# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
#
# 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 GNU Public Licence, v2 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
#
"""\
Base classes --- :mod:`MDAnalysis.coordinates.base`
===================================================
Derive other Timestep, FrameIterator, Reader and Writer classes from the classes
in this module. The derived classes must follow the :ref:`Trajectory API`
in :mod:`MDAnalysis.coordinates.__init__`.
Timestep
--------
A :class:`Timestep` holds information for the current time frame in
the trajectory. It is one of the central data structures in
MDAnalysis.
.. class:: Timestep
.. automethod:: __init__
.. automethod:: from_coordinates
.. automethod:: from_timestep
.. automethod:: _init_unitcell
.. autoattribute:: n_atoms
.. attribute::`frame`
frame number (0-based)
.. versionchanged:: 0.11.0
Frames now 0-based; was 1-based
.. autoattribute:: time
.. autoattribute:: dt
.. autoattribute:: positions
.. autoattribute:: velocities
.. autoattribute:: forces
.. autoattribute:: has_positions
.. autoattribute:: has_velocities
.. autoattribute:: has_forces
.. attribute:: _pos
:class:`numpy.ndarray` of dtype :class:`~numpy.float32` of shape
(*n_atoms*, 3) and internal FORTRAN order, holding the raw
cartesian coordinates (in MDAnalysis units, i.e. Å).
.. Note::
Normally one does not directly access :attr:`_pos` but uses
the :meth:`~MDAnalysis.core.groups.AtomGroup.coordinates`
method of an :class:`~MDAnalysis.core.groups.AtomGroup` but
sometimes it can be faster to directly use the raw
coordinates. Any changes to this array are immediately
reflected in atom positions. If the frame is written to a new
trajectory then the coordinates are changed. If a new
trajectory frame is loaded, then *all* contents of
:attr:`_pos` are overwritten.
.. attribute:: _velocities
:class:`numpy.ndarray` of dtype :class:`~numpy.float32`. of shape
(*n_atoms*, 3), holding the raw velocities (in MDAnalysis
units, i.e. typically Å/ps).
.. Note::
Normally velocities are accessed through the
:attr:`velocities` or the
:meth:`~MDAnalysis.core.groups.AtomGroup.velocities`
method of an :class:`~MDAnalysis.core.groups.AtomGroup`
:attr:`~Timestep._velocities` only exists if the :attr:`has_velocities`
flag is True
.. versionadded:: 0.7.5
.. attribute:: _forces
:class:`numpy.ndarray` of dtype :class:`~numpy.float32`. of shape
(*n_atoms*, 3), holding the forces
:attr:`~Timestep._forces` only exists if :attr:`has_forces`
is True
.. versionadded:: 0.11.0
Added as optional to :class:`Timestep`
.. autoattribute:: dimensions
.. autoattribute:: triclinic_dimensions
.. autoattribute:: volume
.. automethod:: __getitem__
.. automethod:: __eq__
.. automethod:: __iter__
.. automethod:: copy
.. automethod:: copy_slice
FrameIterators
--------------
Iterator classes used by the by the :class:`ProtoReader`.
.. autoclass:: FrameIteratorBase
.. autoclass:: FrameIteratorSliced
.. autoclass:: FrameIteratorAll
.. autoclass:: FrameIteratorIndices
Readers
-------
Readers know how to take trajectory data in a given format and present it in a
common API to the user in MDAnalysis. There are two types of readers:
1. Readers for *multi frame trajectories*, i.e., file formats that typically
contain many frames. These readers are typically derived from
:class:`ReaderBase`.
2. Readers for *single frame formats*: These file formats only contain a single
coordinate set. These readers are derived from
:class`:SingleFrameReaderBase`.
The underlying low-level readers handle closing of files in different
ways. Typically, the MDAnalysis readers try to ensure that files are always
closed when a reader instance is garbage collected, which relies on
implementing a :meth:`~ReaderBase.__del__` method. However, in some cases, this
is not necessary (for instance, for the single frame formats) and then such a
method can lead to undesirable side effects (such as memory leaks). In this
case, :class:`ProtoReader` should be used.
.. autoclass:: ReaderBase
:members:
:inherited-members:
.. autoclass:: SingleFrameReaderBase
:members:
:inherited-members:
.. autoclass:: ProtoReader
:members:
Writers
-------
Writers know how to write information in a :class:`Timestep` to a trajectory
file.
.. autoclass:: WriterBase
:members:
:inherited-members:
Converters
----------
Converters output information to other libraries.
.. autoclass:: ConverterBase
:members:
:inherited-members:
Helper classes
--------------
The following classes contain basic functionality that all readers and
writers share.
.. autoclass:: IOBase
:members:
"""
from __future__ import absolute_import
import six
from six.moves import range
import numpy as np
import numbers
import copy
import warnings
import weakref
from . import core
from .. import NoDataError
from .. import (
_READERS, _READER_HINTS,
_SINGLEFRAME_WRITERS,
_MULTIFRAME_WRITERS,
_CONVERTERS
)
from .. import units
from ..auxiliary.base import AuxReader
from ..auxiliary.core import auxreader
from ..lib.util import asiterable, Namespace
[docs]class Timestep(object):
"""Timestep data for one frame
:Methods:
``ts = Timestep(n_atoms)``
create a timestep object with space for n_atoms
.. versionchanged:: 0.11.0
Added :meth:`from_timestep` and :meth:`from_coordinates` constructor
methods.
:class:`Timestep` init now only accepts integer creation.
:attr:`n_atoms` now a read only property.
:attr:`frame` now 0-based instead of 1-based.
Attributes `status` and `step` removed.
"""
order = 'F'
[docs] def __init__(self, n_atoms, **kwargs):
"""Create a Timestep, representing a frame of a trajectory
Parameters
----------
n_atoms : int
The total number of atoms this Timestep describes
positions : bool, optional
Whether this Timestep has position information [``True``]
velocities : bool (optional)
Whether this Timestep has velocity information [``False``]
forces : bool (optional)
Whether this Timestep has force information [``False``]
reader : Reader (optional)
A weak reference to the owning Reader. Used for
when attributes require trajectory manipulation (e.g. dt)
dt : float (optional)
The time difference between frames (ps). If :attr:`time`
is set, then `dt` will be ignored.
time_offset : float (optional)
The starting time from which to calculate time (in ps)
.. versionchanged:: 0.11.0
Added keywords for `positions`, `velocities` and `forces`.
Can add and remove position/velocity/force information by using
the ``has_*`` attribute.
"""
# readers call Reader._read_next_timestep() on init, incrementing
# self.frame to 0
self.frame = -1
self._n_atoms = n_atoms
self.data = {}
for att in ('dt', 'time_offset'):
try:
self.data[att] = kwargs[att]
except KeyError:
pass
try:
# do I have a hook back to the Reader?
self._reader = weakref.ref(kwargs['reader'])
except KeyError:
pass
# Stupid hack to make it allocate first time round
# ie we have to go from not having, to having positions
# to make the Timestep allocate
self._has_positions = False
self._has_velocities = False
self._has_forces = False
# These will allocate the arrays if the has flag
# gets set to True
self.has_positions = kwargs.get('positions', True)
self.has_velocities = kwargs.get('velocities', False)
self.has_forces = kwargs.get('forces', False)
self._unitcell = self._init_unitcell()
# set up aux namespace for adding auxiliary data
self.aux = Namespace()
[docs] @classmethod
def from_timestep(cls, other, **kwargs):
"""Create a copy of another Timestep, in the format of this Timestep
.. versionadded:: 0.11.0
"""
ts = cls(other.n_atoms,
positions=other.has_positions,
velocities=other.has_velocities,
forces=other.has_forces,
**kwargs)
ts.frame = other.frame
ts.dimensions = other.dimensions
try:
ts.positions = other.positions.copy(order=cls.order)
except NoDataError:
pass
try:
ts.velocities = other.velocities.copy(order=cls.order)
except NoDataError:
pass
try:
ts.forces = other.forces.copy(order=cls.order)
except NoDataError:
pass
# Optional attributes that don't live in .data
# should probably iron out these last kinks
for att in ('_frame',):
try:
setattr(ts, att, getattr(other, att))
except AttributeError:
pass
if hasattr(ts, '_reader'):
other._reader = weakref.ref(ts._reader())
ts.data = copy.deepcopy(other.data)
return ts
[docs] @classmethod
def from_coordinates(cls,
positions=None,
velocities=None,
forces=None,
**kwargs):
"""Create an instance of this Timestep, from coordinate data
Can pass position, velocity and force data to form a Timestep.
.. versionadded:: 0.11.0
"""
has_positions = positions is not None
has_velocities = velocities is not None
has_forces = forces is not None
lens = [len(a) for a in [positions, velocities, forces]
if a is not None]
if not lens:
raise ValueError("Must specify at least one set of data")
n_atoms = max(lens)
# Check arrays are matched length?
if not all(val == n_atoms for val in lens):
raise ValueError("Lengths of input data mismatched")
ts = cls(n_atoms,
positions=has_positions,
velocities=has_velocities,
forces=has_forces,
**kwargs)
if has_positions:
ts.positions = positions
if has_velocities:
ts.velocities = velocities
if has_forces:
ts.forces = forces
return ts
[docs] def _init_unitcell(self):
"""Create custom datastructure for :attr:`_unitcell`."""
# override for other Timesteps
return np.zeros((6), np.float32)
[docs] def __eq__(self, other):
"""Compare with another Timestep
.. versionadded:: 0.11.0
"""
if not isinstance(other, Timestep):
return False
if not self.frame == other.frame:
return False
if not self.n_atoms == other.n_atoms:
return False
if not self.has_positions == other.has_positions:
return False
if self.has_positions:
if not (self.positions == other.positions).all():
return False
if not self.has_velocities == other.has_velocities:
return False
if self.has_velocities:
if not (self.velocities == other.velocities).all():
return False
if not self.has_forces == other.has_forces:
return False
if self.has_forces:
if not (self.forces == other.forces).all():
return False
return True
def __ne__(self, other):
return not self == other
[docs] def __getitem__(self, atoms):
"""Get a selection of coordinates
``ts[i]``
return coordinates for the i'th atom (0-based)
``ts[start:stop:skip]``
return an array of coordinates, where start, stop and skip
correspond to atom indices,
:attr:`MDAnalysis.core.groups.Atom.index` (0-based)
"""
if isinstance(atoms, numbers.Integral):
return self._pos[atoms]
elif isinstance(atoms, (slice, np.ndarray)):
return self._pos[atoms]
else:
raise TypeError
def __getattr__(self, attr):
# special-case timestep info
if attr in ('velocities', 'forces', 'positions'):
raise NoDataError('This Timestep has no ' + attr)
err = "{selfcls} object has no attribute '{attr}'"
raise AttributeError(err.format(selfcls=type(self).__name__,
attr=attr))
def __len__(self):
return self.n_atoms
[docs] def __iter__(self):
"""Iterate over coordinates
``for x in ts``
iterate of the coordinates, atom by atom
"""
for i in range(self.n_atoms):
yield self[i]
def __repr__(self):
desc = "< Timestep {0}".format(self.frame)
try:
tail = " with unit cell dimensions {0} >".format(self.dimensions)
except NotImplementedError:
tail = " >"
return desc + tail
[docs] def copy(self):
"""Make an independent ("deep") copy of the whole :class:`Timestep`."""
return self.__deepcopy__()
def __deepcopy__(self):
return self.from_timestep(self)
[docs] def copy_slice(self, sel):
"""Make a new `Timestep` containing a subset of the original `Timestep`.
Parameters
----------
sel : array_like or slice
The underlying position, velocity, and force arrays are sliced
using a :class:`list`, :class:`slice`, or any array-like.
Returns
-------
:class:`Timestep`
A `Timestep` object of the same type containing all header
information and all atom information relevant to the selection.
Note
----
The selection must be a 0 based :class:`slice` or array of the atom indices
in this :class:`Timestep`
Example
-------
Using a Python :class:`slice` object::
new_ts = ts.copy_slice(slice(start, stop, step))
Using a list of indices::
new_ts = ts.copy_slice([0, 2, 10, 20, 23])
.. versionadded:: 0.8
.. versionchanged:: 0.11.0
Reworked to follow new Timestep API. Now will strictly only
copy official attributes of the Timestep.
"""
# Detect the size of the Timestep by doing a dummy slice
try:
pos = self.positions[sel, :]
except NoDataError:
# It's cool if there's no Data, we'll live
pos = None
except Exception:
six.raise_from(
TypeError(
"Selection type must be compatible with slicing"
" the coordinates"
),
None)
try:
vel = self.velocities[sel, :]
except NoDataError:
vel = None
except Exception:
six.raise_from(
TypeError("Selection type must be compatible with slicing"
" the coordinates"),
None)
try:
force = self.forces[sel, :]
except NoDataError:
force = None
except Exception:
six.raise_from(
TypeError(
"Selection type must be compatible with slicing"
" the coordinates"
),
None)
new_TS = self.__class__.from_coordinates(
positions=pos,
velocities=vel,
forces=force)
new_TS._unitcell = self._unitcell.copy()
new_TS.frame = self.frame
for att in ('_frame',):
try:
setattr(new_TS, att, getattr(self, att))
except AttributeError:
pass
if hasattr(self, '_reader'):
new_TS._reader = weakref.ref(self._reader())
new_TS.data = copy.deepcopy(self.data)
return new_TS
@property
def n_atoms(self):
"""A read only view of the number of atoms this Timestep has
.. versionchanged:: 0.11.0
Changed to read only property
"""
# In future could do some magic here to make setting n_atoms
# resize the coordinate arrays, but
# - not sure if that is ever useful
# - not sure how to manage existing data upon extension
return self._n_atoms
@property
def has_positions(self):
"""A boolean of whether this Timestep has position data
This can be changed to ``True`` or ``False`` to allocate space for
or remove the data.
.. versionadded:: 0.11.0
"""
return self._has_positions
@has_positions.setter
def has_positions(self, val):
if val and not self._has_positions:
# Setting this will always reallocate position data
# ie
# True -> False -> True will wipe data from first True state
self._pos = np.zeros((self.n_atoms, 3), dtype=np.float32,
order=self.order)
self._has_positions = True
elif not val:
# Unsetting val won't delete the numpy array
self._has_positions = False
@property
def positions(self):
"""A record of the positions of all atoms in this Timestep
Setting this attribute will add positions to the Timestep if they
weren't originally present.
Returns
-------
positions : numpy.ndarray with dtype numpy.float32
position data of shape ``(n_atoms, 3)`` for all atoms
Raises
------
:exc:`MDAnalysis.exceptions.NoDataError`
if the Timestep has no position data
.. versionchanged:: 0.11.0
Now can raise :exc:`NoDataError` when no position data present
"""
if self.has_positions:
return self._pos
else:
raise NoDataError("This Timestep has no positions")
@positions.setter
def positions(self, new):
self.has_positions = True
self._pos[:] = new
@property
def _x(self):
"""A view onto the x dimension of position data
.. versionchanged:: 0.11.0
Now read only
"""
return self.positions[:, 0]
@property
def _y(self):
"""A view onto the y dimension of position data
.. versionchanged:: 0.11.0
Now read only
"""
return self.positions[:, 1]
@property
def _z(self):
"""A view onto the z dimension of position data
.. versionchanged:: 0.11.0
Now read only
"""
return self.positions[:, 2]
@property
def has_velocities(self):
"""A boolean of whether this Timestep has velocity data
This can be changed to ``True`` or ``False`` to allocate space for
or remove the data.
.. versionadded:: 0.11.0
"""
return self._has_velocities
@has_velocities.setter
def has_velocities(self, val):
if val and not self._has_velocities:
self._velocities = np.zeros((self.n_atoms, 3), dtype=np.float32,
order=self.order)
self._has_velocities = True
elif not val:
self._has_velocities = False
@property
def velocities(self):
"""A record of the velocities of all atoms in this Timestep
Setting this attribute will add velocities to the Timestep if they
weren't originally present.
Returns
-------
velocities : numpy.ndarray with dtype numpy.float32
velocity data of shape ``(n_atoms, 3)`` for all atoms
Raises
------
:exc:`MDAnalysis.exceptions.NoDataError`
if the Timestep has no velocity data
.. versionadded:: 0.11.0
"""
if self.has_velocities:
return self._velocities
else:
raise NoDataError("This Timestep has no velocities")
@velocities.setter
def velocities(self, new):
self.has_velocities = True
self._velocities[:] = new
@property
def has_forces(self):
"""A boolean of whether this Timestep has force data
This can be changed to ``True`` or ``False`` to allocate space for
or remove the data.
.. versionadded:: 0.11.0
"""
return self._has_forces
@has_forces.setter
def has_forces(self, val):
if val and not self._has_forces:
self._forces = np.zeros((self.n_atoms, 3), dtype=np.float32,
order=self.order)
self._has_forces = True
elif not val:
self._has_forces = False
@property
def forces(self):
"""A record of the forces of all atoms in this Timestep
Setting this attribute will add forces to the Timestep if they
weren't originally present.
Returns
-------
forces : numpy.ndarray with dtype numpy.float32
force data of shape ``(n_atoms, 3)`` for all atoms
Raises
------
:exc:`MDAnalysis.exceptions.NoDataError`
if the Timestep has no force data
.. versionadded:: 0.11.0
"""
if self.has_forces:
return self._forces
else:
raise NoDataError("This Timestep has no forces")
@forces.setter
def forces(self, new):
self.has_forces = True
self._forces[:] = new
@property
def dimensions(self):
"""unitcell dimensions (*A*, *B*, *C*, *alpha*, *beta*, *gamma*)
lengths *a*, *b*, *c* are in the MDAnalysis length unit (Å), and
angles are in degrees.
Setting dimensions will populate the underlying native format
description of box dimensions
"""
# The actual Timestep._unitcell depends on the underlying
# trajectory format. It can be e.g. six floats representing
# the box edges and angles or the 6 unique components of the
# box matrix or the full box matrix.
return self._unitcell
@dimensions.setter
def dimensions(self, box):
self._unitcell[:] = box
@property
def volume(self):
"""volume of the unitcell"""
return core.box_volume(self.dimensions)
@property
def triclinic_dimensions(self):
"""The unitcell dimensions represented as triclinic vectors
Returns
-------
numpy.ndarray
A (3, 3) numpy.ndarray of unit cell vectors
Examples
--------
The unitcell for a given system can be queried as either three
vectors lengths followed by their respective angle, or as three
triclinic vectors.
>>> ts.dimensions
array([ 13., 14., 15., 90., 90., 90.], dtype=float32)
>>> ts.triclinic_dimensions
array([[ 13., 0., 0.],
[ 0., 14., 0.],
[ 0., 0., 15.]], dtype=float32)
Setting the attribute also works::
>>> ts.triclinic_dimensions = [[15, 0, 0], [5, 15, 0], [5, 5, 15]]
>>> ts.dimensions
array([ 15. , 15.81138802, 16.58312416, 67.58049774,
72.45159912, 71.56504822], dtype=float32)
See Also
--------
:func:`MDAnalysis.lib.mdamath.triclinic_vectors`
.. versionadded:: 0.11.0
"""
return core.triclinic_vectors(self.dimensions)
@triclinic_dimensions.setter
def triclinic_dimensions(self, new):
"""Set the unitcell for this Timestep as defined by triclinic vectors
.. versionadded:: 0.11.0
"""
self.dimensions = core.triclinic_box(*new)
@property
def dt(self):
"""The time difference in ps between timesteps
Note
----
This defaults to 1.0 ps in the absence of time data
.. versionadded:: 0.11.0
"""
try:
return self.data['dt']
except KeyError:
pass
try:
dt = self.data['dt'] = self._reader()._get_dt()
return dt
except AttributeError:
pass
warnings.warn("Reader has no dt information, set to 1.0 ps")
return 1.0
@dt.setter
def dt(self, new):
self.data['dt'] = new
@dt.deleter
def dt(self):
del self.data['dt']
@property
def time(self):
"""The time in ps of this timestep
This is calculated as::
time = ts.data['time_offset'] + ts.time
Or, if the trajectory doesn't provide time information::
time = ts.data['time_offset'] + ts.frame * ts.dt
.. versionadded:: 0.11.0
"""
offset = self.data.get('time_offset', 0)
try:
return self.data['time'] + offset
except KeyError:
return self.dt * self.frame + offset
@time.setter
def time(self, new):
self.data['time'] = new
@time.deleter
def time(self):
del self.data['time']
[docs]class FrameIteratorBase(object):
"""
Base iterable over the frames of a trajectory.
A frame iterable has a length that can be accessed with the :func:`len`
function, and can be indexed similarly to a full trajectory. When indexed,
indices are resolved relative to the iterable and not relative to the
trajectory.
.. versionadded:: 0.19.0
"""
def __init__(self, trajectory):
self._trajectory = trajectory
def __len__(self):
raise NotImplementedError()
@staticmethod
def _avoid_bool_list(frames):
if isinstance(frames, list) and frames and isinstance(frames[0], bool):
return np.array(frames, dtype=bool)
return frames
@property
def trajectory(self):
return self._trajectory
[docs]class FrameIteratorSliced(FrameIteratorBase):
"""
Iterable over the frames of a trajectory on the basis of a slice.
Parameters
----------
trajectory: ProtoReader
The trajectory over which to iterate.
frames: slice
A slice to select the frames of interest.
See Also
--------
FrameIteratorBase
.. versionadded:: 0.19.0
"""
def __init__(self, trajectory, frames):
# It would be easier to store directly a range object, as it would
# store its parameters in a single place, calculate its length, and
# take care of most the indexing. Though, doing so is not compatible
# with python 2 where xrange (or range with six) is only an iterator.
super(FrameIteratorSliced, self).__init__(trajectory)
self._start, self._stop, self._step = trajectory.check_slice_indices(
frames.start, frames.stop, frames.step,
)
def __len__(self):
return range_length(self.start, self.stop, self.step)
def __iter__(self):
for i in range(self.start, self.stop, self.step):
yield self.trajectory[i]
self.trajectory.rewind()
def __getitem__(self, frame):
if isinstance(frame, numbers.Integral):
length = len(self)
if not -length < frame < length:
raise IndexError('Index {} is out of range of the range of length {}.'
.format(frame, length))
if frame < 0:
frame = len(self) + frame
frame = self.start + frame * self.step
return self.trajectory._read_frame_with_aux(frame)
elif isinstance(frame, slice):
step = (frame.step or 1) * self.step
if frame.start is None:
if frame.step is None or frame.step > 0:
start = self.start
else:
start = self.start + (len(self) - 1) * self.step
else:
start = self.start + (frame.start or 0) * self.step
if frame.stop is None:
if frame.step is None or frame.step > 0:
last = start + (range_length(start, self.stop, step) - 1) * step
else:
last = self.start
stop = last + np.sign(step)
else:
stop = self.start + (frame.stop or 0) * self.step
new_slice = slice(start, stop, step)
frame_iterator = FrameIteratorSliced(self.trajectory, new_slice)
# The __init__ of FrameIteratorSliced does some conversion between
# the way indices are handled in slices and the way they are
# handled by range. We need to overwrite this conversion as we
# already use the logic for range.
frame_iterator._start = start
frame_iterator._stop = stop
frame_iterator._step = step
return frame_iterator
else:
# Indexing with a lists of bools does not behave the same in all
# version of numpy.
frame = self._avoid_bool_list(frame)
frames = np.array(list(range(self.start, self.stop, self.step)))[frame]
return FrameIteratorIndices(self.trajectory, frames)
@property
def start(self):
return self._start
@property
def stop(self):
return self._stop
@property
def step(self):
return self._step
[docs]class FrameIteratorAll(FrameIteratorBase):
"""
Iterable over all the frames of a trajectory.
Parameters
----------
trajectory: ProtoReader
The trajectory over which to iterate.
See Also
--------
FrameIteratorBase
.. versionadded:: 0.19.0
"""
def __init__(self, trajectory):
super(FrameIteratorAll, self).__init__(trajectory)
def __len__(self):
return self.trajectory.n_frames
def __iter__(self):
return iter(self.trajectory)
def __getitem__(self, frame):
return self.trajectory[frame]
[docs]class FrameIteratorIndices(FrameIteratorBase):
"""
Iterable over the frames of a trajectory listed in a sequence of indices.
Parameters
----------
trajectory: ProtoReader
The trajectory over which to iterate.
frames: sequence
A sequence of indices.
See Also
--------
FrameIteratorBase
"""
def __init__(self, trajectory, frames):
super(FrameIteratorIndices, self).__init__(trajectory)
self._frames = []
for frame in frames:
if not isinstance(frame, numbers.Integral):
raise TypeError("Frames indices must be integers.")
frame = trajectory._apply_limits(frame)
self._frames.append(frame)
self._frames = tuple(self._frames)
def __len__(self):
return len(self.frames)
def __iter__(self):
for frame in self.frames:
yield self.trajectory._read_frame_with_aux(frame)
def __getitem__(self, frame):
if isinstance(frame, numbers.Integral):
frame = self.frames[frame]
return self.trajectory._read_frame_with_aux(frame)
else:
frame = self._avoid_bool_list(frame)
frames = np.array(self.frames)[frame]
return FrameIteratorIndices(self.trajectory, frames)
@property
def frames(self):
return self._frames
[docs]class IOBase(object):
"""Base class bundling common functionality for trajectory I/O.
.. versionchanged:: 0.8
Added context manager protocol.
"""
#: dict with units of of *time* and *length* (and *velocity*, *force*,
#: ... for formats that support it)
units = {'time': None, 'length': None, 'velocity': None}
[docs] def convert_pos_from_native(self, x, inplace=True):
"""Conversion of coordinate array x from native units to base units.
Parameters
----------
x : array_like
Positions to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input `x` is modified in place and also returned.
In-place operations improve performance because allocating new arrays
is avoided.
.. versionchanged:: 0.7.5
Keyword `inplace` can be set to ``False`` so that a
modified copy is returned *unless* no conversion takes
place, in which case the reference to the unmodified `x` is
returned.
"""
f = units.get_conversion_factor('length',
self.units['length'], 'Angstrom')
if f == 1.:
return x
if not inplace:
return f * x
x *= f
return x
[docs] def convert_velocities_from_native(self, v, inplace=True):
"""Conversion of velocities array *v* from native to base units
Parameters
----------
v : array_like
Velocities to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input *v* is modified in place and also returned.
In-place operations improve performance because allocating new arrays
is avoided.
.. versionadded:: 0.7.5
"""
f = units.get_conversion_factor(
'speed', self.units['velocity'], 'Angstrom/ps')
if f == 1.:
return v
if not inplace:
return f * v
v *= f
return v
[docs] def convert_forces_from_native(self, force, inplace=True):
"""Conversion of forces array *force* from native to base units
Parameters
----------
force : array_like
Forces to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input *force* is modified in place and also returned.
In-place operations improve performance because allocating new arrays
is avoided.
.. versionadded:: 0.7.7
"""
f = units.get_conversion_factor(
'force', self.units['force'], 'kJ/(mol*Angstrom)')
if f == 1.:
return force
if not inplace:
return f * force
force *= f
return force
[docs] def convert_time_from_native(self, t, inplace=True):
"""Convert time *t* from native units to base units.
Parameters
----------
t : array_like
Time values to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input `t` is modified in place and also returned
(although note that scalar values `t` are passed by value in Python and
hence an in-place modification has no effect on the caller.) In-place
operations improve performance because allocating new arrays is
avoided.
.. versionchanged:: 0.7.5
Keyword `inplace` can be set to ``False`` so that a
modified copy is returned *unless* no conversion takes
place, in which case the reference to the unmodified `x` is
returned.
"""
f = units.get_conversion_factor(
'time', self.units['time'], 'ps')
if f == 1.:
return t
if not inplace:
return f * t
t *= f
return t
[docs] def convert_pos_to_native(self, x, inplace=True):
"""Conversion of coordinate array `x` from base units to native units.
Parameters
----------
x : array_like
Positions to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input `x` is modified in place and also returned.
In-place operations improve performance because allocating new arrays
is avoided.
.. versionchanged:: 0.7.5
Keyword `inplace` can be set to ``False`` so that a
modified copy is returned *unless* no conversion takes
place, in which case the reference to the unmodified `x` is
returned.
"""
f = units.get_conversion_factor(
'length', 'Angstrom', self.units['length'])
if f == 1.:
return x
if not inplace:
return f * x
x *= f
return x
[docs] def convert_velocities_to_native(self, v, inplace=True):
"""Conversion of coordinate array `v` from base to native units
Parameters
----------
v : array_like
Velocities to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input `v` is modified in place and also returned.
In-place operations improve performance because allocating new arrays
is avoided.
.. versionadded:: 0.7.5
"""
f = units.get_conversion_factor(
'speed', 'Angstrom/ps', self.units['velocity'])
if f == 1.:
return v
if not inplace:
return f * v
v *= f
return v
[docs] def convert_forces_to_native(self, force, inplace=True):
"""Conversion of force array *force* from base to native units.
Parameters
----------
force : array_like
Forces to transform
inplace : bool (optional)
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input `force` is modified in place and also returned.
In-place operations improve performance because allocating new arrays
is avoided.
.. versionadded:: 0.7.7
"""
f = units.get_conversion_factor(
'force', 'kJ/(mol*Angstrom)', self.units['force'])
if f == 1.:
return force
if not inplace:
return f * force
force *= f
return force
[docs] def convert_time_to_native(self, t, inplace=True):
"""Convert time *t* from base units to native units.
Parameters
----------
t : array_like
Time values to transform
inplace : bool, optional
Whether to modify the array inplace, overwriting previous data
Note
----
By default, the input *t* is modified in place and also
returned. (Also note that scalar values *t* are passed by
value in Python and hence an in-place modification has no
effect on the caller.)
.. versionchanged:: 0.7.5
Keyword *inplace* can be set to ``False`` so that a
modified copy is returned *unless* no conversion takes
place, in which case the reference to the unmodified *x* is
returned.
"""
f = units.get_conversion_factor(
'time', 'ps', self.units['time'])
if f == 1.:
return t
if not inplace:
return f * t
t *= f
return t
[docs] def close(self):
"""Close the trajectory file."""
pass # pylint: disable=unnecessary-pass
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
# see http://docs.python.org/2/library/stdtypes.html#typecontextmanager
self.close()
return False # do not suppress exceptions
class _Readermeta(type):
"""Automatic Reader registration metaclass
.. versionchanged:: 1.0.0
Added _format_hint functionality
"""
# Auto register upon class creation
def __init__(cls, name, bases, classdict):
type.__init__(type, name, bases, classdict)
try:
fmt = asiterable(classdict['format'])
except KeyError:
pass
else:
for fmt_name in fmt:
fmt_name = fmt_name.upper()
_READERS[fmt_name] = cls
if '_format_hint' in classdict:
# isn't bound yet, so access __func__
_READER_HINTS[fmt_name] = classdict['_format_hint'].__func__
[docs]class ProtoReader(six.with_metaclass(_Readermeta, IOBase)):
"""Base class for Readers, without a :meth:`__del__` method.
Extends :class:`IOBase` with most attributes and methods of a generic
Reader, with the exception of a :meth:`__del__` method. It should be used
as base for Readers that do not need :meth:`__del__`, especially since
having even an empty :meth:`__del__` might lead to memory leaks.
See the :ref:`Trajectory API` definition in
:mod:`MDAnalysis.coordinates.__init__` for the required attributes and
methods.
See Also
--------
:class:`ReaderBase`
.. versionchanged:: 0.11.0
Frames now 0-based instead of 1-based
"""
#: The appropriate Timestep class, e.g.
#: :class:`MDAnalysis.coordinates.xdrfile.XTC.Timestep` for XTC.
_Timestep = Timestep
def __init__(self):
# initialise list to store added auxiliary readers in
# subclasses should now call super
self._auxs = {}
self._transformations=[]
def __len__(self):
return self.n_frames
[docs] @classmethod
def parse_n_atoms(cls, filename, **kwargs):
"""Read the coordinate file and deduce the number of atoms
Returns
-------
n_atoms : int
the number of atoms in the coordinate file
Raises
------
NotImplementedError
when the number of atoms can't be deduced
"""
raise NotImplementedError("{} cannot deduce the number of atoms"
"".format(cls.__name__))
[docs] def next(self):
"""Forward one step to next frame."""
try:
ts = self._read_next_timestep()
except (EOFError, IOError):
self.rewind()
six.raise_from(StopIteration, None)
else:
for auxname in self.aux_list:
ts = self._auxs[auxname].update_ts(ts)
ts = self._apply_transformations(ts)
return ts
def __next__(self):
"""Forward one step to next frame when using the `next` builtin."""
return self.next()
[docs] def rewind(self):
"""Position at beginning of trajectory"""
self._reopen()
self.next()
@property
def dt(self):
"""Time between two trajectory frames in picoseconds."""
return self.ts.dt
@property
def totaltime(self):
"""Total length of the trajectory
The time is calculated as ``(n_frames - 1) * dt``, i.e., we assume that
the first frame no time as elapsed. Thus, a trajectory with two frames will
be considered to have a length of a single time step `dt` and a
"trajectory" with a single frame will be reported as length 0.
"""
return (self.n_frames - 1) * self.dt
@property
def frame(self):
"""Frame number of the current time step.
This is a simple short cut to :attr:`Timestep.frame`.
"""
return self.ts.frame
@property
def time(self):
"""Time of the current frame in MDAnalysis time units (typically ps).
This is either read straight from the Timestep, or calculated as
time = :attr:`Timestep.frame` * :attr:`Timestep.dt`
"""
return self.ts.time
@property
def trajectory(self):
# Makes a reader effectively commpatible with a FrameIteratorBase
return self
[docs] def Writer(self, filename, **kwargs):
"""A trajectory writer with the same properties as this trajectory."""
raise NotImplementedError(
"Sorry, there is no Writer for this format in MDAnalysis. "
"Please file an enhancement request at "
"https://github.com/MDAnalysis/mdanalysis/issues")
[docs] def OtherWriter(self, filename, **kwargs):
"""Returns a writer appropriate for *filename*.
Sets the default keywords *start*, *step* and *dt* (if
available). *n_atoms* is always set from :attr:`Reader.n_atoms`.
See Also
--------
:meth:`Reader.Writer` and :func:`MDAnalysis.Writer`
"""
kwargs['n_atoms'] = self.n_atoms # essential
kwargs.setdefault('start', self.frame)
try:
kwargs.setdefault('dt', self.dt)
except KeyError:
pass
return core.writer(filename, **kwargs)
def _read_next_timestep(self, ts=None): # pragma: no cover
# Example from DCDReader:
# if ts is None:
# ts = self.ts
# ts.frame = self._read_next_frame(etc)
# return ts
raise NotImplementedError(
"BUG: Override _read_next_timestep() in the trajectory reader!")
def __iter__(self):
""" Iterate over trajectory frames. """
self._reopen()
return self
def _reopen(self):
"""Should position Reader to just before first frame
Calling next after this should return the first frame
"""
pass # pylint: disable=unnecessary-pass
def _apply_limits(self, frame):
if frame < 0:
frame += len(self)
if frame < 0 or frame >= len(self):
raise IndexError("Index {} exceeds length of trajectory ({})."
"".format(frame, len(self)))
return frame
def __getitem__(self, frame):
"""Return the Timestep corresponding to *frame*.
If `frame` is a integer then the corresponding frame is
returned. Negative numbers are counted from the end.
If frame is a :class:`slice` then an iterator is returned that
allows iteration over that part of the trajectory.
Note
----
*frame* is a 0-based frame index.
"""
if isinstance(frame, numbers.Integral):
frame = self._apply_limits(frame)
return self._read_frame_with_aux(frame)
elif isinstance(frame, (list, np.ndarray)):
if len(frame) != 0 and isinstance(frame[0], (bool, np.bool_)):
# Avoid having list of bools
frame = np.asarray(frame, dtype=bool)
# Convert bool array to int array
frame = np.arange(len(self))[frame]
return FrameIteratorIndices(self, frame)
elif isinstance(frame, slice):
start, stop, step = self.check_slice_indices(
frame.start, frame.stop, frame.step)
if start == 0 and stop == len(self) and step == 1:
return FrameIteratorAll(self)
else:
return FrameIteratorSliced(self, frame)
else:
raise TypeError("Trajectories must be an indexed using an integer,"
" slice or list of indices")
def _read_frame(self, frame):
"""Move to *frame* and fill timestep with data."""
raise TypeError("{0} does not support direct frame indexing."
"".format(self.__class__.__name__))
# Example implementation in the DCDReader:
# self._jump_to_frame(frame)
# ts = self.ts
# ts.frame = self._read_next_frame(ts._x, ts._y, ts._z,
# ts._unitcell, 1)
# return ts
def _read_frame_with_aux(self, frame):
"""Move to *frame*, updating ts with trajectory, transformations and auxiliary data."""
ts = self._read_frame(frame) # pylint: disable=assignment-from-no-return
for aux in self.aux_list:
ts = self._auxs[aux].update_ts(ts)
ts = self._apply_transformations(ts)
return ts
def _sliced_iter(self, start, stop, step):
"""Generator for slicing a trajectory.
*start* *stop* and *step* are 3 integers describing the slice.
Error checking is not done past this point.
A :exc:`NotImplementedError` is raised if random access to
frames is not implemented.
"""
# override with an appropriate implementation e.g. using self[i] might
# be much slower than skipping steps in a next() loop
try:
for i in range(start, stop, step):
yield self._read_frame_with_aux(i)
self.rewind()
except TypeError: # if _read_frame not implemented
six.raise_from(
TypeError(
"{0} does not support slicing."
"".format(self.__class__.__name__)),
None)
[docs] def check_slice_indices(self, start, stop, step):
"""Check frame indices are valid and clip to fit trajectory.
The usage follows standard Python conventions for :func:`range` but see
the warning below.
Parameters
----------
start : int or None
Starting frame index (inclusive). ``None`` corresponds to the default
of 0, i.e., the initial frame.
stop : int or None
Last frame index (exclusive). ``None`` corresponds to the default
of n_frames, i.e., it includes the last frame of the trajectory.
step : int or None
step size of the slice, ``None`` corresponds to the default of 1, i.e,
include every frame in the range `start`, `stop`.
Returns
-------
start, stop, step : tuple (int, int, int)
Integers representing the slice
Warning
-------
The returned values `start`, `stop` and `step` give the expected result
when passed in :func:`range` but gives unexpected behavior when passed
in a :class:`slice` when ``stop=None`` and ``step=-1``
This can be a problem for downstream processing of the output from this
method. For example, slicing of trajectories is implemented by passing
the values returned by :meth:`check_slice_indices` to :func:`range` ::
range(start, stop, step)
and using them as the indices to randomly seek to. On the other hand,
in :class:`MDAnalysis.analysis.base.AnalysisBase` the values returned
by :meth:`check_slice_indices` are used to splice the trajectory by
creating a :class:`slice` instance ::
slice(start, stop, step)
This creates a discrepancy because these two lines are not equivalent::
range(10, -1, -1) # [10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
range(10)[slice(10, -1, -1)] # []
"""
slice_dict = {'start': start, 'stop': stop, 'step': step}
for varname, var in slice_dict.items():
if isinstance(var, numbers.Integral):
slice_dict[varname] = int(var)
elif (var is None):
pass
else:
raise TypeError("{0} is not an integer".format(varname))
start = slice_dict['start']
stop = slice_dict['stop']
step = slice_dict['step']
if step == 0:
raise ValueError("Step size is zero")
nframes = len(self)
step = step or 1
if start is None:
start = 0 if step > 0 else nframes - 1
elif start < 0:
start += nframes
if start < 0:
start = 0
if step < 0 and start >= nframes:
start = nframes - 1
if stop is None:
stop = nframes if step > 0 else -1
elif stop < 0:
stop += nframes
if step > 0 and stop > nframes:
stop = nframes
return start, stop, step
def __repr__(self):
return ("<{cls} {fname} with {nframes} frames of {natoms} atoms>"
"".format(
cls=self.__class__.__name__,
fname=self.filename,
nframes=self.n_frames,
natoms=self.n_atoms
))
[docs] def add_auxiliary(self, auxname, auxdata, format=None, **kwargs):
"""Add auxiliary data to be read alongside trajectory.
Auxiliary data may be any data timeseries from the trajectory additional
to that read in by the trajectory reader. *auxdata* can be an
:class:`~MDAnalysis.auxiliary.base.AuxReader` instance, or the data
itself as e.g. a filename; in the latter case an appropriate
:class:`~MDAnalysis.auxiliary.base.AuxReader` is guessed from the
data/file format. An appropriate `format` may also be directly provided
as a key word argument.
On adding, the AuxReader is initially matched to the current timestep
of the trajectory, and will be updated when the trajectory timestep
changes (through a call to :meth:`next()` or jumping timesteps with
``trajectory[i]``).
The representative value(s) of the auxiliary data for each timestep (as
calculated by the :class:`~MDAnalysis.auxiliary.base.AuxReader`) are
stored in the current timestep in the ``ts.aux`` namespace under *auxname*;
e.g. to add additional pull force data stored in pull-force.xvg::
u = MDAnalysis.Universe(PDB, XTC)
u.trajectory.add_auxiliary('pull', 'pull-force.xvg')
The representative value for the current timestep may then be accessed
as ``u.trajectory.ts.aux.pull`` or ``u.trajectory.ts.aux['pull']``.
See Also
--------
:meth:`remove_auxiliary`
Note
----
Auxiliary data is assumed to be time-ordered, with no duplicates. See
the :ref:`Auxiliary API`.
"""
if auxname in self.aux_list:
raise ValueError("Auxiliary data with name {name} already "
"exists".format(name=auxname))
if isinstance(auxdata, AuxReader):
aux = auxdata
aux.auxname = auxname
else:
aux = auxreader(auxdata, format=format, auxname=auxname, **kwargs)
self._auxs[auxname] = aux
self.ts = aux.update_ts(self.ts)
[docs] def remove_auxiliary(self, auxname):
"""Clear data and close the :class:`~MDAnalysis.auxiliary.base.AuxReader`
for the auxiliary *auxname*.
See Also
--------
:meth:`add_auxiliary`
"""
aux = self._check_for_aux(auxname)
aux.close()
del aux
delattr(self.ts.aux, auxname)
@property
def aux_list(self):
""" Lists the names of added auxiliary data. """
return self._auxs.keys()
def _check_for_aux(self, auxname):
""" Check for the existance of an auxiliary *auxname*. If present,
return the AuxReader; if not, raise ValueError
"""
if auxname in self.aux_list:
return self._auxs[auxname]
else:
raise ValueError("No auxiliary named {name}".format(name=auxname))
[docs] def next_as_aux(self, auxname):
""" Move to the next timestep for which there is at least one step from
the auxiliary *auxname* within the cutoff specified in *auxname*.
This allows progression through the trajectory without encountering
``NaN`` representative values (unless these are specifically part of the
auxiliary data).
If the auxiliary cutoff is not set, where auxiliary steps are less frequent
(``auxiliary.dt > trajectory.dt``), this allows progression at the
auxiliary pace (rounded to nearest timestep); while if the auxiliary
steps are more frequent, this will work the same as calling
:meth:`next()`.
See the :ref:`Auxiliary API`.
See Also
--------
:meth:`iter_as_aux`
"""
aux = self._check_for_aux(auxname)
ts = self.ts
# catch up auxiliary if it starts earlier than trajectory
while aux.step_to_frame(aux.step + 1, ts) is None:
next(aux)
# find the next frame that'll have a representative value
next_frame = aux.next_nonempty_frame(ts)
if next_frame is None:
# no more frames with corresponding auxiliary values; stop iteration
raise StopIteration
# some readers set self._frame to -1, rather than self.frame, on
# _reopen; catch here or doesn't read first frame
while self.frame != next_frame or getattr(self, '_frame', 0) == -1:
# iterate trajectory until frame is reached
ts = self.next()
return ts
[docs] def iter_as_aux(self, auxname):
"""Iterate through timesteps for which there is at least one assigned
step from the auxiliary *auxname* within the cutoff specified in *auxname*.
See Also
--------
:meth:`next_as_aux`
:meth:`iter_auxiliary`
"""
aux = self._check_for_aux(auxname)
self._reopen()
aux._restart()
while True:
try:
yield self.next_as_aux(auxname)
except StopIteration:
return
[docs] def iter_auxiliary(self, auxname, start=None, stop=None, step=None,
selected=None):
""" Iterate through the auxiliary *auxname* independently of the trajectory.
Will iterate over the specified steps of the auxiliary (defaults to all
steps). Allows to access all values in an auxiliary, including those out
of the time range of the trajectory, without having to also iterate
through the trajectory.
After interation, the auxiliary will be repositioned at the current step.
Parameters
----------
auxname : str
Name of the auxiliary to iterate over.
(start, stop, step) : optional
Options for iterating over a slice of the auxiliary.
selected : lst | ndarray, optional
List of steps to iterate over.
Yields
------
:class:`~MDAnalysis.auxiliary.base.AuxStep` object
See Also
--------
:meth:`iter_as_aux`
"""
aux = self._check_for_aux(auxname)
if selected is not None:
selection = selected
else:
selection = slice(start, stop, step)
for i in aux[selection]:
yield i
aux.read_ts(self.ts)
[docs] def get_aux_attribute(self, auxname, attrname):
"""Get the value of *attrname* from the auxiliary *auxname*
Parameters
----------
auxname : str
Name of the auxiliary to get value for
attrname : str
Name of gettable attribute in the auxiliary reader
See Also
--------
:meth:`set_aux_attribute`
"""
aux = self._check_for_aux(auxname)
return getattr(aux, attrname)
[docs] def set_aux_attribute(self, auxname, attrname, new):
""" Set the value of *attrname* in the auxiliary *auxname*.
Parameters
----------
auxname : str
Name of the auxiliary to alter
attrname : str
Name of settable attribute in the auxiliary reader
new
New value to try set *attrname* to
See Also
--------
:meth:`get_aux_attribute`
:meth:`rename_aux` - to change the *auxname* attribute
"""
aux = self._check_for_aux(auxname)
if attrname == 'auxname':
self.rename_aux(auxname, new)
else:
setattr(aux, attrname, new)
[docs] def rename_aux(self, auxname, new):
""" Change the name of the auxiliary *auxname* to *new*.
Provided there is not already an auxiliary named *new*, the auxiliary
name will be changed in ts.aux namespace, the trajectory's
list of added auxiliaries, and in the auxiliary reader itself.
Parameters
----------
auxname : str
Name of the auxiliary to rename
new : str
New name to try set
Raises
------
ValueError
If the name *new* is already in use by an existing auxiliary.
"""
aux = self._check_for_aux(auxname)
if new in self.aux_list:
raise ValueError("Auxiliary data with name {name} already "
"exists".format(name=new))
aux.auxname = new
self._auxs[new] = self._auxs.pop(auxname)
setattr(self.ts.aux, new, self.ts.aux[auxname])
delattr(self.ts.aux, auxname)
[docs] def get_aux_descriptions(self, auxnames=None):
"""Get descriptions to allow reloading the specified auxiliaries.
If no auxnames are provided, defaults to the full list of added
auxiliaries.
Passing the resultant description to ``add_auxiliary()`` will allow
recreation of the auxiliary. e.g., to duplicate all auxiliaries into a
second trajectory::
descriptions = trajectory_1.get_aux_descriptions()
for aux in descriptions:
trajectory_2.add_auxiliary(**aux)
Returns
-------
list
List of dictionaries of the args/kwargs describing each auxiliary.
See Also
--------
:meth:`MDAnalysis.auxiliary.base.AuxReader.get_description`
"""
if not auxnames:
auxnames = self.aux_list
descriptions = [self._auxs[aux].get_description() for aux in auxnames]
return descriptions
@property
def transformations(self):
""" Returns the list of transformations"""
return self._transformations
@transformations.setter
def transformations(self, transformations):
if not self._transformations:
self._transformations = transformations
else:
raise ValueError("Transformations are already set")
# call reader here to apply the newly added transformation on the
# current loaded frame?
def _apply_transformations(self, ts):
"""Applies all the transformations given by the user """
for transform in self.transformations:
ts = transform(ts)
return ts
[docs]class ReaderBase(ProtoReader):
"""Base class for trajectory readers that extends :class:`ProtoReader` with a
:meth:`__del__` method.
New Readers should subclass :class:`ReaderBase` and properly implement a
:meth:`close` method, to ensure proper release of resources (mainly file
handles). Readers that are inherently safe in this regard should subclass
:class:`ProtoReader` instead.
See the :ref:`Trajectory API` definition in
:mod:`MDAnalysis.coordinates.__init__` for the required attributes and
methods.
See Also
--------
:class:`ProtoReader`
.. versionchanged:: 0.11.0
Most of the base Reader class definitions were offloaded to
:class:`ProtoReader` so as to allow the subclassing of ReaderBases without a
:meth:`__del__` method. Created init method to create common
functionality, all ReaderBase subclasses must now :func:`super` through this
class. Added attribute :attr:`_ts_kwargs`, which is created in init.
Provides kwargs to be passed to :class:`Timestep`
.. versionchanged:: 1.0
Removed deprecated flags functionality, use convert_units kwarg instead
"""
def __init__(self, filename, convert_units=True, **kwargs):
super(ReaderBase, self).__init__()
self.filename = filename
self.convert_units = convert_units
ts_kwargs = {}
for att in ('dt', 'time_offset'):
try:
val = kwargs[att]
except KeyError:
pass
else:
ts_kwargs[att] = val
self._ts_kwargs = ts_kwargs
[docs] def copy(self):
"""Return independent copy of this Reader.
New Reader will have its own file handle and can seek/iterate
independently of the original.
Will also copy the current state of the Timestep held in
the original Reader
"""
new = self.__class__(self.filename,
n_atoms=self.n_atoms)
if self.transformations:
new.add_transformations(*self.transformations)
# seek the new reader to the same frame we started with
new[self.ts.frame]
# then copy over the current Timestep in case it has
# been modified since initial load
new.ts = self.ts.copy()
for auxname, auxread in self._auxs.items():
new.add_auxiliary(auxname, auxread.copy())
return new
def __del__(self):
for aux in self.aux_list:
self._auxs[aux].close()
self.close()
class _Writermeta(type):
# Auto register this format upon class creation
def __init__(cls, name, bases, classdict):
type.__init__(type, name, bases, classdict)
try:
# grab the string which describes this format
# could be either 'PDB' or ['PDB', 'ENT'] for multiple formats
fmt = asiterable(classdict['format'])
except KeyError:
# not required however
pass
else:
# does the Writer support single and multiframe writing?
single = classdict.get('singleframe', True)
multi = classdict.get('multiframe', False)
if single:
for f in fmt:
f = f.upper()
_SINGLEFRAME_WRITERS[f] = cls
if multi:
for f in fmt:
f = f.upper()
_MULTIFRAME_WRITERS[f] = cls
[docs]class WriterBase(six.with_metaclass(_Writermeta, IOBase)):
"""Base class for trajectory writers.
See Trajectory API definition in :mod:`MDAnalysis.coordinates.__init__` for
the required attributes and methods.
.. deprecated:: 1.0.0
:func:`write_next_timestep` has been deprecated, please use
:func:`write` instead.
"""
[docs] def convert_dimensions_to_unitcell(self, ts, inplace=True):
"""Read dimensions from timestep *ts* and return appropriate unitcell.
The default is to return ``[A,B,C,alpha,beta,gamma]``; if this
is not appropriate then this method has to be overriden.
"""
# override if the native trajectory format does NOT use
# [A,B,C,alpha,beta,gamma]
lengths, angles = ts.dimensions[:3], ts.dimensions[3:]
if not inplace:
lengths = lengths.copy()
lengths = self.convert_pos_to_native(lengths)
return np.concatenate([lengths, angles])
[docs] def write(self, obj):
"""Write current timestep, using the supplied `obj`.
Parameters
----------
obj : :class:`~MDAnalysis.core.groups.AtomGroup` or :class:`~MDAnalysis.core.universe.Universe`
write coordinate information associate with `obj`
Note
----
The size of the `obj` must be the same as the number of atoms provided
when setting up the trajectory.
.. deprecated:: 1.0.0
Deprecated the use of Timestep as arguments to write. Use either
an AtomGroup or Universe. To be removed in version 2.0.
"""
if isinstance(obj, Timestep):
warnings.warn(
'Passing a Timestep to write is deprecated, '
'and will be removed in 2.0; '
'use either an AtomGroup or Universe',
DeprecationWarning)
return self._write_next_frame(obj)
[docs] def write_next_timestep(self, obj):
"""Write current timestep, using the supplied ``obj``.
Parameters
----------
obj : :class:`~MDAnalysis.core.groups.AtomGroup` or :class:`~MDAnalysis.core.universe.Universe`
write coordinate information associated with ``obj``
.. deprecated:: 1.0.0
Deprecated, use write() instead
"""
warnings.warn(
'Writer.write_next_timestep is deprecated, '
'and will be removed in 2.0; '
'use Writer.write()',
DeprecationWarning)
return self.write(obj)
def __del__(self):
self.close()
def __repr__(self):
try:
return "< {0!s} {1!r} for {2:d} atoms >".format(self.__class__.__name__, self.filename, self.n_atoms)
except (TypeError, AttributeError):
# no trajectory loaded yet or a Writer that does not need e.g.
# self.n_atoms
return "< {0!s} {1!r} >".format(self.__class__.__name__, self.filename)
[docs] def has_valid_coordinates(self, criteria, x):
"""Returns ``True`` if all values are within limit values of their formats.
Due to rounding, the test is asymmetric (and *min* is supposed to be negative):
min < x <= max
Parameters
----------
criteria : dict
dictionary containing the *max* and *min* values in native units
x : numpy.ndarray
``(x, y, z)`` coordinates of atoms selected to be written out
Returns
-------
bool
"""
x = np.ravel(x)
return np.all(criteria["min"] < x) and np.all(x <= criteria["max"])
[docs]class SingleFrameReaderBase(ProtoReader):
"""Base class for Readers that only have one frame.
To use this base class, define the method :meth:`_read_first_frame` to
read from file `self.filename`. This should populate the attribute
`self.ts` with a :class:`Timestep` object.
.. versionadded:: 0.10.0
.. versionchanged:: 0.11.0
Added attribute "_ts_kwargs" for subclasses
Keywords "dt" and "time_offset" read into _ts_kwargs
"""
_err = "{0} only contains a single frame"
def __init__(self, filename, convert_units=True, n_atoms=None, **kwargs):
super(SingleFrameReaderBase, self).__init__()
self.filename = filename
self.convert_units = convert_units
self.n_frames = 1
self.n_atom = n_atoms
ts_kwargs = {}
for att in ('dt', 'time_offset'):
try:
val = kwargs[att]
except KeyError:
pass
else:
ts_kwargs[att] = val
self._ts_kwargs = ts_kwargs
self._read_first_frame()
[docs] def copy(self):
"""Return independent copy of this Reader.
New Reader will have its own file handle and can seek/iterate
independently of the original.
Will also copy the current state of the Timestep held in
the original Reader
"""
new = self.__class__(self.filename,
n_atoms=self.n_atoms)
new.ts = self.ts.copy()
for auxname, auxread in self._auxs.items():
new.add_auxiliary(auxname, auxread.copy())
# since the transformations have already been applied to the frame
# simply copy the property
new.transformations = self.transformations
return new
def _read_first_frame(self): # pragma: no cover
# Override this in subclasses to create and fill a Timestep
pass
[docs] def rewind(self):
self._read_first_frame()
for auxname, auxread in self._auxs.items():
self.ts = auxread.update_ts(self.ts)
super(SingleFrameReaderBase, self)._apply_transformations(self.ts)
def _reopen(self):
pass
[docs] def next(self):
raise StopIteration(self._err.format(self.__class__.__name__))
def __iter__(self):
yield self.ts
return
def _read_frame(self, frame):
if frame != 0:
raise IndexError(self._err.format(self.__class__.__name__))
return self.ts
[docs] def close(self):
# all single frame readers should use context managers to access
# self.filename. Explicitly setting it to the null action in case
# the IOBase.close method is ever changed from that.
pass
def _apply_transformations(self, ts):
""" Applies the transformations to the timestep."""
# Overrides :meth:`~MDAnalysis.coordinates.base.ProtoReader.add_transformations`
# to avoid applying the same transformations multiple times on each frame
return ts
def range_length(start, stop, step):
if (step > 0 and start < stop):
# We go from a lesser number to a larger one.
return int(1 + (stop - 1 - start) // step)
elif (step < 0 and start > stop):
# We count backward from a larger number to a lesser one.
return int(1 + (start - 1 - stop) // (-step))
else:
# The range is empty.
return 0
class _Convertermeta(type):
# Auto register upon class creation
def __init__(cls, name, bases, classdict):
type.__init__(type, name, bases, classdict)
try:
fmt = asiterable(classdict['lib'])
except KeyError:
pass
else:
for f in fmt:
f = f.upper()
_CONVERTERS[f] = cls
[docs]class ConverterBase(six.with_metaclass(_Convertermeta, IOBase)):
"""Base class for converting to other libraries.
"""
def __repr__(self):
return "<{cls}>".format(cls=self.__class__.__name__)
def convert(self, obj):
raise NotImplementedError