Metadata-Version: 2.1
Name: ptrail
Version: 0.2.Beta
Summary: PTRAIL: A Mobility-data Preprocessing Library using parallel computation.
Home-page: https://github.com/YakshHaranwala/PTRAIL.git
Maintainer: PTRAIL Developers
Maintainer-email: mobilitylab2021@gmail.com
License: new BSD
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.20)
Requires-Dist: hampel (>=0.0.5)
Requires-Dist: pandas (>=1.2.5)
Requires-Dist: scipy (>=1.6.2)
Requires-Dist: psutil (>=5.8.0)
Requires-Dist: folium (>=0.12)
Requires-Dist: matplotlib (>=3.3.4)
Requires-Dist: scikit-learn (>=0.24.2)
Requires-Dist: osmnx (>=1.1.1)
Requires-Dist: geopandas (>=0.8.1)
Requires-Dist: shapely (>=1.7.1)

<!---------------------- Introduction Section ------------------->
<h1> PTRAIL:  A <b><i>P</i></b>arallel 
<b><i>T</i></b>rajectory 
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> Pip Installation </h2>

1. `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>

<!--------------------- Binder Link ---------------------------->
<h2> Examples </h2>

<span> &#8618; </span>
<a href='https://mybinder.org/v2/gh/YakshHaranwala/PTRAIL/ef4be1ed4c535e0dc9bb40226659ac9f9cecffc5' target='_blank'> <i> Binder Link </i> </a>



