Skip to main content

AnomalousLib is a Python library designed for the study of anomalous diffusion. It enables dataset generation, statistical analysis, model inference, and integrated result visualization.

Project description

AnomalousLib

AnomalousLib is a Python library designed for the study of anomalous diffusion.

It supports dataset generation, statistical analysis, model inference, and integrated result visualization.

The library is published on PyPI under the name AnomalousLib and uses Python version 3.12.10.

Repository Structure

The following diagram shows the structure of the repository:

AnomalousLib
   # Package builds
├───dist
   # Source code
├───src
   └───anomalouslib
          # Analytical tools and metrics
       ├───analysis
          # Dataset handling and generation
       ├───data
          # Model definitions and inference
       ├───models
          # Output handling and reporting
       ├───results
          # Utility functions and helpers
       └───utils
   # QA and testing
└───tests

Development Setup

To test the library locally, follow these steps. All commands should be run from the root of the project, where the pyproject.toml file is located.

1. Set Up the Virtual Environment

First, create a virtual environment:

python -m venv venv

Then activate it:

  • On Linux/macOS:
    source venv/bin/activate
    
  • On Windows:
    .\venv\Scripts\Activate.ps1
    

💡 Note: To deactivate the environment at any time (on both Linux and Windows), use:

deactivate

2. Install Dependencies

Install the required libraries listed in requirements.txt:

pip install -r requirements.txt

To verify the installation, you can regenerate the requirements.txt and check for any differences:

  • On Linux/macOS:
    pip freeze | grep -vE "^-e |@ file://" > requirements.txt
    
  • On Windows:
    pip freeze | Select-String -NotMatch '^-e |@ file://' > requirements.txt
    

💡 Note: This filtering step avoids including the local installation of the library itself.

If no changes appear in the file, the setup is correct.

Local Build & Installation

1. Build the Library

Generate the distribution packages:

python -m build

2. Install the Library Locally

  • First-time installation (or to force reinstall):
    pip install ./dist/anomalouslib-{lib_version}-py3-none-any.whl --force-reinstall
    
  • Subsequent updates (faster and applies only changes):
    pip install --upgrade ./dist/anomalouslib-{lib_version}-py3-none-any.whl
    

💡 Note: Replace {lib_version} with the actual library version, e.g.: pip install --upgrade ./dist/anomalouslib-0.1.0-py3-none-any.whl

Publishing to PyPI

To publish the package to PyPI, run:

twine upload ./dist/*

⚠️ Important: Make sure no version in the ./dist/ folder has already been uploaded to PyPI.

💡 It is strongly recommended not to install the public PyPI version in the same local environment to avoid confusion with the local development version.

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

anomalouslib-0.2.0.tar.gz (11.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

anomalouslib-0.2.0-py3-none-any.whl (14.9 kB view details)

Uploaded Python 3

File details

Details for the file anomalouslib-0.2.0.tar.gz.

File metadata

  • Download URL: anomalouslib-0.2.0.tar.gz
  • Upload date:
  • Size: 11.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.10

File hashes

Hashes for anomalouslib-0.2.0.tar.gz
Algorithm Hash digest
SHA256 a7b564b3ec087dfb590fb2f296a0e99d408ecb6ba35579a1e53f3cb8e212b12f
MD5 58cc7ed641e0814e14a0515360d67fbe
BLAKE2b-256 0a1e6d2ee87d6327e7aa3b156d9b416520c966843333ccd55ac53b02a5d8d8cf

See more details on using hashes here.

File details

Details for the file anomalouslib-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: anomalouslib-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 14.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.10

File hashes

Hashes for anomalouslib-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 2fd865720f8102f037db8153c0b4a101feba8bdfb0ff088cae72385f1bed3906
MD5 b3519235747047cc9e8a155b1f120fea
BLAKE2b-256 9ab3abaea148b05e2b1afeddbd35c1031ceb46d7be1be4ce5ba2f467444ba79f

See more details on using hashes here.

Supported by

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