quel-qal 0.2.2

A Python library for analyzing Quel Imaging fluorescent phantoms and imaging targets.

QUEL-QAL: QUEL Quantitative Analysis Library

Welcome to quel-qal! This repository contains Python code for analyzing images of QUEL Imaging's fluorescence phantoms and obtaining relevant metrics about the capabilities of your fluorescence imaging system. Find more information about our fluorescence targets on our website. Documentation on how to use quel-qal to analyze images can be found in the doc folder and in the Wiki.

Getting Started

This guide will help you get started with setting up and using quel-qal. Follow the steps below to install directly from PyPI, or clone this repository locally. Conda installation is not currently supported.

Prerequisites

• Quel-qal requires Python version ≥ 3.12.

• It is also recommended (though not required) to set up a separate virtual environment to install to. Create and activate a new virtual environment as follows.
  
  

  On macOS/Linux:

  python3 -m venv env
  source env/bin/activate
  

  On Windows:

  python -m venv env
  env\Scripts\activate
  

PyPI Installation

You can install quel-qal directly from PyPI using:

pip install quel-qal

This will install quel-qal along with all its dependencies.

GitHub Installation

Alternatively, you can install the repository from GitHub by following these steps:

1. Clone the repository:

   git clone https://github.com/QUEL-Imaging/quel-qal.git
   cd quel-qal
   

2. Set up a virtual environment (optional):
   Create and activate a virtual environment as described above.
3. Install dependencies:
   You can install the required dependencies using pip:

   pip install -r requirements.txt
   

4. Install quel-qal:
   

   pip install -e .
   

License

Source Code

The source code in this repository is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

Documentation

The contents of the doc folder in this repository are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0).

Notes

• If you contribute to this repository, you agree that your contributions to the source code will be licensed under AGPL-3.0 and your contributions to the documentation will be licensed under CC BY 4.0.
• Please ensure compliance with both licenses when using or modifying the content of this repository.

Funding

This work is partially funded by the NIH and ARPA-H:

• NIBIB Grants R43/44 EB029804
• NCI Contract 75N91021C00035
• NCI/ARPA-H Contract 75N91023C00052