def set_periodic_checkpoint(sim, period, checkpoint_dir='./checkpoints'):
"""
Set up periodic checkpoints of the simulation
The checkpoints are saved in openPMD format, in the specified
directory, with one subdirectory per process.
The E and B fields and particle information of each processor is saved.
NB: Checkpoints are registered in the list `checkpoints` of the Simulation
object `sim`, and written at the end of the PIC loop (whereas regular
diagnostics are written at the beginning of the PIC loop).
Parameters
----------
sim: a Simulation object
The simulation that is to be saved in checkpoints
period: integer
The number of PIC iteration between each checkpoint.
checkpoint_dir: string, optional
The path to the directory in which the checkpoints are stored
(When running a simulation with several MPI ranks, use the
same path for all ranks.)
"""
# Only processor 0 creates a directory where checkpoints will be stored
# Make sure that all processors wait until this directory is created
# (Use the global MPI communicator instead of the `BoundaryCommunicator`
# so that this still works in the case `use_all_ranks=False`)
if comm.rank == 0:
if os.path.exists(checkpoint_dir) is False:
os.mkdir(checkpoint_dir)
comm.barrier()
# Choose the name of the directory: one directory per processor
write_dir = os.path.join(checkpoint_dir, 'proc%d/' % comm.rank)
# Register a periodic FieldDiagnostic in the diagnostics of the simulation
# This saves only the E and B field (and their PML components, if used)
fieldtypes = ["E", "B"]
if sim.use_pml:
fieldtypes += ["Er_pml", "Et_pml", "Br_pml", "Bt_pml"]
sim.checkpoints.append(
FieldDiagnostic(period,
sim.fld,
fieldtypes=fieldtypes,
write_dir=write_dir))
# Register a periodic ParticleDiagnostic, which contains all
# the particles which are present in the simulation
particle_dict = {}
for i in range(len(sim.ptcl)):
particle_dict['species %d' % i] = sim.ptcl[i]
if len(particle_dict) > 0:
sim.checkpoints.append(
ParticleDiagnostic(period, particle_dict, write_dir=write_dir))
def set_periodic_checkpoint(sim, period):
"""
Set up periodic checkpoints of the simulation
The checkpoints are saved in openPMD format, in the directory
`./checkpoints`, with one subdirectory per process.
The E and B fields and particle information of each processor is saved.
NB: Checkpoints are registered in the list `checkpoints` of the Simulation
object `sim`, and written at the end of the PIC loop (whereas regular
diagnostics are written at the beginning of the PIC loop).
Parameters
----------
sim: a Simulation object
The simulation that is to be saved in checkpoints
period: integer
The number of PIC iteration between each checkpoint.
"""
# Only processor 0 creates a directory where checkpoints will be stored
# Make sure that all processors wait until this directory is created
# (Use the global MPI communicator instead of the `BoundaryCommunicator`
# so that this still works in the case `use_all_ranks=False`)
if comm.rank == 0:
if os.path.exists('./checkpoints') is False:
os.mkdir('./checkpoints')
comm.barrier()
# Choose the name of the directory: one directory per processor
write_dir = 'checkpoints/proc%d/' % comm.rank
# Register a periodic FieldDiagnostic in the diagnostics of the simulation
sim.checkpoints.append(
FieldDiagnostic(period,
sim.fld,
fieldtypes=["E", "B"],
write_dir=write_dir))
# Register a periodic ParticleDiagnostic, which contains all
# the particles which are present in the simulation
particle_dict = {}
for i in range(len(sim.ptcl)):
particle_dict['species %d' % i] = sim.ptcl[i]
sim.checkpoints.append(
ParticleDiagnostic(period, particle_dict, write_dir=write_dir))
def restart_from_checkpoint( sim, iteration=None ):
"""
Fills the Simulation object `sim` with data saved in a checkpoint.
More precisely, the following data from `sim` is overwritten:
- Current time and iteration number of the simulation
- Position of the boundaries of the simulation box
- Values of the field arrays
- Size and values of the particle arrays
Any other information (e.g. diagnostics of the simulation, presence of a
moving window, presence of a laser antenna, etc.) need to be set by hand.
For this reason, a successful restart will often require to modify the
original input script that produced the checkpoint, rather than to start
a new input script from scratch.
NB: This function should always be called *before* the initialization
of the moving window, since the moving window infers the position of
particle injection from the existing particle data.
Parameters
----------
sim: a Simulation object
The Simulation object into which the checkpoint should be loaded
iteration: integer (optional)
The iteration number of the checkpoint from which to restart
If None, the latest checkpoint available will be used.
"""
# Import openPMD-viewer
try:
from opmd_viewer import OpenPMDTimeSeries
except ImportError:
raise ImportError(
'The package `opmd_viewer` is required to restart from checkpoints.'
'\nPlease install it from https://github.com/openPMD/openPMD-viewer')
# Verify that the restart is valid (only for the first processor)
# (Use the global MPI communicator instead of the `BoundaryCommunicator`,
# so that this also works for `use_all_ranks=False`)
if comm.rank == 0:
check_restart( sim, iteration )
comm.barrier()
# Choose the name of the directory from which to restart:
# one directory per processor
checkpoint_dir = 'checkpoints/proc%d/hdf5' %comm.rank
ts = OpenPMDTimeSeries( checkpoint_dir )
# Select the iteration, and its index
if iteration is None:
iteration = ts.iterations[-1]
# Find the index of the closest iteration
i_iteration = np.argmin( abs(np.array(ts.iterations) - iteration) )
# Modify parameters of the simulation
sim.iteration = iteration
sim.time = ts.t[ i_iteration ]
# Export available species as a list
avail_species = ts.avail_species
if avail_species is None:
avail_species = []
# Load the particles
# Loop through the different species
if len(avail_species) == len(sim.ptcl):
for i in range(len(sim.ptcl)):
name = 'species %d' %i
load_species( sim.ptcl[i], name, ts, iteration, sim.comm )
else:
raise RuntimeError( \
"""Species numbers in checkpoint and simulation should be same, but
got {:d} and {:d}. Use add_new_species method to add species to
simulation or sim.ptcl = [] to remove them""".format(len(avail_species),
len(sim.ptcl)) )
# Record position of grid before restart
zmin_old = sim.fld.interp[0].zmin
# Load the fields
# Loop through the different modes
for m in range( sim.fld.Nm ):
# Load the fields E and B
for fieldtype in ['E', 'B']:
for coord in ['r', 't', 'z']:
load_fields( sim.fld.interp[m], fieldtype,
coord, ts, iteration )
# Record position after restart (`zmin` is modified by `load_fields`)
# and shift the global domain position in the BoundaryCommunicator
zmin_new = sim.fld.interp[0].zmin
sim.comm.shift_global_domain_positions( zmin_new - zmin_old )