Metadata-Version: 2.1
Name: pymove
Version: 1.1.7
Summary: A lib python to processing and visualization of trajectories and other spatial-temporal data
Home-page: https://github.com/InsightLab/PyMove
Author: Insight Data Science Lab
Author-email: insightlab@dc.ufc.br
License: MIT
Description: # Use PyMove and go much further
        
        ---
        
        ## Information
        
        <table>
        <tr>
          <td>Package Status</td>
          <td>
            <a href="https://pypi.org/project/pymove/">
            <img src="https://img.shields.io/pypi/status/pymove.svg" alt="status" />
            </a>
          </td>
        </tr>
        <tr>
          <td>License</td>
          <td>
            <a href="https://github.com/InsightLab/PyMove/blob/developer/LICENSE">
            <img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="license" />
            </a>
        </td>
        </tr>
        <tr>
          <td>Python Version</td>
          <td>
            <a href="https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8-blue">
            <img src="https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8-blue" alt="license" />
            </a>
        </td>
        </tr>
        <tr>
          <td>Build Status</td>
          <td>
            <a href="https://travis-ci.org/InsightLab/PyMove/">
            <img src="https://api.travis-ci.org/InsightLab/PyMove.svg?branch=developer" alt="travis build status" />
            </a>
          </td>
        </tr>
        <tr>
          <td>Downloads</td>
          <td>
            <img src="https://img.shields.io/pypi/dd/pymove" alt="PyPi downloads" />
            </a>
          </td>
        </tr>
        <tr>
          <td>Stars</td>
          <td>
            <a href="https://github.com/InsightLab/PyMove/stargazers">
            <img src="https://img.shields.io/github/stars/InsightLab/PyMove?style=social"/>
            </a>
          </td>
        </tr>
        <tr>
          <td>Forks</td>
          <td>
              <a href="https://github.com/InsightLab/PyMove/network/members">
            <img src="https://img.shields.io/github/forks/InsightLab/PyMove?style=social"/>
            </a>
          </td>
        </tr>
        <tr>
          <td>Issues</td>
          <td>
            <a href="https://github.com/InsightLab/PyMove/issues">
            <img src="https://img.shields.io/github/issues/InsightLab/PyMove"/>
            </a>
          </td>
        </tr>
        </table>
        
        ---
        
        ## What is PyMove
        
        PyMove is a Python library for processing and visualization of trajectories and other spatial-temporal data.
        
        We will also release wrappers to some useful Java libraries frequently used in the mobility domain.
        
        ---
        
        ## Main Features
        
        PyMove **proposes**:
        
        - A familiar and similar syntax to Pandas;
        - Clear documentation;
        - Extensibility, since you can implement your main data structure by manipulating other data structures such as Dask DataFrame, numpy arrays, etc., in addition to adding new modules;
        - Flexibility, as the user can switch between different data structures;
        - Operations for data preprocessing, pattern mining and data visualization.
        
        ---
        
        ## Creating Virtual Environment
        
        It is recommended to create a virtual environment to use pymove. Requirements: Anaconda Python distribution installed and accessible
        
        1. In the terminal client enter the following where `yourenvname` is the name you want to call your environment, and replace `x.x` with the Python version you wish to use. (To see a list of available python versions first, type conda search "^python$" and press enter.)
            - `conda create -n <yourenvname> python=x.x`
            - Press y to proceed. This will install the Python version and all the associated anaconda packaged libraries at `path_to_your_anaconda_location/anaconda/envs/yourenvname`
        2. Activate your virtual environment. To activate or switch into your virtual environment, simply type the following where yourenvname is the name you gave to your environment at creation.
            - `conda activate <yourenvname>`
        3. Now install the package from pip or github in the virtual environment
        4. If using Windows, you must install `shapely` apart using the command `conda install shapely`. This is due to some dll dependencies
        
        ---
        
        ## Github installation
        
        1. Clone this repository
            - `git clone https://github.com/InsightLab/PyMove`
        2. Make a branch developer
            - `git branch developer`
        3. Switch to a new branch
            - `git checkout developer`
        4. Make a pull of branch
            - `git pull origin developer`
        5. Switch to folder PyMove
            - `cd PyMove`
        6. Install pymove in developer mode
            - `pip install -e .`
        
        ---
        
        ## Pip installation
        
        1. `pip install pymove`
        
        ---
        
        ## Examples
        
        You can access examples of how to use PyMove [here](examples)
        
        ---
        
        ## Papers
        
        (list of publications using/with Pymove)
        
        ---
        
        ## Useful list of related libraries and links
        
        - [Handling GPS Data with Python](https://github.com/FlorianWilhelm/gps_data_with_python/tree/master/notebooks)
        - [mplleaflet - Easily convert matplotlib plots from Python into interactive Leaflet web maps](https://github.com/jwass/mplleaflet)
        - [Pykalman](https://github.com/pykalman/pykalman)
        - [Ramer-Douglas-Peucker algorithm](https://github.com/fhirschmann/rdp)
        - [Knee point detection in Python](https://github.com/arvkevi/kneed)
        - [TrajSuite Java Library](https://github.com/lukehb/TrajSuite)
        - [GraphHopper Map-Matching Java Library](https://github.com/graphhopper/map-matching)
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
