Mercurial > repos > public > sbplib

annotate +time/SBPInTimeImplicitFormulation.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 5df7f99206b2
children 47e86b5270ad
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rev   line source
460
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1 classdef SBPInTimeImplicitFormulation < 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 properties
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5 A,B
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6 f
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7
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8 k % total time step.
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9
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10 blockSize % number of points in each block
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11 N % Number of components
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12
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13 order
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14 nodes
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15
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16 M,K % System matrices
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17 L,U,p,q % LU factorization of M
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18 e_T
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19
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20 % Time state
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21 t
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22 v
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23 n
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24 end
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25
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26 methods
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27 function obj = SBPInTimeImplicitFormulation(A, B, f, k, t0, v0, TYPE, order, blockSize)
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28
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29 default_arg('TYPE','gauss');
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30 default_arg('f',[]);
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31
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32 if(strcmp(TYPE,'gauss'))
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33 default_arg('order',4)
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34 default_arg('blockSize',4)
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35 else
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36 default_arg('order', 8);
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37 default_arg('blockSize',time.SBPInTimeImplicitFormulation.smallestBlockSize(order,TYPE));
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38 end
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39
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40 obj.A = A;
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41 obj.B = B;
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42
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43 if ~isempty(f)
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44 obj.f = f;
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45 else
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46 obj.f = @(t)sparse(length(v0),1);
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47 end
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48
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49 obj.k = k;
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50 obj.blockSize = blockSize;
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51 obj.N = length(v0);
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52
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53 obj.n = 0;
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54 obj.t = t0;
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55
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56 %==== Build the time discretization matrix =====%
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57 switch TYPE
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58 case 'equidistant'
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59 ops = sbp.D2Standard(blockSize,{0,obj.k},order);
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60 case 'optimal'
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61 ops = sbp.D1Nonequidistant(blockSize,{0,obj.k},order);
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62 case 'minimal'
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63 ops = sbp.D1Nonequidistant(blockSize,{0,obj.k},order,'minimal');
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64 case 'gauss'
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65 ops = sbp.D1Gauss(blockSize,{0,obj.k});
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66 end
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67
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68 I = speye(size(A));
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69 I_t = speye(blockSize,blockSize);
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70
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71 D1 = kron(ops.D1, I);
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72 HI = kron(ops.HI, I);
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73 e_0 = kron(ops.e_l, I);
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74 e_T = kron(ops.e_r, I);
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75 obj.nodes = ops.x;
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76
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77 % Convert to form M*w = K*v0 + f(t)
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78 tau = kron(I_t, A) * e_0;
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79 M = kron(I_t, A)*D1 + HI*tau*e_0' - kron(I_t, B);
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80
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81 K = HI*tau;
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82
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83 obj.M = M;
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84 obj.K = K;
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85 obj.e_T = e_T;
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86
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87 % LU factorization
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88 [obj.L,obj.U,obj.p,obj.q] = lu(obj.M, 'vector');
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89
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90 obj.v = v0;
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91 end
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92
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93 function [v,t] = getV(obj)
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94 v = obj.v;
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95 t = obj.t;
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96 end
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97
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98 function obj = step(obj)
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99 RHS = zeros(obj.blockSize*obj.N,1);
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100
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101 for i = 1:obj.blockSize
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102 RHS((1 + (i-1)*obj.N):(i*obj.N)) = obj.f(obj.t + obj.nodes(i));
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103 end
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104
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105 RHS = RHS + obj.K*obj.v;
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106
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107 y = obj.L\RHS(obj.p);
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108 z = obj.U\y;
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109
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110 w = zeros(size(z));
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111 w(obj.q) = z;
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112
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113 obj.v = obj.e_T'*w;
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114
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115 obj.t = obj.t + obj.k;
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116 obj.n = obj.n + 1;
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117 end
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118 end
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119
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120 methods(Static)
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121 function N = smallestBlockSize(order,TYPE)
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122 default_arg('TYPE','gauss')
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123
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124 switch TYPE
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125 case 'gauss'
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126 N = 4;
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127 end
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128 end
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129 end
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130 end