本文整理汇总了Python中mdtraj.Trajectory方法的典型用法代码示例。如果您正苦于以下问题:Python mdtraj.Trajectory方法的具体用法?Python mdtraj.Trajectory怎么用?Python mdtraj.Trajectory使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mdtraj
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在下文中一共展示了mdtraj.Trajectory方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: write_nonequilibrium_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def write_nonequilibrium_trajectory(nonequilibrium_trajectory, trajectory_filename):
"""
Write the results of a nonequilibrium switching trajectory to a file. The trajectory is written to an
mdtraj hdf5 file.
Parameters
----------
nonequilibrium_trajectory : md.Trajectory
The trajectory resulting from a nonequilibrium simulation
trajectory_filename : str
The full filepath for where to store the trajectory
Returns
-------
True : bool
"""
if nonequilibrium_trajectory is not None:
nonequilibrium_trajectory.save_hdf5(trajectory_filename)
return True
示例2: write_equilibrium_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def write_equilibrium_trajectory(trajectory: md.Trajectory, trajectory_filename: str) -> float:
"""
Write the results of an equilibrium simulation to disk. This task will append the results to the given filename.
Parameters
----------
trajectory : md.Trajectory
the trajectory resulting from an equilibrium simulation
trajectory_filename : str
the name of the trajectory file to which we should append
Returns
-------
True
"""
if not os.path.exists(trajectory_filename):
trajectory.save_hdf5(trajectory_filename)
_logger.debug(f"{trajectory_filename} does not exist; instantiating and writing to.")
else:
_logger.debug(f"{trajectory_filename} exists; appending.")
written_traj = md.load_hdf5(trajectory_filename)
concatenated_traj = written_traj.join(trajectory)
concatenated_traj.save_hdf5(trajectory_filename)
return True
示例3: write_equilibrium_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def write_equilibrium_trajectory(trajectory: md.Trajectory, trajectory_filename: str) -> float:
"""
Write the results of an equilibrium simulation to disk. This task will append the results to the given filename.
Arguments
----------
trajectory : md.Trajectory
the trajectory resulting from an equilibrium simulation
trajectory_filename : str
the name of the trajectory file to which we should append
Returns
-------
True
"""
if not os.path.exists(trajectory_filename):
trajectory.save_hdf5(trajectory_filename)
_logger.debug(f"{trajectory_filename} does not exist; instantiating and writing to.")
else:
_logger.debug(f"{trajectory_filename} exists; appending.")
written_traj = md.load_hdf5(trajectory_filename)
concatenated_traj = written_traj.join(trajectory)
concatenated_traj.save_hdf5(trajectory_filename)
return True
示例4: write_nonequilibrium_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def write_nonequilibrium_trajectory(nonequilibrium_trajectory, trajectory_filename):
"""
Write the results of a nonequilibrium switching trajectory to a file. The trajectory is written to an
mdtraj hdf5 file.
Arguments
----------
nonequilibrium_trajectory : md.Trajectory
The trajectory resulting from a nonequilibrium simulation
trajectory_filename : str
The full filepath for where to store the trajectory
Returns
-------
True : bool
"""
if nonequilibrium_trajectory is not None:
nonequilibrium_trajectory.save_hdf5(trajectory_filename)
return True
示例5: generate_dummy_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def generate_dummy_trajectory(xyz, box):
"""Convert xyz coordinates and box vectors into an MDTraj Trajectory (with Topology)."""
try:
import mdtraj as md
import pandas as pd
except ImportError as e:
print("Error: generate_dummy_trajectory() requires mdtraj and pandas!")
raise(e)
n_atoms = len(xyz)
data = []
for i in range(n_atoms):
data.append(dict(serial=i, name="H", element="H", resSeq=i + 1, resName="UNK", chainID=0))
data = pd.DataFrame(data)
unitcell_lengths = box * np.ones((1, 3))
unitcell_angles = 90 * np.ones((1, 3))
top = md.Topology.from_dataframe(data, np.zeros((0, 2), dtype='int'))
traj = md.Trajectory(xyz, top, unitcell_lengths=unitcell_lengths, unitcell_angles=unitcell_angles)
return traj
示例6: test_kmedoids
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def test_kmedoids(self):
'''
Check that pure kmedoid clustering is behaving as expected on
md.Trajectory objects.
'''
N_CLUSTERS = 5
result = kmedoids.kmedoids(
self.trj,
distance_method='rmsd',
n_clusters=N_CLUSTERS,
n_iters=50)
# kcenters will always produce the same number of clusters on
# this input data (unchanged by kmedoids updates)
self.assertEqual(len(np.unique(result.assignments)), N_CLUSTERS)
self.assertAlmostEqual(
np.average(result.distances), 0.085, delta=0.01)
self.assertAlmostEqual(
np.std(result.distances), 0.019, delta=0.005)
示例7: concatenate_trjs
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def concatenate_trjs(trj_list, atoms=None, n_procs=None):
"""Convert a list of trajectories into a single trajectory building
a concatenated array in parallel.
Parameters
----------
trj_list : array-like, shape=(n_trjs,)
The list of md.Trajectory objects
atoms : str, default=None
A selection in the MDTraj DSL for atoms to slice out from each
trajectory in `trj_list`. If none, no slice is performed.
n_procs : int, default=None
Number of parallel processes to use when performing this
operation.
Returns
-------
trj : md.Trajectory
A concatenated trajectory
"""
example_center = trj_list[0]
if atoms is not None:
example_center = example_center.atom_slice(
example_center.top.select(atoms))
lengths = [len(t) for t in trj_list]
intervals = np.cumsum(np.array([0] + lengths))
full_shape, shared_xyz = shared_array_like_trj(lengths, example_center)
with closing(mp.Pool(processes=n_procs, initializer=_init,
initargs=(shared_xyz,))) as p:
func = partial(_slice_and_insert_xyz, atoms=atoms,
arr_shape=full_shape)
p.map(func, [(intervals[i], intervals[i+1], t)
for i, t in enumerate(trj_list)])
p.join()
xyz = _tonumpyarray(shared_xyz).reshape(full_shape)
return md.Trajectory(xyz, topology=example_center.top)
示例8: compute_neighbor_list
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def compute_neighbor_list(coords, neighbor_cutoff, max_num_neighbors,
periodic_box_size):
"""Computes a neighbor list from atom coordinates."""
N = coords.shape[0]
import mdtraj
traj = mdtraj.Trajectory(coords.reshape((1, N, 3)), None)
box_size = None
if periodic_box_size is not None:
box_size = np.array(periodic_box_size)
traj.unitcell_vectors = np.array(
[[[box_size[0], 0, 0], [0, box_size[1], 0], [0, 0, box_size[2]]]],
dtype=np.float32)
neighbors = mdtraj.geometry.compute_neighborlist(traj, neighbor_cutoff)
neighbor_list = {}
for i in range(N):
if max_num_neighbors is not None and len(neighbors[i]) > max_num_neighbors:
delta = coords[i] - coords.take(neighbors[i], axis=0)
if box_size is not None:
delta -= np.round(delta / box_size) * box_size
dist = np.linalg.norm(delta, axis=1)
sorted_neighbors = list(zip(dist, neighbors[i]))
sorted_neighbors.sort()
neighbor_list[i] = [
sorted_neighbors[j][1] for j in range(max_num_neighbors)
]
else:
neighbor_list[i] = list(neighbors[i])
return neighbor_list
示例9: traj_frame_to_sampler_state
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def traj_frame_to_sampler_state(traj: md.Trajectory, frame_number: int,box_vectors):
xyz = traj.xyz[frame_number, :, :]
box_vectors = traj.openmm_boxes(frame_number)
sampler_state = states.SamplerState(unit.Quantity(xyz, unit=unit.nanometers))
return sampler_state
示例10: traj_frame_to_sampler_state
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def traj_frame_to_sampler_state(traj: md.Trajectory, frame_number: int):
xyz = traj.xyz[frame_number, :, :]
box_vectors = traj.openmm_boxes(frame_number)
sampler_state = states.SamplerState(unit.Quantity(xyz, unit=unit.nanometers), box_vectors=box_vectors)
return sampler_state
示例11: extract_molecule
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def extract_molecule(complex_pdb_path: str, resname: str) -> md.Trajectory:
"""
This method extracts the host from the host-guest solvated complex
Parameters
----------
complex_pdb_path : str
The path to the PDB complex
resname : str
The name of the residue to save
Returns
-------
subset_traj : md.Trajectory
The subsetted trajectory of interest.
"""
traj = md.load(complex_pdb_path)
#Extract the specified resname indices
selected_indices = traj.top.select("resname=='{}'".format(resname))
#Subset the topology to contain just the selected residue
subset_topology = traj.top.subset(selected_indices)
#subset the positions
subset_positions = traj.xyz[0, selected_indices]
#create a new Trajectory object with just the selected residue
subset_traj = md.Trajectory(subset_positions, subset_topology)
return subset_traj
示例12: convert_mdtraj_to_oemol
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def convert_mdtraj_to_oemol(traj: md.Trajectory) -> oechem.OEMol:
"""
This method converts an mdtraj Trajectory to an OEMol via saving as a PDBfile
and reading in with OpenEye. Although this seems hacky, it seems less error-prone
than trying to manually construct the OEMol.
Parameters
----------
mdtraj: md.Trajectory
The trajectory to turn into an OEMol
Returns
-------
mol : oechem.OEMol
The trajectory represented as an OEMol
"""
#create a temporary file with a PDB suffix and save with MDTraj
pdb_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdb")
traj.save(pdb_file.name)
pdb_file.close()
#Now use the openeye oemolistream to read in this file as an OEMol:
ifs = oechem.oemolistream()
ifs.open(pdb_file.name)
ifs.SetFormat(oechem.OEFormat_PDB)
mol = oechem.OEMol()
oechem.OEReadMolecule(ifs, mol)
#close the stream and delete the temporary pdb file
ifs.close()
os.unlink(pdb_file.name)
return mol
示例13: write_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def write_trajectory(positions, topology, outputfile='trajectory.pdb',center=True,offline=None):
if offline != None:
traj = md.Trajectory(positions[0::offline],topology)
else:
traj = md.Trajectory(positions, topology)
if center == True:
traj.center_coordinates()
traj.save_pdb(outputfile)
return
示例14: get_nonequilibrium_trajectory
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def get_nonequilibrium_trajectory(self, direction, trajectory_index):
"""
Get a nonequilibrium trajectory corresponding to a particular direction (forward, 0->1, reverse 1->0),
and run index.
Parameters
----------
direction : str
"forward" or "reverse"
trajectory_index : int
Iteration number of protocol
Returns
-------
nonequilibrium_trajectory : md.Trajectory
the nonequilibrium trajectory
"""
if direction=='forward':
lambda_state = 0
elif direction=='reverse':
lambda_state = 1
else:
raise ValueError("direction must be either forward or reverse")
nonequilibrium_trajectory_filename = self._neq_traj_filenames[lambda_state][trajectory_index]
return md.load(nonequilibrium_trajectory_filename)
示例15: lambda_zero_traj
# 需要导入模块: import mdtraj [as 别名]
# 或者: from mdtraj import Trajectory [as 别名]
def lambda_zero_traj(self):
"""
Get the equilibrium trajectory corresponding to lambda=0
Returns
-------
lambda_zero_traj : md.Trajectory object
The equilibrium trajectory at lambda=0
"""
lambda_zero_filename = self._trajectory_filename[0]
return md.load(lambda_zero_filename)