lcandeago / scikit-mobility

scikit-mobility: mobility analysis in Python

scikit-mobility

Human Mobility analysis in Python

scikit-mobility is a library for human mobility analysis in Python. The library allows to:

• represent trajectories and mobility flows with proper data structures, TrajDataFrame and FlowDataFrame.

• manage and manipulate mobility data of various formats (call detail records, GPS data, data from Location Based Social Networks, survey data, etc.);

• extract human mobility metrics and patterns from data, both at individual and collective level (e.g., length of displacements, characteristic distance, origin-destination matrix, etc.)

• generate synthetic individual trajectories using standard mathematical models (random walk models, exploration and preferential return model, etc.)

• generate synthetic mobility flows using standard migration models (gravity model, radiation model, etc.)

• assess the privacy risk associated with a mobility dataset

Install

First, clone the repository - this creates a new directory ./scikit_mobility.

    git clone https://github.com/scikit-mobility/scikit-mobility scikit_mobility

with conda - miniconda

1. Create an environment skmob and install pip

    conda create -n skmob pip
   

2. Activate

    conda activate skmob
   

3. Install skmob

    cd scikit_mobility
    python setup.py
   

   If the installation of a required library fails, reinstall it with conda install.

4. OPTIONAL to use scikit-mobility on the jupyter notebook

   • Install the kernel

     conda install ipykernel
     

   • Open a notebook and check if the kernel skmob is on the kernel list. If not, run the following:

     env=$(basename `echo $CONDA_PREFIX`)
     python -m ipykernel install --user --name "$env" --display-name "Python [conda env:"$env"]"
     

without conda (python >= 3.6 required)

1. Create an environment skmob

    python3 -m venv skmob
   

2. Activate

    source skmob/bin/activate
   

3. Install skmob

    cd scikit_mobility
    python setup.py install
   

4. OPTIONAL to use scikit-mobility on the jupyter notebook

   • Activate the virutalenv:

       source skmob/bin/activate
     

   • Install jupyter notebook:

       pip install jupyter 
     

   • Run jupyter notebook

       jupyter notebook
     

   • (Optional) install the kernel with a specific name

       ipython kernel install --user --name=skmob
     

Test the installation

> source activate skmob
(skmob)> python
>>> import skmob
>>>