<ahref="#pub-methods">Public Member Functions</a>|
<ahref="classgridfire_1_1engine_1_1_dynamic_engine-members.html">List of all members</a></div>
<divclass="headertitle"><divclass="title">gridfire::engine::DynamicEngine Class Reference<spanclass="mlabels"><spanclass="mlabel abstract">abstract</span></span></div></div>
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<divclass="contents">
<p>Abstract class for engines supporting Jacobian and stoichiometry operations.
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Collaboration diagram for gridfire::engine::DynamicEngine:</div>
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<trclass="memdesc:a53276f09346b531f8676db355e1219eb"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Generate the Jacobian matrix for the current state. <br/></td></tr>
<trclass="memdesc:a15d53dac8b622a3b7d0f928a3995dbde"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Generate the Jacobian matrix for the current state using a subset of active species. <br/></td></tr>
<trclass="memdesc:a51d55a21be28e372021b2b8e5ecdc551"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Generate the Jacobian matrix for the current state with a specified sparsity pattern. <br/></td></tr>
<trclass="memdesc:a5e2c45a3e415b53e41def8f743f93464"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Generate the stoichiometry matrix for the network. <br/></td></tr>
<trclass="memdesc:a5ce6ff370e3f0964c6b2688fb3f4bb7e"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get an entry from the stoichiometry matrix. <br/></td></tr>
<trclass="memdesc:aa57fa5e58b98a03fba31bcddda8001d4"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Calculate the molar reaction flow for a given reaction. <br/></td></tr>
<trclass="memdesc:ada6a1295a92c2aede841672ecae0cede"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Calculate the derivatives of the energy generation rate with respect to T and rho. <br/></td></tr>
<trclass="memdesc:a26b59a4c7622bf820c0eeec6a7522aa8"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get the set of logical reactions in the network. <br/></td></tr>
<trclass="memdesc:ab321170954bffc53b1bedaf54f6976be"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Set the reactions for the network. <br/></td></tr>
<trclass="memdesc:aef6ed91d922c0b1733fd7835e99d0efe"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Compute timescales for all species in the network. <br/></td></tr>
<trclass="memdesc:aefc5d0f7842b27a108ba1e4ca346e9a0"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Compute destruction timescales for all species in the network. <br/></td></tr>
<trclass="memdesc:a8dd85442ec54f20d91743c72364e36ff"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Update the internal state of the engine. <br/></td></tr>
<trclass="memdesc:a79423b9f67b4cac702547b4f1d8bd14c"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Check if the engine's internal state is stale. <br/></td></tr>
<trclass="memdesc:a50e76977d0dc3cc23d52b51842d35003"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Set the electron screening model. <br/></td></tr>
<trclass="memdesc:a24103027a38e02d4342161164554d332"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get the current electron screening model. <br/></td></tr>
<trclass="memdesc:ac0f40017603e8e6887b75dc7360d7c5e"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get the index of a species in the network. <br/></td></tr>
<trclass="memdesc:aa9d55b81c1963113aad86aa60c19676f"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Map a <aclass="el"href="structgridfire_1_1_net_in.html">NetIn</a> object to a vector of molar abundances. <br/></td></tr>
<trclass="memdesc:a70e270bb50910c0055a75575c1ef1e95"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Prime the engine with initial conditions. <br/></td></tr>
<trclass="memdesc:ac5a0def6b6af0bd93bf9057c25f048ff"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get the depth of the network. <br/></td></tr>
<trclass="memdesc:a2444b9ed3bc61920ce23c546444269e4"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Rebuild the network with a specified depth. <br/></td></tr>
<trclass="memdesc:a41877719ae5e8de53c1692c7cf9bfbfc"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Recursively collect composition from current engine and any sub engines if they exist. <br/></td></tr>
<trclass="memdesc:a8aebefad50c1aa34207e118e92d7ccf0"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get the status of a species in the network. <br/></td></tr>
<trclass="inherit_header pub_methods_classgridfire_1_1engine_1_1_engine"><tdcolspan="2"onclick="javascript:dynsection.toggleInherit('pub_methods_classgridfire_1_1engine_1_1_engine')"><imgsrc="closed.png"alt="-"/> Public Member Functions inherited from <aclass="el"href="classgridfire_1_1engine_1_1_engine.html">gridfire::engine::Engine</a></td></tr>
<trclass="memdesc:a3263c3fde2509d5d8ec4da3b6e946c48 inherit pub_methods_classgridfire_1_1engine_1_1_engine"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Get the list of species in the network. <br/></td></tr>
<trclass="memdesc:a764fc091c72c12c8529105d7c96badb2 inherit pub_methods_classgridfire_1_1engine_1_1_engine"><tdclass="mdescLeft"> </td><tdclass="mdescRight">Calculate the right-hand side (dY/dt) and energy generation. <br/></td></tr>
<divclass="textblock"><p>Abstract class for engines supporting Jacobian and stoichiometry operations. </p>
<p>Extends <aclass="el"href="classgridfire_1_1engine_1_1_engine.html"title="Abstract base class for a reaction network engine.">Engine</a> with additional methods for:</p><ul>
<li>Generating and accessing the Jacobian matrix (for implicit solvers).</li>
<li>Generating and accessing the stoichiometry matrix.</li>
<li>Calculating molar reaction flows for individual reactions.</li>
<li>Accessing the set of logical reactions in the network.</li>
<li>Computing timescales for each species.</li>
</ul>
<p>Intended usage: Derive from this class to implement engines that support advanced solver features such as implicit integration, sensitivity analysis, QSE (Quasi-Steady-State Equilibrium) handling, and more. Generally this will be the main engine type </p>
</div><h2class="groupheader">Member Function Documentation</h2>
<p>Calculate the derivatives of the energy generation rate with respect to T and rho. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>Composition object containing current abundances. </td></tr>
<tr><tdclass="paramname">T9</td><td>Temperature in units of 10^9 K. </td></tr>
<tr><tdclass="paramname">rho</td><td>Density in g/cm^3. </td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd><aclass="el"href="structgridfire_1_1engine_1_1_energy_derivatives.html"title="Structure holding derivatives of energy generation rate with respect to T and rho.">EnergyDerivatives</a> containing dEps/dT and dEps/dRho.</dd></dl>
<p>This method computes the partial derivatives of the specific nuclear energy generation rate with respect to temperature and density for the current state. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a17bbc9c0d480a8533acb193cb9a46fea">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a2a866a7ba9572d36efab8efe72a063f5">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#ac7e4624ed6eee72e7a8df42381d098bb">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#ac720fcea2f0304c3d7e7ba8a6dfb84da">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a6832a7898da51017a20f578e33cba729">PyDynamicEngine</a>.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a5bd0174105e836dd98c71ab495357e5b">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a2f0ad1febc467bce87b5c6ad29b059fb">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#aaff9cdc04ca01e7c927d36476bcf5da4">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#af030c9bd6a95686a09429b4619ad188c">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a8facba88b6df6e016ce53a0ff3cff125">PyDynamicEngine</a>.</p>
<p>Recursively collect composition from current engine and any sub engines if they exist. </p>
<p>If species i is defined in comp and in any sub engine or self composition then the molar abundance of species i in the returned composition will be that defined in comp. If there are species defined in sub engine compositions which are not defined in comp then their molar abundances will be based on the reported values from each sub engine. </p><dlclass="section note"><dt>Note</dt><dd>It is up to each engine to decide how to handle filling in the return composition. </dd>
<dd>
These methods return an unfinalized composition which must then be finalized by the caller </dd></dl>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>Input composition to "normalize". </td></tr>
<tr><tdclass="paramname">T9</td><td></td></tr>
<tr><tdclass="paramname">rho</td><td></td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd>An updated composition which is a superset of comp. This may contain species which were culled, for example, by either QSE partitioning or reaction flow rate culling </dd></dl>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a77d4c08eecfad5cc414161d0fc8db946">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a25dc44af1a58561b665103b16abe9bbc">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#ae9d4d99c791876c012697fe5a0ba06c8">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a97d9616558f681ad010ee452394f3519">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a239826d90cb5db236e68230f7ac84bcb">PyDynamicEngine</a>.</p>
<p>Generate the Jacobian matrix for the current state. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>Composition object containing current abundances. </td></tr>
<tr><tdclass="paramname">T9</td><td>Temperature in units of 10^9 K. </td></tr>
<tr><tdclass="paramname">rho</td><td>Density in g/cm^3.</td></tr>
</table>
</dd>
</dl>
<p>This method must compute and store the Jacobian matrix (∂(dY/dt)_i/∂Y_j) for the current state. The matrix can then be accessed via getJacobianMatrixEntry(). </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a2a44dfae512b370bad6b977330e0636a">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a4d90439d99da61107d95319b970760bc">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a9ca013f203d7a3ef9d1b9ee4b2982cb0">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a8950fb9c0c36684538805de4f0acf82e">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a298f700c647d2c3973d2a35d370c823e">PyDynamicEngine</a>.</p>
<p>Generate the Jacobian matrix for the current state with a specified sparsity pattern. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>Composition object containing current abundances. </td></tr>
<tr><tdclass="paramname">T9</td><td>Temperature in units of 10^9 K. </td></tr>
<tr><tdclass="paramname">rho</td><td>Density in g/cm^3. </td></tr>
<tr><tdclass="paramname">sparsityPattern</td><td>The sparsity pattern to use for the Jacobian matrix.</td></tr>
</table>
</dd>
</dl>
<p>This method must compute and store the Jacobian matrix (∂(dY/dt)_i/∂Y_j) for the current state using automatic differentiation, taking into account the provided sparsity pattern. The matrix can then be accessed via <code>getJacobianMatrixEntry()</code>.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#ae894f46c67a8b8e02b8988a6b73dc9e5">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a1de5867a0e633de0d0d96ac4fbb141e5">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#ac4f9cd4e2304f681dd9af0f7b751cb81">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a64b6e7e5794cc42edf72899d348d15af">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a204643754cac3cf37c550ecd32f659fe">PyDynamicEngine</a>.</p>
<p>Generate the Jacobian matrix for the current state using a subset of active species. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>Composition object containing current abundances. </td></tr>
<tr><tdclass="paramname">T9</td><td>Temperature in units of 10^9 K. </td></tr>
<tr><tdclass="paramname">rho</td><td>Density in g/cm^3. </td></tr>
<tr><tdclass="paramname">activeSpecies</td><td>The set of species to include in the Jacobian calculation.</td></tr>
</table>
</dd>
</dl>
<p>This method must compute and store the Jacobian matrix (∂(dY/dt)_i/∂Y_j) for the current state, considering only the specified subset of active species. The matrix can then be accessed via getJacobianMatrixEntry(). </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a1b7b3b0b449d0859d57f99188cdd83d6">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a4966f8cbc859ce2a8a465516d0c0abd0">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#acc28ff627d46d8d4066a1acf830cbe27">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#aae6c00cff4f7a992513d1e9481436f8f">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a2b1c054b250abccc2af9a7275c68df4a">PyDynamicEngine</a>.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a754445722193f11ae534b7c0afa9b8aa">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#af4049e5570bd143d41cab1d4005b6824">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a2221feee40542efa1c07f01225bd3828">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a552fa7e1f4e066fa577c55500e782014">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a2066649ca11a869c054079ea12d8d0e9">PyDynamicEngine</a>.</p>
<dlclass="section return"><dt>Returns</dt><dd>The depth of the network, which may indicate the level of detail or complexity in the reaction network.</dd></dl>
<p>This method is intended to provide information about the network's structure, such as how many layers of reactions or species are present. It can be useful for diagnostics and understanding the network's complexity. </p>
<p>Reimplemented in <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#ab29d6c4a7c789cf3d75767833c80c658">gridfire::engine::GraphEngine</a>, and <aclass="el"href="class_py_dynamic_engine.html#a541cf022fe3253279f8f1309c10556d7">PyDynamicEngine</a>.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a722ea6e07d46f739c29ad681c7500f8c">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a81732c1b2d08451849c1ddf833246892">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a749cc482a707cb3a38bdd5de894716e2">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a9dc9de4359beb704b94024f159ae619d">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a1d5143640666631501cf229bc491516e">PyDynamicEngine</a>.</p>
<divclass="ttc"id="anamespacegridfire_1_1screening_html_aa82aafbc4f8c28d0a75b60798e3a7d25"><divclass="ttname"><ahref="namespacegridfire_1_1screening.html#aa82aafbc4f8c28d0a75b60798e3a7d25">gridfire::screening::ScreeningType</a></div><divclass="ttdeci">ScreeningType</div><divclass="ttdoc">Enumerates the available plasma screening models.</div><divclass="ttdef"><b>Definition</b> screening_types.h:15</div></div>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#acbd5b36262fa7d40f3274f4be6f0b8f6">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a413b111f6a643d7aecbae01dd0f82640">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a62c6f3bebe931bcd412fb492deb634a5">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#accdd09720d44cc5efb1ee267706f0500">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#ab4cfdca5e15957c5cef75ffa6dedeee5">PyDynamicEngine</a>.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a420666d17650736e20402514294f9a14">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#ab051d976dbecf325747d54efe7834d04">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#ae026bc87dc8b24fd78d412ac7e58b148">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a27d68f2e6c4572445cd94dc472470a01">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a8d34faa3d6ea804a3467979858d33535">PyDynamicEngine</a>.</p>
<p>Get the index of a species in the network. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">species</td><td>The species to look up.</td></tr>
</table>
</dd>
</dl>
<p>This method allows querying the index of a specific species in the engine's internal representation. It is useful for accessing species data efficiently. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#ad7a82578006e5c55ca7716e7ab7e710c">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#afb3c67ce20746b9acb2766920b8f397b">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#ad67b0022cc783e63ae1954a04c4a68e1">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#ae0c02c830cf45568a7c4d35d4ed15e95">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a95d10a7b240d543a1bc6c67ddf2dc8e0">PyDynamicEngine</a>.</p>
<p>Get the status of a species in the network. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">species</td><td>The species to check. </td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd><aclass="el"href="namespacegridfire_1_1engine.html#a83c9d755597668bba3cf00cd0ea10ee3"title="Enumerates the status of a species in the simulation.">SpeciesStatus</a> indicating whether the species is active, inactive, or culled.</dd></dl>
<p>This method allows querying the current status of a specific species within the engine's network. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a5166197fd61060b2a9a445f707ee871b">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a65af092785759559f4697c7e66bef2e3">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#afe93df16c69e7e10658c82874759dd2f">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#aec5ebaccf625e39d0fa6c1330855d008">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a2947824dca9662e113153de5c6516609">PyDynamicEngine</a>.</p>
<p>Compute timescales for all species in the network. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>Composition object containing current abundances. </td></tr>
<tr><tdclass="paramname">T9</td><td>Temperature in units of 10^9 K. </td></tr>
<tr><tdclass="paramname">rho</td><td>Density in g/cm^3. </td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd>Map from Species to their characteristic timescales (s).</dd></dl>
<p>This method estimates the timescale for abundance change of each species, which can be used for timestep control, diagnostics, and reaction network culling. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#ade5dad29a79209e677b259a9b28c5133">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a1edda1a27247480660cf7a63410f5799">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a3c9b57d2842b6b5535313be845ca6175">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a86390e410db48addfe8dbd094743c38e">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a71678a567bb0cedd8a97aff9ceddd814">PyDynamicEngine</a>.</p>
<p>Get an entry from the stoichiometry matrix. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">species</td><td>species to look up stoichiometry for. </td></tr>
<tr><tdclass="paramname">reaction</td><td>reaction to find </td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd>Stoichiometric coefficient for the species in the reaction.</dd></dl>
<p>The stoichiometry matrix must have been generated by <aclass="el"href="#a5e2c45a3e415b53e41def8f743f93464"title="Generate the stoichiometry matrix for the network.">generateStoichiometryMatrix()</a>. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#aae6d8bab169721f0b89682ce8c4b4f10">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a600dd38a6011089527024f1625130935">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#aec867f0b43e74c8157f7d5085b55bb96">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a1372e7a823841c819f6c1a15d38217a6">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a3dd5cf419f25e76e144af35df15a2067">PyDynamicEngine</a>.</p>
<p>Check if the engine's internal state is stale. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">netIn</td><td>A struct containing the current network input, such as temperature, density, and composition. </td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd>True if the engine's state is stale and needs to be updated; false otherwise.</dd></dl>
<p>This method allows derived classes to determine if their internal state is out-of-date with respect to the provided network conditions. If the engine is stale, it may require a call to <code><aclass="el"href="#a8dd85442ec54f20d91743c72364e36ff"title="Update the internal state of the engine.">update()</a></code> before performing calculations.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a6c08b4235996d12472d2a327eab8e984">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a6ef3052fce2d5e4fdaec6659df64c2bc">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a07acc57c1015903ce3d1b0d0b7f09358">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a10dd189ba40dbb604fdf55746b5d4b79">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a55bf19ed7534a312a36faf74753f7b14">PyDynamicEngine</a>.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a24cc7e1a7471d707707b4d44ebd81068">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#aa053696a7885b8e42562b2d22ee32d84">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a915602acb18a69f34076bea401ffb49d">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#aa839c3893ff9fb8e5a4187224dac7b47">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a61bb4b430fe740cfb2c24e5cc673e4ac">PyDynamicEngine</a>.</p>
<tr><tdclass="paramname">netIn</td><td>The input conditions for the network. </td></tr>
</table>
</dd>
</dl>
<dlclass="section return"><dt>Returns</dt><dd><aclass="el"href="structgridfire_1_1engine_1_1_priming_report.html"title="Captures the result of a network priming operation.">PrimingReport</a> containing information about the priming process.</dd></dl>
<p>This method is used to prepare the engine for calculations by setting up initial conditions, reactions, and species. It may involve compiling reaction rates, initializing internal data structures, and performing any necessary pre-computation. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a955a337f89a375637ac48071be45c54c">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a2bc32a84c9f5372587fca92f2da77595">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#acc7f7fb7f0ef96135e7bda4bb532792e">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#afabb6222bd6cbe3277b6c8639203be25">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#a6118af81e45d2850f7a2517891147274">PyDynamicEngine</a>.</p>
<p>Rebuild the network with a specified depth. </p>
<dlclass="params"><dt>Parameters</dt><dd>
<tableclass="params">
<tr><tdclass="paramname">comp</td><td>The composition to rebuild the network with. </td></tr>
<tr><tdclass="paramname">depth</td><td>The desired depth of the network.</td></tr>
</table>
</dd>
</dl>
<p>This method is intended to allow dynamic adjustment of the network's depth, which may involve adding or removing species and reactions based on the specified depth. However, not all engines support this operation. </p>
<p>Reimplemented in <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a6c5245a27da1b45e10fb410518b79d4e">gridfire::engine::GraphEngine</a>, and <aclass="el"href="class_py_dynamic_engine.html#a25e52496b36d731127603c31e9dcaa97">PyDynamicEngine</a>.</p>
<tr><tdclass="paramname">reactions</td><td>The set of reactions to use in the network.</td></tr>
</table>
</dd>
</dl>
<p>This method replaces the current set of reactions in the network with the provided set. It marks the engine as stale, requiring regeneration of matrices and recalculation of rates. </p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a5dbfcafa606c3242dc4ced62c2494a2d">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#ae89529e13f2b7fd2febcfa5af40d4666">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a90251650123d0d8ce0281e18c4476f45">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#aa378d0e0fa6018b989d83945daa47952">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#af469cba3be850d53f659ec173f0eb4e4">PyDynamicEngine</a>.</p>
<tr><tdclass="paramname">model</td><td>The type of screening model to use for reaction rate calculations.</td></tr>
</table>
</dd>
</dl>
<p>This method allows changing the screening model at runtime. Screening corrections account for the electrostatic shielding of nuclei by electrons, which affects reaction rates in dense stellar plasmas.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#ab050409db954a3fa593633f9d2cd5d89">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a68bd0e51d3e127e5f9fd74fdb8180fd9">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#af842981deaf84a698b6cbfa66abcb715">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#ad11aa1e168ec03d0c3ed90eeddcefe52">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#afa3abfd612033336a656f092721c14ac">PyDynamicEngine</a>.</p>
<tr><tdclass="paramname">netIn</td><td>A struct containing the current network input, such as temperature, density, and composition.</td></tr>
</table>
</dd>
</dl>
<p>This method is intended to be implemented by derived classes to update their internal state based on the provided network conditions. For example, an adaptive engine might use this to re-evaluate which reactions and species are active. For other engines that do not support manually updating, this method might do nothing.</p>
<p>Implemented in <aclass="el"href="classgridfire_1_1engine_1_1_adaptive_engine_view.html#a8db6ba52f454c136ee0a1335436fab6e">gridfire::engine::AdaptiveEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_defined_engine_view.html#a1d99b55bf8e94bc2397715aa1f916733">gridfire::engine::DefinedEngineView</a>, <aclass="el"href="classgridfire_1_1engine_1_1_graph_engine.html#a7f6d98a9a4f22f1bbc015b1cbb8198e3">gridfire::engine::GraphEngine</a>, <aclass="el"href="classgridfire_1_1engine_1_1_multiscale_partitioning_engine_view.html#a28c8ac1ec594cf55a297e3f9586e214a">gridfire::engine::MultiscalePartitioningEngineView</a>, and <aclass="el"href="class_py_dynamic_engine.html#af8e6a8cd44f278535d7bcc9a896d6da8">PyDynamicEngine</a>.</p>
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