Source code for MDAnalysis.topology.DMSParser
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# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
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"""
DESRES Molecular Structure file format topology parser
======================================================
Classes to read a topology from a DESRES_ Molecular Structure file
format (DMS_) coordinate files (as used by the Desmond_ MD package).
.. _DESRES: http://www.deshawresearch.com
.. _Desmond: http://www.deshawresearch.com/resources_desmond.html
.. _DMS: http://www.deshawresearch.com/Desmond_Users_Guide-0.7.pdf
Classes
-------
.. autoclass:: DMSParser
:members:
:inherited-members:
"""
from __future__ import absolute_import
from six import raise_from
import numpy as np
import sqlite3
import os
from . import guessers
from .base import TopologyReaderBase, change_squash
from ..core.topology import Topology
from ..core.topologyattrs import (
Atomids,
Atomnames,
Bonds,
Charges,
ChainIDs,
Atomtypes,
Masses,
Resids,
Resnums,
Resnames,
Segids,
AtomAttr, # for custom Attributes
)
class Atomnums(AtomAttr):
"""The number for each Atom"""
attrname = 'atomnums'
singular = 'atomnum'
[docs]class DMSParser(TopologyReaderBase):
"""Read a topology from a DESRES_ Molecular Structure file.
Format (DMS_) coordinate files (as used by the Desmond_ MD package).
Reads the following attributes:
Atom:
- Atomids
- Atomnums
- Atomnames
- Masses
- Charges
- Chainids
Residue:
- Resnames
- Resids
Segment:
- Segids
Guesses the following attributes
- Atomtypes
.. _DESRES: http://www.deshawresearch.com
.. _Desmond: http://www.deshawresearch.com/resources_desmond.html
.. _DMS: http://www.deshawresearch.com/Desmond_Users_Guide-0.7.pdf
"""
format = 'DMS'
[docs] def parse(self, **kwargs):
"""Parse DMS file *filename* and return the Topology object"""
# Fix by SB: Needed because sqlite3.connect does not raise anything
# if file is not there
if not os.path.isfile(self.filename):
raise IOError("No such file: {0}".format(self.filename))
def dict_factory(cursor, row):
"""
Fetch SQL records as dictionaries, rather than the default tuples.
"""
d = {}
for idx, col in enumerate(cursor.description):
d[col[0]] = row[idx]
return d
attrs = {}
# Row factories for different data types
facs = {np.int32: lambda c, r: r[0],
np.float32: lambda c, r: r[0],
object: lambda c, r: str(r[0].strip())}
with sqlite3.connect(self.filename) as con:
# Selecting single column, so just strip tuple
for attrname, dt in [
('id', np.int32),
('anum', np.int32),
('mass', np.float32),
('charge', np.float32),
('name', object),
('resname', object),
('resid', np.int32),
('chain', object),
('segid', object),
]:
try:
cur = con.cursor()
cur.row_factory = facs[dt]
cur.execute('SELECT {} FROM particle'
''.format(attrname))
vals = cur.fetchall()
except sqlite3.DatabaseError:
raise_from(
IOError("Failed reading the atoms from DMS Database"),
None)
else:
attrs[attrname] = np.array(vals, dtype=dt)
try:
cur.row_factory = dict_factory
cur.execute('SELECT * FROM bond')
bonds = cur.fetchall()
except sqlite3.DatabaseError:
raise_from(
IOError("Failed reading the bonds from DMS Database"),
None)
else:
bondlist = []
bondorder = {}
for b in bonds:
desc = tuple(sorted([b['p0'], b['p1']]))
bondlist.append(desc)
bondorder[desc] = b['order']
attrs['bond'] = bondlist
attrs['bondorder'] = bondorder
atomtypes = guessers.guess_types(attrs['name'])
topattrs = []
# Bundle in Atom level objects
for attr, cls in [
('id', Atomids),
('anum', Atomnums),
('mass', Masses),
('charge', Charges),
('name', Atomnames),
('chain', ChainIDs),
]:
topattrs.append(cls(attrs[attr]))
topattrs.append(Atomtypes(atomtypes, guessed=True))
# Residues
atom_residx, (res_resids,
res_resnums,
res_resnames,
res_segids) = change_squash(
(attrs['resid'], attrs['resname'], attrs['segid']),
(attrs['resid'],
attrs['resid'].copy(),
attrs['resname'],
attrs['segid']),
)
n_residues = len(res_resids)
topattrs.append(Resids(res_resids))
topattrs.append(Resnums(res_resnums))
topattrs.append(Resnames(res_resnames))
if any(res_segids) and not any(val is None for val in res_segids):
res_segidx, (res_segids,) = change_squash((res_segids,),
(res_segids,))
uniq_seg = np.unique(res_segids)
idx2seg = {idx: res_segids[idx] for idx in res_segidx}
res_segids = uniq_seg
nidx = {segid: nidx for nidx, segid in enumerate(uniq_seg)}
res_segidx = np.array([nidx[idx2seg[idx]] for idx in res_segidx])
n_segments = len(res_segids)
topattrs.append(Segids(res_segids))
else:
n_segments = 1
topattrs.append(Segids(np.array(['SYSTEM'], dtype=object)))
res_segidx = None
topattrs.append(Bonds(attrs['bond']))
top = Topology(len(attrs['id']), n_residues, n_segments,
attrs=topattrs,
atom_resindex=atom_residx,
residue_segindex=res_segidx)
return top