Skip to content

zxcver/SFINet

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
data_process
data_process
 
 
experiments
experiments
 
 
metrics
metrics
 
 
models
models
 
 
utils
utils
 
 
.gitignore
.gitignore
 
 
README.md
README.md
 
 
run_ETTh.py
run_ETTh.py
 
 

Repository files navigation

SFINet

Introduction

We release the code on "SFINet: Shuffle–and–Fusion Interaction Networks for Wind Power Forecasting".
We mainly reference the code with SCINet.

Install

please note your cuda version and reference get-started while install pytorch.

cd SFINet
conda create -n sfinet python=3.8
conda activate sfinet
pip install torch torchvision torchaudio 
pip install -r requirements.txt

Data Preparation

./
└── datasets/
    ├── ETT-data
    │   ├── ETTh1.csv
    │   ├── ETTh2.csv
    │   └── ETTm1.csv
    └── windpower
        ├── wpm1.csv
        └── wpm2.csv

We follow the same settings of SCINet for ETTH1, ETTH2, ETTM1 datasets. Since the privacy implications of the data set are being considered, we cannot release WP datasets.

Training

ETTh1

Multivariate, out 24

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features M  --train_epochs 100 --seq_len 48 \
                        --label_len 24 --pred_len 24 --lr 0.02 --batch_size 512 --hidden_size 2 --levels 4

Multivariate, out 48

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features M  --train_epochs 100 --seq_len 96 \
                        --label_len 48 --pred_len 48 --lr 0.01 --batch_size 96 --hidden_size 1 --levels 5

Multivariate, out 168

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features M  --train_epochs 100 --seq_len 336 \
                        --label_len 168 --pred_len 168 --lr 0.005 --batch_size 128 --hidden_size 1 --levels 3

Multivariate, out 336

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features M  --train_epochs 100 --seq_len 672 \
                        --label_len 336 --pred_len 336 --lr 0.0001 --batch_size 256 --hidden_size 1 --levels 1

Multivariate, out 720

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features M  --train_epochs 100 --seq_len 1440 \
                        --label_len 720 --pred_len 720  --lr 0.0001 --batch_size 256 --hidden_size 1 --levels 1

Univariate, out 24

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features S --train_epochs 100 --seq_len 48 \
                        --label_len 24 --pred_len 24 --lr 0.02 --batch_size 256 --hidden_size 4 --levels 4

Univariate, out 48

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features S --train_epochs 100 --seq_len 96 \
                        --label_len 48 --pred_len 48 --lr 0.05 --batch_size 512 --hidden_size 1 --levels 1

Univariate, out 168

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features S --train_epochs 100 --seq_len 336 \
                        --label_len 168 --pred_len 168 --lr 0.001 --batch_size 128 --hidden_size 4 --levels 3

Univariate, out 336

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features S --train_epochs 100 --seq_len 672 \
                        --label_len 336 --pred_len 336 --lr 0.001 --batch_size 64 --hidden_size 2 --levels 1

Univariate, out 720

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh1.csv --features S --train_epochs 100 --seq_len 1440 \
                        --label_len 720 --pred_len 720 --lr 0.001 --batch_size 512 --hidden_size 1 --levels 2

ETTh2

Multivariate, out 24

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features M  --train_epochs 100 --seq_len 48 \
                        --label_len 24 --pred_len 24 --lr 0.01 --batch_size 128 --hidden_size 1 --levels 4

Multivariate, out 48

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features M  --train_epochs 100 --seq_len 96 \
                        --label_len 48 --pred_len 48 --lr 0.007 --batch_size 96 --hidden_size 2 --levels 3

Multivariate, out 168

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features M  --train_epochs 100 --seq_len 336 \
                        --label_len 168 --pred_len 168 --lr 0.005 --batch_size 128 --hidden_size 1 --levels 4

Multivariate, out 336

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features M  --train_epochs 100 --seq_len 672 \
                        --label_len 336 --pred_len 336 --lr 0.01 --batch_size 128 --hidden_size 1 --levels 2

Multivariate, out 720

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features M  --train_epochs 100 --seq_len 1440 \
                        --label_len 720 --pred_len 720  --lr 0.005 --batch_size 512 --hidden_size 1 --levels 1

Univariate, out 24

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features S --train_epochs 100 --seq_len 48 \
                        --label_len 24 --pred_len 24 --lr 0.05 --batch_size 512 --hidden_size 2 --levels 1

Univariate, out 48

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features S --train_epochs 100 --seq_len 96 \
                        --label_len 48 --pred_len 48 --lr 0.05 --batch_size 256 --hidden_size 4 --levels 1

Univariate, out 168

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features S --train_epochs 100 --seq_len 336 \
                        --label_len 168 --pred_len 168 --lr 0.002 --batch_size 512 --hidden_size 2 --levels 2

Univariate, out 336

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features S --train_epochs 100 --seq_len 672 \
                        --label_len 336 --pred_len 336 --lr 0.02 --batch_size 512 --hidden_size 1 --levels 2

Univariate, out 720

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTh2.csv --features S --train_epochs 100 --seq_len 1440 \
                        --label_len 720 --pred_len 720 --lr 0.02 --batch_size 512 --hidden_size 1 --levels 3

ETTm1

Multivariate, out 24

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features M  --train_epochs 100 --seq_len 48 \
                        --label_len 24 --pred_len 24 --lr 0.001 --batch_size 96 --hidden_size 4 --levels 1

Multivariate, out 48

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features M  --train_epochs 100 --seq_len 96 \
                        --label_len 48 --pred_len 48 --lr 0.001 --batch_size 96 --hidden_size 1 --levels 4

Multivariate, out 96

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features M  --train_epochs 100 --seq_len 48 \
                        --label_len 96 --pred_len 96 --lr 0.001 --batch_size 96 --hidden_size 4 --levels 3

Multivariate, out 288

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features M  --train_epochs 100 --seq_len 672 \
                        --label_len 288 --pred_len 288 --lr 0.0001 --batch_size 96 --hidden_size 1 --levels 1

Multivariate, out 672

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features M  --train_epochs 100 --seq_len 672 \
                        --label_len 672 --pred_len 672 --lr 0.00005 --batch_size 32 --hidden_size 1 --levels 1

Univariate, out 24

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features S  --train_epochs 100 --seq_len 96 \
                        --label_len 24 --pred_len 24 --lr 0.001 --batch_size 16 --hidden_size 4 --levels 2

Univariate, out 48

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features S  --train_epochs 100 --seq_len 96 \
                        --label_len 48 --pred_len 48 --lr 0.002 --batch_size 96 --hidden_size 2 --levels 2

Univariate, out 96

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features S  --train_epochs 100 --seq_len 384 \
                        --label_len 96 --pred_len 96 --lr 0.01 --batch_size 96 --hidden_size 1 --levels 1

Univariate, out 288

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features S  --train_epochs 100 --seq_len 672 \
                        --label_len 288 --pred_len 288 --lr 0.001 --batch_size 96 --hidden_size 1 --levels 1

Univariate, out 672

    python run_ETTh.py --data ETTh1 --gpu 0 --patience 80 --root_path datasets/ETT-data \
                        --data_path ETTm1.csv --features S  --train_epochs 100 --seq_len 672 \
                        --label_len 672 --pred_len 672 --lr 0.0005 --batch_size 96 --hidden_size 4 --levels 4

Reference

SCINet

About

No description, website, or topics provided.

Resources

Readme
Activity

Stars

2 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages