Mercurial > repos > public > sbplib
changeset 1331:60c875c18de3 feature/D2_boundary_opt
Merge with feature/poroelastic for Elastic schemes
| author | Vidar Stiernström <vidar.stiernstrom@it.uu.se> |
|---|---|
| date | Thu, 10 Mar 2022 16:54:26 +0100 |
| parents | 855871e0b852 (diff) 412b8ceafbc6 (current diff) |
| children | 8e9df030a0a5 |
| files | +multiblock/DefCurvilinear.m +multiblock/DiffOp.m +parametrization/Curve.m +parametrization/dataSpline.m +sbp/D2VariableCompatible.m +scheme/Elastic2dCurvilinear.m +scheme/Elastic2dVariable.m diracDiscr.m diracDiscrTest.m |
| diffstat | 65 files changed, 3480 insertions(+), 2020 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+grid/boundaryOptimized.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,54 @@ +% Creates a Cartesian grid of dimension length(m) +% over the domain xlim, ylim, ... +% The grid is non-equidistant in the boundary regions, +% with node placement based on boundary-optimized SBP operators. +% Examples: +% g = grid.boundaryOptimized([mx, my], xlim, ylim, order, opt) +% g = grid.boundaryOptimized([10, 15], {0,1}, {0,2}, 4) - defaults to 'accurate' stencils +% g = grid.boundaryOptimized([10, 15], {0,1}, {0,2}, 4, 'minimal') +function g = boundaryOptimized(m, varargin) + n = length(m); + + % Check that parameters matches dimensions + matchingParams = false; + if length(varargin) == n+1 % Minimal number of arguments + matchingParams = iscell([varargin{1:n}]) && ... + isfloat([varargin{n+1}]); + elseif length(varargin) == n+2 % Stencil options supplied + matchingParams = iscell([varargin{1:n}]) && ... + isfloat([varargin{n+1}]) && ... + ischar([varargin{n+2}]); + end + assert(matchingParams,'grid:boundaryOptimized:NonMatchingParameters','The number of parameters per dimensions do not match.'); + + % Check that stencil options are passed correctly (if supplied) + if length(varargin) == n+2 % Stencil options supplied + availabe_opts = ["Accurate","accurate","A","acc","Minimal","minimal","M","min"]; + assert(any(varargin{n+2} == availabe_opts), ... + 'grid:boundaryOptimized:InvalidOption',"The operator option must be 'accurate' or 'minimal.'"); + else %If not passed, populate varargin with default option 'accurate' + varargin(n+2) = {'accurate'}; + end + + % Specify generating function + switch varargin{n+2} + case {'Accurate','accurate','A','acc'} + gridgenerator = @sbp.grid.accurateBoundaryOptimizedGrid; + case {'Minimal','minimal','M','min'} + gridgenerator = @sbp.grid.minimalBoundaryOptimizedGrid; + end + + X = {}; + h = []; + for i = 1:n + try + [X{i},h(i)] = gridgenerator(varargin{i},m(i),varargin{n+1}); + catch exception % Propagate any errors in the grid generation functions. + msgText = getReport(exception); + error('grid:boundaryOptimized:InvalidParameter',msgText) + end + end + + g = grid.Cartesian(X{:}); + g.h = h; +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+grid/boundaryOptimizedCurvilinear.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,57 @@ +% Creates a curvilinear grid of dimension length(m). +% over the logical domain xi_lim, eta_lim, ... +% The grid point distribution is based on the boundary +% optimized SBP operators, passed as arguments, order +% and opt. +% Examples: +% g = grid.boundaryOptimizedCurvilinear(mapping, [mx, my], xlim, ylim, order, opt) +% g = grid.boundaryOptimizedCurvilinear(mapping, [10, 15], {0,1}, {0,2}, 4) - defaults to 'accurate' stencils +% g = grid.boundaryOptimizedCurvilinear(mapping, [10, 15], {0,1}, {0,2}, 4, 'minimal') +function g = boundaryOptimizedCurvilinear(mapping, m, varargin) + n = length(m); + % TODO: The input parameter check is also present in boundaryOptimizedGrid.m, + % Consider refactoring it. + + % Check that parameters matches dimensions + matchingParams = false; + if length(varargin) == n+1 % Minimal number of arguments + matchingParams = iscell([varargin{1:n}]) && ... + isfloat([varargin{n+1}]); + elseif length(varargin) == n+2 % Stencil options supplied + matchingParams = iscell([varargin{1:n}]) && ... + isfloat([varargin{n+1}]) && ... + ischar([varargin{n+2}]); + end + assert(matchingParams,'grid:boundaryOptimizedCurvilinear:NonMatchingParameters','The number of parameters per dimensions do not match.'); + + % Check that stencil options are passed correctly (if supplied) + if length(varargin) == n+2 % Stencil options supplied + availabe_opts = ["Accurate","accurate","A","acc","Minimal","minimal","M","min"]; + assert(any(varargin{n+2} == availabe_opts), ... + 'grid:boundaryOptimizedCurvilinear:InvalidOption',"The operator option must be 'accurate' or 'minimal.'"); + else %If not passed, populate varargin with default option 'accurate' + varargin(n+2) = {'accurate'}; + end + + % Specify generating function + switch varargin{n+2} + case {'Accurate','accurate','A','acc'} + gridgenerator = @sbp.grid.accurateBoundaryOptimizedGrid; + case {'Minimal','minimal','M','min'} + gridgenerator = @sbp.grid.minimalBoundaryOptimizedGrid; + end + + X = {}; + h = []; + for i = 1:n + try + [X{i},h(i)] = gridgenerator(varargin{i},m(i),varargin{n+1}); + catch exception % Propagate any errors in the grid generation functions. + msgText = getReport(exception); + error('grid:boundaryOptimizedCurvilinear:InvalidParameter',msgText) + end + end + + g = grid.Curvilinear(mapping, X{:}); + g.logic.h = h; +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+grid/boundaryOptimizedTest.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,111 @@ +function tests = boundaryOptimizedTest() + tests = functiontests(localfunctions); +end + +function testErrorInvalidParam(testCase) + in = { + %Invalid order + {[10 10],{0,1},{0,2},3}, + %Invalid grid size + {5, {0,1}, 4}, + {[10 5],{0,1},{0,2},4}, + {[10 5],{0,1},{0,2},6,'M'}, + %Invalid limits + {10,{1},4}, + {[10,10],{0,1},{1},4}, + {[10,10],{1},{1,0},4}, + {10,{1,0},4}, + {[10, 5],{1,0},{0,-1},4}, + }; + + for i = 1:length(in) + testCase.verifyError(@()grid.boundaryOptimized(in{i}{:}),'grid:boundaryOptimized:InvalidParameter',sprintf('in(%d) = %s',i,toString(in{i}))); + end +end + +function testErrorInvalidOption(testCase) + in = { + {[8 8],{0,1},{0,2},4,'acrurate'}, + }; + + for i = 1:length(in) + testCase.verifyError(@()grid.boundaryOptimized(in{i}{:}),'grid:boundaryOptimized:InvalidOption',sprintf('in(%d) = %s',i,toString(in{i}))); + end +end + +function testErrorNonMatchingParam(testCase) + in = { + {[],{1},4}, + {[],{0,1},{0,1},4}, + {[5,5],{0,1},{0,1},{0,1},4}, + {[5,5,4],{0,1},{0,1},4,'accurate'} + {[5,5,4],{0,1},{0,1},{0,1},4,4}, + }; + + for i = 1:length(in) + testCase.verifyError(@()grid.boundaryOptimized(in{i}{:}),'grid:boundaryOptimized:NonMatchingParameters',sprintf('in(%d) = %s',i,toString(in{i}))); + end +end + +% Tests that the expected grid points are obtained for a boundary optimized grid with a 4th order +% accurate stencil and 8th order minimal stencil. +% The boundary grid point distance weights are taken from the D1Nonequidistant operators and +% grid spacing is calculated according to Mattsson et al 2018. +function testCompiles(testCase) + + %% 1D 4th order accurate stencil + % Boundary weights, number of non-equidistantly spaced points for 4th order accurate stencil + bw = [0.0000000000000e+00 6.8764546205559e-01 1.8022115125776e+00]; + n = length(bw)-1; + xi_n = bw(end); + + % Grid points in x-direction. + Lx = 1; + mx = 8; + hx_4 = Lx/(2*xi_n+(mx-2*n-1)); + + bp_l = hx_4*bw; + bp_r = Lx-flip(hx_4*bw); + interior = [hx_4*(xi_n+1) hx_4*(xi_n+2)]; + x_4 = [bp_l interior bp_r]; + + % Boundary weights, number of non-equidistantly spaced points for 8th order minimal stencil + bw = [0.0000000000000e+00, 4.9439570885261e-01, 1.4051531374839e+00]; + n = length(bw)-1; + xi_n = bw(end); + + %% 2D 8th order minimal stencil + % Grid points in x-direction. + hx_8 = Lx/(2*xi_n+(mx-2*n-1)); + + bp_l = hx_8*bw; + bp_r = Lx-flip(hx_8*bw); + interior = [hx_8*(xi_n+1) hx_8*(xi_n+2)]; + x_8 = [bp_l interior bp_r]; + + % Grid points in y-direction. + Ly = 2; + my = 9; + hy = Ly/(2*xi_n+(my-2*n-1)); + + bp_l = hy*bw; + bp_r = Ly-flip(hy*bw); + interior = [hy*(xi_n+1) hy*(xi_n+2) hy*(xi_n+3)]; + y = [bp_l interior bp_r]; + + in = { + {mx, {0,Lx},4}, + {[mx, my],{0,Lx},{0,Ly},8,'M'}, + }; + + out = { + {[x_4'],hx_4} + {[kr(x_8',ones(size(y'))),kr(ones(size(x_8')),y')],[hx_8, hy]} + }; + + for i = 1:length(in) + g = grid.boundaryOptimized(in{i}{:}); + testCase.verifyEqual(g.points(),out{i}{1},'AbsTol', 1e-14, 'RelTol', 1e-14); + testCase.verifyEqual(g.scaling(),out{i}{2},'AbsTol', 1e-14, 'RelTol', 1e-14); + end +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+multiblock/+domain/Annulus.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,74 @@ +classdef Annulus < multiblock.DefCurvilinear + properties + r_inner % Radii of inner disk + c_inner % Center of inner disk + r_outer % Radii of outer disk + c_outer % Radii of outer disk + end + + methods + function obj = Annulus(r_inner, c_inner, r_outer, c_outer) + default_arg('r_inner', 0.3); + default_arg('c_inner', [0; 0]); + default_arg('r_outer', 1) + default_arg('c_outer', [0; 0]); + % Assert that the problem is well-defined + d = norm(c_outer-c_inner,2); + assert(r_inner > 0, 'Inner radius must be greater than zero'); + assert(r_outer > d+r_inner, 'Inner disk not contained in outer disk'); + + cir_out_A = parametrization.Curve.circle(c_outer,r_outer,[-pi/2 pi/2]); + cir_in_A = parametrization.Curve.circle(c_inner,r_inner,[pi/2 -pi/2]); + + cir_out_B = parametrization.Curve.circle(c_outer,r_outer,[pi/2 3*pi/2]); + cir_in_B = parametrization.Curve.circle(c_inner,r_inner,[3*pi/2 pi/2]); + + c0_out = cir_out_A(0); + c1_out = cir_out_A(1); + + c0_in_A = cir_in_A(1); + c1_in_A = cir_in_A(0); + + c0_out_B = cir_out_B(0); + c1_out_B = cir_out_B(1); + + c0_in_B = cir_in_B(1); + c1_in_B = cir_in_B(0); + + + sp2_A = parametrization.Curve.line(c0_in_A,c0_out); + sp3_A = parametrization.Curve.line(c1_in_A,c1_out); + + sp2_B = parametrization.Curve.line(c0_in_B,c0_out_B); + sp3_B = parametrization.Curve.line(c1_in_B,c1_out_B); + + + A = parametrization.Ti(sp2_A, cir_out_A, sp3_A.reverse, cir_in_A); + B = parametrization.Ti(sp2_B , cir_out_B,sp3_B.reverse, cir_in_B ); + + blocks = {A,B}; + blocksNames = {'A','B'}; + + conn = cell(2,2); + + conn{1,2} = {'n','s'}; + conn{2,1} = {'n','s'}; + + boundaryGroups = struct(); + boundaryGroups.out = multiblock.BoundaryGroup({{1,'e'},{2,'e'}}); + boundaryGroups.in = multiblock.BoundaryGroup({{1,'w'},{2,'w'}}); + boundaryGroups.all = multiblock.BoundaryGroup({{1,'e'},{2,'w'},{1,'w'},{2,'e'}}); + + obj = obj@multiblock.DefCurvilinear(blocks, conn, boundaryGroups, blocksNames); + + obj.r_inner = r_inner; + obj.r_outer = r_outer; + obj.c_inner = c_inner; + obj.c_outer = c_outer; + end + + function ms = getGridSizes(obj, m) + ms = {[m m], [m m]}; + end + end +end
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+multiblock/+domain/Line.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,153 @@ +classdef Line < multiblock.Definition + properties + + xlims + blockNames % Cell array of block labels + nBlocks + connections % Cell array specifying connections between blocks + boundaryGroups % Structure of boundaryGroups + + end + + + methods + % Creates a divided line + % x is a vector of boundary and interface positions. + % blockNames: cell array of labels. The id is default. + function obj = Line(x,blockNames) + default_arg('blockNames',[]); + + N = length(x)-1; % number of blocks in the x direction. + + if ~issorted(x) + error('The elements of x seem to be in the wrong order'); + end + + % Dimensions of blocks and number of points + blockTi = cell(N,1); + xlims = cell(N,1); + for i = 1:N + xlims{i} = {x(i), x(i+1)}; + end + + % Interface couplings + conn = cell(N,N); + for i = 1:N + conn{i,i+1} = {'r','l'}; + end + + % Block names (id number as default) + if isempty(blockNames) + obj.blockNames = cell(1, N); + for i = 1:N + obj.blockNames{i} = sprintf('%d', i); + end + else + assert(length(blockNames) == N); + obj.blockNames = blockNames; + end + nBlocks = N; + + % Boundary groups + boundaryGroups = struct(); + L = { {1, 'l'} }; + R = { {N, 'r'} }; + boundaryGroups.L = multiblock.BoundaryGroup(L); + boundaryGroups.R = multiblock.BoundaryGroup(R); + boundaryGroups.all = multiblock.BoundaryGroup([L,R]); + + obj.connections = conn; + obj.nBlocks = nBlocks; + obj.boundaryGroups = boundaryGroups; + obj.xlims = xlims; + + end + + + % Returns a multiblock.Grid given some parameters + % ms: cell array of m values + % For same m in every block, just input one scalar. + function g = getGrid(obj, ms, varargin) + + default_arg('ms',21) + + % Extend ms if input is a single scalar + if (numel(ms) == 1) && ~iscell(ms) + m = ms; + ms = cell(1,obj.nBlocks); + for i = 1:obj.nBlocks + ms{i} = m; + end + end + + grids = cell(1, obj.nBlocks); + for i = 1:obj.nBlocks + grids{i} = grid.equidistant(ms{i}, obj.xlims{i}); + end + + g = multiblock.Grid(grids, obj.connections, obj.boundaryGroups); + end + + % Returns a multiblock.Grid given some parameters + % ms: cell array of m values + % For same m in every block, just input one scalar. + function g = getStaggeredGrid(obj, ms, varargin) + + default_arg('ms',21) + + % Extend ms if input is a single scalar + if (numel(ms) == 1) && ~iscell(ms) + m = ms; + ms = cell(1,obj.nBlocks); + for i = 1:obj.nBlocks + ms{i} = m; + end + end + + grids = cell(1, obj.nBlocks); + for i = 1:obj.nBlocks + [g_primal, g_dual] = grid.primalDual1D(ms{i}, obj.xlims{i}); + grids{i} = grid.Staggered1d(g_primal, g_dual); + end + + g = multiblock.Grid(grids, obj.connections, obj.boundaryGroups); + end + + % label is the type of label used for plotting, + % default is block name, 'id' show the index for each block. + function show(obj, label) + default_arg('label', 'name') + + m = 10; + figure + for i = 1:obj.nBlocks + x = linspace(obj.xlims{i}{1}, obj.xlims{i}{2}, m); + y = 0*x + 0.05* ( (-1)^i + 1 ) ; + plot(x,y,'+'); + hold on + end + hold off + + switch label + case 'name' + labels = obj.blockNames; + case 'id' + labels = {}; + for i = 1:obj.nBlocks + labels{i} = num2str(i); + end + otherwise + axis equal + return + end + + legend(labels) + axis equal + end + + % Returns the grid size of each block in a cell array + % The input parameters are determined by the subclass + function ms = getGridSizes(obj, varargin) + end + end +end
--- a/+multiblock/+domain/Rectangle.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+multiblock/+domain/Rectangle.m Thu Mar 10 16:54:26 2022 +0100 @@ -93,7 +93,7 @@ N_id = flat_index(m,j,1); S{j} = {S_id,'s'}; N{j} = {N_id,'n'}; - end + end boundaryGroups.E = multiblock.BoundaryGroup(E); boundaryGroups.W = multiblock.BoundaryGroup(W); boundaryGroups.S = multiblock.BoundaryGroup(S); @@ -117,6 +117,20 @@ % Returns a multiblock.Grid given some parameters % ms: cell array of [mx, my] vectors % For same [mx, my] in every block, just input one vector. + % Currently defaults to equidistant grid if varargin is empty. + % If varargin is non-empty, the first argument should supply the grid type, followed by + % additional arguments required to construct the grid. + % Grid types: + % 'equidist' - equidistant grid + % Additional argumets: none + % 'boundaryopt' - boundary optimized grid based on boundary + % optimized SBP operators + % Additional arguments: order, stencil option + % Example: g = getGrid() - the local blocks are 21x21 equidistant grids. + % g = getGrid(ms,) - block i is an equidistant grid with size given by ms{i}. + % g = getGrid(ms,'equidist') - block i is an equidistant grid with size given by ms{i}. + % g = getGrid(ms,'boundaryopt',4,'minimal') - block i is a Cartesian grid with size given by ms{i} + % and nodes placed according to the boundary optimized minimal 4th order SBP operator. function g = getGrid(obj, ms, varargin) default_arg('ms',[21,21]) @@ -129,10 +143,19 @@ ms{i} = m; end end - + if isempty(varargin) || strcmp(varargin{1},'equidist') + gridgenerator = @(m,xlim,ylim)grid.equidistant(m,xlim,ylim); + elseif strcmp(varargin{1},'boundaryopt') + order = varargin{2}; + stenciloption = varargin{3}; + gridgenerator = @(m,xlim,ylim)grid.boundaryOptimized(m,xlim,ylim,... + order,stenciloption); + else + error('No grid type supplied!'); + end grids = cell(1, obj.nBlocks); for i = 1:obj.nBlocks - grids{i} = grid.equidistant(ms{i}, obj.xlims{i}, obj.ylims{i}); + grids{i} = gridgenerator(ms{i}, obj.xlims{i}, obj.ylims{i}); end g = multiblock.Grid(grids, obj.connections, obj.boundaryGroups);
--- a/+multiblock/DefCurvilinear.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+multiblock/DefCurvilinear.m Thu Mar 10 16:54:26 2022 +0100 @@ -37,13 +37,39 @@ obj.boundaryGroups = boundaryGroups; end - function g = getGrid(obj, varargin) - ms = obj.getGridSizes(varargin{:}); + % Returns a multiblock.Grid given some parameters + % ms: cell array of [mx, my] vectors + % Currently defaults to an equidistant curvilinear grid if varargin is empty. + % If varargin is non-empty, the first argument should supply the grid type, followed by + % additional arguments required to construct the grid. + % Grid types: + % 'equidist' - equidistant curvilinear grid + % Additional argumets: none + % 'boundaryopt' - boundary optimized grid based on boundary + % optimized SBP operators + % Additional arguments: order, stencil option + function g = getGrid(obj, ms, varargin) + % If a scalar is passed, defer to getGridSizes implemented by subclass + % TODO: This forces the interface of subclasses. + % Should ms be included in varargin? Figure out bow to do it properly + if length(ms) == 1 + ms = obj.getGridSizes(ms); + end - grids = cell(1, obj.nBlocks); - for i = 1:obj.nBlocks - grids{i} = grid.equidistantCurvilinear(obj.blockMaps{i}.S, ms{i}); - end + if isempty(varargin) || strcmp(varargin{1},'equidist') + gridgenerator = @(blockMap,m) grid.equidistantCurvilinear(blockMap, m); + elseif strcmp(varargin{1},'boundaryopt') + order = varargin{2}; + stenciloption = varargin{3}; + gridgenerator = @(blockMap,m) grid.boundaryOptimizedCurvilinear(blockMap,m,{0,1},{0,1},... + order,stenciloption); + else + error('No grid type supplied!'); + end + grids = cell(1, obj.nBlocks); + for i = 1:obj.nBlocks + grids{i} = gridgenerator(obj.blockMaps{i}.S, ms{i}); + end g = multiblock.Grid(grids, obj.connections, obj.boundaryGroups); end
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+multiblock/LaplaceSquared.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,105 @@ +classdef LaplaceSquared < scheme.Scheme + properties + grid + order + laplaceDiffOp + + D + H + Hi + + a,b + end + + methods + % Discretisation of a*nabla*b*nabla + function obj = LaplaceSquared(g, order, a, b, opGen) + default_arg('order', 4); + default_arg('a', 1); + default_arg('b', 1); + default_arg('opGen', @sbp.D4Variable); + + if isscalar(a) + a = grid.evalOn(g, a); + end + + if isscalar(b) + b = grid.evalOn(g, b); + end + + obj.grid = g; + obj.order = order; + obj.a = a; + obj.b = b; + + obj.laplaceDiffOp = multiblock.Laplace(g, order, 1, 1, opGen); + + obj.H = obj.laplaceDiffOp.H; + obj.Hi = spdiag(1./diag(obj.H)); + + A = spdiag(a); + B = spdiag(b); + + D_laplace = obj.laplaceDiffOp.D; + obj.D = A*D_laplace*B*D_laplace; + end + + function s = size(obj) + s = size(obj.laplaceDiffOp); + end + + function op = getBoundaryOperator(obj, opName, boundary) + switch opName + case 'e' + op = getBoundaryOperator(obj.laplaceDiffOp, 'e', boundary); + case 'd1' + op = getBoundaryOperator(obj.laplaceDiffOp, 'd', boundary); + case 'd2' + e = getBoundaryOperator(obj.laplaceDiffOp, 'e', boundary); + op = (e'*obj.laplaceDiffOp.D)'; + case 'd3' + d1 = getBoundaryOperator(obj.laplaceDiffOp, 'd', boundary); + op = (d1'*spdiag(obj.b)*obj.laplaceDiffOp.D)'; + end + end + + function op = getBoundaryQuadrature(obj, boundary) + op = getBoundaryQuadrature(obj.laplaceDiffOp, boundary); + end + + function [closure, penalty] = boundary_condition(obj,boundary,type) % TODO: Change name to boundaryCondition + switch type + case 'e' + error('Bc of type ''e'' not implemented') + case 'd1' + error('Bc of type ''d1'' not implemented') + case 'd2' + e = obj.getBoundaryOperator('e', boundary); + d1 = obj.getBoundaryOperator('d1', boundary); + d2 = obj.getBoundaryOperator('d2', boundary); + H_b = obj.getBoundaryQuadrature(boundary); + + A = spdiag(obj.a); + B_b = spdiag(e'*obj.b); + + tau = obj.Hi*A*d1*B_b*H_b; + closure = tau*d2'; + penalty = -tau; + case 'd3' + e = obj.getBoundaryOperator('e', boundary); + d3 = obj.getBoundaryOperator('d3', boundary); + H_b = obj.getBoundaryQuadrature(boundary); + + A = spdiag(obj.a); + + tau = -obj.Hi*A*e*H_b; + closure = tau*d3'; + penalty = -tau; + end + end + + function [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary) + error('Not implemented') + end + end +end
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+multiblock/joinGrids.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,90 @@ +% Connects several multiblock grids into one grid +% gs -- Cell array of multiblock grids +% gConnections -- Upper-triangular cell matrix +% gConnections{i,j} specifies all connections between grid i and grid j +% Example: +% gConnections{i,j} = { {{1,'e'},{2,'w'}}, {{5,'s'},{2,'n'}},... }; +% names -- (Optional) cell array of strings, used for boundary groups in new grid +% default: names = {'g1', 'g2', ..., 'gN'}; +% Boundary groups from grid i are contained in g.boundaryGroups.(names{i}), etc. +function g = joinGrids(gs, gConnections, names) + + nGrids = numel(gs); + + % Default names are {'g1', 'g2', ... 'gN'}. + defaultNames = cell(nGrids, 1); + for i = 1:nGrids + defaultNames{i} = sprintf('g%d',i); + end + default_arg('names', defaultNames); + + nBlocks = 0; + for i = 1:nGrids + nBlocks = nBlocks + gs{i}.nBlocks(); + end + + % Create vector of cumulative sum of number of blocks per grid + startIndex = zeros(1, nGrids); + for i = 2:nGrids + startIndex(i) = startIndex(i-1) + gs{i-1}.nBlocks(); + end + + % Create cell array of all grids + grids = cell(nBlocks, 1); + for i = 1:nGrids + for j = 1:gs{i}.nBlocks(); + grids{startIndex(i)+j} = gs{i}.grids{j}; + end + end + + % Create cell matrix of connections + connections = cell(nBlocks, nBlocks); + + % Connections within grids + for i = 1:nGrids + for j = 1:gs{i}.nBlocks() + for k = 1:gs{i}.nBlocks() + connections{startIndex(i)+j,startIndex(i)+k} = gs{i}.connections{j,k}; + end + end + end + + % Connections between grids + for i = 1:nGrids + for j = 1:nGrids + for k = 1:numel(gConnections{i,j}) + b1 = gConnections{i,j}{k}{1}; + id1 = b1{1}; + str1 = b1{2}; + + b2 = gConnections{i,j}{k}{2}; + id2 = b2{1}; + str2 = b2{2}; + + connections{startIndex(i)+id1, startIndex(j)+id2} = {str1, str2}; + end + end + end + + % Boundary groups + boundaryGroups = struct; + for i = 1:nGrids + bgs = gs{i}.boundaryGroups; + bgNames = fieldnames(bgs); + for j = 1:numel(bgNames) + bg = bgs.(bgNames{j}); + + % Shift block id:s in boundary groups + for k = 1:length(bg) + bg{k}{1} = bg{k}{1} + startIndex(i); + end + + bgs.(bgNames{j}) = bg; + end + boundaryGroups.(names{i}) = bgs; + end + + % Create grid object + g = multiblock.Grid(grids, connections, boundaryGroups); + +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+grid/accurateBoundaryOptimizedGrid.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,67 @@ +% Computes the grid points x and grid spacing h used by the boundary optimized SBP operators +% with improved boundary accuracy, presented in +% 'Boundary optimized diagonal-norm SBP operators - Mattsson, Almquist, van der Weide 2018'. +% +% lim - cell array with domain limits +% N - Number of grid points +% order - order of accuracy of sbp operator. +function [x,h] = accurateBoundaryOptimizedGrid(lim,N,order) + assert(iscell(lim) && numel(lim) == 2,'The limit should be cell array with 2 elements.'); + L = lim{2} - lim{1}; + assert(L>0,'Limits must be given in increasing order.'); + %%%% Non-equidistant grid points %%%%% + xb = boundaryPoints(order); + m = length(xb)-1; % Number of non-equidistant points + assert(N-2*(m+1)>=0,'Not enough grid points to contain the boundary region. Requires at least %d points.',2*(m+1)); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Compute h %%%%%%%%%% + h = L/(2*xb(end) + N-1-2*m); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Define grid %%%%%%%% + x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; + x = x + lim{1}; + %%%%%%%%%%%%%%%%%%%%%%%%% +end +function xb = boundaryPoints(order) + switch order + case 4 + x0 = 0.0000000000000e+00; + x1 = 6.8764546205559e-01; + x2 = 1.8022115125776e+00; + xb = [x0 x1 x2]'; + case 6 + x0 = 0.0000000000000e+00; + x1 = 4.4090263368623e-01; + x2 = 1.2855984345073e+00; + x3 = 2.2638953951239e+00; + xb = [x0 x1 x2 x3]'; + case 8 + x0 = 0.0000000000000e+00; + x1 = 3.8118550247622e-01; + x2 = 1.1899550868338e+00; + x3 = 2.2476300175641e+00; + x4 = 3.3192851303204e+00; + xb = [x0 x1 x2 x3 x4]'; + case 10 + x0 = 0.0000000000000e+00; + x1 = 3.5902433622052e-01; + x2 = 1.1436659188355e+00; + x3 = 2.2144895894456e+00; + x4 = 3.3682742337736e+00; + x5 = 4.4309689056870e+00; + xb = [x0 x1 x2 x3 x4 x5]'; + case 12 + x0 = 0.0000000000000e+00; + x1 = 3.6098032343909e-01; + x2 = 1.1634317168086e+00; + x3 = 2.2975905356987e+00; + x4 = 3.6057529790929e+00; + x5 = 4.8918275675510e+00; + x6 = 6.0000000000000e+00; + xb = [x0 x1 x2 x3 x4 x5 x6]'; + otherwise + error('Invalid operator order %d.',order); + end +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+grid/minimalBoundaryOptimizedGrid.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,60 @@ +% Computes the grid points x and grid spacing h used by the boundary optimized SBP operators +% with minimal number of non-equidistant boundary points, presented in +% 'Boundary optimized diagonal-norm SBP operators - Mattsson, Almquist, van der Weide 2018'. +% +% lim - cell array with domain limits +% N - Number of grid points +% order - order of accuracy of sbp operator. +function [x,h] = minimalBoundaryOptimizedGrid(lim,N,order) + assert(iscell(lim) && numel(lim) == 2,'The limit should be a cell array with 2 elements.'); + L = lim{2} - lim{1}; + assert(L>0,'Limits must be given in increasing order.'); + %%%% Non-equidistant grid points %%%%% + xb = boundaryPoints(order); + m = length(xb)-1; % Number of non-equidistant points + assert(N-2*(m+1)>=0,'Not enough grid points to contain the boundary region. Requires at least %d points.',2*(m+1)); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Compute h %%%%%%%%%% + h = L/(2*xb(end) + N-1-2*m); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Define grid %%%%%%%% + x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; + x = x + lim{1}; + %%%%%%%%%%%%%%%%%%%%%%%%% +end + +function xb = boundaryPoints(order) + switch order + case 4 + x0 = 0.0000000000000e+00; + x1 = 7.7122987842562e-01; + xb = [x0 x1]'; + case 6 + x0 = 0.0000000000000e+00; + x1 = 4.0842950991998e-01; + x2 = 1.1968523189207e+00; + xb = [x0 x1 x2]'; + case 8 + x0 = 0.0000000000000e+00; + x1 = 4.9439570885261e-01; + x2 = 1.4051531374839e+00; + xb = [x0 x1 x2]'; + case 10 + x0 = 0.0000000000000e+00; + x1 = 5.8556160757529e-01; + x2 = 1.7473267488572e+00; + x3 = 3.0000000000000e+00; + xb = [x0 x1 x2 x3]'; + case 12 + x0 = 0.0000000000000e+00; + x1 = 4.6552112904489e-01; + x2 = 1.4647984306493e+00; + x3 = 2.7620429464763e+00; + x4 = 4.0000000000000e+00; + xb = [x0 x1 x2 x3 x4]'; + otherwise + error('Invalid operator order %d.',order); + end +end \ No newline at end of file
--- a/+sbp/+implementations/d1_noneq_10.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_10.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,48 +1,12 @@ -function [D1,H,x,h] = d1_noneq_10(N,L) +function [D1,H] = d1_noneq_10(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<20) error('Operator requires at least 20 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 10; -m = 5; -order = 10; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 3.5902433622052e-01; -x2 = 1.1436659188355e+00; -x3 = 2.2144895894456e+00; -x4 = 3.3682742337736e+00; -x5 = 4.4309689056870e+00; -x6 = 5.4309689056870e+00; -x7 = 6.4309689056870e+00; -x8 = 7.4309689056870e+00; -x9 = 8.4309689056870e+00; -x10 = 9.4309689056870e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -69,22 +33,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 10; +d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_12.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_12.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,50 +1,12 @@ -function [D1,H,x,h] = d1_noneq_12(N,L) +function [D1,H] = d1_noneq_12(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<24) error('Operator requires at least 24 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 12; -m = 6; -order = 12; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 3.6098032343909e-01; -x2 = 1.1634317168086e+00; -x3 = 2.2975905356987e+00; -x4 = 3.6057529790929e+00; -x5 = 4.8918275675510e+00; -x6 = 6.0000000000000e+00; -x7 = 7.0000000000000e+00; -x8 = 8.0000000000000e+00; -x9 = 9.0000000000000e+00; -x10 = 1.0000000000000e+01; -x11 = 1.1000000000000e+01; -x12 = 1.2000000000000e+01; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -73,22 +35,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 12; +d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_4.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_4.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,42 +1,12 @@ -function [D1,H,x,h] = d1_noneq_4(N,L) +function [D1,H] = d1_noneq_4(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<8) error('Operator requires at least 8 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 4; -m = 2; -order = 4; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 6.8764546205559e-01; -x2 = 1.8022115125776e+00; -x3 = 2.8022115125776e+00; -x4 = 3.8022115125776e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -57,22 +27,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 4; +d = [1/12,-2/3,0,2/3,-1/12]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_6.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_6.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,44 +1,12 @@ -function [D1,H,x,h] = d1_noneq_6(N,L) +function [D1,H] = d1_noneq_6(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<12) error('Operator requires at least 12 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 6; -m = 3; -order = 6; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 4.4090263368623e-01; -x2 = 1.2855984345073e+00; -x3 = 2.2638953951239e+00; -x4 = 3.2638953951239e+00; -x5 = 4.2638953951239e+00; -x6 = 5.2638953951239e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -61,22 +29,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 6; +d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_8.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_8.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,46 +1,12 @@ -function [D1,H,x,h] = d1_noneq_8(N,L) +function [D1,H] = d1_noneq_8(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<16) error('Operator requires at least 16 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 8; -m = 4; -order = 8; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 3.8118550247622e-01; -x2 = 1.1899550868338e+00; -x3 = 2.2476300175641e+00; -x4 = 3.3192851303204e+00; -x5 = 4.3192851303204e+00; -x6 = 5.3192851303204e+00; -x7 = 6.3192851303204e+00; -x8 = 7.3192851303204e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -65,22 +31,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 8; +d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_minimal_10.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_minimal_10.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,46 +1,12 @@ -function [D1,H,x,h] = d1_noneq_minimal_10(N,L) +function [D1,H] = d1_noneq_minimal_10(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<16) error('Operator requires at least 16 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 8; -m = 3; -order = 10; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 5.8556160757529e-01; -x2 = 1.7473267488572e+00; -x3 = 3.0000000000000e+00; -x4 = 4.0000000000000e+00; -x5 = 5.0000000000000e+00; -x6 = 6.0000000000000e+00; -x7 = 7.0000000000000e+00; -x8 = 8.0000000000000e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -65,22 +31,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 10; +d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_minimal_12.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_minimal_12.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,48 +1,12 @@ -function [D1,H,x,h] = d1_noneq_minimal_12(N,L) +function [D1,H] = d1_noneq_minimal_12(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<20) error('Operator requires at least 20 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 10; -m = 4; -order = 12; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 4.6552112904489e-01; -x2 = 1.4647984306493e+00; -x3 = 2.7620429464763e+00; -x4 = 4.0000000000000e+00; -x5 = 5.0000000000000e+00; -x6 = 6.0000000000000e+00; -x7 = 7.0000000000000e+00; -x8 = 8.0000000000000e+00; -x9 = 9.0000000000000e+00; -x10 = 1.0000000000000e+01; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -69,22 +33,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 12; +d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_minimal_4.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_minimal_4.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,41 +1,12 @@ -function [D1,H,x,h] = d1_noneq_minimal_4(N,L) +function [D1,H] = d1_noneq_minimal_4(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<6) error('Operator requires at least 6 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 3; -m = 1; -order = 4; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 7.7122987842562e-01; -x2 = 1.7712298784256e+00; -x3 = 2.7712298784256e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -55,22 +26,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 4; +d = [1/12,-2/3,0,2/3,-1/12]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_minimal_6.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_minimal_6.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,43 +1,12 @@ -function [D1,H,x,h] = d1_noneq_minimal_6(N,L) +function [D1,H] = d1_noneq_minimal_6(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<10) error('Operator requires at least 10 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 5; -m = 2; -order = 6; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 4.0842950991998e-01; -x2 = 1.1968523189207e+00; -x3 = 2.1968523189207e+00; -x4 = 3.1968523189207e+00; -x5 = 4.1968523189207e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -59,22 +28,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 6; +d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- a/+sbp/+implementations/d1_noneq_minimal_8.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/+implementations/d1_noneq_minimal_8.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,44 +1,12 @@ -function [D1,H,x,h] = d1_noneq_minimal_8(N,L) +function [D1,H] = d1_noneq_minimal_8(N,h) -% L: Domain length % N: Number of grid points -if(nargin < 2) - L = 1; -end - if(N<12) error('Operator requires at least 12 grid points'); end % BP: Number of boundary points -% m: Number of nonequidistant spacings -% order: Accuracy of interior stencil BP = 6; -m = 2; -order = 8; - -%%%% Non-equidistant grid points %%%%% -x0 = 0.0000000000000e+00; -x1 = 4.9439570885261e-01; -x2 = 1.4051531374839e+00; -x3 = 2.4051531374839e+00; -x4 = 3.4051531374839e+00; -x5 = 4.4051531374839e+00; -x6 = 5.4051531374839e+00; - -xb = sparse(m+1,1); -for i = 0:m - xb(i+1) = eval(['x' num2str(i)]); -end -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Compute h %%%%%%%%%% -h = L/(2*xb(end) + N-1-2*m); -%%%%%%%%%%%%%%%%%%%%%%%%% - -%%%% Define grid %%%%%%%% -x = h*[xb; linspace(xb(end)+1,L/h-xb(end)-1,N-2*(m+1))'; L/h-flip(xb) ]; -%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Norm matrix %%%%%%%% P = sparse(BP,1); @@ -61,22 +29,9 @@ %%%%%%%%%%%%%%%%%%%%%%%%% %%%% Q matrix %%%%%%%%%%% - % interior stencil -switch order - case 2 - d = [-1/2,0,1/2]; - case 4 - d = [1/12,-2/3,0,2/3,-1/12]; - case 6 - d = [-1/60,3/20,-3/4,0,3/4,-3/20,1/60]; - case 8 - d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; - case 10 - d = [-1/1260,5/504,-5/84,5/21,-5/6,0,5/6,-5/21,5/84,-5/504,1/1260]; - case 12 - d = [1/5544,-1/385,1/56,-5/63,15/56,-6/7,0,6/7,-15/56,5/63,-1/56,1/385,-1/5544]; -end +order = 8; +d = [1/280,-4/105,1/5,-4/5,0,4/5,-1/5,4/105,-1/280]; d = repmat(d,N,1); Q = spdiags(d,-order/2:order/2,N,N);
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+implementations/d2_noneq_variable_10.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,323 @@ +function [H, HI, D1, D2, DI] = d2_noneq_variable_10(N, h, options) + % N: Number of grid points + % h: grid spacing + % options: struct containing options for constructing the operator + % current options are: + % options.stencil_type ('minimal','nonminimal','wide') + % options.AD ('upwind', 'op') + + % BP: Number of boundary points + % order: Accuracy of interior stencil + BP = 10; + order = 10; + if(N<2*BP) + error(['Operator requires at least ' num2str(2*BP) ' grid points']); + end + + %%%% Norm matrix %%%%%%%% + P = zeros(BP, 1); + P0 = 1.0000000000000e-01; + P1 = 5.8980851260667e-01; + P2 = 9.5666820955973e-01; + P3 = 1.1500297411596e+00; + P4 = 1.1232986993248e+00; + P5 = 1.0123020150951e+00; + P6 = 9.9877122702527e-01; + P7 = 1.0000873322761e+00; + P8 = 1.0000045540888e+00; + P9 = 9.9999861455083e-01; + + for i = 0:BP - 1 + P(i + 1) = eval(['P' num2str(i)]); + end + + Hv = ones(N, 1); + Hv(1:BP) = P; + Hv(end - BP + 1:end) = flip(P); + Hv = h * Hv; + H = spdiags(Hv, 0, N, N); + HI = spdiags(1 ./ Hv, 0, N, N); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Q matrix %%%%%%%%%%% + + % interior stencil + d = [-1/1260, 5/504, -5/84, 5/21, -5/6, 0, 5/6, -5/21, 5/84, -5/504, 1/1260]; + d = repmat(d, N, 1); + Q = spdiags(d, -order / 2:order / 2, N, N); + + % Boundaries + Q0_0 = -5.0000000000000e-01; + Q0_1 = 6.7548747038002e-01; + Q0_2 = -2.6691978151546e-01; + Q0_3 = 1.4438714982130e-01; + Q0_4 = -7.7273673750760e-02; + Q0_5 = 2.5570078343005e-02; + Q0_6 = 4.2808774693299e-03; + Q0_7 = -8.2902108933389e-03; + Q0_8 = 3.2031176427908e-03; + Q0_9 = -4.4502749689556e-04; + Q0_10 = 0.0000000000000e+00; + Q0_11 = 0.0000000000000e+00; + Q0_12 = 0.0000000000000e+00; + Q0_13 = 0.0000000000000e+00; + Q0_14 = 0.0000000000000e+00; + Q1_0 = -6.7548747038002e-01; + Q1_1 = 0.0000000000000e+00; + Q1_2 = 9.5146052715180e-01; + Q1_3 = -4.2442349882626e-01; + Q1_4 = 2.1538865145190e-01; + Q1_5 = -7.1939778160350e-02; + Q1_6 = -8.2539187832840e-03; + Q1_7 = 1.9930661669090e-02; + Q1_8 = -7.7433256989613e-03; + Q1_9 = 1.0681515760869e-03; + Q1_10 = 0.0000000000000e+00; + Q1_11 = 0.0000000000000e+00; + Q1_12 = 0.0000000000000e+00; + Q1_13 = 0.0000000000000e+00; + Q1_14 = 0.0000000000000e+00; + Q2_0 = 2.6691978151546e-01; + Q2_1 = -9.5146052715180e-01; + Q2_2 = 0.0000000000000e+00; + Q2_3 = 9.6073770842387e-01; + Q2_4 = -3.9378595264609e-01; + Q2_5 = 1.3302097358959e-01; + Q2_6 = 8.1200458151489e-05; + Q2_7 = -2.3849770528789e-02; + Q2_8 = 9.6600442856829e-03; + Q2_9 = -1.3234579460680e-03; + Q2_10 = 0.0000000000000e+00; + Q2_11 = 0.0000000000000e+00; + Q2_12 = 0.0000000000000e+00; + Q2_13 = 0.0000000000000e+00; + Q2_14 = 0.0000000000000e+00; + Q3_0 = -1.4438714982130e-01; + Q3_1 = 4.2442349882626e-01; + Q3_2 = -9.6073770842387e-01; + Q3_3 = 0.0000000000000e+00; + Q3_4 = 9.1551097634196e-01; + Q3_5 = -2.8541713079648e-01; + Q3_6 = 4.1398809121293e-02; + Q3_7 = 1.7256059167927e-02; + Q3_8 = -9.4349194803610e-03; + Q3_9 = 1.3875650645663e-03; + Q3_10 = 0.0000000000000e+00; + Q3_11 = 0.0000000000000e+00; + Q3_12 = 0.0000000000000e+00; + Q3_13 = 0.0000000000000e+00; + Q3_14 = 0.0000000000000e+00; + Q4_0 = 7.7273673750760e-02; + Q4_1 = -2.1538865145190e-01; + Q4_2 = 3.9378595264609e-01; + Q4_3 = -9.1551097634196e-01; + Q4_4 = 0.0000000000000e+00; + Q4_5 = 8.3519401865051e-01; + Q4_6 = -2.0586492924974e-01; + Q4_7 = 3.1230261235901e-02; + Q4_8 = -2.0969453466651e-04; + Q4_9 = -5.0965470499782e-04; + Q4_10 = 0.0000000000000e+00; + Q4_11 = 0.0000000000000e+00; + Q4_12 = 0.0000000000000e+00; + Q4_13 = 0.0000000000000e+00; + Q4_14 = 0.0000000000000e+00; + Q5_0 = -2.5570078343005e-02; + Q5_1 = 7.1939778160350e-02; + Q5_2 = -1.3302097358959e-01; + Q5_3 = 2.8541713079648e-01; + Q5_4 = -8.3519401865051e-01; + Q5_5 = 0.0000000000000e+00; + Q5_6 = 8.1046389580138e-01; + Q5_7 = -2.1879194972141e-01; + Q5_8 = 5.2977237804899e-02; + Q5_9 = -9.0146730522360e-03; + Q5_10 = 7.9365079365079e-04; + Q5_11 = 0.0000000000000e+00; + Q5_12 = 0.0000000000000e+00; + Q5_13 = 0.0000000000000e+00; + Q5_14 = 0.0000000000000e+00; + Q6_0 = -4.2808774693299e-03; + Q6_1 = 8.2539187832840e-03; + Q6_2 = -8.1200458151489e-05; + Q6_3 = -4.1398809121293e-02; + Q6_4 = 2.0586492924974e-01; + Q6_5 = -8.1046389580138e-01; + Q6_6 = 0.0000000000000e+00; + Q6_7 = 8.2787884456005e-01; + Q6_8 = -2.3582460382545e-01; + Q6_9 = 5.9178678209520e-02; + Q6_10 = -9.9206349206349e-03; + Q6_11 = 7.9365079365079e-04; + Q6_12 = 0.0000000000000e+00; + Q6_13 = 0.0000000000000e+00; + Q6_14 = 0.0000000000000e+00; + Q7_0 = 8.2902108933389e-03; + Q7_1 = -1.9930661669090e-02; + Q7_2 = 2.3849770528789e-02; + Q7_3 = -1.7256059167927e-02; + Q7_4 = -3.1230261235901e-02; + Q7_5 = 2.1879194972141e-01; + Q7_6 = -8.2787884456005e-01; + Q7_7 = 0.0000000000000e+00; + Q7_8 = 8.3301028859275e-01; + Q7_9 = -2.3804321850015e-01; + Q7_10 = 5.9523809523809e-02; + Q7_11 = -9.9206349206349e-03; + Q7_12 = 7.9365079365079e-04; + Q7_13 = 0.0000000000000e+00; + Q7_14 = 0.0000000000000e+00; + Q8_0 = -3.2031176427908e-03; + Q8_1 = 7.7433256989613e-03; + Q8_2 = -9.6600442856829e-03; + Q8_3 = 9.4349194803610e-03; + Q8_4 = 2.0969453466651e-04; + Q8_5 = -5.2977237804899e-02; + Q8_6 = 2.3582460382545e-01; + Q8_7 = -8.3301028859275e-01; + Q8_8 = 0.0000000000000e+00; + Q8_9 = 8.3333655748509e-01; + Q8_10 = -2.3809523809524e-01; + Q8_11 = 5.9523809523809e-02; + Q8_12 = -9.9206349206349e-03; + Q8_13 = 7.9365079365079e-04; + Q8_14 = 0.0000000000000e+00; + Q9_0 = 4.4502749689556e-04; + Q9_1 = -1.0681515760869e-03; + Q9_2 = 1.3234579460680e-03; + Q9_3 = -1.3875650645663e-03; + Q9_4 = 5.0965470499782e-04; + Q9_5 = 9.0146730522360e-03; + Q9_6 = -5.9178678209520e-02; + Q9_7 = 2.3804321850015e-01; + Q9_8 = -8.3333655748509e-01; + Q9_9 = 0.0000000000000e+00; + Q9_10 = 8.3333333333333e-01; + Q9_11 = -2.3809523809524e-01; + Q9_12 = 5.9523809523809e-02; + Q9_13 = -9.9206349206349e-03; + Q9_14 = 7.9365079365079e-04; + + for i = 1:BP + + for j = 1:BP + Q(i, j) = eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + Q(N + 1 - i, N + 1 - j) = -eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + end + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%% Undivided difference operators %%%% + % Closed with zeros at the first boundary nodes. + m = N; + + DD_5 = (-diag(ones(m - 3, 1), -3) + 5 * diag(ones(m - 2, 1), -2) - 10 * diag(ones(m - 1, 1), -1) + 10 * diag(ones(m, 1), 0) - 5 * diag(ones(m - 1, 1), 1) + diag(ones(m - 2, 1), 2)); + DD_5(1:8, 1:10) = [0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; -0.88425676349344827581e1 0.18735837038089672208e2 -0.17076524806228533350e2 0.10664693462778093925e2 -0.43403898038449865885e1 0.85895174414023656383e0 0 0 0 0; 0 -0.13262411219221127021e1 0.45552739083119183335e1 -0.73424543813164879330e1 0.70876331528332015948e1 -0.38059884697709954324e1 0.83177691186447613913e0 0 0 0; 0 0 -0.67600766166626540709e0 0.32310531977344450754e1 -0.69639522132755183916e1 0.77488870404680024829e1 -0.42187263911386203939e1 0.87874602787795663432e0 0 0; 0 0 0 -0.66326118352702166971e0 0.38132489024062224761e1 -0.84909798376351149047e1 0.90434791287189283383e1 -0.46461964978830115989e1 0.94370948791999735890e0 0; 0 0 0 0 -0.86903681018048694197e0 0.47050202961852482685e1 -0.96960545214617434798e1 0.97952957162584740145e1 -0.49228410242754295559e1 0.98761634347393769455e0; ]; + DD_5(m - 6:m, m - 9:m) = [-0.98761634347393769455e0 0.49228410242754295559e1 -0.97952957162584740145e1 0.96960545214617434798e1 -0.47050202961852482685e1 0.86903681018048694197e0 0 0 0 0; 0 -0.94370948791999735890e0 0.46461964978830115989e1 -0.90434791287189283383e1 0.84909798376351149047e1 -0.38132489024062224761e1 0.66326118352702166971e0 0 0 0; 0 0 -0.87874602787795663432e0 0.42187263911386203939e1 -0.77488870404680024829e1 0.69639522132755183916e1 -0.32310531977344450754e1 0.67600766166626540709e0 0 0; 0 0 0 -0.83177691186447613913e0 0.38059884697709954324e1 -0.70876331528332015948e1 0.73424543813164879330e1 -0.45552739083119183335e1 0.13262411219221127021e1 0; 0 0 0 0 -0.85895174414023656383e0 0.43403898038449865885e1 -0.10664693462778093925e2 0.17076524806228533350e2 -0.18735837038089672208e2 0.88425676349344827581e1; 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; ]; + DD_5 = sparse(DD_5); + + DD_6 = (diag(ones(m - 3, 1), 3) - 6 * diag(ones(m - 2, 1), 2) + 15 * diag(ones(m - 1, 1), 1) - 20 * diag(ones(m, 1), 0) + 15 * diag(ones(m - 1, 1), -1) - 6 * diag(ones(m - 2, 1), -2) + diag(ones(m - 3, 1), -3)); + DD_6(1:8, 1:11) = [0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; 0.97690498198305661286e1 -0.22164087301995739032e2 0.23898275711233304083e2 -0.19893851160044639280e2 0.12625396854743289626e2 -0.51537104648414193830e1 0.91892654107463785790e0 0 0 0 0; 0 0.13105269062480722931e1 -0.51692977530964314903e1 0.10448225399376470222e2 -0.13885092532071720368e2 0.11417965409312986297e2 -0.49906614711868568348e1 0.86833404141747988109e0 0 0 0; 0 0 0.64511698871199831925e0 -0.37163607887886698482e1 0.10284728893981919286e2 -0.15497774080936004966e2 0.12656179173415861182e2 -0.52724761672677398059e1 0.90058598088263583338e0 0 0; 0 0 0 0.64016413450696574250e0 -0.45192323253005276829e1 0.12736469756452672357e2 -0.18086958257437856677e2 0.13938589493649034797e2 -0.56622569275199841534e1 0.95322412564969561677e0 0; 0 0 0 0 0.86005005088560527649e0 -0.56460243554222979222e1 0.14544081782192615220e2 -0.19590591432516948029e2 0.14768523072826288668e2 -0.59256980608436261673e1 0.98965894287836295484e0; ]; + DD_6(m - 7:m, m - 10:m) = [0.98965894287836295484e0 -0.59256980608436261673e1 0.14768523072826288668e2 -0.19590591432516948029e2 0.14544081782192615220e2 -0.56460243554222979222e1 0.86005005088560527649e0 0 0 0 0; 0 0.95322412564969561677e0 -0.56622569275199841534e1 0.13938589493649034797e2 -0.18086958257437856677e2 0.12736469756452672357e2 -0.45192323253005276829e1 0.64016413450696574250e0 0 0 0; 0 0 0.90058598088263583338e0 -0.52724761672677398059e1 0.12656179173415861182e2 -0.15497774080936004966e2 0.10284728893981919286e2 -0.37163607887886698482e1 0.64511698871199831925e0 0 0; 0 0 0 0.86833404141747988109e0 -0.49906614711868568348e1 0.11417965409312986297e2 -0.13885092532071720368e2 0.10448225399376470222e2 -0.51692977530964314903e1 0.13105269062480722931e1 0; 0 0 0 0 0.91892654107463785790e0 -0.51537104648414193830e1 0.12625396854743289626e2 -0.19893851160044639280e2 0.23898275711233304083e2 -0.22164087301995739032e2 0.97690498198305661286e1; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_6 = sparse(DD_6); + + DD_7 = (-diag(ones(m - 4, 1), -4) + 7 * diag(ones(m - 3, 1), -3) - 21 * diag(ones(m - 2, 1), -2) + 35 * diag(ones(m - 1, 1), -1) - 35 * diag(ones(m, 1), 0) + 21 * diag(ones(m - 1, 1), 1) - 7 * diag(ones(m - 2, 1), 2) + diag(ones(m - 3, 1), 3)); + DD_7(1:9, 1:12) = [0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; -0.10633444157744515342e2 0.25551717302255079868e2 -0.31639558087487298930e2 0.33026832975062979647e2 -0.28856215669710369771e2 0.18037986626944967840e2 -0.64324857875224650053e1 0.94516679820162169311e0 0 0 0 0; 0 -0.12971946051930944772e1 0.57552633215463132945e1 -0.14020486493241325087e2 0.23923936099960072962e2 -0.26641919288396968027e2 0.17467315149153998922e2 -0.60783382899223591677e1 0.89142410609336157976e0 0 0 0; 0 0 -0.61968315701047317846e0 0.41847682905586435755e1 -0.14220312881453249947e2 0.27121104641638008690e2 -0.29531084737970342758e2 0.18453666585437089321e2 -0.63041018661784508337e1 0.91564312497877513070e0 0 0; 0 0 0 -0.62096054671195295664e0 0.52179151332917540372e1 -0.17831057659033741300e2 0.31652176950516249184e2 -0.32523375485181081192e2 0.19817899246319944537e2 -0.66725688795478693174e1 0.95997124034669700791e0 0; 0 0 0 0 -0.85241549236735026150e0 0.65870284146593475759e1 -0.20361714495069661308e2 0.34283535006904659051e2 -0.34459887169928006891e2 0.20739943212952691585e2 -0.69276126001485406839e1 0.99112312299686093167e0; ]; + DD_7(m - 7:m, m - 11:m) = [-0.99112312299686093167e0 0.69276126001485406839e1 -0.20739943212952691585e2 0.34459887169928006891e2 -0.34283535006904659051e2 0.20361714495069661308e2 -0.65870284146593475759e1 0.85241549236735026150e0 0 0 0 0; 0 -0.95997124034669700791e0 0.66725688795478693174e1 -0.19817899246319944537e2 0.32523375485181081192e2 -0.31652176950516249184e2 0.17831057659033741300e2 -0.52179151332917540372e1 0.62096054671195295664e0 0 0 0; 0 0 -0.91564312497877513070e0 0.63041018661784508337e1 -0.18453666585437089321e2 0.29531084737970342758e2 -0.27121104641638008690e2 0.14220312881453249947e2 -0.41847682905586435755e1 0.61968315701047317846e0 0 0; 0 0 0 -0.89142410609336157976e0 0.60783382899223591677e1 -0.17467315149153998922e2 0.26641919288396968027e2 -0.23923936099960072962e2 0.14020486493241325087e2 -0.57552633215463132945e1 0.12971946051930944772e1 0; 0 0 0 0 -0.94516679820162169311e0 0.64324857875224650053e1 -0.18037986626944967840e2 0.28856215669710369771e2 -0.33026832975062979647e2 0.31639558087487298930e2 -0.25551717302255079868e2 0.10633444157744515342e2; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_7 = sparse(DD_7); + + DD_8 = (diag(ones(m - 4, 1), 4) - 8 * diag(ones(m - 3, 1), 3) + 28 * diag(ones(m - 2, 1), 2) - 56 * diag(ones(m - 1, 1), 1) + 70 * diag(ones(m, 1), 0) - 56 * diag(ones(m - 1, 1), -1) + 28 * diag(ones(m - 2, 1), -2) - 8 * diag(ones(m - 3, 1), -3) + diag(ones(m - 4, 1), -4)); + DD_8(1:9, 1:13) = [0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0.11447706798618566234e2 -0.28904884139025747734e2 0.40258353260409964223e2 -0.50649997399180126990e2 0.56821824921675878869e2 -0.48101297671853247575e2 0.25729943150089860021e2 -0.75613343856129735449e1 0.95968546487782649665e0 0 0 0 0; 0 0.12856328177474934636e1 -0.63181271116961104382e1 0.18042992864608611563e2 -0.37804272468074727719e2 0.53283838576793936053e2 -0.46579507064410663791e2 0.24313353159689436671e2 -0.71313928487468926381e1 0.90748207408891683663e0 0 0 0; 0 0 0.59820007352804876260e0 -0.46391245450012267365e1 0.18764346418211454409e2 -0.43393767426620813904e2 0.59062169475940685515e2 -0.49209777561165571522e2 0.25216407464713803335e2 -0.73251449998302010456e1 0.92669110022382118702e0 0 0; 0 0 0 0.60460011916248255841e0 -0.59103958199322344450e1 0.23774743545378321733e2 -0.50643483120825998695e2 0.65046750970362162385e2 -0.52847731323519852099e2 0.26690275518191477270e2 -0.76797699227735760633e1 0.96501003395721735560e0 0; 0 0 0 0 0.84578719850252712660e0 -0.75280324738963972296e1 0.27148952660092881743e2 -0.54853656011047454481e2 0.68919774339856013782e2 -0.55306515234540510895e2 0.27710450400594162736e2 -0.79289849839748874534e1 0.99222410441366467138e0; ]; + DD_8(m - 8:m, m - 12:m) = [0.99222410441366467138e0 -0.79289849839748874534e1 0.27710450400594162736e2 -0.55306515234540510895e2 0.68919774339856013782e2 -0.54853656011047454481e2 0.27148952660092881743e2 -0.75280324738963972296e1 0.84578719850252712660e0 0 0 0 0; 0 0.96501003395721735560e0 -0.76797699227735760633e1 0.26690275518191477270e2 -0.52847731323519852099e2 0.65046750970362162385e2 -0.50643483120825998695e2 0.23774743545378321733e2 -0.59103958199322344450e1 0.60460011916248255841e0 0 0 0; 0 0 0.92669110022382118702e0 -0.73251449998302010456e1 0.25216407464713803335e2 -0.49209777561165571522e2 0.59062169475940685515e2 -0.43393767426620813904e2 0.18764346418211454409e2 -0.46391245450012267365e1 0.59820007352804876260e0 0 0; 0 0 0 0.90748207408891683663e0 -0.71313928487468926381e1 0.24313353159689436671e2 -0.46579507064410663791e2 0.53283838576793936053e2 -0.37804272468074727719e2 0.18042992864608611563e2 -0.63181271116961104382e1 0.12856328177474934636e1 0; 0 0 0 0 0.95968546487782649665e0 -0.75613343856129735449e1 0.25729943150089860021e2 -0.48101297671853247575e2 0.56821824921675878869e2 -0.50649997399180126990e2 0.40258353260409964223e2 -0.28904884139025747734e2 0.11447706798618566234e2; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_8 = sparse(DD_8); + + DD_9 = (-diag(ones(m - 5, 1), -5) + 9 * diag(ones(m - 4, 1), -4) - 36 * diag(ones(m - 3, 1), -3) + 84 * diag(ones(m - 2, 1), -2) - 126 * diag(ones(m - 1, 1), -1) + 126 * diag(ones(m, 1), 0) - 84 * diag(ones(m - 1, 1), 1) + 36 * diag(ones(m - 2, 1), 2) - 9 * diag(ones(m - 3, 1), 3) + diag(ones(m - 4, 1), 4)); + DD_9(1:10, 1:14) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; -0.12220346479758703402e2 0.32228164479135716142e2 -0.49720065159556828467e2 0.73329283892516285142e2 -0.10101269332559123572e3 0.10822791976166980704e3 -0.77189829450269580063e2 0.34026004735258380952e2 -0.86371691839004384699e1 0.96873073049659684460e0 0 0 0 0; 0 -0.12754371756934054072e1 0.68614776237194576426e1 -0.22502238094968228382e2 0.56120004490560654424e2 -0.95910909438229084895e2 0.10480389089492399353e3 -0.72940059479068310012e2 0.32091267819361016871e2 -0.81673386668002515297e1 0.91934202619415775756e0 0 0 0; 0 0 -0.57969473693003825890e0 0.50815098898235167347e1 -0.23911428372444897689e2 0.65090651139931220857e2 -0.10631190505669323393e3 0.11072199951262253592e3 -0.75649222394141410004e2 0.32963152499235904705e2 -0.83402199020143906832e1 0.93515742061079234147e0 0 0; 0 0 0 -0.59039909771982400264e0 0.65974918490578446834e1 -0.30567527415486413657e2 0.75965224681238998042e2 -0.11708415174665189229e3 0.11890739547791966722e3 -0.80070826554574431809e2 0.34558964652481092285e2 -0.86850903056149562004e1 0.96891845934991572940e0 0; 0 0 0 0 -0.83993614063969059233e0 0.84690365331334468834e1 -0.34905796277262276527e2 0.82280484016571181722e2 -0.12405559381174082481e3 0.12443965927771614951e3 -0.83131351201782488207e2 0.35680432427886993540e2 -0.89300169397229820424e1 0.99308211584049051802e0; ]; + DD_9(m - 8:m, m - 13:m) = [-0.99308211584049051802e0 0.89300169397229820424e1 -0.35680432427886993540e2 0.83131351201782488207e2 -0.12443965927771614951e3 0.12405559381174082481e3 -0.82280484016571181722e2 0.34905796277262276527e2 -0.84690365331334468834e1 0.83993614063969059233e0 0 0 0 0; 0 -0.96891845934991572940e0 0.86850903056149562004e1 -0.34558964652481092285e2 0.80070826554574431809e2 -0.11890739547791966722e3 0.11708415174665189229e3 -0.75965224681238998042e2 0.30567527415486413657e2 -0.65974918490578446834e1 0.59039909771982400264e0 0 0 0; 0 0 -0.93515742061079234147e0 0.83402199020143906832e1 -0.32963152499235904705e2 0.75649222394141410004e2 -0.11072199951262253592e3 0.10631190505669323393e3 -0.65090651139931220857e2 0.23911428372444897689e2 -0.50815098898235167347e1 0.57969473693003825890e0 0 0; 0 0 0 -0.91934202619415775756e0 0.81673386668002515297e1 -0.32091267819361016871e2 0.72940059479068310012e2 -0.10480389089492399353e3 0.95910909438229084895e2 -0.56120004490560654424e2 0.22502238094968228382e2 -0.68614776237194576426e1 0.12754371756934054072e1 0; 0 0 0 0 -0.96873073049659684460e0 0.86371691839004384699e1 -0.34026004735258380952e2 0.77189829450269580063e2 -0.10822791976166980704e3 0.10101269332559123572e3 -0.73329283892516285142e2 0.49720065159556828467e2 -0.32228164479135716142e2 0.12220346479758703402e2; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_9 = sparse(DD_9); + + DD_10 = (diag(ones(m - 5, 1), 5) - 10 * diag(ones(m - 4, 1), 4) + 45 * diag(ones(m - 3, 1), 3) - 120 * diag(ones(m - 2, 1), 2) + 210 * diag(ones(m - 1, 1), 1) - 252 * diag(ones(m, 1), 0) + 210 * diag(ones(m - 1, 1), -1) - 120 * diag(ones(m - 2, 1), -2) + 45 * diag(ones(m - 3, 1), -3) - 10 * diag(ones(m - 4, 1), -4) + diag(ones(m - 5, 1), -5)); + DD_10(1:10, 1:15) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0.12957678688124699986e2 -0.35525089722887367966e2 0.59995471673283665865e2 -0.10161365491269611714e3 0.16661352548983481943e3 -0.21645583952333961409e3 0.19297457362567395016e3 -0.11342001578419460317e3 0.43185845919502192349e2 -0.96873073049659684460e1 0.97481185166434302666e0 0 0 0 0; 0 0.12663266431786644877e1 -0.73880195719183439765e1 0.27386715439651102593e2 -0.79459763018974764721e2 0.15985151573038180816e3 -0.20960778178984798706e3 0.18235014869767077503e3 -0.10697089273120338957e3 0.40836693334001257648e2 -0.91934202619415775756e1 0.92847752900245498778e0 0 0 0; 0 0 0.56350506801536116666e0 -0.55135043604652958562e1 0.29656869502625787574e2 -0.92986644485616029795e2 0.17718650842782205655e3 -0.22144399902524507185e3 0.18912305598535352501e3 -0.10987717499745301568e3 0.41701099510071953416e2 -0.93515742061079234147e1 0.94185858099865288757e0 0 0; 0 0 0 0.57788899624281661128e0 -0.72798346274475049971e1 0.38209409269358017071e2 -0.10852174954462714006e3 0.19514025291108648715e3 -0.23781479095583933444e3 0.20017706638643607952e3 -0.11519654884160364095e3 0.43425451528074781002e2 -0.96891845934991572940e1 0.97203947181859638306e0 0; 0 0 0 0 0.83470299758184640199e0 -0.94100405923704965371e1 0.43632245346577845659e2 -0.11754354859510168817e3 0.20675932301956804135e3 -0.24887931855543229903e3 0.20782837800445622052e3 -0.11893477475962331180e3 0.44650084698614910212e2 -0.99308211584049051802e1 0.99376959413383658153e0; ]; + DD_10(m - 9:m, m - 14:m) = [0.99376959413383658153e0 -0.99308211584049051802e1 0.44650084698614910212e2 -0.11893477475962331180e3 0.20782837800445622052e3 -0.24887931855543229903e3 0.20675932301956804135e3 -0.11754354859510168817e3 0.43632245346577845659e2 -0.94100405923704965371e1 0.83470299758184640199e0 0 0 0 0; 0 0.97203947181859638306e0 -0.96891845934991572940e1 0.43425451528074781002e2 -0.11519654884160364095e3 0.20017706638643607952e3 -0.23781479095583933444e3 0.19514025291108648715e3 -0.10852174954462714006e3 0.38209409269358017071e2 -0.72798346274475049971e1 0.57788899624281661128e0 0 0 0; 0 0 0.94185858099865288757e0 -0.93515742061079234147e1 0.41701099510071953416e2 -0.10987717499745301568e3 0.18912305598535352501e3 -0.22144399902524507185e3 0.17718650842782205655e3 -0.92986644485616029795e2 0.29656869502625787574e2 -0.55135043604652958562e1 0.56350506801536116666e0 0 0; 0 0 0 0.92847752900245498778e0 -0.91934202619415775756e1 0.40836693334001257648e2 -0.10697089273120338957e3 0.18235014869767077503e3 -0.20960778178984798706e3 0.15985151573038180816e3 -0.79459763018974764721e2 0.27386715439651102593e2 -0.73880195719183439765e1 0.12663266431786644877e1 0; 0 0 0 0 0.97481185166434302666e0 -0.96873073049659684460e1 0.43185845919502192349e2 -0.11342001578419460317e3 0.19297457362567395016e3 -0.21645583952333961409e3 0.16661352548983481943e3 -0.10161365491269611714e3 0.59995471673283665865e2 -0.35525089722887367966e2 0.12957678688124699986e2; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_10 = sparse(DD_10); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Difference operator %% + D1 = H \ Q; + + % Helper functions for constructing D2(c) + % TODO: Consider changing sparse(diag(...)) to spdiags(....) + + % Minimal 11 point stencil width + function D2 = D2_fun_minimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 2/7 * diag(ones(m - 1, 1), -1) + 2/7 * diag(ones(m - 1, 1), 1) + 3/7 * diag(ones(m, 1), 0); C3(1, 3) = 2/7; C3(m, m - 2) = 2/7; + C4 = 1/5 * diag(ones(m - 2, 1), -2) + 3/10 * diag(ones(m - 1, 1), -1) + 1/5 * diag(ones(m - 1, 1), 1) + 3/10 * diag(ones(m, 1), 0); C4(2, 4) = 1/5; C4(1, 3) = 1/5; C4(1, 4) = 3/10; C4(m, m - 2) = 1/5; C4(m, m - 3) = 1/5; + C5 = 1/5 * diag(ones(m - 2, 1), -2) + 1/5 * diag(ones(m - 2, 1), 2) + 1/5 * diag(ones(m - 1, 1), -1) + 1/5 * diag(ones(m - 1, 1), 1) + 1/5 * diag(ones(m, 1), 0); C5(2, 4) = 1/5; C5(1, 4) = 1/5; C5(1, 5) = 1/5; C5(2, 5) = 1/5; C5(m - 1, m - 4) = 1/5; C5(m, m - 4) = 1/5; C5(m, m - 3) = 1/5; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + C4 = sparse(diag(C4 * c)); + C5 = sparse(diag(C5 * c)); + + % Remainder term added to wide second derivative operator + R = (1/1587600 / h) * transpose(DD_10) * C1 * DD_10 + (1/317520 / h) * transpose(DD_9) * C2 * DD_9 + (1/60480 / h) * transpose(DD_8) * C3 * DD_8 + (1/10584 / h) * transpose(DD_7) * C4 * DD_7 + (1/1512 / h) * transpose(DD_6) * C5 * DD_6; + D2 = D1 * C1 * D1 - H \ R; + end + + % Few additional grid point in interior stencil cmp. to minimal + function D2 = D2_fun_nonminimal(c) + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 2/7 * diag(ones(m - 1, 1), -1) + 2/7 * diag(ones(m - 1, 1), 1) + 3/7 * diag(ones(m, 1), 0); C3(1, 3) = 2/7; C3(m, m - 2) = 2/7; + C4 = 1/5 * diag(ones(m - 2, 1), -2) + 3/10 * diag(ones(m - 1, 1), -1) + 1/5 * diag(ones(m - 1, 1), 1) + 3/10 * diag(ones(m, 1), 0); C4(2, 4) = 1/5; C4(1, 3) = 1/5; C4(1, 4) = 3/10; C4(m, m - 2) = 1/5; C4(m, m - 3) = 1/5; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + C4 = sparse(diag(C4 * c)); + + % Remainder term added to wide second derivative operator + R = (1/1587600 / h) * transpose(DD_10) * C1 * DD_10 + (1/317520 / h) * transpose(DD_9) * C2 * DD_9 + (1/60480 / h) * transpose(DD_8) * C3 * DD_8 + (1/10584 / h) * transpose(DD_7) * C4 * DD_7; + D2 = D1 * C1 * D1 - H \ R; + end + + % Wide stencil + function D2 = D2_fun_wide(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + D2 = D1 * C1 * D1; + end + + switch options.stencil_width + case 'minimal' + D2 = @D2_fun_minimal; + case 'nonminimal' + D2 = @D2_fun_nonminimal; + case 'wide' + D2 = @D2_fun_wide; + otherwise + error('No option %s for stencil width', options.stencil_width) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Artificial dissipation operator %%% + switch options.AD + case 'upwind' + % This is the choice that yield 9th order Upwind + DI = H \ (transpose(DD_5) * DD_5) * (-1/1260); + case 'op' + % This choice will preserve the order of the underlying + % Non-dissipative D1 SBP operator + DI = H \ (transpose(DD_6) * DD_6) * (-1 / (5 * 1260)); + % Notice that you can use any negative number instead of (-1/(5*1260)) + otherwise + error("Artificial dissipation options '%s' not implemented.", option.AD) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+implementations/d2_noneq_variable_12.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,404 @@ +function [H, HI, D1, D2, DI] = d2_noneq_variable_12(N, h, options) + % N: Number of grid points + % h: grid spacing + % options: struct containing options for constructing the operator + % current options are: + % options.stencil_type ('minimal','nonminimal','wide') + % options.AD ('upwind', 'op') + + % BP: Number of boundary points + % order: Accuracy of interior stencil + BP = 12; + order = 12; + if(N<2*BP) + error(['Operator requires at least ' num2str(2*BP) ' grid points']); + end + + %%%% Norm matrix %%%%%%%% + P = zeros(BP, 1); + P0 = 1.0000000000011e-01; + P1 = 5.9616216757547e-01; + P2 = 9.9065699844442e-01; + P3 = 1.2512548713913e+00; + P4 = 1.3316678989403e+00; + P5 = 1.2093375037721e+00; + P6 = 1.0236491595704e+00; + P7 = 9.9685258909811e-01; + P8 = 1.0004766563923e+00; + P9 = 9.9993617879146e-01; + P10 = 1.0000063122914e+00; + P11 = 9.9999966373260e-01; + + for i = 0:BP - 1 + P(i + 1) = eval(['P' num2str(i)]); + end + + Hv = ones(N, 1); + Hv(1:BP) = P; + Hv(end - BP + 1:end) = flip(P); + Hv = h * Hv; + H = spdiags(Hv, 0, N, N); + HI = spdiags(1 ./ Hv, 0, N, N); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Q matrix %%%%%%%%%%% + + % interior stencil + d = [1/5544, -1/385, 1/56, -5/63, 15/56, -6/7, 0, 6/7, -15/56, 5/63, -1/56, 1/385, -1/5544]; + d = repmat(d, N, 1); + Q = spdiags(d, -order / 2:order / 2, N, N); + + % Boundaries + Q0_0 = -5.0000000000000e-01; + Q0_1 = 6.7597560728423e-01; + Q0_2 = -2.6859785384416e-01; + Q0_3 = 1.4850302678903e-01; + Q0_4 = -8.7976689586154e-02; + Q0_5 = 4.1833336322613e-02; + Q0_6 = -2.2216684976993e-03; + Q0_7 = -1.5910034062022e-02; + Q0_8 = 1.1296706376589e-02; + Q0_9 = -3.1823678285130e-03; + Q0_10 = 2.4843594063649e-04; + Q0_11 = 3.1501105449828e-05; + Q0_12 = 0.0000000000000e+00; + Q0_13 = 0.0000000000000e+00; + Q0_14 = 0.0000000000000e+00; + Q0_15 = 0.0000000000000e+00; + Q0_16 = 0.0000000000000e+00; + Q0_17 = 0.0000000000000e+00; + Q1_0 = -6.7597560728423e-01; + Q1_1 = 0.0000000000000e+00; + Q1_2 = 9.5424013647146e-01; + Q1_3 = -4.3389334603464e-01; + Q1_4 = 2.4285669347653e-01; + Q1_5 = -1.1443465137214e-01; + Q1_6 = 8.5942765682435e-03; + Q1_7 = 4.0290424215772e-02; + Q1_8 = -2.9396383714543e-02; + Q1_9 = 8.5601827834256e-03; + Q1_10 = -7.8128092862319e-04; + Q1_11 = -6.0444181254875e-05; + Q1_12 = 0.0000000000000e+00; + Q1_13 = 0.0000000000000e+00; + Q1_14 = 0.0000000000000e+00; + Q1_15 = 0.0000000000000e+00; + Q1_16 = 0.0000000000000e+00; + Q1_17 = 0.0000000000000e+00; + Q2_0 = 2.6859785384416e-01; + Q2_1 = -9.5424013647146e-01; + Q2_2 = 0.0000000000000e+00; + Q2_3 = 9.7065114311923e-01; + Q2_4 = -4.3205328628292e-01; + Q2_5 = 1.9549970932735e-01; + Q2_6 = -2.4406885385172e-02; + Q2_7 = -5.5737279079895e-02; + Q2_8 = 4.3772338637753e-02; + Q2_9 = -1.3727655130726e-02; + Q2_10 = 1.6271304373071e-03; + Q2_11 = 1.7066984372933e-05; + Q2_12 = 0.0000000000000e+00; + Q2_13 = 0.0000000000000e+00; + Q2_14 = 0.0000000000000e+00; + Q2_15 = 0.0000000000000e+00; + Q2_16 = 0.0000000000000e+00; + Q2_17 = 0.0000000000000e+00; + Q3_0 = -1.4850302678903e-01; + Q3_1 = 4.3389334603464e-01; + Q3_2 = -9.7065114311923e-01; + Q3_3 = 0.0000000000000e+00; + Q3_4 = 9.5375878629204e-01; + Q3_5 = -3.6113954384951e-01; + Q3_6 = 6.9749289223875e-02; + Q3_7 = 6.5161366516465e-02; + Q3_8 = -6.0325702283960e-02; + Q3_9 = 2.1188913621662e-02; + Q3_10 = -3.2632650250470e-03; + Q3_11 = 1.3097937809499e-04; + Q3_12 = 0.0000000000000e+00; + Q3_13 = 0.0000000000000e+00; + Q3_14 = 0.0000000000000e+00; + Q3_15 = 0.0000000000000e+00; + Q3_16 = 0.0000000000000e+00; + Q3_17 = 0.0000000000000e+00; + Q4_0 = 8.7976689586154e-02; + Q4_1 = -2.4285669347653e-01; + Q4_2 = 4.3205328628292e-01; + Q4_3 = -9.5375878629204e-01; + Q4_4 = 0.0000000000000e+00; + Q4_5 = 8.8676146394834e-01; + Q4_6 = -2.1292503103800e-01; + Q4_7 = -4.6037018833218e-02; + Q4_8 = 7.4338719466734e-02; + Q4_9 = -3.1217656663809e-02; + Q4_10 = 6.1239492854797e-03; + Q4_11 = -4.5892226603067e-04; + Q4_12 = 0.0000000000000e+00; + Q4_13 = 0.0000000000000e+00; + Q4_14 = 0.0000000000000e+00; + Q4_15 = 0.0000000000000e+00; + Q4_16 = 0.0000000000000e+00; + Q4_17 = 0.0000000000000e+00; + Q5_0 = -4.1833336322613e-02; + Q5_1 = 1.1443465137214e-01; + Q5_2 = -1.9549970932735e-01; + Q5_3 = 3.6113954384951e-01; + Q5_4 = -8.8676146394834e-01; + Q5_5 = 0.0000000000000e+00; + Q5_6 = 7.7461223007026e-01; + Q5_7 = -1.0609547334165e-01; + Q5_8 = -4.4853791547749e-02; + Q5_9 = 3.2436468405486e-02; + Q5_10 = -8.4387621360184e-03; + Q5_11 = 8.5964292632428e-04; + Q5_12 = 0.0000000000000e+00; + Q5_13 = 0.0000000000000e+00; + Q5_14 = 0.0000000000000e+00; + Q5_15 = 0.0000000000000e+00; + Q5_16 = 0.0000000000000e+00; + Q5_17 = 0.0000000000000e+00; + Q6_0 = 2.2216684976993e-03; + Q6_1 = -8.5942765682435e-03; + Q6_2 = 2.4406885385172e-02; + Q6_3 = -6.9749289223875e-02; + Q6_4 = 2.1292503103800e-01; + Q6_5 = -7.7461223007026e-01; + Q6_6 = 0.0000000000000e+00; + Q6_7 = 7.4758103262966e-01; + Q6_8 = -1.5730779067906e-01; + Q6_9 = 2.6517620342970e-02; + Q6_10 = -4.3175367549700e-03; + Q6_11 = 1.1092605832824e-03; + Q6_12 = -1.8037518037522e-04; + Q6_13 = 0.0000000000000e+00; + Q6_14 = 0.0000000000000e+00; + Q6_15 = 0.0000000000000e+00; + Q6_16 = 0.0000000000000e+00; + Q6_17 = 0.0000000000000e+00; + Q7_0 = 1.5910034062022e-02; + Q7_1 = -4.0290424215772e-02; + Q7_2 = 5.5737279079895e-02; + Q7_3 = -6.5161366516465e-02; + Q7_4 = 4.6037018833218e-02; + Q7_5 = 1.0609547334165e-01; + Q7_6 = -7.4758103262966e-01; + Q7_7 = 0.0000000000000e+00; + Q7_8 = 8.0975719267918e-01; + Q7_9 = -2.3568822398349e-01; + Q7_10 = 6.9373143801571e-02; + Q7_11 = -1.6606121869177e-02; + Q7_12 = 2.5974025974031e-03; + Q7_13 = -1.8037518037522e-04; + Q7_14 = 0.0000000000000e+00; + Q7_15 = 0.0000000000000e+00; + Q7_16 = 0.0000000000000e+00; + Q7_17 = 0.0000000000000e+00; + Q8_0 = -1.1296706376589e-02; + Q8_1 = 2.9396383714543e-02; + Q8_2 = -4.3772338637753e-02; + Q8_3 = 6.0325702283960e-02; + Q8_4 = -7.4338719466734e-02; + Q8_5 = 4.4853791547749e-02; + Q8_6 = 1.5730779067906e-01; + Q8_7 = -8.0975719267918e-01; + Q8_8 = 0.0000000000000e+00; + Q8_9 = 8.4765775072084e-01; + Q8_10 = -2.6369594097148e-01; + Q8_11 = 7.8759594625702e-02; + Q8_12 = -1.7857142857146e-02; + Q8_13 = 2.5974025974031e-03; + Q8_14 = -1.8037518037522e-04; + Q8_15 = 0.0000000000000e+00; + Q8_16 = 0.0000000000000e+00; + Q8_17 = 0.0000000000000e+00; + Q9_0 = 3.1823678285130e-03; + Q9_1 = -8.5601827834256e-03; + Q9_2 = 1.3727655130726e-02; + Q9_3 = -2.1188913621662e-02; + Q9_4 = 3.1217656663809e-02; + Q9_5 = -3.2436468405486e-02; + Q9_6 = -2.6517620342970e-02; + Q9_7 = 2.3568822398349e-01; + Q9_8 = -8.4765775072084e-01; + Q9_9 = 0.0000000000000e+00; + Q9_10 = 8.5631774953989e-01; + Q9_11 = -2.6769768119702e-01; + Q9_12 = 7.9365079365093e-02; + Q9_13 = -1.7857142857146e-02; + Q9_14 = 2.5974025974031e-03; + Q9_15 = -1.8037518037522e-04; + Q9_16 = 0.0000000000000e+00; + Q9_17 = 0.0000000000000e+00; + Q10_0 = -2.4843594063649e-04; + Q10_1 = 7.8128092862319e-04; + Q10_2 = -1.6271304373071e-03; + Q10_3 = 3.2632650250470e-03; + Q10_4 = -6.1239492854797e-03; + Q10_5 = 8.4387621360184e-03; + Q10_6 = 4.3175367549700e-03; + Q10_7 = -6.9373143801571e-02; + Q10_8 = 2.6369594097148e-01; + Q10_9 = -8.5631774953989e-01; + Q10_10 = 0.0000000000000e+00; + Q10_11 = 8.5712580212095e-01; + Q10_12 = -2.6785714285718e-01; + Q10_13 = 7.9365079365093e-02; + Q10_14 = -1.7857142857146e-02; + Q10_15 = 2.5974025974031e-03; + Q10_16 = -1.8037518037522e-04; + Q10_17 = 0.0000000000000e+00; + Q11_0 = -3.1501105449828e-05; + Q11_1 = 6.0444181254875e-05; + Q11_2 = -1.7066984372933e-05; + Q11_3 = -1.3097937809499e-04; + Q11_4 = 4.5892226603067e-04; + Q11_5 = -8.5964292632428e-04; + Q11_6 = -1.1092605832824e-03; + Q11_7 = 1.6606121869177e-02; + Q11_8 = -7.8759594625702e-02; + Q11_9 = 2.6769768119702e-01; + Q11_10 = -8.5712580212095e-01; + Q11_11 = 0.0000000000000e+00; + Q11_12 = 8.5714285714289e-01; + Q11_13 = -2.6785714285718e-01; + Q11_14 = 7.9365079365093e-02; + Q11_15 = -1.7857142857146e-02; + Q11_16 = 2.5974025974031e-03; + Q11_17 = -1.8037518037522e-04; + + for i = 1:BP + + for j = 1:BP + Q(i, j) = eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + Q(N + 1 - i, N + 1 - j) = -eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + end + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%% Undivided difference operators %%%% + % Closed with zeros at the first boundary nodes. + m = N; + + DD_6 = (diag(ones(m - 3, 1), 3) - 6 * diag(ones(m - 2, 1), 2) + 15 * diag(ones(m - 1, 1), 1) - 20 * diag(ones(m, 1), 0) + 15 * diag(ones(m - 1, 1), -1) - 6 * diag(ones(m - 2, 1), -2) + diag(ones(m - 3, 1), -3)); + DD_6(1:9, 1:12) = [0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0.70504538217624485042e1 -0.15481773512478815978e2 0.15439628908176388584e2 -0.11355022328644135767e2 0.62553652361133177256e1 -0.23565505827757565576e1 0.44789845784655348861e0 0 0 0 0 0; 0 0.84178325750049836493e0 -0.30776567832262484696e1 0.55480476621608890820e1 -0.66451562589578036671e1 0.54681670852508283306e1 -0.26873907470793164527e1 0.55220578435115281189e0 0 0 0 0; 0 0 0.36124410255434790612e0 -0.18841869963752696615e1 0.49068751071627186058e1 -0.79710602635488243814e1 0.75771246506939812399e1 -0.36661050678180486359e1 0.67610846733109492706e0 0 0 0; 0 0 0 0.31883568286286899671e0 -0.22216567686182446798e1 0.72341822309820977868e1 -0.12215760254444741754e2 0.10698736280837039597e2 -0.46222617037529123987e1 0.80792453213389245238e0 0 0; 0 0 0 0 0.45451605753051033631e0 -0.36739526096585069959e1 0.11306936594922967126e2 -0.16769946247690595362e2 0.13179014442979029716e2 -0.54150410306154005497e1 0.91847279253199572926e0 0; 0 0 0 0 0 0.77355004999207313207e0 -0.54143198515959566716e1 0.14230335022999000858e2 -0.19303948318184081752e2 0.14605034473743418451e2 -0.58729419174319386168e1 0.98229054047748459948e0; ]; + DD_6(m - 8:m, m - 11:m) = [0.98229054047748459948e0 -0.58729419174319386168e1 0.14605034473743418451e2 -0.19303948318184081752e2 0.14230335022999000858e2 -0.54143198515959566716e1 0.77355004999207313207e0 0 0 0 0 0; 0 0.91847279253199572926e0 -0.54150410306154005497e1 0.13179014442979029716e2 -0.16769946247690595362e2 0.11306936594922967126e2 -0.36739526096585069959e1 0.45451605753051033631e0 0 0 0 0; 0 0 0.80792453213389245238e0 -0.46222617037529123987e1 0.10698736280837039597e2 -0.12215760254444741754e2 0.72341822309820977868e1 -0.22216567686182446798e1 0.31883568286286899671e0 0 0 0; 0 0 0 0.67610846733109492706e0 -0.36661050678180486359e1 0.75771246506939812399e1 -0.79710602635488243814e1 0.49068751071627186058e1 -0.18841869963752696615e1 0.36124410255434790612e0 0 0; 0 0 0 0 0.55220578435115281189e0 -0.26873907470793164527e1 0.54681670852508283306e1 -0.66451562589578036671e1 0.55480476621608890820e1 -0.30776567832262484696e1 0.84178325750049836493e0 0; 0 0 0 0 0 0.44789845784655348861e0 -0.23565505827757565576e1 0.62553652361133177256e1 -0.11355022328644135767e2 0.15439628908176388584e2 -0.15481773512478815978e2 0.70504538217624485042e1; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_6 = sparse(DD_6); + + DD_7 = (-diag(ones(m - 4, 1), -4) + 7 * diag(ones(m - 3, 1), -3) - 21 * diag(ones(m - 2, 1), -2) + 35 * diag(ones(m - 1, 1), -1) - 35 * diag(ones(m, 1), 0) + 21 * diag(ones(m - 1, 1), 1) - 7 * diag(ones(m - 2, 1), 2) + diag(ones(m - 3, 1), 3)); + DD_7(1:10, 1:13) = [0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; -0.70504538217624585762e1 0.16323556769979337662e2 -0.18517285691402663507e2 0.16903069990805048996e2 -0.12900521495071139822e2 0.78247176680265960663e1 -0.31352892049258744203e1 0.55220578435115360075e0 0 0 0 0 0; 0 -0.77136636008199086135e0 0.31512297676528003033e1 -0.68105129732006589582e1 0.10585680229488408490e2 -0.12315008394369015993e2 0.94058676147776075845e1 -0.38654404904580696832e1 0.61955060619091911792e0 0 0 0 0; 0 0 -0.32268062071305431283e0 0.19678458985349116625e1 -0.63675477999083230026e1 0.13582054493165302513e2 -0.17679957518285956226e2 0.12831367737363170226e2 -0.47327592713176644894e1 0.72167708116161363042e0 0 0 0; 0 0 0 -0.28975994984220671445e0 0.24321233335964448997e1 -0.99133841479577475282e1 0.21377580445278298070e2 -0.24963717988619759059e2 0.16177915963135193396e2 -0.56554717249372471666e1 0.83471406934702410357e0 0 0; 0 0 0 0 -0.43028213606032104517e0 0.42103703770684731501e1 -0.15829711232892153976e2 0.29347405933458541883e2 -0.30751033700284402671e2 0.18952643607153901924e2 -0.64293095477239701048e1 0.92991669927993083983e0 0; 0 0 0 0 0 -0.76177813656089336989e0 0.63167064935286161169e1 -0.19922469032198601202e2 0.33781909556822143066e2 -0.34078413772067976385e2 0.20555296711011785159e2 -0.68760337833423921963e1 0.98478196280731881078e0; ]; + DD_7(m - 8:m, m - 12:m) = [-0.98478196280731881078e0 0.68760337833423921963e1 -0.20555296711011785159e2 0.34078413772067976385e2 -0.33781909556822143066e2 0.19922469032198601202e2 -0.63167064935286161169e1 0.76177813656089336989e0 0 0 0 0 0; 0 -0.92991669927993083983e0 0.64293095477239701048e1 -0.18952643607153901924e2 0.30751033700284402671e2 -0.29347405933458541883e2 0.15829711232892153976e2 -0.42103703770684731501e1 0.43028213606032104517e0 0 0 0 0; 0 0 -0.83471406934702410357e0 0.56554717249372471666e1 -0.16177915963135193396e2 0.24963717988619759059e2 -0.21377580445278298070e2 0.99133841479577475282e1 -0.24321233335964448997e1 0.28975994984220671445e0 0 0 0; 0 0 0 -0.72167708116161363042e0 0.47327592713176644894e1 -0.12831367737363170226e2 0.17679957518285956226e2 -0.13582054493165302513e2 0.63675477999083230026e1 -0.19678458985349116625e1 0.32268062071305431283e0 0 0; 0 0 0 0 -0.61955060619091911792e0 0.38654404904580696832e1 -0.94058676147776075845e1 0.12315008394369015993e2 -0.10585680229488408490e2 0.68105129732006589582e1 -0.31512297676528003033e1 0.77136636008199086135e0 0; 0 0 0 0 0 -0.55220578435115360075e0 0.31352892049258744203e1 -0.78247176680265960663e1 0.12900521495071139822e2 -0.16903069990805048996e2 0.18517285691402663507e2 -0.16323556769979337662e2 0.70504538217624585762e1; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_7 = sparse(DD_7); + + DD_8 = (diag(ones(m - 4, 1), 4) - 8 * diag(ones(m - 3, 1), 3) + 28 * diag(ones(m - 2, 1), 2) - 56 * diag(ones(m - 1, 1), 1) + 70 * diag(ones(m, 1), 0) - 56 * diag(ones(m - 1, 1), -1) + 28 * diag(ones(m - 2, 1), -2) - 8 * diag(ones(m - 3, 1), -3) + diag(ones(m - 4, 1), -4)); + DD_8(1:10, 1:14) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0.70504538217624673892e1 -0.17094923130061349891e2 0.21668515459055490895e2 -0.23713582964005737596e2 0.23486201724559577669e2 -0.20139726062395637234e2 0.12541156819703497681e2 -0.44176462748092288060e1 0.61955060619091989235e0 0 0 0 0 0; 0 0.71430915910501867497e0 -0.32169486987428931518e1 0.81290324137612243914e1 -0.15699214646211457760e2 0.23981482952559874949e2 -0.25082313639406953559e2 0.15461761961832278733e2 -0.49564048495273529434e1 0.66829534663026066516e0 0 0 0 0; 0 0 0.29213206789956748018e0 -0.20438756549159061384e1 0.79665959467484077329e1 -0.21271097908734749058e2 0.35359915036571912453e2 -0.34216980632968453935e2 0.18931037085270657958e2 -0.57734166492929090433e1 0.75569070942147255138e0 0 0 0; 0 0 0 0.26637215914130374043e0 -0.26313682263734604148e1 0.12983764630211125301e2 -0.34204128712445276912e2 0.49927435977239518119e2 -0.43141109235027182388e2 0.22621886899748988667e2 -0.66777125547761928286e1 0.85485906228117671607e0 0 0; 0 0 0 0 0.41007336094698233166e0 -0.47386249189431794318e1 0.21106281643856205301e2 -0.46955849493533667013e2 0.61502067400568805342e2 -0.50540382952410405130e2 0.25717238190895880419e2 -0.74393335942394467187e1 0.93853036285882489957e0 0; 0 0 0 0 0 0.75161513192516571838e0 -0.72190931354612755621e1 0.26563292042931468269e2 -0.54051055290915428906e2 0.68156827544135952769e2 -0.54814124562698093757e2 0.27504135133369568785e2 -0.78782557024585504862e1 0.98665883917119316896e0; ]; + DD_8(m - 9:m, m - 13:m) = [0.98665883917119316896e0 -0.78782557024585504862e1 0.27504135133369568785e2 -0.54814124562698093757e2 0.68156827544135952769e2 -0.54051055290915428906e2 0.26563292042931468269e2 -0.72190931354612755621e1 0.75161513192516571838e0 0 0 0 0 0; 0 0.93853036285882489957e0 -0.74393335942394467187e1 0.25717238190895880419e2 -0.50540382952410405130e2 0.61502067400568805342e2 -0.46955849493533667013e2 0.21106281643856205301e2 -0.47386249189431794318e1 0.41007336094698233166e0 0 0 0 0; 0 0 0.85485906228117671607e0 -0.66777125547761928286e1 0.22621886899748988667e2 -0.43141109235027182388e2 0.49927435977239518119e2 -0.34204128712445276912e2 0.12983764630211125301e2 -0.26313682263734604148e1 0.26637215914130374043e0 0 0 0; 0 0 0 0.75569070942147255138e0 -0.57734166492929090433e1 0.18931037085270657958e2 -0.34216980632968453935e2 0.35359915036571912453e2 -0.21271097908734749058e2 0.79665959467484077329e1 -0.20438756549159061384e1 0.29213206789956748018e0 0 0; 0 0 0 0 0.66829534663026066516e0 -0.49564048495273529434e1 0.15461761961832278733e2 -0.25082313639406953559e2 0.23981482952559874949e2 -0.15699214646211457760e2 0.81290324137612243914e1 -0.32169486987428931518e1 0.71430915910501867497e0 0; 0 0 0 0 0 0.61955060619091989235e0 -0.44176462748092288060e1 0.12541156819703497681e2 -0.20139726062395637234e2 0.23486201724559577669e2 -0.23713582964005737596e2 0.21668515459055490895e2 -0.17094923130061349891e2 0.70504538217624673892e1; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_8 = sparse(DD_8); + + DD_9 = (-diag(ones(m - 5, 1), -5) + 9 * diag(ones(m - 4, 1), -4) - 36 * diag(ones(m - 3, 1), -3) + 84 * diag(ones(m - 2, 1), -2) - 126 * diag(ones(m - 1, 1), -1) + 126 * diag(ones(m, 1), 0) - 84 * diag(ones(m - 1, 1), 1) + 36 * diag(ones(m - 2, 1), 2) - 9 * diag(ones(m - 3, 1), 3) + diag(ones(m - 4, 1), 4)); + DD_9(1:11, 1:15) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; -0.70504538217624752230e1 0.17809232289166388354e2 -0.24885464157798411697e2 0.31842615377766997368e2 -0.39185416370771078968e2 0.44121209014955561206e2 -0.37623470459110493043e2 0.19879408236641529627e2 -0.55759554557182790312e1 0.66829534663026140771e0 0 0 0 0 0; 0 -0.66695396914459764542e0 0.32764459415493351213e1 -0.94984942131335544919e1 0.22096883550779531311e2 -0.42252556942280502185e2 0.56435205688665645507e2 -0.46385285885496836199e2 0.22303821822873088245e2 -0.60146581196723459865e1 0.70559212586023632254e0 0 0 0 0; 0 0 -0.26728718140337933088e0 0.21137687176984662199e1 -0.96966416347745772182e1 0.31341597391980823551e2 -0.63647847065829442415e2 0.76988206424179021354e2 -0.56793111255811973873e2 0.25980374921818090695e2 -0.68012163847932529624e1 0.78215606693622397877e0 0 0 0; 0 0 0 -0.24708804973573377055e0 0.28212553166921198174e1 -0.16439370707786854975e2 0.51306193068667915368e2 -0.89869384759031132614e2 0.97067495778811160373e2 -0.67865660699246966000e2 0.30049706496492867728e2 -0.76937315605305904447e1 0.87058511566721451662e0 0 0; 0 0 0 0 -0.39286387086790423439e0 0.52598319320161875843e1 -0.27136647827815121102e2 0.70433774240300500520e2 -0.11070372132102384962e3 0.11371586164292341154e3 -0.77151714572687641258e2 0.33477001174077510234e2 -0.84467732657294240961e1 0.94525186880633042479e0 0; 0 0 0 0 0 -0.74268863896636254047e0 0.81214797773939350074e1 -0.34152804055197602060e2 0.81076582936373143359e2 -0.12268228957944471498e3 0.12333178026607071095e3 -0.82512405400108706356e2 0.35452150661063477188e2 -0.88799295525407385207e1 0.98812358535685795524e0; ]; + DD_9(m - 9:m, m - 14:m) = [-0.98812358535685795524e0 0.88799295525407385207e1 -0.35452150661063477188e2 0.82512405400108706356e2 -0.12333178026607071095e3 0.12268228957944471498e3 -0.81076582936373143359e2 0.34152804055197602060e2 -0.81214797773939350074e1 0.74268863896636254047e0 0 0 0 0 0; 0 -0.94525186880633042479e0 0.84467732657294240961e1 -0.33477001174077510234e2 0.77151714572687641258e2 -0.11371586164292341154e3 0.11070372132102384962e3 -0.70433774240300500520e2 0.27136647827815121102e2 -0.52598319320161875843e1 0.39286387086790423439e0 0 0 0 0; 0 0 -0.87058511566721451662e0 0.76937315605305904447e1 -0.30049706496492867728e2 0.67865660699246966000e2 -0.97067495778811160373e2 0.89869384759031132614e2 -0.51306193068667915368e2 0.16439370707786854975e2 -0.28212553166921198174e1 0.24708804973573377055e0 0 0 0; 0 0 0 -0.78215606693622397877e0 0.68012163847932529624e1 -0.25980374921818090695e2 0.56793111255811973873e2 -0.76988206424179021354e2 0.63647847065829442415e2 -0.31341597391980823551e2 0.96966416347745772182e1 -0.21137687176984662199e1 0.26728718140337933088e0 0 0; 0 0 0 0 -0.70559212586023632254e0 0.60146581196723459865e1 -0.22303821822873088245e2 0.46385285885496836199e2 -0.56435205688665645507e2 0.42252556942280502185e2 -0.22096883550779531311e2 0.94984942131335544919e1 -0.32764459415493351213e1 0.66695396914459764542e0 0; 0 0 0 0 0 -0.66829534663026140771e0 0.55759554557182790312e1 -0.19879408236641529627e2 0.37623470459110493043e2 -0.44121209014955561206e2 0.39185416370771078968e2 -0.31842615377766997368e2 0.24885464157798411697e2 -0.17809232289166388354e2 0.70504538217624752230e1; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_9 = sparse(DD_9); + + DD_10 = (diag(ones(m - 5, 1), 5) - 10 * diag(ones(m - 4, 1), 4) + 45 * diag(ones(m - 3, 1), 3) - 120 * diag(ones(m - 2, 1), 2) + 210 * diag(ones(m - 1, 1), 1) - 252 * diag(ones(m, 1), 0) + 210 * diag(ones(m - 1, 1), -1) - 120 * diag(ones(m - 2, 1), -2) + 45 * diag(ones(m - 3, 1), -3) - 10 * diag(ones(m - 4, 1), -4) + diag(ones(m - 5, 1), -5)); + DD_10(1:11, 1:16) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0.70504538217624822734e1 -0.18476186258311004476e2 0.28161910099347774980e2 -0.41341109590900593201e2 0.61282299921550671561e2 -0.86373765957236149764e2 0.94058676147776232608e2 -0.66264694122138432090e2 0.27879777278591395156e2 -0.66829534663026140771e1 0.70559212586023702812e0 0 0 0 0 0; 0 0.62689419647750179604e0 -0.33308831364980034247e1 0.10914786591113557343e2 -0.29883886064802801254e2 0.69173811658980680918e2 -0.11287041137733129101e3 0.11596321471374209050e3 -0.74346072742910294151e2 0.30073290598361729932e2 -0.70559212586023632254e1 0.73517682146919258207e0 0 0 0 0; 0 0 0.24665297575614270036e0 -0.21786018467637256442e1 0.11551532389532584562e2 -0.44092342567416599454e2 0.10607974510971573736e3 -0.15397641284835804271e3 0.14198277813952993468e3 -0.86601249739393635650e2 0.34006081923966264812e2 -0.78215606693622397877e1 0.80337713279357912969e0 0 0 0; 0 0 0 0.23087142251463535911e0 -0.30031734426541638399e1 0.20275063024062368195e2 -0.73294561526668450525e2 0.14978230793171855436e3 -0.19413499155762232075e3 0.16966415174811741500e3 -0.10016568832164289243e3 0.38468657802652952223e2 -0.87058511566721451662e1 0.88321407619404757308e0 0 0; 0 0 0 0 0.37796280007363075810e0 -0.57748488744870271355e1 0.33920809784768901377e2 -0.10061967748614357217e3 0.18450620220170641603e3 -0.22743172328584682309e3 0.19287928643171910314e3 -0.11159000391359170078e3 0.42233866328647120480e2 -0.94525186880633042479e1 0.95064470121725563376e0 0; 0 0 0 0 0 0.73474076934244039806e0 -0.90238664193265944527e1 0.42691005068997002575e2 -0.11582368990910449051e3 0.20447048263240785831e3 -0.24666356053214142190e3 0.20628101350027176589e3 -0.11817383553687825729e3 0.44399647762703692603e2 -0.98812358535685795524e1 0.98929851729658394154e0; ]; + DD_10(m - 10:m, m - 15:m) = [0.98929851729658394154e0 -0.98812358535685795524e1 0.44399647762703692603e2 -0.11817383553687825729e3 0.20628101350027176589e3 -0.24666356053214142190e3 0.20447048263240785831e3 -0.11582368990910449051e3 0.42691005068997002575e2 -0.90238664193265944527e1 0.73474076934244039806e0 0 0 0 0 0; 0 0.95064470121725563376e0 -0.94525186880633042479e1 0.42233866328647120480e2 -0.11159000391359170078e3 0.19287928643171910314e3 -0.22743172328584682309e3 0.18450620220170641603e3 -0.10061967748614357217e3 0.33920809784768901377e2 -0.57748488744870271355e1 0.37796280007363075810e0 0 0 0 0; 0 0 0.88321407619404757308e0 -0.87058511566721451662e1 0.38468657802652952223e2 -0.10016568832164289243e3 0.16966415174811741500e3 -0.19413499155762232075e3 0.14978230793171855436e3 -0.73294561526668450525e2 0.20275063024062368195e2 -0.30031734426541638399e1 0.23087142251463535911e0 0 0 0; 0 0 0 0.80337713279357912969e0 -0.78215606693622397877e1 0.34006081923966264812e2 -0.86601249739393635650e2 0.14198277813952993468e3 -0.15397641284835804271e3 0.10607974510971573736e3 -0.44092342567416599454e2 0.11551532389532584562e2 -0.21786018467637256442e1 0.24665297575614270036e0 0 0; 0 0 0 0 0.73517682146919258207e0 -0.70559212586023632254e1 0.30073290598361729932e2 -0.74346072742910294151e2 0.11596321471374209050e3 -0.11287041137733129101e3 0.69173811658980680918e2 -0.29883886064802801254e2 0.10914786591113557343e2 -0.33308831364980034247e1 0.62689419647750179604e0 0; 0 0 0 0 0 0.70559212586023702812e0 -0.66829534663026140771e1 0.27879777278591395156e2 -0.66264694122138432090e2 0.94058676147776232608e2 -0.86373765957236149764e2 0.61282299921550671561e2 -0.41341109590900593201e2 0.28161910099347774980e2 -0.18476186258311004476e2 0.70504538217624822734e1; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_10 = sparse(DD_10); + + %[-1, 11, -55, 165, -330, 462, -462, 330, -165, 55, -11, 1, 0] + DD_11 = (-diag(ones(m - 6, 1), -6) + 11 * diag(ones(m - 5, 1), -5) - 55 * diag(ones(m - 4, 1), -4) + 165 * diag(ones(m - 3, 1), -3) - 330 * diag(ones(m - 2, 1), -2) + 462 * diag(ones(m - 1, 1), -1) - 462 * diag(ones(m, 1), 0) + 330 * diag(ones(m - 1, 1), 1) - 165 * diag(ones(m - 2, 1), 2) + 55 * diag(ones(m - 3, 1), 3) - 11 * diag(ones(m - 4, 1), 4) + diag(ones(m - 5, 1), 5)); + DD_11(1:12, 1:17) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; -0.70504538217624886828e1 0.19103080454788523638e2 -0.31492793235845807035e2 0.52255896182014198048e2 -0.91166185986353555693e2 0.15554757761621697209e3 -0.20692908752510771174e3 0.18222790883588068825e3 -0.10222585002150178224e3 0.36756244064664377424e2 -0.77615133844626073094e1 0.73517682146919325041e0 0 0 0 0 0; 0 -0.59247568548574727441e0 0.33811178542850964393e1 -0.12374519230919224800e2 0.39160480492663455349e2 -0.10704747746062038309e3 0.20692908752510736686e3 -0.25511907237023259909e3 0.20445170004300330891e3 -0.11026873219399300975e3 0.38807566922312997740e2 -0.80869450361611184028e1 0.75926914003985711330e0 0 0 0 0; 0 0 -0.22922038452398770506e0 0.22391799149842653766e1 -0.13526028855965613027e2 0.59818136859120542509e2 -0.16669674231526758728e3 0.28229009022198974497e3 -0.31236211190696585630e3 0.23815343678333249804e3 -0.12468896705454297098e3 0.43018583681492318832e2 -0.88371484607293704266e1 0.82079151707601599340e0 0 0 0; 0 0 0 -0.21701391114437616116e0 0.31781915325611402199e1 -0.24486327517266714070e2 0.10078002209916911947e3 -0.23537219817841487113e3 0.35591415118897425470e3 -0.37326113384585831300e3 0.27545564288451795418e3 -0.14105174527639415815e3 0.47882181361696798414e2 -0.97153548381345233039e1 0.89358450029368883150e0 0 0; 0 0 0 0 -0.36488508570871329747e0 0.62843543720560487741e1 -0.41458767514717546128e2 0.13835205654344741174e3 -0.28993831774553865375e3 0.41695815935738584232e3 -0.42433443014978202692e3 0.30687251076237717714e3 -0.15485750987170610843e3 0.51988852784348173364e2 -0.10457091713389811971e2 0.95506826122820715686e0 0; 0 0 0 0 0 -0.72758579432539352184e0 0.99262530612592538979e1 -0.52177895084329669814e2 0.15925757362501867446e3 -0.32131075842235520591e3 0.45221652764225927349e3 -0.45381822970059788496e3 0.32497804772641520756e3 -0.16279870846324687288e3 0.54346797194627187538e2 -0.10882283690262423357e2 0.99026190553785350209e0; ]; + DD_11(m - 10:m, m - 16:m) = [-0.99026190553785350209e0 0.10882283690262423357e2 -0.54346797194627187538e2 0.16279870846324687288e3 -0.32497804772641520756e3 0.45381822970059788496e3 -0.45221652764225927349e3 0.32131075842235520591e3 -0.15925757362501867446e3 0.52177895084329669814e2 -0.99262530612592538979e1 0.72758579432539352184e0 0 0 0 0 0; 0 -0.95506826122820715686e0 0.10457091713389811971e2 -0.51988852784348173364e2 0.15485750987170610843e3 -0.30687251076237717714e3 0.42433443014978202692e3 -0.41695815935738584232e3 0.28993831774553865375e3 -0.13835205654344741174e3 0.41458767514717546128e2 -0.62843543720560487741e1 0.36488508570871329747e0 0 0 0 0; 0 0 -0.89358450029368883150e0 0.97153548381345233039e1 -0.47882181361696798414e2 0.14105174527639415815e3 -0.27545564288451795418e3 0.37326113384585831300e3 -0.35591415118897425470e3 0.23537219817841487113e3 -0.10078002209916911947e3 0.24486327517266714070e2 -0.31781915325611402199e1 0.21701391114437616116e0 0 0 0; 0 0 0 -0.82079151707601599340e0 0.88371484607293704266e1 -0.43018583681492318832e2 0.12468896705454297098e3 -0.23815343678333249804e3 0.31236211190696585630e3 -0.28229009022198974497e3 0.16669674231526758728e3 -0.59818136859120542509e2 0.13526028855965613027e2 -0.22391799149842653766e1 0.22922038452398770506e0 0 0; 0 0 0 0 -0.75926914003985711330e0 0.80869450361611184028e1 -0.38807566922312997740e2 0.11026873219399300975e3 -0.20445170004300330891e3 0.25511907237023259909e3 -0.20692908752510736686e3 0.10704747746062038309e3 -0.39160480492663455349e2 0.12374519230919224800e2 -0.33811178542850964393e1 0.59247568548574727441e0 0; 0 0 0 0 0 -0.73517682146919325041e0 0.77615133844626073094e1 -0.36756244064664377424e2 0.10222585002150178224e3 -0.18222790883588068825e3 0.20692908752510771174e3 -0.15554757761621697209e3 0.91166185986353555693e2 -0.52255896182014198048e2 0.31492793235845807035e2 -0.19103080454788523638e2 0.70504538217624886828e1; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_11 = sparse(DD_11); + + %[1, -12, 66, -220, 495, -792, 924, -792, 495, -220, 66,-12, 1] + DD_12 = (diag(ones(m - 6, 1), 6) - 12 * diag(ones(m - 5, 1), 5) + 66 * diag(ones(m - 4, 1), 4) - 220 * diag(ones(m - 3, 1), 3) + 495 * diag(ones(m - 2, 1), 2) - 792 * diag(ones(m - 1, 1), 1) + 924 * diag(ones(m, 1), 0) - 792 * diag(ones(m - 1, 1), -1) + 495 * diag(ones(m - 2, 1), -2) - 220 * diag(ones(m - 3, 1), -3) + 66 * diag(ones(m - 4, 1), -4) - 12 * diag(ones(m - 5, 1), -5) + diag(ones(m - 6, 1), -6)); + DD_12(1:12, 1:18) = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0.70504538217624945581e1 -0.19695556140274287325e2 0.34873911090130932535e2 -0.64630415412933476707e2 0.13032666647901711965e3 -0.26259505507683757401e3 0.41385817505021542347e3 -0.43734698120611365179e3 0.30667755006450534672e3 -0.14702497625865750970e3 0.46569080306775643856e2 -0.88221218576303190049e1 0.75926914003985774602e0 0 0 0 0 0; 0 0.56252054413792412864e0 -0.34278021535209417538e1 0.13874841106233553089e2 -0.50022717612825328606e2 0.15842900977125025845e3 -0.35473557861446977176e3 0.51023814474046519819e3 -0.49068408010320794140e3 0.33080619658197902926e3 -0.15523026768925199096e3 0.48521670216966710417e2 -0.91112296804782853596e1 0.77929289272158630803e0 0 0 0 0; 0 0 0.21428192906429919385e0 -0.22961219278627835050e1 0.15615594467315483385e2 -0.78810282483468544556e2 0.25004511347290138092e3 -0.48392586895198241994e3 0.62472422381393171260e3 -0.57156824827999799529e3 0.37406690116362891293e3 -0.17207433472596927533e3 0.53022890764376222560e2 -0.98494982049121919208e1 0.83534896297519895228e0 0 0 0; 0 0 0 0.20501361895561890151e0 -0.33471539032596363119e1 0.29069145008244604383e2 -0.13437336279889215930e3 0.35305829726762230670e3 -0.61013854489538443663e3 0.74652226769171662600e3 -0.66109354292284309003e3 0.42315523582918247446e3 -0.19152872544678719366e3 0.58292129028807139823e2 -0.10723014003524265978e2 0.90225552616201164306e0 0 0; 0 0 0 0 0.35327850260839005288e0 -0.67888982569607603271e1 0.49750521017661055353e2 -0.18446940872459654898e3 0.43490747661830798063e3 -0.71478541604123287255e3 0.84866886029956405384e3 -0.73649402582970522515e3 0.46457252961511832529e3 -0.20795541113739269345e3 0.62742550280338871828e2 -0.11460819134738485882e2 0.95876279102790935799e0 0; 0 0 0 0 0 0.72108566182178027310e0 -0.10828639703191913343e2 0.62613474101195603777e2 -0.21234343150002489927e3 0.48196613763353280887e3 -0.77522833310101589741e3 0.90763645940119576992e3 -0.77994731454339649814e3 0.48839612538974061864e3 -0.21738718877850875015e3 0.65293702141574540142e2 -0.11883142866454242025e2 0.99106616353107873319e0; ]; + DD_12(m - 11:m, m - 17:m) = [0.99106616353107873319e0 -0.11883142866454242025e2 0.65293702141574540142e2 -0.21738718877850875015e3 0.48839612538974061864e3 -0.77994731454339649814e3 0.90763645940119576992e3 -0.77522833310101589741e3 0.48196613763353280887e3 -0.21234343150002489927e3 0.62613474101195603777e2 -0.10828639703191913343e2 0.72108566182178027310e0 0 0 0 0 0; 0 0.95876279102790935799e0 -0.11460819134738485882e2 0.62742550280338871828e2 -0.20795541113739269345e3 0.46457252961511832529e3 -0.73649402582970522515e3 0.84866886029956405384e3 -0.71478541604123287255e3 0.43490747661830798063e3 -0.18446940872459654898e3 0.49750521017661055353e2 -0.67888982569607603271e1 0.35327850260839005288e0 0 0 0 0; 0 0 0.90225552616201164306e0 -0.10723014003524265978e2 0.58292129028807139823e2 -0.19152872544678719366e3 0.42315523582918247446e3 -0.66109354292284309003e3 0.74652226769171662600e3 -0.61013854489538443663e3 0.35305829726762230670e3 -0.13437336279889215930e3 0.29069145008244604383e2 -0.33471539032596363119e1 0.20501361895561890151e0 0 0 0; 0 0 0 0.83534896297519895228e0 -0.98494982049121919208e1 0.53022890764376222560e2 -0.17207433472596927533e3 0.37406690116362891293e3 -0.57156824827999799529e3 0.62472422381393171260e3 -0.48392586895198241994e3 0.25004511347290138092e3 -0.78810282483468544556e2 0.15615594467315483385e2 -0.22961219278627835050e1 0.21428192906429919385e0 0 0; 0 0 0 0 0.77929289272158630803e0 -0.91112296804782853596e1 0.48521670216966710417e2 -0.15523026768925199096e3 0.33080619658197902926e3 -0.49068408010320794140e3 0.51023814474046519819e3 -0.35473557861446977176e3 0.15842900977125025845e3 -0.50022717612825328606e2 0.13874841106233553089e2 -0.34278021535209417538e1 0.56252054413792412864e0 0; 0 0 0 0 0 0.75926914003985774602e0 -0.88221218576303190049e1 0.46569080306775643856e2 -0.14702497625865750970e3 0.30667755006450534672e3 -0.43734698120611365179e3 0.41385817505021542347e3 -0.26259505507683757401e3 0.13032666647901711965e3 -0.64630415412933476707e2 0.34873911090130932535e2 -0.19695556140274287325e2 0.70504538217624945581e1; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_12 = sparse(DD_12); + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Difference operators %% + D1 = H \ Q; + + % Helper functions for constructing D2(c) + % TODO: Consider changing sparse(diag(...)) to spdiags(....) + + % Minimal 13 point stencil width + function D2 = D2_fun_minimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 5/18 * diag(ones(m - 1, 1), -1) + 5/18 * diag(ones(m - 1, 1), 1) + 4/9 * diag(ones(m, 1), 0); C3(1, 3) = 5/18; C3(m, m - 2) = 5/18; + C4 = 5/28 * diag(ones(m - 2, 1), -2) + 9/28 * diag(ones(m - 1, 1), -1) + 5/28 * diag(ones(m - 1, 1), 1) + 9/28 * diag(ones(m, 1), 0); C4(2, 4) = 5/28; C4(1, 3) = 5/28; C4(1, 4) = 9/28; C4(m, m - 2) = 5/28; C4(m, m - 3) = 5/28; + C5 = 1/7 * diag(ones(m - 2, 1), -2) + 1/7 * diag(ones(m - 2, 1), 2) + 8/35 * diag(ones(m - 1, 1), -1) + 8/35 * diag(ones(m - 1, 1), 1) + 9/35 * diag(ones(m, 1), 0); C5(2, 4) = 1/7; C5(1, 3) = 1/7; C5(1, 4) = 1/7; C5(1, 5) = 8/35; C5(2, 5) = 1/7; C5(m - 1, m - 4) = 1/7; C5(m, m - 4) = 8/35; C5(m, m - 3) = 1/7; + C6 = 1/6 * diag(ones(m - 3, 1), -3) + 1/6 * diag(ones(m - 2, 1), -2) + 1/6 * diag(ones(m - 2, 1), 2) + 1/6 * diag(ones(m - 1, 1), -1) + 1/6 * diag(ones(m - 1, 1), 1) + 1/6 * diag(ones(m, 1), 0); + C6(1, 4) = 1/6; C6(1, 5) = 1/6; C6(1, 6) = 1/6; C6(2, 5) = 1/6; C6(2, 6) = 1/6; C6(3, 6) = 1/6; C6(m - 1, m - 5) = 1/6; C6(m, m - 4) = 1/6; C6(m, m - 5) = 1/6; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + C4 = sparse(diag(C4 * c)); + C5 = sparse(diag(C5 * c)); + C6 = sparse(diag(C6 * c)); + + % Remainder term added to wide second derivative operator + R = (1/30735936 / h) * transpose(DD_12) * C1 * DD_12 + (1/6403320 / h) * transpose(DD_11) * C2 * DD_11 + (1/1293600 / h) * transpose(DD_10) * C3 * DD_10 + (1/249480 / h) * transpose(DD_9) * C4 * DD_9 + (1/44352 / h) * transpose(DD_8) * C5 * DD_8 + (1/6468 / h) * transpose(DD_7) * C6 * DD_7; + D2 = D1 * C1 * D1 - H \ R; + end + + % Few additional grid point in interior stencil cmp. to minimal + function D2 = D2_fun_nonminimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 5/18 * diag(ones(m - 1, 1), -1) + 5/18 * diag(ones(m - 1, 1), 1) + 4/9 * diag(ones(m, 1), 0); C3(1, 3) = 5/18; C3(m, m - 2) = 5/18; + C4 = 5/28 * diag(ones(m - 2, 1), -2) + 9/28 * diag(ones(m - 1, 1), -1) + 5/28 * diag(ones(m - 1, 1), 1) + 9/28 * diag(ones(m, 1), 0); C4(2, 4) = 5/28; C4(1, 3) = 5/28; C4(1, 4) = 9/28; C4(m, m - 2) = 5/28; C4(m, m - 3) = 5/28; + C5 = 1/7 * diag(ones(m - 2, 1), -2) + 1/7 * diag(ones(m - 2, 1), 2) + 8/35 * diag(ones(m - 1, 1), -1) + 8/35 * diag(ones(m - 1, 1), 1) + 9/35 * diag(ones(m, 1), 0); C5(2, 4) = 1/7; C5(1, 3) = 1/7; C5(1, 4) = 1/7; C5(1, 5) = 8/35; C5(2, 5) = 1/7; C5(m - 1, m - 4) = 1/7; C5(m, m - 4) = 8/35; C5(m, m - 3) = 1/7; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + C4 = sparse(diag(C4 * c)); + C5 = sparse(diag(C5 * c)); + + % Remainder term added to wide second derivative operator + R = (1/30735936 / h) * transpose(DD_12) * C1 * DD_12 + (1/6403320 / h) * transpose(DD_11) * C2 * DD_11 + (1/1293600 / h) * transpose(DD_10) * C3 * DD_10 + (1/249480 / h) * transpose(DD_9) * C4 * DD_9 + (1/44352 / h) * transpose(DD_8) * C5 * DD_8; + D2 = D1 * C1 * D1 - H \ R; + end + + % Wide stencil + function D2 = D2_fun_wide(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + D2 = D1 * C1 * D1; + end + + switch options.stencil_width + case 'minimal' + D2 = @D2_fun_minimal; + case 'nonminimal' + D2 = @D2_fun_nonminimal; + case 'wide' + D2 = @D2_fun_wide; + otherwise + error('No option %s for stencil width', options.stencil_width) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Artificial dissipation operator %%% + switch options.AD + case 'upwind' + % This is the choice that yield 11th order Upwind + DI = H \ (transpose(DD_6) * DD_6) * (-1/5544); + case 'op' + % This choice will preserve the order of the underlying + % Non-dissipative D1 SBP operator + DI = H \ (transpose(DD_7) * DD_7) * (-1 / (5 * 5544)); + % Notice that you can use any negative number instead of (-1/(5*5544)) + otherwise + error("Artificial dissipation options '%s' not implemented.", option.AD) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+implementations/d2_noneq_variable_4.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,162 @@ +function [H, HI, D1, D2, DI] = d2_noneq_variable_4(N, h, options) + % N: Number of grid points + % h: grid spacing + % options: struct containing options for constructing the operator + % current options are: + % options.stencil_type ('minimal','nonminimal','wide') + % options.AD ('upwind', 'op') + + % BP: Number of boundary points + % order: Accuracy of interior stencil + BP = 4; + order = 4; + if(N<2*BP) + error(['Operator requires at least ' num2str(2*BP) ' grid points']); + end + + %%%% Norm matrix %%%%%%%% + P = zeros(BP, 1); + P0 = 2.1259737557798e-01; + P1 = 1.0260290400758e+00; + P2 = 1.0775123588954e+00; + P3 = 9.8607273802835e-01; + + for i = 0:BP - 1 + P(i + 1) = eval(['P' num2str(i)]); + end + + Hv = ones(N, 1); + Hv(1:BP) = P; + Hv(end - BP + 1:end) = flip(P); + Hv = h * Hv; + H = spdiags(Hv, 0, N, N); + HI = spdiags(1 ./ Hv, 0, N, N); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Q matrix %%%%%%%%%%% + d = [1/12, -2/3, 0, 2/3, -1/12]; + d = repmat(d, N, 1); + Q = spdiags(d, -order / 2:order / 2, N, N); + + % Boundaries + Q0_0 = -5.0000000000000e-01; + Q0_1 = 6.5605279837843e-01; + Q0_2 = -1.9875859409017e-01; + Q0_3 = 4.2705795711740e-02; + Q0_4 = 0.0000000000000e+00; + Q0_5 = 0.0000000000000e+00; + Q1_0 = -6.5605279837843e-01; + Q1_1 = 0.0000000000000e+00; + Q1_2 = 8.1236966439895e-01; + Q1_3 = -1.5631686602052e-01; + Q1_4 = 0.0000000000000e+00; + Q1_5 = 0.0000000000000e+00; + Q2_0 = 1.9875859409017e-01; + Q2_1 = -8.1236966439895e-01; + Q2_2 = 0.0000000000000e+00; + Q2_3 = 6.9694440364211e-01; + Q2_4 = -8.3333333333333e-02; + Q2_5 = 0.0000000000000e+00; + Q3_0 = -4.2705795711740e-02; + Q3_1 = 1.5631686602052e-01; + Q3_2 = -6.9694440364211e-01; + Q3_3 = 0.0000000000000e+00; + Q3_4 = 6.6666666666667e-01; + Q3_5 = -8.3333333333333e-02; + + for i = 1:BP + + for j = 1:BP + Q(i, j) = eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + Q(N + 1 - i, N + 1 - j) = -eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + end + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%% Undivided difference operators %%%% + % Closed with zeros at the first boundary nodes. + m = N; + + DD_2 = (diag(ones(m - 1, 1), -1) - 2 * diag(ones(m, 1), 0) + diag(ones(m - 1, 1), 1)); + DD_2(1:3, 1:4) = [0 0 0 0; 0.16138369498429727170e1 -0.26095138364100825853e1 0.99567688656710986834e0 0; 0 0.84859980956172494512e0 -0.17944203477786665350e1 0.94582053821694158989e0; ]; + DD_2(m - 2:m, m - 3:m) = [0.94582053821694158989e0 -0.17944203477786665350e1 0.84859980956172494512e0 0; 0 0.99567688656710986834e0 -0.26095138364100825853e1 0.16138369498429727170e1; 0 0 0 0; ]; + DD_2 = sparse(DD_2); + + DD_3 = (-diag(ones(m - 2, 1), -2) + 3 * diag(ones(m - 1, 1), -1) - 3 * diag(ones(m, 1), 0) + diag(ones(m - 1, 1), 1)); + DD_3(1:4, 1:5) = [0 0 0 0 0; 0 0 0 0 0; -0.17277463987989539852e1 0.37021976718569105700e1 -0.29870306597013296050e1 0.10125793866433730203e1 0; 0 -0.81738495424057284493e0 0.26916305216679998025e1 -0.28374616146508247697e1 0.96321604722339781208e0; ]; + DD_3(m - 2:m, m - 4:m) = [-0.96321604722339781208e0 0.28374616146508247697e1 -0.26916305216679998025e1 0.81738495424057284493e0 0; 0 -0.10125793866433730203e1 0.29870306597013296050e1 -0.37021976718569105700e1 0.17277463987989539852e1; 0 0 0 0 0; ]; + DD_3 = sparse(DD_3); + + DD_4 = (diag(ones(m - 2, 1), 2) - 4 * diag(ones(m - 1, 1), 1) + 6 * diag(ones(m, 1), 0) - 4 * diag(ones(m - 1, 1), -1) + diag(ones(m - 2, 1), -2)); + DD_4(1:4, 1:6) = [0 0 0 0 0 0; 0 0 0 0 0 0; 0.18176226052481525189e1 -0.47546882767009058782e1 0.59740613194026592100e1 -0.40503175465734920811e1 0.10133218986235862303e1 0; 0 0.79462567299107735362e0 -0.35888406955573330700e1 0.56749232293016495393e1 -0.38528641888935912483e1 0.97215598215819742539e0; ]; + DD_4(m - 3:m, m - 5:m) = [0.97215598215819742539e0 -0.38528641888935912483e1 0.56749232293016495393e1 -0.35888406955573330700e1 0.79462567299107735362e0 0; 0 0.10133218986235862303e1 -0.40503175465734920811e1 0.59740613194026592100e1 -0.47546882767009058782e1 0.18176226052481525189e1; 0 0 0 0 0 0; 0 0 0 0 0 0; ]; + DD_4 = sparse(DD_4); + %%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Difference operators %%% + D1 = H \ Q; + + % Helper functions for constructing D2(c) + % TODO: Consider changing sparse(diag(...)) to spdiags(....) + + % Minimal 5 point stencil width + function D2 = D2_fun_minimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + + C2 = sparse(diag(C2 * c)); + + % Remainder term added to wide second drivative opereator, to obtain a 5 + % point narrow stencil. + R = (1/144 / h) * transpose(DD_4) * C1 * DD_4 + (1/18 / h) * transpose(DD_3) * C2 * DD_3; + D2 = D1 * C1 * D1 - H \ R; + end + + % Few additional grid point in interior stencil cmp. to minimal + function D2 = D2_fun_nonminimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + + % Remainder term added to wide second derivative operator + R = (1/144 / h) * transpose(DD_4) * C1 * DD_4; + D2 = D1 * C1 * D1 - H \ R; + end + + % Wide stencil + function D2 = D2_fun_wide(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + D2 = D1 * C1 * D1; + end + + switch options.stencil_width + case 'minimal' + D2 = @D2_fun_minimal; + case 'nonminimal' + D2 = @D2_fun_nonminimal; + case 'wide' + D2 = @D2_fun_wide; + otherwise + error('No option %s for stencil width', options.stencil_width) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Artificial dissipation operator %%% + switch options.AD + case 'upwind' + % This is the choice that yield 3rd order Upwind + DI = H \ (transpose(DD_2) * DD_2) * (-1/12); + case 'op' + % This choice will preserve the order of the underlying + % Non-dissipative D1 SBP operator + DI = H \ (transpose(DD_3) * DD_3) * (-1 / (5 * 12)); + otherwise + error("Artificial dissipation options '%s' not implemented.", option.AD) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+implementations/d2_noneq_variable_6.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,205 @@ +function [H, HI, D1, D2, DI] = d2_noneq_variable_6(N, h, options) + % N: Number of grid points + % h: grid spacing + % options: struct containing options for constructing the operator + % current options are: + % options.stencil_type ('minimal','nonminimal','wide') + % options.AD ('upwind', 'op') + + % BP: Number of boundary points + % order: Accuracy of interior stencil + BP = 6; + order = 6; + if(N<2*BP) + error(['Operator requires at least ' num2str(2*BP) ' grid points']); + end + + %%%% Norm matrix %%%%%%%% + P = zeros(BP, 1); + P0 = 1.3030223027124e-01; + P1 = 6.8851501587715e-01; + P2 = 9.5166202564389e-01; + P3 = 9.9103890475697e-01; + P4 = 1.0028757074552e+00; + P5 = 9.9950151111941e-01; + + for i = 0:BP - 1 + P(i + 1) = eval(['P' num2str(i)]); + end + + Hv = ones(N, 1); + Hv(1:BP) = P; + Hv(end - BP + 1:end) = flip(P); + Hv = h * Hv; + H = spdiags(Hv, 0, N, N); + HI = spdiags(1 ./ Hv, 0, N, N); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Q matrix %%%%%%%%%%% + + % interior stencil + d = [-1/60, 3/20, -3/4, 0, 3/4, -3/20, 1/60]; + d = repmat(d, N, 1); + Q = spdiags(d, -order / 2:order / 2, N, N); + + % Boundaries + Q0_0 = -5.0000000000000e-01; + Q0_1 = 6.6042071945824e-01; + Q0_2 = -2.2104152954203e-01; + Q0_3 = 7.6243679810093e-02; + Q0_4 = -1.7298206716724e-02; + Q0_5 = 1.6753369904210e-03; + Q0_6 = 0.0000000000000e+00; + Q0_7 = 0.0000000000000e+00; + Q0_8 = 0.0000000000000e+00; + Q1_0 = -6.6042071945824e-01; + Q1_1 = 0.0000000000000e+00; + Q1_2 = 8.7352798702787e-01; + Q1_3 = -2.6581719253084e-01; + Q1_4 = 5.7458484948314e-02; + Q1_5 = -4.7485599871040e-03; + Q1_6 = 0.0000000000000e+00; + Q1_7 = 0.0000000000000e+00; + Q1_8 = 0.0000000000000e+00; + Q2_0 = 2.2104152954203e-01; + Q2_1 = -8.7352798702787e-01; + Q2_2 = 0.0000000000000e+00; + Q2_3 = 8.1707122038457e-01; + Q2_4 = -1.8881125503769e-01; + Q2_5 = 2.4226492138960e-02; + Q2_6 = 0.0000000000000e+00; + Q2_7 = 0.0000000000000e+00; + Q2_8 = 0.0000000000000e+00; + Q3_0 = -7.6243679810093e-02; + Q3_1 = 2.6581719253084e-01; + Q3_2 = -8.1707122038457e-01; + Q3_3 = 0.0000000000000e+00; + Q3_4 = 7.6798636652679e-01; + Q3_5 = -1.5715532552963e-01; + Q3_6 = 1.6666666666667e-02; + Q3_7 = 0.0000000000000e+00; + Q3_8 = 0.0000000000000e+00; + Q4_0 = 1.7298206716724e-02; + Q4_1 = -5.7458484948314e-02; + Q4_2 = 1.8881125503769e-01; + Q4_3 = -7.6798636652679e-01; + Q4_4 = 0.0000000000000e+00; + Q4_5 = 7.5266872305402e-01; + Q4_6 = -1.5000000000000e-01; + Q4_7 = 1.6666666666667e-02; + Q4_8 = 0.0000000000000e+00; + Q5_0 = -1.6753369904210e-03; + Q5_1 = 4.7485599871040e-03; + Q5_2 = -2.4226492138960e-02; + Q5_3 = 1.5715532552963e-01; + Q5_4 = -7.5266872305402e-01; + Q5_5 = 0.0000000000000e+00; + Q5_6 = 7.5000000000000e-01; + Q5_7 = -1.5000000000000e-01; + Q5_8 = 1.6666666666667e-02; + + for i = 1:BP + + for j = 1:BP + Q(i, j) = eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + Q(N + 1 - i, N + 1 - j) = -eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + end + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%% Undivided difference operators %%%% + % Closed with zeros at the first boundary nodes. + m = N; + + DD_3 = (-diag(ones(m - 2, 1), -2) + 3 * diag(ones(m - 1, 1), -1) - 3 * diag(ones(m, 1), 0) + diag(ones(m - 1, 1), 1)); + DD_3(1:5, 1:6) = [0 0 0 0 0 0; 0 0 0 0 0 0; -0.46757024540266021836e1 0.88373748766984018738e1 -0.56477423503490435435e1 0.14860699276772438533e1 0 0; 0 -0.13802450758054908946e1 0.36701915175801340778e1 -0.33643068661005748879e1 0.10743604243259317047e1 0; 0 0 -0.10409288946349185618e1 0.30665535320781497878e1 -0.30329117010471766032e1 0.10072870636039453772e1; ]; + DD_3(m - 3:m, m - 5:m) = [-0.10072870636039453772e1 0.30329117010471766032e1 -0.30665535320781497878e1 0.10409288946349185618e1 0 0; 0 -0.10743604243259317047e1 0.33643068661005748879e1 -0.36701915175801340778e1 0.13802450758054908946e1 0; 0 0 -0.14860699276772438533e1 0.56477423503490435435e1 -0.88373748766984018738e1 0.46757024540266021836e1; 0 0 0 0 0 0; ]; + DD_3 = sparse(DD_3); + + DD_4 = (diag(ones(m - 2, 1), 2) - 4 * diag(ones(m - 1, 1), 1) + 6 * diag(ones(m, 1), 0) - 4 * diag(ones(m - 1, 1), -1) + diag(ones(m - 2, 1), -2)); + DD_4(1:5, 1:7) = [0 0 0 0 0 0 0; 0 0 0 0 0 0 0; 0.57302111593550648941e1 -0.12521994384708052700e2 0.11419402572582197931e2 -0.59442797107089754133e1 0.13166603634797652881e1 0 0; 0 0.14441513881249918393e1 -0.49292485821432017638e1 0.67286137322011497757e1 -0.42974416973037268190e1 0.10539251591207869677e1 0; 0 0 0.10466075357769140419e1 -0.40887380427708663837e1 0.60658234020943532065e1 -0.40291482544157815088e1 0.10054553593153806442e1; ]; + DD_4(m - 4:m, m - 6:m) = [0.10054553593153806442e1 -0.40291482544157815088e1 0.60658234020943532065e1 -0.40887380427708663837e1 0.10466075357769140419e1 0 0; 0 0.10539251591207869677e1 -0.42974416973037268190e1 0.67286137322011497757e1 -0.49292485821432017638e1 0.14441513881249918393e1 0; 0 0 0.13166603634797652881e1 -0.59442797107089754133e1 0.11419402572582197931e2 -0.12521994384708052700e2 0.57302111593550648941e1; 0 0 0 0 0 0 0; 0 0 0 0 0 0 0; ]; + DD_4 = sparse(DD_4); + + DD_5 = (-diag(ones(m - 3, 1), -3) + 5 * diag(ones(m - 2, 1), -2) - 10 * diag(ones(m - 1, 1), -1) + 10 * diag(ones(m, 1), 0) - 5 * diag(ones(m - 1, 1), 1) + diag(ones(m - 2, 1), 2)); + DD_5(1:6, 1:8) = [0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0; -0.67194556014531368457e1 0.16377214352871472626e2 -0.19171027475746103125e2 0.14860699276772438533e2 -0.65833018173988264407e1 0.12358712649541552519e1 0 0; 0 -0.14971527633959360324e1 0.61951742553920293904e1 -0.11214356220335249626e2 0.10743604243259317047e2 -0.52696257956039348385e1 0.10423562806837740594e1 0; 0 0 -0.10511702536596915242e1 0.51109225534635829797e1 -0.10109705670157255344e2 0.10072870636039453772e2 -0.50272767965769032212e1 0.10043595308908133377e1; ]; + DD_5(m - 4:m, m - 7:m) = [-0.10043595308908133377e1 0.50272767965769032212e1 -0.10072870636039453772e2 0.10109705670157255344e2 -0.51109225534635829797e1 0.10511702536596915242e1 0 0; 0 -0.10423562806837740594e1 0.52696257956039348385e1 -0.10743604243259317047e2 0.11214356220335249626e2 -0.61951742553920293904e1 0.14971527633959360324e1 0; 0 0 -0.12358712649541552519e1 0.65833018173988264407e1 -0.14860699276772438533e2 0.19171027475746103125e2 -0.16377214352871472626e2 0.67194556014531368457e1; 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0; ]; + DD_5 = sparse(DD_5); + + DD_6 = (diag(ones(m - 3, 1), 3) - 6 * diag(ones(m - 2, 1), 2) + 15 * diag(ones(m - 1, 1), 1) - 20 * diag(ones(m, 1), 0) + 15 * diag(ones(m - 1, 1), -1) - 6 * diag(ones(m - 2, 1), -2) + diag(ones(m - 3, 1), -3)); + DD_6(1:6, 1:9) = [0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; 0.76591061528436941127e1 -0.20373923615000091397e2 0.28913418478606999359e2 -0.29721398553544877066e2 0.19749905452196479322e2 -0.74152275897249315116e1 0.11881196746227271813e1 0 0; 0 0.15426631885693469226e1 -0.74666187707188589528e1 0.16821534330502874439e2 -0.21487208486518634095e2 0.15808877386811804515e2 -0.62541376841026443562e1 0.10348900354561115264e1 0; 0 0 0.10549863219420430611e1 -0.61331070641562995756e1 0.15164558505235883016e2 -0.20145741272078907544e2 0.15081830389730709664e2 -0.60261571853448800265e1 0.10036303046714514054e1; ]; + DD_6(m - 5:m, m - 8:m) = [0.10036303046714514054e1 -0.60261571853448800265e1 0.15081830389730709664e2 -0.20145741272078907544e2 0.15164558505235883016e2 -0.61331070641562995756e1 0.10549863219420430611e1 0 0; 0 0.10348900354561115264e1 -0.62541376841026443562e1 0.15808877386811804515e2 -0.21487208486518634095e2 0.16821534330502874439e2 -0.74666187707188589528e1 0.15426631885693469226e1 0; 0 0 0.11881196746227271813e1 -0.74152275897249315116e1 0.19749905452196479322e2 -0.29721398553544877066e2 0.28913418478606999359e2 -0.20373923615000091397e2 0.76591061528436941127e1; 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; ]; + DD_6 = sparse(DD_6); + + %%%% Difference operators %%% + D1 = H \ Q; + + % Helper functions for constructing D2(c) + % TODO: Consider changing sparse(diag(...)) to spdiags(....) + + % Minimal 7 point stencil width + function D2 = D2_fun_minimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 1/3 * diag(ones(m - 1, 1), -1) + 1/3 * diag(ones(m - 1, 1), 1) + 1/3 * diag(ones(m, 1), 0); C3(1, 3) = 1/3; C3(m, m - 2) = 1/3; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + + % Remainder term added to wide second derivative operator + R = (1/3600 / h) * transpose(DD_6) * C1 * DD_6 + (1/600 / h) * transpose(DD_5) * C2 * DD_5 + (1/80 / h) * transpose(DD_4) * C3 * DD_4; + D2 = D1 * C1 * D1 - H \ R; + end + + % Few additional grid point in interior stencil cmp. to minimal + function D2 = D2_fun_nonminimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + + C2 = sparse(diag(C2 * c)); + + % Remainder term added to wide second derivative operator + R = (1/3600 / h) * transpose(DD_6) * C1 * DD_6 + (1/600 / h) * transpose(DD_5) * C2 * DD_5; + D2 = D1 * C1 * D1 - H \ R; + end + + % Wide stencil + function D2 = D2_fun_wide(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + D2 = D1 * C1 * D1; + end + + switch options.stencil_width + case 'minimal' + D2 = @D2_fun_minimal; + case 'nonminimal' + D2 = @D2_fun_nonminimal; + case 'wide' + D2 = @D2_fun_wide; + otherwise + error('No option %s for stencil width', options.stencil_width) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Artificial dissipation operator %%% + switch options.AD + case 'upwind' + % This is the choice that yield 3rd order Upwind + DI = H \ (transpose(DD_3) * DD_3) * (-1/60); + case 'op' + % This choice will preserve the order of the underlying + % Non-dissipative D1 SBP operator + DI = H \ (transpose(DD_4) * DD_4) * (-1 / (5 * 60)); + % Notice that you can use any negative number instead of (-1/(5*60)) + otherwise + error("Artificial dissipation options '%s' not implemented.", option.AD) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% +end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/+implementations/d2_noneq_variable_8.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,261 @@ +function [H, HI, D1, D2, DI] = d2_noneq_variable_8(N, h, options) + % N: Number of grid points + % h: grid spacing + % options: struct containing options for constructing the operator + % current options are: + % options.stencil_type ('minimal','nonminimal','wide') + % options.AD ('upwind', 'op') + + % BP: Number of boundary points + % order: Accuracy of interior stencil + BP = 8; + order = 8; + if(N<2*BP) + error(['Operator requires at least ' num2str(2*BP) ' grid points']); + end + + %%%% Norm matrix %%%%%%%% + P = zeros(BP, 1); + P0 = 1.0758368078310e-01; + P1 = 6.1909685107891e-01; + P2 = 9.6971176519117e-01; + P3 = 1.1023441350947e+00; + P4 = 1.0244688965833e+00; + P5 = 9.9533550116831e-01; + P6 = 1.0008236941028e+00; + P7 = 9.9992060631812e-01; + + for i = 0:BP - 1 + P(i + 1) = eval(['P' num2str(i)]); + end + + Hv = ones(N, 1); + Hv(1:BP) = P; + Hv(end - BP + 1:end) = flip(P); + Hv = h * Hv; + H = spdiags(Hv, 0, N, N); + HI = spdiags(1 ./ Hv, 0, N, N); + %%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Q matrix %%%%%%%%%%% + + % interior stencil + d = [1/280, -4/105, 1/5, -4/5, 0, 4/5, -1/5, 4/105, -1/280]; + d = repmat(d, N, 1); + Q = spdiags(d, -order / 2:order / 2, N, N); + + % Boundaries + Q0_0 = -5.0000000000000e-01; + Q0_1 = 6.7284756079369e-01; + Q0_2 = -2.5969732837062e-01; + Q0_3 = 1.3519390385721e-01; + Q0_4 = -6.9678474730984e-02; + Q0_5 = 2.6434024071371e-02; + Q0_6 = -5.5992311465618e-03; + Q0_7 = 4.9954552590464e-04; + Q0_8 = 0.0000000000000e+00; + Q0_9 = 0.0000000000000e+00; + Q0_10 = 0.0000000000000e+00; + Q0_11 = 0.0000000000000e+00; + Q1_0 = -6.7284756079369e-01; + Q1_1 = 0.0000000000000e+00; + Q1_2 = 9.4074021172233e-01; + Q1_3 = -4.0511642426516e-01; + Q1_4 = 1.9369192209331e-01; + Q1_5 = -6.8638079843479e-02; + Q1_6 = 1.3146457241484e-02; + Q1_7 = -9.7652615479254e-04; + Q1_8 = 0.0000000000000e+00; + Q1_9 = 0.0000000000000e+00; + Q1_10 = 0.0000000000000e+00; + Q1_11 = 0.0000000000000e+00; + Q2_0 = 2.5969732837062e-01; + Q2_1 = -9.4074021172233e-01; + Q2_2 = 0.0000000000000e+00; + Q2_3 = 9.4316393361096e-01; + Q2_4 = -3.5728039257451e-01; + Q2_5 = 1.1266686855013e-01; + Q2_6 = -1.8334941452280e-02; + Q2_7 = 8.2741521740941e-04; + Q2_8 = 0.0000000000000e+00; + Q2_9 = 0.0000000000000e+00; + Q2_10 = 0.0000000000000e+00; + Q2_11 = 0.0000000000000e+00; + Q3_0 = -1.3519390385721e-01; + Q3_1 = 4.0511642426516e-01; + Q3_2 = -9.4316393361096e-01; + Q3_3 = 0.0000000000000e+00; + Q3_4 = 8.7694387866575e-01; + Q3_5 = -2.4698058719506e-01; + Q3_6 = 4.7291642094198e-02; + Q3_7 = -4.0135203618880e-03; + Q3_8 = 0.0000000000000e+00; + Q3_9 = 0.0000000000000e+00; + Q3_10 = 0.0000000000000e+00; + Q3_11 = 0.0000000000000e+00; + Q4_0 = 6.9678474730984e-02; + Q4_1 = -1.9369192209331e-01; + Q4_2 = 3.5728039257451e-01; + Q4_3 = -8.7694387866575e-01; + Q4_4 = 0.0000000000000e+00; + Q4_5 = 8.1123946853807e-01; + Q4_6 = -2.0267150541446e-01; + Q4_7 = 3.8680398901392e-02; + Q4_8 = -3.5714285714286e-03; + Q4_9 = 0.0000000000000e+00; + Q4_10 = 0.0000000000000e+00; + Q4_11 = 0.0000000000000e+00; + Q5_0 = -2.6434024071371e-02; + Q5_1 = 6.8638079843479e-02; + Q5_2 = -1.1266686855013e-01; + Q5_3 = 2.4698058719506e-01; + Q5_4 = -8.1123946853807e-01; + Q5_5 = 0.0000000000000e+00; + Q5_6 = 8.0108544742793e-01; + Q5_7 = -2.0088756283071e-01; + Q5_8 = 3.8095238095238e-02; + Q5_9 = -3.5714285714286e-03; + Q5_10 = 0.0000000000000e+00; + Q5_11 = 0.0000000000000e+00; + Q6_0 = 5.5992311465618e-03; + Q6_1 = -1.3146457241484e-02; + Q6_2 = 1.8334941452280e-02; + Q6_3 = -4.7291642094198e-02; + Q6_4 = 2.0267150541446e-01; + Q6_5 = -8.0108544742793e-01; + Q6_6 = 0.0000000000000e+00; + Q6_7 = 8.0039405922650e-01; + Q6_8 = -2.0000000000000e-01; + Q6_9 = 3.8095238095238e-02; + Q6_10 = -3.5714285714286e-03; + Q6_11 = 0.0000000000000e+00; + Q7_0 = -4.9954552590464e-04; + Q7_1 = 9.7652615479254e-04; + Q7_2 = -8.2741521740941e-04; + Q7_3 = 4.0135203618880e-03; + Q7_4 = -3.8680398901392e-02; + Q7_5 = 2.0088756283071e-01; + Q7_6 = -8.0039405922650e-01; + Q7_7 = 0.0000000000000e+00; + Q7_8 = 8.0000000000000e-01; + Q7_9 = -2.0000000000000e-01; + Q7_10 = 3.8095238095238e-02; + Q7_11 = -3.5714285714286e-03; + + for i = 1:BP + + for j = 1:BP + Q(i, j) = eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + Q(N + 1 - i, N + 1 - j) = -eval(['Q' num2str(i - 1) '_' num2str(j - 1)]); + end + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%% Undivided difference operators %%%% + % Closed with zeros at the first boundary nodes. + m = N; + + DD_4 = (diag(ones(m - 2, 1), 2) - 4 * diag(ones(m - 1, 1), 1) + 6 * diag(ones(m, 1), 0) - 4 * diag(ones(m - 1, 1), -1) + diag(ones(m - 2, 1), -2)); + DD_4(1:6, 1:8) = [0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0; 0.70921010190504348684e1 -0.14196080536361841322e2 0.11072881931325435634e2 -0.50473576941871051066e1 0.10784552801730759259e1 0 0 0; 0 0.13740993382151221352e1 -0.42105600869792757010e1 0.54761010136211975317e1 -0.35797005751940657417e1 0.94006031033702177578e0 0 0; 0 0 0.82467928104463767301e0 -0.33274694995849432461e1 0.52587584638857303123e1 -0.37020511582893568152e1 0.94608291294393207601e0 0; 0 0 0 0.86436129166612654748e0 -0.37325441295306179390e1 0.57924699560798105338e1 -0.39066885960487908497e1 0.98240147783347170744e0; ]; + DD_4(m - 5:m, m - 7:m) = [0.98240147783347170744e0 -0.39066885960487908497e1 0.57924699560798105338e1 -0.37325441295306179390e1 0.86436129166612654748e0 0 0 0; 0 0.94608291294393207601e0 -0.37020511582893568152e1 0.52587584638857303123e1 -0.33274694995849432461e1 0.82467928104463767301e0 0 0; 0 0 0.94006031033702177578e0 -0.35797005751940657417e1 0.54761010136211975317e1 -0.42105600869792757010e1 0.13740993382151221352e1 0; 0 0 0 0.10784552801730759259e1 -0.50473576941871051066e1 0.11072881931325435634e2 -0.14196080536361841322e2 0.70921010190504348684e1; 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0; ]; + DD_4 = sparse(DD_4); + + DD_5 = (-diag(ones(m - 3, 1), -3) + 5 * diag(ones(m - 2, 1), -2) - 10 * diag(ones(m - 1, 1), -1) + 10 * diag(ones(m, 1), 0) - 5 * diag(ones(m - 1, 1), 1) + diag(ones(m - 2, 1), 2)); + DD_5(1:7, 1:9) = [0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; -0.82098088052411907132e1 0.18024024120655590699e2 -0.17692096674769448317e2 0.12181944917152947702e2 -0.53922764008653796295e1 0.10882128430674802600e1 0 0 0; 0 -0.13913240333052950751e1 0.50983574122643719988e1 -0.89139255753021486176e1 0.89492514379851643542e1 -0.47003015516851088789e1 0.95794231004301621873e0 0 0; 0 0 -0.80388595981635823711e0 0.40861386922975635215e1 -0.87645974398095505205e1 0.92551278957233920380e1 -0.47304145647196603800e1 0.95763137632461357808e0 0; 0 0 0 -0.85214912336218661144e0 0.46656801619132724238e1 -0.96541165934663508896e1 0.97667214901219771242e1 -0.49120073891673585372e1 0.98587145396064649030e0; ]; + DD_5(m - 5:m, m - 8:m) = [-0.98587145396064649030e0 0.49120073891673585372e1 -0.97667214901219771242e1 0.96541165934663508896e1 -0.46656801619132724238e1 0.85214912336218661144e0 0 0 0; 0 -0.95763137632461357808e0 0.47304145647196603800e1 -0.92551278957233920380e1 0.87645974398095505205e1 -0.40861386922975635215e1 0.80388595981635823711e0 0 0; 0 0 -0.95794231004301621873e0 0.47003015516851088789e1 -0.89492514379851643542e1 0.89139255753021486176e1 -0.50983574122643719988e1 0.13913240333052950751e1 0; 0 0 0 -0.10882128430674802600e1 0.53922764008653796295e1 -0.12181944917152947702e2 0.17692096674769448317e2 -0.18024024120655590699e2 0.82098088052411907132e1; 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0; ]; + DD_5 = sparse(DD_5); + + DD_6 = (diag(ones(m - 3, 1), 3) - 6 * diag(ones(m - 2, 1), 2) + 15 * diag(ones(m - 1, 1), 1) - 20 * diag(ones(m, 1), 0) + 15 * diag(ones(m - 1, 1), -1) - 6 * diag(ones(m - 2, 1), -2) + diag(ones(m - 3, 1), -3)); + DD_6(1:7, 1:10) = [0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; 0.92604272237009487731e1 -0.21899951980342041757e2 0.25706973995952182034e2 -0.23795532642767976509e2 0.16176829202596138889e2 -0.65292770584048815597e1 0.10805312592656301300e1 0 0 0; 0 0.14058275749850312569e1 -0.59637699688344396810e1 0.13135580487711615439e2 -0.17898502875970328708e2 0.14100904655055326637e2 -0.57476538602580973124e1 0.96761398731089236944e0 0 0; 0 0 0.78692381135906040550e0 -0.48340889923923043812e1 0.13146896159714325781e2 -0.18510255791446784076e2 0.14191243694158981140e2 -0.57457882579476814685e1 0.96506937655440259938e0 0; 0 0 0 0.84209241882516286974e0 -0.55988161942959269085e1 0.14481174890199526334e2 -0.19533442980243954248e2 0.14736022167502075612e2 -0.59152287237638789418e1 0.98819842177699528293e0; ]; + DD_6(m - 6:m, m - 9:m) = [0.98819842177699528293e0 -0.59152287237638789418e1 0.14736022167502075612e2 -0.19533442980243954248e2 0.14481174890199526334e2 -0.55988161942959269085e1 0.84209241882516286974e0 0 0 0; 0 0.96506937655440259938e0 -0.57457882579476814685e1 0.14191243694158981140e2 -0.18510255791446784076e2 0.13146896159714325781e2 -0.48340889923923043812e1 0.78692381135906040550e0 0 0; 0 0 0.96761398731089236944e0 -0.57476538602580973124e1 0.14100904655055326637e2 -0.17898502875970328708e2 0.13135580487711615439e2 -0.59637699688344396810e1 0.14058275749850312569e1 0; 0 0 0 0.10805312592656301300e1 -0.65292770584048815597e1 0.16176829202596138889e2 -0.23795532642767976509e2 0.25706973995952182034e2 -0.21899951980342041757e2 0.92604272237009487731e1; 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0; ]; + DD_6 = sparse(DD_6); + + DD_7 = (-diag(ones(m - 4, 1), -4) + 7 * diag(ones(m - 3, 1), -3) - 21 * diag(ones(m - 2, 1), -2) + 35 * diag(ones(m - 1, 1), -1) - 35 * diag(ones(m, 1), 0) + 21 * diag(ones(m - 1, 1), 1) - 7 * diag(ones(m - 2, 1), 2) + diag(ones(m - 3, 1), 3)); + DD_7(1:8, 1:11) = [0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; -0.10257962606384161889e2 0.25816283570514673553e2 -0.35082323899232605336e2 0.40909341259657284245e2 -0.37745934806057657407e2 0.22852469704417085459e2 -0.75637188148594109098e1 0.10718455919447922848e1 0 0 0; 0 -0.14183700945143243060e1 0.68109221539151178574e1 -0.18129991367652287552e2 0.31322380032948075240e2 -0.32902110861795762152e2 0.20116788510903340593e2 -0.67732979111762465861e1 0.97367953737208690559e0 0 0; 0 0 -0.77264857229409862775e0 0.55732122985135573041e1 -0.18405654623600056093e2 0.32392947635031872133e2 -0.33112901953037622660e2 0.20110258902816885140e2 -0.67554856358808181957e1 0.97027194845028099974e0 0; 0 0 0 -0.83355973075426177031e0 0.65319522266785813933e1 -0.20273644846279336868e2 0.34183525215426919935e2 -0.34384051724171509761e2 0.20703300533173576296e2 -0.69173889524389669805e1 0.98986727836499775519e0; ]; + DD_7(m - 6:m, m - 10:m) = [-0.98986727836499775519e0 0.69173889524389669805e1 -0.20703300533173576296e2 0.34384051724171509761e2 -0.34183525215426919935e2 0.20273644846279336868e2 -0.65319522266785813933e1 0.83355973075426177031e0 0 0 0; 0 -0.97027194845028099974e0 0.67554856358808181957e1 -0.20110258902816885140e2 0.33112901953037622660e2 -0.32392947635031872133e2 0.18405654623600056093e2 -0.55732122985135573041e1 0.77264857229409862775e0 0 0; 0 0 -0.97367953737208690559e0 0.67732979111762465861e1 -0.20116788510903340593e2 0.32902110861795762152e2 -0.31322380032948075240e2 0.18129991367652287552e2 -0.68109221539151178574e1 0.14183700945143243060e1 0; 0 0 0 -0.10718455919447922848e1 0.75637188148594109098e1 -0.22852469704417085459e2 0.37745934806057657407e2 -0.40909341259657284245e2 0.35082323899232605336e2 -0.25816283570514673553e2 0.10257962606384161889e2; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_7 = sparse(DD_7); + + DD_8 = (diag(ones(m - 4, 1), 4) - 8 * diag(ones(m - 3, 1), 3) + 28 * diag(ones(m - 2, 1), 2) - 56 * diag(ones(m - 1, 1), 1) + 70 * diag(ones(m, 1), 0) - 56 * diag(ones(m - 1, 1), -1) + 28 * diag(ones(m - 2, 1), -2) - 8 * diag(ones(m - 3, 1), -3) + diag(ones(m - 4, 1), -4)); + DD_8(1:8, 1:12) = [0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0.11211983054345146839e2 -0.29767555907566203748e2 0.45789440151310044599e2 -0.64530162797168947524e2 0.75491869612115314813e2 -0.60939919211778894557e2 0.30254875259437643639e2 -0.85747647355583382784e1 0.10642345748642342173e1 0 0 0; 0 0.14294303785648149613e1 -0.76427065234692260122e1 0.23888038475126051744e2 -0.50115808052716920383e2 0.65804221723591524304e2 -0.53644769362408908249e2 0.27093191644704986344e2 -0.77894362989766952447e1 0.97783801558437253538e0 0 0; 0 0 0.76035645561041265933e0 -0.63048462739199410204e1 0.24540872831466741457e2 -0.51828716216050995413e2 0.66225803906075245320e2 -0.53627357074178360373e2 0.27021942543523272783e2 -0.77621755876022479980e1 0.97411941507587258409e0 0; 0 0 0 0.82615990808320718845e0 -0.74650882590612358780e1 0.27031526461705782491e2 -0.54693640344683071895e2 0.68768103448343019521e2 -0.55208801421796203457e2 0.27669555809755867922e2 -0.79189382269199820415e1 0.99112262457261614959e0; ]; + DD_8(m - 7:m, m - 11:m) = [0.99112262457261614959e0 -0.79189382269199820415e1 0.27669555809755867922e2 -0.55208801421796203457e2 0.68768103448343019521e2 -0.54693640344683071895e2 0.27031526461705782491e2 -0.74650882590612358780e1 0.82615990808320718845e0 0 0 0; 0 0.97411941507587258409e0 -0.77621755876022479980e1 0.27021942543523272783e2 -0.53627357074178360373e2 0.66225803906075245320e2 -0.51828716216050995413e2 0.24540872831466741457e2 -0.63048462739199410204e1 0.76035645561041265933e0 0 0; 0 0 0.97783801558437253538e0 -0.77894362989766952447e1 0.27093191644704986344e2 -0.53644769362408908249e2 0.65804221723591524304e2 -0.50115808052716920383e2 0.23888038475126051744e2 -0.76427065234692260122e1 0.14294303785648149613e1 0; 0 0 0 0.10642345748642342173e1 -0.85747647355583382784e1 0.30254875259437643639e2 -0.60939919211778894557e2 0.75491869612115314813e2 -0.64530162797168947524e2 0.45789440151310044599e2 -0.29767555907566203748e2 0.11211983054345146839e2; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 0 0 0 0 0; ]; + DD_8 = sparse(DD_8); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Difference operators %% + D1 = H \ Q; + + % Helper functions for constructing D2(c) + % TODO: Consider changing sparse(diag(...)) to spdiags(....) + + % Minimal 9 point stencil width + function D2 = D2_fun_minimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 3/10 * diag(ones(m - 1, 1), -1) + 3/10 * diag(ones(m - 1, 1), 1) + 2/5 * diag(ones(m, 1), 0); C3(1, 3) = 3/10; C3(m, m - 2) = 3/10; + C4 = 1/4 * diag(ones(m - 2, 1), -2) + 1/4 * diag(ones(m - 1, 1), -1) + 1/4 * diag(ones(m - 1, 1), 1) + 1/4 * diag(ones(m, 1), 0); C4(2, 4) = 1/4; C4(1, 3) = 1/4; C4(1, 4) = 1/4; C4(m, m - 2) = 1/4; C4(m, m - 3) = 1/4; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + C4 = sparse(diag(C4 * c)); + + % Remainder term added to wide second derivative operator + R = (1/78400 / h) * transpose(DD_8) * C1 * DD_8 + (1/14700 / h) * transpose(DD_7) * C2 * DD_7 + (1/2520 / h) * transpose(DD_6) * C3 * DD_6 + (1/350 / h) * transpose(DD_5) * C4 * DD_5; + + D2 = D1 * C1 * D1 - H \ R; + end + + % Few additional grid point in interior stencil cmp. to minimal + function D2 = D2_fun_nonminimal(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + C2 = 1/2 * diag(ones(m - 1, 1), -1) + 1/2 * diag(ones(m, 1), 0); C2(1, 2) = 1/2; + C3 = 3/10 * diag(ones(m - 1, 1), -1) + 3/10 * diag(ones(m - 1, 1), 1) + 2/5 * diag(ones(m, 1), 0); C3(1, 3) = 3/10; C3(m, m - 2) = 3/10; + + C2 = sparse(diag(C2 * c)); + C3 = sparse(diag(C3 * c)); + + % Remainder term added to wide second derivative operator + R = (1/78400 / h) * transpose(DD_8) * C1 * DD_8 + (1/14700 / h) * transpose(DD_7) * C2 * DD_7 + (1/2520 / h) * transpose(DD_6) * C3 * DD_6; + D2 = D1 * C1 * D1 - H \ R; + end + + % Wide stencil + function D2 = D2_fun_wide(c) + % Here we add variable diffusion + C1 = sparse(diag(c)); + D2 = D1 * C1 * D1; + end + + switch options.stencil_width + case 'minimal' + D2 = @D2_fun_minimal; + case 'nonminimal' + D2 = @D2_fun_nonminimal; + case 'wide' + D2 = @D2_fun_wide; + otherwise + error('No option %s for stencil width', options.stencil_width) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%% Artificial dissipation operator %%% + switch options.AD + case 'upwind' + % This is the choice that yield 7th order Upwind + DI = H \ (transpose(DD_4) * DD_4) * (-1/280); + case 'op' + % This choice will preserve the order of the underlying + % Non-dissipative D1 SBP operator + DI = H \ (transpose(DD_5) * DD_5) * (-1 / (5 * 280)); + % Notice that you can use any negative number instead of (-1/(5*280)) + otherwise + error("Artificial dissipation options '%s' not implemented.", option.AD) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%% +end \ No newline at end of file
--- a/+sbp/D1Nonequidistant.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/D1Nonequidistant.m Thu Mar 10 16:54:26 2022 +0100 @@ -19,58 +19,53 @@ % 'Accurate' operators are optimized for accuracy % 'Minimal' operators have the smallest possible boundary % closure - - x_l = lim{1}; - x_r = lim{2}; - L = x_r-x_l; - switch option case {'Accurate','accurate','A'} - + [x,h] = sbp.grid.accurateBoundaryOptimizedGrid(lim,m,order); if order == 4 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_4(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_4(m,h); elseif order == 6 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_6(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_6(m,h); elseif order == 8 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_8(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_8(m,h); elseif order == 10 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_10(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_10(m,h); elseif order == 12 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_12(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_12(m,h); else error('Invalid operator order %d.',order); end case {'Minimal','minimal','M'} - + [x,h] = sbp.grid.minimalBoundaryOptimizedGrid(lim,m,order); if order == 4 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_minimal_4(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_minimal_4(m,h); elseif order == 6 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_minimal_6(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_minimal_6(m,h); elseif order == 8 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_minimal_8(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_minimal_8(m,h); elseif order == 10 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_minimal_10(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_minimal_10(m,h); elseif order == 12 - [obj.D1,obj.H,obj.x,obj.h] = ... - sbp.implementations.d1_noneq_minimal_12(m,L); + [obj.D1,obj.H] = ... + sbp.implementations.d1_noneq_minimal_12(m,h); else error('Invalid operator order %d.',order); end end - - obj.x = obj.x + x_l; + obj.h = h; + obj.x = x; obj.e_l = sparse(m,1); obj.e_r = sparse(m,1);
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/+sbp/D2Nonequidistant.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,93 @@ +classdef D2Nonequidistant < sbp.OpSet + % Implements the boundary optimized variable coefficient + % second derivative. + % + % The boundary closure uses the first and last rows of the + % boundary-optimized D1 operator, i.e. the operators are + % fully compatible. + properties + H % Norm matrix + HI % H^-1 + D1 % SBP operator approximating first derivative + D2 % SBP operator approximating second derivative + DI % Dissipation operator + e_l % Left boundary operator + e_r % Right boundary operator + d1_l % Left boundary first derivative + d1_r % Right boundary first derivative + m % Number of grid points. + h % Step size + x % grid + borrowing % Struct with borrowing limits for different norm matrices + options % Struct holding options used to create the operator + end + + methods + + function obj = D2Nonequidistant(m, lim, order, options) + % m - number of gridpoints + % lim - cell array holding the limits of the domain + % order - order of the operator + % options - struct holding options used to construct the operator + % struct.stencil_width: {'minimal', 'nonminimal', 'wide'} + % minimal: minimal compatible stencil width (default) + % nonminimal: a few additional stencil points compared to minimal + % wide: wide stencil obtained by applying D1 twice + % struct.AD: {'op', 'upwind'} + % 'op': order-preserving AD (preserving interior stencil order) (default) + % 'upwind': upwind AD (order-1 upwind interior stencil) + % struct.variable_coeffs: {true, false} + % true: obj.D2 is a function handle D2(c) returning a matrix + % for coefficient vector c (default) + % false: obj.D2 is a matrix. + default_arg('options', struct); + default_field(options,'stencil_width','minimal'); + default_field(options,'AD','op'); + default_field(options,'variable_coeffs',true); + [x, h] = sbp.grid.accurateBoundaryOptimizedGrid(lim, m, order); + switch order + case 4 + [obj.H, obj.HI, obj.D1, obj.D2, obj.DI] = sbp.implementations.d2_noneq_variable_4(m, h, options); + case 6 + [obj.H, obj.HI, obj.D1, obj.D2, obj.DI] = sbp.implementations.d2_noneq_variable_6(m, h, options); + case 8 + [obj.H, obj.HI, obj.D1, obj.D2, obj.DI] = sbp.implementations.d2_noneq_variable_8(m, h, options); + case 10 + [obj.H, obj.HI, obj.D1, obj.D2, obj.DI] = sbp.implementations.d2_noneq_variable_10(m, h, options); + case 12 + [obj.H, obj.HI, obj.D1, obj.D2, obj.DI] = sbp.implementations.d2_noneq_variable_12(m, h, options); + otherwise + error('Invalid operator order %d.', order); + end + + if ~options.variable_coeffs + obj.D2 = obj.D2(ones(m,1)); + end + + % Boundary operators + obj.e_l = sparse(m, 1); obj.e_l(1) = 1; + obj.e_r = sparse(m, 1); obj.e_r(m) = 1; + obj.d1_l = (obj.e_l' * obj.D1)'; + obj.d1_r = (obj.e_r' * obj.D1)'; + + % Borrowing coefficients + obj.borrowing.H11 = obj.H(1, 1) / h; % First element in H/h, + obj.borrowing.M.d1 = obj.H(1, 1) / h; % First element in H/h is borrowing also for M + obj.borrowing.R.delta_D = inf; + + % grid data + obj.x = x; + obj.h = h; + obj.m = m; + + % misc + obj.options = options; + end + + function str = string(obj) + str = [class(obj) '_' num2str(obj.order)]; + end + + end + +end
--- a/+sbp/D2VariableCompatible.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+sbp/D2VariableCompatible.m Thu Mar 10 16:54:26 2022 +0100 @@ -59,8 +59,10 @@ % D2 = Hinv * (-M + br*er*d1r^T - bl*el*d1l^T); % Replace d1' by e'*D1 in D2. - D2_compatible = @(b) D2(b) - obj.HI*(b(m)*e_r*d1_r' - b(m)*e_r*e_r'*D1) ... - + obj.HI*(b(1)*e_l*d1_l' - b(1)*e_l*e_l'*D1); + correction_l = obj.HI*(e_l*d1_l' - e_l*e_l'*D1); + correction_r = - obj.HI*(e_r*d1_r' - e_r*e_r'*D1); + + D2_compatible = @(b) D2(b) + b(1)*correction_l + b(m)*correction_r; obj.D2 = D2_compatible; obj.d1_l = (e_l'*D1)';
--- a/+scheme/Beam.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Beam.m Thu Mar 10 16:54:26 2022 +0100 @@ -86,7 +86,11 @@ function [closure, penalty] = boundary_condition(obj,boundary,type) default_arg('type','dn'); - [e, d1, d2, d3, s] = obj.get_boundary_ops(boundary); + e = obj.getBoundaryOperator('e', boundary); + d1 = obj.getBoundaryOperator('d1', boundary); + d2 = obj.getBoundaryOperator('d2', boundary); + d3 = obj.getBoundaryOperator('d3', boundary); + s = obj.getBoundarySign(boundary); gamm = obj.gamm; delt = obj.delt; @@ -124,7 +128,7 @@ closure = obj.Hi*(tau*d2' + sig*d3'); penalty{1} = -obj.Hi*tau; - penalty{1} = -obj.Hi*sig; + penalty{2} = -obj.Hi*sig; case 'e' alpha = obj.alpha; @@ -173,14 +177,21 @@ function [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary, type) % u denotes the solution in the own domain % v denotes the solution in the neighbour domain - [e_u,d1_u,d2_u,d3_u,s_u] = obj.get_boundary_ops(boundary); - [e_v,d1_v,d2_v,d3_v,s_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); + e_u = obj.getBoundaryOperator('e', boundary); + d1_u = obj.getBoundaryOperator('d1', boundary); + d2_u = obj.getBoundaryOperator('d2', boundary); + d3_u = obj.getBoundaryOperator('d3', boundary); + s_u = obj.getBoundarySign(boundary); + e_v = neighbour_scheme.getBoundaryOperator('e', neighbour_boundary); + d1_v = neighbour_scheme.getBoundaryOperator('d1', neighbour_boundary); + d2_v = neighbour_scheme.getBoundaryOperator('d2', neighbour_boundary); + d3_v = neighbour_scheme.getBoundaryOperator('d3', neighbour_boundary); + s_v = neighbour_scheme.getBoundarySign(neighbour_boundary); alpha_u = obj.alpha; alpha_v = neighbour_scheme.alpha; - switch boundary case 'l' interface_opt = obj.opt.interface_l; @@ -234,24 +245,37 @@ penalty = -obj.Hi*(tau*e_v' + sig*d1_v' + phi*alpha_v*d2_v' + psi*alpha_v*d3_v'); end - % Returns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e, d1, d2, d3, s] = get_boundary_ops(obj,boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string + % boundary -- string + function o = getBoundaryOperator(obj, op, boundary) + assertIsMember(op, {'e', 'd1', 'd2', 'd3'}) + assertIsMember(boundary, {'l', 'r'}) + + o = obj.([op, '_', boundary]); + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + % Note: for 1d diffOps, the boundary quadrature is the scalar 1. + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + + H_b = 1; + end + + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + switch boundary - case 'l' - e = obj.e_l; - d1 = obj.d1_l; - d2 = obj.d2_l; - d3 = obj.d3_l; + case {'r'} + s = 1; + case {'l'} s = -1; - case 'r' - e = obj.e_r; - d1 = obj.d1_r; - d2 = obj.d2_r; - d3 = obj.d3_r; - s = 1; - otherwise - error('No such boundary: boundary = %s',boundary); end end
--- a/+scheme/Beam2d.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,245 +0,0 @@ -classdef Beam2d < scheme.Scheme - properties - grid - order % Order accuracy for the approximation - - D % non-stabalized scheme operator - M % Derivative norm - alpha - - H % Discrete norm - Hi - H_x, H_y % Norms in the x and y directions - Hx,Hy % Kroneckerd norms. 1'*Hx*v corresponds to integration in the x dir. - Hi_x, Hi_y - Hix, Hiy - e_w, e_e, e_s, e_n - d1_w, d1_e, d1_s, d1_n - d2_w, d2_e, d2_s, d2_n - d3_w, d3_e, d3_s, d3_n - gamm_x, gamm_y - delt_x, delt_y - end - - methods - function obj = Beam2d(m,lim,order,alpha,opsGen) - default_arg('alpha',1); - default_arg('opsGen',@sbp.Higher); - - if ~isa(grid, 'grid.Cartesian') || grid.D() ~= 2 - error('Grid must be 2d cartesian'); - end - - obj.grid = grid; - obj.alpha = alpha; - obj.order = order; - - m_x = grid.m(1); - m_y = grid.m(2); - - h = grid.scaling(); - h_x = h(1); - h_y = h(2); - - ops_x = opsGen(m_x,h_x,order); - ops_y = opsGen(m_y,h_y,order); - - I_x = speye(m_x); - I_y = speye(m_y); - - D4_x = sparse(ops_x.derivatives.D4); - H_x = sparse(ops_x.norms.H); - Hi_x = sparse(ops_x.norms.HI); - e_l_x = sparse(ops_x.boundary.e_1); - e_r_x = sparse(ops_x.boundary.e_m); - d1_l_x = sparse(ops_x.boundary.S_1); - d1_r_x = sparse(ops_x.boundary.S_m); - d2_l_x = sparse(ops_x.boundary.S2_1); - d2_r_x = sparse(ops_x.boundary.S2_m); - d3_l_x = sparse(ops_x.boundary.S3_1); - d3_r_x = sparse(ops_x.boundary.S3_m); - - D4_y = sparse(ops_y.derivatives.D4); - H_y = sparse(ops_y.norms.H); - Hi_y = sparse(ops_y.norms.HI); - e_l_y = sparse(ops_y.boundary.e_1); - e_r_y = sparse(ops_y.boundary.e_m); - d1_l_y = sparse(ops_y.boundary.S_1); - d1_r_y = sparse(ops_y.boundary.S_m); - d2_l_y = sparse(ops_y.boundary.S2_1); - d2_r_y = sparse(ops_y.boundary.S2_m); - d3_l_y = sparse(ops_y.boundary.S3_1); - d3_r_y = sparse(ops_y.boundary.S3_m); - - - D4 = kr(D4_x, I_y) + kr(I_x, D4_y); - - % Norms - obj.H = kr(H_x,H_y); - obj.Hx = kr(H_x,I_x); - obj.Hy = kr(I_x,H_y); - obj.Hix = kr(Hi_x,I_y); - obj.Hiy = kr(I_x,Hi_y); - obj.Hi = kr(Hi_x,Hi_y); - - % Boundary operators - obj.e_w = kr(e_l_x,I_y); - obj.e_e = kr(e_r_x,I_y); - obj.e_s = kr(I_x,e_l_y); - obj.e_n = kr(I_x,e_r_y); - obj.d1_w = kr(d1_l_x,I_y); - obj.d1_e = kr(d1_r_x,I_y); - obj.d1_s = kr(I_x,d1_l_y); - obj.d1_n = kr(I_x,d1_r_y); - obj.d2_w = kr(d2_l_x,I_y); - obj.d2_e = kr(d2_r_x,I_y); - obj.d2_s = kr(I_x,d2_l_y); - obj.d2_n = kr(I_x,d2_r_y); - obj.d3_w = kr(d3_l_x,I_y); - obj.d3_e = kr(d3_r_x,I_y); - obj.d3_s = kr(I_x,d3_l_y); - obj.d3_n = kr(I_x,d3_r_y); - - obj.D = alpha*D4; - - obj.gamm_x = h_x*ops_x.borrowing.N.S2/2; - obj.delt_x = h_x^3*ops_x.borrowing.N.S3/2; - - obj.gamm_y = h_y*ops_y.borrowing.N.S2/2; - obj.delt_y = h_y^3*ops_y.borrowing.N.S3/2; - end - - - % Closure functions return the opertors applied to the own doamin to close the boundary - % Penalty functions return the opertors 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'. - % type is a string specifying the type of boundary condition if there are several. - % 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. - function [closure, penalty_e,penalty_d] = boundary_condition(obj,boundary,type,data) - default_arg('type','dn'); - default_arg('data',0); - - [e,d1,d2,d3,s,gamm,delt,halfnorm_inv] = obj.get_boundary_ops(boundary); - - switch type - % Dirichlet-neumann boundary condition - case {'dn'} - alpha = obj.alpha; - - % tau1 < -alpha^2/gamma - tuning = 1.1; - - tau1 = tuning * alpha/delt; - tau4 = s*alpha; - - sig2 = tuning * alpha/gamm; - sig3 = -s*alpha; - - tau = tau1*e+tau4*d3; - sig = sig2*d1+sig3*d2; - - closure = halfnorm_inv*(tau*e' + sig*d1'); - - pp_e = halfnorm_inv*tau; - pp_d = halfnorm_inv*sig; - switch class(data) - case 'double' - penalty_e = pp_e*data; - penalty_d = pp_d*data; - case 'function_handle' - penalty_e = @(t)pp_e*data(t); - penalty_d = @(t)pp_d*data(t); - otherwise - error('Wierd data argument!') - end - - % Unknown, boundary condition - otherwise - error('No such boundary condition: type = %s',type); - end - end - - function [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary, type) - % u denotes the solution in the own domain - % v denotes the solution in the neighbour domain - [e_u,d1_u,d2_u,d3_u,s_u,gamm_u,delt_u, halfnorm_inv] = obj.get_boundary_ops(boundary); - [e_v,d1_v,d2_v,d3_v,s_v,gamm_v,delt_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); - - tuning = 2; - - alpha_u = obj.alpha; - alpha_v = neighbour_scheme.alpha; - - tau1 = ((alpha_u/2)/delt_u + (alpha_v/2)/delt_v)/2*tuning; - % tau1 = (alpha_u/2 + alpha_v/2)/(2*delt_u)*tuning; - tau4 = s_u*alpha_u/2; - - sig2 = ((alpha_u/2)/gamm_u + (alpha_v/2)/gamm_v)/2*tuning; - sig3 = -s_u*alpha_u/2; - - phi2 = s_u*1/2; - - psi1 = -s_u*1/2; - - tau = tau1*e_u + tau4*d3_u; - sig = sig2*d1_u + sig3*d2_u ; - phi = phi2*d1_u ; - psi = psi1*e_u ; - - closure = halfnorm_inv*(tau*e_u' + sig*d1_u' + phi*alpha_u*d2_u' + psi*alpha_u*d3_u'); - penalty = -halfnorm_inv*(tau*e_v' + sig*d1_v' + phi*alpha_v*d2_v' + psi*alpha_v*d3_v'); - end - - % Ruturns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e,d1,d2,d3,s,gamm, delt, halfnorm_inv] = get_boundary_ops(obj,boundary) - switch boundary - case 'w' - e = obj.e_w; - d1 = obj.d1_w; - d2 = obj.d2_w; - d3 = obj.d3_w; - s = -1; - gamm = obj.gamm_x; - delt = obj.delt_x; - halfnorm_inv = obj.Hix; - case 'e' - e = obj.e_e; - d1 = obj.d1_e; - d2 = obj.d2_e; - d3 = obj.d3_e; - s = 1; - gamm = obj.gamm_x; - delt = obj.delt_x; - halfnorm_inv = obj.Hix; - case 's' - e = obj.e_s; - d1 = obj.d1_s; - d2 = obj.d2_s; - d3 = obj.d3_s; - s = -1; - gamm = obj.gamm_y; - delt = obj.delt_y; - halfnorm_inv = obj.Hiy; - case 'n' - e = obj.e_n; - d1 = obj.d1_n; - d2 = obj.d2_n; - d3 = obj.d3_n; - s = 1; - gamm = obj.gamm_y; - delt = obj.delt_y; - halfnorm_inv = obj.Hiy; - otherwise - error('No such boundary: boundary = %s',boundary); - end - end - - function N = size(obj) - N = prod(obj.m); - end - - end -end
--- a/+scheme/Elastic2dCurvilinear.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Elastic2dCurvilinear.m Thu Mar 10 16:54:26 2022 +0100 @@ -387,7 +387,7 @@ % j is the coordinate direction of the boundary j = obj.get_boundary_number(boundary); - [e, T, tau, H_gamma] = obj.get_boundary_operator({'e','T','tau','H'}, boundary); + [e, T, tau, H_gamma] = obj.getBoundaryOperator({'e','T','tau','H'}, boundary); E = obj.E; Hi = obj.Hi; @@ -457,8 +457,8 @@ j_v = neighbour_scheme.get_boundary_number(neighbour_boundary); % Get boundary operators - [e, T, tau, H_gamma] = obj.get_boundary_operator({'e','T','tau','H'}, boundary); - [e_v, tau_v] = neighbour_scheme.get_boundary_operator({'e','tau'}, neighbour_boundary); + [e, T, tau, H_gamma] = obj.getBoundaryOperator({'e','T','tau','H'}, boundary); + [e_v, tau_v] = neighbour_scheme.getBoundaryOperator({'e','tau'}, neighbour_boundary); % Operators and quantities that correspond to the own domain only Hi = obj.Hi; @@ -555,7 +555,7 @@ % Returns the boundary operator op for the boundary specified by the string boundary. % op: may be a cell array of strings - function [varargout] = get_boundary_operator(obj, op, boundary) + function [varargout] = getBoundaryOperator(obj, op, boundary) switch boundary case {'w','W','west','West', 'e', 'E', 'east', 'East'} @@ -614,6 +614,27 @@ end + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'w'} + H = H_boundary_l{1}; + case 'e' + H = H_boundary_r{1}; + case 's' + H = H_boundary_l{2}; + case 'n' + H = H_boundary_r{2}; + end + I_dim = speye(obj.dim, obj.dim); + H = kron(H, I_dim); + end + function N = size(obj) N = obj.dim*prod(obj.m); end
--- a/+scheme/Euler1d.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Euler1d.m Thu Mar 10 16:54:26 2022 +0100 @@ -201,7 +201,8 @@ % Enforces the boundary conditions % w+ = R*w- + g(t) function closure = boundary_condition(obj,boundary, type, varargin) - [e_s,e_S,s] = obj.get_boundary_ops(boundary); + [e_s, e_S] = obj.getBoundaryOperator({'e', 'E'}, boundary); + s = obj.getBoundarySign(boundary); % Boundary condition on form % w_in = R*w_out + g, where g is data @@ -232,7 +233,8 @@ % % Returns closure(q,g) function closure = boundary_condition_L(obj, boundary, L_fun, p_in) - [e_s,e_S,s] = obj.get_boundary_ops(boundary); + [e_s, e_S] = obj.getBoundaryOperator({'e', 'E'}, boundary); + s = obj.getBoundarySign(boundary); p_ot = 1:3; p_ot(p_in) = []; @@ -273,7 +275,8 @@ % Return closure(q,g) function closure = boundary_condition_char(obj,boundary) - [e_s,e_S,s] = obj.get_boundary_ops(boundary); + [e_s, e_S] = obj.getBoundaryOperator({'e', 'E'}, boundary); + s = obj.getBoundarySign(boundary); function o = closure_fun(q, w_data) q_s = e_S'*q; @@ -314,7 +317,7 @@ % Return closure(q,[v; p]) function closure = boundary_condition_inflow(obj, boundary) - [~,~,s] = obj.get_boundary_ops(boundary); + s = obj.getBoundarySign(boundary); switch s case -1 @@ -335,7 +338,7 @@ % Return closure(q, p) function closure = boundary_condition_outflow(obj, boundary) - [~,~,s] = obj.get_boundary_ops(boundary); + s = obj.getBoundarySign(boundary); switch s case -1 @@ -352,7 +355,7 @@ % Return closure(q,[v; rho]) function closure = boundary_condition_inflow_rho(obj, boundary) - [~,~,s] = obj.get_boundary_ops(boundary); + s = obj.getBoundarySign(boundary); switch s case -1 @@ -372,7 +375,7 @@ % Return closure(q,rho) function closure = boundary_condition_outflow_rho(obj, boundary) - [~,~,s] = obj.get_boundary_ops(boundary); + s = obj.getBoundarySign(boundary); switch s case -1 @@ -388,7 +391,8 @@ % Set wall boundary condition v = 0. function closure = boundary_condition_wall(obj,boundary) - [e_s,e_S,s] = obj.get_boundary_ops(boundary); + [e_s, e_S] = obj.getBoundaryOperator({'e', 'E'}, boundary); + s = obj.getBoundarySign(boundary); % Vill vi sätta penalty på karateristikan som är nära noll också eller vill % vi låta den vara fri? @@ -478,18 +482,61 @@ penalty = -halfnorm_inv*(tau*e_v' + sig*d1_v' + phi*alpha_v*d2_v' + psi*alpha_v*d3_v'); end - % Ruturns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e,E,s] = get_boundary_ops(obj,boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + + if ~iscell(op) + op = {op}; + end + + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'l' + e = obj.e_l; + case 'r' + e = obj.e_r; + otherwise + error('No such boundary: boundary = %s',boundary); + end + varargout{i} = e; + + case 'E' + switch boundary + case 'l' + E = obj.e_L; + case 'r' + E = obj.e_R; + otherwise + error('No such boundary: boundary = %s',boundary); + end + varargout{i} = E; + end + end + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + % Note: for 1d diffOps, the boundary quadrature is the scalar 1. + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + + H_b = 1; + end + + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) switch boundary - case 'l' - e = obj.e_l; - E = obj.e_L; + case {'r'} + s = 1; + case {'l'} s = -1; - case 'r' - e = obj.e_r; - E = obj.e_R; - s = 1; otherwise error('No such boundary: boundary = %s',boundary); end
--- a/+scheme/Heat2dCurvilinear.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Heat2dCurvilinear.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,9 +1,9 @@ classdef Heat2dCurvilinear < scheme.Scheme % Discretizes the Laplacian with variable coefficent, curvilinear, -% in the Heat equation way (i.e., the discretization matrix is not necessarily +% in the Heat equation way (i.e., the discretization matrix is not necessarily % symmetric) -% u_t = div * (kappa * grad u ) +% u_t = div * (kappa * grad u ) % opSet should be cell array of opSets, one per dimension. This % is useful if we have periodic BC in one direction. @@ -29,9 +29,9 @@ e_l, e_r d1_l, d1_r % Normal derivatives at the boundary alpha % Vector of borrowing constants - + % Boundary inner products - H_boundary_l, H_boundary_r + H_boundary_l, H_boundary_r % Metric coefficients b % Cell matrix of size dim x dim @@ -109,7 +109,7 @@ opSetMetric{1} = sbp.D2Variable(m(1), {0, xmax}, order); opSetMetric{2} = sbp.D2Variable(m(2), {0, ymax}, order); D1Metric{1} = kron(opSetMetric{1}.D1, I{2}); - D1Metric{2} = kron(I{1}, opSetMetric{2}.D1); + D1Metric{2} = kron(I{1}, opSetMetric{2}.D1); x_xi = D1Metric{1}*x; x_eta = D1Metric{2}*x; @@ -157,7 +157,7 @@ % D2 coefficients kappa_coeff = cell(dim,dim); for j = 1:dim - obj.D2_kappa{j} = sparse(m_tot,m_tot); + obj.D2_kappa{j} = sparse(m_tot,m_tot); kappa_coeff{j} = sparse(m_tot,1); for i = 1:dim kappa_coeff{j} = kappa_coeff{j} + b{i,j}*J*b{i,j}*kappa; @@ -270,28 +270,20 @@ default_arg('symmetric', false); default_arg('tuning',1.2); - % j is the coordinate direction of the boundary - % nj: outward unit normal component. + % nj: outward unit normal component. % nj = -1 for west, south, bottom boundaries % nj = 1 for east, north, top boundaries - [j, nj] = obj.get_boundary_number(boundary); - switch nj - case 1 - e = obj.e_r{j}; - flux = obj.flux_r{j}; - H_gamma = obj.H_boundary_r{j}; - case -1 - e = obj.e_l{j}; - flux = obj.flux_l{j}; - H_gamma = obj.H_boundary_l{j}; - end + nj = obj.getBoundarySign(boundary); + + Hi = obj.Hi; + [e, flux] = obj.getBoundaryOperator({'e', 'flux'}, boundary); + H_gamma = obj.getBoundaryQuadrature(boundary); + alpha = obj.getBoundaryBorrowing(boundary); Hi = obj.Hi; Ji = obj.Ji; KAPPA = obj.KAPPA; - kappa_gamma = e'*KAPPA*e; - h = obj.h(j); - alpha = h*obj.alpha(j); + kappa_gamma = e'*KAPPA*e; switch type @@ -299,19 +291,19 @@ case {'D','d','dirichlet','Dirichlet'} if ~symmetric - closure = -Ji*Hi*flux'*e*H_gamma*(e' ); + closure = -Ji*Hi*flux'*e*H_gamma*(e' ); penalty = Ji*Hi*flux'*e*H_gamma; else closure = Ji*Hi*flux'*e*H_gamma*(e' )... - -tuning*2/alpha*Ji*Hi*e*kappa_gamma*H_gamma*(e' ) ; + -tuning*2/alpha*Ji*Hi*e*kappa_gamma*H_gamma*(e' ) ; penalty = -Ji*Hi*flux'*e*H_gamma ... +tuning*2/alpha*Ji*Hi*e*kappa_gamma*H_gamma; end % Normal flux boundary condition case {'N','n','neumann','Neumann'} - closure = -Ji*Hi*e*H_gamma*(e'*flux ); - penalty = Ji*Hi*e*H_gamma; + closure = -Ji*Hi*e*H_gamma*(e'*flux ); + penalty = Ji*Hi*e*H_gamma; % Unknown boundary condition otherwise @@ -325,57 +317,103 @@ error('Interface not implemented'); end - % Returns the coordinate number and outward normal component for the boundary specified by the string boundary. - function [j, nj] = get_boundary_number(obj, boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) - switch boundary - case {'w','W','west','West', 'e', 'E', 'east', 'East'} - j = 1; - case {'s','S','south','South', 'n', 'N', 'north', 'North'} - j = 2; - otherwise - error('No such boundary: boundary = %s',boundary); + if ~iscell(op) + op = {op}; end - switch boundary - case {'w','W','west','West','s','S','south','South'} - nj = -1; - case {'e', 'E', 'east', 'East','n', 'N', 'north', 'North'} - nj = 1; + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'w' + e = obj.e_l{1}; + case 'e' + e = obj.e_r{1}; + case 's' + e = obj.e_l{2}; + case 'n' + e = obj.e_r{2}; + end + varargout{i} = e; + + case 'd' + switch boundary + case 'w' + d = obj.d1_l{1}; + case 'e' + d = obj.d1_r{1}; + case 's' + d = obj.d1_l{2}; + case 'n' + d = obj.d1_r{2}; + end + varargout{i} = d; + + case 'flux' + switch boundary + case 'w' + flux = obj.flux_l{1}; + case 'e' + flux = obj.flux_r{1}; + case 's' + flux = obj.flux_l{2}; + case 'n' + flux = obj.flux_r{2}; + end + varargout{i} = flux; + end end end - % Returns the coordinate number and outward normal component for the boundary specified by the string boundary. - function [return_op] = get_boundary_operator(obj, op, boundary) + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) switch boundary - case {'w','W','west','West', 'e', 'E', 'east', 'East'} - j = 1; - case {'s','S','south','South', 'n', 'N', 'north', 'North'} - j = 2; - otherwise - error('No such boundary: boundary = %s',boundary); - end - - switch op + case 'w' + H_b = obj.H_boundary_l{1}; case 'e' - switch boundary - case {'w','W','west','West','s','S','south','South'} - return_op = obj.e_l{j}; - case {'e', 'E', 'east', 'East','n', 'N', 'north', 'North'} - return_op = obj.e_r{j}; - end - case 'd' - switch boundary - case {'w','W','west','West','s','S','south','South'} - return_op = obj.d1_l{j}; - case {'e', 'E', 'east', 'East','n', 'N', 'north', 'North'} - return_op = obj.d1_r{j}; - end - otherwise - error(['No such operator: operatr = ' op]); + H_b = obj.H_boundary_r{1}; + case 's' + H_b = obj.H_boundary_l{2}; + case 'n' + H_b = obj.H_boundary_r{2}; end + end + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'e','n'} + s = 1; + case {'w','s'} + s = -1; + end + end + + % Returns borrowing constant gamma*h + % boundary -- string + function gamm = getBoundaryBorrowing(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'w','e'} + gamm = obj.h(1)*obj.alpha(1); + case {'s','n'} + gamm = obj.h(2)*obj.alpha(2); + end end function N = size(obj)
--- a/+scheme/Heat2dVariable.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Heat2dVariable.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,9 +1,9 @@ classdef Heat2dVariable < scheme.Scheme % Discretizes the Laplacian with variable coefficent, -% In the Heat equation way (i.e., the discretization matrix is not necessarily +% In the Heat equation way (i.e., the discretization matrix is not necessarily % symmetric) -% u_t = div * (kappa * grad u ) +% u_t = div * (kappa * grad u ) % opSet should be cell array of opSets, one per dimension. This % is useful if we have periodic BC in one direction. @@ -29,7 +29,7 @@ e_l, e_r d1_l, d1_r % Normal derivatives at the boundary alpha % Vector of borrowing constants - + H_boundary % Boundary inner products end @@ -162,26 +162,18 @@ default_arg('symmetric', false); default_arg('tuning',1.2); - % j is the coordinate direction of the boundary - % nj: outward unit normal component. + % nj: outward unit normal component. % nj = -1 for west, south, bottom boundaries % nj = 1 for east, north, top boundaries - [j, nj] = obj.get_boundary_number(boundary); - switch nj - case 1 - e = obj.e_r; - d = obj.d1_r; - case -1 - e = obj.e_l; - d = obj.d1_l; - end + nj = obj.getBoundarySign(boundary); Hi = obj.Hi; - H_gamma = obj.H_boundary{j}; + [e, d] = obj.getBoundaryOperator({'e', 'd'}, boundary); + H_gamma = obj.getBoundaryQuadrature(boundary); + alpha = obj.getBoundaryBorrowing(boundary); + KAPPA = obj.KAPPA; - kappa_gamma = e{j}'*KAPPA*e{j}; - h = obj.h(j); - alpha = h*obj.alpha(j); + kappa_gamma = e'*KAPPA*e; switch type @@ -189,19 +181,19 @@ case {'D','d','dirichlet','Dirichlet'} if ~symmetric - closure = -nj*Hi*d{j}*kappa_gamma*H_gamma*(e{j}' ); - penalty = nj*Hi*d{j}*kappa_gamma*H_gamma; + closure = -nj*Hi*d*kappa_gamma*H_gamma*(e' ); + penalty = nj*Hi*d*kappa_gamma*H_gamma; else - closure = nj*Hi*d{j}*kappa_gamma*H_gamma*(e{j}' )... - -tuning*2/alpha*Hi*e{j}*kappa_gamma*H_gamma*(e{j}' ) ; - penalty = -nj*Hi*d{j}*kappa_gamma*H_gamma ... - +tuning*2/alpha*Hi*e{j}*kappa_gamma*H_gamma; + closure = nj*Hi*d*kappa_gamma*H_gamma*(e' )... + -tuning*2/alpha*Hi*e*kappa_gamma*H_gamma*(e' ) ; + penalty = -nj*Hi*d*kappa_gamma*H_gamma ... + +tuning*2/alpha*Hi*e*kappa_gamma*H_gamma; end % Free boundary condition case {'N','n','neumann','Neumann'} - closure = -nj*Hi*e{j}*kappa_gamma*H_gamma*(d{j}' ); - penalty = Hi*e{j}*kappa_gamma*H_gamma; + closure = -nj*Hi*e*kappa_gamma*H_gamma*(d' ); + penalty = Hi*e*kappa_gamma*H_gamma; % penalty is for normal derivative and not for derivative, hence the sign. % Unknown boundary condition @@ -216,57 +208,90 @@ error('Interface not implemented'); end - % Returns the coordinate number and outward normal component for the boundary specified by the string boundary. - function [j, nj] = get_boundary_number(obj, boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) - switch boundary - case {'w','W','west','West', 'e', 'E', 'east', 'East'} - j = 1; - case {'s','S','south','South', 'n', 'N', 'north', 'North'} - j = 2; - otherwise - error('No such boundary: boundary = %s',boundary); + if ~iscell(op) + op = {op}; end - switch boundary - case {'w','W','west','West','s','S','south','South'} - nj = -1; - case {'e', 'E', 'east', 'East','n', 'N', 'north', 'North'} - nj = 1; + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'w' + e = obj.e_l{1}; + case 'e' + e = obj.e_r{1}; + case 's' + e = obj.e_l{2}; + case 'n' + e = obj.e_r{2}; + end + varargout{i} = e; + + case 'd' + switch boundary + case 'w' + d = obj.d1_l{1}; + case 'e' + d = obj.d1_r{1}; + case 's' + d = obj.d1_l{2}; + case 'n' + d = obj.d1_r{2}; + end + varargout{i} = d; + end end end - % Returns the coordinate number and outward normal component for the boundary specified by the string boundary. - function [return_op] = get_boundary_operator(obj, op, boundary) + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) switch boundary - case {'w','W','west','West', 'e', 'E', 'east', 'East'} - j = 1; - case {'s','S','south','South', 'n', 'N', 'north', 'North'} - j = 2; - otherwise - error('No such boundary: boundary = %s',boundary); - end - - switch op + case 'w' + H_b = obj.H_boundary{1}; case 'e' - switch boundary - case {'w','W','west','West','s','S','south','South'} - return_op = obj.e_l{j}; - case {'e', 'E', 'east', 'East','n', 'N', 'north', 'North'} - return_op = obj.e_r{j}; - end - case 'd' - switch boundary - case {'w','W','west','West','s','S','south','South'} - return_op = obj.d1_l{j}; - case {'e', 'E', 'east', 'East','n', 'N', 'north', 'North'} - return_op = obj.d1_r{j}; - end - otherwise - error(['No such operator: operatr = ' op]); + H_b = obj.H_boundary{1}; + case 's' + H_b = obj.H_boundary{2}; + case 'n' + H_b = obj.H_boundary{2}; end + end + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'e','n'} + s = 1; + case {'w','s'} + s = -1; + end + end + + % Returns borrowing constant gamma*h + % boundary -- string + function gamm = getBoundaryBorrowing(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'w','e'} + gamm = obj.h(1)*obj.alpha(1); + case {'s','n'} + gamm = obj.h(2)*obj.alpha(2); + end end function N = size(obj)
--- a/+scheme/Hypsyst2d.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Hypsyst2d.m Thu Mar 10 16:54:26 2022 +0100 @@ -186,10 +186,10 @@ params = obj.params; x = obj.x; y = obj.y; + e_ = obj.getBoundaryOperator('e', boundary); switch boundary case {'w','W','west'} - e_ = obj.e_w; mat = obj.A; boundPos = 'l'; Hi = obj.Hxi; @@ -197,7 +197,6 @@ L = obj.evaluateCoefficientMatrix(L,x(1),y); side = max(length(y)); case {'e','E','east'} - e_ = obj.e_e; mat = obj.A; boundPos = 'r'; Hi = obj.Hxi; @@ -205,7 +204,6 @@ L = obj.evaluateCoefficientMatrix(L,x(end),y); side = max(length(y)); case {'s','S','south'} - e_ = obj.e_s; mat = obj.B; boundPos = 'l'; Hi = obj.Hyi; @@ -213,7 +211,6 @@ L = obj.evaluateCoefficientMatrix(L,x,y(1)); side = max(length(x)); case {'n','N','north'} - e_ = obj.e_n; mat = obj.B; boundPos = 'r'; Hi = obj.Hyi; @@ -297,5 +294,54 @@ signVec = [sum(poseig),sum(zeroeig),sum(negeig)]; end + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + if ~iscell(op) + op = {op}; + end + + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'w' + e = obj.e_w; + case 'e' + e = obj.e_e; + case 's' + e = obj.e_s; + case 'n' + e = obj.e_n; + end + varargout{i} = e; + end + end + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + e = obj.getBoundaryOperator('e', boundary); + + switch boundary + case 'w' + H_b = inv(e'*obj.Hyi*e); + case 'e' + H_b = inv(e'*obj.Hyi*e); + case 's' + H_b = inv(e'*obj.Hxi*e); + case 'n' + H_b = inv(e'*obj.Hxi*e); + end + end + end end \ No newline at end of file
--- a/+scheme/Hypsyst2dCurve.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Hypsyst2dCurve.m Thu Mar 10 16:54:26 2022 +0100 @@ -169,31 +169,28 @@ Y = obj.Y; xi = obj.xi; eta = obj.eta; + e_ = obj.getBoundaryOperator('e', boundary); switch boundary case {'w','W','west'} - e_ = obj.e_w; mat = obj.Ahat; boundPos = 'l'; Hi = obj.Hxii; [V,Vi,D,signVec] = obj.matrixDiag(mat,X(obj.index_w),Y(obj.index_w),obj.X_eta(obj.index_w),obj.Y_eta(obj.index_w)); side = max(length(eta)); case {'e','E','east'} - e_ = obj.e_e; mat = obj.Ahat; boundPos = 'r'; Hi = obj.Hxii; [V,Vi,D,signVec] = obj.matrixDiag(mat,X(obj.index_e),Y(obj.index_e),obj.X_eta(obj.index_e),obj.Y_eta(obj.index_e)); side = max(length(eta)); case {'s','S','south'} - e_ = obj.e_s; mat = obj.Bhat; boundPos = 'l'; Hi = obj.Hetai; [V,Vi,D,signVec] = obj.matrixDiag(mat,X(obj.index_s),Y(obj.index_s),obj.X_xi(obj.index_s),obj.Y_xi(obj.index_s)); side = max(length(xi)); case {'n','N','north'} - e_ = obj.e_n; mat = obj.Bhat; boundPos = 'r'; Hi = obj.Hetai; @@ -374,5 +371,56 @@ Vi = [Vi(poseig,:); Vi(zeroeig,:); Vi(negeig,:)]; signVec = [sum(poseig),sum(zeroeig),sum(negeig)]; end + + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + if ~iscell(op) + op = {op}; + end + + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'w' + e = obj.e_w; + case 'e' + e = obj.e_e; + case 's' + e = obj.e_s; + case 'n' + e = obj.e_n; + end + varargout{i} = e; + end + end + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + e = obj.getBoundaryOperator('e', boundary); + + switch boundary + case 'w' + H_b = inv(e'*obj.Hetai*e); + case 'e' + H_b = inv(e'*obj.Hetai*e); + case 's' + H_b = inv(e'*obj.Hxii*e); + case 'n' + H_b = inv(e'*obj.Hxii*e); + end + end + + end end \ No newline at end of file
--- a/+scheme/Laplace1d.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Laplace1d.m Thu Mar 10 16:54:26 2022 +0100 @@ -56,11 +56,13 @@ default_arg('type','neumann'); default_arg('data',0); - [e,d,s] = obj.get_boundary_ops(boundary); + e = obj.getBoundaryOperator('e', boundary); + d = obj.getBoundaryOperator('d', boundary); + s = obj.getBoundarySign(boundary); switch type % Dirichlet boundary condition - case {'D','dirichlet'} + case {'D','d','dirichlet'} tuning = 1.1; tau1 = -tuning/obj.gamm; tau2 = 1; @@ -68,10 +70,10 @@ tau = tau1*e + tau2*d; closure = obj.a*obj.Hi*tau*e'; - penalty = obj.a*obj.Hi*tau; + penalty = -obj.a*obj.Hi*tau; % Neumann boundary condition - case {'N','neumann'} + case {'N','n','neumann'} tau = -e; closure = obj.a*obj.Hi*tau*d'; @@ -86,10 +88,13 @@ function [closure, penalty] = interface(obj, boundary, neighbour_scheme, neighbour_boundary, type) % u denotes the solution in the own domain % v denotes the solution in the neighbour domain + e_u = obj.getBoundaryOperator('e', boundary); + d_u = obj.getBoundaryOperator('d', boundary); + s_u = obj.getBoundarySign(boundary); - [e_u,d_u,s_u] = obj.get_boundary_ops(boundary); - [e_v,d_v,s_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); - + e_v = neighbour_scheme.getBoundaryOperator('e', neighbour_boundary); + d_v = neighbour_scheme.getBoundaryOperator('d', neighbour_boundary); + s_v = neighbour_scheme.getBoundarySign(neighbour_boundary); a_u = obj.a; a_v = neighbour_scheme.a; @@ -99,7 +104,7 @@ tuning = 1.1; - tau1 = -(a_u/gamm_u + a_v/gamm_v) * tuning; + tau1 = -1/4*(a_u/gamm_u + a_v/gamm_v) * tuning; tau2 = 1/2*a_u; sig1 = -1/2; sig2 = 0; @@ -111,20 +116,37 @@ penalty = obj.Hi*(-tau*e_v' + sig*a_v*d_v'); end - % Ruturns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e,d,s] = get_boundary_ops(obj,boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string + % boundary -- string + function o = getBoundaryOperator(obj, op, boundary) + assertIsMember(op, {'e', 'd'}) + assertIsMember(boundary, {'l', 'r'}) + + o = obj.([op, '_', boundary]); + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + % Note: for 1d diffOps, the boundary quadrature is the scalar 1. + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + + H_b = 1; + end + + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + switch boundary - case 'l' - e = obj.e_l; - d = obj.d_l; + case {'r'} + s = 1; + case {'l'} s = -1; - case 'r' - e = obj.e_r; - d = obj.d_r; - s = 1; - otherwise - error('No such boundary: boundary = %s',boundary); end end @@ -133,14 +155,4 @@ end end - - methods(Static) - % Calculates the matrcis need for the inteface coupling between boundary bound_u of scheme schm_u - % and bound_v of scheme schm_v. - % [uu, uv, vv, vu] = inteface_couplong(A,'r',B,'l') - function [uu, uv, vv, vu] = interface_coupling(schm_u,bound_u,schm_v,bound_v) - [uu,uv] = schm_u.interface(bound_u,schm_v,bound_v); - [vv,vu] = schm_v.interface(bound_v,schm_u,bound_u); - end - end -end \ No newline at end of file +end
--- a/+scheme/LaplaceCurvilinear.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/LaplaceCurvilinear.m Thu Mar 10 16:54:26 2022 +0100 @@ -238,7 +238,10 @@ default_arg('type','neumann'); default_arg('parameter', []); - [e, d, gamm, H_b, ~] = obj.get_boundary_ops(boundary); + e = obj.getBoundaryOperator('e', boundary); + d = obj.getBoundaryOperator('d', boundary); + H_b = obj.getBoundaryQuadrature(boundary); + gamm = obj.getBoundaryBorrowing(boundary); switch type % Dirichlet boundary condition case {'D','d','dirichlet'} @@ -298,8 +301,17 @@ % u denotes the solution in the own domain % v denotes the solution in the neighbour domain - [e_u, d_u, gamm_u, H_b_u, I_u] = obj.get_boundary_ops(boundary); - [e_v, d_v, gamm_v, H_b_v, I_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); + e_u = obj.getBoundaryOperator('e', boundary); + d_u = obj.getBoundaryOperator('d', boundary); + H_b_u = obj.getBoundaryQuadrature(boundary); + I_u = obj.getBoundaryIndices(boundary); + gamm_u = obj.getBoundaryBorrowing(boundary); + + e_v = neighbour_scheme.getBoundaryOperator('e', neighbour_boundary); + d_v = neighbour_scheme.getBoundaryOperator('d', neighbour_boundary); + H_b_v = neighbour_scheme.getBoundaryQuadrature(neighbour_boundary); + I_v = neighbour_scheme.getBoundaryIndices(neighbour_boundary); + gamm_v = neighbour_scheme.getBoundaryBorrowing(neighbour_boundary); u = obj; v = neighbour_scheme; @@ -336,8 +348,18 @@ % u denotes the solution in the own domain % v denotes the solution in the neighbour domain - [e_u, d_u, gamm_u, H_b_u, I_u] = obj.get_boundary_ops(boundary); - [e_v, d_v, gamm_v, H_b_v, I_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); + e_u = obj.getBoundaryOperator('e', boundary); + d_u = obj.getBoundaryOperator('d', boundary); + H_b_u = obj.getBoundaryQuadrature(boundary); + I_u = obj.getBoundaryIndices(boundary); + gamm_u = obj.getBoundaryBorrowing(boundary); + + e_v = neighbour_scheme.getBoundaryOperator('e', neighbour_boundary); + d_v = neighbour_scheme.getBoundaryOperator('d', neighbour_boundary); + H_b_v = neighbour_scheme.getBoundaryQuadrature(neighbour_boundary); + I_v = neighbour_scheme.getBoundaryIndices(neighbour_boundary); + gamm_v = neighbour_scheme.getBoundaryBorrowing(neighbour_boundary); + % Find the number of grid points along the interface m_u = size(e_u, 2); @@ -378,37 +400,48 @@ end - % Returns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string + % boundary -- string + function o = getBoundaryOperator(obj, op, boundary) + assertIsMember(op, {'e', 'd'}) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + o = obj.([op, '_', boundary]); + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points % - % I -- the indices of the boundary points in the grid matrix - function [e, d, gamm, H_b, I] = get_boundary_ops(obj, boundary) + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + H_b = obj.(['H_', boundary]); + end + + % Returns the indices of the boundary points in the grid matrix + % boundary -- string + function I = getBoundaryIndices(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + ind = grid.funcToMatrix(obj.grid, 1:prod(obj.m)); - switch boundary case 'w' - e = obj.e_w; - d = obj.d_w; - H_b = obj.H_w; I = ind(1,:); case 'e' - e = obj.e_e; - d = obj.d_e; - H_b = obj.H_e; I = ind(end,:); case 's' - e = obj.e_s; - d = obj.d_s; - H_b = obj.H_s; I = ind(:,1)'; case 'n' - e = obj.e_n; - d = obj.d_n; - H_b = obj.H_n; I = ind(:,end)'; - otherwise - error('No such boundary: boundary = %s',boundary); end + end + + % Returns borrowing constant gamma + % boundary -- string + function gamm = getBoundaryBorrowing(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) switch boundary case {'w','e'}
--- a/+scheme/Scheme.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Scheme.m Thu Mar 10 16:54:26 2022 +0100 @@ -31,20 +31,10 @@ % depending on the particular scheme implementation [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary,type) - % TODO: op = getBoundaryOperator()?? - % makes sense to have it available through a method instead of random properties + op = getBoundaryOperator(obj, opName, boundary) + H_b= getBoundaryQuadrature(obj, boundary) % Returns the number of degrees of freedom. N = size(obj) end - - methods(Static) - % Calculates the matrcis need for the inteface coupling between - % boundary bound_u of scheme schm_u and bound_v of scheme schm_v. - % [uu, uv, vv, vu] = inteface_coupling(A,'r',B,'l') - function [uu, uv, vv, vu] = interface_coupling(schm_u,bound_u,schm_v,bound_v) - [uu,uv] = schm_u.interface(bound_u,schm_v,bound_v); - [vv,vu] = schm_v.interface(bound_v,schm_u,bound_u); - end - end end
--- a/+scheme/Schrodinger.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Schrodinger.m Thu Mar 10 16:54:26 2022 +0100 @@ -67,7 +67,8 @@ default_arg('type','dirichlet'); default_arg('data',0); - [e,d,s] = obj.get_boundary_ops(boundary); + [e, d] = obj.getBoundaryOperator({'e', 'd'}, boundary); + s = obj.getBoundarySign(boundary); switch type % Dirichlet boundary condition @@ -93,8 +94,11 @@ function [closure, penalty] = interface(obj, boundary, neighbour_scheme, neighbour_boundary, type) % u denotes the solution in the own domain % v denotes the solution in the neighbour domain - [e_u,d_u,s_u] = obj.get_boundary_ops(boundary); - [e_v,d_v,s_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); + [e_u, d_u] = obj.getBoundaryOperator({'e', 'd'}, boundary); + s_u = obj.getBoundarySign(boundary); + + [e_v, d_v] = neighbour_scheme.getBoundaryOperator({'e', 'd'}, neighbour_boundary); + s_v = neighbour_scheme.getBoundarySign(neighbour_boundary); a = -s_u* 1/2 * 1i ; b = a'; @@ -106,20 +110,60 @@ penalty = obj.Hi * (-tau*e_v' - sig*d_v'); end - % Ruturns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e,d,s] = get_boundary_ops(obj,boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'l', 'r'}) + + if ~iscell(op) + op = {op}; + end + + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'l' + e = obj.e_l; + case 'r' + e = obj.e_r; + end + varargout{i} = e; + + case 'd' + switch boundary + case 'l' + d = obj.d1_l; + case 'r' + d = obj.d1_r; + end + varargout{i} = d; + end + end + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + % Note: for 1d diffOps, the boundary quadrature is the scalar 1. + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + + H_b = 1; + end + + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + switch boundary - case 'l' - e = obj.e_l; - d = obj.d1_l; + case {'r'} + s = 1; + case {'l'} s = -1; - case 'r' - e = obj.e_r; - d = obj.d1_r; - s = 1; - otherwise - error('No such boundary: boundary = %s',boundary); end end @@ -128,14 +172,4 @@ end end - - methods(Static) - % Calculates the matrcis need for the inteface coupling between boundary bound_u of scheme schm_u - % and bound_v of scheme schm_v. - % [uu, uv, vv, vu] = inteface_couplong(A,'r',B,'l') - function [uu, uv, vv, vu] = interface_coupling(schm_u,bound_u,schm_v,bound_v) - [uu,uv] = schm_u.interface(bound_u,schm_v,bound_v); - [vv,vu] = schm_v.interface(bound_v,schm_u,bound_u); - end - end -end \ No newline at end of file +end
--- a/+scheme/Schrodinger2d.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Schrodinger2d.m Thu Mar 10 16:54:26 2022 +0100 @@ -162,35 +162,26 @@ default_arg('type','Neumann'); default_arg('parameter', []); - % j is the coordinate direction of the boundary % nj: outward unit normal component. % nj = -1 for west, south, bottom boundaries % nj = 1 for east, north, top boundaries - [j, nj] = obj.get_boundary_number(boundary); - switch nj - case 1 - e = obj.e_r; - d = obj.d1_r; - case -1 - e = obj.e_l; - d = obj.d1_l; - end - + nj = obj.getBoundarySign(boundary); + [e, d] = obj.getBoundaryOperator({'e', 'd'}, boundary); + H_gamma = obj.getBoundaryQuadrature(boundary); Hi = obj.Hi; - H_gamma = obj.H_boundary{j}; - a = e{j}'*obj.a*e{j}; + a = e'*obj.a*e; switch type % Dirichlet boundary condition case {'D','d','dirichlet','Dirichlet'} - closure = nj*Hi*d{j}*a*1i*H_gamma*(e{j}' ); - penalty = -nj*Hi*d{j}*a*1i*H_gamma; + closure = nj*Hi*d*a*1i*H_gamma*(e' ); + penalty = -nj*Hi*d*a*1i*H_gamma; % Free boundary condition case {'N','n','neumann','Neumann'} - closure = -nj*Hi*e{j}*a*1i*H_gamma*(d{j}' ); - penalty = nj*Hi*e{j}*a*1i*H_gamma; + closure = -nj*Hi*e*a*1i*H_gamma*(d' ); + penalty = nj*Hi*e*a*1i*H_gamma; % Unknown boundary condition otherwise @@ -221,13 +212,14 @@ % v denotes the solution in the neighbour domain % Get boundary operators - [e_neighbour, d_neighbour] = neighbour_scheme.get_boundary_ops(neighbour_boundary); - [e, d, H_gamma] = obj.get_boundary_ops(boundary); + [e_v, d_v] = neighbour_scheme.getBoundaryOperator({'e', 'd'}, neighbour_boundary); + [e_u, d_u] = obj.getBoundaryOperator({'e', 'd'}, boundary); + H_gamma = obj.getBoundaryQuadrature(boundary); Hi = obj.Hi; a = obj.a; % Get outward unit normal component - [~, n] = obj.get_boundary_number(boundary); + n = obj.getBoundarySign(boundary); Hi = obj.Hi; sigma = -n*1i*a/2; @@ -247,13 +239,14 @@ % u denotes the solution in the own domain % v denotes the solution in the neighbour domain - [e_v, d_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); - [e_u, d_u, H_gamma] = obj.get_boundary_ops(boundary); + [e_v, d_v] = neighbour_scheme.getBoundaryOperator({'e', 'd'}, neighbour_boundary); + [e_u, d_u] = obj.getBoundaryOperator({'e', 'd'}, boundary); + H_gamma = obj.getBoundaryQuadrature(boundary); Hi = obj.Hi; a = obj.a; % Get outward unit normal component - [~, n] = obj.get_boundary_number(boundary); + n = obj.getBoundarySign(boundary); % Find the number of grid points along the interface m_u = size(e_u, 2); @@ -293,29 +286,76 @@ end end - % Returns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e, d, H_b] = get_boundary_ops(obj, boundary) + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + if ~iscell(op) + op = {op}; + end + + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'w' + e = obj.e_w; + case 'e' + e = obj.e_e; + case 's' + e = obj.e_s; + case 'n' + e = obj.e_n; + end + varargout{i} = e; + + case 'd' + switch boundary + case 'w' + d = obj.d_w; + case 'e' + d = obj.d_e; + case 's' + d = obj.d_s; + case 'n' + d = obj.d_n; + end + varargout{i} = d; + end + end + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) switch boundary case 'w' - e = obj.e_w; - d = obj.d_w; H_b = obj.H_boundary{1}; case 'e' - e = obj.e_e; - d = obj.d_e; H_b = obj.H_boundary{1}; case 's' - e = obj.e_s; - d = obj.d_s; H_b = obj.H_boundary{2}; case 'n' - e = obj.e_n; - d = obj.d_n; H_b = obj.H_boundary{2}; - otherwise - error('No such boundary: boundary = %s',boundary); + end + end + + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'e','n'} + s = 1; + case {'w','s'} + s = -1; end end
--- a/+scheme/TODO.txt Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1 +0,0 @@ -% TODO: Rename package and abstract class to diffOp
--- a/+scheme/Utux.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Utux.m Thu Mar 10 16:54:26 2022 +0100 @@ -72,19 +72,30 @@ end + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string + % boundary -- string + function o = getBoundaryOperator(obj, op, boundary) + assertIsMember(op, {'e'}) + assertIsMember(boundary, {'l', 'r'}) + + o = obj.([op, '_', boundary]); + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + % Note: for 1d diffOps, the boundary quadrature is the scalar 1. + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'l', 'r'}) + + H_b = 1; + end + function N = size(obj) N = obj.m; end end - - methods(Static) - % Calculates the matrices needed for the inteface coupling between boundary bound_u of scheme schm_u - % and bound_v of scheme schm_v. - % [uu, uv, vv, vu] = inteface_coupling(A,'r',B,'l') - function [uu, uv, vv, vu] = interface_coupling(schm_u,bound_u,schm_v,bound_v) - [uu,uv] = schm_u.interface(bound_u,schm_v,bound_v); - [vv,vu] = schm_v.interface(bound_v,schm_u,bound_u); - end - end -end \ No newline at end of file +end
--- a/+scheme/Utux2d.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Utux2d.m Thu Mar 10 16:54:26 2022 +0100 @@ -12,6 +12,7 @@ H % Discrete norm H_x, H_y % Norms in the x and y directions Hi, Hx, Hy, Hxi, Hyi % Kroneckered norms + H_w, H_e, H_s, H_n % Boundary quadratures % Derivatives Dx, Dy @@ -59,6 +60,10 @@ Hxi = ops_x.HI; Hyi = ops_y.HI; + obj.H_w = Hy; + obj.H_e = Hy; + obj.H_s = Hx; + obj.H_n = Hx; obj.H_x = Hx; obj.H_y = Hy; obj.H = kron(Hx,Hy); @@ -139,16 +144,7 @@ couplingType = type.couplingType; % Get neighbour boundary operator - switch neighbour_boundary - case {'e','E','east','East'} - e_neighbour = neighbour_scheme.e_e; - case {'w','W','west','West'} - e_neighbour = neighbour_scheme.e_w; - case {'n','N','north','North'} - e_neighbour = neighbour_scheme.e_n; - case {'s','S','south','South'} - e_neighbour = neighbour_scheme.e_s; - end + e_neighbour = neighbour_scheme.getBoundaryOperator('e', neighbour_boundary); switch couplingType @@ -197,16 +193,7 @@ interpolationDamping = type.interpolationDamping; % Get neighbour boundary operator - switch neighbour_boundary - case {'e','E','east','East'} - e_neighbour = neighbour_scheme.e_e; - case {'w','W','west','West'} - e_neighbour = neighbour_scheme.e_w; - case {'n','N','north','North'} - e_neighbour = neighbour_scheme.e_n; - case {'s','S','south','South'} - e_neighbour = neighbour_scheme.e_s; - end + e_neighbour = neighbour_scheme.getBoundaryOperator('e', neighbour_boundary); switch couplingType @@ -290,19 +277,29 @@ end + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string + % boundary -- string + function o = getBoundaryOperator(obj, op, boundary) + assertIsMember(op, {'e'}) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + o = obj.([op, '_', boundary]); + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + H_b = obj.(['H_', boundary]); + end + function N = size(obj) N = obj.m; end end - - methods(Static) - % Calculates the matrices needed for the inteface coupling between boundary bound_u of scheme schm_u - % and bound_v of scheme schm_v. - % [uu, uv, vv, vu] = inteface_coupling(A,'r',B,'l') - function [uu, uv, vv, vu] = interface_coupling(schm_u,bound_u,schm_v,bound_v) - [uu,uv] = schm_u.interface(bound_u,schm_v,bound_v); - [vv,vu] = schm_v.interface(bound_v,schm_u,bound_u); - end - end -end \ No newline at end of file +end
--- a/+scheme/Wave2d.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+scheme/Wave2d.m Thu Mar 10 16:54:26 2022 +0100 @@ -106,7 +106,10 @@ default_arg('type','neumann'); default_arg('data',0); - [e,d,s,gamm,halfnorm_inv] = obj.get_boundary_ops(boundary); + [e, d] = obj.getBoundaryOperator({'e', 'd'}, boundary); + gamm = obj.getBoundaryBorrowing(boundary); + s = obj.getBoundarySign(boundary); + halfnorm_inv = obj.getHalfnormInv(boundary); switch type % Dirichlet boundary condition @@ -164,6 +167,15 @@ [e_u,d_u,s_u,gamm_u, halfnorm_inv] = obj.get_boundary_ops(boundary); [e_v,d_v,s_v,gamm_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); + [e_u, d_u] = obj.getBoundaryOperator({'e', 'd'}, boundary); + gamm_u = obj.getBoundaryBorrowing(boundary); + s_u = obj.getBoundarySign(boundary); + halfnorm_inv = obj.getHalfnormInv(boundary); + + [e_v, d_v] = neighbour_scheme.getBoundaryOperator({'e', 'd'}, neighbour_boundary); + gamm_v = neighbour_scheme.getBoundaryBorrowing(neighbour_boundary); + s_v = neighbour_scheme.getBoundarySign(neighbour_boundary); + tuning = 1.1; alpha_u = obj.alpha; @@ -183,36 +195,107 @@ penalty = halfnorm_inv*(-tau*e_v' - sig*alpha_v*d_v'); end - % Ruturns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - function [e,d,s,gamm, halfnorm_inv] = get_boundary_ops(obj,boundary) + + % Returns the boundary operator op for the boundary specified by the string boundary. + % op -- string or a cell array of strings + % boundary -- string + function varargout = getBoundaryOperator(obj, op, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + if ~iscell(op) + op = {op}; + end + + for i = 1:numel(op) + switch op{i} + case 'e' + switch boundary + case 'w' + e = obj.e_w; + case 'e' + e = obj.e_e; + case 's' + e = obj.e_s; + case 'n' + e = obj.e_n; + end + varargout{i} = e; + + case 'd' + switch boundary + case 'w' + d = obj.d1_w; + case 'e' + d = obj.d1_e; + case 's' + d = obj.d1_s; + case 'n' + d = obj.d1_n; + end + varargout{i} = d; + end + end + + end + + % Returns square boundary quadrature matrix, of dimension + % corresponding to the number of boundary points + % + % boundary -- string + function H_b = getBoundaryQuadrature(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + switch boundary case 'w' - e = obj.e_w; - d = obj.d1_w; - s = -1; - gamm = obj.gamm_x; - halfnorm_inv = obj.Hix; + H_b = obj.H_y; case 'e' - e = obj.e_e; - d = obj.d1_e; - s = 1; - gamm = obj.gamm_x; - halfnorm_inv = obj.Hix; + H_b = obj.H_y; case 's' - e = obj.e_s; - d = obj.d1_s; - s = -1; - gamm = obj.gamm_y; - halfnorm_inv = obj.Hiy; + H_b = obj.H_x; case 'n' - e = obj.e_n; - d = obj.d1_n; - s = 1; + H_b = obj.H_x; + end + end + + % Returns borrowing constant gamma + % boundary -- string + function gamm = getBoundaryBorrowing(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'w','e'} + gamm = obj.gamm_x; + case {'s','n'} gamm = obj.gamm_y; - halfnorm_inv = obj.Hiy; - otherwise - error('No such boundary: boundary = %s',boundary); + end + end + + % Returns the boundary sign. The right boundary is considered the positive boundary + % boundary -- string + function s = getBoundarySign(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case {'e','n'} + s = 1; + case {'w','s'} + s = -1; + end + end + + % Returns the halfnorm_inv used in SATs. TODO: better notation + function Hinv = getHalfnormInv(obj, boundary) + assertIsMember(boundary, {'w', 'e', 's', 'n'}) + + switch boundary + case 'w' + Hinv = obj.Hix; + case 'e' + Hinv = obj.Hix; + case 's' + Hinv = obj.Hiy; + case 'n' + Hinv = obj.Hiy; end end @@ -221,14 +304,4 @@ end end - - methods(Static) - % Calculates the matrcis need for the inteface coupling between boundary bound_u of scheme schm_u - % and bound_v of scheme schm_v. - % [uu, uv, vv, vu] = inteface_couplong(A,'r',B,'l') - function [uu, uv, vv, vu] = interface_coupling(schm_u,bound_u,schm_v,bound_v) - [uu,uv] = schm_u.interface(bound_u,schm_v,bound_v); - [vv,vu] = schm_v.interface(bound_v,schm_u,bound_u); - end - end -end \ No newline at end of file +end
--- a/+scheme/Wave2dCurve.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,359 +0,0 @@ -classdef Wave2dCurve < scheme.Scheme - properties - m % Number of points in each direction, possibly a vector - h % Grid spacing - - grid - - order % Order accuracy for the approximation - - D % non-stabalized scheme operator - M % Derivative norm - c - J, Ji - a11, a12, a22 - - H % Discrete norm - Hi - H_u, H_v % Norms in the x and y directions - Hu,Hv % Kroneckerd norms. 1'*Hx*v corresponds to integration in the x dir. - Hi_u, Hi_v - Hiu, Hiv - e_w, e_e, e_s, e_n - du_w, dv_w - du_e, dv_e - du_s, dv_s - du_n, dv_n - gamm_u, gamm_v - lambda - - Dx, Dy % Physical derivatives - - x_u - x_v - y_u - y_v - end - - methods - function obj = Wave2dCurve(g ,order, c, opSet) - default_arg('opSet',@sbp.D2Variable); - default_arg('c', 1); - - warning('Use LaplaceCruveilinear instead') - - assert(isa(g, 'grid.Curvilinear')) - - m = g.size(); - m_u = m(1); - m_v = m(2); - m_tot = g.N(); - - h = g.scaling(); - h_u = h(1); - h_v = h(2); - - % Operators - ops_u = opSet(m_u, {0, 1}, order); - ops_v = opSet(m_v, {0, 1}, order); - - I_u = speye(m_u); - I_v = speye(m_v); - - D1_u = ops_u.D1; - D2_u = ops_u.D2; - H_u = ops_u.H; - Hi_u = ops_u.HI; - e_l_u = ops_u.e_l; - e_r_u = ops_u.e_r; - d1_l_u = ops_u.d1_l; - d1_r_u = ops_u.d1_r; - - D1_v = ops_v.D1; - D2_v = ops_v.D2; - H_v = ops_v.H; - Hi_v = ops_v.HI; - e_l_v = ops_v.e_l; - e_r_v = ops_v.e_r; - d1_l_v = ops_v.d1_l; - d1_r_v = ops_v.d1_r; - - Du = kr(D1_u,I_v); - Dv = kr(I_u,D1_v); - - % Metric derivatives - coords = g.points(); - x = coords(:,1); - y = coords(:,2); - - 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; - a11 = 1./J .* (x_v.^2 + y_v.^2); - a12 = -1./J .* (x_u.*x_v + y_u.*y_v); - a22 = 1./J .* (x_u.^2 + y_u.^2); - lambda = 1/2 * (a11 + a22 - sqrt((a11-a22).^2 + 4*a12.^2)); - - % Assemble full operators - L_12 = spdiags(a12, 0, m_tot, m_tot); - Duv = Du*L_12*Dv; - Dvu = Dv*L_12*Du; - - Duu = sparse(m_tot); - Dvv = sparse(m_tot); - ind = grid.funcToMatrix(g, 1:m_tot); - - for i = 1:m_v - D = D2_u(a11(ind(:,i))); - p = ind(:,i); - Duu(p,p) = D; - end - - for i = 1:m_u - D = D2_v(a22(ind(i,:))); - p = ind(i,:); - Dvv(p,p) = D; - end - - obj.H = kr(H_u,H_v); - obj.Hi = kr(Hi_u,Hi_v); - obj.Hu = kr(H_u,I_v); - obj.Hv = kr(I_u,H_v); - obj.Hiu = kr(Hi_u,I_v); - obj.Hiv = kr(I_u,Hi_v); - - obj.e_w = kr(e_l_u,I_v); - obj.e_e = kr(e_r_u,I_v); - obj.e_s = kr(I_u,e_l_v); - obj.e_n = kr(I_u,e_r_v); - obj.du_w = kr(d1_l_u,I_v); - obj.dv_w = (obj.e_w'*Dv)'; - obj.du_e = kr(d1_r_u,I_v); - obj.dv_e = (obj.e_e'*Dv)'; - obj.du_s = (obj.e_s'*Du)'; - obj.dv_s = kr(I_u,d1_l_v); - obj.du_n = (obj.e_n'*Du)'; - obj.dv_n = kr(I_u,d1_r_v); - - obj.x_u = x_u; - obj.x_v = x_v; - obj.y_u = y_u; - obj.y_v = y_v; - - obj.m = m; - obj.h = [h_u h_v]; - obj.order = order; - obj.grid = g; - - obj.c = c; - obj.J = spdiags(J, 0, m_tot, m_tot); - obj.Ji = spdiags(1./J, 0, m_tot, m_tot); - obj.a11 = a11; - obj.a12 = a12; - obj.a22 = a22; - obj.D = obj.Ji*c^2*(Duu + Duv + Dvu + Dvv); - obj.lambda = lambda; - - obj.Dx = spdiag( y_v./J)*Du + spdiag(-y_u./J)*Dv; - obj.Dy = spdiag(-x_v./J)*Du + spdiag( x_u./J)*Dv; - - obj.gamm_u = h_u*ops_u.borrowing.M.d1; - obj.gamm_v = h_v*ops_v.borrowing.M.d1; - end - - - % Closure functions return the opertors applied to the own doamin to close the boundary - % Penalty functions return the opertors 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'. - % type is a string specifying the type of boundary condition if there are several. - % 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. - function [closure, penalty] = boundary_condition(obj, boundary, type, parameter) - default_arg('type','neumann'); - default_arg('parameter', []); - - [e, d_n, d_t, coeff_n, coeff_t, s, gamm, halfnorm_inv , ~, ~, ~, scale_factor] = obj.get_boundary_ops(boundary); - switch type - % Dirichlet boundary condition - case {'D','d','dirichlet'} - % v denotes the solution in the neighbour domain - tuning = 1.2; - % tuning = 20.2; - [e, d_n, d_t, coeff_n, coeff_t, s, gamm, halfnorm_inv_n, halfnorm_inv_t, halfnorm_t] = obj.get_boundary_ops(boundary); - - a_n = spdiag(coeff_n); - a_t = spdiag(coeff_t); - - F = (s * a_n * d_n' + s * a_t*d_t')'; - - u = obj; - - b1 = gamm*u.lambda./u.a11.^2; - b2 = gamm*u.lambda./u.a22.^2; - - tau = -1./b1 - 1./b2; - tau = tuning * spdiag(tau); - sig1 = 1; - - penalty_parameter_1 = halfnorm_inv_n*(tau + sig1*halfnorm_inv_t*F*e'*halfnorm_t)*e; - - closure = obj.Ji*obj.c^2 * penalty_parameter_1*e'; - penalty = -obj.Ji*obj.c^2 * penalty_parameter_1; - - - % Neumann boundary condition - case {'N','n','neumann'} - c = obj.c; - - a_n = spdiags(coeff_n,0,length(coeff_n),length(coeff_n)); - a_t = spdiags(coeff_t,0,length(coeff_t),length(coeff_t)); - d = (a_n * d_n' + a_t*d_t')'; - - tau1 = -s; - tau2 = 0; - tau = c.^2 * obj.Ji*(tau1*e + tau2*d); - - closure = halfnorm_inv*tau*d'; - penalty = -halfnorm_inv*tau; - - % Characteristic boundary condition - case {'characteristic', 'char', 'c'} - default_arg('parameter', 1); - beta = parameter; - c = obj.c; - - a_n = spdiags(coeff_n,0,length(coeff_n),length(coeff_n)); - a_t = spdiags(coeff_t,0,length(coeff_t),length(coeff_t)); - d = s*(a_n * d_n' + a_t*d_t')'; % outward facing normal derivative - - tau = -c.^2 * 1/beta*obj.Ji*e; - - warning('is this right?! /c?') - closure{1} = halfnorm_inv*tau/c*spdiag(scale_factor)*e'; - closure{2} = halfnorm_inv*tau*beta*d'; - penalty = -halfnorm_inv*tau; - - % Unknown, boundary condition - otherwise - error('No such boundary condition: type = %s',type); - end - end - - function [closure, penalty] = interface(obj, boundary, neighbour_scheme, neighbour_boundary, type) - % u denotes the solution in the own domain - % v denotes the solution in the neighbour domain - tuning = 1.2; - % tuning = 20.2; - [e_u, d_n_u, d_t_u, coeff_n_u, coeff_t_u, s_u, gamm_u, halfnorm_inv_u_n, halfnorm_inv_u_t, halfnorm_u_t, I_u] = obj.get_boundary_ops(boundary); - [e_v, d_n_v, d_t_v, coeff_n_v, coeff_t_v, s_v, gamm_v, halfnorm_inv_v_n, halfnorm_inv_v_t, halfnorm_v_t, I_v] = neighbour_scheme.get_boundary_ops(neighbour_boundary); - - a_n_u = spdiag(coeff_n_u); - a_t_u = spdiag(coeff_t_u); - a_n_v = spdiag(coeff_n_v); - a_t_v = spdiag(coeff_t_v); - - F_u = (s_u * a_n_u * d_n_u' + s_u * a_t_u*d_t_u')'; - F_v = (s_v * a_n_v * d_n_v' + s_v * a_t_v*d_t_v')'; - - u = obj; - v = neighbour_scheme; - - b1_u = gamm_u*u.lambda(I_u)./u.a11(I_u).^2; - b2_u = gamm_u*u.lambda(I_u)./u.a22(I_u).^2; - b1_v = gamm_v*v.lambda(I_v)./v.a11(I_v).^2; - b2_v = gamm_v*v.lambda(I_v)./v.a22(I_v).^2; - - tau = -1./(4*b1_u) -1./(4*b1_v) -1./(4*b2_u) -1./(4*b2_v); - tau = tuning * spdiag(tau); - sig1 = 1/2; - sig2 = -1/2; - - penalty_parameter_1 = halfnorm_inv_u_n*(e_u*tau + sig1*halfnorm_inv_u_t*F_u*e_u'*halfnorm_u_t*e_u); - penalty_parameter_2 = halfnorm_inv_u_n * sig2 * e_u; - - - closure = obj.Ji*obj.c^2 * ( penalty_parameter_1*e_u' + penalty_parameter_2*F_u'); - penalty = obj.Ji*obj.c^2 * (-penalty_parameter_1*e_v' + penalty_parameter_2*F_v'); - end - - % Ruturns the boundary ops and sign for the boundary specified by the string boundary. - % The right boundary is considered the positive boundary - % - % I -- the indecies of the boundary points in the grid matrix - function [e, d_n, d_t, coeff_n, coeff_t, s, gamm, halfnorm_inv_n, halfnorm_inv_t, halfnorm_t, I, scale_factor] = get_boundary_ops(obj, boundary) - - % gridMatrix = zeros(obj.m(2),obj.m(1)); - % gridMatrix(:) = 1:numel(gridMatrix); - - ind = grid.funcToMatrix(obj.grid, 1:prod(obj.m)); - - switch boundary - case 'w' - e = obj.e_w; - d_n = obj.du_w; - d_t = obj.dv_w; - s = -1; - - I = ind(1,:); - coeff_n = obj.a11(I); - coeff_t = obj.a12(I); - scale_factor = sqrt(obj.x_v(I).^2 + obj.y_v(I).^2); - case 'e' - e = obj.e_e; - d_n = obj.du_e; - d_t = obj.dv_e; - s = 1; - - I = ind(end,:); - coeff_n = obj.a11(I); - coeff_t = obj.a12(I); - scale_factor = sqrt(obj.x_v(I).^2 + obj.y_v(I).^2); - case 's' - e = obj.e_s; - d_n = obj.dv_s; - d_t = obj.du_s; - s = -1; - - I = ind(:,1)'; - coeff_n = obj.a22(I); - coeff_t = obj.a12(I); - scale_factor = sqrt(obj.x_u(I).^2 + obj.y_u(I).^2); - case 'n' - e = obj.e_n; - d_n = obj.dv_n; - d_t = obj.du_n; - s = 1; - - I = ind(:,end)'; - coeff_n = obj.a22(I); - coeff_t = obj.a12(I); - scale_factor = sqrt(obj.x_u(I).^2 + obj.y_u(I).^2); - otherwise - error('No such boundary: boundary = %s',boundary); - end - - switch boundary - case {'w','e'} - halfnorm_inv_n = obj.Hiu; - halfnorm_inv_t = obj.Hiv; - halfnorm_t = obj.Hv; - gamm = obj.gamm_u; - case {'s','n'} - halfnorm_inv_n = obj.Hiv; - halfnorm_inv_t = obj.Hiu; - halfnorm_t = obj.Hu; - gamm = obj.gamm_v; - end - end - - function N = size(obj) - N = prod(obj.m); - end - - - end -end \ No newline at end of file
--- a/+scheme/error1d.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,4 +0,0 @@ -function e = error1d(discr, v1, v2) - h = discr.h; - e = sqrt(h*sum((v1-v2).^2)); -end \ No newline at end of file
--- a/+scheme/error2d.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,5 +0,0 @@ -function e = error2d(discr, v1, v2) - % If v1 and v2 are more complex types, something like grid functions... Then we may use .getVectorFrom here! - h = discr.h; - e = sqrt(h.^2*sum((v1-v2).^2)); -end \ No newline at end of file
--- a/+scheme/errorMax.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,3 +0,0 @@ -function e = errorMax(~, v1, v2) - e = max(abs(v1-v2)); -end
--- a/+scheme/errorRelative.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,3 +0,0 @@ -function e = errorRelative(~,v1,v2) - e = sqrt(sum((v1-v2).^2)/sum(v2.^2)); -end \ No newline at end of file
--- a/+scheme/errorSbp.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,6 +0,0 @@ -function e = errorSbp(discr, v1, v2) - % If v1 and v2 are more complex types, something like grid functions... Then we may use .getVectorFrom here! - H = discr.H; - err = v2 - v1; - e = sqrt(err'*H*err); -end \ No newline at end of file
--- a/+scheme/errorVector.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,3 +0,0 @@ -function e = errorVector(~, v1, v2) - e = v2-v1; -end \ No newline at end of file
--- a/+time/+cdiff/cdiff.m Sat Oct 24 20:58:26 2020 -0700 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,16 +0,0 @@ -% Takes a step of -% v_tt = Dv+Ev_t+S -% -% 1/k^2 * (v_next - 2v + v_prev) = Dv + E 1/(2k)(v_next - v_prev) + S -% -function [v_next, v] = cdiff(v, v_prev, k, D, E, S) - % 1/k^2 * (v_next - 2v + v_prev) = Dv + E 1/(2k)(v_next - v_prev) + S - % ekv to - % A v_next = B v + C v_prev + S - I = speye(size(D)); - A = 1/k^2 * I - 1/(2*k)*E; - B = 2/k^2 * I + D; - C = -1/k^2 * I - 1/(2*k)*E; - - v_next = A\(B*v + C*v_prev + S); -end \ No newline at end of file
--- a/+time/Cdiff.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+time/Cdiff.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,36 +1,45 @@ classdef Cdiff < time.Timestepper properties - D - E - S + A, B, C + AA, BB, CC + G k t - v - v_prev + v, v_prev n end methods - % Solves u_tt = Du + Eu_t + S - % D, E, S can either all be constants or all be function handles, - % They can also be omitted by setting them equal to the empty matrix. - % Cdiff(D, E, S, k, t0, n0, v, v_prev) - function obj = Cdiff(D, E, S, k, t0, n0, v, v_prev) - m = length(v); - default_arg('E',sparse(m,m)); - default_arg('S',sparse(m,1)); + % Solves + % A*v_tt + B*v_t + C*v = G(t) + % v(t0) = v0 + % v_t(t0) = v0t + % starting at time t0 with timestep k + % Using + % A*Dp*Dm*v_n + B*D0*v_n + C*v_n = G(t_n) + function obj = Cdiff(A, B, C, G, v0, v0t, k, t0) + m = length(v0); + default_arg('A', speye(m)); + default_arg('B', sparse(m,m)); + default_arg('G', @(t) sparse(m,1)); + default_arg('t0', 0); - obj.D = D; - obj.E = E; - obj.S = S; + obj.A = A; + obj.B = B; + obj.C = C; + obj.G = G; + % Rewrite as AA*v_(n+1) + BB*v_n + CC*v_(n-1) = G(t_n) + obj.AA = A/k^2 + B/(2*k); + obj.BB = -2*A/k^2 + C; + obj.CC = A/k^2 - B/(2*k); obj.k = k; - obj.t = t0; - obj.n = n0; - obj.v = v; - obj.v_prev = v_prev; + obj.v_prev = v0; + obj.v = v0 + k*v0t; + obj.t = t0+k; + obj.n = 1; end function [v,t] = getV(obj) @@ -43,10 +52,21 @@ t = obj.t; end + function E = getEnergy(obj) + v = obj.v; + vp = obj.v_prev; + vt = (obj.v - obj.v_prev)/obj.k; + + E = vt'*obj.A*vt + v'*obj.C*vp; + end + function obj = step(obj) - [obj.v, obj.v_prev] = time.cdiff.cdiff(obj.v, obj.v_prev, obj.k, obj.D, obj.E, obj.S); + v_next = obj.AA\(-obj.BB*obj.v - obj.CC*obj.v_prev + obj.G(obj.t)); + + obj.v_prev = obj.v; + obj.v = v_next; obj.t = obj.t + obj.k; obj.n = obj.n + 1; end end -end \ No newline at end of file +end
--- a/+time/CdiffImplicit.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+time/CdiffImplicit.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,7 +1,8 @@ classdef CdiffImplicit < time.Timestepper properties - A, B, C, G + A, B, C AA, BB, CC + G k t v, v_prev @@ -13,61 +14,36 @@ methods % Solves - % A*u_tt + B*u + C*v_t = G(t) - % u(t0) = f1 - % u_t(t0) = f2 - % starting at time t0 with timestep k - - % TODO: Fix order of matrices - function obj = CdiffImplicit(A, B, C, G, f1, f2, k, t0) - default_arg('A', []); - default_arg('C', []); - default_arg('G', []); - default_arg('f1', 0); - default_arg('f2', 0); + % A*v_tt + B*v_t + C*v = G(t) + % v(t0) = v0 + % v_t(t0) = v0t + % starting at time t0 with timestep + % Using + % A*Dp*Dm*v_n + B*D0*v_n + C*I0*v_n = G(t_n) + function obj = CdiffImplicit(A, B, C, G, v0, v0t, k, t0) + m = length(v0); + default_arg('A', speye(m)); + default_arg('B', sparse(m,m)); + default_arg('G', @(t) sparse(m,1)); default_arg('t0', 0); - m = size(B,1); - - if isempty(A) - A = speye(m); - end - - if isempty(C) - C = sparse(m,m); - end - - if isempty(G) - G = @(t) sparse(m,1); - end - - if isempty(f1) - f1 = sparse(m,1); - end - - if isempty(f2) - f2 = sparse(m,1); - end - obj.A = A; obj.B = B; obj.C = C; obj.G = G; - AA = 1/k^2*A + 1/2*B + 1/(2*k)*C; - BB = -2/k^2*A; - CC = 1/k^2*A + 1/2*B - 1/(2*k)*C; - % AA*v_next + BB*v + CC*v_prev == G(t_n) + % Rewrite as AA*v_(n+1) + BB*v_n + CC*v_(n-1) = G(t_n) + AA = A/k^2 + B/(2*k) + C/2; + BB = -2*A/k^2; + CC = A/k^2 - B/(2*k) + C/2; obj.AA = AA; obj.BB = BB; obj.CC = CC; - v_prev = f1; + v_prev = v0; I = speye(m); - % v = (1/k^2*A)\((1/k^2*A - 1/2*B)*f1 + (1/k*I - 1/2*C)*f2 + 1/2*G(0)); - v = f1 + k*f2; - + v = v0 + k*v0t; if ~issparse(A) || ~issparse(B) || ~issparse(C) error('LU factorization with full pivoting only works for sparse matrices.') @@ -80,7 +56,6 @@ obj.p = p; obj.q = q; - obj.k = k; obj.t = t0+k; obj.n = 1; @@ -94,17 +69,17 @@ end function [vt,t] = getVt(obj) - % Calculate next time step to be able to do centered diff. - v_next = zeros(size(obj.v)); - b = obj.G(obj.t) - obj.BB*obj.v - obj.CC*obj.v_prev; + vt = (obj.v-obj.v_prev)/obj.k; % Could be improved using u_tt = f(u)) + t = obj.t; + end - y = obj.L\b(obj.p); - z = obj.U\y; - v_next(obj.q) = z; + % Calculate the conserved energy (Dm*v_n)^2_A + Im*v_n^2_B + function E = getEnergy(obj) + v = obj.v; + vp = obj.v_prev; + vt = (obj.v - obj.v_prev)/obj.k; - - vt = (v_next-obj.v_prev)/(2*obj.k); - t = obj.t; + E = vt'*obj.A*vt + 1/2*(v'*obj.C*v + vp'*obj.C*vp); end function obj = step(obj) @@ -125,30 +100,3 @@ end end end - - - - - -%%% Derivation -% syms A B C G -% syms n k -% syms f1 f2 - -% v = symfun(sym('v(n)'),n); - - -% d = A/k^2 * (v(n+1) - 2*v(n) +v(n-1)) + B/2*(v(n+1)+v(n-1)) + C/(2*k)*(v(n+1) - v(n-1)) == G -% ic1 = v(0) == f1 -% ic2 = A/k*(v(1)-f1) + k/2*(B*f1 + C*f2 - G) - f2 == 0 - -% c = collect(d, [v(n) v(n-1) v(n+1)]) % (-(2*A)/k^2)*v(n) + (B/2 + A/k^2 - C/(2*k))*v(n - 1) + (B/2 + A/k^2 + C/(2*k))*v(n + 1) == G -% syms AA BB CC -% % AA = B/2 + A/k^2 + C/(2*k) -% % BB = -(2*A)/k^2 -% % CC = B/2 + A/k^2 - C/(2*k) -% s = subs(c, [B/2 + A/k^2 + C/(2*k), -(2*A)/k^2, B/2 + A/k^2 - C/(2*k)], [AA, BB, CC]) - - -% ic2_a = collect(ic2, [v(1) f1 f2]) % (A/k)*v(1) + ((B*k)/2 - A/k)*f1 + ((C*k)/2 - 1)*f2 - (G*k)/2 == 0 -
--- a/+time/Rungekutta4SecondOrder.m Sat Oct 24 20:58:26 2020 -0700 +++ b/+time/Rungekutta4SecondOrder.m Thu Mar 10 16:54:26 2022 +0100 @@ -36,9 +36,32 @@ obj.S = S; obj.m = length(v0); obj.n = 0; - + + % Construct RHS system on first order form. + % 3 different setups are handeled: + % If none of D, E, S are time-dependent (e.g function_handles) + % then a complete matrix of the RHS is constructed. + % If the source term S is time-depdentent, then the first order system matrix M + % is formed via D and E, while S is kept as a function handle + % If D or E are time-dependent, then all terns are treated as function handles. + if ~isa(D, 'function_handle') && ~isa(E, 'function_handle') && isa(S, 'function_handle') + default_arg('D', sparse(obj.m, obj.m)); + default_arg('E', sparse(obj.m, obj.m)); + default_arg('S', @(t)sparse(obj.m, 1)); + + I = speye(obj.m); + O = sparse(obj.m,obj.m); - if isa(D, 'function_handle') || isa(E, 'function_handle') || isa(S, 'function_handle') + obj.M = [ + O, I; + D, E; + ]; + + obj.k = k; + obj.t = t0; + obj.w = [v0; v0t]; + obj.F = @(w,t)obj.rhsTimeDepS(w,t,obj.M,S,obj.m); + elseif isa(D, 'function_handle') || isa(E, 'function_handle') default_arg('D', @(t)sparse(obj.m, obj.m)); default_arg('E', @(t)sparse(obj.m, obj.m)); default_arg('S', @(t)sparse(obj.m, 1) ); @@ -63,7 +86,6 @@ D(t)*w(1:obj.m) + E(t)*w(obj.m+1:end) + S(t); ]; else - default_arg('D', sparse(obj.m, obj.m)); default_arg('E', sparse(obj.m, obj.m)); default_arg('S', sparse(obj.m, 1) ); @@ -110,6 +132,11 @@ function k = getTimeStep(lambda) k = rk4.get_rk4_time_step(lambda); end + + function F = rhsTimeDepS(w,t,M,S,m) + F = M*w; + F(m+1:end) = F(m+1:end) + S(t); + end end end \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/assertLength.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,4 @@ +function assertLength(A,l) + assert(isvector(A), sprintf('Expected ''%s'' to be a vector, got matrix of size %s',inputname(1), toString(size(A)))); + assert(length(A) == l, sprintf('Expected ''%s'' to have length %d, got %d', inputname(1), l, length(A))); +end
--- a/assertSize.m Sat Oct 24 20:58:26 2020 -0700 +++ b/assertSize.m Thu Mar 10 16:54:26 2022 +0100 @@ -2,13 +2,13 @@ function assertSize(A,varargin) if length(varargin) == 1 s = varargin{1}; - errmsg = sprintf('Expected %s to have size %s, got: %s',inputname(1), toString(s), toString(size(A))); - assert(all(size(A) == s), errmsg); + assert(length(size(A)) == length(s), sprintf('Expected ''%s'' to have dimension %d, got %d', inputname(1), length(s), length(size(A)))); + assert(all(size(A) == s), sprintf('Expected ''%s'' to have size %s, got: %s',inputname(1), toString(s), toString(size(A)))); elseif length(varargin) == 2 dim = varargin{1}; s = varargin{2}; - errmsg = sprintf('Expected %s to have size %d along dimension %d, got: %d',inputname(1), s, dim, size(A,dim)); + errmsg = sprintf('Expected ''%s'' to have size %d along dimension %d, got: %d',inputname(1), s, dim, size(A,dim)); assert(size(A,dim) == s, errmsg); else error('Expected 2 or 3 arguments to assertSize()');
--- a/diracDiscr.m Sat Oct 24 20:58:26 2020 -0700 +++ b/diracDiscr.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,116 +1,74 @@ - -function d = diracDiscr(x_s, x, m_order, s_order, H) - % n-dimensional delta function - % x_s: source point coordinate vector, e.g. [x, y] or [x, y, z]. - % x: cell array of grid point column vectors for each dimension. - % m_order: Number of moment conditions - % s_order: Number of smoothness conditions - % H: cell array of 1D norm matrices - - dim = length(x_s); +% n-dimensional delta function +% g: cartesian grid +% x_s: source point coordinate vector, e.g. [x; y] or [x; y; z]. +% m_order: Number of moment conditions +% s_order: Number of smoothness conditions +% H: cell array of 1D norm matrices +function d = diracDiscr(g, x_s, m_order, s_order, H) + assertType(g, 'grid.Cartesian'); + + dim = g.d; d_1D = cell(dim,1); - % If 1D, non-cell input is accepted - if dim == 1 && ~iscell(x) - d = diracDiscr1D(x_s, x, m_order, s_order, H); - - else - for i = 1:dim - d_1D{i} = diracDiscr1D(x_s(i), x{i}, m_order, s_order, H{i}); - end - - d = d_1D{dim}; - for i = dim-1: -1: 1 - % Perform outer product, transpose, and then turn into column vector - d = (d_1D{i}*d')'; - d = d(:); - end + % Allow for non-cell input in 1D + if dim == 1 + H = {H}; + end + % Create 1D dirac discr for each coordinate dir. + for i = 1:dim + d_1D{i} = diracDiscr1D(x_s(i), g.x{i}, m_order, s_order, H{i}); end + d = d_1D{dim}; + for i = dim-1: -1: 1 + % Perform outer product, transpose, and then turn into column vector + d = (d_1D{i}*d')'; + d = d(:); + end end % Helper function for 1D delta functions -function ret = diracDiscr1D(x_0in , x , m_order, s_order, H) - -m = length(x); - -% Return zeros if x0 is outside grid -if(x_0in < x(1) || x_0in > x(end) ) +function ret = diracDiscr1D(x_s, x, m_order, s_order, H) - ret = zeros(size(x)); - -else - - fnorm = diag(H); - eta = abs(x-x_0in); - tot = m_order+s_order; + % Return zeros if x0 is outside grid + if x_s < x(1) || x_s > x(end) + ret = zeros(size(x)); + return + end + + tot_order = m_order+s_order; %This is equiv. to the number of equations solved for S = []; M = []; % Get interior grid spacing - middle = floor(m/2); - h = x(middle+1) - x(middle); - - poss = find(tot*h/2 >= eta); + middle = floor(length(x)/2); + h = x(middle+1) - x(middle); % Use middle point to allow for staggered grids. - % Ensure that poss is not too long - if length(poss) == (tot + 2) - poss = poss(2:end-1); - elseif length(poss) == (tot + 1) - poss = poss(1:end-1); - end - - % Use first tot grid points - if length(poss)<tot && x_0in < x(1) + ceil(tot/2)*h; - index=1:tot; - pol=(x(1:tot)-x(1))/(x(tot)-x(1)); - x_0=(x_0in-x(1))/(x(tot)-x(1)); - norm=fnorm(1:tot)/h; + index = sourceIndices(x_s, x, tot_order, h); - % Use last tot grid points - elseif length(poss)<tot && x_0in > x(end) - ceil(tot/2)*h; - index = length(x)-tot+1:length(x); - pol = (x(end-tot+1:end)-x(end-tot+1))/(x(end)-x(end-tot+1)); - norm = fnorm(end-tot+1:end)/h; - x_0 = (x_0in-x(end-tot+1))/(x(end)-x(end-tot+1)); + polynomial = (x(index)-x(index(1)))/(x(index(end))-x(index(1))); + x_0 = (x_s-x(index(1)))/(x(index(end))-x(index(1))); - % Interior, compensate for round-off errors. - elseif length(poss) < tot - if poss(end)<m - poss = [poss; poss(end)+1]; - else - poss = [poss(1)-1; poss]; - end - pol = (x(poss)-x(poss(1)))/(x(poss(end))-x(poss(1))); - x_0 = (x_0in-x(poss(1)))/(x(poss(end))-x(poss(1))); - norm = fnorm(poss)/h; - index = poss; + quadrature = diag(H); + quadrature_weights = quadrature(index)/h; - % Interior - else - pol = (x(poss)-x(poss(1)))/(x(poss(end))-x(poss(1))); - x_0 = (x_0in-x(poss(1)))/(x(poss(end))-x(poss(1))); - norm = fnorm(poss)/h; - index = poss; - end - - h_pol = pol(2)-pol(1); - b = zeros(m_order+s_order,1); + h_polynomial = polynomial(2)-polynomial(1); + b = zeros(tot_order,1); for i = 1:m_order b(i,1) = x_0^(i-1); end - for i = 1:(m_order+s_order) + for i = 1:tot_order for j = 1:m_order - M(j,i) = pol(i)^(j-1)*h_pol*norm(i); + M(j,i) = polynomial(i)^(j-1)*h_polynomial*quadrature_weights(i); end end - for i = 1:(m_order+s_order) + for i = 1:tot_order for j = 1:s_order - S(j,i) = (-1)^(i-1)*pol(i)^(j-1); + S(j,i) = (-1)^(i-1)*polynomial(i)^(j-1); end end @@ -118,13 +76,31 @@ d = A\b; ret = x*0; - ret(index) = d/h*h_pol; -end - + ret(index) = d/h*h_polynomial; end - +function I = sourceIndices(x_s, x, tot_order, h) + % Find the indices that are within range of of the point source location + I = find(tot_order*h/2 >= abs(x-x_s)); - - + if length(I) > tot_order + if length(I) == tot_order + 2 + I = I(2:end-1); + elseif length(I) == tot_order + 1 + I = I(1:end-1); + end + elseif length(I) < tot_order + if x_s < x(1) + ceil(tot_order/2)*h + I = 1:tot_order; + elseif x_s > x(end) - ceil(tot_order/2)*h + I = length(x)-tot_order+1:length(x); + else + if I(end) < length(x) + I = [I; I(end)+1]; + else + I = [I(1)-1; I]; + end + end + end +end
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/diracDiscrCurve.m Thu Mar 10 16:54:26 2022 +0100 @@ -0,0 +1,63 @@ +% 2-dimensional delta function for single-block curvilinear grid +% x_s: source point coordinate vector, e.g. [x; y] or [x; y; z]. +% g: single-block grid containing the source +% m_order: Number of moment conditions +% s_order: Number of smoothness conditions +% order: Order of SBP derivative approximations +% opSet: Cell array of function handle to opSet generator +function d = diracDiscrCurve(x_s, g, m_order, s_order, order, opSet) + default_arg('order', m_order); + default_arg('opSet', {@sbp.D2Variable, @sbp.D2Variable}); + + dim = length(x_s); + assert(dim == 2, 'diracDiscrCurve: Only implemented for 2d.'); + assertType(g, 'grid.Curvilinear'); + + % Compute Jacobian + J = jacobian(g, opSet, order); + + % Find approximate logical coordinates of point source + X = g.points(); + U = g.logic.points(); + U_interp = scatteredInterpolant(X, U(:,1)); + V_interp = scatteredInterpolant(X, U(:,2)); + uS = U_interp(x_s); + vS = V_interp(x_s); + + % Get quadrature matrices for moment conditions + m = g.size(); + ops_u = opSet{1}(m(1), {0, 1}, order); + ops_v = opSet{2}(m(2), {0, 1}, order); + H_u = ops_u.H; + H_v = ops_v.H; + + % Get delta function for logical grid and scale by Jacobian + d = (1./J).*diracDiscr(g, [uS; vS], m_order, s_order, {H_u, H_v}); +end + +function J = jacobian(g, opSet, order) + m = g.size(); + m_u = m(1); + m_v = m(2); + ops_u = opSet{1}(m_u, {0, 1}, order); + ops_v = opSet{2}(m_v, {0, 1}, order); + I_u = speye(m_u); + I_v = speye(m_v); + + D1_u = ops_u.D1; + D1_v = ops_v.D1; + + Du = kr(D1_u,I_v); + Dv = kr(I_u,D1_v); + + coords = g.points(); + x = coords(:,1); + y = coords(:,2); + + 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; +end
--- a/diracDiscrTest.m Sat Oct 24 20:58:26 2020 -0700 +++ b/diracDiscrTest.m Thu Mar 10 16:54:26 2022 +0100 @@ -2,42 +2,24 @@ tests = functiontests(localfunctions); end -function testLeftGP(testCase) - - orders = [2, 4, 6]; - mom_conds = orders; - - for o = 1:length(orders) - order = orders(o); - mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); - - % Test left boundary grid points - x0s = xl + [0, h, 2*h]; - - for j = 1:length(fs) - f = fs{j}; - fx = f(x); - for i = 1:length(x0s) - x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); - integral = delta'*H*fx; - err = abs(integral - f(x0)); - testCase.verifyLessThan(err, 1e-12); - end - end - end -end +%TODO: +% 1. Test discretizing with smoothness conditions. +% Only discretization with moment conditions currently tested. +% 2. Test using other types of grids. Only equidistant grids currently used. function testLeftRandom(testCase) orders = [2, 4, 6]; mom_conds = orders; + rng(1) % Set seed for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); + [g, H, fs] = setup1D(order, mom_cond); + xl = g.lim{1}{1}; + h = g.scaling(); + x = g.x{1}; % Test random points near left boundary x0s = xl + 2*h*rand(1,10); @@ -47,34 +29,7 @@ fx = f(x); for i = 1:length(x0s) x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); - integral = delta'*H*fx; - err = abs(integral - f(x0)); - testCase.verifyLessThan(err, 1e-12); - end - end - end -end - -function testRightGP(testCase) - - orders = [2, 4, 6]; - mom_conds = orders; - - for o = 1:length(orders) - order = orders(o); - mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); - - % Test right boundary grid points - x0s = xr-[0, h, 2*h]; - - for j = 1:length(fs) - f = fs{j}; - fx = f(x); - for i = 1:length(x0s) - x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H*fx; err = abs(integral - f(x0)); testCase.verifyLessThan(err, 1e-12); @@ -87,11 +42,15 @@ orders = [2, 4, 6]; mom_conds = orders; + rng(1) % Set seed for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); + [g, H, fs] = setup1D(order, mom_cond); + xr = g.lim{1}{2}; + h = g.scaling(); + x = g.x{1}; % Test random points near right boundary x0s = xr - 2*h*rand(1,10); @@ -101,35 +60,7 @@ fx = f(x); for i = 1:length(x0s) x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); - integral = delta'*H*fx; - err = abs(integral - f(x0)); - testCase.verifyLessThan(err, 1e-12); - end - end - end -end - -function testInteriorGP(testCase) - - orders = [2, 4, 6]; - mom_conds = orders; - - for o = 1:length(orders) - order = orders(o); - mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); - - % Test interior grid points - m_half = round(m/2); - x0s = xl + (m_half-1:m_half+1)*h; - - for j = 1:length(fs) - f = fs{j}; - fx = f(x); - for i = 1:length(x0s) - x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H*fx; err = abs(integral - f(x0)); testCase.verifyLessThan(err, 1e-12); @@ -142,11 +73,16 @@ orders = [2, 4, 6]; mom_conds = orders; + rng(1) % Set seed for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); + [g, H, fs] = setup1D(order, mom_cond); + xl = g.lim{1}{1}; + xr = g.lim{1}{2}; + h = g.scaling(); + x = g.x{1}; % Test random points in interior x0s = (xl+2*h) + (xr-xl-4*h)*rand(1,20); @@ -156,7 +92,7 @@ fx = f(x); for i = 1:length(x0s) x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H*fx; err = abs(integral - f(x0)); testCase.verifyLessThan(err, 1e-12); @@ -174,7 +110,11 @@ for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); + [g, H, fs] = setup1D(order, mom_cond); + xl = g.lim{1}{1}; + xr = g.lim{1}{2}; + h = g.scaling(); + x = g.x{1}; % Test points outisde grid x0s = [xl-1.1*h, xr+1.1*h]; @@ -184,7 +124,7 @@ fx = f(x); for i = 1:length(x0s) x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H*fx; err = abs(integral - 0); testCase.verifyLessThan(err, 1e-12); @@ -201,7 +141,8 @@ for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); + [g, H, fs] = setup1D(order, mom_cond); + x = g.x{1}; % Test all grid points x0s = x; @@ -211,7 +152,7 @@ fx = f(x); for i = 1:length(x0s) x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H*fx; err = abs(integral - f(x0)); testCase.verifyLessThan(err, 1e-12); @@ -228,17 +169,18 @@ for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond); + [g, H, fs] = setup1D(order, mom_cond); + x = g.x{1}; % Test halfway between all grid points - x0s = 1/2*( x(2:end)+x(1:end-1) ); + x0s = 1/2*(x(2:end)+x(1:end-1)); for j = 1:length(fs) f = fs{j}; fx = f(x); for i = 1:length(x0s) x0 = x0s(i); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H*fx; err = abs(integral - f(x0)); testCase.verifyLessThan(err, 1e-12); @@ -247,87 +189,6 @@ end end -% function testAllGPStaggered(testCase) - -% orders = [2, 4, 6]; -% mom_conds = orders; - -% for o = 1:length(orders) -% order = orders(o); -% mom_cond = mom_conds(o); -% [xl, xr, m, h, x, H, fs] = setupStaggered(order, mom_cond); - -% % Test all grid points -% x0s = x; - -% for j = 1:length(fs) -% f = fs{j}; -% fx = f(x); -% for i = 1:length(x0s) -% x0 = x0s(i); -% delta = diracDiscr(x0, x, mom_cond, 0, H); -% integral = delta'*H*fx; -% err = abs(integral - f(x0)); -% testCase.verifyLessThan(err, 1e-12); -% end -% end -% end -% end - -% function testHalfGPStaggered(testCase) - -% orders = [2, 4, 6]; -% mom_conds = orders; - -% for o = 1:length(orders) -% order = orders(o); -% mom_cond = mom_conds(o); -% [xl, xr, m, h, x, H, fs] = setupStaggered(order, mom_cond); - -% % Test halfway between all grid points -% x0s = 1/2*( x(2:end)+x(1:end-1) ); - -% for j = 1:length(fs) -% f = fs{j}; -% fx = f(x); -% for i = 1:length(x0s) -% x0 = x0s(i); -% delta = diracDiscr(x0, x, mom_cond, 0, H); -% integral = delta'*H*fx; -% err = abs(integral - f(x0)); -% testCase.verifyLessThan(err, 1e-12); -% end -% end -% end -% end - -% function testRandomStaggered(testCase) - -% orders = [2, 4, 6]; -% mom_conds = orders; - -% for o = 1:length(orders) -% order = orders(o); -% mom_cond = mom_conds(o); -% [xl, xr, m, h, x, H, fs] = setupStaggered(order, mom_cond); - -% % Test random points within grid boundaries -% x0s = xl + (xr-xl)*rand(1,300); - -% for j = 1:length(fs) -% f = fs{j}; -% fx = f(x); -% for i = 1:length(x0s) -% x0 = x0s(i); -% delta = diracDiscr(x0, x, mom_cond, 0, H); -% integral = delta'*H*fx; -% err = abs(integral - f(x0)); -% testCase.verifyLessThan(err, 1e-12); -% end -% end -% end -% end - %=============== 2D tests ============================== function testAllGP2D(testCase) @@ -337,9 +198,9 @@ for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xlims, ylims, m, x, X, ~, H, fs] = setup2D(order, mom_cond); + [g, H, fs] = setup2D(order, mom_cond); H_global = kron(H{1}, H{2}); - + X = g.points(); % Test all grid points x0s = X; @@ -348,7 +209,7 @@ fx = f(X(:,1), X(:,2)); for i = 1:length(x0s) x0 = x0s(i,:); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H_global*fx; err = abs(integral - f(x0(1), x0(2))); testCase.verifyLessThan(err, 1e-12); @@ -361,29 +222,32 @@ orders = [2, 4, 6]; mom_conds = orders; + rng(1) % Set seed for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xlims, ylims, m, x, X, h, H, fs] = setup2D(order, mom_cond); + [g, H, fs] = setup2D(order, mom_cond); H_global = kron(H{1}, H{2}); + X = g.points(); + xl = g.lim{1}{1}; + xr = g.lim{1}{2}; + yl = g.lim{2}{1}; + yr = g.lim{2}{2}; + h = g.scaling(); - xl = xlims{1}; - xr = xlims{2}; - yl = ylims{1}; - yr = ylims{2}; % Test random points, even outside grid Npoints = 100; - x0s = [(xl-3*h{1}) + (xr-xl+6*h{1})*rand(Npoints,1), ... - (yl-3*h{2}) + (yr-yl+6*h{2})*rand(Npoints,1) ]; + x0s = [(xl-3*h(1)) + (xr-xl+6*h(1))*rand(Npoints,1), ... + (yl-3*h(2)) + (yr-yl+6*h(2))*rand(Npoints,1) ]; for j = 1:length(fs) f = fs{j}; fx = f(X(:,1), X(:,2)); for i = 1:length(x0s) x0 = x0s(i,:); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H_global*fx; % Integral should be 0 if point is outside grid @@ -407,9 +271,9 @@ for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xlims, ylims, zlims, m, x, X, h, H, fs] = setup3D(order, mom_cond); + [g, H, fs] = setup3D(order, mom_cond); H_global = kron(kron(H{1}, H{2}), H{3}); - + X = g.points(); % Test all grid points x0s = X; @@ -418,7 +282,7 @@ fx = f(X(:,1), X(:,2), X(:,3)); for i = 1:length(x0s) x0 = x0s(i,:); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H_global*fx; err = abs(integral - f(x0(1), x0(2), x0(3))); testCase.verifyLessThan(err, 1e-12); @@ -431,32 +295,34 @@ orders = [2, 4, 6]; mom_conds = orders; + rng(1) % Set seed for o = 1:length(orders) order = orders(o); mom_cond = mom_conds(o); - [xlims, ylims, zlims, m, x, X, h, H, fs] = setup3D(order, mom_cond); + [g, H, fs] = setup3D(order, mom_cond); H_global = kron(kron(H{1}, H{2}), H{3}); - - xl = xlims{1}; - xr = xlims{2}; - yl = ylims{1}; - yr = ylims{2}; - zl = zlims{1}; - zr = zlims{2}; + X = g.points(); + xl = g.lim{1}{1}; + xr = g.lim{1}{2}; + yl = g.lim{2}{1}; + yr = g.lim{2}{2}; + zl = g.lim{3}{1}; + zr = g.lim{3}{2}; + h = g.scaling(); % Test random points, even outside grid Npoints = 200; - x0s = [(xl-3*h{1}) + (xr-xl+6*h{1})*rand(Npoints,1), ... - (yl-3*h{2}) + (yr-yl+6*h{2})*rand(Npoints,1), ... - (zl-3*h{3}) + (zr-zl+6*h{3})*rand(Npoints,1) ]; + x0s = [(xl-3*h(1)) + (xr-xl+6*h(1))*rand(Npoints,1), ... + (yl-3*h(2)) + (yr-yl+6*h(2))*rand(Npoints,1), ... + (zl-3*h(3)) + (zr-zl+6*h(3))*rand(Npoints,1) ]; for j = 1:length(fs) f = fs{j}; fx = f(X(:,1), X(:,2), X(:,3)); for i = 1:length(x0s) x0 = x0s(i,:); - delta = diracDiscr(x0, x, mom_cond, 0, H); + delta = diracDiscr(g, x0, mom_cond, 0, H); integral = delta'*H_global*fx; % Integral should be 0 if point is outside grid @@ -475,16 +341,14 @@ % ====================================================== % ============== Setup functions ======================= % ====================================================== -function [xl, xr, m, h, x, H, fs] = setup1D(order, mom_cond) +function [g, H, fs] = setup1D(order, mom_cond) % Grid xl = -3; xr = 900; L = xr-xl; m = 101; - h = (xr-xl)/(m-1); g = grid.equidistant(m, {xl, xr}); - x = g.points(); % Quadrature ops = sbp.D2Standard(m, {xl, xr}, order); @@ -498,18 +362,15 @@ end -function [xlims, ylims, m, x, X, h, H, fs] = setup2D(order, mom_cond) +function [g, H, fs] = setup2D(order, mom_cond) % Grid xlims = {-3, 20}; ylims = {-11,5}; Lx = xlims{2} - xlims{1}; Ly = ylims{2} - ylims{1}; - m = [15, 16]; g = grid.equidistant(m, xlims, ylims); - X = g.points(); - x = g.x; % Quadrature opsx = sbp.D2Standard(m(1), xlims, order); @@ -523,16 +384,9 @@ for p = 0:mom_cond-1 fs{p+1} = @(x,y) (x/Lx + y/Ly).^p; end - - % Grid spacing in interior - mm = round(m/2); - hx = x{1}(mm(1)+1) - x{1}(mm(1)); - hy = x{2}(mm(2)+1) - x{2}(mm(2)); - h = {hx, hy}; - end -function [xlims, ylims, zlims, m, x, X, h, H, fs] = setup3D(order, mom_cond) +function [g, H, fs] = setup3D(order, mom_cond) % Grid xlims = {-3, 20}; @@ -541,11 +395,8 @@ Lx = xlims{2} - xlims{1}; Ly = ylims{2} - ylims{1}; Lz = zlims{2} - zlims{1}; - m = [13, 14, 15]; g = grid.equidistant(m, xlims, ylims, zlims); - X = g.points(); - x = g.x; % Quadrature opsx = sbp.D2Standard(m(1), xlims, order); @@ -561,35 +412,4 @@ for p = 0:mom_cond-1 fs{p+1} = @(x,y,z) (x/Lx + y/Ly + z/Lz).^p; end - - % Grid spacing in interior - mm = round(m/2); - hx = x{1}(mm(1)+1) - x{1}(mm(1)); - hy = x{2}(mm(2)+1) - x{2}(mm(2)); - hz = x{3}(mm(3)+1) - x{3}(mm(3)); - h = {hx, hy, hz}; - end - -function [xl, xr, m, h, x, H, fs] = setupStaggered(order, mom_cond) - - % Grid - xl = -3; - xr = 900; - L = xr-xl; - m = 101; - [~, g_dual] = grid.primalDual1D(m, {xl, xr}); - x = g_dual.points(); - h = g_dual.h; - - % Quadrature - ops = sbp.D1Staggered(m, {xl, xr}, order); - H = ops.H_dual; - - % Moment conditions - fs = cell(mom_cond,1); - for p = 0:mom_cond-1 - fs{p+1} = @(x) (x/L).^p; - end - -end
--- a/runtestsAll.m Sat Oct 24 20:58:26 2020 -0700 +++ b/runtestsAll.m Thu Mar 10 16:54:26 2022 +0100 @@ -15,7 +15,7 @@ rootSuite = matlab.unittest.TestSuite.fromFolder(pwd); packageSuites = {}; for i = 1:length(packages) - packageSuites{i} = matlab.unittest.TestSuite.fromPackage(packages{i}); + packageSuites{i} = matlab.unittest.TestSuite.fromPackage(packages{i}, 'IncludingSubpackages', true); end ts = [rootSuite, packageSuites{:}];
--- a/runtestsPackage.m Sat Oct 24 20:58:26 2020 -0700 +++ b/runtestsPackage.m Thu Mar 10 16:54:26 2022 +0100 @@ -1,4 +1,4 @@ function res = runtestsPackage(pkgName) - ts = matlab.unittest.TestSuite.fromPackage(pkgName); + ts = matlab.unittest.TestSuite.fromPackage(pkgName, 'IncludingSubpackages', true); res = ts.run(); -end \ No newline at end of file +end