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+#! bin/bash
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+
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+# file which contains model names we want to use for simulation
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+simulate_models="simulate_models.csv"
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+
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+# selection of four scenes (only maxwell)
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+scenes="A, D, G, H"
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+
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+feature="sub_blocks_stats_reduced"
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+start_index=0
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+end_index=24
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+number=24
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+
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+for nb_zones in {4,6,8,10,12}; do
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+
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+ for mode in {"svd","svdn","svdne"}; do
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+ for model in {"svm_model","ensemble_model","ensemble_model_v2"}; do
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+
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+ FILENAME="data/${model}_N${number}_B${start_index}_E${end_index}_nb_zones_${nb_zones}_${feature}_${mode}"
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+ MODEL_NAME="${model}_N${number}_B${start_index}_E${end_index}_nb_zones_${nb_zones}_${feature}_${mode}"
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+
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+ if grep -xq "${MODEL_NAME}" "${simulate_models}"; then
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+ echo "Run simulation for model ${MODEL_NAME}"
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+
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+ # by default regenerate model
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+ python generate/generate_data_model_random.py --output ${FILENAME} --interval "${start_index},${end_index}" --kind ${mode} --feature ${feature} --scenes "${scenes}" --nb_zones "${nb_zones}" --percent 1 --renderer "maxwell" --random 1
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+
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+ python train_model.py --data ${FILENAME} --output ${MODEL_NAME} --choice ${model}
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+
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+ python prediction/predict_seuil_expe_maxwell_curve.py --interval "${start_index},${end_index}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --feature ${feature} --limit_detection '2'
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+
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+ python others/save_model_result_in_md_maxwell.py --interval "${start_index},${end_index}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --feature ${feature}
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+
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+ fi
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+ done
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+ done
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+done
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