pip install -r requirements.txt
python evaluation.py [-h] [--level LEVEL] [--day_lag DAY_LAG] [--step STEP]
[--start_date START_DATE] [--end_date END_DATE]
[--run_comparison RUN_COMPARISON]
[--plot_prediction PLOT_PREDICTION]
[--plot_param PLOT_PARAM] [--image_folder IMAGE_FOLDER]
[--cuda CUDA]
Optional arguments:
-h, --help show this help message and exit
--level LEVEL 0: world; 1: countries; 2: both
--day_lag DAY_LAG The number of day lag.
--step STEP The number of forecasting step.
--start_date START_DATE
The start day from which to make prediction.
--end_date END_DATE The end date of prediction.
--run_comparison RUN_COMPARISON
Wheather to compare model.
--plot_prediction PLOT_PREDICTION
Wheather to plot prediction.
--plot_param PLOT_PARAM
Wheather to plot parameters.
--image_folder IMAGE_FOLDER
Where to save plotted pictures.
--cuda CUDA Enable cuda
Edit .env file for following arguments
Optional arguments:
INIT_DATA Whether run prediction.
DATA_DIR Where to store website data.
CUDA_VISIBLE_DEVICES GPU device
PORT Deployment port
Then run
bash run_web.sh
In our experiments, we use a computer with below configurations.
Processor Intel(R) Core(TM) i7-4940MX CPU @ 3.10GHz 3.30 GHz
RAM 32.0 GB
GPU NVIDIA Quadro K2100M 2GB
Python 3.7.5
You should run the following commands.
python evaluation.py --level 0 --day_lag 7 --step 31 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/world_7_step_31.txt
python evaluation.py --level 0 --day_lag 10 --step 31 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/world_10_step_31.txt
python evaluation.py --level 0 --day_lag 14 --step 31 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/world_14_step_31.txt
After that, you will have 3 result files located in results folder. Then, you can use those files to compare performance and choose the best suitable day lag number.
The command to do this task is the same as the one provided in Part 1.
python evaluation.py --level 0 --day_lag 10 --step 31 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/world_10_step_31.txt
To reproduce this task, you need to run the evaluation 3 times with different step number. The commands for this task are provided below.
python evaluation.py --level 1 --day_lag 10 --step 1 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/countries_10_step_1.txt
python evaluation.py --level 1 --day_lag 10 --step 7 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/countries_10_step_7.txt
python evaluation.py --level 1 --day_lag 10 --step 15 --start_date 161 --end_date 192 --run_comparison 1 --cuda 1 | grep ... > results/countries_10_step_15.txt
You should run the below command. After successfully running this command, the figures will be saved in images/world folder.
python evaluation.py --level 0 --day_lag 10 --start_date 161 --end_date 192 --plot_prediction 1 --plot_param 1 --cuda 1
You should run the below command. After successfully running this command, the figure swill be saved in images/[COUNTRY NAME] folder.
python evaluation.py --level 1 --day_lag 10 --start_date 161 --end_date 223 --plot_prediction 1 --plot_param 1 --cuda 1
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