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# 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
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# doi: 10.25080/majora-629e541a-00e
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# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
#
"""Hydrogen Bond Analysis --- :mod:`MDAnalysis.analysis.hydrogenbonds.hbond_analysis`
=====================================================================================
:Author: Paul Smith
:Year: 2019
:Copyright: GNU Public License v3
.. versionadded:: 1.0.0
This module provides methods to find and analyse hydrogen bonds in a Universe.
The :class:`HydrogenBondAnalysis` class is a new version of the original
:class:`MDAnalysis.analysis.hbonds.HydrogenBondAnalysis` class from the module
:mod:`MDAnalysis.analysis.hbonds.hbond_analysis`, which itself was modeled after the `VMD
HBONDS plugin`_.
.. _`VMD HBONDS plugin`: http://www.ks.uiuc.edu/Research/vmd/plugins/hbonds/
Input
------
Required:
- *universe* : an MDAnalysis Universe object
Options:
- *donors_sel* [None] : Atom selection for donors. If `None`, then will be identified via the topology.
- *hydrogens_sel* [None] : Atom selection for hydrogens. If `None`, then will be identified via charge and mass.
- *acceptors_sel* [None] : Atom selection for acceptors. If `None`, then will be identified via charge.
- *d_h_cutoff* (Å) [1.2] : Distance cutoff used for finding donor-hydrogen pairs
- *d_a_cutoff* (Å) [3.0] : Distance cutoff for hydrogen bonds. This cutoff refers to the D-A distance.
- *d_h_a_angle_cutoff* (degrees) [150] : D-H-A angle cutoff for hydrogen bonds.
- *update_selections* [True] : If true, will update atom selections at each frame.
Output
------
- *frame* : frame at which a hydrogen bond was found
- *donor id* : atom id of the hydrogen bond donor atom
- *hydrogen id* : atom id of the hydrogen bond hydrogen atom
- *acceptor id* : atom id of the hydrogen bond acceptor atom
- *distance* (Å): length of the hydrogen bond
- *angle* (degrees): angle of the hydrogen bond
Hydrogen bond data are returned in a :class:`numpy.ndarray` on a "one line, one observation" basis
and can be accessed via :attr:`HydrogenBondAnalysis.results.hbonds`::
results = [
[
<frame>,
<donor index (0-based)>,
<hydrogen index (0-based)>,
<acceptor index (0-based)>,
<distance>,
<angle>
],
...
]
Example use of :class:`HydrogenBondAnalysis`
--------------------------------------------
The simplest use case is to allow :class:`HydrogenBondAnalysis` to guess the acceptor and hydrogen atoms, and to
identify donor-hydrogen pairs via the bonding information in the topology::
import MDAnalysis
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import HydrogenBondAnalysis as HBA
u = MDAnalysis.Universe(psf, trajectory)
hbonds = HBA(universe=u)
hbonds.run()
It is also possible to specify which hydrogens and acceptors to use in the analysis. For example, to find all hydrogen
bonds in water::
import MDAnalysis
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import HydrogenBondAnalysis as HBA
u = MDAnalysis.Universe(psf, trajectory)
hbonds = HBA(universe=u, hydrogens_sel='resname TIP3 and name H1 H2', acceptors_sel='resname TIP3 and name OH2')
hbonds.run()
Alternatively, :attr:`hydrogens_sel` and :attr:`acceptors_sel` may be generated via the :attr:`guess_hydrogens` and
:attr:`guess_acceptors`. This selection strings may then be modified prior to calling :attr:`run`, or a subset of
the universe may be used to guess the atoms. For example, find hydrogens and acceptors belonging to a protein::
import MDAnalysis
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import HydrogenBondAnalysis as HBA
u = MDAnalysis.Universe(psf, trajectory)
hbonds = HBA(universe=u)
hbonds.hydrogens_sel = hbonds.guess_hydrogens("protein")
hbonds.acceptors_sel = hbonds.guess_acceptors("protein")
hbonds.run()
Slightly more complex selection strings are also possible. For example, to find hydrogen bonds involving a protein and
any water molecules within 10 Å of the protein (which may be useful for subsequently finding the lifetime of
protein-water hydrogen bonds or finding water-bridging hydrogen bond paths)::
import MDAnalysis
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import HydrogenBondAnalysis as HBA
u = MDAnalysis.Universe(psf, trajectory)
hbonds = HBA(universe=u)
protein_hydrogens_sel = hbonds.guess_hydrogens("protein")
protein_acceptors_sel = hbonds.guess_acceptors("protein")
water_hydrogens_sel = "resname TIP3 and name H1 H2"
water_acceptors_sel = "resname TIP3 and name OH2"
hbonds.hydrogens_sel = f"({protein_hydrogens_sel}) or ({water_hydrogens_sel} and around 10 not resname TIP3})"
hbonds.acceptors_sel = f"({protein_acceptors_sel}) or ({water_acceptors_sel} and around 10 not resname TIP3})"
hbonds.run()
To calculate the hydrogen bonds between different groups, for example a
protein and water, one can use the :attr:`between` keyword. The
following will find protein-water hydrogen bonds but not protein-protein
or water-water hydrogen bonds::
import MDAnalysis
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import (
HydrogenBondAnalysis as HBA)
u = MDAnalysis.Universe(psf, trajectory)
hbonds = HBA(
universe=u,
between=['resname TIP3', 'protein']
)
protein_hydrogens_sel = hbonds.guess_hydrogens("protein")
protein_acceptors_sel = hbonds.guess_acceptors("protein")
water_hydrogens_sel = "resname TIP3 and name H1 H2"
water_acceptors_sel = "resname TIP3 and name OH2"
hbonds.hydrogens_sel = f"({protein_hydrogens_sel}) or ({water_hydrogens_sel}"
hbonds.acceptors_sel = f"({protein_acceptors_sel}) or ({water_acceptors_sel}"
hbonds.run()
It is further possible to compute hydrogen bonds between several groups with
with use of :attr:`between`. If in the above example,
`between=[['resname TIP3', 'protein'], ['protein', 'protein']]`, all
protein-water and protein-protein hydrogen bonds will be found, but
no water-water hydrogen bonds.
In order to compute the hydrogen bond lifetime, after finding hydrogen bonds
one can use the :attr:`lifetime` function::
...
hbonds.run()
tau_timeseries, timeseries = hbonds.lifetime()
It is **highly recommended** that a topology with bond information is used to
generate the universe, e.g `PSF`, `TPR`, or `PRMTOP` files. This is the only
method by which it can be guaranteed that donor-hydrogen pairs are correctly
identified. However, if, for example, a `PDB` file is used instead, a
:attr:`donors_sel` may be provided along with a :attr:`hydrogens_sel` and the
donor-hydrogen pairs will be identified via a distance cutoff,
:attr:`d_h_cutoff`::
import MDAnalysis
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import (
HydrogenBondAnalysis as HBA)
u = MDAnalysis.Universe(pdb, trajectory)
hbonds = HBA(
universe=u,
donors_sel='resname TIP3 and name OH2',
hydrogens_sel='resname TIP3 and name H1 H2',
acceptors_sel='resname TIP3 and name OH2',
d_h_cutoff=1.2
)
hbonds.run()
The class and its methods
-------------------------
.. autoclass:: HydrogenBondAnalysis
:members:
.. attribute:: results.hbonds
A :class:`numpy.ndarray` which contains a list of all observed hydrogen
bond interactions. See `Output`_ for more information.
.. versionadded:: 2.0.0
.. attribute:: hbonds
Alias to the :attr:`results.hbonds` attribute.
.. deprecated:: 2.0.0
Will be removed in MDAnalysis 3.0.0. Please use
:attr:`results.hbonds` instead.
"""
import logging
import warnings
from collections.abc import Iterable
import numpy as np
from ..base import AnalysisBase, Results
from MDAnalysis.lib.distances import capped_distance, calc_angles
from MDAnalysis.lib.correlations import autocorrelation, correct_intermittency
from MDAnalysis.exceptions import NoDataError
from MDAnalysis.core.groups import AtomGroup
from ...due import due, Doi
due.cite(Doi("10.1039/C9CP01532A"),
description="Hydrogen bond analysis implementation",
path="MDAnalysis.analysis.hydrogenbonds.hbond_analysis",
cite_module=True)
del Doi
[docs]class HydrogenBondAnalysis(AnalysisBase):
"""
Perform an analysis of hydrogen bonds in a Universe.
"""
def __init__(self, universe,
donors_sel=None, hydrogens_sel=None, acceptors_sel=None,
between=None, d_h_cutoff=1.2,
d_a_cutoff=3.0, d_h_a_angle_cutoff=150,
update_selections=True):
"""Set up atom selections and geometric criteria for finding hydrogen
bonds in a Universe.
Parameters
----------
universe : Universe
MDAnalysis Universe object
donors_sel : str
Selection string for the hydrogen bond donor atoms. If the
universe topology contains bonding information, leave
:attr:`donors_sel` as `None` so that donor-hydrogen pairs can be
correctly identified.
hydrogens_sel : str
Selection string for the hydrogen bond hydrogen atoms. Leave as
`None` to guess which hydrogens to use in the analysis using
:attr:`guess_hydrogens`. If :attr:`hydrogens_sel` is left as
`None`, also leave :attr:`donors_sel` as None so that
donor-hydrogen pairs can be correctly identified.
acceptors_sel : str
Selection string for the hydrogen bond acceptor atoms. Leave as
`None` to guess which atoms to use in the analysis using
:attr:`guess_acceptors`
between : List (optional),
Specify two selection strings for non-updating atom groups between
which hydrogen bonds will be calculated. For example, if the donor
and acceptor selections include both protein and water, it is
possible to find only protein-water hydrogen bonds - and not
protein-protein or water-water - by specifying
between=["protein", "SOL"]`. If a two-dimensional list is
passed, hydrogen bonds between each pair will be found. For
example, between=[["protein", "SOL"], ["protein", "protein"]]`
will calculate all protein-water and protein-protein hydrogen
bonds but not water-water hydrogen bonds. If `None`, hydrogen
bonds between all donors and acceptors will be calculated.
d_h_cutoff : float (optional)
Distance cutoff used for finding donor-hydrogen pairs.
Only used to find donor-hydrogen pairs if the
universe topology does not contain bonding information
d_a_cutoff : float (optional)
Distance cutoff for hydrogen bonds. This cutoff refers to the D-A distance.
d_h_a_angle_cutoff : float (optional)
D-H-A angle cutoff for hydrogen bonds, in degrees.
update_selections : bool (optional)
Whether or not to update the acceptor, donor and hydrogen
lists at each frame.
Note
----
It is highly recommended that a universe topology with bond
information is used, as this is the only way that guarantees the
correct identification of donor-hydrogen pairs.
.. versionadded:: 2.0.0
Added `between` keyword
"""
self.u = universe
self._trajectory = self.u.trajectory
self.donors_sel = donors_sel
self.hydrogens_sel = hydrogens_sel
self.acceptors_sel = acceptors_sel
# If hydrogen bonding groups are selected, then generate
# corresponding atom groups
if between is not None:
if not isinstance(between, Iterable) or len(between) == 0:
raise ValueError("between must be a non-empty list/iterable")
if isinstance(between[0], str):
between = [between]
between_ags = []
for group1, group2 in between:
between_ags.append(
[
self.u.select_atoms(group1, updating=False),
self.u.select_atoms(group2, updating=False)
]
)
self.between_ags = between_ags
else:
self.between_ags = None
self.d_h_cutoff = d_h_cutoff
self.d_a_cutoff = d_a_cutoff
self.d_h_a_angle = d_h_a_angle_cutoff
self.update_selections = update_selections
self.results = Results()
self.results.hbonds = None
[docs] def guess_hydrogens(self,
select='all',
max_mass=1.1,
min_charge=0.3,
min_mass=0.9
):
"""Guesses which hydrogen atoms should be used in the analysis.
Parameters
----------
select: str (optional)
Selection string for atom group from which hydrogens will be identified.
max_mass: float (optional)
Maximum allowed mass of a hydrogen atom.
min_charge: float (optional)
Minimum allowed charge of a hydrogen atom.
Returns
-------
potential_hydrogens: str
String containing the :attr:`resname` and :attr:`name` of all hydrogen atoms potentially capable of forming
hydrogen bonds.
Notes
-----
This function makes use of atomic masses and atomic charges to identify which atoms are hydrogen atoms that are
capable of participating in hydrogen bonding. If an atom has a mass less than :attr:`max_mass` and an atomic
charge greater than :attr:`min_charge` then it is considered capable of participating in hydrogen bonds.
If :attr:`hydrogens_sel` is `None`, this function is called to guess the selection.
Alternatively, this function may be used to quickly generate a :class:`str` of potential hydrogen atoms involved
in hydrogen bonding. This str may then be modified before being used to set the attribute
:attr:`hydrogens_sel`.
"""
if min_mass > max_mass:
raise ValueError("min_mass is higher than (or equal to) max_mass")
ag = self.u.select_atoms(select)
hydrogens_ag = ag[
np.logical_and.reduce((
ag.masses < max_mass,
ag.charges > min_charge,
ag.masses > min_mass,
))
]
hydrogens_list = np.unique(
[
'(resname {} and name {})'.format(r, p) for r, p in zip(hydrogens_ag.resnames, hydrogens_ag.names)
]
)
return " or ".join(hydrogens_list)
[docs] def guess_donors(self, select='all', max_charge=-0.5):
"""Guesses which atoms could be considered donors in the analysis. Only use if the universe topology does not
contain bonding information, otherwise donor-hydrogen pairs may be incorrectly assigned.
Parameters
----------
select: str (optional)
Selection string for atom group from which donors will be identified.
max_charge: float (optional)
Maximum allowed charge of a donor atom.
Returns
-------
potential_donors: str
String containing the :attr:`resname` and :attr:`name` of all atoms that potentially capable of forming
hydrogen bonds.
Notes
-----
This function makes use of and atomic charges to identify which atoms could be considered donor atoms in the
hydrogen bond analysis. If an atom has an atomic charge less than :attr:`max_charge`, and it is within
:attr:`d_h_cutoff` of a hydrogen atom, then it is considered capable of participating in hydrogen bonds.
If :attr:`donors_sel` is `None`, and the universe topology does not have bonding information, this function is
called to guess the selection.
Alternatively, this function may be used to quickly generate a :class:`str` of potential donor atoms involved
in hydrogen bonding. This :class:`str` may then be modified before being used to set the attribute
:attr:`donors_sel`.
"""
# We need to know `hydrogens_sel` before we can find donors
# Use a new variable `hydrogens_sel` so that we do not set `self.hydrogens_sel` if it is currently `None`
if not self.hydrogens_sel:
hydrogens_sel = self.guess_hydrogens()
else:
hydrogens_sel = self.hydrogens_sel
hydrogens_ag = self.u.select_atoms(hydrogens_sel)
ag = hydrogens_ag.residues.atoms.select_atoms(
"({donors_sel}) and around {d_h_cutoff} {hydrogens_sel}".format(
donors_sel=select,
d_h_cutoff=self.d_h_cutoff,
hydrogens_sel=hydrogens_sel
)
)
donors_ag = ag[ag.charges < max_charge]
donors_list = np.unique(
[
'(resname {} and name {})'.format(r, p) for r, p in zip(donors_ag.resnames, donors_ag.names)
]
)
return " or ".join(donors_list)
[docs] def guess_acceptors(self, select='all', max_charge=-0.5):
"""Guesses which atoms could be considered acceptors in the analysis.
Parameters
----------
select: str (optional)
Selection string for atom group from which acceptors will be identified.
max_charge: float (optional)
Maximum allowed charge of an acceptor atom.
Returns
-------
potential_acceptors: str
String containing the :attr:`resname` and :attr:`name` of all atoms that potentially capable of forming
hydrogen bonds.
Notes
-----
This function makes use of and atomic charges to identify which atoms could be considered acceptor atoms in the
hydrogen bond analysis. If an atom has an atomic charge less than :attr:`max_charge` then it is considered
capable of participating in hydrogen bonds.
If :attr:`acceptors_sel` is `None`, this function is called to guess the selection.
Alternatively, this function may be used to quickly generate a :class:`str` of potential acceptor atoms involved
in hydrogen bonding. This :class:`str` may then be modified before being used to set the attribute
:attr:`acceptors_sel`.
"""
ag = self.u.select_atoms(select)
acceptors_ag = ag[ag.charges < max_charge]
acceptors_list = np.unique(
[
'(resname {} and name {})'.format(r, p) for r, p in zip(acceptors_ag.resnames, acceptors_ag.names)
]
)
return " or ".join(acceptors_list)
def _get_dh_pairs(self):
"""Finds donor-hydrogen pairs.
Returns
-------
donors, hydrogens: AtomGroup, AtomGroup
AtomGroups corresponding to all donors and all hydrogens. AtomGroups are ordered such that, if zipped, will
produce a list of donor-hydrogen pairs.
"""
# If donors_sel is not provided, use topology to find d-h pairs
if not self.donors_sel:
# We're using u._topology.bonds rather than u.bonds as it is a million times faster to access.
# This is because u.bonds also calculates properties of each bond (e.g bond length).
# See https://github.com/MDAnalysis/mdanalysis/issues/2396#issuecomment-596251787
if not (hasattr(self.u._topology, 'bonds') and len(self.u._topology.bonds.values) != 0):
raise NoDataError('Cannot assign donor-hydrogen pairs via topology as no bond information is present. '
'Please either: load a topology file with bond information; use the guess_bonds() '
'topology guesser; or set HydrogenBondAnalysis.donors_sel so that a distance cutoff '
'can be used.')
hydrogens = self.u.select_atoms(self.hydrogens_sel)
donors = sum(h.bonded_atoms[0] for h in hydrogens) if hydrogens \
else AtomGroup([], self.u)
# Otherwise, use d_h_cutoff as a cutoff distance
else:
hydrogens = self.u.select_atoms(self.hydrogens_sel)
donors = self.u.select_atoms(self.donors_sel)
donors_indices, hydrogen_indices = capped_distance(
donors.positions,
hydrogens.positions,
max_cutoff=self.d_h_cutoff,
box=self.u.dimensions,
return_distances=False
).T
donors = donors[donors_indices]
hydrogens = hydrogens[hydrogen_indices]
return donors, hydrogens
def _filter_atoms(self, donors, hydrogens, acceptors):
"""Filter donor, hydrogen and acceptor atoms to consider only hydrogen
bonds between two or more specified groups.
Groups are specified with the `between` keyword when creating the
HydrogenBondAnalysis object.
Returns
-------
donors, hydrogens, acceptors: Filtered AtomGroups
"""
mask = np.full(donors.n_atoms, fill_value=False)
for group1, group2 in self.between_ags:
# Find donors in G1 and acceptors in G2
mask[
np.logical_and(
np.in1d(donors.indices, group1.indices),
np.in1d(acceptors.indices, group2.indices)
)
] = True
# Find acceptors in G1 and donors in G2
mask[
np.logical_and(
np.in1d(acceptors.indices, group1.indices),
np.in1d(donors.indices, group2.indices)
)
] = True
return donors[mask], hydrogens[mask], acceptors[mask]
def _prepare(self):
self.results.hbonds = [[], [], [], [], [], []]
# Set atom selections if they have not been provided
if not self.acceptors_sel:
self.acceptors_sel = self.guess_acceptors()
if not self.hydrogens_sel:
self.hydrogens_sel = self.guess_hydrogens()
# Select atom groups
self._acceptors = self.u.select_atoms(self.acceptors_sel,
updating=self.update_selections)
self._donors, self._hydrogens = self._get_dh_pairs()
def _single_frame(self):
box = self._ts.dimensions
# Update donor-hydrogen pairs if necessary
if self.update_selections:
self._donors, self._hydrogens = self._get_dh_pairs()
# find D and A within cutoff distance of one another
# min_cutoff = 1.0 as an atom cannot form a hydrogen bond with itself
d_a_indices, d_a_distances = capped_distance(
self._donors.positions,
self._acceptors.positions,
max_cutoff=self.d_a_cutoff,
min_cutoff=1.0,
box=box,
return_distances=True,
)
# Remove D-A pairs more than d_a_cutoff away from one another
tmp_donors = self._donors[d_a_indices.T[0]]
tmp_hydrogens = self._hydrogens[d_a_indices.T[0]]
tmp_acceptors = self._acceptors[d_a_indices.T[1]]
# Remove donor-acceptor pairs between pairs of AtomGroups we are not
# interested in
if self.between_ags is not None:
tmp_donors, tmp_hydrogens, tmp_acceptors = \
self._filter_atoms(tmp_donors, tmp_hydrogens, tmp_acceptors)
# Find D-H-A angles greater than d_h_a_angle_cutoff
d_h_a_angles = np.rad2deg(
calc_angles(
tmp_donors.positions,
tmp_hydrogens.positions,
tmp_acceptors.positions,
box=box
)
)
hbond_indices = np.where(d_h_a_angles > self.d_h_a_angle)[0]
# Retrieve atoms, distances and angles of hydrogen bonds
hbond_donors = tmp_donors[hbond_indices]
hbond_hydrogens = tmp_hydrogens[hbond_indices]
hbond_acceptors = tmp_acceptors[hbond_indices]
hbond_distances = d_a_distances[hbond_indices]
hbond_angles = d_h_a_angles[hbond_indices]
# Store data on hydrogen bonds found at this frame
self.results.hbonds[0].extend(np.full_like(hbond_donors,
self._ts.frame))
self.results.hbonds[1].extend(hbond_donors.indices)
self.results.hbonds[2].extend(hbond_hydrogens.indices)
self.results.hbonds[3].extend(hbond_acceptors.indices)
self.results.hbonds[4].extend(hbond_distances)
self.results.hbonds[5].extend(hbond_angles)
def _conclude(self):
self.results.hbonds = np.asarray(self.results.hbonds).T
@property
def hbonds(self):
wmsg = ("The `hbonds` attribute was deprecated in MDAnalysis 2.0.0 "
"and will be removed in MDAnalysis 3.0.0. Please use "
"`results.hbonds` instead.")
warnings.warn(wmsg, DeprecationWarning)
return self.results.hbonds
[docs] def lifetime(self, tau_max=20, window_step=1, intermittency=0):
"""Computes and returns the time-autocorrelation
(HydrogenBondLifetimes) of hydrogen bonds.
Before calling this method, the hydrogen bonds must first be computed
with the `run()` function. The same `start`, `stop` and `step`
parameters used in finding hydrogen bonds will be used here for
calculating hydrogen bond lifetimes. That is, the same frames will be
used in the analysis.
Unique hydrogen bonds are identified using hydrogen-acceptor pairs.
This means an acceptor switching to a different hydrogen atom - with
the same donor - from one frame to the next is considered a different
hydrogen bond.
Please see :func:`MDAnalysis.lib.correlations.autocorrelation` and
:func:`MDAnalysis.lib.correlations.intermittency` functions for more
details.
Parameters
----------
window_step : int, optional
The number of frames between each t(0).
tau_max : int, optional
Hydrogen bond lifetime is calculated for frames in the range
1 <= `tau` <= `tau_max`
intermittency : int, optional
The maximum number of consecutive frames for which a bond can
disappear but be counted as present if it returns at the next
frame. An intermittency of `0` is equivalent to a continuous
autocorrelation, which does not allow for hydrogen bond
disappearance. For example, for `intermittency=2`, any given
hydrogen bond may disappear for up to two consecutive frames yet
be treated as being present at all frames. The default is
continuous (intermittency=0).
Returns
-------
tau_timeseries : np.array
tau from 1 to `tau_max`
timeseries : np.array
autcorrelation value for each value of `tau`
"""
if self.results.hbonds is None:
logging.error(
"Autocorrelation analysis of hydrogen bonds cannot be done"
"before the hydrogen bonds are found"
)
logging.error(
"Autocorrelation: Please use the .run() before calling this"
"function"
)
raise NoDataError(".hbonds attribute is None: use .run() first")
if self.step != 1:
logging.warning(
"Autocorrelation: Hydrogen bonds were computed with step > 1."
)
logging.warning(
"Autocorrelation: We recommend recomputing hydrogen bonds with"
" step = 1."
)
logging.warning(
"Autocorrelation: if you would like to allow bonds to break"
" and reform, please use 'intermittency'"
)
# Extract the hydrogen bonds IDs only in the format
# [set(superset(x1,x2), superset(x3,x4)), ..]
found_hydrogen_bonds = [set() for _ in self.frames]
for frame_index, frame in enumerate(self.frames):
for hbond in self.results.hbonds[self.results.hbonds[:, 0] == frame]:
found_hydrogen_bonds[frame_index].add(frozenset(hbond[2:4]))
intermittent_hbonds = correct_intermittency(
found_hydrogen_bonds,
intermittency=intermittency
)
tau_timeseries, timeseries, timeseries_data = autocorrelation(
intermittent_hbonds,
tau_max,
window_step=window_step
)
return np.vstack([tau_timeseries, timeseries])
[docs] def count_by_time(self):
"""Counts the number of hydrogen bonds per timestep.
Returns
-------
counts : numpy.ndarray
Contains the total number of hydrogen bonds found at each timestep.
Can be used along with :attr:`HydrogenBondAnalysis.times` to plot
the number of hydrogen bonds over time.
"""
indices, tmp_counts = np.unique(self.results.hbonds[:, 0], axis=0,
return_counts=True)
indices -= self.start
indices /= self.step
counts = np.zeros_like(self.frames)
counts[indices.astype(np.intp)] = tmp_counts
return counts
[docs] def count_by_type(self):
"""Counts the total number of each unique type of hydrogen bond.
Returns
-------
counts : numpy.ndarray
Each row of the array contains the donor resname, donor atom type, acceptor resname, acceptor atom type and
the total number of times the hydrogen bond was found.
Note
----
Unique hydrogen bonds are determined through a consideration of the resname and atom type of the donor and
acceptor atoms in a hydrogen bond.
"""
d = self.u.atoms[self.hbonds[:, 1].astype(np.intp)]
a = self.u.atoms[self.hbonds[:, 3].astype(np.intp)]
tmp_hbonds = np.array([d.resnames, d.types, a.resnames, a.types],
dtype=str).T
hbond_type, type_counts = np.unique(
tmp_hbonds, axis=0, return_counts=True)
hbond_type_list = []
for hb_type, hb_count in zip(hbond_type, type_counts):
hbond_type_list.append([":".join(hb_type[:2]),
":".join(hb_type[2:4]), hb_count])
return np.array(hbond_type_list)
[docs] def count_by_ids(self):
"""Counts the total number hydrogen bonds formed by unique combinations of donor, hydrogen and acceptor atoms.
Returns
-------
counts : numpy.ndarray
Each row of the array contains the donor atom id, hydrogen atom id, acceptor atom id and the total number
of times the hydrogen bond was observed. The array is sorted by frequency of occurrence.
Note
----
Unique hydrogen bonds are determined through a consideration of the hydrogen atom id and acceptor atom id
in a hydrogen bond.
"""
d = self.u.atoms[self.hbonds[:, 1].astype(np.intp)]
h = self.u.atoms[self.hbonds[:, 2].astype(np.intp)]
a = self.u.atoms[self.hbonds[:, 3].astype(np.intp)]
tmp_hbonds = np.array([d.ids, h.ids, a.ids]).T
hbond_ids, ids_counts = np.unique(tmp_hbonds, axis=0,
return_counts=True)
# Find unique hbonds and sort rows so that most frequent observed bonds are at the top of the array
unique_hbonds = np.concatenate((hbond_ids, ids_counts[:, None]),
axis=1)
unique_hbonds = unique_hbonds[unique_hbonds[:, 3].argsort()[::-1]]
return unique_hbonds