forked from p94628173/idrlnet
86 lines
2.3 KiB
Python
86 lines
2.3 KiB
Python
from sympy import Symbol, sin
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import math
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import matplotlib.pyplot as plt
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import matplotlib.tri as tri
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import idrlnet.shortcut as sc
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x = Symbol("x")
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t_symbol = Symbol("t")
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time_range = {t_symbol: (0, 1)}
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geo = sc.Line1D(-1.0, 1.0)
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@sc.datanode(name="burgers_equation")
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def interior_domain():
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points = geo.sample_interior(
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10000, bounds={x: (-1.0, 1.0)}, param_ranges=time_range
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)
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constraints = {"burgers_u": 0}
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return points, constraints
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@sc.datanode(name="t_boundary")
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def init_domain():
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points = geo.sample_interior(100, param_ranges={t_symbol: 0.0})
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constraints = sc.Variables({"u": -sin(math.pi * x)})
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return points, constraints
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@sc.datanode(name="x_boundary")
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def boundary_domain():
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points = geo.sample_boundary(100, param_ranges=time_range)
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constraints = sc.Variables({"u": 0})
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return points, constraints
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net = sc.get_net_node(
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inputs=(
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"x",
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"t",
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),
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outputs=("u",),
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name="net1",
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arch=sc.Arch.mlp,
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)
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pde = sc.BurgersNode(u="u", v=0.01 / math.pi)
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s = sc.Solver(
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sample_domains=(interior_domain(), init_domain(), boundary_domain()),
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netnodes=[net],
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pdes=[pde],
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max_iter=4000,
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)
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s.solve()
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coord = s.infer_step(
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{
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"burgers_equation": ["x", "t", "u"],
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"t_boundary": ["x", "t"],
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"x_boundary": ["x", "t"],
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}
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)
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num_x = coord["burgers_equation"]["x"].cpu().detach().numpy().ravel()
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num_t = coord["burgers_equation"]["t"].cpu().detach().numpy().ravel()
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num_u = coord["burgers_equation"]["u"].cpu().detach().numpy().ravel()
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init_x = coord["t_boundary"]["x"].cpu().detach().numpy().ravel()
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init_t = coord["t_boundary"]["t"].cpu().detach().numpy().ravel()
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boundary_x = coord["x_boundary"]["x"].cpu().detach().numpy().ravel()
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boundary_t = coord["x_boundary"]["t"].cpu().detach().numpy().ravel()
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triang_total = tri.Triangulation(num_t.flatten(), num_x.flatten())
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u_pre = num_u.flatten()
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fig = plt.figure(figsize=(15, 5))
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ax1 = fig.add_subplot(221)
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tcf = ax1.tricontourf(triang_total, u_pre, 100, cmap="jet")
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tc_bar = plt.colorbar(tcf)
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tc_bar.ax.tick_params(labelsize=10)
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ax1.set_xlabel("$t$")
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ax1.set_ylabel("$x$")
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ax1.set_title("$u(x,t)$")
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ax1.scatter(init_t, init_x, c="black", marker="x", s=8)
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ax1.scatter(boundary_t, boundary_x, c="black", marker="x", s=8)
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plt.xlim(0, 1)
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plt.ylim(-1, 1)
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plt.savefig("Burgers.png", dpi=500, bbox_inches="tight", pad_inches=0.02)
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