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Co-authored-by: Gustavo Viera López <[email protected]>
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jmorgadov and gvieralopez committed Jun 7, 2023
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name: Run tests

on: [push, workflow_dispatch]
on: [push]

jobs:
test:
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89.83 79.1 82.35 91.42 87.88 95.76
```

## Available datasets

See the whole [list of datasets](https://github.com/yupidevs/trajectory-datasets) compatible with pactus


## Contributing

Follow the guidlines from [pactus documentation](https://pactus.readthedocs.io/en/latest/)
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Available datasets
==================

All datasets are available in the `releases section
<https://github.com/yupidevs/trajectory-datasets/releases>`_ of the `trajectory
dataset <https://github.com/yupidevs/trajectory-datasets>`_ repository.

.. list-table::
:header-rows: 1

* - Dataset
- Description
- Classification Goal
* - geolife
- | Records of people
| outdoor movements
- | **Transportation mode:**
| walk • bike • bus • car • subway
| train • airplane • boat • run
| motorcycle
* - animals
- | Elk, deer and cattle dataset.
| `Starkey Project <https://www.fs.usda.gov/research/treesearch/21989>`_
- | **Animal species**
| Elk • Deer • Cattle
* - hurdat2
- | Atlantic hurricane database
- | **Huracane intensity (Saffir-Simpson scale):**
| 0 • 1 • 2 • 3 • 4 • 5
| *(Zero means it was not a hurricane)*
* - mnist_stroke
- | Sequences of strokes
| representing
| handwritten digits
- | **Decimal digits:**
| 1 • 2 • 3 • 4 • 5 • 6 • 7 • 8 • 9 • 0
* - cma_bst
- | Western North Pacific tropical
| cyclone database
- | **Huracane intensity:**
| Weaker or unknown • Tropical Depression
| Tropical Storm • Severe Tropical Storm
| Typhoon • Severe Typhoon • Super Typhoon
| Extratropical Cyclone
* - uci_gotrack
- Cars and buses GPS trayectories
- | **Transportation mode:**
| bus • car
* - uci_pen_digits
- | Pen-Based Recognition of
| Handwritten Digits
- | **Decimal digits:**
| 1 • 2 • 3 • 4 • 5 • 6 • 7 • 8 • 9 • 0
* - uci_characters
- Character Trajectories Data Set
- | **Characters:**
| a • b • c • d • e • g • h • l • m • n • o
| p • q • r • s • u • v • w • y • z
* - uci_movement_libras
- | LIBRAS (brazilian signal
| language) movement dataset
- | **Movement type:**
| curved swing • horizontal swing
| vertical swing • anti-clockwise arc
| clockwise arc • horizontal straight-line
| circle • vertical straight-line
| horizontal zigzag • vertical zigzag
| horizontal wavy • vertical wavy
| face-up curve • face-down curve • tremble
* - stochastic_models
- | Trajectories generated
| using statistical models
- | **Model used:**
| Random Walk • Langevin Ecquation
| Diffusing Diffusivity
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Adding datasets
===============
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Adding featurizers
==================
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Adding models
=============
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Increasing Visibility and Engagement
====================================
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Report issues
=============
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Example 1
=========
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Example 2
=========
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Example 3
=========
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Example 4
=========
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Installation and compatibility
==============================

To start using pactus, simply install it from pypi:

>>> pip install pactus

pactus is compatible with:

* Python 3.8 or later
* Ubuntu 18.04 or later
* Windows 7 or later
* macOS 10.12.6 (Sierra) or later.
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Getting Support
===============

There are different options you can use for support:

* You can ask questions and join the development discussion on our `Telegram group <https://t.me/yupi_discuss>`_.

* You can also post bug reports and feature requests in `GitHub issues <https://github.com/yupidevs/pactus/issues>`_.

* You can email us directly:

* | Gustavo Viera López <[email protected]>
* | Alfredo Reyes <[email protected]>
* | Jorge Morgado <[email protected]>

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67 changes: 59 additions & 8 deletions docs/source/index.rst
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Welcome to pactus's documentation!
==================================

.. .. toctree::
.. :maxdepth: 2
.. :caption: Getting Started
Standing from Path Classification Tools for Unifying Strategies, `pactus`
is a Python library that allows testing different classification methods on
several trajectory datasets.

It comes with some built-in models and datasets according to the
state-of-the-art in trajectory classification. However, it is implemented in an
extensible way, so the users can build their own models and datasets.

.. figure:: /images/example.jpg
:alt: Minimal example of a pactus classification task
:align: center
:width: 550

*pactus capabilities represented in an example classification task.*

.. note::
Code from the example shown above:

.. code-block:: python
from pactus import Dataset, featurizers
from pactus.models import RandomForestModel
dataset = Dataset.animals()
train, test = dataset.split(0.9)
ft = featurizers.UniversalFeaturizer()
model = RandomForestModel(featurizer=ft)
model.train(train, cross_validation=5)
evaluation = model.evaluate(test)
evaluation.show()
.. toctree::
:maxdepth: 2
:caption: Getting Started

getting_started/installation
getting_started/support

.. toctree::
:maxdepth: 2
:caption: Examples

examples/example1
examples/example2
examples/example3
examples/example4

.. toctree::
:maxdepth: 2
:caption: Contributing

.. GS/Installation
.. Getting Support <GS/Support>
.. GS/Contributing
.. GS/About
.. GS/FAQ
contributing/engaging
contributing/report_issues
contributing/adding_datasets
contributing/adding_models
contributing/adding_featurizers

.. .. toctree::
.. :maxdepth: 2
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:maxdepth: 2
:caption: Advanced Resources

available_datasets/available_datasets
api_reference/api_reference


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Dataset.hurdat2(),
Dataset.cma_bst(),
Dataset.mnist_stroke(),
Dataset.uci_pen_digits(),
Dataset.uci_gotrack(),
Dataset.uci_characters(),
Dataset.uci_movement_libras(),
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