run_maxwell_simulation_filters_statistics.sh 1.9 KB

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  1. #! bin/bash
  2. # file which contains model names we want to use for simulation
  3. simulate_models="simulate_models.csv"
  4. # selection of four scenes (only maxwell)
  5. scenes="A, D, G, H"
  6. size="26"
  7. # for metric in {"lab","mscn","low_bits_2","low_bits_3","low_bits_4","low_bits_5","low_bits_6","low_bits_4_shifted_2","ica_diff","svd_trunc_diff","ipca_diff","svd_reconstruct"}; do
  8. metric="filters_statistics"
  9. for nb_zones in {4,6,8,10,12}; do
  10. for mode in {"svd","svdn","svdne"}; do
  11. for model in {"svm_model","ensemble_model","ensemble_model_v2"}; do
  12. FILENAME="data/${model}_N${size}_B0_E${size}_nb_zones_${nb_zones}_${metric}_${mode}"
  13. MODEL_NAME="${model}_N${size}_B0_E${size}_nb_zones_${nb_zones}_${metric}_${mode}"
  14. CUSTOM_MIN_MAX_FILENAME="N${size}_B0_E${size}_nb_zones_${nb_zones}_${metric}_${mode}_min_max"
  15. echo $MODEL_NAME
  16. # only compute if necessary (perhaps server will fall.. Just in case)
  17. if grep -q "${MODEL_NAME}" "${simulate_models}"; then
  18. echo "${MODEL_NAME} results already generated..."
  19. else
  20. # Use of already generated model
  21. # python generate/generate_data_model_random.py --output ${FILENAME} --interval "0,${size}" --kind ${mode} --metric ${metric} --scenes "${scenes}" --nb_zones "${nb_zones}" --percent 1 --renderer "maxwell" --step 40 --random 1 --custom ${CUSTOM_MIN_MAX_FILENAME}
  22. # python train_model.py --data ${FILENAME} --output ${MODEL_NAME} --choice ${model}
  23. python prediction/predict_seuil_expe_maxwell_curve.py --interval "0,${size}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --metric ${metric} --custom ${CUSTOM_MIN_MAX_FILENAME}
  24. python others/save_model_result_in_md_maxwell.py --interval "0,${size}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --metric ${metric}
  25. fi
  26. done
  27. done
  28. done