def run_simulations(self,i_iteration):
self.rank_directory = self.RANK_DIR_FORMAT.format(
self.mpi_rank)
# if the directory exists delete it
if os.path.isdir(self.rank_directory):
shutil.rmtree(self.rank_directory)
os.makedirs(self.rank_directory)
# change execution context for this rank
# this provides a directory for each worker directory so that the
# disk IO writes don't conflict
os.chdir(self.rank_directory)
_config_filename = os.path.join(
self.root_directory,
self.pyposmat_configuration_filename)
_results_filename = os.path.join(
self.root_directory,
self.rank_directory,
'pyposmat.results.out')
# determine number of sims for this rank
_n_sims = 1000 * self.mpi_size +2
_n_sims_per_rank = int(_n_sims/self.mpi_size)
if _n_sims%self.mpi_size > self.mpi_rank:
_n_sims_per_rank += 1
# set random seed
np.random.seed(self.rv_seeds[self.mpi_rank,i_iteration])
self.pyposmat_mc_sampler = PyposmatMonteCarloSampler(
filename_in = _config_filename,
filename_out = _results_filename)
self.pyposmat_mc_sampler.create_base_directories()
self.pyposmat_mc_sampler.read_configuration_file()
self.pyposmat_mc_sampler.configure_qoi_manager()
self.pyposmat_mc_sampler.configure_task_manager()
self.pyposmat_mc_sampler.configure_pyposmat_datafile_out()
#pyposmat_datafile_out = PyposmatDataFile(filename_out)
if self.mpi_rank == 0:
self.pyposmat_mc_sampler.print_structure_database()
self.pyposmat_mc_sampler.print_sampling_configuration()
self.pyposmat_mc_sampler.print_initial_parameter_distribution()
for i in range(self.pyposmat_mc_sampler.n_iterations):
self.pyposmat_mc_sampler.run_simulations(i_iteration=i,n_samples=1000)
os.chdir(self.root_directory)
MgO_structures['structure_directory'] = 'test__PyposmatMonteCarloSampler'
MgO_structures['structures'] = OrderedDict()
MgO_structures['structures']['MgO_NaCl'] = 'MgO_NaCl_unit.gga.relax.vasp'
MgO_configuration = PyposmatConfigurationFile()
MgO_configuration.qois = MgO_qoi_db.qois
MgO_configuration.potential = MgO_potential
MgO_configuration.structures = MgO_structures
assert isinstance(MgO_configuration.configuration,OrderedDict)
MgO_configuration.write(filename='pypospack.config.in')
MgO_configuration.read(filename='pypospack.config.in')
# <---------------- end make configuration file
filename_in='pypospack.config.in'
filename_out='pypospack.results.out'
engine = PyposmatMonteCarloSampler(
filename_in=filename_in,
filename_out=filename_out)
# <---------------- printout for debugging purposes
print('base_directory:{}'.format(engine.base_directory))
print('input_filename:{}'.format(engine.pyposmat_filename_in))
print('output_filename:{}'.format(engine.pyposmat_filename_out))
# <---------------- the steps of engine.configure() tested individually
# this is the step which configures the object from the
# configuration file
# engine.configure()
engine.create_base_directories()
engine.read_configuration_file()
engine.configure_qoi_manager()
engine.configure_task_manager()
#------------------------------------------------------------------------------
# WRITE CONFIGURATION FILE
#------------------------------------------------------------------------------
Ni_eam_configuration = PyposmatConfigurationFile()
Ni_eam_configuration.qois = Ni_eam.Ni_qoi_db.qois
Ni_eam_configuration.potential = Ni_eam.Ni_eam_potential_formalism
Ni_eam_configuration.structures = Ni_eam.Ni_structure_db
Ni_eam_configuration.sampling_type = Ni_eam.Ni_eam_sampling
Ni_eam_configuration.sampling_distribution = Ni_eam.Ni_eam_parameter_distribution
Ni_eam_configuration.write(filename='pypospack.config.in')
Ni_eam_configuration.read(filename='pypospack.config.in')
# <---------------- end make configuration file
filename_in = 'pypospack.config.in'
filename_out = 'pypospack.results.out'
engine = PyposmatMonteCarloSampler(filename_in=filename_in,
filename_out=filename_out)
# <---------------- printout for debugging purposes
print('base_directory:{}'.format(engine.base_directory))
print('input_filename:{}'.format(engine.pyposmat_filename_in))
print('output_filename:{}'.format(engine.pyposmat_filename_out))
# <---------------- the steps of engine.configure() tested individually
# this is the step which configures the object from the
# configuration file
# engine.configure()
engine.create_base_directories()
engine.read_configuration_file()
engine.configure_qoi_manager()
engine.configure_task_manager()
engine.configure_pyposmat_datafile_out()
#pyposmat_datafile_out = PyposmatDataFile(filename_out)
# WRITE CONFIGURATION FILE
#------------------------------------------------------------------------------
Si_sw_configuration = PyposmatConfigurationFile()
Si_sw_configuration.qois = Si_sw_qoi_db.qois
Si_sw_configuration.potential = Si_sw_potential
Si_sw_configuration.structures = Si_sw_structures
Si_sw_configuration.sampling_type = sampling
Si_sw_configuration.sampling_distribution = Si_sw_param_dist
Si_sw_configuration.write(filename='pypospack.config.in')
Si_sw_configuration.read(filename='pypospack.config.in')
# <---------------- end make configuration file
filename_in='pypospack.config.in'
filename_out='pypospack.results.out'
engine = PyposmatMonteCarloSampler(
filename_in=filename_in,
filename_out=filename_out)
# <---------------- printout for debugging purposes
print('base_directory:{}'.format(engine.base_directory))
print('input_filename:{}'.format(engine.pyposmat_filename_in))
print('output_filename:{}'.format(engine.pyposmat_filename_out))
# <---------------- the steps of engine.configure() tested individually
# this is the step which configures the object from the
# configuration file
engine.create_base_directories()
engine.read_configuration_file()
engine.configure_qoi_manager()
engine.configure_task_manager()
engine.configure_pyposmat_datafile_out()
#pyposmat_datafile_out = PyposmatDataFile(filename_out)
class PyposmatIterativeSampler(object):
def __init__(self,
configuration_filename):
self.RANK_DIR_FORMAT = 'rank_{}'
self.mpi_comm = None
self.mpi_rank = None
self.mpi_nprocs = None
self.n_iterations = None
self.rv_seed = None
self.rv_seeds = None
self.pyposmat_configuration_filename = configuration_filename
self.pyposmat_mc_sampler = None
self.root_directory = os.getcwd()
def run_simulations(self,i_iteration):
self.rank_directory = self.RANK_DIR_FORMAT.format(
self.mpi_rank)
# if the directory exists delete it
if os.path.isdir(self.rank_directory):
shutil.rmtree(self.rank_directory)
os.makedirs(self.rank_directory)
# change execution context for this rank
# this provides a directory for each worker directory so that the
# disk IO writes don't conflict
os.chdir(self.rank_directory)
_config_filename = os.path.join(
self.root_directory,
self.pyposmat_configuration_filename)
_results_filename = os.path.join(
self.root_directory,
self.rank_directory,
'pyposmat.results.out')
# determine number of sims for this rank
_n_sims = 1000 * self.mpi_size +2
_n_sims_per_rank = int(_n_sims/self.mpi_size)
if _n_sims%self.mpi_size > self.mpi_rank:
_n_sims_per_rank += 1
# set random seed
np.random.seed(self.rv_seeds[self.mpi_rank,i_iteration])
self.pyposmat_mc_sampler = PyposmatMonteCarloSampler(
filename_in = _config_filename,
filename_out = _results_filename)
self.pyposmat_mc_sampler.create_base_directories()
self.pyposmat_mc_sampler.read_configuration_file()
self.pyposmat_mc_sampler.configure_qoi_manager()
self.pyposmat_mc_sampler.configure_task_manager()
self.pyposmat_mc_sampler.configure_pyposmat_datafile_out()
#pyposmat_datafile_out = PyposmatDataFile(filename_out)
if self.mpi_rank == 0:
self.pyposmat_mc_sampler.print_structure_database()
self.pyposmat_mc_sampler.print_sampling_configuration()
self.pyposmat_mc_sampler.print_initial_parameter_distribution()
for i in range(self.pyposmat_mc_sampler.n_iterations):
self.pyposmat_mc_sampler.run_simulations(i_iteration=i,n_samples=1000)
os.chdir(self.root_directory)
def setup_mpi_environment(self):
self.mpi_comm = MPI.COMM_WORLD
self.mpi_rank = self.mpi_comm.Get_rank()
self.mpi_size = self.mpi_comm.Get_size()
self.mpi_procname = MPI.Get_processor_name()
if self.mpi_rank == 0:
self.print_mpi_environment()
def print_mpi_environment(self):
print(80*'-')
print('{:^80}'.format('MPI COMMUNICATION INFORMATION'))
print(80*'-')
print('mpi_size={}'.format(self.mpi_size))
def determine_rv_seeds(self):
_randint_low = 0
_randint_high = 2147483647
# set original seed
if self.rv_seed is None:
self.rv_seed = np.random.randint(
low=_randint_low,
high=_randint_high)
np.random.seed(self.rv_seed)
# determine rank seed
self.rv_seeds = np.random.randint(
low=0,
high=2147483647,
size=(int(self.mpi_size),self.n_iterations)
)
if self.mpi_rank == 0:
self.print_random_seeds()
def run_all(self):
self.setup_mpi_environment()
self.determine_rv_seeds()
for i in range(self.n_iterations):
self.run_simulations(i)
MPI.COMM_WORLD.Barrier()
self.analyze_results(i)
MPI.COMM_WORLD.Barrier()
def analyze_results(self,i_iterations):
# merge datafiles
if self.mpi_rank == 0:
_filename_out = 'pyposmat.results.{}.out'.format(
i_iterations)
print('merging results into {}'.format(_filename_out))
for i_rank in range(self.mpi_size):
_filename_in = os.path.join(
self.RANK_DIR_FORMAT.format(i_rank))
print('\t merging...{}'.format(_filename_in))
def print_random_seeds(self):
print(80*'-')
print('{:^80}'.format('GENERATED RANDOM SEEDS'))
print(80*'-')
print()
print('rv_seed={}'.format(self.rv_seed))
print()
print('{:^8} {:^8} {:^10}'.format('rank','iter','seed'))
print('{} {} {}'.format(8*'-',8*'-',10*'-'))
for i_rank in range(self.mpi_size):
for i_iter in range(self.n_iterations):
print('{:^8} {:^8} {:>10}'.format(
i_rank,
i_iter,
self.rv_seeds[i_rank,i_iter]))