def get_latest_checkpoint_file(directory_name):
"""
Yields the file with the most up-to-date checkpoint in it in terms of the 'step'.
:param directory_name: the directory in which to look for checkpoints
:return: the latest checkpoint or raise if directory is empty
"""
from readdy import Trajectory
checkpoint_files = Simulation.list_checkpoint_files(directory_name)
if len(checkpoint_files) == 0:
raise ValueError(
"No checkpoints found in {}".format(directory_name))
latest = None
latest_step = None
for filename in checkpoint_files:
traj = Trajectory(filename)
ckpt = traj.list_checkpoints()
# print(f"GetLatestCheckpointFile: File {filename} checkpoints {ckpt}")
latest_ckpt_step = 0
for c in ckpt:
latest_ckpt_step = c['step'] if latest_step is None else (
c['step'] if c['step'] > latest_step else latest_step)
if latest is None:
latest = (filename, ckpt)
latest_step = latest_ckpt_step
# print(f" -> got new latest {latest}")
else:
if latest_ckpt_step > latest_step:
latest = (filename, ckpt)
latest_step = latest_ckpt_step
# print(f" -> got new latest {latest}")
return latest[0]
def list_checkpoints(file_name):
"""
Returns a list of checkpoints in a trajectory file.
:param file_name: the trajectory file
"""
from readdy import Trajectory
traj = Trajectory(file_name)
return traj.list_checkpoints()
def list_checkpoints(file_name):
"""
Returns a list of checkpoints in a trajectory file.
:param file_name: the trajectory file
"""
from readdy import Trajectory
traj = Trajectory(file_name)
return traj.list_checkpoints()
def list_checkpoint_files(directory_name):
import os
from glob import glob
from readdy import Trajectory
files = glob(os.path.join(directory_name, '*.h5'))
result = []
for f in files:
try:
traj = Trajectory(f)
traj.list_checkpoints()
result.append(f)
except:
pass
return result
def load_particles_from_checkpoint(self, file_name, n=None):
"""
Adds particles to the simulation as contained in the n-th checkpoint of a trajectory file.
:param file_name: the trajectory file
:param n: if n is None, retrieve configuration from latest checkpoint, otherwise use 'n-th' checkpoint, n >= 0
"""
import numpy as _np
from readdy import Trajectory
from readdy.api.trajectory import _CKPT
from readdy.util.io_utils import get_particle_types
checkpoints = self.list_checkpoints(file_name)
if n is None:
n = len(checkpoints) - 1
else:
assert n < len(
checkpoints
), f"n={n} is out of bounds, only have {len(checkpoints)} checkpoints"
assert n >= 0, f"n must be positive but was {n}"
# group particle types by flavor (NORMAL, TOPOLOGY)
ptypes = get_particle_types(filename=file_name)
normal_types = []
topology_types = []
for t in ptypes.values():
if t['flavor'] == 'TOPOLOGY':
topology_types.append(t['type_id'])
if t['flavor'] == 'NORMAL':
normal_types.append(t['type_id'])
# load frame into memory
traj = Trajectory(file_name)
n_particles_per_frame, positions, types, ids = traj.to_numpy(
start=n, stop=n + 1, name=_CKPT.POSITIONS_CKPT)
# add particles with flavor NORMAL
for normal_type in normal_types:
tixs = _np.argwhere(types[0] == normal_type)
pos = positions[0][tixs].squeeze()
if len(pos) > 0:
self.add_particles(traj.species_name(normal_type),
_np.atleast_2d(pos))
# add topologies
time, topology_records = traj.read_observable_topologies(
start=n, stop=n + 1, data_set_name=_CKPT.TOPOLOGY_CKPT)
assert len(topology_records) == 1
for topology in topology_records[0]:
particle_types = [
traj.species_name(types[0, i]) for i in topology.particles
]
pos = _np.atleast_2d(
_np.array([positions[0, i] for i in topology.particles]))
top = self.add_topology(traj.topology_type_name(topology.type),
particle_types, pos)
for e in topology.edges:
top.graph.add_edge(e[0], e[1])
def load_particles_from_checkpoint(self, file_name, n=None):
"""
Adds particles to the simulation as contained in the n-th checkpoint of a trajectory file.
:param file_name: the trajectory file
:param n: if n is None, retrieve configuration from latest checkpoint, otherwise use 'n-th' checkpoint, n >= 0
"""
import numpy as _np
from readdy import Trajectory
from readdy.api.trajectory import _CKPT
from readdy.util.io_utils import get_particle_types
checkpoints = self.list_checkpoints(file_name)
if n is None:
n = len(checkpoints)-1
else:
assert n < len(checkpoints), f"n={n} is out of bounds, only have {len(checkpoints)} checkpoints"
assert n >= 0, f"n must be positive but was {n}"
# group particle types by flavor (NORMAL, TOPOLOGY)
ptypes = get_particle_types(filename=file_name)
normal_types = []
topology_types = []
for t in ptypes.values():
if t['flavor'] == 'TOPOLOGY':
topology_types.append(t['type_id'])
if t['flavor'] == 'NORMAL':
normal_types.append(t['type_id'])
# load frame into memory
traj = Trajectory(file_name)
n_particles_per_frame, positions, types, ids = traj.to_numpy(start=n, stop=n+1, name=_CKPT.POSITIONS_CKPT)
# add particles with flavor NORMAL
for normal_type in normal_types:
tixs = _np.argwhere(types[0] == normal_type)
pos = positions[0][tixs].squeeze()
if len(pos) > 0:
self.add_particles(traj.species_name(normal_type), _np.atleast_2d(pos))
# add topologies
time, topology_records = traj.read_observable_topologies(start=n, stop=n+1, data_set_name=_CKPT.TOPOLOGY_CKPT)
assert len(topology_records) == 1
for topology in topology_records[0]:
particle_types = [traj.species_name(types[0, i]) for i in topology.particles]
pos = _np.atleast_2d(_np.array([positions[0, i] for i in topology.particles]))
top = self.add_topology(traj.topology_type_name(topology.type), particle_types, pos)
for e in topology.edges:
top.graph.add_edge(e[0], e[1])