# we do not need to consider the z-dimension). # ncx = 10 # number of core mesh cells in x ncy = 15 # number of core mesh cells in y dx = 15 # base cell width x dy = 10 # base cell width y hx = dx * np.ones(ncx) hy = dy * np.ones(ncy) x0 = 0 y0 = -150 mesh = TensorMesh([hx, hy], x0=[x0, y0]) mesh.plotGrid() ############################################### # Padding Cells and Plotting # -------------------------- # # For practical purposes, the user may want to define a region where the cell # widths are increasing/decreasing in size. For example, padding is often used # to define a large domain while reducing the total number of mesh cells. # Here we demonstrate how to create tensor meshes that have padding cells. # ncx = 10 # number of core mesh cells in x ncy = 15 # number of core mesh cells in y dx = 15 # base cell width x
# Although the divergence cannot be constructed through Kronecker product
# operations, the initial steps are exactly the same for calculating the
# stencil, volumes, and areas. This yields a divergence defined for every
# cell in the mesh using all faces. There is, however, redundant information
# when hanging faces are included.
#
mesh = TreeMesh([[(1, 16)], [(1, 16)]], levels=4)
mesh.insert_cells(np.array([5.0, 5.0]), np.array([3]))
mesh.number()
fig = plt.figure(figsize=(10, 10))
ax1 = fig.add_subplot(211)
mesh.plotGrid(centers=True, nodes=False, ax=ax1)
ax1.axis("off")
ax1.set_title("Simple QuadTree Mesh")
ax1.set_xlim([-1, 17])
ax1.set_ylim([-1, 17])
for ii, loc in zip(range(mesh.nC), mesh.gridCC):
ax1.text(loc[0] + 0.2, loc[1], "{0:d}".format(ii), color="r")
ax1.plot(mesh.gridFx[:, 0], mesh.gridFx[:, 1], "g>")
for ii, loc in zip(range(mesh.nFx), mesh.gridFx):
ax1.text(loc[0] + 0.2, loc[1], "{0:d}".format(ii), color="g")
ax1.plot(mesh.gridFy[:, 0], mesh.gridFy[:, 1], "m^")
for ii, loc in zip(range(mesh.nFy), mesh.gridFy):
ax1.text(loc[0] + 0.2,
