agomax 0.1.8

Universal Drone Anomaly Detection Python Package

Agomax v0.1.8

Universal Drone Anomaly Detection Python Package

Folder Structure

• agomax/ - Python package with backend logic
• data/ - Place your data files here (e.g., base.csv, random1.csv, etc.)
• models/ - Place trained model files here (kmeans.pkl, lof.pkl, svm.pkl, dbscan.pkl, optics.pkl)
• configs/ - Place your rules config here (rules.yaml)

Installation

pip install agomax

Dashboard Usage

import agomax
agomax.dashboard()  # Launches Streamlit dashboard

API Usage

from agomax.detect import agomax_detect

# Using the included demo data
result = agomax_detect(
    data_source='data/crash.csv',    # Package will auto-resolve this path
    mode='offline',
    rules_path='configs/rules.yaml',  # Package will auto-resolve this path
    model_dir='models/'              # Package will auto-resolve this path
)
print(result)

# Or using your own absolute paths
result = agomax_detect(
    data_source='/path/to/your/data.csv',
    mode='offline',
    rules_path='/path/to/your/rules.yaml',
    model_dir='/path/to/your/models/'
)
print(result)

Data Files

The package includes a demo file crash.csv in the data/ folder for testing and demonstration. You can use this file in the dashboard or with the API to see how anomaly detection works out of the box.

For your own experiments, name your data files as in your prototype: base.csv, random1.csv, wind1.csv, engine1.csv, sensor1.csv, crash.csv and place them in the data/ folder.

Package Setup

To make this a pip-installable package, use the following setup.py:

from setuptools import setup, find_packages

setup(
    name='agomax',
    version='0.1.8',
    author='shaguntembhurne',
    author_email='[e-mail]',
    description='Universal Drone Anomaly Detection Python Package',
    long_description=open('README.md').read(),
    long_description_content_type='text/markdown',
    url='https://github.com/shaguntembhurne/agomax',
    packages=find_packages(),
    install_requires=[
        'pandas',
        'numpy',
        'scikit-learn',
        'pyyaml',
        'streamlit',
        'plotly'
    ],
    include_package_data=True,
    package_data={
        '': ['data/crash.csv', 'configs/rules.yaml', 'models/*.pkl'],
    },
    classifiers=[
        'Programming Language :: Python :: 3',
        'License :: OSI Approved :: MIT License',
        'Operating System :: OS Independent',
    ],
    python_requires='>=3.7',
)

Or use a pyproject.toml for modern builds.