def load_model(project_dir, mode, hypers=False, build=True):
"""
Load config from project directory and return BEAT problem including model.
Parameters
----------
project_dir : string
path to beat model directory
mode : string
problem name to be loaded
hypers : boolean
flag to return hyper parameter estimation model instead of main model.
build : boolean
flag to build models
Returns
-------
problem : :class:`Problem`
"""
try:
config = bconfig.load_config(project_dir, mode)
except ArgumentError:
raise ConfigNeedsUpdatingError()
pc = config.problem_config
if hypers and len(pc.hyperparameters) == 0:
raise ValueError('No hyperparameters specified!'
' option --hypers not applicable')
if pc.mode in problem_catalog.keys():
problem = problem_catalog[pc.mode](config, hypers)
else:
logger.error('Modeling problem %s not supported' % pc.mode)
raise ValueError('Model not supported')
if build:
if hypers:
problem.built_hyper_model()
else:
problem.built_model()
return problem
def load_model(project_dir, mode, hypers=False):
"""
Load config from project directory and return BEAT problem including model.
Parameters
----------
project_dir : string
path to beat model directory
mode : string
problem name to be loaded
hypers : boolean
flag to return hyper parameter estimation model instead of main model.
Returns
-------
:class:`Problem`
"""
config = bconfig.load_config(project_dir, mode)
pc = config.problem_config
if hypers and len(pc.hyperparameters) == 0:
raise Exception('No hyperparameters specified!'
' option --hypers not applicable')
if pc.mode == 'geometry':
problem = GeometryOptimizer(config)
else:
logger.error('Modeling problem %s not supported' % pc.mode)
raise Exception('Model not supported')
if hypers:
problem.built_hyper_model()
else:
problem.built_model()
return problem