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| diffusion2.msize = mpi.Get_size() |
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| diffusion2.mrank = mpi.Get_rank() |
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| diffusion2._print_Indexed |
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str | diffusion2.sidx = lambda i: "e.i{}{}".format(*idx[i]) |
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| diffusion2.x |
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| diffusion2.y |
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| diffusion2.X |
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| diffusion2.Y |
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| diffusion2.ξ = x / X |
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| diffusion2.ζ = y / Y |
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| diffusion2.Φ = np.linalg.inv(np.array([[1, 0, 0, 0], [0, 1, 0, 0], [1, 1, 1, 1], [0, 1, 2, 3]])).T |
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list | diffusion2.φx = [sum(int(c) * ξ**i for i, c in enumerate(p)) for p in Φ] |
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list | diffusion2.φy = [sum(int(c) * ζ**i for i, c in enumerate(p)) for p in Φ] |
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list | diffusion2.idx = [(0,0), (0,1), (1,0), (0,2), (0,3), (1,2), (2,0), (2,1), (3,0), (2,2), (2,3), (3,2)] |
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| diffusion2.φ = np.array([φx[idx[i][0]] * φy[idx[i][1]] for i in range(12)]) |
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| diffusion2.dφx = np.array([sym.expand(sym.diff(a, x)) for a in φ]) |
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| diffusion2.dφy = np.array([sym.expand(sym.diff(a, y)) for a in φ]) |
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| diffusion2.U = sym.IndexedBase('U', shape=(4, 4)) |
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| diffusion2.u0 = sum(U[idx[k]] * φ[k] for k in range(12)) |
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| diffusion2.sep |
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| diffusion2.zx = np.array([0, X]) |
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| diffusion2.zy = np.array([0, Y]) |
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| diffusion2.J = sym.IndexedBase('J', shape=(2, 2)) |
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| diffusion2.Jxy = sym.simplify(sum(J[i,j] * La(i, x, zx) * La(j, y, zy) for i in range(len(zx)) for j in range(len(zy)))) |
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| diffusion2.KD |
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| diffusion2.end |
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| diffusion2.KA |
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| diffusion2.KB |
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| diffusion2.u02 = sym.expand(u0**2) |
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| diffusion2.u03 = sym.expand(u0**3) |
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| diffusion2.KC |
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| diffusion2.KK = KD, KA, KB, KC |
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| diffusion2.FB |
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| diffusion2.FC |
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| diffusion2.F0 |
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| diffusion2.FF = FB, FC, F0 |
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| diffusion2.P = sym.IndexedBase('P', shape=(2,2,2)) |
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| diffusion2.G = sym.IndexedBase('G', shape=(2,)) |
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| diffusion2.dG = sym.IndexedBase('dG', shape=(2,)) |
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| diffusion2.ug = sym.symbols('Ug') |
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list | diffusion2.Pxy = [sym.simplify(sum(P[i, j, c] * La(i, x, zx) * La(j, y, zy) for i in range(len(zx)) for j in range(len(zy)))) for c in range(2)] |
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| diffusion2.KL |
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| diffusion2.FL |
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