This codebase is an adaptation of the Python Telecommunication Assessment Library (pytal) applied to India. The repo enables 5G strategies to be tested with the ultimate aim of helping to connect more people to a faster internet.
Importantly, we provide all data inputs and code so that the results can be reproduced. Both unit tests and integration tests are provided for the codebase to ensure reliability.
The recommended installation method is to use conda, which handles packages and virtual environments, along with the conda-forge channel which has a host of pre-built libraries and packages.
Create a conda environment called India5G:
conda create --name india5g python=3.6 gdal geopandas
Activate it (run this each time you switch projects):
conda activate india5g
Install India5G:
python setup.py install
Alternatively, for development purposes, clone this repo and run:
python setup.py develop
You will need numerous input data sets.
First, download the Global Administrative Database (GADM), following the link below and making sure you download the "six separate layers.":
Place the data into the following path data/raw/gadm36_levels_shp.
Then download the WorldPop global settlement data from:
Place the data in data/raw/settlement_layer.
Next, download the nightlight data here:
https://ngdc.noaa.gov/eog/data/web_data/v4composites/F182013.v4.tar
Place the unzipped data in data/raw/nightlights/2013.
Obtain the Mobile Coverage Explorer data from Collins Bartholomew:
https://www.collinsbartholomew.com/mobile-coverage-maps/mobile-coverage-explorer/
Place the data into data/raw/Mobile Coverage Explorer.
Once complete, run the following to preprocess all data:
python scripts/preprocess.py
To obtain model results once all inputs have been generated, simply execute the runner script:
python scripts/run.py
India5G was written and developed at GGS, George Mason University <https://science.gmu.edu/academics/departments-units/geography-geoinformation-science>.