def refTop():
return topology.Topology(
3, 2, 2,
attrs = [
ta.Atomnames(TA_FILLER[object]),
ta.Masses(TA_FILLER[float]),
ta.Resids(TA_FILLER[int]),
ta.Bonds(TA_FILLER['bond']),
],
atom_resindex=np.array([0, 0, 1]),
residue_segindex=np.array([0, 1])
)
def make_masses(size):
"""Atom masses (5.1, 4.2, 3.3, 1.5, 0.5) repeated"""
import MDAnalysis.core.topologyattrs as ta
na, nr, ns = size
masses = itertools.cycle([5.1, 4.2, 3.3, 1.5, 0.5])
return ta.Masses(np.array([next(masses) for _ in range(na)]))
def _apply_map(self, mapping):
"""Apply the mapping scheme to the beads.
Parameters
----------
mapping : dict
Mapping definitions per bead/
Returns
-------
:class:`~MDAnalysis.core.topology.Topology` defining the new universe.
"""
# Allocate arrays
_beads = []
atomnames = []
atomids = []
resids = []
resnames = []
segids = []
charges = []
masses = []
residues = self.atu.atoms.split("residue")
select_residues = enumerate(
itertools.product(residues, viewitems(mapping)))
for i, (res, (name, selection)) in select_residues:
if name != "CB":
bead = res.select_atoms(selection)
else:
bead = res.select_atoms(
selection.get(res.resname[0],
"hsidechain and not name H*"))
if bead:
_beads.append(bead)
atomnames.append(name)
atomids.append(i)
resids.append(bead.resids[0])
resnames.append(bead.resnames[0])
segids.append(bead.segids[0].split("_")[-1])
try:
charges.append(bead.total_charge())
except AttributeError:
charges.append(0.)
masses.append(bead.total_mass())
_beads = np.array(_beads)
n_atoms = len(_beads)
# Atom
# _beads = topattrs._Beads(_beads)
vdwradii = np.zeros_like(atomids)
vdwradii = topologyattrs.Radii(vdwradii)
atomids = topologyattrs.Atomids(np.asarray(atomids))
atomnames = topologyattrs.Atomnames(
np.asarray(atomnames, dtype=np.object))
atomtypes = topologyattrs.Atomtypes(
np.asarray(np.arange(n_atoms) + 100))
charges = topologyattrs.Charges(np.asarray(charges))
masses = topologyattrs.Masses(np.asarray(masses))
# Residue
# resids, resnames
segids = np.asarray(segids, dtype=np.object)
resids = np.asarray(resids)
resnames = np.asarray(resnames, dtype=np.object)
residx, (new_resids, new_resnames, new_segids) = topbase.change_squash(
(resids, ), (resids, resnames, segids))
# transform from atom:Rid to atom:Rix
residueids = topologyattrs.Resids(new_resids)
residuenums = topologyattrs.Resnums(new_resids.copy())
residuenames = topologyattrs.Resnames(new_resnames)
# Segment
segidx, (perseg_segids, ) = topbase.change_squash((new_segids, ),
(new_segids, ))
segids = topologyattrs.Segids(perseg_segids)
# Setup topology
top = topology.Topology(len(atomids),
len(new_resids),
len(segids),
attrs=[
atomids, atomnames, atomtypes, charges,
masses, vdwradii, residueids, residuenums,
residuenames, segids
],
atom_resindex=residx,
residue_segindex=segidx)
return top
def __new__(cls,
have_bonds=True,
have_masses=True,
have_molnums=True,
have_charges=True,
is_triclinic=False):
# box:
a = 10.0 # edge length
tfac = 0.1 # factor for box vector shift of triclinic boxes (~84°)
if is_triclinic:
box = triclinic_box([a, 0.0, 0.0], [a * tfac, a, 0.0],
[a * tfac, a * tfac, a])
else:
box = np.array([a, a, a, 90.0, 90.0, 90.0], dtype=np.float32)
# number of atoms, residues, and segments:
n_atoms = 47
n_residues = 15
n_segments = 6
# resindices:
residx = np.empty(n_atoms, dtype=np.int64)
# type A
rix = 0
for i in range(0, 3, 1):
residx[i] = rix
rix += 1
# type B
for i in range(3, 15, 3):
residx[i:i + 3] = rix
rix += 1
# type C & D
for i in range(15, 47, 4):
residx[i:i + 4] = rix
rix += 1
# segindices:
segidx = np.empty(n_residues, dtype=np.int64)
segidx[0:3] = 0
segidx[3:7] = 1
segidx[7:9] = 2
segidx[9:11] = 3
segidx[11:13] = 4
segidx[13:15] = 5
# universe:
u = mda.Universe.empty(
# topology things
n_atoms=n_atoms,
n_residues=n_residues,
n_segments=n_segments,
atom_resindex=residx,
residue_segindex=segidx,
# trajectory things
trajectory=True,
velocities=False,
forces=False,
)
# resnames: we always want those for selection purposes
resnames = ['A'] * 3
resnames += ['B'] * 4
resnames += ['C'] * 2
resnames += ['D1', 'D2'] * 3
u.add_TopologyAttr(topologyattrs.Resnames(resnames))
# moltypes: we always want those for selection purposes
moltypes = ['A'] * 3
moltypes += ['B'] * 4
moltypes += ['C'] * 2
moltypes += ['D'] * 6
u.add_TopologyAttr(topologyattrs.Moltypes(moltypes))
# trajectory:
ts = u.trajectory.ts
ts.frame = 0
ts.dimensions = box
# positions:
relpos = np.empty((n_atoms, 3), dtype=np.float32)
# type A
relpos[0:3, :] = np.array(
[[0.5, 0.5, 0.5], [1.4, 0.5, 0.5], [2.1, 0.5, 0.5]],
dtype=np.float32)
# type B
relpos[3:15, :] = np.array(
[[0.1, 0.1, 0.2], [0.1, 0.1, 0.1], [0.2, 0.1, 0.1],
[-0.05, 0.2, 0.05], [0.05, 0.2, 0.05], [0.05, 0.2, 0.95],
[-0.2, -0.9, 1.05], [-0.2, 0.1, -0.05], [-0.1, 0.1, -0.05],
[0.95, 0.2, 0.25], [0.95, 0.2, 0.15], [1.05, 0.2, 0.15]],
dtype=np.float32)
# type C
relpos[15:23, :] = np.array(
[[0.4, 0.95, 1.05], [0.4, 0.95, 0.95], [0.4, 0.05, 0.95],
[0.4, 0.05, 1.05], [0.6, 0.05, 0.25], [0.6, 0.05, 0.15],
[0.6, 0.15, 0.15], [0.6, 0.15, 0.25]],
dtype=np.float32)
# type D
relpos[23:47, :] = np.array(
[[0.2, 0.7, 0.8], [0.3, 0.7, 0.8], [0.4, 0.7, 0.8],
[0.5, 0.7, 0.8], [0.6, 0.7, 0.8], [0.7, 0.7, 0.8],
[0.8, 0.7, 0.8], [0.9, 0.7, 0.8], [0.66, 0.75, 0.7],
[0.76, 0.75, 0.7], [0.86, 0.75, 0.7], [0.96, 0.75, 0.7],
[0.06, 0.75, 0.7], [0.16, 0.75, 0.7], [0.26, 0.75, 0.7],
[0.36, 0.75, 0.7], [1.14, 0.65, -0.4], [1.04, 0.65, -0.4],
[0.94, 0.65, -0.4], [0.84, 0.65, -0.4], [0.74, 0.65, -0.4],
[0.64, 0.65, -0.4], [0.54, 0.65, -0.4], [0.44, 0.65, -0.4]],
dtype=np.float32)
# make a copy, we need the original later
_relpos = relpos.copy()
# apply y- and z-dependent shift of x and y coords for triclinic boxes:
if is_triclinic:
# x-coord shift depends on y- and z-coords
_relpos[:, 0] += tfac * _relpos[:, 1:].sum(axis=1)
# y-coord shift depends on z-coords only
_relpos[:, 1] += tfac * _relpos[:, 2]
# scale relative to absolute positions:
ts.positions = (_relpos * np.array([a, a, a])).astype(np.float32)
# bonds:
if have_bonds:
bonds = []
# type A has no bonds
#type B
for base in range(3, 15, 3):
for i in range(2):
bonds.append((base + i, base + i + 1))
# type C
for base in range(15, 23, 4):
for i in range(3):
bonds.append((base + i, base + i + 1))
bonds.append((0 + base, 3 + base))
# type D
for base in range(23, 47, 8):
for i in range(7):
bonds.append((base + i, base + i + 1))
u.add_TopologyAttr(topologyattrs.Bonds(bonds))
# masses:
if have_masses:
# masses are all set to 1 so that one can cross-check the results of
# reference='com' with reference='cog' unwrapping
masses = np.ones(n_atoms)
u.add_TopologyAttr(topologyattrs.Masses(masses))
# molnums:
if have_molnums:
molnums = [0, 1, 2]
molnums += [3, 4, 5, 6]
molnums += [7, 8]
molnums += [9, 9, 10, 10, 11, 11]
u.add_TopologyAttr(topologyattrs.Molnums(molnums))
# charges:
if have_charges:
# type A
charges = [2] * 3
# type B
charges += [-0.5] * 12
# type C
charges += [-1.5] * 8
# type C
charges += [0.5] * 24
u.add_TopologyAttr(topologyattrs.Charges(charges))
# shamelessly monkey-patch some custom universe attributes:
u._is_triclinic = is_triclinic
u._relpos = relpos
u._tfac = tfac
u._box_edge = a
# bind custom methods to universe:
u.unwrapped_coords = cls.unwrapped_coords.__get__(u)
u.wrapped_coords = cls.wrapped_coords.__get__(u)
u.center = cls.center.__get__(u)
return u