Emily Boudreaux
3c80ccc77f
Mirroring what was done in fourdst (see fourdst/tree/v0.8.5) we have added a temporary patch to let python bindings work on mac while the meson-python folks resolve the duplicate rpath issue in the shared object file
108 lines
3.4 KiB
Python
108 lines
3.4 KiB
Python
# import numpy as np
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# from scipy.integrate import solve_ivp
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#
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# import pp_chain_robust as network
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#
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#
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# T = 1e7
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# rho = 1.5e2
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#
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# Y0 = np.zeros(network.nnuc)
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# Y0[network.jp] = 0.702583
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# Y0[network.jhe3] = 9.74903e-6
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# Y0[network.jhe4] = 0.068963
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# Y0[network.jc12] = 0.000250029
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# Y0[network.jn14] = 7.85632e-5
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# Y0[network.jo16] = 0.00060151
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# Y0[network.jne20] = 8.10399e-5
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# Y0[network.jmg24] = 2.15159e-5
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#
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# t_start = 0.0
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# t_end = 3.14e17
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# t_span = (t_start, t_end)
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#
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# sol = solve_ivp(
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# network.rhs,
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# t_span=t_span,
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# y0=Y0,
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# method='Radau',
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# jac=network.jacobian,
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# args=(rho, T),
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# dense_output=True,
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# rtol=1e-8,
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# atol=1e-8
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# )
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#
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#
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# with open("pynucastro_results.csv", 'w') as f:
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# f.write("t,h1,h2,he3,he4,c12,n14,o16,ne20,mg24\n")
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# for (t,h1,h2,he3,he4,c12,n14,o16,ne20,mg24) in zip(sol.t, sol.y[network.jp, :], sol.y[network.jd, :], sol.y[network.jhe3, :], sol.y[network.jhe4, :], sol.y[network.jc12, :], sol.y[network.jn14, :], sol.y[network.jo16, :], sol.y[network.jne20, :], sol.y[network.jmg24, :]):
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# f.write(f"{t},{h1},{h2},{he3},{he4},{c12},{n14},{o16},{ne20},{mg24}\n")
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from gridfire.engine import GraphEngine, MultiscalePartitioningEngineView, AdaptiveEngineView
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from gridfire.solver import CVODESolverStrategy
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from gridfire.type import NetIn
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from fourdst.composition import Composition
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from fourdst.atomic import species
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symbols : list[str] = ["H-1", "He-3", "He-4", "C-12", "N-14", "O-16", "Ne-20", "Mg-24"]
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X : list[float] = [0.708, 2.94e-5, 0.276, 0.003, 0.0011, 9.62e-3, 1.62e-3, 5.16e-4]
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comp = Composition()
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comp.registerSymbol(symbols)
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comp.setMassFraction(symbols, X)
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comp.finalize(True)
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print(f"Initial H-1 mass fraction {comp.getMassFraction("H-1")}")
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netIn = NetIn()
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netIn.composition = comp
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netIn.temperature = 1.5e7
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netIn.density = 1.6e2
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netIn.tMax = 3.14e16
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netIn.dt0 = 1e-12
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baseEngine = GraphEngine(netIn.composition, 2)
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baseEngine.setUseReverseReactions(False)
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qseEngine = MultiscalePartitioningEngineView(baseEngine)
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adaptiveEngine = AdaptiveEngineView(qseEngine)
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solver = CVODESolverStrategy(adaptiveEngine)
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data = []
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def callback(context):
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H1Index = context.engine.getSpeciesIndex(species["H-1"])
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H2Index = context.engine.getSpeciesIndex(species["H-2"])
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He3Index = context.engine.getSpeciesIndex(species["He-3"])
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He4Index = context.engine.getSpeciesIndex(species["He-4"])
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C12Index = context.engine.getSpeciesIndex(species["C-12"])
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N14Index = context.engine.getSpeciesIndex(species["N-14"])
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O16Index = context.engine.getSpeciesIndex(species["O-16"])
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Ne20Index = context.engine.getSpeciesIndex(species["Mg-24"])
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Mg24Index = context.engine.getSpeciesIndex(species["Mg-24"])
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data.append([context.t,
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context.state[H1Index],
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context.state[H2Index],
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context.state[He3Index],
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context.state[He4Index],
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context.state[C12Index],
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context.state[N14Index],
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context.state[O16Index],
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context.state[Ne20Index],
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context.state[Mg24Index]
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])
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solver.set_callback(callback)
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results = solver.evaluate(netIn, False)
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# with open("gridfire_results.csv", 'w') as f:
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# f.write("t,h1,h2,he3,he4,c12,n14,o16,ne20,mg24\n")
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# for row in data:
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# rowStr = ','.join([str(x) for x in row])
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# f.write(f"{rowStr}\n")
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