wdfkit is a Python toolkit for Renishaw WiRE .wdf spectroscopy data—especially Raman and photoluminescence work. It reads single spectra, line scans, depth/time series, and raster maps into xarray.DataArray objects with consistent, predictable dimension names: the spectral axis is always "spectral"; maps always use ("row", "column", "spectral"); series and point collections always use ("point", "spectral"). Spatial and temporal coordinates from the instrument's ORGN metadata are attached automatically.
The project is inspired by spectrapy by Dejan Skrelic—an earlier tool that shaped how spectroscopy users treat this kind of data.
For more information about the wdfkit library, please consult our online documentation.
If you use wdfkit in a scientific publication, we would like you to cite this package as
wdfkit Package, https://github.com/svi-lab/wdfkit
The preferred method is to use Miniconda Python and install from the "conda-forge" channel of Conda packages.
To add "conda-forge" to the conda channels, run the following in a terminal.
conda config --add channels conda-forge
We want to install our packages in a suitable conda environment.
The following creates and activates a new environment named wdfkit_env
conda create -n wdfkit_env wdfkit conda activate wdfkit_env
The output should print the latest version displayed on the badges above.
If the above does not work, you can use pip to download and install the latest release from
Python Package Index.
To install using pip into your wdfkit_env environment, type
pip install wdfkit
If you prefer to install from sources, after installing the dependencies, obtain the source archive from
GitHub. Once installed, cd into your wdfkit directory
and run the following
pip install .
This package also provides command-line utilities. To check the software has been installed correctly, type
wdfkit --version
You can also type the following command to verify the installation.
python -c "import wdfkit; print(wdfkit.__version__)"
To view the basic usage and available commands, type
wdfkit -h
You may consult our online documentation for tutorials and API references.
If you see a bug or want to request a feature, please report it as an issue and/or submit a fix as a PR.
Feel free to fork the project and contribute. To install wdfkit in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory
pip install -e .
To ensure code quality and to prevent accidental commits into the default branch, please set up the use of our pre-commit hooks.
- Install pre-commit in your working environment by running
conda install pre-commit. - Initialize pre-commit (one time only)
pre-commit install.
Thereafter your code will be linted by black and isort and checked against flake8 before you can commit. If it fails by black or isort, just rerun and it should pass (black and isort will modify the files so should pass after they are modified). If the flake8 test fails please see the error messages and fix them manually before trying to commit again.
Improvements and fixes are always appreciated.
Before contributing, please read our Code of Conduct.
For more information on wdfkit please visit the project web-page or email the maintainers Danila Shiryaev(danila.shiryaev@polytechnique.edu).
wdfkit draws conceptual inspiration from spectrapy by Dejan Skrelic.
wdfkit is built and maintained with scikit-package.