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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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+size="26"
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+
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+# 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
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+metric="filters_statistics"
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+
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+for nb_zones in {4,6,8,10,12}; do
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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/${model}_N${size}_B0_E${size}_nb_zones_${nb_zones}_${metric}_${mode}"
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+ MODEL_NAME="${model}_N${size}_B0_E${size}_nb_zones_${nb_zones}_${metric}_${mode}"
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+ CUSTOM_MIN_MAX_FILENAME="N${size}_B0_E${size}_nb_zones_${nb_zones}_${metric}_${mode}_min_max"
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+
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+ echo $MODEL_NAME
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+
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+ # only compute if necessary (perhaps server will fall.. Just in case)
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+ if grep -q "${MODEL_NAME}" "${simulate_models}"; then
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+
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+ echo "${MODEL_NAME} results already generated..."
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+ else
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+ # Use of already generated model
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+ # python 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}
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+ # python train_model.py --data ${FILENAME} --output ${MODEL_NAME} --choice ${model}
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+
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+ python predict_seuil_expe_maxwell_curve.py --interval "0,${size}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --metric ${metric} --limit_detection '2' --custom ${CUSTOM_MIN_MAX_FILENAME}
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+
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+ python save_model_result_in_md_maxwell.py --interval "0,${size}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --metric ${metric}
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+ fi
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+ done
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+ done
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+done
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