ptrail 1.0
PTRAIL: A Mobility-data Preprocessing Library using parallel computation.
License: new BSD
Requires Python: >=3.6

<!---------------------- Introduction Section ------------------->
<h1> PTRAIL:  A <b><i>P</i></b>arallel 
<b><i>TR</i></b>ajectory 
d<b><i>A</i></b>ta
preprocess<b><i>I</i></b>ng
<b><i>L</i></b>ibrary

 </h1>

<h2> Introduction </h2>

<p align='justify'>
PTRAIL is a state-of-the art Mobility Data Preprocessing Library that mainly deals with filtering data, generating features and interpolation of Trajectory Data.

<b><i> The main features of PTRAIL are: </i></b>
</p>

<ol align='justify'>
<li> PTRAIL uses primarily parallel computation based on
     python Pandas and numpy which makes it very fast as compared
     to other libraries available.
</li>

<li> PTRAIL harnesses the full power of the machine that
     it is running on by using all the cores available in the
     computer.
</li>

<li> PTRAIL uses a customized DataFrame built on top of python
     pandas for representation and storage of Trajectory Data.
</li>

<li> PTRAIL also provides several Temporal and spatial features
     which are calculated mostly using parallel computation for very
     fast and accurate calculations.
</li>

<li> Moreover, PTRAIL also provides several filteration and
     outlier detection methods for cleaning and noise reduction of
     the Trajectory Data.
</li>

<li> Apart from the features mentioned above, <i><b> four </b></i>
     different kinds of Trajectory Interpolation techniques are
     offered by PTRAIL which is a first in the community.
</li>
</ol>

<!------------------------- Documentation Link ----------------->
<h2> Documentation </h2>

<span> &#8618; </span>
<a href='https://PTRAIL.readthedocs.io/en/latest/' target='_blank'> <i> PTRAIL Documentation </i> </a>

<!-------------------- Pip Installation ------------------------->
<h2> Installation </h2>

1. Create Virtual Environment:
  - Using Pip:
    - `python3 -m venv ptr`
    - `source ptr/bin/activate`
    - `pip install PTRAIL`
  - Using Conda:
    - `conda create -c conda-forge ptr python=3.10 rtree`
    - `conda activate ptr`
    - `pip install PTRAIL`

<!------------------------ Usage Examples ----------------------->
<h2> Examples </h2>

<span> &#8618; </span>
<a href='https://github.com/YakshHaranwala/PTRAIL/tree/main/examples' target='_blank'> <i> PTRAIL Examples </i> </a>

<!-------------------- MISC ------------------------------------>
<h2> Miscellaneous </h2>

[![Downloads](https://static.pepy.tech/personalized-badge/ptrail?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads)](https://pepy.tech/project/ptrail)

<!------------------- Citation ---------------------------------->
<h2> Citation </h2>

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

```bibtex
@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}
}
```