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- #! bin/bash
- # file which contains model names we want to use for simulation
- simulate_models="simulate_models.csv"
- # selection of four scenes (only maxwell)
- scenes="A, D, G, H"
- VECTOR_SIZE=200
- for size in {"4","8","16","26","32","40"}; do
- for metric in {"lab","mscn","mscn_revisited","low_bits_2","low_bits_3","low_bits_4"}; do
- half=$(($size/2))
- start=-$half
- for counter in {0..4}; do
- end=$(($start+$size))
- if [ "$end" -gt "$VECTOR_SIZE" ]; then
- start=$(($VECTOR_SIZE-$size))
- end=$(($VECTOR_SIZE))
- fi
- if [ "$start" -lt "0" ]; then
- start=$((0))
- end=$(($size))
- fi
- for nb_zones in {4,6,8,10,12,14}; do
- for mode in {"svd","svdn","svdne"}; do
- for model in {"svm_model","ensemble_model","ensemble_model_v2"}; do
- FILENAME="data/data_maxwell_N${size}_B${start}_E${end}_nb_zones_${nb_zones}_${metric}_${mode}"
- MODEL_NAME="${model}_N${size}_B${start}_E${end}_nb_zones_${nb_zones}_${metric}_${mode}"
- if grep -q "${MODEL_NAME}" "${simulate_models}"; then
- echo "Run simulation for model ${MODEL_NAME}"
- # by default regenerate model
- python generate_data_model_random_maxwell.py --output ${FILENAME} --interval "${start},${end}" --kind ${mode} --metric ${metric} --scenes "${scenes}" --nb_zones "${nb_zones}" --percent 1 --sep ';' --rowindex '0'
- python models/${model}_train.py --data ${FILENAME} --output ${MODEL_NAME}
- python predict_seuil_expe_maxwell.py --interval "${start},${end}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --metric ${metric} --limit_detection '2' &
- fi
- done
- done
- done
- if [ "$counter" -eq "0" ]; then
- start=$(($start+50-$half))
- else
- start=$(($start+50))
- fi
- done
- done
- done
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