# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
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#
# MDAnalysis --- https://www.mdanalysis.org
# Copyright (c) 2006-2017 The MDAnalysis Development Team and contributors
# (see the file AUTHORS for the full list of names)
#
# Released under the Lesser GNU Public Licence, v2.1 or any higher version
#
# Please cite your use of MDAnalysis in published work:
#
# R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler,
# D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein.
# MDAnalysis: A Python package for the rapid analysis of molecular dynamics
# simulations. In S. Benthall and S. Rostrup editors, Proceedings of the 15th
# Python in Science Conference, pages 102-109, Austin, TX, 2016. SciPy.
# doi: 10.25080/majora-629e541a-00e
#
# N. Michaud-Agrawal, E. J. Denning, T. B. Woolf, and O. Beckstein.
# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
#
"""\
Set box dimensions --- :mod:`MDAnalysis.transformations.boxdimensions`
=======================================================================
Set dimensions of the simulation box, either to a constant vector across
all timesteps or to a specified vector at each frame.
.. 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.
Examples
--------
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.
The same dimensions will be used for every frame in the trajectory.
.. code-block:: python
dim = np.array([2, 2, 2, 90, 90, 90])
transform = mda.transformations.boxdimensions.set_dimensions(dim)
u.trajectory.add_transformations(transform)
Or e.g. set simulation box dimensions to a vector containing unit cell
dimensions [*a*, *b*, *c*, *alpha*, *beta*, *gamma*] at the first frame,
and [*2a*, *2b*, *2c*, *alpha*, *beta*, *gamma*] at the second frame.
.. code-block:: python
dim = np.array([
[2, 2, 2, 90, 90, 90],
[4, 4, 4, 90, 90, 90],
])
transform = mda.transformations.boxdimensions.set_dimensions(dim)
u.trajectory.add_transformations(transform)
Parameters
----------
dimensions: iterable of floats or two-dimensional np.typing.NDArrayLike
vector that contains unit cell lengths and angles.
Expected shapes are (6, 0) or (1, 6) or (N, 6), where
N is the number of frames in the trajectory. If shape is (6, 0) or
(1, 6), the same dimensions will be used at every frame in the
trajectory.
Returns
-------
:class:`~MDAnalysis.coordinates.timestep.Timestep` object
.. versionchanged:: 2.7.0
Added the option to set varying box dimensions (i.e. an NPT trajectory).
"""
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(-1, 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, 0), (1, 6), "
"or (N, 6) where N is the number of frames in the "
"trajectory and the dimension vector(s) containing "
"3 lengths and 3 angles: "
"[a, b, c, alpha, beta, gamma]"
)
raise ValueError(errmsg)
def _transform(self, ts):
try:
ts.dimensions = (
self.dimensions[0]
if self.dimensions.shape[0] == 1
else self.dimensions[ts.frame]
)
except IndexError as e:
raise ValueError(
f"Dimensions array has no data for frame {ts.frame}"
) from e
return ts