/FusionSF

Primary LanguagePython

FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting

python pytorch lightning hydra license

Description

This is the official repository to the paper "FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting" by Ziqing Ma*, Wenwei Wang*, Tian Zhou*, Chao Chen, Bingqing Peng, Liang Sun and Rong Jin. (* equal contribution)

Dataset

You can access the dataset as follows:

Folder: https://drive.google.com/drive/folders/1qGVOw-hAVQlO3n-1d4ZNHvL42L9PkdBK?usp=drive_link

Zip File: https://drive.google.com/file/d/18Y-kwNUkT9t5EBugWxtDoE5HnMfaFG2D/view?usp=drive_link

The dataset is supposed to be organized as follows: ./data/nwp/nwp.csv ./data/satellite/satellite.npy ./data/satellite/satellite_coords.npy ./data/satellite/satellite_times.npy ./data/solar_power/solar_power.csv

Installation

Pip

# clone project
git clone https://github.com/MAZiqing/FusionSF.git
cd FusionSF

# [OPTIONAL] create conda environment
conda create -n MyEnvName python=3.10
conda activate MyEnvName

# install requirements
pip install -r requirements.txt

Experiments

To help the users reproduce our results, we released the sbatch scripts that we used.

  • FusionSF (145M): scripts/fusionSF.sh

License

CrossViVit is licensed under the MIT License.

MIT License

Copyright (c) (2023) Ghait Boukachab

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