easyunfold.utils

Utility functions

Module Contents

Functions

write_kpoints	Write the kpoints to a file
write_kpoints_castep	Write kpoints to a CASTEP input file. Optically can use an existing file as the template and update it.
write_kpoints_vasp	Write kpoints to VASP KPOINTS file
read_kpoints_line_vasp	Read kpoints in the VASP KPOINTS file line mode, the results are resolved to explicit kpoints
read_kpoints	Read the kpoints from a given file
read_kpoints_vasp	Read kpoints from a KPOINTS file containing reciprocal space coordinates (fractional)
read_kpoints_castep	Read explicitly defined kpoints in a cell file to CASTEP
wrap_kpoints	Wrap the kpoints to range [-0.5, 0.5)
find_unique	Find unique slices along the first dimension of an np.array. This function is not optimised for high performance and has a O(N^2) scaling.
reduce_kpoints	Reduce the kpoint set by finding duplicated kpoints
kpoints_equal	Return two if two kpoints are equivalent to each other

Data

RE_COMMENT

API

easyunfold.utils.RE_COMMENT

None

easyunfold.utils.write_kpoints(kpoints: Union[numpy.ndarray, list], outpath, *args, code='vasp', **kwargs)

Write the kpoints to a file

Parameters:

• kpoints – A Nx3 array of the kpoint coordinates (fractional) to be written.

• outpath – Path of the output file to be used.

• code – The code that the kpoint file is used for.

easyunfold.utils.write_kpoints_castep(kpoints: Union[numpy.ndarray, list], dest, source=None, tag='spectral', weights=None, **kwargs)

Write kpoints to a CASTEP input file. Optically can use an existing file as the template and update it.

easyunfold.utils.write_kpoints_vasp(kpoints: Union[numpy.ndarray, list], outpath: str = 'KPOINTS', comment: str = '', weights: Union[None, List[float]] = None, **kwargs)

Write kpoints to VASP KPOINTS file

Parameters:

• kpoints – A list of kpoints to be written

• outpath – Path to the output file

• comments – Comments to be put into the KPOINTS file

• weights – If given, the weighting of the kpoints, otherwise all kpoints are equal weighted.

easyunfold.utils.read_kpoints_line_vasp(content, density=20)

Read kpoints in the VASP KPOINTS file line mode, the results are resolved to explicit kpoints

Returns:

The kpoints, the comment, the labels, and the weights at each kpoint

easyunfold.utils.read_kpoints(path='KPOINTS', code='vasp', **kwargs)

Read the kpoints from a given file

This function dispatches to code-specific function based on the code keyword variable.

easyunfold.utils.read_kpoints_vasp(path='KPOINTS')

Read kpoints from a KPOINTS file containing reciprocal space coordinates (fractional)

Returns:

The kpoints, the comment, the labels, and the weights at each kpoint.

easyunfold.utils.read_kpoints_castep(path, tag='spectral')

Read explicitly defined kpoints in a cell file to CASTEP

easyunfold.utils.wrap_kpoints(kpoints: Union[list, numpy.ndarray])

Wrap the kpoints to range [-0.5, 0.5)

easyunfold.utils.find_unique(seq: numpy.ndarray, func=None)

Find unique slices along the first dimension of an np.array. This function is not optimised for high performance and has a O(N^2) scaling.

Returns:

A tuple of (unique, unique_idx, inv_mapping)

easyunfold.utils.reduce_kpoints(kpoints: Union[list, numpy.ndarray], time_reversal=True, rounding_digits=10)

Reduce the kpoint set by finding duplicated kpoints

easyunfold.utils.kpoints_equal(k1, k2, time_reversal=False, atol=1e-05)

Return two if two kpoints are equivalent to each other