Source code for MDAnalysis.transformations.boxdimensions

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"""\
Set box dimensions --- :mod:`MDAnalysis.transformations.boxdimensions`
=======================================================================

Set dimensions of the simulation box to a constant vector across all timesteps.


.. autoclass:: set_dimensions
"""
import numpy as np

from .base import TransformationBase


[docs]class set_dimensions(TransformationBase): """ Set simulation box dimensions. Timestep dimensions are modified in place. Example ------- e.g. set simulation box dimensions to a vector containing unit cell dimensions [*a*, *b*, *c*, *alpha*, *beta*, *gamma*], lengths *a*, *b*, *c* are in the MDAnalysis length unit (Å), and angles are in degrees. .. code-block:: python dim = [2, 2, 2, 90, 90, 90] transform = mda.transformations.boxdimensions.set_dimensions(dim) u.trajectory.add_transformations(transform) Parameters ---------- dimensions: iterable of floats vector that contains unit cell lengths and angles. Expected shapes are (6, 0) or (1, 6) Returns ------- :class:`~MDAnalysis.coordinates.base.Timestep` object """ def __init__(self, dimensions, max_threads=None, parallelizable=True): super().__init__(max_threads=max_threads, parallelizable=parallelizable) self.dimensions = dimensions try: self.dimensions = np.asarray(self.dimensions, np.float32) except ValueError: errmsg = (f'{self.dimensions} cannot be converted into ' 'np.float32 numpy.ndarray') raise ValueError(errmsg) try: self.dimensions = self.dimensions.reshape(6, ) except ValueError: errmsg = (f'{self.dimensions} array does not have valid box ' 'dimension shape.\nSimulation box dimensions are ' 'given by an float array of shape (6, ), ' ' containing 3 lengths and 3 angles: ' '[a, b, c, alpha, beta, gamma]') raise ValueError(errmsg) def _transform(self, ts): ts.dimensions = self.dimensions return ts