68 lines
2.8 KiB
C++
68 lines
2.8 KiB
C++
#include "gm3d.h"
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int GM3D::ForwardVzy(char* noise_level){
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int i,j;
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double x1,x2,y1,y2,z1,z2;
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double R222,R122,R212,R112,R221,R121,R211,R111;
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double G222,G122,G212,G112,G221,G121,G211,G111;
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//初始化正演值和不确定度
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for (int i = 0; i < obs_num_; i++){
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obs_p_[i].val = obs_p_[i].dev = 0.0;
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}
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double noise_mean, noise_dev, temp_noise;
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if (2 != sscanf(noise_level,"%lf/%lf",&noise_mean,&noise_dev)){
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noise_mean = noise_dev = 0.0;
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}
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//添加高斯噪声值
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default_random_engine generator;
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normal_distribution<double> dist(noise_mean, noise_dev);
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_1dArray temp_obs(model_num_);
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//ProgressBar *bar = new ProgressBar(obs_num_,"Forward modeling");
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for (i = 0; i < obs_num_; i++){
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//bar->Progressed(i);
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#pragma omp parallel for private(j,R222,R122,R212,R112,R221,R121,R211,R111,G222,G122,G212,G112,G221,G121,G211,G111,x1,x2,y1,y2,z1,z2) shared(i) schedule(guided)
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for (j = 0; j < model_num_; j++){
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if (fabs(forward_model_[j]) > ZERO){
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x1 = model_cube_[j].cen.x - 0.5*model_cube_[j].dx; x2 = model_cube_[j].cen.x + 0.5*model_cube_[j].dx;
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y1 = model_cube_[j].cen.y - 0.5*model_cube_[j].dy; y2 = model_cube_[j].cen.y + 0.5*model_cube_[j].dy;
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z1 = model_cube_[j].cen.z - 0.5*model_cube_[j].dz; z2 = model_cube_[j].cen.z + 0.5*model_cube_[j].dz;
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R222=sqrt((x2-obs_p_[i].x)*(x2-obs_p_[i].x)+(y2-obs_p_[i].y)*(y2-obs_p_[i].y)+(z2-obs_p_[i].z)*(z2-obs_p_[i].z));
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R122=sqrt((x1-obs_p_[i].x)*(x1-obs_p_[i].x)+(y2-obs_p_[i].y)*(y2-obs_p_[i].y)+(z2-obs_p_[i].z)*(z2-obs_p_[i].z));
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R212=sqrt((x2-obs_p_[i].x)*(x2-obs_p_[i].x)+(y1-obs_p_[i].y)*(y1-obs_p_[i].y)+(z2-obs_p_[i].z)*(z2-obs_p_[i].z));
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R112=sqrt((x1-obs_p_[i].x)*(x1-obs_p_[i].x)+(y1-obs_p_[i].y)*(y1-obs_p_[i].y)+(z2-obs_p_[i].z)*(z2-obs_p_[i].z));
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R221=sqrt((x2-obs_p_[i].x)*(x2-obs_p_[i].x)+(y2-obs_p_[i].y)*(y2-obs_p_[i].y)+(z1-obs_p_[i].z)*(z1-obs_p_[i].z));
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R121=sqrt((x1-obs_p_[i].x)*(x1-obs_p_[i].x)+(y2-obs_p_[i].y)*(y2-obs_p_[i].y)+(z1-obs_p_[i].z)*(z1-obs_p_[i].z));
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R211=sqrt((x2-obs_p_[i].x)*(x2-obs_p_[i].x)+(y1-obs_p_[i].y)*(y1-obs_p_[i].y)+(z1-obs_p_[i].z)*(z1-obs_p_[i].z));
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R111=sqrt((x1-obs_p_[i].x)*(x1-obs_p_[i].x)+(y1-obs_p_[i].y)*(y1-obs_p_[i].y)+(z1-obs_p_[i].z)*(z1-obs_p_[i].z));
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G222=log((x2-obs_p_[i].x)+R222);
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G122=log((x1-obs_p_[i].x)+R122);
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G212=log((x2-obs_p_[i].x)+R212);
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G112=log((x1-obs_p_[i].x)+R112);
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G221=log((x2-obs_p_[i].x)+R221);
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G121=log((x1-obs_p_[i].x)+R121);
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G211=log((x2-obs_p_[i].x)+R211);
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G111=log((x1-obs_p_[i].x)+R111);
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temp_obs[j] = G0*(G222-G122-G212+G112-G221+G121+G211-G111)*forward_model_[j];
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}
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}
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for (int n = 0; n < model_num_; n++){
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obs_p_[i].val += temp_obs[n];
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}
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}
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for (int i = 0; i < obs_num_; i++){
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temp_noise = dist(generator);
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obs_p_[i].val += temp_noise;
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obs_p_[i].dev = noise_dev;
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}
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return 0;
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} |