diff --git a/docs/extended.rst b/docs/extended.rst index f27c8048..90acb348 100644 --- a/docs/extended.rst +++ b/docs/extended.rst @@ -241,8 +241,8 @@ more descriptive and readable. .. sourcecode:: - dof_subset_right_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) - fe_approximation[dof_subset_right_edge] = 2 + dof_subset_top_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) + fe_approximation[dof_subset_top_edge] = 2 plt.subplots(figsize=(6,5)) skfem.visuals.matplotlib.plot(basis_p1, fe_approximation, vmin=0, vmax=2, ax=plt.gca(), colorbar=True, shading='gouraud') skfem.visuals.matplotlib.draw(mesh, ax=plt.gca()) @@ -263,8 +263,8 @@ more descriptive and readable. return x[0] < 0.1 dof_subset_left_edge = basis_p1.get_dofs(facets=is_on_left_edge) fe_approximation[dof_subset_left_edge] = 0 - dof_subset_right_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) - fe_approximation[dof_subset_right_edge] = 2 + dof_subset_top_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) + fe_approximation[dof_subset_top_edge] = 2 plt.subplots(figsize=(6,5)) skfem.visuals.matplotlib.plot(basis_p1, fe_approximation, vmin=0, vmax=2, ax=plt.gca(), colorbar=True, shading='gouraud') skfem.visuals.matplotlib.draw(mesh, ax=plt.gca()) @@ -298,8 +298,8 @@ In a directly analogous manner, we can specify values over entire elements inste return x[0] < 0.1 dof_subset_left_edge = basis_p1.get_dofs(facets=is_on_left_edge) fe_approximation[dof_subset_left_edge] = 0 - dof_subset_right_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) - fe_approximation[dof_subset_right_edge] = 2 + dof_subset_top_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) + fe_approximation[dof_subset_top_edge] = 2 # reset the function to be 1 everywhere fe_approximation[:] = 1 dof_subset_bottom_left = basis_p1.get_dofs(elements=lambda x: np.logical_and(x[0]<.3, x[1]<.3)) @@ -392,8 +392,8 @@ labelling facets and elements during mesh construction.) return x[0] < 0.1 dof_subset_left_edge = basis_p1.get_dofs(facets=is_on_left_edge) fe_approximation[dof_subset_left_edge] = 0 - dof_subset_right_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) - fe_approximation[dof_subset_right_edge] = 2 + dof_subset_top_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) + fe_approximation[dof_subset_top_edge] = 2 # reset the function to be 1 everywhere fe_approximation[:] = 1 dof_subset_bottom_left = basis_p1.get_dofs(elements=lambda x: np.logical_and(x[0]<.3, x[1]<.3)) @@ -439,8 +439,8 @@ function values at those points. return x[0] < 0.1 dof_subset_left_edge = basis_p1.get_dofs(facets=is_on_left_edge) fe_approximation[dof_subset_left_edge] = 0 - dof_subset_right_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) - fe_approximation[dof_subset_right_edge] = 2 + dof_subset_top_edge = basis_p1.get_dofs(facets=lambda x: x[1] > 0.9) + fe_approximation[dof_subset_top_edge] = 2 # reset the function to be 1 everywhere fe_approximation[:] = 1 dof_subset_bottom_left = basis_p1.get_dofs(elements=lambda x: np.logical_and(x[0]<.3, x[1]<.3)) @@ -475,7 +475,7 @@ important to understand their relationship with the projections we've been constructing. To start this discussion, however, it is important to distinguish between "local" coordinates and "global" coordinates. In this triangulation we've been working in, the local, -or reference, triangle is on with vertexes and (0, 0), (1, 0), and (0, 1). +or reference, triangle is within the unit square with vertexes and (0, 0), (1, 0), and (0, 1). .. sourcecode::