engine_graph.h.

@@ -193,7 +193,7 @@ Public Attributes

Atomic mass unit in g.

-

Definition at line 401 of file engine_graph.h.

+

Definition at line 400 of file engine_graph.h.

diff --git a/docs/html/usage_8md.html b/docs/html/usage_8md.html new file mode 100644 index 00000000..ed4ffe7c --- /dev/null +++ b/docs/html/usage_8md.html @@ -0,0 +1,115 @@ + + + + + + + +GridFire: docs/static/usage.md File Reference + + + + + + + + + + + + + + + + + +
+
+ + + + + + +
+
GridFire 0.0.1a +
+
General Purpose Nuclear Network
+
+
+ + + + + + + + +
+
+ +
+
+
+ +
+ +
+
+ + +
+
+
+
+
+
Loading...
+
Searching...
+
No Matches
+
+
+
+
+ +
+
docs/static/usage.md File Reference
+
+
+
+
+ + + + diff --git a/docs/static/mainpage.md b/docs/static/mainpage.md index 19e9e95e..4fc59d7d 100644 --- a/docs/static/mainpage.md +++ b/docs/static/mainpage.md @@ -216,13 +216,33 @@ gridfire::AdaptiveEngineView adaptiveView(baseEngine); ### Python Example ```python import gridfire + + +from fourdst.composition import Composition + +symbols = ["H-1", ...] +X = [0.708, ...] + +comp = Composition() +comp.registerSymbols(symbols) +comp.setMassFraction(X) +comp.finalize(true) # Initialize GraphEngine with predefined composition -engine = gridfire.GraphEngine(composition="example_composition") +engine = gridfire.GraphEngine(comp) +netIn = gridfire.types.NetIn +netIn.composition = comp +netIn.tMax = 1e-3 +netIn.temperature = 1.5e7 +netIn.density = 1.6e2 +netIn.dt0 = 1e-12 + # Perform one integration step -engine.step(dt=1e-3) -print(engine.abundances) +netOut = engine.evaluate(netIn) +print(netOut) ``` +More detailed python usage can be found [here](usage.md) + ## Common Workflow Example A representative workflow often composes multiple engine views to balance accuracy, stability, and performance when integrating stiff nuclear networks: @@ -277,4 +297,4 @@ GridFire integrates with and builds upon several key 4D-STAR libraries: - [libcomposition](https://github.com/4D-STAR/libcomposition) ([docs](https://4d-star.github.io/libcomposition/)): Composition management toolkit. - [libconfig](https://github.com/4D-STAR/libconfig): Configuration file parsing utilities. - [liblogging](https://github.com/4D-STAR/liblogging): Flexible logging framework. -- [libconstants](https://github.com/4D-STAR/libconstants): Physical constants \ No newline at end of file +- [libconstants](https://github.com/4D-STAR/libconstants): Physical constants diff --git a/docs/static/usage.md b/docs/static/usage.md new file mode 100644 index 00000000..6ed2a1a3 --- /dev/null +++ b/docs/static/usage.md @@ -0,0 +1,164 @@ +# GridFire Python Usage Guide + +This tutorial walks you through installing GridFire’s Python bindings, choosing engines and views thoughtfully, running a simulation, and visualizing your results. + +--- +## 1. Installation + +### 1.1 PyPI Release +The quickest way to get started is: +```bash +pip install gridfire +``` + +### 1.2 Development from Source +If you want the cutting-edge features or need to hack the C++ backend: +```bash +git clone https://github.com/4DSTAR/GridFire.git +cd GridFire +# Create a virtualenv to isolate dependencies +python3 -m venv .venv && source .venv/bin/activate + +# Install Python bindings (meson-python & pybind11 under the hood) +pip install . +``` + +You can also build manually with Meson (generally end users will not need to do this): +```bash +meson setup build-python +meson compile -C build_gridfire +``` + +--- +## 2. Why These Engines and Views? +GridFire’s design [balances physical fidelity and performance](../README.md). Here’s why we pick each component: + +1. **GraphEngine**: Constructs the **full** reaction network from Reaclib rates and composition. Use this when: + - You need maximum physical accuracy (no reactions are omitted). + - You are exploring new burning pathways or validating against literature. + +2. **MultiscalePartitioningEngineView**: Implements the Hix & Thielemann partitioning strategy: + - **Fast reactions** vs **slow reactions** are split onto separate kernels. + - This reduces stiffness by isolating processes on very different timescales. + - Choose when your network spans orders of magnitude in timescales (e.g., rapid proton captures vs. slow beta decays). + +3. **AdaptiveEngineView**: Dynamically culls low-flow reactions at runtime: + - At each timestep, reactions with negligible contribution are temporarily removed. + - This greatly accelerates large networks without significant loss of accuracy. + - Ideal for long integrations where the active set evolves over time. + +4. **Leading-Edge Views**: + - `NetworkPrimingEngineView` to inject seed species and study ignition phenomena. + - `DefinedEngineView` to freeze the network to a user-specified subset (e.g., focus on the CNO cycle). + +By composing these views in sequence, you can tailor accuracy vs performance for your scientific question. Commonly one might use a flow like **GraphEngine → Partitioning → Adaptive** to capture both full-network physics and manageable stiffness. + +--- +## 3. Step-by-Step Example +Adapted from [`tests/python/test.py`](../../tests/python/test.py). Comments explain each choice. + +```python +import matplotlib.pyplot as plt +from gridfire.engine import GraphEngine, MultiscalePartitioningEngineView, AdaptiveEngineView +from gridfire.solver import DirectNetworkSolver +from gridfire.type import NetIn +from fourdst.composition import Composition + +# 1. Define your composition (e.g., M-dwarf surface mix) +symbols = ["H-1","He-3","He-4","C-12","N-14","O-16","Ne-20","Mg-24"] +abundances = [0.708,2.94e-5,0.276,0.003,0.0011,9.62e-3,1.62e-3,5.16e-4] +comp = Composition() +comp.registerSymbols(symbols) +comp.setMassFraction(symbols, abundances) +comp.finalize(normalize=True) # scale to total mass = 1 + +# 2. Prepare the NetIn object +netIn = NetIn() +netIn.composition = comp +netIn.temperature = 1.5e7 # Kelvin +netIn.density = 1.6e2 # g/cm³ +netIn.tMax = 3.15e7 # seconds to evolve (~1yr) +netIn.dt0 = 1e-12 # initial timestep + +# 3. Construct the full network engine +build_depth = 2 # shallow test network for speed; Full = -1 +baseEngine = GraphEngine(comp, buildDepth=build_depth) +baseEngine.setUseReverseReactions(False) # At these temps we can turn off reverse reactions + +# 4. Partition fast/slow reactions (reduces stiffness) +partitionedEngine = MultiscalePartitioningEngineView(baseEngine) + +# 5. Adaptively cull negligible flows (improves speed) +adaptiveEngine = AdaptiveEngineView(partitionedEngine) + +# 6. Choose an ODE solver (implicit Rosenbrock4) +solver = DirectNetworkSolver(adaptiveEngine, absTol=1e-12, relTol=1e-8) + +# 7. Run the integration + +netOut = solver.evaluate(netIn) + +# 8. Final result: +print(f"Final H-1 fraction: {netOut.composition.getMassFraction('H-1')}") +``` + +**Why these choices?** +- **buildDepth=2**: In Emily’s preliminary tests, depth=2 captures key reaction loops without the overhead of a full network. +- **Partition & Adaptive Views**: Partitioning reduces stiffness between rapid charged-particle captures and slower β-decays; adaptive culling keeps the working set minimal. +- **Implicit solver**: Rosenbrock4 handles stiff systems robustly, letting you push to longer `tMax`. + +--- +## 4. Visualizing Reaction Networks + +GridFire engines and views provide built-in export methods for Graphviz DOT and CSV formats: + +```python +# Export the base network to DOT for Graphviz +baseEngine.exportToDot('network.dot') +# Optionally generate a PNG (shell): +# dot -Tpng network.dot -o network.png + +# Export a partitioned view of the network +partitionedEngine.exportToDot('partitioned.dot') + +# Export to CSV for programmatic analysis +baseEngine.exportToCSV('network.csv') +``` +You can then use tools like Graphviz or pandas: +```bash +# Convert DOT to PNG +dot -Tpng network.dot -o network.png +``` +```python +import pandas as pd + +# Load and inspect reaction list +df = pd.read_csv('network.csv') +print(df.head()) +``` +For time-series data, record intermediates with an observer and save with pandas or numpy: +```python +import pandas as pd + +# Build a DataFrame of time vs species fraction +df = pd.DataFrame({'time': t, 'H-1': X_H1}) +df.to_csv('H1_evolution.csv', index=False) +``` +Then plot in pandas or Excel for custom figures. + +--- +## 5. Beyond the Basics + +- **Custom Partition Functions**: In Python, subclass `gridfire.partition.PartitionFunction`, override `evaluate`, `supports`, and `clone` to implement new weighting schemes. +- **Parameter Studies**: Loop over `buildDepth`, solver tolerances, or initial compositions to get a sense of the sensitity of the network to input conditions or build a monte carlo grid. +- **Error Handling**: + ```python + try: + results = solver.evaluate(netIn) + except GridFireRuntimeError as e: + print('Fatal engine error:', e) + except GridFireValueError as e: + print('Invalid input:', e) + ``` + +For full API details, consult the docstrings in `src/python/` and the C++ implementation in `src/lib/`. Enjoy exploring nuclear astrophysics with GridFire!