GitXplorerGitXplorer
d

arctix

public
0 stars
0 forks
3 issues

Commits

List of commits on branch main.
Verified
f0a9a0e92c21c35ee308bb29959f1c353a881821

Update pre-commit hooks (#442)

ggithub-actions[bot] committed 5 days ago
Verified
7eda820822afbc3ee7d6f19eca4c8cd62cb9eddc

Bump pygments from 2.18.0 to 2.19.1 (#441)

ddependabot[bot] committed 5 days ago
Verified
294e32c44d83f9f8f93973500daad7a899d4b514

Bump coverage from 7.6.9 to 7.6.10 (#436)

ddependabot[bot] committed 5 days ago
Verified
e14ec435cea3e613bd2e89a53d3056389820d498

Bump polars from 1.17.1 to 1.19.0 (#440)

ddependabot[bot] committed 5 days ago
Verified
a2800a6944bd136fa5a95cb4aeaaa311b2464e67

Bump ruff from 0.8.4 to 0.8.6 (#439)

ddependabot[bot] committed 5 days ago
Verified
23a4351445b0501653a6aa412ca67726813ca361

Update workflows (#438)

ddurandtibo committed 13 days ago

README

The README file for this repository.

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 This documentation may contain a lot of work-in-progress/outdated/missing parts.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 >=0.1,<1.0 >=0.8.4,<1.0 ">=0.1,<1.0" >=1.22,<3.0 >=1.0,<2.0 >=3.9,<3.14
0.0.8 >=0.1,<1.0 >=0.8.4,<1.0 ">=0.1,<1.0" >=1.22,<3.0 >=1.0,<2.0 >=3.9,<3.14
0.0.7 >=0.0.2,<1.0 >=0.3,<1.0 ">=0.0.3,<1.0" >=1.22,<3.0 >=1.0,<2.0 >=3.9,<3.13
0.0.6 >=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
0.0.5 >=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

⚠️ 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.