A light package for build and analyse co-locationship for paper: Contrasting social and non-social sources of predictability in human mobility
Project description
co-locationship
Leveraging information transfer in social and co-location networks to improve predictability in human mobility
The code was tested on Python 3.6.
Install (via pypi version)
pip install colocationship
Install (via GitHub)
git clone https://github.com/Magica-Chen/co-locationship.git
cd co-locationship
The dependencies package are shown in requirements.txt
, also, you can run
pip install -r requirements.txt
After installing all dependencies clone the repository and do (inside the top directory):
pip install .
This will install a copy of the code as a package. If you want to install a package that links to the cloned code, run
pip install --editable .
This makes changes to the source files in the cloned directory immediately available to everything that imports the package.
After installation, anywhere on the system you can then import the package:
import colocationship as cl
Dataset
All processed datasets (Weeplaces, BrightKite, Gowalla) we used in this repo can be found in Google Drive.
Usage
The example please refers to example/example_weeplaces.ipynb
.
Project details
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