Source code for MDAnalysis.analysis.rdf

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r"""Radial Distribution Functions --- :mod:`MDAnalysis.analysis.rdf`
====================================================================

This module contains two classes to calculate radial
`pair distribution functions`_ (`radial distribution functions`_ or "RDF").
The RDF :math:`g_{ab}(r)` between types of particles :math:`a` and :math:`b` is

.. _equation-gab:

.. math::

   g_{ab}(r) = (N_{a} N_{b})^{-1} \sum_{i=1}^{N_a} \sum_{j=1}^{N_b}
               \langle \delta(|\mathbf{r}_i - \mathbf{r}_j| - r) \rangle

which is normalized so that the RDF becomes 1 for large separations in a
homogenous system. The RDF effectively counts the average number of :math:`b`
neighbours in a shell at distance :math:`r` around a :math:`a` particle and
represents it as a density.

The radial cumulative distribution function is

.. math::

   G_{ab}(r) = \int_0^r \!\!dr' 4\pi r'^2 g_{ab}(r')

and the average number of :math:`b` particles within radius :math:`r`

.. _equation-countab:

.. math::

   N_{ab}(r) = \rho G_{ab}(r)

(with the appropriate density :math:`\rho`). The latter function can be used to
compute, for instance, coordination numbers such as the number of neighbors in
the first solvation shell :math:`N(r_1)` where :math:`r_1` is the position of
the first minimum in :math:`g(r)`.

We provide options for calculating the density of particle :math:`b`
in a shell at distance :math:`r` around a :math:`a` particle, which is

.. _equation-nab:

.. math::
   n_{ab}(r) = \rho g_{ab}(r)

.. _`pair distribution functions`:
   https://en.wikipedia.org/wiki/Pair_distribution_function
.. _`radial distribution functions`:
   https://en.wikipedia.org/wiki/Radial_distribution_function

.. Not Implemented yet:
.. - Structure factor?
.. - Coordination number
"""
import warnings
import numpy as np

from ..lib import distances
from .base import AnalysisBase


[docs] class InterRDF(AnalysisBase): r"""Radial distribution function :class:`InterRDF` is a tool to calculate average radial distribution functions between two groups of atoms. Suppose we have two AtomGroups ``A`` and ``B``. ``A`` contains atom ``A1``, ``A2``, and ``B`` contains ``B1``, ``B2``. Given ``A`` and ``B`` to :class:`InterRDF`, the output will be the average of RDFs between ``A1`` and ``B1``, ``A1`` and ``B2``, ``A2`` and ``B1``, ``A2`` and ``B2``. A typical application is to calculate the RDF of solvent with itself or with another solute. The :ref:`radial distribution function<equation-gab>` is calculated by histogramming distances between all particles in `g1` and `g2` while taking periodic boundary conditions into account via the minimum image convention. The `exclusion_block` keyword may be used to exclude a set of distances from the calculations. Results are available in the attributes :attr:`results.rdf` and :attr:`results.count`. Parameters ---------- g1 : AtomGroup First AtomGroup g2 : AtomGroup Second AtomGroup nbins : int Number of bins in the histogram range : tuple or list The size of the RDF norm : str, {'rdf', 'density', 'none'} For 'rdf' calculate :math:`g_{ab}(r)`. For 'density' the :ref:`single particle density<equation-nab>` :math:`n_{ab}(r)` is computed. 'none' computes the number of particles occurences in each spherical shell. .. versionadded:: 2.3.0 exclusion_block : tuple A tuple representing the tile to exclude from the distance array. exclude_same : str Will exclude pairs of atoms that share the same "residue", "segment", or "chain". Those are the only valid values. This is intended to remove atoms that are spatially correlated due to direct bonded connections. verbose : bool Show detailed progress of the calculation if set to `True` Attributes ---------- results.bins : numpy.ndarray :class:`numpy.ndarray` of the centers of the `nbins` histogram bins. .. versionadded:: 2.0.0 bins : numpy.ndarray Alias to the :attr:`results.bins` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.bins` instead. results.edges : numpy.ndarray :class:`numpy.ndarray` of the `nbins + 1` edges of the histogram bins. .. versionadded:: 2.0.0 edges : numpy.ndarray Alias to the :attr:`results.edges` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.edges` instead. results.rdf : numpy.ndarray :class:`numpy.ndarray` of the :ref:`radial distribution function<equation-gab>` values for the :attr:`results.bins`. .. versionadded:: 2.0.0 rdf : numpy.ndarray Alias to the :attr:`results.rdf` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.rdf` instead. results.count : numpy.ndarray :class:`numpy.ndarray` representing the radial histogram, i.e., the raw counts, for all :attr:`results.bins`. .. versionadded:: 2.0.0 count : numpy.ndarray Alias to the :attr:`results.count` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.count` instead. Example ------- First create the :class:`InterRDF` object, by supplying two AtomGroups then use the :meth:`run` method :: rdf = InterRDF(ag1, ag2) rdf.run() Results are available through the :attr:`results.bins` and :attr:`results.rdf` attributes:: plt.plot(rdf.results.bins, rdf.results.rdf) The `exclusion_block` keyword allows the masking of pairs from within the same molecule. For example, if there are 7 of each atom in each molecule, the exclusion mask ``(7, 7)`` can be used. .. versionadded:: 0.13.0 .. versionchanged:: 1.0.0 Support for the `start`, `stop`, and `step` keywords has been removed. These should instead be passed to :meth:`InterRDF.run`. .. versionchanged:: 2.0.0 Store results as attributes `bins`, `edges`, `rdf` and `count` of the `results` attribute of :class:`~MDAnalysis.analysis.AnalysisBase`. """ def __init__(self, g1, g2, nbins=75, range=(0.0, 15.0), norm="rdf", exclusion_block=None, exclude_same=None, **kwargs): super(InterRDF, self).__init__(g1.universe.trajectory, **kwargs) self.g1 = g1 self.g2 = g2 self.norm = str(norm).lower() self.rdf_settings = {'bins': nbins, 'range': range} self._exclusion_block = exclusion_block if exclude_same is not None and exclude_same not in ['residue', 'segment', 'chain']: raise ValueError( "The exclude_same argument to InterRDF must be None, 'residue', 'segment' " "or 'chain'." ) if exclude_same is not None and exclusion_block is not None: raise ValueError( "The exclude_same argument to InterRDF cannot be used with exclusion_block." ) name_to_attr = {'residue': 'resindices', 'segment': 'segindices', 'chain': 'chainIDs'} self.exclude_same = name_to_attr.get(exclude_same) if self.norm not in ['rdf', 'density', 'none']: raise ValueError(f"'{self.norm}' is an invalid norm. " "Use 'rdf', 'density' or 'none'.") def _prepare(self): # Empty histogram to store the RDF count, edges = np.histogram([-1], **self.rdf_settings) count = count.astype(np.float64) count *= 0.0 self.results.count = count self.results.edges = edges self.results.bins = 0.5 * (edges[:-1] + edges[1:]) if self.norm == "rdf": # Cumulative volume for rdf normalization self.volume_cum = 0 # Set the max range to filter the search radius self._maxrange = self.rdf_settings['range'][1] def _single_frame(self): pairs, dist = distances.capped_distance(self.g1.positions, self.g2.positions, self._maxrange, box=self._ts.dimensions) # Maybe exclude same molecule distances if self._exclusion_block is not None: idxA = pairs[:, 0]//self._exclusion_block[0] idxB = pairs[:, 1]//self._exclusion_block[1] mask = np.where(idxA != idxB)[0] dist = dist[mask] if self.exclude_same is not None: # Ignore distances between atoms in the same attribute attr_ix_a = getattr(self.g1, self.exclude_same)[pairs[:, 0]] attr_ix_b = getattr(self.g2, self.exclude_same)[pairs[:, 1]] mask = np.where(attr_ix_a != attr_ix_b)[0] dist = dist[mask] count, _ = np.histogram(dist, **self.rdf_settings) self.results.count += count if self.norm == "rdf": self.volume_cum += self._ts.volume def _conclude(self): norm = self.n_frames if self.norm in ["rdf", "density"]: # Volume in each radial shell vols = np.power(self.results.edges, 3) norm *= 4/3 * np.pi * np.diff(vols) if self.norm == "rdf": # Number of each selection nA = len(self.g1) nB = len(self.g2) N = nA * nB # If we had exclusions, take these into account if self._exclusion_block: xA, xB = self._exclusion_block nblocks = nA / xA N -= xA * xB * nblocks # Average number density box_vol = self.volume_cum / self.n_frames norm *= N / box_vol self.results.rdf = self.results.count / norm @property def edges(self): wmsg = ("The `edges` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.bins` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.edges @property def count(self): wmsg = ("The `count` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.bins` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.count @property def bins(self): wmsg = ("The `bins` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.bins` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.bins @property def rdf(self): wmsg = ("The `rdf` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.rdf` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.rdf
[docs] class InterRDF_s(AnalysisBase): r"""Site-specific radial distribution function Calculates site-specific radial distribution functions. Instead of two groups of atoms it takes as input a list of pairs of AtomGroup, ``[[A, B], [C, D], ...]``. Given the same ``A`` and ``B`` to :class:`InterRDF_s`, the output will be a list of individual RDFs between ``A1`` and ``B1``, ``A1`` and ``B2``, ``A2`` and ``B1``, ``A2`` and ``B2`` (and similarly for ``C`` and ``D``). These site-specific radial distribution functions are typically calculated if one is interested in the solvation shells of a ligand in a binding site or the solvation of specific residues in a protein. Parameters ---------- u : Universe a Universe that contains atoms in `ags` .. deprecated:: 2.3.0 This parameter is superflous and will be removed in MDAnalysis 3.0.0. ags : list a list of pairs of :class:`~MDAnalysis.core.groups.AtomGroup` instances nbins : int Number of bins in the histogram range : tuple or list The size of the RDF norm : str, {'rdf', 'density', 'none'} For 'rdf' calculate :math:`g_{ab}(r)`. For 'density' the :ref:`single particle density<equation-nab>` :math:`n_{ab}(r)` is computed. 'none' computes the number of particles occurences in each spherical shell. .. versionadded:: 2.3.0 density : bool `False`: calculate :math:`g_{ab}(r)`; `True`: calculate the true :ref:`single particle density<equation-nab>` :math:`n_{ab}(r)`. `density` overwrites the `norm` parameter. .. versionadded:: 1.0.1 This keyword was available since 0.19.0 but was not documented. Furthermore, it had the opposite meaning. Since 1.0.1 it is officially supported as documented. .. deprecated:: 2.3.0 Instead of `density=True` use `norm='density'` Attributes ---------- results.bins : numpy.ndarray :class:`numpy.ndarray` of the centers of the `nbins` histogram bins; all individual site-specific RDFs have the same bins. .. versionadded:: 2.0.0 bins : numpy.ndarray Alias to the :attr:`results.bins` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.bins` instead. results.edges : numpy.ndarray array of the ``nbins + 1`` edges of the histogram bins; all individual site-specific RDFs have the same bins. .. versionadded:: 2.0.0 edges : numpy.ndarray Alias to the :attr:`results.edges` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.edges` instead. results.rdf : list :class:`list` of the site-specific :ref:`radial distribution functions<equation-gab>` if `norm='rdf'` or :ref:`density functions<equation-nab>` for the :attr:`bins` if `norm='density'`. The list contains ``len(ags)`` entries. Each entry for the ``i``-th pair `[A, B] = ags[i]` in `ags` is a :class:`numpy.ndarray` with shape ``(len(A), len(B))``, i.e., a stack of RDFs. For example, ``results.rdf[i][0, 2]`` is the RDF between atoms ``A[0]`` and ``B[2]``. .. versionadded:: 2.0.0 rdf : list Alias to the :attr:`results.rdf` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.rdf` instead. results.count : list :class:`list` of the site-specific radial histograms, i.e., the raw counts, for all :attr:`results.bins`. The data have the same structure as :attr:`results.rdf` except that the arrays contain the raw counts. .. versionadded:: 2.0.0 count : list Alias to the :attr:`results.count` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.count` instead. results.cdf : list :class:`list` of the site-specific :ref:`cumulative counts<equation-countab>`, for all :attr:`results.bins`. The data have the same structure as :attr:`results.rdf` except that the arrays contain the cumulative counts. This attribute only exists after :meth:`get_cdf` has been run. .. versionadded:: 2.0.0 cdf : list Alias to the :attr:`results.cdf` attribute. .. deprecated:: 2.0.0 This attribute will be removed in 3.0.0. Use :attr:`results.cdf` instead. Example ------- First create the :class:`InterRDF_s` object, by supplying one Universe and one list of pairs of AtomGroups, then use the :meth:`~InterRDF_s.run` method:: from MDAnalysisTests.datafiles import GRO_MEMPROT, XTC_MEMPROT u = mda.Universe(GRO_MEMPROT, XTC_MEMPROT) s1 = u.select_atoms('name ZND and resid 289') s2 = u.select_atoms('(name OD1 or name OD2) and resid 51 and sphzone 5.0 (resid 289)') s3 = u.select_atoms('name ZND and (resid 291 or resid 292)') s4 = u.select_atoms('(name OD1 or name OD2) and sphzone 5.0 (resid 291)') ags = [[s1, s2], [s3, s4]] rdf = InterRDF_s(u, ags) rdf.run() Results are available through the :attr:`results.bins` and :attr:`results.rdf` attributes:: plt.plot(rdf.results.bins, rdf.results.rdf[0][0, 0]) (Which plots the rdf between the first atom in ``s1`` and the first atom in ``s2``) To generate the *cumulative distribution function* (cdf) in the sense of "particles within radius :math:`r`", i.e., :math:`N_{ab}(r)`, use the :meth:`~InterRDF_s.get_cdf` method :: cdf = rdf.get_cdf() Results are available through the :attr:`results.cdf` attribute:: plt.plot(rdf.results.bins, rdf.results.cdf[0][0, 0]) (Which plots the cdf between the first atom in ``s1`` and the first atom in ``s2``) .. versionadded:: 0.19.0 .. versionchanged:: 1.0.0 Support for the `start`, `stop`, and `step` keywords has been removed. These should instead be passed to :meth:`InterRDF_s.run`. .. versionchanged:: 2.0.0 Store results as attributes `bins`, `edges`, `rdf`, `count` and `cdf` of the `results` attribute of :class:`~MDAnalysis.analysis.AnalysisBase`. .. versionchanged:: 2.3.0 Introduce `norm` and `exclusion_blocks` attributes. .. deprecated:: 2.3.0 Instead of `density=True` use `norm='density'` .. deprecated:: 2.3.0 The `universe` parameter is superflous. """ def __init__(self, u, ags, nbins=75, range=(0.0, 15.0), norm="rdf", density=False, **kwargs): super(InterRDF_s, self).__init__(ags[0][0].universe.trajectory, **kwargs) warnings.warn("The `u` attribute is superflous and will be removed " "in MDAnalysis 3.0.0.", DeprecationWarning) self.ags = ags self.norm = str(norm).lower() self.rdf_settings = {'bins': nbins, 'range': range} if self.norm not in ['rdf', 'density', 'none']: raise ValueError(f"'{self.norm}' is an invalid norm. " "Use 'rdf', 'density' or 'none'.") if density: warnings.warn("The `density` attribute was deprecated in " "MDAnalysis 2.3.0 and will be removed in " "MDAnalysis 3.0.0. Please use `norm=density` " "instead.", DeprecationWarning) self.norm = "density" def _prepare(self): count, edges = np.histogram([-1], **self.rdf_settings) self.results.count = [np.zeros((ag1.n_atoms, ag2.n_atoms, len(count)), dtype=np.float64) for ag1, ag2 in self.ags] self.results.edges = edges self.results.bins = 0.5 * (edges[:-1] + edges[1:]) if self.norm == "rdf": # Cumulative volume for rdf normalization self.volume_cum = 0 self._maxrange = self.rdf_settings['range'][1] def _single_frame(self): for i, (ag1, ag2) in enumerate(self.ags): pairs, dist = distances.capped_distance(ag1.positions, ag2.positions, self._maxrange, box=self._ts.dimensions) for j, (idx1, idx2) in enumerate(pairs): count, _ = np.histogram(dist[j], **self.rdf_settings) self.results.count[i][idx1, idx2, :] += count if self.norm == "rdf": self.volume_cum += self._ts.volume def _conclude(self): norm = self.n_frames if self.norm in ["rdf", "density"]: # Volume in each radial shell vols = np.power(self.results.edges, 3) norm *= 4/3 * np.pi * np.diff(vols) if self.norm == "rdf": # Average number density norm *= 1 / (self.volume_cum / self.n_frames) # Empty lists to restore indices, RDF self.results.indices = [] self.results.rdf = [] for i, (ag1, ag2) in enumerate(self.ags): # Number of each selection self.results.indices.append([ag1.indices, ag2.indices]) self.results.rdf.append(self.results.count[i] / norm)
[docs] def get_cdf(self): r"""Calculate the cumulative counts for all sites. This is the :ref:`cumulative count<equation-countab>` within a given radius, i.e., :math:`N_{ab}(r)`. The result is returned and also stored in the attribute :attr:`results.cdf`. Returns ------- cdf : list list of arrays with the same structure as :attr:`results.rdf` """ self.results.cdf = [] for count in self.results.count: self.results.cdf.append(np.cumsum(count, axis=2) / self.n_frames) return self.results.cdf
@property def edges(self): wmsg = ("The `edges` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.bins` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.edges @property def count(self): wmsg = ("The `count` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.bins` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.count @property def bins(self): wmsg = ("The `bins` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.bins` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.bins @property def rdf(self): wmsg = ("The `rdf` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.rdf` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.rdf @property def cdf(self): wmsg = ("The `cdf` attribute was deprecated in MDAnalysis 2.0.0 " "and will be removed in MDAnalysis 3.0.0. Please use " "`results.cdf` instead") warnings.warn(wmsg, DeprecationWarning) return self.results.cdf