enricgrau/Respository-for-Accelerating-the-development-of-thin-film-photovoltaic-technologies

This repository works as complementry information for the paper.

ML-for-CISe

This repository serves as a valuable supplementary information for the article titled "Accelerating the Development of Thin Film Photovoltaic Technologies: An Artificial Intelligence Assisted Methodology Using Spectroscopic and Optoelectronic Techniques". It provides access to both the sample code and the data that were used to achieve the results presented in the article. This additional material offers readers and researchers an in-depth look into the practical application of the methodologies discussed, enhancing the article's utility.

How to use:

1. Make sure you have at least 1 GB available in your system before downloading and installing this repository.

2. Fork the repository and download the files into a folder. Alternatively, you can download it directly from the original repository into your system.

3. Make it your working folder:

   cd '../folder/location'
   

4. Download and install Python 3.11.x. Python 3.12 and above not tested.

5. Create a virtual environment with Python 3.11.x:

   python -m venv venv
   

6. Activate the virtual environment created:

   venv\Scripts\activate
   

7. Install the requirements using pip:

    pip install -r requirements.txt
   

8. You venv should be up and ready to run the scripts available. Try running any of the including scripts in code folder to test it.