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Processing, analysis, and plotting of scattering data.

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pyScattData

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!

Setup and installation

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.

Create a new pyscattdata conda environment

  • 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

Activate pyscattdata conda environment

  • When the user has a pyscattdata conda environment, the user should activate the pyscattdata conda environment:
    conda activate pyscattdata

Install dependencies

  • Navigate to the main pyScattData directory. Using conda, dependencies present in the run.txt file in the requirements directory will be installed from the conda-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 the requirements 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 the requirements directory will be installed, when running:
    pip install -r requirements/diffpy_extras.txt
    Unfortunately, these diffpy packages are not available for Windows users.

Now, all pyScattData dependencies are installed for the pyscattdata conda environment. You are now ready to run the code present in the pyScattData repository.

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