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@@ -0,0 +1,48 @@
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+#! bin/bash
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+
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+if [ -z "$1" ]
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+ then
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+ echo "No argument supplied"
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+ echo "Need of vector size"
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+ exit 1
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+fi
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+
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+if [ -z "$2" ]
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+ then
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+ echo "No argument supplied"
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+ echo "Need of metric information"
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+ exit 1
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+fi
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+
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+result_filename="models_info/models_comparisons.csv"
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+VECTOR_SIZE=200
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+size=$1
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+metric=$2
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+
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+# selection of four scenes (only maxwell)
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+scenes="A, D, G, H"
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+
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+for nb_zones in {4,6,8,10,12}; do
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+ for mode in {"svd","svdn","svdne"}; do
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+ for model in {"svm_model","ensemble_model","ensemble_model_v2"}; do
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+
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+ FILENAME="data/${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 $FILENAME
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+
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+ # only compute if necessary (perhaps server will fall.. Just in case)
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+ if grep -q "${MODEL_NAME}" "${result_filename}"; then
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+
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+ echo "${MODEL_NAME} results already generated..."
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+ else
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+ python generate_data_model_random_center.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 ${model}
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+
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+ python save_model_result_in_md_maxwell.py --interval "0,${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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+
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