MAT-data: Data Preprocessing for Multiple Aspect Trajectory Data Mining [MAT-Tools Framework]

[Publication] [Bibtex] [GitHub] [PyPi] [Docs]

The present package offers a tool, to support the user in the task of data preprocessing of multiple aspect trajectories, or to generating synthetic datasets. It integrates into a unique framework for multiple aspects trajectories and in general for multidimensional sequence data mining methods.

Main Modules

proprocess: Methods for trajectory preprocessing;
generator: Methods for trajectory datasets generation;
dataset: Methods for loading trajectory datasets;
converter: Methods for conferting dataset formats.

Installation

Install directly from PyPi repository, or, download from github. (python >= 3.7 required)

    pip install mat-data

Getting Started

On how to use this package, see MAT-data-Tutorial.ipynb

Citing

If you use mat-data please cite the following paper:

Portela, T. T.; Machado, V. L.; Renso, C. Unified Approach to Trajectory Data Mining and Multi-Aspect Trajectory Analysis with MAT-Tools Framework. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 39. , 2024, Florianópolis/SC. [Bibtex]

Collaborate with us

Any contribution is welcome. This is an active project and if you would like to include your code, feel free to fork the project, open an issue and contact us.

Feel free to contribute in any form, such as scientific publications referencing this package, teaching material and workshop videos.

Related packages

This package is part of MAT-Tools Framework for Multiple Aspect Trajectory Data Mining, check the guide project:

mat-tools: Reference guide for MAT-Tools Framework repositories

Change Log

This is a package under construction, see CHANGELOG.md

Metadata

Release files for mat-data 0.1rc6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mat-data 0.1rc6
File	Size	Uploaded	Provenance
mat_data-0.1rc6.tar.gz	10.2 MB	Oct 2, 2024	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for mat-data 0.1rc6
File	Interpreter	ABI	Platform	Reset
mat_data-0.1rc6-py3-none-any.whl 6.9 MB Oct 2, 2024 Without provenance	Python 3	none	any	Details

Total release size: 17.1 MB

Release files / mat_data-0.1rc6.tar.gz

Download URL	mat_data-0.1rc6.tar.gz
Size	10.2 MB
Tags	Source
SHA-256 checksum How to use checksums	`b871d001f19c5aa7365a85113fb0baf2bb6bfb4d17b50535b74d1a2111dd4b25`
BLAKE2b-256 checksum How to use checksums	`51f5e70ed193679b056475ede7b1d5b5921369ea580fd299e5d24d2e89ef259a`
Upload date	Oct 2, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.1 CPython/3.9.13`

Release files / mat_data-0.1rc6-py3-none-any.whl

Download URL	mat_data-0.1rc6-py3-none-any.whl
Size	6.9 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`b55519844a241069f936e844b0620c05889eb59d33c50dcf1879fa96361ee0ea`
BLAKE2b-256 checksum How to use checksums	`243819f0481eebf006409f70fa77f8d5872f89ee58c02d5cd1255195c352f4c4`
Upload date	Oct 2, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.1 CPython/3.9.13`

Security for mat-data 0.1rc6

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.