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- #! bin/bash
- if [ -z "$1" ]
- then
- echo "No argument supplied"
- echo "Need of vector size"
- exit 1
- fi
- if [ -z "$2" ]
- then
- echo "No argument supplied"
- echo "Need of feature information"
- exit 1
- fi
- result_filename="results/models_comparisons.csv"
- VECTOR_SIZE=200
- size=$1
- feature=$2
- # selection of four scenes (only maxwell)
- scenes="A, D, G, H"
- half=$(($size/2))
- start=-$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}; do
- echo $start $end
- for mode in {"svd","svdn","svdne"}; do
- for model in {"svm_model","ensemble_model","ensemble_model_v2"}; do
- FILENAME="data/${model}_N${size}_B${start}_E${end}_nb_zones_${nb_zones}_${feature}_${mode}"
- MODEL_NAME="${model}_N${size}_B${start}_E${end}_nb_zones_${nb_zones}_${feature}_${mode}"
- echo $FILENAME
- # only compute if necessary (perhaps server will fall.. Just in case)
- if grep -q "${MODEL_NAME}" "${result_filename}"; then
- echo "${MODEL_NAME} results already generated..."
- else
- python generate/generate_data_model_random.py --output ${FILENAME} --interval "${start},${end}" --kind ${mode} --feature ${feature} --scenes "${scenes}" --nb_zones "${nb_zones}" --renderer "maxwell" --step 40 --random 1 --percent 1
- python train_model.py --data ${FILENAME} --output ${MODEL_NAME} --choice ${model}
- #python prediction/predict_seuil_expe_maxwell.py --interval "${start},${end}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --feature ${feature} --limit_detection '2'
- python others/save_model_result_in_md_maxwell.py --interval "${start},${end}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --feature ${feature}
- fi
- done
- done
- done
- if [ "$counter" -eq "0" ]; then
- start=$(($start+50-$half))
- else
- start=$(($start+50))
- fi
- done
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