1 | #include "ekf_example/matrix_vs.h" |
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2 | #include "ekf_example/ekf_obj.h" |
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3 | int main(){ |
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4 | int i; |
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5 | mat A = 0.99*eye(5); |
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6 | A(0,3) = 0.06; |
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7 | A(0,2) = 0.01; |
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8 | A(1,2) = 0.01; |
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9 | A(1,3) = -0.07; |
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10 | A(3,2) = 0.0001; |
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11 | |
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12 | // RNG_randomize(); |
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13 | |
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14 | mat U=eye(5); |
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15 | for (int i=0; i<5;i++) { |
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16 | for (int j=i+1; j<5;j++) U(i,j)=2*randu(1)(0)-1; |
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17 | } |
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18 | mat Q = 0.1*diag(vec(" 0.2000 0.3000 0.4000 0.5000 0.6")); |
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19 | vec R = vec(" 0.2000 0.3000"); |
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20 | |
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21 | vec D = randu(5)*0.9; |
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22 | vec xref = ones(5); |
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23 | |
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24 | mat Ch = U*diag(sqrt(D)); |
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25 | |
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26 | int PSI[25]; |
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27 | int PSICh[25]={0,0,0,0,0, 0,0,0,0,0, 0,0,0,0,0, 0,0,0,0,0, 0,0,0,0,0}; |
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28 | int Chf[25]={0,0,0,0,0, 0,0,0,0,0, 0,0,0,0,0, 0,0,0,0,0, 0,0,0,0,0}; |
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29 | int Cf[10]={0,0,0,0,0, 0,0,0,0,0}; |
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30 | int multip=1<<15; |
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31 | |
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32 | /////////// COPY |
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33 | imat Af=round_i(A*multip); |
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34 | mat_to_int16(Af, PSI); |
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35 | mat_to_int16(round_i(Ch*multip),Chf); |
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36 | int Qf[25]; |
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37 | mat_to_int16(round_i(sqrt(Q)*multip), Qf); |
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38 | int Rf[2]; |
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39 | vec_to_int16(round_i(R*multip), Rf); |
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40 | |
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41 | |
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42 | ////////////// Test mmultAU |
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43 | mmultACh(PSI,Chf,PSICh,5,5); |
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44 | |
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45 | mat PhiCh =round(A*32768)*round(Ch*32768)/32768/32768; |
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46 | /* cout << "A*U" << round_i(PhiU*multip) <<endl; |
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47 | cout << "PSIU: "; for (i=0; i<25;i++) cout << PSIU[i] << ","; cout <<endl;*/ |
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48 | |
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49 | imat PChcmp(PSICh,5,5); |
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50 | cout << "Delta PSI: " << round_i(PhiCh*multip-PChcmp) <<endl; |
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51 | |
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52 | mat_to_int16(round_i(PhiCh*multip),PSICh); //<< make is same |
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53 | |
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54 | mat PhiU= A*U; |
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55 | /////////// Test Thorton: |
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56 | int dim=5;double sigma; int j,k; |
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57 | vec Din = D; |
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58 | mat G=eye(5); |
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59 | for (i=dim-1; i>=0;i--){ |
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60 | sigma = 0.0; |
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61 | for (j=0; j<dim; j++) { |
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62 | sigma += PhiU(i,j)*PhiU(i,j) *Din(j); |
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63 | sigma += G(i,j)*G(i,j) * Q(j,j); |
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64 | } |
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65 | D(i) = sigma; |
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66 | for (j=0;j<i;j++){ |
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67 | sigma = 0.0; |
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68 | for (k=0;k<dim;k++){ |
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69 | sigma += PhiU(i,k)*Din(k)*PhiU(j,k); |
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70 | } |
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71 | for (k=0;k<dim;k++){ |
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72 | sigma += G(i,k)*Q(k,k)*G(j,k); |
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73 | } |
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74 | // |
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75 | U(j,i) = sigma/D(i); |
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76 | for (k=0;k<dim;k++){ |
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77 | PhiU(j,k) = PhiU(j,k) - U(j,i)*PhiU(i,k); |
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78 | } |
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79 | for (k=0;k<dim;k++){ |
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80 | G(j,k) = G(j,k) - U(j,i)*G(i,k); |
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81 | } |
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82 | } |
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83 | } |
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84 | |
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85 | cout << "PSICh: " << imat(PSICh,5,5) << endl; |
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86 | cout << "Qf: " << imat(Qf,5,5) << endl; |
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87 | |
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88 | Ch = U*diag(sqrt(D)); |
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89 | |
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90 | |
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91 | householder(PSICh,Qf,5); |
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92 | // givens(PSICh,Qf,5); |
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93 | |
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94 | /////// disp |
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95 | |
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96 | cout << endl<<"after householder " <<endl; |
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97 | |
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98 | imat Chcmp(PSICh,5,5); |
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99 | cout << "Ch(UD): " << round_i(Ch*multip) << endl; |
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100 | cout << "Ch: " << (Chcmp) << endl; |
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101 | cout << "Delta Ch: " << round_i(Ch*multip-Chcmp) << endl; |
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102 | |
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103 | // synchronize |
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104 | vec d=diag(Ch*Ch.T()); |
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105 | mat Ch2 = 0.9*diag(1./sqrt(d))*Ch; |
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106 | mat_to_int16(round_i(Ch2*multip),Chf); |
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107 | |
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108 | D = pow(diag(Ch2),2); |
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109 | U = sqrt(diag(1./D)); |
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110 | U = Ch2*U; |
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111 | |
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112 | vec ydif = 2*randu(2)-1; |
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113 | vec xp = 2*randu(5)-1; |
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114 | |
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115 | int difz[2]; |
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116 | vec_to_int16(round_i(ydif*multip), difz); |
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117 | int xf[5]; |
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118 | vec_to_int16(round_i(xp*multip), xf); |
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119 | |
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120 | cout << "x: "<< round_i(xp*multip) <<endl; |
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121 | cout << "xf: "; for (i=0; i<5;i++) cout << xf[i] << ","; cout << endl; |
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122 | |
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123 | |
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124 | int xf_old[5]; |
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125 | vec_to_int16(ivec(xf,5),xf_old); |
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126 | |
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127 | /////// Test bierman |
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128 | double dz,alpha,gamma,beta,lambda; |
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129 | vec a; |
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130 | vec b; |
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131 | mat C = zeros(2,5); |
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132 | C(0,0)=.2;C(1,1)=0.4;C(0,1)=0.3; |
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133 | |
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134 | for (int iy=0; iy<2; iy++){ |
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135 | a = U.T()*C.get_row(iy); // a is not modified, but |
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136 | b = elem_mult(D,a); // b is modified to become unscaled Kalman gain. |
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137 | dz = ydif(iy); |
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138 | |
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139 | alpha = R(iy); |
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140 | gamma = 1/alpha; |
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141 | for (j=0;j<dim;j++){ |
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142 | beta = alpha; |
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143 | alpha = alpha + a(j)*b(j); |
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144 | lambda = -a(j)*gamma; |
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145 | gamma = 1.0/alpha; |
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146 | D(j) = beta*gamma*D(j); |
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147 | |
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148 | // cout << "a: " << alpha << "g: " << gamma << endl; |
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149 | for (i=0;i<j;i++){ |
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150 | beta = U(i,j); |
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151 | U(i,j) = beta + b(i)*lambda; |
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152 | b(i) = b(i) + b(j)*beta; |
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153 | } |
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154 | } |
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155 | double dzs = gamma*dz; // apply scaling to innovations |
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156 | xp = xp + dzs*b; // multiply by unscaled Kalman gain |
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157 | |
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158 | //cout << "Ub: " << U << endl; |
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159 | //cout << "Db: " << D << endl <<endl; |
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160 | |
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161 | } |
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162 | |
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163 | Ch = U*diag(sqrt(D)); |
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164 | mat_to_int16(round_i(C*multip),Cf); |
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165 | |
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166 | cout << "bef Carlson: " << imat(Chf,5,5) << endl; |
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167 | |
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168 | carlson_fastC(difz,xf, Chf, Cf,Rf, 2, 5); |
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169 | |
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170 | cout << endl<<"after Carlson" <<endl; |
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171 | cout << "x: "<< round_i(xp*multip) <<endl; |
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172 | cout << "xf: "; for (i=0; i<5;i++) cout << xf[i] << ","; cout << endl; |
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173 | |
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174 | { |
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175 | imat Chcmp(Chf,5,5); |
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176 | cout << "Delta Ch: " << round_i(Ch*multip-Chcmp) << endl; |
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177 | cout << "Delta Ch: " << Chcmp << endl; |
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178 | } |
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179 | |
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180 | return 0; |
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181 | } |
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