refactor(reaction): refactored to an abstract reaction class in prep for weak reactions

validation/pynucastro/GridFireEquiv/generate_proton_proton.py

@@ -0,0 +1,47 @@
+import pynucastro as pyna
+
+from gridfire.engine import GraphEngine, MultiscalePartitioningEngineView, AdaptiveEngineView
+from gridfire.solver import DirectNetworkSolver
+from gridfire.type import NetIn
+
+from fourdst.composition import Composition
+
+symbols : list[str] = ["H-1", "He-3", "He-4", "C-12", "N-14", "O-16", "Ne-20", "Mg-24"]
+X : list[float]     = [0.708, 2.94e-5, 0.276, 0.003, 0.0011, 9.62e-3, 1.62e-3, 5.16e-4]
+
+
+comp = Composition()
+comp.registerSymbol(symbols)
+comp.setMassFraction(symbols, X)
+comp.finalize(True)
+
+print(f"Initial H-1 mass fraction {comp.getMassFraction("H-1")}")
+
+netIn = NetIn()
+netIn.composition = comp
+netIn.temperature = 1.5e7
+netIn.density = 1.6e2
+netIn.tMax = 1e-9
+netIn.dt0 = 1e-12
+
+baseEngine = GraphEngine(netIn.composition, 2)
+
+equiv_species = baseEngine.getNetworkSpecies()
+equiv_species = [x.name().replace("-","").lower() for x in equiv_species]
+
+equiv_species = [x if x != 'h1' else 'p' for x in equiv_species]
+equiv_species = [x if x != 'n1' else 'n' for x in equiv_species]
+
+rl = pyna.ReacLibLibrary()
+
+# equiv_species = ['p', 'd', 'he3', 'he4', 'c12', 'n14', 'o16', 'ne20', 'mg24']
+full_lib = rl.linking_nuclei(equiv_species)
+
+print(f"\nFound {len(full_lib.get_rates())} rates.")
+
+net = pyna.PythonNetwork(libraries=[full_lib])
+
+output_filename = "pp_chain_robust.py"
+net.write_network(output_filename)
+
+print(f"\nSuccessfully wrote robust PP-chain network to: {output_filename}")