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- #! bin/bash
- # erase "results/models_comparisons.csv" file and write new header
- file_path='results/models_comparisons.csv'
- erased=$1
- if [ "${erased}" == "Y" ]; then
- echo "Previous data file erased..."
- rm ${file_path}
- mkdir -p results
- touch ${file_path}
- # add of header
- echo 'model_name; vector_size; start; end; nb_zones; feature; mode; tran_size; val_size; test_size; train_pct_size; val_pct_size; test_pct_size; train_acc; val_acc; test_acc; all_acc; F1_train; recall_train; roc_auc_train; F1_val; recall_val; roc_auc_val; F1_test; recall_test; roc_auc_test; F1_all; recall_all; roc_auc_all;' >> ${file_path}
- fi
- start_index=0
- end_index=24
- # selection of four scenes (only maxwell)
- scenes="A, D, G, H"
- feature="lab"
- for label in {"0","1"}; do
- for highest in {"0","1"}; do
- for nb_zones in {4,6,8,10,12}; do
- for size in {5,10,15,20,25,30,35,40}; do
- for mode in {"svd","svdn","svdne"}; do
- FILENAME="data/deep_keras_N${size}_B${start_index}_E${size}_nb_zones_${nb_zones}_${feature}_${mode}_corr_L${label}_H${highest}"
- MODEL_NAME="deep_keras_N${size}_B${start_index}_E${size}_nb_zones_${nb_zones}_${feature}_${mode}_corr_L${label}_H${highest}"
- echo $FILENAME
- # only compute if necessary (perhaps server will fall.. Just in case)
- if grep -q "${MODEL_NAME}" "${file_path}"; then
- echo "${MODEL_NAME} results already generated..."
- else
- python generate/generate_data_model_corr_random.py --output ${FILENAME} --n ${size} --highest ${highest} --label ${label} --kind ${mode} --feature ${feature} --scenes "${scenes}" --nb_zones "${nb_zones}" --percent 1 --renderer "maxwell" --step 10 --random 1
- python deep_network_keras_svd.py --data ${FILENAME} --output ${MODEL_NAME} --size ${size}
- # use of interval but it is not really an interval..
- python others/save_model_result_in_md_maxwell.py --interval "${start_index},${size}" --model "saved_models/${MODEL_NAME}.json" --mode "${mode}" --feature ${feature}
- fi
- done
- done
- done
- done
- done
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