Metadata-Version: 2.1
Name: automatize
Version: 1.0b1
Summary: Automatize: A Multiple Aspect Trajectory Data Mining Tool Library
Home-page: https://github.com/ttportela/automatize
Author: Tarlis Tortelli Portela
Author-email: Tarlis Tortelli Portela <tarlis@tarlis.com.br>
Maintainer-email: Tarlis Tortelli Portela <tarlis@tarlis.com.br>
License: GPL Version 3 or superior (see LICENSE file)
Project-URL: homepage, https://github.com/ttportela/automatize
Project-URL: repository, https://github.com/ttportela/automatize
Project-URL: documentation, https://github.com/ttportela/automatize
Project-URL: download, https://pypi.org/project/automatize/#files
Keywords: data-science,machine-learning,data-mining,trajectory,multiple-trajectory,trajectory-classification,movelet,movelet-visualization
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Operating System :: OS Independent
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: <3.10,>=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: glob2 (==0.7)
Requires-Dist: numpy
Requires-Dist: pandas (==1.3.4)
Provides-Extra: all_extras
Requires-Dist: python-dateutil (==2.8.2) ; extra == 'all_extras'
Requires-Dist: anytree (==2.8.0) ; extra == 'all_extras'
Requires-Dist: chart-studio (==1.1.0) ; extra == 'all_extras'
Requires-Dist: colorlover (==0.3.0) ; extra == 'all_extras'
Requires-Dist: cycler (==0.11.0) ; extra == 'all_extras'
Requires-Dist: graphviz (==0.19.1) ; extra == 'all_extras'
Requires-Dist: jsonschema (==4.3.1) ; extra == 'all_extras'
Requires-Dist: matplotlib (==3.5.1) ; extra == 'all_extras'
Requires-Dist: mpld3 (==0.5.7) ; extra == 'all_extras'
Requires-Dist: networkx (==2.6.3) ; extra == 'all_extras'
Requires-Dist: notebook (==6.4.6) ; extra == 'all_extras'
Requires-Dist: plotly (==5.4.0) ; extra == 'all_extras'
Requires-Dist: tensorflow ; extra == 'all_extras'
Requires-Dist: pm4py ; extra == 'all_extras'
Requires-Dist: geohash ; extra == 'all_extras'
Requires-Dist: scikit-learn ; extra == 'all_extras'
Provides-Extra: binder
Requires-Dist: jupyter ; extra == 'binder'
Provides-Extra: dev
Requires-Dist: pre-commit ; extra == 'dev'
Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: pytest-cov ; extra == 'dev'
Requires-Dist: pytest-xdist ; extra == 'dev'
Requires-Dist: wheel ; extra == 'dev'
Provides-Extra: dl
Requires-Dist: tensorflow ; extra == 'dl'
Provides-Extra: docs
Requires-Dist: jupyter ; extra == 'docs'
Requires-Dist: numpydoc ; extra == 'docs'

# Automatize: Multiple Aspect Trajectory Data Mining Tool Library
---

Welcome to Automatize Framework for Multiple Aspect Trajectory Analysis. You can use it as a web-platform or a Python library.

The present application offers a tool, called AutoMATize, to support the user in the classification task of multiple aspect trajectories, specifically for extracting and visualizing the movelets, the parts of the trajectory that better discriminate a class. The AutoMATize integrates into a unique platform the fragmented approaches available for multiple aspects trajectories and in general for multidimensional sequence classification into a unique web-based and python library system. Offers both movelets visualization and a complete configuration of classification experimental settings.


### *Attention:* this package is being tested and finalized for the second beta version more complete than the previous package:

For now, you can install and use the previous version in:

```bash
    pip install automatise
```

