Name | evaluation-lumo JSON |
Version |
0.1.10
JSON |
| download |
home_page | None |
Summary | evaluation_lumo is a package for evaluating the LUMO damage detection system. |
upload_time | 2025-02-12 10:55:04 |
maintainer | None |
docs_url | None |
author | None |
requires_python | >=3.9.0 |
license | None |
keywords |
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
# LUMO Damage Detection Evaluation Package
This package provides a standardized framework for evaluating damage detection and localization strategies using the LUMO dataset. Users can input timestamps alongside their corresponding anomaly indices, and the package computes various performance scores for each damage case, promoting consistency in damage detection evaluation.
## Features
- **Standardized Evaluation Metrics**: Calculates TPR and FPR at a threshold set such as FPR for training data is 1%.
The training dataset should be only the first month of data.
- **Damage Case Analysis**: Provides detailed performance evaluations for each specific damage scenario within the LUMO dataset.
## Installation
To install the package, run:
```bash
pip install evaluation_lumo
```
## Usage
To use the package, import the `evaluation_lumo.evaluation` module and call the `compute_tr_by_events` function, `compute_mean_variation` function, or `compute_mad` function.
```python
from evaluation_lumo.evaluation import compute_tr_by_events, compute_mean_variation, compute_mad
# Example usage
date_index = pd.date_range(start='2021-08-01', ends="2022-08-01", freq='10T')
associated_damage_index = np.random.random(len(date_index))
compute_tr_by_events(date_index, associated_damage_index)
compute_median_variation(date_index, associated_damage_index)
compute_mad(date_index, associated_damage_index)
```
## Contributing
pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
pre-commit is used to ensure code quality. Please install it before making any changes.
run the following command to install pre-commit:
```bash
pre-commit run --all-files
```
then push your changes.
Raw data
{
"_id": null,
"home_page": null,
"name": "evaluation-lumo",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9.0",
"maintainer_email": "Yacine Bel-Hadj <yacine.bel-hadj@vub.be>",
"keywords": null,
"author": null,
"author_email": "Yacine Bel-Hadj <yacine.bel-hadj@vub.be>",
"download_url": "https://files.pythonhosted.org/packages/1d/a5/ca8463c28efcb8c6e508a4a42b656d76a855944c63dd4ed16a293631b283/evaluation_lumo-0.1.10.tar.gz",
"platform": null,
"description": "# LUMO Damage Detection Evaluation Package\n\nThis package provides a standardized framework for evaluating damage detection and localization strategies using the LUMO dataset. Users can input timestamps alongside their corresponding anomaly indices, and the package computes various performance scores for each damage case, promoting consistency in damage detection evaluation.\n\n## Features\n\n- **Standardized Evaluation Metrics**: Calculates TPR and FPR at a threshold set such as FPR for training data is 1%.\nThe training dataset should be only the first month of data.\n- **Damage Case Analysis**: Provides detailed performance evaluations for each specific damage scenario within the LUMO dataset.\n\n## Installation\n\nTo install the package, run:\n\n```bash\npip install evaluation_lumo\n```\n\n## Usage\n\nTo use the package, import the `evaluation_lumo.evaluation` module and call the `compute_tr_by_events` function, `compute_mean_variation` function, or `compute_mad` function.\n\n```python\nfrom evaluation_lumo.evaluation import compute_tr_by_events, compute_mean_variation, compute_mad\n\n# Example usage\n\ndate_index = pd.date_range(start='2021-08-01', ends=\"2022-08-01\", freq='10T')\nassociated_damage_index = np.random.random(len(date_index))\ncompute_tr_by_events(date_index, associated_damage_index)\ncompute_median_variation(date_index, associated_damage_index)\ncompute_mad(date_index, associated_damage_index)\n```\n\n## Contributing\n\npull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.\npre-commit is used to ensure code quality. Please install it before making any changes.\nrun the following command to install pre-commit:\n\n```bash\npre-commit run --all-files\n```\nthen push your changes.\n\n",
"bugtrack_url": null,
"license": null,
"summary": "evaluation_lumo is a package for evaluating the LUMO damage detection system.",
"version": "0.1.10",
"project_urls": {
"Repository": "https://github.com/YacineBelHadj/evaluation_lumo"
},
"split_keywords": [],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "3588bad0ce869aa3195c0786279f1bf5fd32523e575b358baba23b9af31aaff5",
"md5": "f1983e75a1af5fae62d9a41096f16c95",
"sha256": "a2533b46187f6cd30de261604cce355aa021684277f0f5bd3659f3fb666d6261"
},
"downloads": -1,
"filename": "evaluation_lumo-0.1.10-py3-none-any.whl",
"has_sig": false,
"md5_digest": "f1983e75a1af5fae62d9a41096f16c95",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9.0",
"size": 7534,
"upload_time": "2025-02-12T10:55:02",
"upload_time_iso_8601": "2025-02-12T10:55:02.871064Z",
"url": "https://files.pythonhosted.org/packages/35/88/bad0ce869aa3195c0786279f1bf5fd32523e575b358baba23b9af31aaff5/evaluation_lumo-0.1.10-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "1da5ca8463c28efcb8c6e508a4a42b656d76a855944c63dd4ed16a293631b283",
"md5": "6e1126a4524afada8d11358252874812",
"sha256": "42dd93ffd47d1166121fa311aa1a00923da28b26f385ee4e781421287033d859"
},
"downloads": -1,
"filename": "evaluation_lumo-0.1.10.tar.gz",
"has_sig": false,
"md5_digest": "6e1126a4524afada8d11358252874812",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9.0",
"size": 8740,
"upload_time": "2025-02-12T10:55:04",
"upload_time_iso_8601": "2025-02-12T10:55:04.526028Z",
"url": "https://files.pythonhosted.org/packages/1d/a5/ca8463c28efcb8c6e508a4a42b656d76a855944c63dd4ed16a293631b283/evaluation_lumo-0.1.10.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-02-12 10:55:04",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "YacineBelHadj",
"github_project": "evaluation_lumo",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "evaluation-lumo"
}