Mercurial > repos > public > sbplib

annotate +time/SBPInTimeScaled.m @ 1037:2d7ba44340d0 feature/burgers1d

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Pass scheme specific parameters as cell array. This will enabale constructDiffOps to be more general. In addition, allow for schemes returning function handles as diffOps, which is currently how non-linear schemes such as Burgers1d are implemented.
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Fri, 18 Jan 2019 09:02:02 +0100
parents e95a0f2f7a8d
children 47e86b5270ad
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746
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1 classdef SBPInTimeScaled < time.Timestepper
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2 % The SBP in time method.
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3 % Implemented for A*v_t = B*v + f(t), v(0) = v0
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4 % The resulting system of equations is
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5 % M*u_next= K*u_prev_end + f
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6 properties
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7 A,B
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8 f
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9
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10 k % total time step.
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11
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12 blockSize % number of points in each block
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13 N % Number of components
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14
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15 order
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16 nodes
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17
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18 Mtilde,Ktilde % System matrices
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19 L,U,p,q % LU factorization of M
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20 e_T
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21
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22 scaling
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23 S, Sinv % Scaling matrices
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24
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25 % Time state
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26 t
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27 vtilde
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28 n
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29 end
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30
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31 methods
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32 function obj = SBPInTimeScaled(A, B, f, k, t0, v0, scaling, TYPE, order, blockSize)
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33 default_arg('TYPE','gauss');
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34 default_arg('f',[]);
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35
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36 if(strcmp(TYPE,'gauss'))
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37 default_arg('order',4)
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38 default_arg('blockSize',4)
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39 else
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40 default_arg('order', 8);
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41 default_arg('blockSize',time.SBPInTimeImplicitFormulation.smallestBlockSize(order,TYPE));
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42 end
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43
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44 obj.A = A;
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45 obj.B = B;
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46 obj.scaling = scaling;
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47
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48 if ~isempty(f)
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49 obj.f = f;
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50 else
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51 obj.f = @(t)sparse(length(v0),1);
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52 end
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53
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54 obj.k = k;
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55 obj.blockSize = blockSize;
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56 obj.N = length(v0);
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57
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58 obj.n = 0;
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59 obj.t = t0;
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60
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61 %==== Build the time discretization matrix =====%
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62 switch TYPE
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63 case 'equidistant'
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64 ops = sbp.D2Standard(blockSize,{0,obj.k},order);
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65 case 'optimal'
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66 ops = sbp.D1Nonequidistant(blockSize,{0,obj.k},order);
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67 case 'minimal'
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68 ops = sbp.D1Nonequidistant(blockSize,{0,obj.k},order,'minimal');
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69 case 'gauss'
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70 ops = sbp.D1Gauss(blockSize,{0,obj.k});
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71 end
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72
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73 I = speye(size(A));
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74 I_t = speye(blockSize,blockSize);
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75
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76 D1 = kron(ops.D1, I);
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77 HI = kron(ops.HI, I);
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78 e_0 = kron(ops.e_l, I);
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79 e_T = kron(ops.e_r, I);
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80 obj.nodes = ops.x;
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81
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82 % Convert to form M*w = K*v0 + f(t)
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83 tau = kron(I_t, A) * e_0;
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84 M = kron(I_t, A)*D1 + HI*tau*e_0' - kron(I_t, B);
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85
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86 K = HI*tau;
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87
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88 obj.S = kron(I_t, spdiag(scaling));
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89 obj.Sinv = kron(I_t, spdiag(1./scaling));
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90
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91 obj.Mtilde = obj.Sinv*M*obj.S;
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92 obj.Ktilde = obj.Sinv*K*spdiag(scaling);
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93 obj.e_T = e_T;
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94
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95
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96 % LU factorization
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97 [obj.L,obj.U,obj.p,obj.q] = lu(obj.Mtilde, 'vector');
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98
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99 obj.vtilde = (1./obj.scaling).*v0;
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100 end
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101
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102 function [v,t] = getV(obj)
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103 v = obj.scaling.*obj.vtilde;
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104 t = obj.t;
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105 end
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106
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107 function obj = step(obj)
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108 forcing = zeros(obj.blockSize*obj.N,1);
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109
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110 for i = 1:obj.blockSize
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111 forcing((1 + (i-1)*obj.N):(i*obj.N)) = obj.f(obj.t + obj.nodes(i));
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112 end
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113
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114 RHS = obj.Sinv*forcing + obj.Ktilde*obj.vtilde;
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115
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116 y = obj.L\RHS(obj.p);
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117 z = obj.U\y;
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118
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119 w = zeros(size(z));
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120 w(obj.q) = z;
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121
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122 obj.vtilde = obj.e_T'*w;
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123
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124 obj.t = obj.t + obj.k;
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125 obj.n = obj.n + 1;
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126 end
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127 end
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128
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129 methods(Static)
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130 function N = smallestBlockSize(order,TYPE)
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131 default_arg('TYPE','gauss')
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132
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133 switch TYPE
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134 case 'gauss'
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135 N = 4;
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136 end
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137 end
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138 end
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139 end