A lib python to processing and visualization of trajectories and other spatial-temporal data
Project description
Use PyMove and go much further...
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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.
Github installation
- Clone this repository
git clone https://github.com/InsightLab/PyMove
- Make a branch developer
git branch developer
- Switch to a new branch
git checkout developer
- Make a pull of branch
git pull origin developer
- Switch to folder PyMove
cd PyMove
- Install pymove in developer mode
pip install -e .
Pip installation
pip install pymove
Creating Virtual Environment
In case of an error when running the library, it is recommended to create a virtual environment to use pymove. Requirements: Anaconda Python distribution installed and accessible
- 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”
- 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 environement at creation.
source activate <yourenvname>
- Now install the package from pip or github in the virtual environment
Examples
You can access examples of how to use PyMove here
Papers
(list of publications using/with Pymove)
Useful list of related libraries and links
Project details
Release history Release notifications | RSS feed
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