def write_trajectory(self, clone_dir, output_dir, trajectory_number, stride,
max_rmsd, min_gens, center_conformations, memory_check,
omp_parallel_rmsd=True):
"""
This function takes in a path to a CLONE and merges all the XTC files
it finds into a H5 trajectory:
Parameters
----------
clone_dir : str
the directory in which the xtc files are found. All of the xtc files
in this directory are joined together to make a single trajectory
(.h5) output file
output_dir : str
directory where the outputted files will be placed
trajectory_number : int
A unique number for this trajectory. This number is used in
constructing the filename to write the outputted .h5 trajectory to,
and thus must be unique
stride: int
Subsample by only considering every Nth snapshop.
max_rmsd: {int, None}
if this value is not None, calculate the RMSD to the pdb_file from
each snapshot and reject trajectories which have snapshots with RMSD
greated than max_rmsd. If None, no check is performed
min_gens : int
Discard the trajectories that contain fewer than `min_gens` XTC files.
center_conformations : bool
center conformations before saving.
memory_check : bool
if yes, uses the memory dictionary to do an update rather than a
complete re-convert.
omp_parallel_rmsd : bool
If true, use OpenMP accelerated RMSD calculation for max_rmsd check
"""
xtc_files = self.list_xtcs_in_dir(clone_dir)
# Ensure that we're only joining contiguously numbered xtc files -- starting at 0 --
# into a trajectory. If there are gaps in the xtc files in the directory, we only
# want to use the the ones such that they are contiguously numbered
i = 0
for i, filename in enumerate(xtc_files):
if self.integer_component(filename) != i:
logger.error("Found discontinuity in xtc numbering - check data in %s", clone_dir)
xtc_files = xtc_files[0:i]
break
# check the memory object to see which xtc files have already been converted, and
# exclude those from this conversion
if memory_check:
if clone_dir in self.memory.keys():
previous_convert_exists = True
num_xtcs_converted = self.memory[clone_dir][1]
if len(xtc_files) == num_xtcs_converted: # if we have converted everything,
logger.info("Already converted all files in %s, skipping...", clone_dir)
return # just bail out
else:
xtc_files = xtc_files[num_xtcs_converted:]
else:
previous_convert_exists = False
else:
previous_convert_exists = False
xtc_file_paths = [os.path.join(clone_dir, f) for f in xtc_files]
logger.info("Processing %d xtc files in clone_dir = %s", len(xtc_files), clone_dir)
if len(xtc_files) <= min_gens:
logger.info("Skipping trajectory in clone_dir = %s", clone_dir)
logger.info("Too few xtc files (generations).")
return
try:
# [this should check for and discard overlapping snapshots]
trajectory = Trajectory.load_from_xtc(xtc_file_paths, PDBFilename=self.pdb_topology,
discard_overlapping_frames=True)
except IOError as e:
logger.error("IOError (%s) when processing trajectory in clone_dir = %s", e, clone_dir)
logger.error("Attempting rescue by disregarding final frame, which is often")
logger.error("the first/only frame to be corrupted")
if len(xtc_file_paths) == 1:
logger.error("Didn't find any other frames in %s, continuing...", clone_dir)
return
try:
trajectory = Trajectory.load_from_xtc(xtc_file_paths[0:-1], PDBFilename=self.pdb_topology)
except IOError:
logger.error("Unfortunately, the error remained even after ignoring the final frame.")
logger.error("Skipping the trajectory in clone_dir = %s", clone_dir)
return
else:
logger.error("Sucessfully recovered from IOError by disregarding final frame.")
if max_rmsd is not None:
atomindices = [ int(i)-1 for i in trajectory['AtomID'] ]
rmsdmetric = RMSD(atomindices, omp_parallel=omp_parallel_rmsd)
ppdb = rmsdmetric.prepare_trajectory(Trajectory.load_trajectory_file(self.pdb_topology))
ptraj = rmsdmetric.prepare_trajectory(trajectory)
rmsds = rmsdmetric.one_to_all(ppdb, ptraj, 0)
if max(rmsds) > max_rmsd:
logger.warning("Snapshot %d RMSD %f > the %f cutoff" , argmax(rmsds), max(rmsds), max_rmsd)
logger.warning("Dropping trajectory")
return
if center_conformations:
RMSD.TheoData.centerConformations(trajectory["XYZList"])
# if we are adding to a previous trajectory, we have to load that traj up and extend it
if previous_convert_exists:
output_filename = self.memory[clone_dir][0]
output_file_path = output_filename
logger.info("Extending: %s", output_filename)
assert os.path.exists( output_filename )
# load the traj and extend it [this should check for and discard overlapping snapshots]
Trajectory.append_frames_to_file( output_filename,
trajectory['XYZList'][::stride],
discard_overlapping_frames=True )
num_xtcs_processed = len(xtc_file_paths) + self.memory[clone_dir][1]
# if we are not adding to a traj, then we create a new one
else:
output_filename = 'trj%s.h5' % trajectory_number
output_file_path = os.path.join(output_dir, output_filename)
if os.path.exists(output_file_path):
logger.info("The file name %s already exists. Skipping it.", output_file_path)
return
# stide and discard by snapshot
trajectory['XYZList'] = trajectory['XYZList'][::stride]
trajectory.save(output_file_path)
num_xtcs_processed = len(xtc_file_paths)
# log what we did into the memory object
self.memory[clone_dir] = [ output_file_path, num_xtcs_processed ]
return
def write_trajectory(self,
clone_dir,
output_dir,
trajectory_number,
stride,
max_rmsd,
min_gens,
center_conformations,
memory_check,
omp_parallel_rmsd=True):
"""
This function takes in a path to a CLONE and merges all the XTC files
it finds into a LH5 trajectory:
Parameters
----------
clone_dir : str
the directory in which the xtc files are found. All of the xtc files
in this directory are joined together to make a single trajectory
(.lh5) output file
output_dir : str
directory where the outputted files will be placed
trajectory_number : int
A unique number for this trajectory. This number is used in
constructing the filename to write the outputted .lh5 trajectory to,
and thus must be unique
stride: int
Subsample by only considering every Nth snapshop.
max_rmsd: {int, None}
if this value is not None, calculate the RMSD to the pdb_file from
each snapshot and reject trajectories which have snapshots with RMSD
greated than max_rmsd. If None, no check is performed
min_gens : int
Discard the trajectories that contain fewer than `min_gens` XTC files.
center_conformations : bool
center conformations before saving.
memory_check : bool
if yes, uses the memory dictionary to do an update rather than a
complete re-convert.
omp_parallel_rmsd : bool
If true, use OpenMP accelerated RMSD calculation for max_rmsd check
"""
xtc_files = self.list_xtcs_in_dir(clone_dir)
# Ensure that we're only joining contiguously numbered xtc files -- starting at 0 --
# into a trajectory. If there are gaps in the xtc files in the directory, we only
# want to use the the ones such that they are contiguously numbered
i = 0
for i, filename in enumerate(xtc_files):
if self.integer_component(filename) != i:
logger.error(
"Found discontinuity in xtc numbering - check data in %s",
clone_dir)
xtc_files = xtc_files[0:i]
break
# check the memory object to see which xtc files have already been converted, and
# exclude those from this conversion
if memory_check:
if clone_dir in self.memory.keys():
previous_convert_exists = True
num_xtcs_converted = self.memory[clone_dir][1]
if len(
xtc_files
) == num_xtcs_converted: # if we have converted everything,
logger.info(
"Already converted all files in %s, skipping...",
clone_dir)
return # just bail out
else:
xtc_files = xtc_files[num_xtcs_converted:]
else:
previous_convert_exists = False
else:
previous_convert_exists = False
xtc_file_paths = [os.path.join(clone_dir, f) for f in xtc_files]
logger.info("Processing %d xtc files in clone_dir = %s",
len(xtc_files), clone_dir)
if len(xtc_files) <= min_gens:
logger.info("Skipping trajectory in clone_dir = %s", clone_dir)
logger.info("Too few xtc files (generations).")
return
try:
# [this should check for and discard overlapping snapshots]
trajectory = Trajectory.load_from_xtc(
xtc_file_paths,
PDBFilename=self.pdb_topology,
discard_overlapping_frames=True)
except IOError as e:
logger.error(
"IOError (%s) when processing trajectory in clone_dir = %s", e,
clone_dir)
logger.error(
"Attempting rescue by disregarding final frame, which is often"
)
logger.error("the first/only frame to be corrupted")
if len(xtc_file_paths) == 1:
logger.error(
"Didn't find any other frames in %s, continuing...",
clone_dir)
return
try:
trajectory = Trajectory.load_from_xtc(
xtc_file_paths[0:-1], PDBFilename=self.pdb_topology)
except IOError:
logger.error(
"Unfortunately, the error remained even after ignoring the final frame."
)
logger.error("Skipping the trajectory in clone_dir = %s",
clone_dir)
return
else:
logger.error(
"Sucessfully recovered from IOError by disregarding final frame."
)
if max_rmsd is not None:
atomindices = [int(i) - 1 for i in trajectory['AtomID']]
rmsdmetric = RMSD(atomindices, omp_parallel=omp_parallel_rmsd)
ppdb = rmsdmetric.prepare_trajectory(
Trajectory.load_trajectory_file(self.pdb_topology))
ptraj = rmsdmetric.prepare_trajectory(trajectory)
rmsds = rmsdmetric.one_to_all(ppdb, ptraj, 0)
if max(rmsds) > max_rmsd:
logger.warning("Snapshot %d RMSD %f > the %f cutoff",
argmax(rmsds), max(rmsds), max_rmsd)
logger.warning("Dropping trajectory")
return
if center_conformations:
RMSD.TheoData.centerConformations(trajectory["XYZList"])
# if we are adding to a previous trajectory, we have to load that traj up and extend it
if previous_convert_exists:
output_filename = self.memory[clone_dir][0]
output_file_path = output_filename
logger.info("Extending: %s", output_filename)
assert os.path.exists(output_filename)
# load the traj and extend it [this should check for and discard overlapping snapshots]
Trajectory.append_frames_to_file(output_filename,
trajectory['XYZList'][::stride],
discard_overlapping_frames=True)
num_xtcs_processed = len(
xtc_file_paths) + self.memory[clone_dir][1]
# if we are not adding to a traj, then we create a new one
else:
output_filename = 'trj%s.lh5' % trajectory_number
output_file_path = os.path.join(output_dir, output_filename)
if os.path.exists(output_file_path):
logger.info("The file name %s already exists. Skipping it.",
output_file_path)
return
# stide and discard by snapshot
trajectory['XYZList'] = trajectory['XYZList'][::stride]
trajectory.save(output_file_path)
num_xtcs_processed = len(xtc_file_paths)
# log what we did into the memory object
self.memory[clone_dir] = [output_file_path, num_xtcs_processed]
return
