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annotate +scheme/Hypsyst3dCurve.m @ 354:dbac99d2c318 feature/hypsyst

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Removed inv(Vi) to save time
author Ylva Rydin <ylva.rydin@telia.com>
date Mon, 28 Nov 2016 08:46:28 +0100
parents 7cc3d5bd3692
children 69b078cf8072
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1 classdef Hypsyst3dCurve < scheme.Scheme
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2 properties
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3 m % Number of points in each direction, possibly a vector
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4 n %size of system
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5 h % Grid spacing
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6 X, Y, Z% Values of x and y for each grid point
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7 Yx, Zx, Xy, Zy, Xz, Yz %Grid values for boundary surfaces
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8
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9 xi,eta,zeta
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10 Xi, Eta, Zeta
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11
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12 Eta_xi, Zeta_xi, Xi_eta, Zeta_eta, Xi_zeta, Eta_zeta
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13
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14 X_xi, X_eta, X_zeta,Y_xi,Y_eta,Y_zeta,Z_xi,Z_eta,Z_zeta
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15 Aev
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16
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17 metric_terms
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18
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19 order % Order accuracy for the approximation
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20
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21 D % non-stabalized scheme operator
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22 Aevaluated, Bevaluated, Cevaluated, Eevaluated
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23 Ahat, Bhat, Chat, E
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24 A,B,C
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25
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26 J, Ji
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27
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28 H % Discrete norm
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29 % Norms in the x, y and z directions
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30 Hxii,Hetai,Hzetai, Hzi % Kroneckerd norms. 1'*Hx*v corresponds to integration in the x dir.
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31 Hxi,Heta,Hzeta
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32 I_xi,I_eta,I_zeta, I_N,onesN
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33 e_w, e_e, e_s, e_n, e_b, e_t
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34 index_w, index_e,index_s,index_n, index_b, index_t
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35 params %parameters for the coeficient matrice
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36 end
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39 methods
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40 function obj = Hypsyst3dCurve(m, order, A, B,C, E, params,ti,operator)
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41 xilim ={0 1};
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42 etalim = {0 1};
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43 zetalim = {0 1};
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44
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45 if length(m) == 1
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46 m = [m m m];
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47 end
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48 m_xi = m(1);
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49 m_eta = m(2);
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50 m_zeta = m(3);
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51 m_tot = m_xi*m_eta*m_zeta;
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52 obj.params = params;
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53 obj.n = length(A(obj,0,0,0));
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54
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55 obj.m = m;
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56
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57 obj.order = order;
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58 obj.onesN = ones(obj.n);
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59
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60 switch operator
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61 case 'upwind'
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62 ops_xi = sbp.D1Upwind(m_xi,xilim,order);
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63 ops_eta = sbp.D1Upwind(m_eta,etalim,order);
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64 ops_zeta = sbp.D1Upwind(m_zeta,zetalim,order);
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65 case 'standard'
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66 ops_xi = sbp.D2Standard(m_xi,xilim,order);
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67 ops_eta = sbp.D2Standard(m_eta,etalim,order);
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68 ops_zeta = sbp.D2Standard(m_zeta,zetalim,order);
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69 otherwise
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70 error('Operator not available')
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71 end
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72
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73 obj.xi = ops_xi.x;
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74 obj.eta = ops_eta.x;
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75 obj.zeta = ops_zeta.x;
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76
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77 obj.Xi = kr(obj.xi,ones(m_eta,1),ones(m_zeta,1));%% Que pasa?
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78 obj.Eta = kr(ones(m_xi,1),obj.eta,ones(m_zeta,1));
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79 obj.Zeta = kr(ones(m_xi,1),ones(m_eta,1),obj.zeta);
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80
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81 obj.Eta_xi = kr(obj.eta,ones(m_xi,1));
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82 obj.Zeta_xi = kr(ones(m_eta,1),obj.zeta);
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83
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84 obj.Xi_eta = kr(obj.xi,ones(m_zeta,1));
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85 obj.Zeta_eta = kr(ones(m_xi,1),obj.zeta);
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86
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87 obj.Xi_zeta = kr(obj.xi,ones(m_eta,1));
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88 obj.Eta_zeta = kr(ones(m_zeta,1),obj.eta);
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89
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90 [X,Y,Z] = ti.map(obj.Xi,obj.Eta,obj.Zeta);
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91 obj.X = X;
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92 obj.Y = Y;
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93 obj.Z = Z;
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94
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95 I_n = eye(obj.n);
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96 I_xi = speye(m_xi);
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97 obj.I_xi = I_xi;
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98 I_eta = speye(m_eta);
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99 obj.I_eta = I_eta;
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100 I_zeta = speye(m_zeta);
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101 obj.I_zeta = I_zeta;
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102
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103 I_N=kr(I_n,I_xi,I_eta,I_zeta);
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104
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105 O_xi = ones(m_xi,1);
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106 O_eta = ones(m_eta,1);
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107 O_zeta = ones(m_zeta,1);
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108
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109 obj.Hxii = kr(I_n, ops_xi.HI, I_eta,I_zeta);
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110 obj.Hetai = kr(I_n, I_xi, ops_eta.HI,I_zeta);
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111 obj.Hzetai = kr(I_n, I_xi,I_eta, ops_zeta.HI);
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112 obj.Hxi = ops_xi.H;
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113 obj.Heta = ops_eta.H;
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114 obj.Hzeta = ops_zeta.H;
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115 obj.h = [ops_xi.h ops_eta.h ops_zeta.h];
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116
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117 switch operator
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118 case 'upwind'
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119 D1_xi = kr((ops_xi.Dp+ops_xi.Dm)/2, I_eta,I_zeta);
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120 D1_eta = kr(I_xi, (ops_eta.Dp+ops_eta.Dm)/2,I_zeta);
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121 D1_zeta = kr(I_xi, I_eta,(ops_zeta.Dp+ops_zeta.Dm)/2);
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122 otherwise
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123 D1_xi = kr(ops_xi.D1, I_eta,I_zeta);
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124 D1_eta = kr(I_xi, ops_eta.D1,I_zeta);
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125 D1_zeta = kr(I_xi, I_eta,ops_zeta.D1);
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126 end
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127
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128 obj.e_w = kr(I_n, ops_xi.e_l, I_eta,I_zeta);
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129 obj.e_e = kr(I_n, ops_xi.e_r, I_eta,I_zeta);
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130 obj.e_s = kr(I_n, I_xi, ops_eta.e_l,I_zeta);
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131 obj.e_n = kr(I_n, I_xi, ops_eta.e_r,I_zeta);
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132 obj.e_b = kr(I_n, I_xi, I_eta, ops_zeta.e_l);
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133 obj.e_t = kr(I_n, I_xi, I_eta, ops_zeta.e_r);
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134
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135 obj.A = A;
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136 obj.B = B;
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137 obj.C = C;
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138
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139 obj.X_xi = D1_xi*X;
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140 obj.X_eta = D1_eta*X;
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141 obj.X_zeta = D1_zeta*X;
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142 obj.Y_xi = D1_xi*Y;
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143 obj.Y_eta = D1_eta*Y;
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144 obj.Y_zeta = D1_zeta*Y;
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145 obj.Z_xi = D1_xi*Z;
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146 obj.Z_eta = D1_eta*Z;
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147 obj.Z_zeta = D1_zeta*Z;
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148
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149 D1_xi = kr(I_n,D1_xi);
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150 D1_eta = kr(I_n,D1_eta);
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151 D1_zeta = kr(I_n,D1_zeta);
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152
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153 obj.index_w = (kr(ops_xi.e_l, O_eta,O_zeta)==1);
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154 obj.index_e = (kr(ops_xi.e_r, O_eta,O_zeta)==1);
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155 obj.index_s = (kr(O_xi, ops_eta.e_l,O_zeta)==1);
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156 obj.index_n = (kr(O_xi, ops_eta.e_r,O_zeta)==1);
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157 obj.index_b = (kr(O_xi, O_eta, ops_zeta.e_l)==1);
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158 obj.index_t = (kr(O_xi, O_eta, ops_zeta.e_r)==1);
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159
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160
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161 obj.Ahat = @transform_coefficient_matrix;
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162 obj.Bhat = @transform_coefficient_matrix;
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163 obj.Chat = @transform_coefficient_matrix;
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164 obj.E = @(obj,x,y,z,~,~,~,~,~,~)E(obj,x,y,z);
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165
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166 obj.Aevaluated = obj.evaluateCoefficientMatrix(obj.Ahat,obj.X, obj.Y,obj.Z, obj.X_eta,obj.X_zeta,obj.Y_eta,obj.Y_zeta,obj.Z_eta,obj.Z_zeta);
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167 obj.Bevaluated = obj.evaluateCoefficientMatrix(obj.Bhat,obj.X, obj.Y,obj.Z, obj.X_zeta,obj.X_xi,obj.Y_zeta,obj.Y_xi,obj.Z_zeta,obj.Z_xi);
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168 obj.Cevaluated = obj.evaluateCoefficientMatrix(obj.Chat,obj.X,obj.Y,obj.Z, obj.X_xi,obj.X_eta,obj.Y_xi,obj.Y_eta,obj.Z_xi,obj.Z_eta);
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169 obj.Eevaluated = obj.evaluateCoefficientMatrix(obj.E, obj.X, obj.Y,obj.Z,[],[],[],[],[],[]);
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170
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171 obj.J = obj.X_xi.*obj.Y_eta.*obj.Z_zeta...
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172 +obj.X_zeta.*obj.Y_xi.*obj.Z_eta...
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173 +obj.X_eta.*obj.Y_zeta.*obj.Z_xi...
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174 -obj.X_xi.*obj.Y_zeta.*obj.Z_eta...
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175 -obj.X_eta.*obj.Y_xi.*obj.Z_zeta...
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176 -obj.X_zeta.*obj.Y_eta.*obj.Z_xi;
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177
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178 obj.Ji = kr(I_n,spdiags(1./obj.J,0,m_tot,m_tot));
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179
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180
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181 switch operator
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182 case 'upwind'
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183 alphaA = max(eig(obj.Ahat(obj,obj.X(end), obj.Y(end),obj.Z(end), obj.X_eta(end),obj.X_zeta(end),obj.Y_eta(end),obj.Y_zeta(end),obj.Z_eta(end),obj.Z_zeta(end))));
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184 alphaB = max(eig(obj.Bhat(obj,obj.X(end), obj.Y(end),obj.Z(end), obj.X_zeta(end),obj.X_xi(end),obj.Y_zeta(end),obj.Y_xi(end),obj.Z_zeta(end),obj.Z_xi(end))));
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185 alphaC = max(eig(obj.Chat(obj,obj.X(end), obj.Y(end),obj.Z(end), obj.X_xi(end),obj.X_eta(end),obj.Y_xi(end),obj.Y_eta(end),obj.Z_xi(end),obj.Z_eta(end))));
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186
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187 Ap = (obj.Aevaluated+alphaA*I_N)/2;
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188 Am = (obj.Aevaluated-alphaA*I_N)/2;
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189 Bp = (obj.Bevaluated+alphaB*I_N)/2;
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190 Bm = (obj.Bevaluated-alphaB*I_N)/2;
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191 Cp = (obj.Cevaluated+alphaC*I_N)/2;
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192 Cm = (obj.Cevaluated-alphaC*I_N)/2;
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193
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194 Dpxi = kr(I_n, ops_xi.Dp, I_eta,I_zeta);
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195 Dmxi = kr(I_n, ops_xi.Dm, I_eta,I_zeta);
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196 Dpeta = kr(I_n, I_xi, ops_eta.Dp,I_zeta);
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197 Dmeta = kr(I_n, I_xi, ops_eta.Dm,I_zeta);
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198 Dpzeta = kr(I_n, I_xi, I_eta,ops_zeta.Dp);
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199 Dmzeta = kr(I_n, I_xi, I_eta,ops_zeta.Dm);
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200
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201 obj.D = obj.Ji*(-Am*Dpxi-Ap*Dmxi-Bm*Dpeta-Bp*Dmeta-Cm*Dpzeta-Cp*Dmzeta)-obj.Eevaluated;
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202 otherwise
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203 obj.D = obj.Ji*(-obj.Aevaluated*D1_xi-obj.Bevaluated*D1_eta -obj.Cevaluated*D1_zeta)-obj.Eevaluated;
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204 end
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205
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206
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207 end
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208
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209 function [ret] = transform_coefficient_matrix(obj,x,y,z,x_1,x_2,y_1,y_2,z_1,z_2)
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210 ret = obj.A(obj,x,y,z).*(y_1.*z_2-z_1.*y_2);
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211 ret = ret+obj.B(obj,x,y,z).*(x_2.*z_1-x_1.*z_2);
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212 ret = ret+obj.C(obj,x,y,z).*(x_1.*y_2-x_2.*y_1);
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213 end
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214
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215
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216 % Closure functions return the opertors applied to the own doamin to close the boundary
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217 % Penalty functions return the opertors to force the solution. In the case of an interface it returns the operator applied to the other doamin.
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218 % boundary is a string specifying the boundary e.g. 'l','r' or 'e','w','n','s'.
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219 % type is a string specifying the type of boundary condition if there are several.
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220 % data is a function returning the data that should be applied at the boundary.
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221 function [closure, penalty] = boundary_condition(obj,boundary,type,L)
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222 default_arg('type','char');
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223 BM = boundary_matrices(obj,boundary);
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224
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225 switch type
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226 case{'c','char'}
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227 [closure,penalty] = boundary_condition_char(obj,BM);
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228 case{'general'}
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229 [closure,penalty] = boundary_condition_general(obj,BM,boundary,L);
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230 otherwise
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231 error('No such boundary condition')
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232 end
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233 end
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234
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235 function [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary)
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236 error('An interface function does not exist yet');
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237 end
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238
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239 function N = size(obj)
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240 N = obj.m;
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241 end
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242
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243 function [ret] = evaluateCoefficientMatrix(obj,mat, X, Y, Z , x_1 , x_2 , y_1 , y_2 , z_1 , z_2)
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244 params = obj.params;
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245 side = max(length(X),length(Y));
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246 if isa(mat,'function_handle')
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247 [rows,cols] = size(mat(obj,0,0,0,0,0,0,0,0,0));
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248 x_1 = kr(obj.onesN,x_1);
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249 x_2 = kr(obj.onesN,x_2);
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250 y_1 = kr(obj.onesN,y_1);
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251 y_2 = kr(obj.onesN,y_2);
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252 z_1 = kr(obj.onesN,z_1);
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253 z_2 = kr(obj.onesN,z_2);
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254 matVec = mat(obj,X',Y',Z',x_1',x_2',y_1',y_2',z_1',z_2');
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255 matVec = sparse(matVec);
350
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256 else
354
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257 matVec = mat;
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258 [rows,cols] = size(matVec);
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diff changeset
259 side = max(length(X),length(Y));
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260 cols = cols/side;
350
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261 end
354
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262 ret = cell(rows,cols);
351
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263
350
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264
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265 for ii=1:rows
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266 for jj=1:cols
354
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267 ret{ii,jj} = diag(matVec(ii,(jj-1)*side+1:jj*side));
350
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268 end
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269 end
351
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270
354
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271 ret = cell2mat(ret);
350
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272 end
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273
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274
354
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275 function [BM] = boundary_matrices(obj,boundary)
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276 params = obj.params;
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277 BM.boundary = boundary;
350
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278 switch boundary
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279 case {'w','W','west'}
354
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280 BM.e_ = obj.e_w;
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281 mat = obj.Ahat;
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282 BM.boundpos = 'l';
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283 BM.Hi = obj.Hxii;
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284 BM.index = obj.index_w;
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285 BM.x_1 = obj.X_eta(BM.index);
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286 BM.x_2 = obj.X_zeta(BM.index);
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287 BM.y_1 = obj.Y_eta(BM.index);
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288 BM.y_2 = obj.Y_zeta(BM.index);
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289 BM.z_1 = obj.Z_eta(BM.index);
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290 BM.z_2 = obj.Z_zeta(BM.index);
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291 case {'e','E','east'}
354
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292 BM.e_ = obj.e_e;
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293 mat = obj.Ahat;
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294 BM.boundpos = 'r';
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295 BM.Hi = obj.Hxii;
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296 BM.index = obj.index_e;
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297 BM.x_1 = obj.X_eta(BM.index);
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298 BM.x_2 = obj.X_zeta(BM.index);
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299 BM.y_1 = obj.Y_eta(BM.index);
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300 BM.y_2 = obj.Y_zeta(BM.index);
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301 BM.z_1 = obj.Z_eta(BM.index);
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302 BM.z_2 = obj.Z_zeta(BM.index);
350
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303 case {'s','S','south'}
354
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304 BM.e_ = obj.e_s;
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diff changeset
305 mat = obj.Bhat;
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306 BM.boundpos = 'l';
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307 BM.Hi = obj.Hetai;
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diff changeset
308 BM.index = obj.index_s;
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diff changeset
309 BM.x_1 = obj.X_zeta(BM.index);
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310 BM.x_2 = obj.X_xi(BM.index);
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311 BM.y_1 = obj.Y_zeta(BM.index);
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312 BM.y_2 = obj.Y_xi(BM.index);
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313 BM.z_1 = obj.Z_zeta(BM.index);
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314 BM.z_2 = obj.Z_xi(BM.index);
350
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315 case {'n','N','north'}
354
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diff changeset
316 BM.e_ = obj.e_n;
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317 mat = obj.Bhat;
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318 BM.boundpos = 'r';
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319 BM.Hi = obj.Hetai;
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320 BM.index = obj.index_n;
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321 BM.x_1 = obj.X_zeta(BM.index);
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322 BM.x_2 = obj.X_xi(BM.index);
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323 BM.y_1 = obj.Y_zeta(BM.index);
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324 BM.y_2 = obj.Y_xi(BM.index);
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325 BM.z_1 = obj.Z_zeta(BM.index);
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326 BM.z_2 = obj.Z_xi(BM.index);
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327 case{'b','B','Bottom'}
354
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328 BM.e_ = obj.e_b;
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329 mat = obj.Chat;
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330 BM.boundpos = 'l';
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331 BM.Hi = obj.Hzetai;
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332 BM.index = obj.index_b;
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333 BM.x_1 = obj.X_xi(BM.index);
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334 BM.x_2 = obj.X_eta(BM.index);
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335 BM.y_1 = obj.Y_xi(BM.index);
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336 BM.y_2 = obj.Y_eta(BM.index);
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337 BM.z_1 = obj.Z_xi(BM.index);
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338 BM.z_2 = obj.Z_eta(BM.index);
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339 case{'t','T','Top'}
354
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diff changeset
340 BM.e_ = obj.e_t;
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341 mat = obj.Chat;
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342 BM.boundpos = 'r';
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343 BM.Hi = obj.Hzetai;
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344 BM.index = obj.index_t;
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345 BM.x_1 = obj.X_xi(BM.index);
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346 BM.x_2 = obj.X_eta(BM.index);
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347 BM.y_1 = obj.Y_xi(BM.index);
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348 BM.y_2 = obj.Y_eta(BM.index);
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diff changeset
349 BM.z_1 = obj.Z_xi(BM.index);
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350 BM.z_2 = obj.Z_eta(BM.index);
350
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351 end
354
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diff changeset
352 [BM.V,BM.Vi,BM.D,signVec] = obj.matrixDiag(mat,obj.X(BM.index),obj.Y(BM.index),obj.Z(BM.index),...
350
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353 BM.x_1,BM.x_2,BM.y_1,BM.y_2,BM.z_1,BM.z_2);
354
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diff changeset
354 BM.side = sum(BM.index);
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diff changeset
355 BM.pos = signVec(1); BM.zeroval=signVec(2); BM.neg=signVec(3);
350
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356 end
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357
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358
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359 function [closure, penalty]=boundary_condition_char(obj,BM)
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diff changeset
360 side = BM.side;
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361 pos = BM.pos;
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362 neg = BM.neg;
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diff changeset
363 zeroval = BM.zeroval;
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364 V = BM.V;
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365 Vi = BM.Vi;
354
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diff changeset
366 Hi = BM.Hi;
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diff changeset
367 D = BM.D;
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diff changeset
368 e_ = BM.e_;
350
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369
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370 switch BM.boundpos
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371 case {'l'}
354
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diff changeset
372 tau = sparse(obj.n*side,pos);
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diff changeset
373 Vi_plus = Vi(1:pos,:);
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diff changeset
374 tau(1:pos,:) = -abs(D(1:pos,1:pos));
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diff changeset
375 closure = Hi*e_*V*tau*Vi_plus*e_';
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diff changeset
376 penalty = -Hi*e_*V*tau*Vi_plus;
350
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diff changeset
377 case {'r'}
354
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diff changeset
378 tau = sparse(obj.n*side,neg);
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diff changeset
379 tau((pos+zeroval)+1:obj.n*side,:) = -abs(D((pos+zeroval)+1:obj.n*side,(pos+zeroval)+1:obj.n*side));
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diff changeset
380 Vi_minus = Vi((pos+zeroval)+1:obj.n*side,:);
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diff changeset
381 closure = Hi*e_*V*tau*Vi_minus*e_';
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diff changeset
382 penalty = -Hi*e_*V*tau*Vi_minus;
350
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383 end
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parents:
diff changeset
384 end
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parents:
diff changeset
385
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diff changeset
386
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387 function [closure,penalty]=boundary_condition_general(obj,BM,boundary,L)
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388 side = BM.side;
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389 pos = BM.pos;
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390 neg = BM.neg;
354
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diff changeset
391 zeroval = BM.zeroval;
350
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392 V = BM.V;
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393 Vi = BM.Vi;
354
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diff changeset
394 Hi = BM.Hi;
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diff changeset
395 D = BM.D;
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diff changeset
396 e_ = BM.e_;
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diff changeset
397 index = BM.index;
350
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398
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diff changeset
399 switch BM.boundary
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400 case{'b','B','bottom'}
354
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diff changeset
401 Ji_vec = diag(obj.Ji);
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diff changeset
402 Ji = diag(Ji_vec(index));
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diff changeset
403 Zeta_x = Ji*(obj.Y_xi(index).*obj.Z_eta(index)-obj.Z_xi(index).*obj.Y_eta(index));
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diff changeset
404 Zeta_y = Ji*(obj.X_eta(index).*obj.Z_xi(index)-obj.X_xi(index).*obj.Z_eta(index));
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diff changeset
405 Zeta_z = Ji*(obj.X_xi(index).*obj.Y_eta(index)-obj.Y_xi(index).*obj.X_eta(index));
350
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406
354
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diff changeset
407 L = obj.evaluateCoefficientMatrix(L,Zeta_x,Zeta_y,Zeta_z,[],[],[],[],[],[]);
350
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408 end
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parents:
diff changeset
409
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parents:
diff changeset
410 switch BM.boundpos
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411 case {'l'}
354
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diff changeset
412 tau = sparse(obj.n*side,pos);
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parents: 351
diff changeset
413 Vi_plus = Vi(1:pos,:);
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parents: 351
diff changeset
414 Vi_minus = Vi(pos+zeroval+1:obj.n*side,:);
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diff changeset
415 V_plus = V(:,1:pos);
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parents: 351
diff changeset
416 V_minus = V(:,(pos+zeroval)+1:obj.n*side);
350
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417
354
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diff changeset
418 tau(1:pos,:) = -abs(D(1:pos,1:pos));
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parents: 351
diff changeset
419 R = -inv(L*V_plus)*(L*V_minus);
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parents: 351
diff changeset
420 closure = Hi*e_*V*tau*(Vi_plus-R*Vi_minus)*e_';
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parents: 351
diff changeset
421 penalty = -Hi*e_*V*tau*inv(L*V_plus)*L;
350
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422 case {'r'}
354
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diff changeset
423 tau = sparse(obj.n*side,neg);
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parents: 351
diff changeset
424 tau((pos+zeroval)+1:obj.n*side,:) = -abs(D((pos+zeroval)+1:obj.n*side,(pos+zeroval)+1:obj.n*side));
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parents: 351
diff changeset
425 Vi_plus = Vi(1:pos,:);
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parents: 351
diff changeset
426 Vi_minus = Vi((pos+zeroval)+1:obj.n*side,:);
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427
354
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diff changeset
428 V_plus = V(:,1:pos);
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parents: 351
diff changeset
429 V_minus = V(:,(pos+zeroval)+1:obj.n*side);
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parents: 351
diff changeset
430 R = -inv(L*V_minus)*(L*V_plus);
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parents: 351
diff changeset
431 closure = Hi*e_*V*tau*(Vi_minus-R*Vi_plus)*e_';
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parents: 351
diff changeset
432 penalty = -Hi*e_*V*tau*inv(L*V_minus)*L;
350
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diff changeset
433 end
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parents:
diff changeset
434 end
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parents:
diff changeset
435
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436
354
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parents: 351
diff changeset
437 function [V,Vi, D,signVec] = matrixDiag(obj,mat,x,y,z,x_1,x_2,y_1,y_2,z_1,z_2)
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diff changeset
438 params = obj.params;
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diff changeset
439 eps = 10^(-10);
350
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440 if(sum(abs(x_1))>eps)
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parents:
diff changeset
441 syms x_1s
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442 else
354
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diff changeset
443 x_1s = 0;
350
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444 end
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parents:
diff changeset
445
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446 if(sum(abs(x_2))>eps)
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diff changeset
447 syms x_2s;
350
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448 else
354
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diff changeset
449 x_2s = 0;
350
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450 end
354
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parents: 351
diff changeset
451
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parents: 351
diff changeset
452
350
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453 if(sum(abs(y_1))>eps)
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Ylva Rydin <ylva.rydin@telia.com>
parents:
diff changeset
454 syms y_1s
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455 else
354
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diff changeset
456 y_1s = 0;
350
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diff changeset
457 end
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parents:
diff changeset
458
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diff changeset
459 if(sum(abs(y_2))>eps)
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parents: 351
diff changeset
460 syms y_2s;
350
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461 else
354
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diff changeset
462 y_2s = 0;
350
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463 end
354
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parents: 351
diff changeset
464
350
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diff changeset
465 if(sum(abs(z_1))>eps)
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parents:
diff changeset
466 syms z_1s
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diff changeset
467 else
354
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parents: 351
diff changeset
468 z_1s = 0;
350
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parents:
diff changeset
469 end
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parents:
diff changeset
470
5d5652fe826a A commit before I try resolving the performance issues
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parents:
diff changeset
471 if(sum(abs(z_2))>eps)
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parents: 351
diff changeset
472 syms z_2s;
350
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parents:
diff changeset
473 else
354
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parents: 351
diff changeset
474 z_2s = 0;
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parents: 351
diff changeset
475 end
350
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parents:
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476
354
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parents: 351
diff changeset
477 syms xs ys zs
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parents: 351
diff changeset
478 [V, D] = eig(mat(obj,xs,ys,zs,x_1s,x_2s,y_1s,y_2s,z_1s,z_2s));
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parents: 351
diff changeset
479 Vi = inv(V);
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parents: 351
diff changeset
480 % syms x_1s x_2s y_1s y_2s z_1s z_2s
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parents: 351
diff changeset
481 xs = x;
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parents: 351
diff changeset
482 ys = y;
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parents: 351
diff changeset
483 zs = z;
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parents: 351
diff changeset
484 x_1s = x_1;
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parents: 351
diff changeset
485 x_2s = x_2;
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parents: 351
diff changeset
486 y_1s = y_1;
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parents: 351
diff changeset
487 y_2s = y_2;
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parents: 351
diff changeset
488 z_1s = z_1;
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parents: 351
diff changeset
489 z_2s = z_2;
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parents: 351
diff changeset
490
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parents: 351
diff changeset
491 side = max(length(x),length(y));
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parents: 351
diff changeset
492 Dret = zeros(obj.n,side*obj.n);
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parents: 351
diff changeset
493 Vret = zeros(obj.n,side*obj.n);
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parents: 351
diff changeset
494 Viret = zeros(obj.n,side*obj.n);
350
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parents:
diff changeset
495
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parents:
diff changeset
496 for ii=1:obj.n
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497 for jj=1:obj.n
354
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parents: 351
diff changeset
498 Dret(jj,(ii-1)*side+1:side*ii) = eval(D(jj,ii));
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parents: 351
diff changeset
499 Vret(jj,(ii-1)*side+1:side*ii) = eval(V(jj,ii));
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parents: 351
diff changeset
500 Viret(jj,(ii-1)*side+1:side*ii) = eval(Vi(jj,ii));
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501 end
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parents:
diff changeset
502 end
354
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parents: 351
diff changeset
503
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parents: 351
diff changeset
504 D = sparse(Dret);
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parents: 351
diff changeset
505 V = sparse(Vret);
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parents: 351
diff changeset
506 Vi = sparse(Viret);
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parents: 351
diff changeset
507 V = obj.evaluateCoefficientMatrix(V,x,y,z,x_1,x_2,y_1,y_2,z_1,z_2);
dbac99d2c318 Removed inv(Vi) to save time
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diff changeset
508 D = obj.evaluateCoefficientMatrix(D,x,y,z,x_1,x_2,y_1,y_2,z_1,z_2);
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
509 Vi = obj.evaluateCoefficientMatrix(Vi,x,y,z,x_1,x_2,y_1,y_2,z_1,z_2);
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
510 DD = diag(D);
350
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diff changeset
511
354
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
512 poseig = (DD>0);
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
513 zeroeig = (DD==0);
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
514 negeig = (DD<0);
350
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515
354
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
516 D = diag([DD(poseig); DD(zeroeig); DD(negeig)]);
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
517 V = [V(:,poseig) V(:,zeroeig) V(:,negeig)];
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
518 Vi = [Vi(poseig,:); Vi(zeroeig,:); Vi(negeig,:)];
dbac99d2c318 Removed inv(Vi) to save time
Ylva Rydin <ylva.rydin@telia.com>
parents: 351
diff changeset
519 signVec = [sum(poseig),sum(zeroeig),sum(negeig)];
350
5d5652fe826a A commit before I try resolving the performance issues
Ylva Rydin <ylva.rydin@telia.com>
parents:
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520 end
5d5652fe826a A commit before I try resolving the performance issues
Ylva Rydin <ylva.rydin@telia.com>
parents:
diff changeset
521 end
354
dbac99d2c318 Removed inv(Vi) to save time
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parents: 351
diff changeset
522 end