- Install the conda environment, via `conda env create --name utci --file env.yml
- Activate the environemnt, via `conda activate utci'
-
Download the raw data
-
Run
python preprocess.py --raw_data data/raw/UHTC_NN --output_dir data -
Run
python preprocess_mean_std.py --output_dir dataand copy the printed strings into the dictionaryUTCI_STATISTICSinutils.py
To train the UTCI model, run
python train.py exp/01 --data_path data --skip 1 2 3 --amp --clip_grad --without_avegTo test the previously trained UTCI model, run
python eval.py exp/01/model.pthIf you want to:
- save detailed information (per sample additionally to the aggregated information), add
--detailed. - plot the UTCI predictions, add
--plot. - save the UTCI predictions as numpy files for further processing, add
--save_np.
To predict UTCIs for a given time period and get the aggregated results, run
python eval_time_period.py exp/01/model.pth --amp --verbose --temporal_data $temporal_datawhere $temporal_data is a placeholder for the path to the csv file with the meteorological data of the time period.