FeniCS：可视化高阶元素

我才刚刚开始使用FEniCS。我正在用三阶元素求解泊松，并想将结果可视化。但是，当我使用plot（u）时，可视化只是结果的线性插值。当输出到VTK时，我会得到相同的结果。在我正在使用的另一个代码中，我编写了一个VTK输出器，该输出器将对高阶元素进行升采样，以使它们实际上在Paraview中看起来较高阶。FEniCS中是否有类似（或更好）的东西？

您可以将解插值到更细的网格上，然后将其绘制：

from dolfin import *

coarse_mesh = UnitSquareMesh(2, 2)
fine_mesh = refine(refine(refine(coarse_mesh)))

P2_coarse = FunctionSpace(coarse_mesh, "CG", 2)
P1_fine = FunctionSpace(fine_mesh, "CG", 1)

f = interpolate(Expression("sin(pi*x[0])*sin(pi*x[1])"), P2_coarse)
g = interpolate(f, P1_fine)

plot(f, title="Bad plot")
plot(g, title="Good plot")

interactive()

注意如何在较细的网格上的图中看到粗P2三角形的轮廓。

我已经在自适应优化方面做了一些工作（请参见下面的代码）。误差指示器在网格总大小和网格功能总变化中的缩放比例并不理想，但是您可以根据需要进行调整。下图是针对第4个测试用例的。单元格的数量从200个增加到大约24,000个，可能有点超出顶部，但结果还是不错的。网格显示只有相关部分已被细化。您仍然可以看到的伪像是三阶元素本身无法表示的足够准确。

from dolfin import *
from numpy import abs


def compute_error(expr, mesh):
    DG = FunctionSpace(mesh, "DG", 0)
    e = project(expr, DG)
    err = abs(e.vector().array())
    dofmap = DG.dofmap()
    return err, dofmap


def refine_by_bool_array(mesh, to_mark, dofmap):
    cell_markers = CellFunction("bool", mesh)
    cell_markers.set_all(False)
    n = 0
    for cell in cells(mesh):
        index = dofmap.cell_dofs(cell.index())[0]
        if to_mark[index]:
            cell_markers[cell] = True
            n += 1
    mesh = refine(mesh, cell_markers)
    return mesh, n


def adapt_mesh(f, mesh, max_err=0.001, exp=0):
    V = FunctionSpace(mesh, "CG", 1)
    while True:
        fi = interpolate(f, V)
        v = CellVolume(mesh)
        expr = v**exp * abs(f-fi)
        err, dofmap = compute_error(expr, mesh)

        to_mark = (err>max_err)
        mesh, n = refine_by_bool_array(mesh, to_mark, dofmap)
        if not n:
            break

        V = FunctionSpace(mesh, "CG", 1)
    return fi, mesh


def show_testcase(i, p, N, fac, title1="", title2=""):
    funcs = ["sin(60*(x[0]-0.5)*(x[1]-0.5))",
             "sin(10*(x[0]-0.5)*(x[1]-0.5))",
             "sin(10*(x[0]-0.5))*sin(pow(3*(x[1]-0.05),2))"]

    mesh = UnitSquareMesh(N, N)
    U = FunctionSpace(mesh, "CG", p)
    f = interpolate(Expression(funcs[i]), U)

    v0 = (1.0/N) ** 2;
    exp = 1
    #exp = 0
    fac2 = (v0/100)**exp
    max_err = fac * fac2
    #print v0, fac, exp, fac2, max_err
    g, mesh2 = adapt_mesh(f, mesh, max_err=max_err, exp=exp)

    plot(mesh, title=title1 + " (mesh)")
    plot(f, title=title1)
    plot(mesh2, title=title2 + " (mesh)")
    plot(g, title=title2)
    interactive()


if __name__ == "__main__":
    N = 10
    fac = 0.01
    show_testcase(0, 1, 10, fac, "degree 1 - orig", "degree 1 - refined (no change)")
    show_testcase(0, 2, 10, fac, "degree 2 - orig", "degree 2 - refined")
    show_testcase(0, 3, 10, fac, "degree 3 - orig", "degree 3 - refined")
    show_testcase(0, 3, 10, 0.2*fac, "degree 3 - orig", "degree 3 - more refined")
    show_testcase(1, 2, 10, fac, "smooth: degree 2 - orig", "smooth: degree 2 - refined")
    show_testcase(1, 3, 10, fac, "smooth: degree 3 - orig", "smooth: degree 3 - refined")
    show_testcase(2, 2, 10, fac, "bumps: degree 2 - orig", "bumps: degree 2 - refined")
    show_testcase(2, 3, 10, fac, "bumps: degree 3 - orig", "bumps: degree 3 - refined")