Provides methods for the analysis of PV modules using different modalities
This package provides methods for the analysis of solar modules using different imaging modalities. We put huge efforts into providing a clean and easy to use API and additional tooling like the wrapper classes for module images that bundle image with meta data in an expressive way. You are invited to publish you own methods using this API and hence contribute to building a consistent and open tooling that might be useful to others. If you like to integrate your methods directly, please create a merge request.
This package is in an early stage of development. Please be aware that the API might change regularily within the next months.
We recommend to install
pvinspect in a Python virtual environment using Python 3.8. This document only supplies a short description on the usage of virtual environments in Python. For a complete guide, please refer to this tutorial.
0. Check that you have the correct Python version available:
Depending on the OS and configuration of your machine,
python needs to be substituted with
python3.exe or even the absolute path to the Python interpreter. In any case, the displayed version should be compatible to
pvinspect. At the moment,
Python 3.7 or
1. Create a new virtual environment:
python -m venv /path/to/your/venv
This initializes a new virtual environement in
/path/to/your/venv (which you should adapt to your needs). All packages that you install within this environment are stored in this folder. Depending on the OS and configuration of your machine,
python needs to be substituted with
2. Activate the new virtual environment:
# For Windows users (Powershell): /path/to/your/venv/Scripts/Activate.ps1 # For Linux users: /path/to/your/vent/Scripts/activate
Please note that the procedure depends on the type of shell that you are using. We've given example for Powershell and Linux-shell users.
3. Install pvinspect:
pip install pvinspect
This installs the
pvinspect package in the currently active environment (which is normally indicated in the shell). So please make sure to have the correct environment activated. After installation, you can use
pvinspect at any time from within that environment.
A note to Anaconda users
We do not ship
pvinspect as an Anaconda package. However, you can of course install it in an Anaconda environment using pip. However, you might come across an error indicating that
geos_c.dll is missing. In that case, you need to install
conda install -c conda-forge shapely
You can update
pvinspect to the newest version simply using
pip install --upgrade pvinspect
In case you encounter anything that does not work, please open an issue and provide a precise description (include your OS version, python distribution and the like) as well as a minimal code example to reproduce the issue.
In case you install
pvinspect in a conda environment using
pip on Windows, the
shapely library, which is installed as a dependency of
pvinspect does not find
geos.dll. This can be fixed by installing
shapely using conda:
conda install shapely
This is reported as a bug to shapely: #1032
In case you use methods from this package for research purposes, please make sure to cite the the corresponding papers correctly. Please refer to the documentation for the correct references.
We greatly acknowledge the HI-ERN for providing us a demo dataset of electroluminescense images that is published along with this package.
We gratefully acknowledge funding of the Federal Ministry for Economic Affairs and Energy (BMWi: Grant No. 0324286, iPV4.0).
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