def test_multiple_models(self):
"""
Test running running with two different pysd models
Returns
-------
"""
relative_path_to_file = '../models/Sales_Agent_Market_Building_Dynamics.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
market_model = PysdModel(mdl_file=mdl_file)
market_model.uncertainties = [RealParameter('Startup Subsidy',0, 3),
RealParameter('Startup Subsidy Length', 0, 10)]
market_model.outcomes = [TimeSeriesOutcome('Still Employed')]
relative_path_to_file = '../models/Sales_Agent_Motivation_Dynamics.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
motivation_model = PysdModel(mdl_file=mdl_file)
motivation_model.uncertainties = [RealParameter('Startup Subsidy', 0, 3),
RealParameter('Startup Subsidy Length', 0, 10)]
motivation_model.outcomes =[TimeSeriesOutcome('Still Employed')]
models = [market_model, motivation_model] # set the model on the ensemble
perform_experiments(models, 5)
def test_multiple_models(self):
"""
Test running running with two different pysd models
Returns
-------
"""
relative_path_to_file = '../models/Sales_Agent_Market_Building_Dynamics.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
market_model = PysdModel(mdl_file=mdl_file)
market_model.uncertainties = [RealParameter('Startup Subsidy',0, 3),
RealParameter('Startup Subsidy Length', 0, 10)]
market_model.outcomes = [TimeSeriesOutcome('Still Employed')]
relative_path_to_file = '../models/Sales_Agent_Motivation_Dynamics.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
motivation_model = PysdModel(mdl_file=mdl_file)
motivation_model.uncertainties = [RealParameter('Startup Subsidy', 0, 3),
RealParameter('Startup Subsidy Length', 0, 10)]
motivation_model.outcomes =[TimeSeriesOutcome('Still Employed')]
models = [market_model, motivation_model] # set the model on the ensemble
perform_experiments(models, 5)
def test_parallel_experiment(self):
"""
Test running an experiment in parallel
Returns
-------
"""
relative_path_to_file = '../models/Teacup.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
model = PysdModel(mdl_file=mdl_file)
model.uncertainties = [RealParameter('Room Temperature', 33, 120)]
model.outcomes = [TimeSeriesOutcome('Teacup Temperature')]
with MultiprocessingEvaluator(model, 2) as evaluator:
perform_experiments(model, 5, evaluator=evaluator)
def test_parallel_experiment(self):
"""
Test running an experiment in parallel
Returns
-------
"""
relative_path_to_file = '../models/Teacup.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
model = PysdModel(mdl_file=mdl_file)
model.uncertainties = [RealParameter('Room Temperature', 33, 120)]
model.outcomes = [TimeSeriesOutcome('Teacup Temperature')]
with MultiprocessingEvaluator(model, 2) as evaluator:
perform_experiments(model, 5, evaluator=evaluator)
def test_sequential_experiment(self):
"""
Test running an experiment in parallel
Returns
-------
"""
directory = os.path.dirname(__file__)
relative_path_to_file = '../models/Teacup.mdl'
mdl_file = os.path.join(directory, relative_path_to_file)
model = PysdModel(mdl_file=mdl_file)
model.uncertainties = [RealParameter('Room Temperature', 33, 120)]
model.outcomes = [TimeSeriesOutcome('Teacup Temperature')]
with SequentialEvaluator(model) as evaluator:
evaluator.perform_experiments(5)
def test_parallel_experiment(self):
"""
Test running an experiment in parallel
Returns
-------
"""
relative_path_to_file = '../models/Teacup.mdl'
directory = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
mdl_file = os.path.join(directory, relative_path_to_file)
model = PysdModel(mdl_file=mdl_file)
model.uncertainties = [RealParameter('Room Temperature', 33, 120)]
model.outcomes = [TimeSeriesOutcome('Teacup Temperature')]
ensemble = ModelEnsemble() # instantiate an ensemble
ensemble.model_structures = model # set the model on the ensemble
ensemble.parallel = True
ensemble.perform_experiments(5)
'''
'''
# Created on Jul 23, 2016
#
# .. codeauthor::jhkwakkel <j.h.kwakkel (at) tudelft (dot) nl>
from ema_workbench import (RealParameter, TimeSeriesOutcome, ema_logging,
perform_experiments)
from ema_workbench.connectors.pysd_connector import PysdModel
if __name__ == '__main__':
ema_logging.log_to_stderr(ema_logging.INFO)
mdl_file = './models/pysd/Teacup.mdl'
model = PysdModel(mdl_file=mdl_file)
model.uncertainties = [RealParameter('Room Temperature', 33, 120)]
model.outcomes = [TimeSeriesOutcome('Teacup Temperature')]
perform_experiments(model, 100)
'''
'''
from __future__ import (unicode_literals, print_function, absolute_import,
division)
# Created on Jul 23, 2016
#
# .. codeauthor::jhkwakkel <j.h.kwakkel (at) tudelft (dot) nl>
from ema_workbench import (RealParameter, TimeSeriesOutcome, ema_logging,
perform_experiments)
from ema_workbench.connectors.pysd_connector import PysdModel
if __name__ == '__main__':
ema_logging.log_to_stderr(ema_logging.DEBUG)
mdl_file = './models/pysd/Teacup.mdl'
model = PysdModel(mdl_file=mdl_file)
model.uncertainties = [RealParameter('Room Temperature', 33, 120)]
model.outcomes = [TimeSeriesOutcome('Teacup Temperature')]
perform_experiments(model, 100)