class TorsionScanSet(Trajectory):
"""container object for torsion scan
A TorsionScanSet should be constructed by loading Gaussian 09 torsion scan log files from disk
with an mdtraj.Topology object
Examples
--------
>>> torsion_set = read_scan_logfile('FRG.scanN.dir.log')
>>> print torsion_set
<torsions.TorsionScanSet with 346 frames, 22 atoms, 1 residues, 4 unique torsions without MM Energy at 0x10b099b10>
Attributes
----------
structure: chemistry.Structure
qm_energy: simtk.unit.Quantity((n_frames), unit=kilojoule/mole)
mm_energy: simtk.unit.Quantity((n_frames), unit=kilojoule/mole)
delta_energy: simtk.unit.Quantity((n_frames), unit=kilojoule/mole)
torsion_index: {np.ndarray, shape(n_frames, 4)}
step: {np.ndarray, shape(n_frame, 3)}
direction: {np.ndarray, shape(n_frame)}. 0 = negative, 1 = positive
"""
def __init__(self, positions, topology, structure, torsions, directions, steps, qm_energies):
"""Create new TorsionScanSet object"""
assert isinstance(topology, object)
super(TorsionScanSet, self).__init__(positions, topology)
self.structure = structure
self.qm_energy = Quantity(value=qm_energies, unit=kilojoules_per_mole)
self.mm_energy = Quantity()
self.delta_energy = Quantity()
self.torsion_index = torsions
self.direction = directions
self.steps = steps
def to_dataframe(self):
""" convert TorsionScanSet to pandas dataframe """
data = []
for i in range(self.n_frames):
if len(self.mm_energy) == self.n_frames and len(self.delta_energy) == self.n_frames:
data.append(
(
self.torsion_index[i],
self.direction[i],
self.steps[i],
self.qm_energy[i],
self.mm_energy[i],
self.delta_energy[i],
)
)
else:
data.append(
(
self.torsion_index[i],
self.direction[i],
self.steps[i],
self.qm_energy[i],
float("nan"),
float("nan"),
)
)
torsion_set = pd.DataFrame(
data,
columns=[
"torsion",
"scan_direction",
"step_point_total",
"QM_energy KJ/mol",
"MM_energy KJ/mole",
"delta KJ/mole",
],
)
return torsion_set
def _string_summary_basic(self):
"""Basic summary of TorsionScanSet in string form."""
energy_str = "with MM Energy" if self._have_mm_energy else "without MM Energy"
value = "torsions.TorsionScanSet with %d frames, %d atoms, %d residues, %s" % (
self.n_frames,
self.n_atoms,
self.n_residues,
energy_str,
)
return value
def extract_geom_opt(self):
key = []
for i, step in enumerate(self.steps):
try:
if step[1] != self.steps[i + 1][1]:
key.append(i)
except IndexError:
key.append(i)
new_torsionScanSet = self.slice(key)
return new_torsionScanSet
def compute_energy(self, param, offset, platform=None):
""" Computes energy for a given structure with a given parameter set
Parameters
----------
param: chemistry.charmm.CharmmParameterSet
platform: simtk.openmm.Platform to evaluate energy on (if None, will select automatically)
"""
# Create Context.
integrator = mm.VerletIntegrator(0.004 * u.picoseconds)
system = self.structure.createSystem(param)
if platform != None:
context = mm.Context(system, integrator, platform)
else:
context = mm.Context(system, integrator)
# Compute potential energies for all snapshots.
self.mm_energy = Quantity(value=np.zeros([self.n_frames], np.float64), unit=kilojoules_per_mole)
for i in range(self.n_frames):
context.setPositions(self.openmm_positions(i))
state = context.getState(getEnergy=True)
self.mm_energy[i] = state.getPotentialEnergy()
# Subtract off minimum of mm_energy
self.mm_energy -= self.mm_energy.min() + Quantity(value=float(offset.value), unit=kilojoules_per_mole)
self.delta_energy = self.qm_energy - self.mm_energy
# Compute deviation between MM and QM energies with offset
# self.delta_energy = mm_energy - self.qm_energy + Quantity(value=offset, unit=kilojoule_per_mole)
# Clean up.
del context
del system
del integrator
# print('Heap at end of compute_energy'), hp.heeap()
@property
def _have_mm_energy(self):
return len(self.mm_energy) is not 0
# @property
# def _unique_torsions(self):
# Not returning the right amount. debug
# torsions = []
# for i in range(len(self.torsion_index)):
# try:
# if (self.torsion_index[i] != self.torsion_index[i+1]).all():
# torsions.append(self.torsion_index[i]), torsions.append(self.torsion_index[i+1])
# except:
# pass
# return len(torsions), torsions
def __getitem__(self, key):
"Get a slice of this trajectory"
return self.slice(key)
def slice(self, key, copy=True):
"""Slice trajectory, by extracting one or more frames into a separate object
This method can also be called using index bracket notation, i.e
`traj[1] == traj.slice(1)`
Parameters
----------
key : {int, np.ndarray, slice}
The slice to take. Can be either an int, a list of ints, or a slice
object.
copy : bool, default=True
Copy the arrays after slicing. If you set this to false, then if
you modify a slice, you'll modify the original array since they
point to the same data.
"""
xyz = self.xyz[key]
time = self.time[key]
torsions = self.torsion_index[key]
direction = self.direction[key]
steps = self.steps[key]
qm_energy = self.qm_energy[key]
unitcell_lengths, unitcell_angles = None, None
if self.unitcell_angles is not None:
unitcell_angles = self.unitcell_angles[key]
if self.unitcell_lengths is not None:
unitcell_lengths = self.unitcell_lengths[key]
if copy:
xyz = xyz.copy()
time = time.copy()
topology = deepcopy(self._topology)
structure = deepcopy(self.structure)
torsions = torsions.copy()
direction = direction.copy()
steps = steps.copy()
qm_energy = qm_energy.copy()
if self.unitcell_angles is not None:
unitcell_angles = unitcell_angles.copy()
if self.unitcell_lengths is not None:
unitcell_lengths = unitcell_lengths.copy()
newtraj = self.__class__(xyz, topology, structure, torsions, direction, steps, qm_energy)
if self._rmsd_traces is not None:
newtraj._rmsd_traces = np.array(self._rmsd_traces[key], ndmin=1, copy=True)
return newtraj
class TorsionScanSet(Trajectory):
"""container object for torsion scan
A TorsionScanSet should be constructed by loading Gaussian 09 torsion scan log files from disk
with an mdtraj.Topology object
Examples
--------
>>> torsion_set = read_scan_logfile('../examples/data/pyrrole/torsion-scan/PRL.scan2.neg.log', '../examples/data/pyrrole/pyrrol.psf')
>>> print(torsion_set)
<torsions.TorsionScanSet with 40 frames, 22 atoms, 1 residues, without MM Energy>
Attributes
----------
structure: ParmEd.Structure
qm_energy: simtk.unit.Quantity((n_frames), unit=kilojoule/mole)
mm_energy: simtk.unit.Quantity((n_frames), unit=kilojoule/mole)
delta_energy: simtk.unit.Quantity((n_frames), unit=kilojoule/mole)
torsion_index: {np.ndarray, shape(n_frames, 4)}
step: {np.ndarray, shape(n_frame, 3)}
direction: {np.ndarray, shape(n_frame)}. 0 = negative, 1 = positive
"""
def __init__(self, positions, topology, structure, torsions, directions, steps, qm_energies):
"""Create new TorsionScanSet object"""
assert isinstance(topology, object)
super(TorsionScanSet, self).__init__(positions, topology)
self.structure = structure
self.qm_energy = Quantity(value=qm_energies, unit=kilojoules_per_mole)
self.mm_energy = Quantity()
self.delta_energy = Quantity()
self.torsion_index = torsions
self.direction = directions
self.steps = steps
self.positions = positions
self.context = None
self.system = None
self.integrator = mm.VerletIntegrator(0.004*u.picoseconds)
self.energy = np.array
# Don't allow an empty TorsionScanSet to be created
if self.n_frames == 0:
msg = 'TorsionScanSet has no frames!\n'
msg += '\n'
msg += 'positions provided were:\n'
msg += str(positions)
raise Exception(msg)
def create_context(self, param, platform=None):
self.structure.load_parameters(param, copy_parameters=False)
self.system = self.structure.createSystem()
if platform != None:
self.context = mm.Context(self.system, self.integrator, platform)
else:
self.context = mm.Context(self.system, self.integrator)
def copy_torsions(self):
forces = {self.system.getForce(i).__class__.__name__: self.system.getForce(i)
for i in range(self.system.getNumForces())}
torsion_force = forces['PeriodicTorsionForce']
# create new force
new_torsion_force = self.structure.omm_dihedral_force()
# copy parameters
for i in range(new_torsion_force.getNumTorsions()):
torsion = new_torsion_force.getTorsionParameters(i)
torsion_force.setTorsionParameters(i, *torsion)
# update parameters in context
torsion_force.updateParametersInContext(self.context)
#clean up
del new_torsion_force
def to_dataframe(self):
""" convert TorsionScanSet to pandas dataframe """
data = []
for i in range(self.n_frames):
if len(self.mm_energy) == self.n_frames and len(self.delta_energy) == self.n_frames:
data.append((self.torsion_index[i], self.direction[i], self.steps[i], self.qm_energy[i], self.mm_energy[i],
self.delta_energy[i]))
else:
data.append((self.torsion_index[i], self.direction[i], self.steps[i], self.qm_energy[i], float('nan'), float('nan')))
torsion_set = pd.DataFrame(data, columns=[ "torsion", "scan_direction", "step_point_total", "QM_energy KJ/mol",
"MM_energy KJ/mole", "delta KJ/mole"])
return torsion_set
def _string_summary_basic(self):
"""Basic summary of TorsionScanSet in string form."""
energy_str = 'with MM Energy' if self._have_mm_energy else 'without MM Energy'
value = "torsions.TorsionScanSet with %d frames, %d atoms, %d residues, %s" % (
self.n_frames, self.n_atoms, self.n_residues, energy_str)
return value
def extract_geom_opt(self):
key = []
for i, step in enumerate(self.steps):
try:
if step[1] != self.steps[i+1][1]:
key.append(i)
except IndexError:
key.append(i)
new_torsionScanSet = self.slice(key)
return new_torsionScanSet
def compute_energy(self, param, offset, platform=None,):
""" Computes energy for a given structure with a given parameter set
Parameters
----------
param: parmed.charmm.CharmmParameterSet
platform: simtk.openmm.Platform to evaluate energy on (if None, will select automatically)
"""
if self.n_frames == 0:
raise Exception("self.n_frames = 0! There are no frames to compute energy for.")
# Check if context exists.
if not self.context:
self.create_context(param, platform)
else:
# copy new torsion parameters
self.copy_torsions()
# Compute potential energies for all snapshots.
self.mm_energy = Quantity(value=np.zeros([self.n_frames], np.float64), unit=kilojoules_per_mole)
for i in range(self.n_frames):
self.context.setPositions(self.positions[i])
state = self.context.getState(getEnergy=True)
self.mm_energy[i] = state.getPotentialEnergy()
# Subtract off minimum of mm_energy and add offset
min_energy = self.mm_energy.min()
self.mm_energy -= min_energy
self.mm_energy += offset
self.delta_energy = (self.qm_energy - self.mm_energy)
# Compute deviation between MM and QM energies with offset
#self.delta_energy = mm_energy - self.qm_energy + Quantity(value=offset, unit=kilojoule_per_mole)
@property
def _have_mm_energy(self):
return len(self.mm_energy) is not 0
# @property
# def _unique_torsions(self):
# Not returning the right amount. debug
# torsions = []
# for i in range(len(self.torsion_index)):
# try:
# if (self.torsion_index[i] != self.torsion_index[i+1]).all():
# torsions.append(self.torsion_index[i]), torsions.append(self.torsion_index[i+1])
# except:
# pass
# return len(torsions), torsions
def __getitem__(self, key):
"Get a slice of this trajectory"
return self.slice(key)
def slice(self, key, copy=True):
"""Slice trajectory, by extracting one or more frames into a separate object
This method can also be called using index bracket notation, i.e
`traj[1] == traj.slice(1)`
Parameters
----------
key : {int, np.ndarray, slice}
The slice to take. Can be either an int, a list of ints, or a slice
object.
copy : bool, default=True
Copy the arrays after slicing. If you set this to false, then if
you modify a slice, you'll modify the original array since they
point to the same data.
"""
xyz = self.xyz[key]
time = self.time[key]
torsions = self.torsion_index[key]
direction = self.direction[key]
steps = self.steps[key]
qm_energy = self.qm_energy[key]
unitcell_lengths, unitcell_angles = None, None
if self.unitcell_angles is not None:
unitcell_angles = self.unitcell_angles[key]
if self.unitcell_lengths is not None:
unitcell_lengths = self.unitcell_lengths[key]
if copy:
xyz = xyz.copy()
time = time.copy()
topology = deepcopy(self._topology)
structure = deepcopy(self.structure)
torsions = torsions.copy()
direction = direction.copy()
steps = steps.copy()
qm_energy = qm_energy.copy()
if self.unitcell_angles is not None:
unitcell_angles = unitcell_angles.copy()
if self.unitcell_lengths is not None:
unitcell_lengths = unitcell_lengths.copy()
newtraj = self.__class__(
xyz, topology, structure, torsions, direction, steps, qm_energy)
if self._rmsd_traces is not None:
newtraj._rmsd_traces = np.array(self._rmsd_traces[key],
ndmin=1, copy=True)
return newtraj
