Troubleshooting & Support

doped/pymatgen Errors

For most error cases, doped has been designed to try and give informative error messages about why the functions are failing. In the majority of cases, if you encounter an error using doped which does not have a clear error message about the origin of the problem, it is likely to be an issue with your version of pymatgen (and/or doped), and may be fixed by doing:

pip install pymatgen --upgrade
pip install doped --upgrade

If this does not solve your issue, please contact the developers through the GitHub Issues page, or by email.

numpy Errors

• A previous known issue with numpy/pymatgen is that it could give an error similar to this:

  ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject
  

  This should be avoided with current versions of doped, due to the package installation requirements (handled automatically by pip), but depending on your python environment and previously-installed packages, it could possibly still arise. It occurs due to a recent change in the numpy C API in version 1.20.0, see here for details. It should be fixed by reinstalling numpy and pymatgen (so that they play nice together), so that it is rebuilt with the new numpy C API:

  pip install --force --no-cache-dir numpy==1.23
  pip uninstall pymatgen
  pip install pymatgen
  

spglib Errors

• A previous known issue with spglib is that it could give an error similar to:

  spglib: ssm_get_exact_positions failed (attempt=0).
  ...
  spglib: ssm_get_exact_positions failed (attempt=4).
  spglib: get_bravais_exact_positions_and_lattice failed
  spglib: ref_get_exact_structure_and_symmetry failed.
  

  This can be fixed by reinstalling spglib with conda install -c conda-forge spglib. It’s important to use conda rather than pip as conda will bundle the C and Fortran libraries.

ShakeNBreak

For issues relating to the ShakeNBreak part of the defect calculation workflow, please refer to the ShakeNBreak documentation.

Errors with Python Scripts

The recommended usage of doped is through interactive python sessions, such as with Jupyter notebooks, IPython or an IDE (e.g. PyCharm or VSCode), as shown in the doped tutorials. However, it is possible to also use doped through Python scripts if preferred. Due to the use of the multiprocessing module in doped.generation, doped.vasp and doped.analysis, you need to use the proper syntax for running Python scripts, with if __name__ == '__main__':...

A simple example script of generating the intrinsic defects and writing the VASP input files (all with default settings – in reality you likely need to customise some options!) would be:

from pymatgen.core.structure import Structure
from doped import generation, vasp

def generate_and_write_vasp_files():
    primitive_struct = Structure.from_file("prim_POSCAR")
    # generate defects:
    defect_gen = generation.DefectsGenerator(primitive_struct)
    # generate VASP input files:
    defects_set = vasp.DefectsSet(defect_gen)
    defects_set.write_files()

if __name__ == '__main__':
    generate_and_write_vasp_files()

If you do not use the if __name__ == '__main__':... syntax, you may encounter this error:

RuntimeError:
    An attempt has been made to start a new process before the
    current process has finished its bootstrapping phase.
    This probably means that you are not using fork to start your
    child processes and you have forgotten to use the proper idiom
    in the main module:
        if __name__ == ‘__main__‘:
            freeze_support()
            ...
    The “freeze_support()” line can be omitted if the program
    is not going to be frozen to produce an executable.
    To fix this issue, refer to the “Safe importing of main module”
    section in https://docs.python.org/3/library/multiprocessing.html

Note

If you run into any issues using doped that aren’t addressed above, please contact the developers through the GitHub Issues page, or by email.