Processing, analysis, and plotting of scattering data.
If you encounter any bugs or have suggestions for new code or functionalities, please post an issue here on GitHub. If you refer to a specific script, please include that in the title of the issue.
Go explore the Bragg peaks and whatever might be hidden underneath them!
The following guidelines assume that the user runs a conda distribution, i.e.,
Anaconda or Miniconda. If these guidelines are followed, all dependencies for
the pyScattData
code will be installed.
- It is highly recommended to run the code in a conda environment dedicated to
the pyScattData library. If the user does not already have that, such a conda
environment, called
pyscattdata
and using the latest Python 3 version, can be created from:conda create -n pyscattdata python=3
- When the user has a
pyscattdata
conda environment, the user should activate the pyscattdata conda environment:conda activate pyscattdata
- Navigate to the main
pyScattData
directory. Using conda, dependencies present in therun.txt
file in therequirements
directory will be installed from theconda-forge
channel, when running (NB: this might take some time - consider to go for a coffee...):conda install -c conda-forge --file requirements/run.txt
- Using pip, additional dependencies present in the
pip_requirements.txt
file in therequirements
directory will be installed, when running:pip install -r requirements/pip_requirements.txt
- If running on a Unix-based OS (MacOS or Linux), additional dependencies
present in the
diffpy_extras.txt
file in therequirements
directory will be installed, when running:Unfortunately, these diffpy packages are not available for Windows users.pip install -r requirements/diffpy_extras.txt
Now, all pyScattData
dependencies are installed for the pyscattdata
conda
environment. You are now ready to run the code present in the pyScattData
repository.