Skip to main content

No project description provided

Project description

arctix

CI Nightly Tests Nightly Package Tests
Documentation Documentation
Codecov
Code style: black Doc style: google Ruff Doc style: google
PYPI version Python BSD-3-Clause
Downloads Monthly downloads

Overview

The arctix package consists of functionalities to prepare dataset of asynchronous time series. It is design to make dataset preparation reusable and reproducible. For each dataset, arctix provides 3 main functions:

  • fetch_data to load the raw data are loaded in a polars.DataFrame. When possible, it downloads automatically the data.
  • prepare_data to prepare the data. It outputs the prepared data in polars.DataFrame, and the metadata.
  • to_array to convert the prepared data to a dictionary of numpy arrays.

For example, it is possible to use the following lines to download and prepare the MultiTHUMOS data.

>>> from pathlib import Path
>>> from arctix.dataset.multithumos import fetch_data, prepare_data, to_array
>>> dataset_path = Path("/path/to/dataset/multithumos")
>>> data_raw = fetch_data(dataset_path)  # doctest: +SKIP
>>> data, metadata = prepare_data(data_raw)  # doctest: +SKIP
>>> arrays = to_array(data)  # doctest: +SKIP

Documentation

  • latest (stable): documentation from the latest stable release.
  • main (unstable): documentation associated to the main branch of the repo. This documentation may contain a lot of work-in-progress/outdated/missing parts.

Installation

We highly recommend installing a virtual environment. arctix can be installed from pip using the following command:

pip install arctix

To make the package as slim as possible, only the minimal packages required to use arctix are installed. To include all the packages, you can use the following command:

pip install arctix[all]

Please check the get started page to see how to install only some specific packages or other alternatives to install the library. The following is the corresponding karbonn versions and dependencies.

batcharray batcharray coola iden numpy polars python
main >=0.0.2,<0.1 >=0.3,<1.0 ">=0.0.3,<1.0" >=1.22,<2.0 >=0.20.0,<1.0 >=3.9,<3.13
0.0.4 >=0.0.2,<0.1 >=0.3,<1.0 ">=0.0.3,<1.0" >=1.22,<2.0 >=0.20.0,<1.0 >=3.9,<3.13
0.0.3 >=0.0.2,<0.1 >=0.3,<1.0 ">=0.0.3,<1.0" >=1.22,<2.0 >=0.20.0,<1.0 >=3.9,<3.13

Contributing

Please check the instructions in CONTRIBUTING.md.

API stability

:warning: While arctix is in development stage, no API is guaranteed to be stable from one release to the next. In fact, it is very likely that the API will change multiple times before a stable 1.0.0 release. In practice, this means that upgrading arctix to a new version will possibly break any code that was using the old version of arctix.

License

arctix is licensed under BSD 3-Clause "New" or "Revised" license available in LICENSE file.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

arctix-0.0.4.tar.gz (33.4 kB view details)

Uploaded Source

Built Distribution

arctix-0.0.4-py3-none-any.whl (45.3 kB view details)

Uploaded Python 3

File details

Details for the file arctix-0.0.4.tar.gz.

File metadata

  • Download URL: arctix-0.0.4.tar.gz
  • Upload date:
  • Size: 33.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.5.0-1018-azure

File hashes

Hashes for arctix-0.0.4.tar.gz
Algorithm Hash digest
SHA256 fa6bfaa90c45d997a09e64bcea9e8ee3d77846ca6c4bfc5fa449d8ef08cdb198
MD5 c0ec905ef7bcaa33158ca8bd9fb86303
BLAKE2b-256 d9053ce5c97242ca1ba0738901630c0bb3eee0392959e8f3987e6f2471d1578b

See more details on using hashes here.

File details

Details for the file arctix-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: arctix-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 45.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.5.0-1018-azure

File hashes

Hashes for arctix-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 7f6b662ad50d9b5f08c0b0a474d149bd8263ff5d29b1a76985c8b07eebaaddfb
MD5 00267119d93b44eaa83d70ab37933151
BLAKE2b-256 e1754a3bf750066938578c03148cd031161813d54c3b019093bb0c17a8ea161f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page