PTRAIL: A Parallel TRajectory dAta preprocessIng Library

Introduction

PTRAIL is a state-of-the art Mobility Data Preprocessing Library that mainly deals with filtering data, generating features and interpolation of Trajectory Data.

The main features of PTRAIL are:

• PTRAIL uses primarily parallel computation based on python Pandas and numpy which makes it very fast as compared to other libraries available.
• PTRAIL harnesses the full power of the machine that it is running on by using all the cores available in the computer.
• PTRAIL uses a customized DataFrame built on top of python pandas for representation and storage of Trajectory Data.
• PTRAIL also provides several Temporal and spatial features which are calculated mostly using parallel computation for very fast and accurate calculations.
• Moreover, PTRAIL also provides several filteration and outlier detection methods for cleaning and noise reduction of the Trajectory Data.
• Apart from the features mentioned above, four different kinds of Trajectory Interpolation techniques are offered by PTRAIL which is a first in the community.

Documentation

↪ PTRAIL Documentation

Installation

• Create Virtual Environment:

Examples

↪ PTRAIL Examples

Miscellaneous

Citation

To cite PTRAIL in your academic work, please use the following citation:

@article{haidri2022ptrail,
  title={PTRAIL—A python package for parallel trajectory data preprocessing},
  author={Haidri, Salman and Haranwala, Yaksh J and Bogorny, Vania and Renso, Chiara and da Fonseca, Vinicius Prado and Soares, Amilcar},
  journal={SoftwareX},
  volume={19},
  pages={101176},
  year={2022},
  publisher={Elsevier}
}