Source code for MDAnalysis.analysis.lineardensity
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# 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
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# 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
#
"""
Linear Density --- :mod:`MDAnalysis.analysis.lineardensity`
===========================================================
A tool to compute mass and charge density profiles along the three
cartesian axes [xyz] of the simulation cell. Works only for orthorombic,
fixed volume cells (thus for simulations in canonical NVT ensemble).
"""
import os.path as path
import numpy as np
import warnings
from MDAnalysis.analysis.base import AnalysisBase, Results
from MDAnalysis.units import constants
from MDAnalysis.lib.util import deprecate
# TODO: Remove in version 3.0.0
[docs]
class Results(Results):
"""From version 3.0.0 onwards, some entries in Results will be renamed. See
the docstring for LinearDensity for details. The Results class is defined
here to implement deprecation warnings for the user."""
_deprecation_dict = {"pos": "mass_density",
"pos_std": "mass_density_stddev",
"char": "charge_density",
"char_std": "charge_density_stddev"}
def _deprecation_warning(self, key):
warnings.warn(
f"`{key}` is deprecated and will be removed in version 3.0.0. "
f"Please use `{self._deprecation_dict[key]}` instead.",
DeprecationWarning)
def __getitem__(self, key):
if key in self._deprecation_dict.keys():
self._deprecation_warning(key)
return super(Results, self).__getitem__(self._deprecation_dict[key])
return super(Results, self).__getitem__(key)
def __getattr__(self, attr):
if attr in self._deprecation_dict.keys():
self._deprecation_warning(attr)
attr = self._deprecation_dict[attr]
return super(Results, self).__getattr__(attr)
[docs]
class LinearDensity(AnalysisBase):
r"""Linear density profile
Parameters
----------
select : AtomGroup
any atomgroup
grouping : str {'atoms', 'residues', 'segments', 'fragments'}
Density profiles will be computed either on the atom positions (in
the case of 'atoms') or on the center of mass of the specified
grouping unit ('residues', 'segments', or 'fragments').
binsize : float
Bin width in Angstrom used to build linear density
histograms. Defines the resolution of the resulting density
profile (smaller --> higher resolution)
verbose : bool, optional
Show detailed progress of the calculation if set to ``True``
Attributes
----------
results.x.dim : int
index of the [xyz] axes
results.x.mass_density : numpy.ndarray
mass density in :math:`g \cdot cm^{-3}` in [xyz] direction
results.x.mass_density_stddev : numpy.ndarray
standard deviation of the mass density in [xyz] direction
results.x.charge_density : numpy.ndarray
charge density in :math:`\mathrm{e} \cdot mol \cdot cm^{-3}` in
[xyz] direction
results.x.charge_density_stddev : numpy.ndarray
standard deviation of the charge density in [xyz] direction
results.x.pos: numpy.ndarray
Alias to the :attr:`results.x.mass_density` attribute.
.. deprecated:: 2.2.0
Will be removed in MDAnalysis 3.0.0. Please use
:attr:`results.x.mass_density` instead.
results.x.pos_std: numpy.ndarray
Alias to the :attr:`results.x.mass_density_stddev` attribute.
.. deprecated:: 2.2.0
Will be removed in MDAnalysis 3.0.0. Please use
:attr:`results.x.mass_density_stddev` instead.
results.x.char: numpy.ndarray
Alias to the :attr:`results.x.charge_density` attribute.
.. deprecated:: 2.2.0
Will be removed in MDAnalysis 3.0.0. Please use
:attr:`results.x.charge_density` instead.
results.x.char_std: numpy.ndarray
Alias to the :attr:`results.x.charge_density_stddev` attribute.
.. deprecated:: 2.2.0
Will be removed in MDAnalysis 3.0.0. Please use
:attr:`results.x.charge_density_stddev` instead.
results.x.slice_volume : float
volume of bin in [xyz] direction
results.x.hist_bin_edges : numpy.ndarray
edges of histogram bins for mass/charge densities, useful for, e.g.,
plotting of histogram data.
Note: These density units are likely to be changed in the future.
Example
-------
First create a :class:`LinearDensity` object by supplying a selection,
then use the :meth:`run` method. Finally access the results
stored in results, i.e. the mass density in the x direction.
.. code-block:: python
ldens = LinearDensity(selection)
ldens.run()
print(ldens.results.x.mass_density)
Alternatively, other types of grouping can be selected using the
``grouping`` keyword. For example to calculate the density based on
a grouping of the :class:`~MDAnalysis.core.groups.ResidueGroup`
of the input :class:`~MDAnalysis.core.groups.AtomGroup`.
.. code-block:: python
ldens = LinearDensity(selection, grouping='residues', binsize=1.0)
ldens.run()
.. versionadded:: 0.14.0
.. versionchanged:: 1.0.0
Support for the ``start``, ``stop``, and ``step`` keywords has been
removed. These should instead be passed to :meth:`LinearDensity.run`.
The ``save()`` method was also removed, you can use ``np.savetxt()`` or
``np.save()`` on the :attr:`LinearDensity.results` dictionary contents
instead.
.. versionchanged:: 1.0.0
Changed `selection` keyword to `select`
.. versionchanged:: 2.0.0
Results are now instances of
:class:`~MDAnalysis.core.analysis.Results` allowing access
via key and attribute.
.. versionchanged:: 2.2.0
* Fixed a bug that caused LinearDensity to fail if grouping="residues"
or grouping="segments" were set.
* Residues, segments, and fragments will be analysed based on their
centre of mass, not centre of geometry as previously stated.
* LinearDensity now works with updating atom groups.
* Added new result container :attr:`results.x.hist_bin_edges`.
It contains the bin edges of the histrogram bins for calculated
densities and can be used for easier plotting of histogram data.
.. deprecated:: 2.2.0
The `results` dictionary has been changed and the attributes
:attr:`results.x.pos`, :attr:`results.x.pos_std`, :attr:`results.x.char`
and :attr:`results.x.char_std` are now deprecated. They will be removed
in 3.0.0. Please use :attr:`results.x.mass_density`,
:attr:`results.x.mass_density_stddev`, :attr:`results.x.charge_density`,
and :attr:`results.x.charge_density_stddev` instead.
"""
def __init__(self, select, grouping='atoms', binsize=0.25, **kwargs):
super(LinearDensity, self).__init__(select.universe.trajectory,
**kwargs)
# allows use of run(parallel=True)
self._ags = [select]
self._universe = select.universe
self.binsize = binsize
# group of atoms on which to compute the COM (same as used in
# AtomGroup.wrap())
self.grouping = grouping
# Initiate result instances
self.results["x"] = Results(dim=0)
self.results["y"] = Results(dim=1)
self.results["z"] = Results(dim=2)
# Box sides
self.dimensions = self._universe.dimensions[:3]
self.volume = np.prod(self.dimensions)
# number of bins
bins = (self.dimensions // self.binsize).astype(int)
# Here we choose a number of bins of the largest cell side so that
# x, y and z values can use the same "coord" column in the output file
self.nbins = bins.max()
slices_vol = self.volume / bins
self.keys = ['mass_density', 'mass_density_stddev',
'charge_density', 'charge_density_stddev']
# Initialize results array with zeros
for dim in self.results:
idx = self.results[dim]['dim']
self.results[dim]['slice_volume'] = slices_vol[idx]
for key in self.keys:
self.results[dim][key] = np.zeros(self.nbins)
# Variables later defined in _single_frame() method
self.masses = None
self.charges = None
self.totalmass = None
def _single_frame(self):
# Get masses and charges for the selection
if self.grouping == "atoms":
self.masses = self._ags[0].masses
self.charges = self._ags[0].charges
elif self.grouping in ["residues", "segments", "fragments"]:
self.masses = self._ags[0].total_mass(compound=self.grouping)
self.charges = self._ags[0].total_charge(compound=self.grouping)
else:
raise AttributeError(
f"{self.grouping} is not a valid value for grouping.")
self.totalmass = np.sum(self.masses)
self.group = getattr(self._ags[0], self.grouping)
self._ags[0].wrap(compound=self.grouping)
# Find position of atom/group of atoms
if self.grouping == 'atoms':
positions = self._ags[0].positions # faster for atoms
else:
# Centre of mass for residues, segments, fragments
positions = self._ags[0].center_of_mass(compound=self.grouping)
for dim in ['x', 'y', 'z']:
idx = self.results[dim]['dim']
key = 'mass_density'
key_std = 'mass_density_stddev'
# histogram for positions weighted on masses
hist, _ = np.histogram(positions[:, idx],
weights=self.masses,
bins=self.nbins,
range=(0.0, max(self.dimensions)))
self.results[dim][key] += hist
self.results[dim][key_std] += np.square(hist)
key = 'charge_density'
key_std = 'charge_density_stddev'
# histogram for positions weighted on charges
hist, bin_edges = np.histogram(positions[:, idx],
weights=self.charges,
bins=self.nbins,
range=(0.0, max(self.dimensions)))
self.results[dim][key] += hist
self.results[dim][key_std] += np.square(hist)
self.results[dim]['hist_bin_edges'] = bin_edges
def _conclude(self):
avogadro = constants["N_Avogadro"] # unit: mol^{-1}
volume_conversion = 1e-24 # unit: A^3/cm^3
# divide result values by avodagro and convert from A3 to cm3
k = avogadro * volume_conversion
# Average results over the number of configurations
for dim in ['x', 'y', 'z']:
for key in ['mass_density', 'mass_density_stddev',
'charge_density', 'charge_density_stddev']:
self.results[dim][key] /= self.n_frames
# Compute standard deviation for the error
# For certain tests in testsuite, floating point imprecision
# can lead to negative radicands of tiny magnitude (yielding nan).
# radicand_mass and radicand_charge are therefore calculated first
# and negative values set to 0 before the square root
# is calculated.
radicand_mass = self.results[dim]['mass_density_stddev'] - \
np.square(self.results[dim]['mass_density'])
radicand_mass[radicand_mass < 0] = 0
self.results[dim]['mass_density_stddev'] = np.sqrt(radicand_mass)
radicand_charge = self.results[dim]['charge_density_stddev'] - \
np.square(self.results[dim]['charge_density'])
radicand_charge[radicand_charge < 0] = 0
self.results[dim]['charge_density_stddev'] = \
np.sqrt(radicand_charge)
for dim in ['x', 'y', 'z']:
# norming factor, units of mol^-1 cm^3
norm = k * self.results[dim]['slice_volume']
for key in self.keys:
self.results[dim][key] /= norm
# TODO: Remove in 3.0.0
@deprecate(release="2.2.0", remove="3.0.0",
message="It will be replaced by a :meth:`_reduce` "
"method in the future")
def _add_other_results(self, other):
"""For parallel analysis"""
for dim in ['x', 'y', 'z']:
for key in self.keys:
self.results[dim][key] += other.results[dim][key]