Examples

Running examples

Notes

Python packages time, pandas, seaborn, geopandas, and matplotlib are required to run the following experiments.

• A simple pipeline illsutrating the basic features of the package is available here.
• Several simulation examples are available, to illustrate the usage of geospaNN for different statistical tasks:
  • Choice of neural network architectures.
  • Compare with the add-to-spatial-feature approaches.
  • Compare with GAM.
• A real data experiment is shown here.

In the real data experiment, the PM2.5 data is collected from the U.S. Environmental Protection Agency datasets for each state are collected and bound together to obtain 'pm25_2022.csv'. daily PM2.5 files are subsets of 'pm25_2022.csv' produced by 'realdata_preprocess.py'. One can skip the preprocessing and use the daily files directory.

The meteorological data is collected from the National Centers for Environmental Prediction's (NCEP) North American Regional Reanalysis (NARR) product. The '.nc' (netCDF) files should be downloaded from the website and saved in the root directory to run 'realdata_preprocess.py'. Otherwise, one may skip the preprocessing and use covariate files directly.