1 | |
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2 | #include "OgreOdePrecompiledHeaders.h" |
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3 | |
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4 | #include "OgreOdeEigenSolver.h" |
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5 | |
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6 | using namespace OgreOde; |
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7 | using namespace Ogre; |
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8 | |
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9 | void EigenSolver::DecrSortEigenStuff3 () |
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10 | { |
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11 | Tridiagonal3(); |
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12 | QLAlgorithm(); |
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13 | DecreasingSort(); |
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14 | GuaranteeRotation(); |
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15 | } |
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16 | |
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17 | void EigenSolver::Tridiagonal3 () |
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18 | { |
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19 | const Ogre::Real fM00 = m_kMat[0][0]; |
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20 | Ogre::Real fM01 = m_kMat[0][1]; |
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21 | Real fM02 = m_kMat[0][2]; |
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22 | const Ogre::Real fM11 = m_kMat[1][1]; |
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23 | const Ogre::Real fM12 = m_kMat[1][2]; |
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24 | const Ogre::Real fM22 = m_kMat[2][2]; |
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25 | |
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26 | m_afDiag[0] = fM00; |
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27 | m_afSubd[2] = (Real)0.0; |
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28 | if ( fM02 != (Real)0.0 ) |
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29 | { |
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30 | const Ogre::Real fLength = sqrtf(fM01*fM01+fM02*fM02); |
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31 | const Ogre::Real fInvLength = ((Real)1.0)/fLength; |
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32 | fM01 *= fInvLength; |
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33 | fM02 *= fInvLength; |
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34 | const Ogre::Real fQ = ((Real)2.0)*fM01*fM12+fM02*(fM22-fM11); |
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35 | m_afDiag[1] = fM11+fM02*fQ; |
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36 | m_afDiag[2] = fM22-fM02*fQ; |
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37 | m_afSubd[0] = fLength; |
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38 | m_afSubd[1] = fM12-fM01*fQ; |
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39 | m_kMat[0][0] = (Real)1.0; |
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40 | m_kMat[0][1] = (Real)0.0; |
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41 | m_kMat[0][2] = (Real)0.0; |
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42 | m_kMat[1][0] = (Real)0.0; |
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43 | m_kMat[1][1] = fM01; |
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44 | m_kMat[1][2] = fM02; |
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45 | m_kMat[2][0] = (Real)0.0; |
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46 | m_kMat[2][1] = fM02; |
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47 | m_kMat[2][2] = -fM01; |
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48 | } |
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49 | else |
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50 | { |
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51 | m_afDiag[1] = fM11; |
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52 | m_afDiag[2] = fM22; |
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53 | m_afSubd[0] = fM01; |
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54 | m_afSubd[1] = fM12; |
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55 | m_kMat[0][0] = (Real)1.0; |
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56 | m_kMat[0][1] = (Real)0.0; |
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57 | m_kMat[0][2] = (Real)0.0; |
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58 | m_kMat[1][0] = (Real)0.0; |
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59 | m_kMat[1][1] = (Real)1.0; |
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60 | m_kMat[1][2] = (Real)0.0; |
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61 | m_kMat[2][0] = (Real)0.0; |
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62 | m_kMat[2][1] = (Real)0.0; |
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63 | m_kMat[2][2] = (Real)1.0; |
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64 | } |
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65 | } |
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66 | |
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67 | bool EigenSolver::QLAlgorithm () |
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68 | { |
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69 | const int iMaxIter = 32; |
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70 | |
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71 | for (int i0 = 0; i0 < m_iSize; i0++) |
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72 | { |
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73 | int i1; |
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74 | for (i1 = 0; i1 < iMaxIter; i1++) |
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75 | { |
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76 | int i2; |
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77 | for (i2 = i0; i2 <= m_iSize-2; i2++) |
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78 | { |
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79 | Real fTmp = fabs(m_afDiag[i2]) + fabs(m_afDiag[i2+1]); |
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80 | if ( fabs(m_afSubd[i2]) + fTmp == fTmp ) break; |
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81 | } |
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82 | if ( i2 == i0 ) break; |
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83 | |
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84 | Real fG = (m_afDiag[i0+1] - m_afDiag[i0])/(((Real)2.0) * m_afSubd[i0]); |
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85 | Real fR = sqrtf(fG*fG+(Real)1.0); |
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86 | if ( fG < (Real)0.0 ) fG = m_afDiag[i2]-m_afDiag[i0]+m_afSubd[i0]/(fG-fR); |
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87 | else fG = m_afDiag[i2]-m_afDiag[i0]+m_afSubd[i0]/(fG+fR); |
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88 | Real fSin = (Real)1.0, fCos = (Real)1.0, fP = (Real)0.0; |
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89 | for (int i3 = i2-1; i3 >= i0; i3--) |
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90 | { |
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91 | Real fF = fSin*m_afSubd[i3]; |
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92 | Ogre::Real fB = fCos*m_afSubd[i3]; |
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93 | if ( fabs(fF) >= fabs(fG) ) |
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94 | { |
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95 | fCos = fG/fF; |
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96 | fR = sqrtf(fCos*fCos+(Real)1.0); |
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97 | m_afSubd[i3+1] = fF*fR; |
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98 | fSin = ((Real)1.0)/fR; |
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99 | fCos *= fSin; |
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100 | } |
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101 | else |
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102 | { |
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103 | fSin = fF/fG; |
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104 | fR = sqrtf(fSin*fSin+(Real)1.0); |
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105 | m_afSubd[i3+1] = fG*fR; |
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106 | fCos = ((Real)1.0)/fR; |
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107 | fSin *= fCos; |
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108 | } |
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109 | fG = m_afDiag[i3+1]-fP; |
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110 | fR = (m_afDiag[i3]-fG)*fSin+((Real)2.0)*fB*fCos; |
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111 | fP = fSin*fR; |
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112 | m_afDiag[i3+1] = fG+fP; |
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113 | fG = fCos*fR-fB; |
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114 | |
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115 | for (int i4 = 0; i4 < m_iSize; i4++) |
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116 | { |
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117 | fF = m_kMat[i4][i3+1]; |
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118 | m_kMat[i4][i3+1] = fSin*m_kMat[i4][i3]+fCos*fF; |
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119 | m_kMat[i4][i3] = fCos*m_kMat[i4][i3]-fSin*fF; |
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120 | } |
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121 | } |
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122 | m_afDiag[i0] -= fP; |
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123 | m_afSubd[i0] = fG; |
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124 | m_afSubd[i2] = (Real)0.0; |
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125 | } |
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126 | if ( i1 == iMaxIter ) return false; |
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127 | } |
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128 | return true; |
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129 | } |
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130 | |
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131 | void EigenSolver::DecreasingSort () |
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132 | { |
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133 | // sort eigenvalues in decreasing order, e[0] >= ... >= e[iSize-1] |
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134 | for (int i0 = 0, i1; i0 <= m_iSize-2; i0++) |
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135 | { |
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136 | // locate maximum eigenvalue |
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137 | i1 = i0; |
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138 | Real fMax = m_afDiag[i1]; |
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139 | int i2; |
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140 | for (i2 = i0+1; i2 < m_iSize; i2++) |
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141 | { |
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142 | if ( m_afDiag[i2] > fMax ) |
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143 | { |
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144 | i1 = i2; |
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145 | fMax = m_afDiag[i1]; |
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146 | } |
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147 | } |
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148 | |
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149 | if ( i1 != i0 ) |
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150 | { |
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151 | // swap eigenvalues |
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152 | m_afDiag[i1] = m_afDiag[i0]; |
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153 | m_afDiag[i0] = fMax; |
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154 | |
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155 | // swap eigenvectors |
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156 | for (i2 = 0; i2 < m_iSize; i2++) |
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157 | { |
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158 | Real fTmp = m_kMat[i2][i0]; |
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159 | m_kMat[i2][i0] = m_kMat[i2][i1]; |
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160 | m_kMat[i2][i1] = fTmp; |
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161 | m_bIsRotation = !m_bIsRotation; |
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162 | } |
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163 | } |
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164 | } |
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165 | } |
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166 | |
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167 | void EigenSolver::GuaranteeRotation () |
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168 | { |
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169 | if ( !m_bIsRotation ) |
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170 | { |
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171 | // change sign on the first column |
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172 | for (int iRow = 0; iRow < m_iSize; iRow++) |
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173 | m_kMat[iRow][0] = -m_kMat[iRow][0]; |
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174 | } |
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175 | } |
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176 | |
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177 | void EigenSolver::orthogonalLineFit(unsigned int vertex_count, const Ogre::Vector3* vertices,Vector3& origin,Vector3& direction) |
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178 | { |
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179 | unsigned int i; |
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180 | |
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181 | // compute average of points |
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182 | origin = vertices[0]; |
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183 | for(i = 1; i < vertex_count; ++i) |
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184 | origin += vertices[i]; |
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185 | |
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186 | const Ogre::Real fInvQuantity = 1.0 / vertex_count; |
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187 | origin *= fInvQuantity; |
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188 | |
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189 | // compute sums of products |
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190 | Real fSumXX = 0.0, fSumXY = 0.0, fSumXZ = 0.0; |
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191 | Ogre::Real fSumYY = 0.0, fSumYZ = 0.0, fSumZZ = 0.0; |
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192 | for (i = 0; i < vertex_count; i++) |
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193 | { |
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194 | const Ogre::Vector3 kDiff (vertices[i] - origin); |
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195 | fSumXX += kDiff.x*kDiff.x; |
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196 | fSumXY += kDiff.x*kDiff.y; |
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197 | fSumXZ += kDiff.x*kDiff.z; |
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198 | fSumYY += kDiff.y*kDiff.y; |
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199 | fSumYZ += kDiff.y*kDiff.z; |
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200 | fSumZZ += kDiff.z*kDiff.z; |
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201 | } |
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202 | fSumXX *= fInvQuantity; |
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203 | fSumXY *= fInvQuantity; |
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204 | fSumXZ *= fInvQuantity; |
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205 | fSumYY *= fInvQuantity; |
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206 | fSumYZ *= fInvQuantity; |
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207 | fSumZZ *= fInvQuantity; |
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208 | |
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209 | // setup the eigensolver |
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210 | EigenSolver kES(3); |
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211 | kES(0,0) = fSumYY+fSumZZ; |
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212 | kES(0,1) = -fSumXY; |
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213 | kES(0,2) = -fSumXZ; |
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214 | kES(1,0) = kES(0,1); |
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215 | kES(1,1) = fSumXX+fSumZZ; |
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216 | kES(1,2) = -fSumYZ; |
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217 | kES(2,0) = kES(0,2); |
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218 | kES(2,1) = kES(1,2); |
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219 | kES(2,2) = fSumXX+fSumYY; |
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220 | |
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221 | // compute eigenstuff, smallest eigenvalue is in last position |
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222 | kES.DecrSortEigenStuff3(); |
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223 | |
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224 | // unit-length direction for best-fit line |
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225 | kES.GetEigenvector(2,direction); |
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226 | } |
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227 | |
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228 | Real EigenSolver::SqrDistance(const Ogre::Vector3& rkPoint,const Ogre::Vector3& origin,const Ogre::Vector3& direction) |
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229 | { |
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230 | Vector3 kDiff(rkPoint - origin); |
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231 | const Ogre::Real fSqrLen = direction.squaredLength(); |
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232 | const Ogre::Real fT = kDiff.dotProduct(direction) / fSqrLen; |
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233 | |
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234 | kDiff -= fT*direction; |
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235 | |
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236 | return kDiff.squaredLength(); |
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237 | } |
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238 | |
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239 | void EigenSolver::GenerateOrthonormalBasis (Vector3& rkU, Ogre::Vector3& rkV, Ogre::Vector3& rkW, bool bUnitLengthW) |
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240 | { |
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241 | if ( !bUnitLengthW ) rkW.normalise(); |
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242 | |
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243 | Real fInvLength; |
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244 | |
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245 | if ( fabs(rkW[0]) >= fabs(rkW[1]) ) |
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246 | { |
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247 | // W.x or W.z is the largest magnitude component, swap them |
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248 | fInvLength = 1.0 / sqrtf(rkW[0]*rkW[0] + rkW[2]*rkW[2]); |
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249 | |
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250 | rkU[0] = -rkW[2]*fInvLength; |
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251 | rkU[1] = (Real)0.0; |
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252 | rkU[2] = +rkW[0]*fInvLength; |
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253 | } |
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254 | else |
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255 | { |
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256 | // W.y or W.z is the largest magnitude component, swap them |
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257 | fInvLength = 1.0 / sqrtf(rkW[1]*rkW[1] + rkW[2]*rkW[2]); |
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258 | |
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259 | rkU[0] = (Real)0.0; |
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260 | rkU[1] = +rkW[2]*fInvLength; |
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261 | rkU[2] = -rkW[1]*fInvLength; |
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262 | } |
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263 | |
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264 | rkV = rkW.crossProduct(rkU); |
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265 | } |
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266 | |
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267 | EigenSolver::EigenSolver(int iSize) |
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268 | { |
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269 | assert( iSize >= 2 ); |
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270 | m_iSize = iSize; |
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271 | m_afDiag = new Ogre::Real[m_iSize]; |
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272 | m_afSubd = new Ogre::Real[m_iSize]; |
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273 | |
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274 | // set according to the parity of the number of Householder reflections |
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275 | m_bIsRotation = ((iSize % 2) == 0); |
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276 | } |
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277 | |
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278 | Ogre::Real& EigenSolver::operator() (int iRow, int iCol) |
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279 | { |
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280 | return m_kMat[iRow][iCol]; |
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281 | } |
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282 | |
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283 | EigenSolver::~EigenSolver() |
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284 | { |
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285 | delete[] m_afSubd; |
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286 | delete[] m_afDiag; |
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287 | } |
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288 | |
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289 | void EigenSolver::GetEigenvector (int i, Ogre::Vector3& rkV) const |
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290 | { |
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291 | assert( m_iSize == 3 ); |
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292 | if ( m_iSize == 3 ) |
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293 | { |
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294 | for (int iRow = 0; iRow < m_iSize; iRow++) |
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295 | rkV[iRow] = m_kMat[iRow][i]; |
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296 | } |
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297 | else |
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298 | { |
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299 | rkV = Ogre::Vector3::ZERO; |
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300 | } |
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301 | } |
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302 | |
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303 | void EigenSolver::GaussPointsFit(unsigned int iQuantity,const Ogre::Vector3* akPoint,Vector3 &rkCenter,Vector3 akAxis[3],Real afExtent[3]) |
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304 | { |
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305 | // compute mean of points |
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306 | rkCenter = akPoint[0]; |
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307 | unsigned int i; |
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308 | for (i = 1; i < iQuantity; i++) |
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309 | rkCenter += akPoint[i]; |
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310 | const Ogre::Real fInvQuantity = ((Real)1.0)/iQuantity; |
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311 | rkCenter *= fInvQuantity; |
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312 | |
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313 | // compute covariances of points |
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314 | Ogre::Real fSumXX = (Real)0.0, fSumXY = (Real)0.0, fSumXZ = (Real)0.0; |
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315 | Ogre::Real fSumYY = (Real)0.0, fSumYZ = (Real)0.0, fSumZZ = (Real)0.0; |
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316 | for (i = 0; i < iQuantity; i++) |
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317 | { |
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318 | const Ogre::Vector3 kDiff (akPoint[i] - rkCenter); |
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319 | fSumXX += kDiff.x*kDiff.x; |
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320 | fSumXY += kDiff.x*kDiff.y; |
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321 | fSumXZ += kDiff.x*kDiff.z; |
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322 | fSumYY += kDiff.y*kDiff.y; |
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323 | fSumYZ += kDiff.y*kDiff.z; |
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324 | fSumZZ += kDiff.z*kDiff.z; |
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325 | } |
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326 | fSumXX *= fInvQuantity; |
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327 | fSumXY *= fInvQuantity; |
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328 | fSumXZ *= fInvQuantity; |
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329 | fSumYY *= fInvQuantity; |
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330 | fSumYZ *= fInvQuantity; |
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331 | fSumZZ *= fInvQuantity; |
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332 | |
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333 | // compute eigenvectors for covariance matrix |
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334 | EigenSolver kES(3); |
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335 | kES(0,0) = fSumXX; |
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336 | kES(0,1) = fSumXY; |
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337 | kES(0,2) = fSumXZ; |
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338 | kES(1,0) = fSumXY; |
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339 | kES(1,1) = fSumYY; |
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340 | kES(1,2) = fSumYZ; |
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341 | kES(2,0) = fSumXZ; |
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342 | kES(2,1) = fSumYZ; |
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343 | kES(2,2) = fSumZZ; |
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344 | kES.IncrSortEigenStuff3(); |
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345 | |
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346 | for (i = 0; i < 3; i++) |
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347 | { |
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348 | afExtent[i] = kES.GetEigenvalue(i); |
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349 | kES.GetEigenvector(i,akAxis[i]); |
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350 | } |
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351 | } |
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352 | |
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353 | Real EigenSolver::GetEigenvalue (int i) const |
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354 | { |
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355 | return m_afDiag[i]; |
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356 | } |
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357 | |
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358 | void EigenSolver::IncrSortEigenStuff3 () |
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359 | { |
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360 | Tridiagonal3(); |
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361 | QLAlgorithm(); |
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362 | IncreasingSort(); |
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363 | GuaranteeRotation(); |
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364 | } |
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365 | |
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366 | void EigenSolver::IncreasingSort () |
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367 | { |
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368 | // sort eigenvalues in increasing order, e[0] <= ... <= e[iSize-1] |
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369 | for (int i0 = 0, i1; i0 <= m_iSize-2; i0++) |
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370 | { |
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371 | // locate minimum eigenvalue |
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372 | i1 = i0; |
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373 | Ogre::Real fMin = m_afDiag[i1]; |
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374 | int i2; |
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375 | for (i2 = i0+1; i2 < m_iSize; i2++) |
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376 | { |
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377 | if ( m_afDiag[i2] < fMin ) |
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378 | { |
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379 | i1 = i2; |
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380 | fMin = m_afDiag[i1]; |
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381 | } |
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382 | } |
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383 | |
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384 | if ( i1 != i0 ) |
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385 | { |
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386 | // swap eigenvalues |
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387 | m_afDiag[i1] = m_afDiag[i0]; |
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388 | m_afDiag[i0] = fMin; |
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389 | |
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390 | // swap eigenvectors |
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391 | for (i2 = 0; i2 < m_iSize; i2++) |
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392 | { |
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393 | Ogre::Real fTmp = m_kMat[i2][i0]; |
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394 | m_kMat[i2][i0] = m_kMat[i2][i1]; |
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395 | m_kMat[i2][i1] = fTmp; |
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396 | m_bIsRotation = !m_bIsRotation; |
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397 | } |
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398 | } |
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399 | } |
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400 | } |
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