Source code for magnopy._parallelization

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# Magnopy - Python package for magnons.
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from multiprocessing import Pool

# Save local scope at this moment
old_dir = set(dir())
old_dir.add("old_dir")


[docs] def multiprocess_over_k( kpoints, function, relative=False, units="meV", number_processors=None ): r""" Parallelizes calculation over the kpoints using |multiprocessing|_ module. Parameters ---------- kpoints : (N, 3) |array-like|_ List of the kpoints. function : callable Function that process one kpoint and is called as .. code-block:: python result = function(kpoints[i], relative, units) relative : bool, default False If ``relative=True``, then ``k`` is interpreted as given relative to the reciprocal unit cell. Otherwise it is interpreted as given in absolute coordinates. units : str, default "meV" .. versionadded:: 0.3.0 Units of energy. See :py:attr:`.SpinHamiltonian.units` for the list of supported units. number_processors : int, optional By default magnopy uses all available processes. Pass ``number_processors=1`` to run in serial. Returns ------- results : (N, ) list List of objects that are returned by the ``function``. Notes ----- When using this function of magnopy in your Python scripts make sure to safeguard your script with the .. code-block:: python import magnopy # Import more stuff # or # Define your functions, classes if __name__ == "__main__": # Write your executable code here For more information refer to the "Safe importing of main module" section in |multiprocessing|_ docs. """ relative = [relative for _ in kpoints] units = [units for _ in kpoints] if number_processors == 1: results = list(map(function, kpoints, relative, units)) else: with Pool(number_processors) as p: results = p.starmap(function, zip(kpoints, relative, units)) return results
# Populate __all__ with objects defined in this file __all__ = list(set(dir()) - old_dir) # Remove all semi-private objects __all__ = [i for i in __all__ if not i.startswith("_")] del old_dir