Mercurial > repos > public > sbplib
view +scheme/Elastic2dStaggeredCurvilinearAnisotropic.m @ 1281:01a0500de446 feature/poroelastic
Add working implementation of Elastic2dStaggeredCurvilinearAnisotropic, which wraps around the Cartesian anisotropic scheme.
author | Martin Almquist <malmquist@stanford.edu> |
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date | Sun, 07 Jun 2020 11:33:44 -0700 |
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classdef Elastic2dStaggeredCurvilinearAnisotropic < scheme.Scheme % Discretizes the elastic wave equation: % rho u_{i,tt} = dj C_{ijkl} dk u_j % in curvilinear coordinates, using Lebedev staggered grids properties m % Number of points in each direction, possibly a vector h % Grid spacing grid dim nGrids order % Order of accuracy for the approximation % Diagonal matrices for variable coefficients J, Ji RHO % Density C % Elastic stiffness tensor D % Total operator % Dx, Dy % Physical derivatives n_w, n_e, n_s, n_n % Physical normals % Boundary operators in cell format, used for BC T_w, T_e, T_s, T_n % Traction operators % tau_w, tau_e, tau_s, tau_n % Return vector field % tau1_w, tau1_e, tau1_s, tau1_n % Return scalar field % tau2_w, tau2_e, tau2_s, tau2_n % Return scalar field % Inner products H % Boundary inner products (for scalar field) H_w, H_e, H_s, H_n % Surface Jacobian vectors s_w, s_e, s_s, s_n % Boundary restriction operators e_w_u, e_e_u, e_s_u, e_n_u % Act on scalar field, return scalar field at boundary e_w_s, e_e_s, e_s_s, e_n_s % Act on scalar field, return scalar field at boundary % e1_w, e1_e, e1_s, e1_n % Act on vector field, return scalar field at boundary % e2_w, e2_e, e2_s, e2_n % Act on vector field, return scalar field at boundary % e_scalar_w, e_scalar_e, e_scalar_s, e_scalar_n; % Act on scalar field, return scalar field % en_w, en_e, en_s, en_n % Act on vector field, return normal component % U{i}^T picks out component i U % G{i}^T picks out displacement grid i G % Elastic2dVariableAnisotropic object for reference domain refObj end methods % The coefficients can either be function handles or grid functions % optFlag -- if true, extra computations are performed, which may be helpful for optimization. function obj = Elastic2dStaggeredCurvilinearAnisotropic(g, order, rho, C) default_arg('rho', @(x,y) 0*x+1); opSet = @sbp.D1StaggeredUpwind; dim = 2; nGrids = 2; C_default = cell(dim,dim,dim,dim); for i = 1:dim for j = 1:dim for k = 1:dim for l = 1:dim C_default{i,j,k,l} = @(x,y) 0*x; end end end end default_arg('C', C_default); assert(isa(g, 'grid.Staggered')); g_u = g.gridGroups{1}; g_s = g.gridGroups{2}; m_u = {g_u{1}.size(), g_u{2}.size()}; m_s = {g_s{1}.size(), g_s{2}.size()}; if isa(rho, 'function_handle') rho_vec = cell(nGrids, 1); for a = 1:nGrids rho_vec{a} = grid.evalOn(g_u{a}, rho); end rho = rho_vec; end for a = 1:nGrids RHO{a} = spdiag(rho{a}); end obj.RHO = RHO; C_mat = cell(nGrids, 1); for a = 1:nGrids C_mat{a} = cell(dim,dim,dim,dim); end for a = 1:nGrids for i = 1:dim for j = 1:dim for k = 1:dim for l = 1:dim if numel(C) == dim C_mat{a}{i,j,k,l} = spdiag(C{a}{i,j,k,l}); else C_mat{a}{i,j,k,l} = spdiag(grid.evalOn(g_s{a}, C{i,j,k,l})); end end end end end end obj.C = C_mat; C = cell(nGrids, 1); for a = 1:nGrids C{a} = cell(dim,dim,dim,dim); for i = 1:dim for j = 1:dim for k = 1:dim for l = 1:dim C{a}{i,j,k,l} = diag(C_mat{a}{i,j,k,l}); end end end end end % Reference m for primal grid m = g_u{1}.size(); % 1D operators ops = cell(dim,1); D1p = cell(dim, 1); D1d = cell(dim, 1); mp = cell(dim, 1); md = cell(dim, 1); Ip = cell(dim, 1); Id = cell(dim, 1); Hp = cell(dim, 1); Hd = cell(dim, 1); opSet = @sbp.D1StaggeredUpwind; for i = 1:dim ops{i} = opSet(m(i), {0,1}, order); D1p{i} = ops{i}.D1_dual; D1d{i} = ops{i}.D1_primal; mp{i} = length(ops{i}.x_primal); md{i} = length(ops{i}.x_dual); Ip{i} = speye(mp{i}, mp{i}); Id{i} = speye(md{i}, md{i}); Hp{i} = ops{i}.H_primal; Hd{i} = ops{i}.H_dual; ep_l{i} = ops{i}.e_primal_l; ep_r{i} = ops{i}.e_primal_r; ed_l{i} = ops{i}.e_dual_l; ed_r{i} = ops{i}.e_dual_r; end % D1_u2s{a, b}{i} approximates ddi and % takes from u grid number b to s grid number a % Some of D1_x2y{a, b} are 0. D1_u2s = cell(nGrids, nGrids); D1_s2u = cell(nGrids, nGrids); N_u = cell(nGrids, 1); N_s = cell(nGrids, 1); for a = 1:nGrids N_u{a} = g_u{a}.N(); N_s{a} = g_s{a}.N(); end %---- Grid layout ------- % gu1 = xp o yp; % gu2 = xd o yd; % gs1 = xd o yp; % gs2 = xp o yd; %------------------------ % Logical operators D1_u2s{1,1}{1} = kron(D1p{1}, Ip{2}); D1_s2u{1,1}{1} = kron(D1d{1}, Ip{2}); D1_u2s{1,2}{2} = kron(Id{1}, D1d{2}); D1_u2s{2,1}{2} = kron(Ip{1}, D1p{2}); D1_s2u{1,2}{2} = kron(Ip{1}, D1d{2}); D1_s2u{2,1}{2} = kron(Id{1}, D1p{2}); D1_u2s{2,2}{1} = kron(D1d{1}, Id{2}); D1_s2u{2,2}{1} = kron(D1p{1}, Id{2}); D1_u2s{1,1}{2} = sparse(N_s{1}, N_u{1}); D1_s2u{1,1}{2} = sparse(N_u{1}, N_s{1}); D1_u2s{2,2}{2} = sparse(N_s{2}, N_u{2}); D1_s2u{2,2}{2} = sparse(N_u{2}, N_s{2}); D1_u2s{1,2}{1} = sparse(N_s{1}, N_u{2}); D1_s2u{1,2}{1} = sparse(N_u{1}, N_s{2}); D1_u2s{2,1}{1} = sparse(N_s{2}, N_u{1}); D1_s2u{2,1}{1} = sparse(N_u{2}, N_s{1}); %---- Combine grids and components ----- % U{a}{i}^T picks out u component i on grid a U = cell(nGrids, 1); for a = 1:nGrids U{a} = cell(dim, 1); I = speye(N_u{a}, N_u{a}); for i = 1:dim E = sparse(dim,1); E(i) = 1; U{a}{i} = kron(I, E); end end obj.U = U; % Order grids % u1, u2 Iu1 = speye(dim*N_u{1}, dim*N_u{1}); Iu2 = speye(dim*N_u{2}, dim*N_u{2}); Gu1 = cell2mat( {Iu1; sparse(dim*N_u{2}, dim*N_u{1})} ); Gu2 = cell2mat( {sparse(dim*N_u{1}, dim*N_u{2}); Iu2} ); G = {Gu1; Gu2}; %---- Grid layout ------- % gu1 = xp o yp; % gu2 = xd o yd; % gs1 = xd o yp; % gs2 = xp o yd; %------------------------ % Boundary restriction ops e_w_u = cell(nGrids, 1); e_s_u = cell(nGrids, 1); e_e_u = cell(nGrids, 1); e_n_u = cell(nGrids, 1); e_w_s = cell(nGrids, 1); e_s_s = cell(nGrids, 1); e_e_s = cell(nGrids, 1); e_n_s = cell(nGrids, 1); e_w_u{1} = kron(ep_l{1}, Ip{2}); e_e_u{1} = kron(ep_r{1}, Ip{2}); e_s_u{1} = kron(Ip{1}, ep_l{2}); e_n_u{1} = kron(Ip{1}, ep_r{2}); e_w_u{2} = kron(ed_l{1}, Id{2}); e_e_u{2} = kron(ed_r{1}, Id{2}); e_s_u{2} = kron(Id{1}, ed_l{2}); e_n_u{2} = kron(Id{1}, ed_r{2}); e_w_s{1} = kron(ed_l{1}, Ip{2}); e_e_s{1} = kron(ed_r{1}, Ip{2}); e_s_s{1} = kron(Id{1}, ep_l{2}); e_n_s{1} = kron(Id{1}, ep_r{2}); e_w_s{2} = kron(ep_l{1}, Id{2}); e_e_s{2} = kron(ep_r{1}, Id{2}); e_s_s{2} = kron(Ip{1}, ed_l{2}); e_n_s{2} = kron(Ip{1}, ed_r{2}); % --- Metric coefficients on stress grids ------- x = cell(nGrids, 1); y = cell(nGrids, 1); J = cell(nGrids, 1); x_xi = cell(nGrids, 1); x_eta = cell(nGrids, 1); y_xi = cell(nGrids, 1); y_eta = cell(nGrids, 1); for a = 1:nGrids coords = g_u{a}.points(); x{a} = coords(:,1); y{a} = coords(:,2); end for a = 1:nGrids x_xi{a} = zeros(N_s{a}, 1); y_xi{a} = zeros(N_s{a}, 1); x_eta{a} = zeros(N_s{a}, 1); y_eta{a} = zeros(N_s{a}, 1); for b = 1:nGrids x_xi{a} = x_xi{a} + D1_u2s{a,b}{1}*x{b}; y_xi{a} = y_xi{a} + D1_u2s{a,b}{1}*y{b}; x_eta{a} = x_eta{a} + D1_u2s{a,b}{2}*x{b}; y_eta{a} = y_eta{a} + D1_u2s{a,b}{2}*y{b}; end end for a = 1:nGrids J{a} = x_xi{a}.*y_eta{a} - x_eta{a}.*y_xi{a}; end K = cell(nGrids, 1); for a = 1:nGrids K{a} = cell(dim, dim); K{a}{1,1} = y_eta{a}./J{a}; K{a}{1,2} = -y_xi{a}./J{a}; K{a}{2,1} = -x_eta{a}./J{a}; K{a}{2,2} = x_xi{a}./J{a}; end % ---------------------------------------------- % --- Metric coefficients on displacement grids ------- x_s = cell(nGrids, 1); y_s = cell(nGrids, 1); J_u = cell(nGrids, 1); x_xi_u = cell(nGrids, 1); x_eta_u = cell(nGrids, 1); y_xi_u = cell(nGrids, 1); y_eta_u = cell(nGrids, 1); for a = 1:nGrids coords = g_s{a}.points(); x_s{a} = coords(:,1); y_s{a} = coords(:,2); end for a = 1:nGrids x_xi_u{a} = zeros(N_u{a}, 1); y_xi_u{a} = zeros(N_u{a}, 1); x_eta_u{a} = zeros(N_u{a}, 1); y_eta_u{a} = zeros(N_u{a}, 1); for b = 1:nGrids x_xi_u{a} = x_xi_u{a} + D1_s2u{a,b}{1}*x_s{b}; y_xi_u{a} = y_xi_u{a} + D1_s2u{a,b}{1}*y_s{b}; x_eta_u{a} = x_eta_u{a} + D1_s2u{a,b}{2}*x_s{b}; y_eta_u{a} = y_eta_u{a} + D1_s2u{a,b}{2}*y_s{b}; end end for a = 1:nGrids J_u{a} = x_xi_u{a}.*y_eta_u{a} - x_eta_u{a}.*y_xi_u{a}; end % ---------------------------------------------- % x_u = Du*x; % x_v = Dv*x; % y_u = Du*y; % y_v = Dv*y; % J = x_u.*y_v - x_v.*y_u; % K = cell(dim, dim); % K{1,1} = y_v./J; % K{1,2} = -y_u./J; % K{2,1} = -x_v./J; % K{2,2} = x_u./J; % Physical derivatives % obj.Dx = spdiag( y_v./J)*Du + spdiag(-y_u./J)*Dv; % obj.Dy = spdiag(-x_v./J)*Du + spdiag( x_u./J)*Dv; % Wrap around Aniosotropic Cartesian. Transformed density and stiffness rho_tilde = cell(nGrids, 1); PHI = cell(nGrids, 1); for a = 1:nGrids rho_tilde{a} = J_u{a}.*rho{a}; end for a = 1:nGrids PHI{a} = cell(dim,dim,dim,dim); for i = 1:dim for j = 1:dim for k = 1:dim for l = 1:dim PHI{a}{i,j,k,l} = 0*C{a}{i,j,k,l}; for m = 1:dim for n = 1:dim PHI{a}{i,j,k,l} = PHI{a}{i,j,k,l} + J{a}.*K{a}{m,i}.*C{a}{m,j,n,l}.*K{a}{n,k}; end end end end end end end refObj = scheme.Elastic2dStaggeredAnisotropic(g.logic, order, rho_tilde, PHI); G = refObj.G; U = refObj.U; H_u = refObj.H_u; % Volume quadrature [m, n] = size(refObj.H); obj.H = sparse(m, n); obj.J = sparse(m, n); for a = 1:nGrids for i = 1:dim obj.H = obj.H + G{a}*U{a}{i}*spdiag(J_u{a})*refObj.H_u{a}*U{a}{i}'*G{a}'; obj.J = obj.J + G{a}*U{a}{i}*spdiag(J_u{a})*U{a}{i}'*G{a}'; end end obj.Ji = inv(obj.J); % Boundary quadratures on stress grids s_w = cell(nGrids, 1); s_e = cell(nGrids, 1); s_s = cell(nGrids, 1); s_n = cell(nGrids, 1); % e_w_u = refObj.e_w_u; % e_e_u = refObj.e_e_u; % e_s_u = refObj.e_s_u; % e_n_u = refObj.e_n_u; e_w_s = refObj.e_w_s; e_e_s = refObj.e_e_s; e_s_s = refObj.e_s_s; e_n_s = refObj.e_n_s; for a = 1:nGrids s_w{a} = sqrt((e_w_s{a}'*x_eta{a}).^2 + (e_w_s{a}'*y_eta{a}).^2); s_e{a} = sqrt((e_e_s{a}'*x_eta{a}).^2 + (e_e_s{a}'*y_eta{a}).^2); s_s{a} = sqrt((e_s_s{a}'*x_xi{a}).^2 + (e_s_s{a}'*y_xi{a}).^2); s_n{a} = sqrt((e_n_s{a}'*x_xi{a}).^2 + (e_n_s{a}'*y_xi{a}).^2); end obj.s_w = s_w; obj.s_e = s_e; obj.s_s = s_s; obj.s_n = s_n; % for a = 1:nGrids % obj.H_w_s{a} = refObj.H_w_s{a}*spdiag(s_w{a}); % obj.H_e_s{a} = refObj.H_e_s{a}*spdiag(s_e{a}); % obj.H_s_s{a} = refObj.H_s_s{a}*spdiag(s_s{a}); % obj.H_n_s{a} = refObj.H_n_s{a}*spdiag(s_n{a}); % end % Restriction operators obj.e_w_u = refObj.e_w_u; obj.e_e_u = refObj.e_e_u; obj.e_s_u = refObj.e_s_u; obj.e_n_u = refObj.e_n_u; obj.e_w_s = refObj.e_w_s; obj.e_e_s = refObj.e_e_s; obj.e_s_s = refObj.e_s_s; obj.e_n_s = refObj.e_n_s; % Adapt things from reference object obj.D = refObj.D; obj.U = refObj.U; obj.G = refObj.G; % obj.e1_w = refObj.e1_w; % obj.e1_e = refObj.e1_e; % obj.e1_s = refObj.e1_s; % obj.e1_n = refObj.e1_n; % obj.e2_w = refObj.e2_w; % obj.e2_e = refObj.e2_e; % obj.e2_s = refObj.e2_s; % obj.e2_n = refObj.e2_n; % obj.e_scalar_w = refObj.e_scalar_w; % obj.e_scalar_e = refObj.e_scalar_e; % obj.e_scalar_s = refObj.e_scalar_s; % obj.e_scalar_n = refObj.e_scalar_n; % e1_w = obj.e1_w; % e1_e = obj.e1_e; % e1_s = obj.e1_s; % e1_n = obj.e1_n; % e2_w = obj.e2_w; % e2_e = obj.e2_e; % e2_s = obj.e2_s; % e2_n = obj.e2_n; % obj.tau1_w = (spdiag(1./s_w)*refObj.tau1_w')'; % obj.tau1_e = (spdiag(1./s_e)*refObj.tau1_e')'; % obj.tau1_s = (spdiag(1./s_s)*refObj.tau1_s')'; % obj.tau1_n = (spdiag(1./s_n)*refObj.tau1_n')'; % obj.tau2_w = (spdiag(1./s_w)*refObj.tau2_w')'; % obj.tau2_e = (spdiag(1./s_e)*refObj.tau2_e')'; % obj.tau2_s = (spdiag(1./s_s)*refObj.tau2_s')'; % obj.tau2_n = (spdiag(1./s_n)*refObj.tau2_n')'; % obj.tau_w = (refObj.e_w'*obj.e1_w*obj.tau1_w')' + (refObj.e_w'*obj.e2_w*obj.tau2_w')'; % obj.tau_e = (refObj.e_e'*obj.e1_e*obj.tau1_e')' + (refObj.e_e'*obj.e2_e*obj.tau2_e')'; % obj.tau_s = (refObj.e_s'*obj.e1_s*obj.tau1_s')' + (refObj.e_s'*obj.e2_s*obj.tau2_s')'; % obj.tau_n = (refObj.e_n'*obj.e1_n*obj.tau1_n')' + (refObj.e_n'*obj.e2_n*obj.tau2_n')'; % % Physical normals % e_w = obj.e_scalar_w; % e_e = obj.e_scalar_e; % e_s = obj.e_scalar_s; % e_n = obj.e_scalar_n; % e_w_vec = obj.e_w; % e_e_vec = obj.e_e; % e_s_vec = obj.e_s; % e_n_vec = obj.e_n; % nu_w = [-1,0]; % nu_e = [1,0]; % nu_s = [0,-1]; % nu_n = [0,1]; % obj.n_w = cell(2,1); % obj.n_e = cell(2,1); % obj.n_s = cell(2,1); % obj.n_n = cell(2,1); % n_w_1 = (1./s_w).*e_w'*(J.*(K{1,1}*nu_w(1) + K{1,2}*nu_w(2))); % n_w_2 = (1./s_w).*e_w'*(J.*(K{2,1}*nu_w(1) + K{2,2}*nu_w(2))); % obj.n_w{1} = spdiag(n_w_1); % obj.n_w{2} = spdiag(n_w_2); % n_e_1 = (1./s_e).*e_e'*(J.*(K{1,1}*nu_e(1) + K{1,2}*nu_e(2))); % n_e_2 = (1./s_e).*e_e'*(J.*(K{2,1}*nu_e(1) + K{2,2}*nu_e(2))); % obj.n_e{1} = spdiag(n_e_1); % obj.n_e{2} = spdiag(n_e_2); % n_s_1 = (1./s_s).*e_s'*(J.*(K{1,1}*nu_s(1) + K{1,2}*nu_s(2))); % n_s_2 = (1./s_s).*e_s'*(J.*(K{2,1}*nu_s(1) + K{2,2}*nu_s(2))); % obj.n_s{1} = spdiag(n_s_1); % obj.n_s{2} = spdiag(n_s_2); % n_n_1 = (1./s_n).*e_n'*(J.*(K{1,1}*nu_n(1) + K{1,2}*nu_n(2))); % n_n_2 = (1./s_n).*e_n'*(J.*(K{2,1}*nu_n(1) + K{2,2}*nu_n(2))); % obj.n_n{1} = spdiag(n_n_1); % obj.n_n{2} = spdiag(n_n_2); % % Operators that extract the normal component % obj.en_w = (obj.n_w{1}*obj.e1_w' + obj.n_w{2}*obj.e2_w')'; % obj.en_e = (obj.n_e{1}*obj.e1_e' + obj.n_e{2}*obj.e2_e')'; % obj.en_s = (obj.n_s{1}*obj.e1_s' + obj.n_s{2}*obj.e2_s')'; % obj.en_n = (obj.n_n{1}*obj.e1_n' + obj.n_n{2}*obj.e2_n')'; % Misc. obj.refObj = refObj; obj.m = refObj.m; obj.h = refObj.h; obj.order = order; obj.grid = g; obj.dim = dim; obj.nGrids = nGrids; end % Closure functions return the operators applied to the own domain to close the boundary % Penalty functions return the operators to force the solution. In the case of an interface it returns the operator applied to the other doamin. % boundary is a string specifying the boundary e.g. 'l','r' or 'e','w','n','s'. % bc is a cell array of component and bc type, e.g. {1, 'd'} for Dirichlet condition % on the first component. Can also be e.g. % {'normal', 'd'} or {'tangential', 't'} for conditions on % tangential/normal component. % data is a function returning the data that should be applied at the boundary. % neighbour_scheme is an instance of Scheme that should be interfaced to. % neighbour_boundary is a string specifying which boundary to interface to. % For displacement bc: % bc = {comp, 'd', dComps}, % where % dComps = vector of components with displacement BC. Default: 1:dim. % In this way, we can specify one BC at a time even though the SATs depend on all BC. function [closure, penalty] = boundary_condition(obj, boundary, bc, tuning) default_arg('tuning', 1.0); assert( iscell(bc), 'The BC type must be a 2x1 or 3x1 cell array' ); [closure, penalty] = obj.refObj.boundary_condition(boundary, bc, tuning); type = bc{2}; switch type case {'F','f','Free','free','traction','Traction','t','T'} s = obj.(['s_' boundary]); s = spdiag(cell2mat(s)); penalty = penalty*s; end end % type Struct that specifies the interface coupling. % Fields: % -- tuning: penalty strength, defaults to 1.0 % -- interpolation: type of interpolation, default 'none' function [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary,type) defaultType.tuning = 1.0; defaultType.interpolation = 'none'; default_struct('type', defaultType); [closure, penalty] = obj.refObj.interface(boundary,neighbour_scheme.refObj,neighbour_boundary,type); end % Returns h11 for the boundary specified by the string boundary. % op -- string function h11 = getBorrowing(obj, boundary) assertIsMember(boundary, {'w', 'e', 's', 'n'}) switch boundary case {'w','e'} h11 = obj.refObj.h11{1}; case {'s', 'n'} h11 = obj.refObj.h11{2}; end end % Returns the outward unit normal vector for the boundary specified by the string boundary. % n is a cell of diagonal matrices for each normal component, n{1} = n_1, n{2} = n_2. function n = getNormal(obj, boundary) error('Not implemented'); assertIsMember(boundary, {'w', 'e', 's', 'n'}) n = obj.(['n_' boundary]); end % Returns the boundary operator op for the boundary specified by the string boundary. % op -- string function o = getBoundaryOperator(obj, op, boundary) assertIsMember(boundary, {'w', 'e', 's', 'n'}) assertIsMember(op, {'e', 'e1', 'e2', 'tau', 'tau1', 'tau2', 'en'}) o = obj.([op, '_', boundary]); end % Returns the boundary operator op for the boundary specified by the string boundary. % op -- string function o = getBoundaryOperatorForScalarField(obj, op, boundary) assertIsMember(boundary, {'w', 'e', 's', 'n'}) assertIsMember(op, {'e_u', 'e_s'}) switch op case 'e_u' o = obj.(['e_', boundary, '_u']); case 'e_s' o = obj.(['e_', boundary, '_s']); end end % Returns the boundary operator T_ij (cell format) for the boundary specified by the string boundary. % Formula: tau_i = T_ij u_j % op -- string function T = getBoundaryTractionOperator(obj, boundary) assertIsMember(boundary, {'w', 'e', 's', 'n'}) T = obj.(['T', '_', boundary]); end % Returns square boundary quadrature matrix, of dimension % corresponding to the number of boundary unknowns % % boundary -- string function H = getBoundaryQuadrature(obj, boundary) assertIsMember(boundary, {'w', 'e', 's', 'n'}) H = obj.getBoundaryQuadratureForScalarField(boundary); I_dim = speye(obj.dim, obj.dim); H = kron(H, I_dim); end % Returns square boundary quadrature matrix, of dimension % corresponding to the number of boundary grid points % % boundary -- string function H_b = getBoundaryQuadratureForScalarField(obj, boundary) assertIsMember(boundary, {'w', 'e', 's', 'n'}) H_b = obj.(['H_', boundary]); end function N = size(obj) N = length(obj.D); end end end