if [ ! -d "./logs" ]; then mkdir ./logs fi if [ ! -d "./logs/onerun" ]; then mkdir ./logs/onerun fi seq_len=36 percentage=100 model_name=DLinear # aug 0: None # aug 1: Frequency Masking # aug 2: Frequency Mixing # aug 3: Wave Masking # aug 4: Wave Mixing # aug 5: STAug pred_lens=(24 36 48 60) # For Aug 0: None for pred_len in "${pred_lens[@]}"; do python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len $pred_len \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 0 --aug_rate 0.0 >logs/onerun/$model_name'_'ill_$seq_len'_'$pred_len'_'0.0'_'$percentage'_'None.log done # For Aug 1: Freq-Masking python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 24 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 1 --aug_rate 0.2 >logs/onerun/$model_name'_'ill_$seq_len'_'96'_'0.4'_'$percentage'_'FreqMask.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 36 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 1 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'36'_'0.4'_'$percentage'_'FreqMask.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 48 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 1 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'48'_'0.4'_'$percentage'_'FreqMask.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 60 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 1 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'60'_'0.4'_'$percentage'_'FreqMask.log # For Aug 2: Freq-Mixing python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 24 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 2 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'24'_'0.4'_'$percentage'_'FreqMix.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 36 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 2 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'36'_'0.4'_'$percentage'_'FreqMix.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 48 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 2 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'48'_'0.4'_'$percentage'_'FreqMix.log python3 -u ./run_main2.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 60 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 2 --aug_rate 0.1 >logs/onerun/$model_name'_'ill_$seq_len'_'60'_'0.4'_'$percentage'_'FreqMix.log # For Aug 3: Wave Masking python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 24 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 3 --rates "[0.4, 0.8, 0.9, 0.7, 0.9, 0.0, 0.5]" --wavelet 'db25' --level 1 --sampling_rate 0.2 >logs/onerun/$model_name'_'ill_$seq_len'_'24'_'0.0'_'$percentage'_'WaveMask.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 36 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 3 --rates "[0.6, 0.8, 0.3, 0.1, 0.9, 0.0, 0.5]" --wavelet 'db25' --level 1 --sampling_rate 0.2 >logs/onerun/$model_name'_'ill_$seq_len'_'36'_'0.0'_'$percentage'_'WaveMask.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 48 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 3 --rates "[0.2, 0.7, 1.0, 0.4, 0.4, 0.0, 0.5]" --wavelet 'db2' --level 1 --sampling_rate 0.2 >logs/onerun/$model_name'_'ill_$seq_len'_'48'_'0.0'_'$percentage'_'WaveMask.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 60 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 3 --rates "[0.2, 0.8, 0.5, 0.1, 0.9, 0.0, 0.5]" --wavelet 'db25' --level 1 --sampling_rate 0.2 >logs/onerun/$model_name'_'ill_$seq_len'_'60'_'0.0'_'$percentage'_'WaveMask.log # For Aug 4: Wave Mixing python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 24 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 4 --rates "[0.1, 0.8, 1.0, 0.0, 0.5, 0.7, 0.1]" --wavelet 'db1' --level 1 --sampling_rate 0.2 >logs/onerun/$model_name'_'ill_$seq_len'_'24'_'0.0'_'$percentage'_'WaveMix.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 36 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 4 --rates "[0.1, 1.0, 0.9, 0.2, 0.1, 0.7, 0.1]" --wavelet 'db25' --level 1 --sampling_rate 0.8 >logs/onerun/$model_name'_'ill_$seq_len'_'36'_'0.0'_'$percentage'_'WaveMix.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 48 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 4 --rates "[0.1, 1.0, 0.4, 0.5, 0.1, 0.6, 0.1]" --wavelet 'db3' --level 1 --sampling_rate 1.0 >logs/onerun/$model_name'_'ill_$seq_len'_'48'_'0.0'_'$percentage'_'WaveMix.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 60 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 4 --rates "[0.1, 0.9, 0.3, 0.9, 0.5, 0.7, 0.1]" --wavelet 'db1' --level 1 --sampling_rate 0.5 >logs/onerun/$model_name'_'ill_$seq_len'_'60'_'0.0'_'$percentage'_'WaveMix.log # For Aug 5: STAug python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 24 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 5 --aug_rate 0.7 --nIMF 200 >logs/onerun/$model_name'_'ill_$seq_len'_'24'_'0.9'_'$percentage'_'StAug.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 36 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 5 --aug_rate 0.3 --nIMF 300 >logs/onerun/$model_name'_'ill_$seq_len'_'36'_'0.9'_'$percentage'_'StAug.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 48 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 5 --aug_rate 0.9 --nIMF 300 >logs/onerun/$model_name'_'ill_$seq_len'_'48'_'0.9'_'$percentage'_'StAug.log python3 -u ./run_main.py \ --is_training 1 \ --root_path ./dataset/ \ --data_path national_illness.csv \ --model $model_name \ --data custom \ --features M \ --seq_len $seq_len \ --pred_len 60 \ --enc_in 7 \ --des '100p-ili-' \ --percentage $percentage \ --itr 10 --batch_size 32 --learning_rate 0.01 --aug_type 5 --aug_rate 0.7 --nIMF 1000 >logs/onerun/$model_name'_'ill_$seq_len'_'60'_'0.9'_'$percentage'_'StAug.log