Metadata-Version: 2.1
Name: movekit
Version: 0.1.24
Summary: Simple and effective tools for the analysis of movement data
Home-page: https://github.com/dbvis-ukon/movekit
Author: Lukas Weixkler, Arjun Majumdar, Eren Cakmak, Jolle Jolles
Author-email: lukas.weixler@uni-konstanz.de, arjun.majumdar@uni-konstanz.de, eren.cakmak@uni-konstanz.de, j.w.jolles@gmail.com
License: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Project-URL: Documentation, https://pyscaffold.org/
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Requires-Python: <3.10,>=3.5
Description-Content-Type: text/markdown; charset=UTF-8
Provides-Extra: testing
License-File: LICENSE
License-File: AUTHORS.rst

MOVEKIT
======

<p align="center">
    <img src="media/mover.gif" height=150px/>
    <img src="media/voronoi.png" height=150px>
    <img src="media/network.png" height=150px>
    <img src="media/movement.png" height=150px>
    <img src="media/movebank.png" height=150px>
    <img src="media/clustering.png" height=150px>
</p>


`movekit` is an open-source software package for the processing and analysis of movement data.

__`movekit` supports different tasks:__

* Data pre-processing
  * Clean data (remove duplicates, drop missing values, etc.)
  * Normalize and filter the data
  * ...
* Feature extraction:
  * Extract different features such as the distance covered, average speed, the average acceleration, etc. 
  * Apply time series analysis on these extracted features
  * Check different distances (euclidean & hausdorff) between movers
  * Detect outliers in data
  * ...
* Group-level analysis
  * Calculate centroids and medoids of the group of movers for different time steps
  * Compute polarization of movers
  * Identify different clusters/groups
  * Obtain dynamic time warping of all mover trajectories 
  * ...
* Spatial data analysis:
  * Create convex hull, voronoi diagram and delaunay triangulation for all movers at each time step
  * Extract areas of the created objects
* Network analysis with networkX
  * Create networks created for each time step and examine their attributes (centroid, polarization, total distance, mean speed, ...)
  * Investigate individual nodes of each time steps network graph
  * Investigate individual edges of each time steps network graph
  * Track development of network graphs over time
  * ...
* Plotting analysis results:
  * Create basic plots for features such as acceleration or speed
  * Plot movement of movers in static or animated images
  * Create interactive map to plot geo data

`movekit` provides support for movement data and trajectories in different format:

__Data:__

* 2-dimensional data in the Euclidean space
* 3-dimensional data in the Euclidean space
* GPS coordinates (latitude and longitude)
* Data with different time formats
* Data in (Geo)JSON format
* Data from Movebank data base

---

## Installation

The easiest way to install *movekit* is by using `pip` :

    pip install movekit

---

## Docs & Demo

The following website contains the [documentation](https://movekit.readthedocs.io/en/latest/)

You can view a demo of common features here:
[Jupyter Notebooks](examples/).

---

### License

Released under a GNU General Public License. See the [LICENSE](LICENSE) file for details. List of [Authors](AUTHORS.rst)

The package is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2117 – 422037984.


