def __init__(self, params, filename=None):
self.num_results = 1
self.params = params
self.filename = filename
# load uq setting
self.uqBuilder = UQBuilder()
if filename is not None:
self.uqBuilder.fromFile(filename)
self.buildUQSetting()
self.uqSetting = self.uqBuilder.andGetResult()
class Model(object):
def __init__(self, params, filename=None):
self.num_results = 1
self.params = params
self.filename = filename
# load uq setting
self.uqBuilder = UQBuilder()
if filename is not None:
self.uqBuilder.fromFile(filename)
self.buildUQSetting()
self.uqSetting = self.uqBuilder.andGetResult()
def buildUQSetting(self):
raise NotImplementedError
def evaluate(self, samples, distributed=False):
self.uqSetting.runSamples(samples, dist=distributed)
def __init__(self):
self.asgcUQManager = ASGCUQManager()
self.uqSettingBuilder = UQBuilder()
self.learnerBuilder = LearnerBuilder()
self.samplerBuilder = ASGCSamplerBuilder(self.asgcUQManager)
def buildSetting(self, params, simulation, N):
mcSampler = MCSampler.withLatinHypercubeSampleGenerator(params, N)
uqSetting = UQBuilder().withSimulation(simulation).andGetResult()
return mcSampler, uqSetting
class ASGCUQManagerBuilder(object):
def __init__(self):
self.asgcUQManager = ASGCUQManager()
self.uqSettingBuilder = UQBuilder()
self.learnerBuilder = LearnerBuilder()
self.samplerBuilder = ASGCSamplerBuilder(self.asgcUQManager)
def useUQSetting(self, uqSetting):
self.asgcUQManager.uqSetting = uqSetting
return self
def defineUQSetting(self):
return self.uqSettingBuilder
def defineSampler(self):
return self.samplerBuilder
def useInterpolation(self):
self.learnerBuilder.buildInterpolant()
return self
def withParameters(self, params):
"""
Set the parameter setting
@param params: ParameterSet
"""
self.asgcUQManager.setParameters(params)
return self
def withQoI(self, qoi):
"""
Define, which quantity of interest we study.
@param qoi: string quantity of interest
"""
self.asgcUQManager.setQoI(qoi)
return self
def withTypesOfKnowledge(self, knowledgeTypes):
"""
Define for which type of functions the hierarchical coefficients are
computed using the specified learner.
@param knowledgeTypes: list of KnowledgetTypes
"""
self.asgcUQManager.setKnowledgeTypes(knowledgeTypes)
return self
def withTimeStepsOfInterest(self, ts):
"""
Define the time steps in which we are interested in. The learner
just learns those, which are specified here. Moreover, it considers
just this time steps for refinement.
@param ts: list of floats, time steps
"""
# check for uniqueness of time steps
if len(ts) != len(set(ts)):
raise AttributeError('time steps of interest are not unique')
self.asgcUQManager.setTimeStepsOfInterest(ts)
return self
def withTestSet(self, testset):
"""
Set the test set
@param testset: UQSetting
"""
self.asgcUQManager.setTestSet(testset)
return self
def learnWithTest(self):
"""
Set if the learner should use test data points for learning
"""
if self.asgcUQManager.getTestSet() is None:
raise AttributeError('you need to specify a test set before you\
can use it in the learning process')
self.asgcUQManager.setLearnWithTest(True)
return self
def withKnowledge(self, filename):
if not os.path.exists(filename):
raise AttributeError("the file '%s' does not exist" % filename)
# read knowledge file
jsonObject = ASGCKnowledgeFormatter().deserializeFromFile(filename)
self.asgcUQManager.knowledge = ASGCKnowledge.fromJson(jsonObject)
self.asgcUQManager.iteration = self.asgcUQManager.knowledge.getIteration(
)
return self
# -------------------------------------------------------------------------
def __initUQSetting(self):
if self.asgcUQManager.uqSetting is None:
self.asgcUQManager.uqSetting = self.uqSettingBuilder.andGetResult()
def __collectLearner(self):
# check for parameter specification
if self.asgcUQManager.getParameters() is None:
raise AttributeError('parameter setting is missing')
# create the specification of the learner
if self.learnerBuilder is None:
raise AttributeError('no learner specified')
self.asgcUQManager.learner = self.learnerBuilder.andGetResult()
def __collectSampler(self):
self.asgcUQManager.sampler = self.samplerBuilder.andGetResult()
def andGetResult(self):
"""
Returns the simulation learner object that is
currently being constructed
"""
if self.asgcUQManager.getParameters() is None:
raise AttributeError('the parameters are not specified')
# initialize the different objects
self.__initUQSetting()
self.__collectLearner()
self.__collectSampler()
return self.asgcUQManager