def __init__(self, parameters=None):
if parameters is None:
parameters = {}
self.parameters = parameters
self.parameters.setdefault('zed', 1)
self.psf = None
self.target = None
self.phantom = True
if 'logging' not in gparameters:
gparameters.logging = DictionaryObject({'path': '.'})
gparameters.generation = 0
gparameters.mpi = DictionaryObject({'rank': 0})
# Set default normalization to E = E/nprotons
if "normalize" not in self.parameters:
self.parameters.setdefault("normalize", {})
self.parameters['normalize'].setdefault('nprotons', True)
self.parameters['normalize'].setdefault('SSE', False)
# If running within StructOpt, create directory for saving files
# and faster loading of PSF and target data
path = os.path.join(gparameters.logging.path, 'fitness/STEM')
path = os.path.join(path, 'rank-{}'.format(gparameters.mpi.rank))
self.path = path
os.makedirs(self.path, exist_ok=True)
def __init__(self, dir):
self.genealogy_file = os.path.join(dir, 'genealogy.log')
self.fitnesses_file = os.path.join(dir, 'fitnesses.log')
self.XYZs = os.path.join(dir, 'XYZs')
# Load input parameters from output file
self.output_file = os.path.join(dir, 'output.log')
parameters = []
start_flag = False
for line in open(self.output_file):
if 'Current parameters:' in line:
start_flag = True
continue
if start_flag:
if 'INFO : {' in line:
line = line.split('INFO : ')[1]
parameters.append(line)
if line == '}\n':
start_flag = False
break
parameters = ''.join(parameters)
self.parameters = DictionaryObject(json.loads(parameters))
sys.modules['gparameters'] = self.parameters
self.generations = Generations(self.genealogy_file)
for population in self.generations:
for individual in population.values():
individual.filename = os.path.join(
self.XYZs, 'generation{}'.format(individual.created_on),
'individual{}.xyz'.format(individual.id))
individual.parameters = DictionaryObject(
self.parameters.copy())
def __init__(self, parameters):
# These variables never change
self.parameters = parameters
if 'logging' not in gparameters:
gparameters.logging = DictionaryObject({'path': '.'})
gparameters.generation = 0
gparameters.mpi = DictionaryObject({'rank': 0})
self.output_dir = gparameters.logging.path
# Set default normalization to E = E/natoms
if "normalize" not in self.parameters:
self.parameters.setdefault("normalize", {})
self.parameters.normalize.setdefault('natoms', True)
def set_default(parameters):
paramters = set_default_mpi_parameters(parameters)
parameters.setdefault('logging', {})
if "path" in parameters.logging:
raise ValueError(
"'path' should not be defined in the parameter file currently. If you think you want to define it, talk to the developers about why."
)
# If parallel and no seed, all nodes need the same seed and same path
if parameters.mpi.ncores > 1:
from mpi4py import MPI
seed = MPI.COMM_WORLD.bcast(int(time.time()), root=0)
path = MPI.COMM_WORLD.bcast(os.path.join(
os.getcwd(), "logs{}".format(time.strftime("%Y%m%d%H%M%S"))),
root=0)
else:
seed = None
path = os.path.join(os.getcwd(),
"logs{}".format(time.strftime("%Y%m%d%H%M%S")))
parameters.logging.path = path
parameters.setdefault('seed', seed)
parameters.setdefault('post_processing', DictionaryObject({}))
parameters.post_processing.setdefault('XYZs', 0)
parameters.setdefault('fingerprinters', DictionaryObject({'options': []}))
parameters.convergence.setdefault('max_generations', 10)
if 'relaxations' not in parameters or not parameters['relaxations']:
raise ValueError(
'Relaxations must be specified in the parameter file.')
if 'fitnesses' not in parameters or not parameters['fitnesses']:
raise ValueError('Fitnesses must be specified in the parameter file.')
# Make sure every operation is defined, and that every operation has a
# kwargs
for operation in MODULES:
parameters.setdefault(operation, None)
if parameters[operation] is not None:
for operator in parameters[operation]:
if operator not in EXCEPTION_FUNCTIONS:
parameters[operation][operator].setdefault('kwargs', {})
return parameters
def read(input):
"""Sets StructOpt parameters from a dictionary or filename"""
# Read and store the input
if isinstance(input, dict):
parameters = input
elif isinstance(input, str) and os.path.exists(input):
parameters = DictionaryObject(json.load(open(input)))
else:
raise IOError('Error in input or input file')
parameters = set_default(parameters)
return parameters
def parameters(self):
parameters = []
start_flag = False
for line in open(self.output_file):
if 'Current parameters:' in line:
start_flag = True
continue
if start_flag:
if 'INFO : {' in line:
line = line.split('INFO : ')[1]
parameters.append(line)
if line == '}\n':
start_flag = False
break
parameters = ''.join(parameters)
parameters = DictionaryObject(json.loads(parameters))
sys.modules['gparameters'] = parameters
return parameters
import logging
import sys
import os
import json
from structopt.tools.dictionaryobject import DictionaryObject
sys.modules['gparameters'] = DictionaryObject({})
from structopt.io.parameters import read as read_parameters
from structopt.io.parameters import write as write_parameters
from structopt.io.logger_utils import initialize_logger, initialize_logger_for_root
from structopt import common
def setup(parameter_file):
# Read in the parameters
parameters = read_parameters(parameter_file)
sys.modules['gparameters'].update(parameters)
# Setup all the loggers
logging_level = parameters.logging.get("logging_level", "info")
logging_level = getattr(logging, logging_level.upper())
rank = parameters.mpi.rank
path = parameters.logging.path
os.makedirs(path, exist_ok=True)
os.makedirs(os.path.join(path, 'modelfiles'), exist_ok=True)
if rank == 0:
print("Logging directory:", path)
logger = initialize_logger_for_root(rank=rank, filename=os.path.join(path, 'output.log'), name="output", level=logging_level)
from structopt.common.population import Population
from structopt.tools.dictionaryobject import DictionaryObject
import structopt
parameters = structopt.setup(
DictionaryObject({
"structure_type": "cluster",
"generators": {
"sphere": {
"number_of_individuals": 2,
"kwargs": {
"atomlist": [["Au", 55]],
"cell": [20, 20, 20]
}
}
},
"fingerprinters": {
"all_close_atom_positions": {
"probability": 1.0
}
},
}))
def test_all_close_atom_postions():
parameters.fingerprinters = {
"keep_best": True,
"all_close_atom_positions": {
"probability": 1.0,
"kwargs": {}
}
def set_default(parameters):
paramters = set_default_mpi_parameters(parameters)
parameters.setdefault('logging', {})
if "path" in parameters.logging:
raise ValueError(
"'path' should not be defined in the parameter file currently. If you think you want to define it, talk to the developers about why."
)
# If parallel and no seed, all nodes need the same seed and same path
path_extension = time.strftime("%Y%m%d%H%M%S")
if len(sys.argv) > 2:
path_extension += '_' + sys.argv[2]
if parameters.mpi.ncores > 1:
from mpi4py import MPI
seed = MPI.COMM_WORLD.bcast(int(time.time()), root=0)
path_extension = MPI.COMM_WORLD.bcast(path_extension, root=0)
path = MPI.COMM_WORLD.bcast(os.path.join(
os.getcwd(), "logs{}".format(path_extension)),
root=0)
else:
seed = None
path = os.path.join(os.getcwd(), "logs{}".format(path_extension))
parameters.logging.path = path
parameters.setdefault('seed', seed)
parameters.setdefault('post_processing', DictionaryObject({}))
if 'post_processing' in parameters:
parameters.post_processing.setdefault('XYZs', -1)
parameters.setdefault('fingerprinters', DictionaryObject({}))
if 'convergence' in parameters:
parameters.convergence.setdefault('max_generations', 10)
if 'fingerprinters' in parameters:
parameters.fingerprinters.setdefault('keep_best', False)
try:
parameters.fitnesses.FEMSIM.skip_bad_lammps = False
except:
pass
try:
# Set default LAMMPS normalization to E = E/natoms
parameters.fitnesses.LAMMPS.setdefault("normalize", {})
parameters.fitnesses.LAMMPS.normalize.setdefault('natoms', True)
except:
pass
try:
# Set default STEM normalization to E = E/nprotons
parameters.fitnesses.STEM.setdefault("normalize", {})
parameters.fitnesses.STEM.normalize.setdefault('nprotons', True)
parameters.fitnesses.STEM.normalize.setdefault('SSE', False)
except:
pass
# Make sure every operation is defined, and that every operation has a
# kwargs
for operation in MODULES:
parameters.setdefault(operation, None)
if parameters[operation] is not None:
for operator in parameters[operation]:
if operator not in EXCEPTION_FUNCTIONS:
parameters[operation][operator].setdefault('kwargs', {})
return parameters