evaluation_lumo is a package for evaluating the LUMO damage detection system.
Project description
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 moth of data
- Damage Case Analysis: Provides detailed performance evaluations for each specific damage scenario within the LUMO dataset.
Installation
To install the package, run:
pip install evaluation_lumo
## Usage
To use the package, import the `evaluation_lumo.evaluation` module and call the `compute_tr_by_events` function or `compute_mean_variation` function.
```python
from evaluation_lumo.evaluation import compute_tr_by_events, compute_mean_variation
# 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_mean_variation(date_index, associated_damage_index)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file evaluation_lumo-0.1.7.tar.gz.
File metadata
- Download URL: evaluation_lumo-0.1.7.tar.gz
- Upload date:
- Size: 8.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.8.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ece98388f6ad3865d1141f1c0d3f18bec6dcb5bc00dfe12d2196c12749ee5da6
|
|
| MD5 |
0129e408ee8c0bff4bfb26e6c572322b
|
|
| BLAKE2b-256 |
6fd230e25bafbba8b3a6ce8efd7f2350330c07df834cda0fb7fce7ed4b858bbd
|
File details
Details for the file evaluation_lumo-0.1.7-py3-none-any.whl.
File metadata
- Download URL: evaluation_lumo-0.1.7-py3-none-any.whl
- Upload date:
- Size: 7.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.8.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2649e6b9fb26acaf929612d40e8c460e5927eca220cccbc6b0654f2a7fe76cdf
|
|
| MD5 |
09bbf498f7522c6c1dbb557c702b231e
|
|
| BLAKE2b-256 |
491ab5ca7661a90f27b4397f36d68945f812a3de8b7599153bef8e85334c6e4d
|