Metadata-Version: 2.1
Name: traja
Version: 0.0.2a2
Summary: Traja is a trajectory analysis and visualization tool
Home-page: https://github.com/justinshenk/traja
Author: Justin Shenk
Author-email: shenkjustin@gmail.com
License: MIT license
Description: # traja
        Trajectory Analysis in Python
        
        traja extends the capability of pandas DataFrame specific for animal trajectory analysis in 2D, and provides convenient interfaces to other geometric analysis packages (eg, shapely).
        
        ## Introduction
        
        The traja Python package is a toolkit for the numerical characterisation and analysis of the trajectories of moving animals. Trajectory analysis is applicable in fields as diverse as optimal foraging theory, migration, and behavioural mimicry (e.g. for verifying similarities in locomotion). A trajectory is simply a record of the path followed by a moving animal. Trajr operates on trajectories in the form of a series of locations (as x, y coordinates) with times. Trajectories may be obtained by any method which provides this information, including manual tracking, radio telemetry, GPS tracking, and motion tracking from videos.
        
        The goal of this package (and this document) is to aid biological researchers, who may not have extensive experience with Python, to analyse trajectories without being handicapped by a limited knowledge of Python or programming. However, a basic understanding of Python is useful.
        
        If you use traja in your publications, please cite [add citation].
        
        ## Installation and setup
        
        To install traja onto your system, run
        
        ```pip install traja```
        
        or download the zip file and run the graphical user interface [coming soon].
        
        Import traja into your Python script or via the Python command-line with `import traja`.
        
        ## Trajectories with traja
        
        traja stores trajectories in pandas DataFrames, allowing any pandas functions to be used.
        
        Load trajectory with x,y and time coordinates:
        
        ```python
        import traja
        
        df = traja.read_file('coords.csv')
        ```
        
        Once a DataFrame is loaded, use the `.traja` accessor to access the visualization and analysis methods:
        
        ```python
        df.traja.plot(title='Cage trajectory')
        ```
        
        ![dvc_screenshot](dvc_screenshot.png)
        
        ### Random walk
        
        Generate random walks with
        
        ```python
        df = traja.generate(n=1000, step_length=2)
        df.traja.plot()
        
        ```
        
        ![walk_screenshot.png](walk_screenshot.png)
        
        ## Demo
        
        Coming soon.
        
        ## Acknowledgements
        
        traja code implementation and analytical methods (particularly `rediscretize_points`) are heavily inspired by Jim McLean's R package [trajr](https://github.com/JimMcL/trajr). Many thanks to Jim for his feedback. 
        
Keywords: trajectory analysis
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Libraries
Requires-Python: != 3.0.*, != 3.1.*
Description-Content-Type: text/markdown
