Source code for MDAnalysis.topology.base

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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
# 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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# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
Base topology reader classes --- :mod:`MDAnalysis.topology.base`

Derive topology reader classes from the base class in this module. All
topology readers raise :exc:`IOError` upon failing to read a topology
file and :exc:`ValueError` upon failing to make sense of the read data.


.. autoclass:: TopologyReaderBase

from __future__ import absolute_import
import six
from six.moves import zip
# While reduce is a built-in in python 2, it is not in python 3
from functools import reduce

import itertools
import numpy as np
import warnings

from .. import _PARSERS, _PARSER_HINTS
from ..coordinates.base import IOBase
from ..lib import util

class _Topologymeta(type):
    """Internal: Topology Parser registration voodoo

    When classes which inherit from TopologyReaderBase are *defined*
    this metaclass makes it known to MDAnalysis.  The optional `format`
    attribute and `_format_hint` staticmethod are read:
     - `format` defines the file extension this Parser targets.
     - `_format_hint` defines a function which returns a boolean if the
       Parser can process a particular object


      class ThingParser(TopologyReaderBase):
          format = ['foo', 'bar']

                  import WeirdPackage
              except ImportError:
                  return False
              return isinstance(thing, WeirdPackage.Thing)

    This way there is no strict dependency on "WeirdPackage", but if
    a user supplies a WeirdPackage.Thing the "ThingParser' will be able
    to step up and read it.

    .. versionchanged:: 1.0.0
       Added format_hint functionality
    def __init__(cls, name, bases, classdict):
        type.__init__(type, name, bases, classdict)
            fmt = util.asiterable(classdict['format'])
        except KeyError:
            for fmt_name in fmt:
                fmt_name = fmt_name.upper()
                _PARSERS[fmt_name] = cls

                if '_format_hint' in classdict:
                    _PARSER_HINTS[fmt_name] = classdict['_format_hint'].__func__

[docs]class TopologyReaderBase(six.with_metaclass(_Topologymeta, IOBase)): """Base class for topology readers Parameters ---------- filename : str name of the topology file universe : Universe, optional Supply a Universe to the Parser. This then passes it to the atom instances that are created within parsers. All topology readers must define a `parse` method which returns a Topology object Raises ------ * :exc:`IOError` upon failing to read a topology file * :exc:`ValueError` upon failing to make sense of the read data .. versionadded:: 0.9.0 .. versionchanged:: 0.9.2 Added keyword 'universe' to pass to Atom creation. """ def __init__(self, filename): self.filename = filename def parse(self, **kwargs): # pragma: no cover raise NotImplementedError("Override this in each subclass")
def squash_by(child_parent_ids, *attributes): """Squash a child-parent relationship Arguments --------- child_parent_ids - array of ids (unique values that identify the parent) *attributes - other arrays that need to follow the sorting of ids Returns ------- child_parents_idx - an array of len(child) which points to the index of parent parent_ids - len(parent) of the ids *parent_attrs - len(parent) of the other attributes """ unique_resids, sort_mask, atom_idx = np.unique( child_parent_ids, return_index=True, return_inverse=True) return atom_idx, unique_resids, [attr[sort_mask] for attr in attributes] def change_squash(criteria, to_squash): """Squash per atom data to per residue according to changes in resid Parameters ---------- criteria : list of numpy ndarray Arrays which when changing indicate a new residue to_squash : list of numpy arrays Arrays which get squashed according to the criteria arrays Returns ------- residx : numpy array The Residue *index* that each Atom gets assigned to. [len(resids)] squashed : numpy array The to_squash arrays reduced down to per Residue values Example ------- resids = np.array([2, 2, 3, 3, 2, 2]) resnames = np.array(['RsA', 'RsA', 'RsB', 'RsB', 'RsC', 'RsC']) segids = np.array(['A', 'A', 'A', 'A', 'B', 'B']) residx, (new_resids, new_resnames, new_segids) = resid_change_squash( (resids,), (resids, resnames, segids)) # Per atom res index residx: [0, 0, 1, 1, 2, 2] # Per residue record of each attribute new_resids: [2, 3, 2] new_resnames: ['RsA', 'RsB', 'RsC'] new_segids: ['A', 'A', 'B'] """ def get_borders(*arrays): """Generator of indices to slice arrays when they change""" borders = np.nonzero(reduce(np.logical_or, (a[:-1] != a[1:] for a in arrays))) # Add Nones so we can slice from start to end return [None] + list(borders[0] + 1) + [None] l0 = len(criteria[0]) if not all(len(other) == l0 for other in itertools.chain(criteria[1:], to_squash)): raise ValueError("All arrays must be equally sized") # 1) Detect where resids change borders = get_borders(*criteria) # Number of groups = number of changes + 1 # 2 `None`s have been added, so -1 nres = len(borders) - 1 # 2) Allocate new arrays # Per atom record of what residue they belong to residx = np.zeros_like(criteria[0], # Per residue record of various attributes new_others = [np.zeros(nres, dtype=o.dtype) for o in to_squash] # 3) Slice through resids and others to find values for i, (x, y) in enumerate(zip(borders[:-1], borders[1:])): residx[x:y] = i # atoms between x & y are in the i'th residue for old, new in zip(to_squash, new_others): new[i] = old[x:y][0] # TODO: Check that x:y is the same # Should be the same for self consistency... return residx, new_others def reduce_singular(values): """Returns the value in an array of length 1, or the tuple of an array with a longer lengh. Parameters ---------- values: array-like Array to squash Returns ------- values: tuple or single value """ if len(values) == 1: return values[0] else: return tuple(values)